1980 Census of Population DDI_IDN_1980_PHC_v01_M_v7.6_A_IPUMS IPUMS

Integrated Public Use Microdata Series (IPUMS) International

IPUMS April 1, 2025 IPUMS, 50 Willey Hall, 225 - 19th Avenue South, Minneapolis, MN 55455 Organization for Economic Co-operation and Development, Development Co-operation Directorate JADE#:60525;MEHLB(2010)12 IPUMS Version 7.6 October 2025 : NEW FEATURES. --NO "new features" listed in Revision History NEW SAMPLES. --Six new census samples for Honduras (2013), Kenya (2019), Malawi (2018), Mongolia (2010, 2020), and Mozambique (2017) were added to the data series. All census samples extend pre-existing series for those countries. --91 quarterly labor force surveys from the Philippines (1997 - 2019) were added to IPUMS. SUPPLEMENTAL DATA. --No "supplemental data" listed in revision history NEW VARIABLES. --New spatially harmonized birthplace and previous-residence variables are available for samples in this data release. More information is available here (https://international.ipums.org/international/geo_mig.shtml). --Users should note that many older migration and birthplace variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. For birthplace variables refer to this table (https://international.ipums.org/international/resources/misc_docs/migCrosswalk_names.pdf). EDITED SAMPLES. --For the Zambia 2000 sample, an error in the household breaks was corrected, resulting in the creation of 1,988 new households (1% increase) that were previously combined with other households. The person records included in the sample did not change. Due to an inconsistency in the original file, no household-level information other than geographic location is available for these newly identified households, necessitating the addition of "unknown" values for this sample to the following variables: BEDROOMS, ELECTRIC, FLOOR, FUELCOOK, FUELHEAT, OWNERSHIP, PHONE, RADIO, REFRIG, ROOMS, SEWAGE, TRASH, WATSRC, TV, TOILET, GQ, ROOF, WATSUP, BIKE, MOTORCYCLE, KITCHEN, GQTYPE, AUTOS, and WALL. EDITED VARIABLES. --For the 1998 and 2008 Malawi samples, the family interrelationship pointer variables MOMLOC and POPLOC were modified to allow a "Spouse/partner" of the household head to be linked as a parent to an "Other relative", because the enumeration instructions specify that adopted and stepchildren were categorized as "Other relative". These samples are now consistent with the links made in the newly released 2018 Malawi sample, which had the same enumeration instructions for adopted and stepchildren. --In the samples for Côte d'Ivoire 1988 and 1998, Rwanda 1991 and 2002, Togo 1960 and 2010, and South Africa 2001, for the harmonized variable POLYGAM, persons in consensual unions were previously coded as "No, in monogamous union". Because there was no response option in these samples for polygamous consensual unions, it is more appropriate to treat these cases as not-in-universe, so they have been recoded to "NIU (not in universe)". --MARST has been edited for Honduras 1974 to reclassify the source variable responses "married, wife lives separately" and "consensual union, companion lives separately" as separations. The documentation suggests that "separately" actually indicates a relationship separation and not an absent spouse or companion. Other minor edits were implemented for MARST for Mozambique 1997 and 2007. --In the Mozambique 1997 sample, an error was corrected that recoded persons with a relationship of "Unknown" in the source data to "Other relative or non-relative" (6000) in the harmonized variable RELATE. These persons are now coded as "Not Stated/Unknown" (9999). --In the Malawi 1987, 1998, and 2008 samples, for variable WATSUP, a programming error was corrected such that any households who reported having piped water in either the wet or the dry season are classified as having access to piped water. This programming was also applied to the newly released 2018 sample. --The NATIVITY variable has been edited in the Chile 2017 sample to correct a programming error that mistakenly classified as foreign-born about 20 thousand person records that were actually native-born. --The MIGRATE5 variable has been edited in the Chile 2017 sample, given a programming error that classified most migrants as having changed their major geographic unit. The MIGRATE5 variable for the Chile 1982 and 1992 samples has been edited to use spatially harmonized geographic units to calculate migration status. --In the 1989, 1999, and 2009 Kenya samples, households who indicated that their lighting type or fuel was "Solar" were recoded from "No" to "Yes" in ELECTRIC, based on secondary sources documenting the spread of home solar energy systems in Kenya beginning in the mid-1980s. In the 1989 and 1999 Kenya samples, programming was removed that previously recoded households that reported using electricity as their main cooking fuel to "Yes" in the access to electricity variable ELECTRIC, making it more consistent across samples. Other minor edits were implemented for ELECTRIC in Botswana 2011, Ethiopia 1984 and 1994, Mongolia 1989, Mozambique 2007. --Some samples in DISCARE classified responses indicating "some" difficulty into "yes". These cases were revised to consistently include in "yes" only responses indicating "a lot of difficulty" or "cannot do at all". --Some codes were improperly labeled for municipalities in Honduras 1961 and 1974, which affect variables on place of residence, birthplace, and previous residence. 1980 Census of Population - IPUMS Subset PHC id1980a (IPUMS Harmonized Subset) IDN_1980_PHC_v01_M_v7.6_A_IPUMS Central Bureau of Statistics IPUMS (c) Copyright 1980, Central Bureau of Statistics and Minnesota Population Center Central Bureau of Statistics Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.6 Version 7.6. The datasets contain selected variables from the original microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Fertility and Mortality Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Nativity and Birthplace Variables -- PERSON Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Utilities Variables -- HOUSEHOLD Geography: F-N Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Ethnicity and Language Variables -- PERSON Migration: F-N Variables -- PERSON Household Economic Variables -- HOUSEHOLD Technical Person Variables -- PERSON Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Constructed Family Interrelationship Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Technical Household Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Work Variables -- PERSON Education Variables -- PERSON Technical Person Variables -- PERSON Geography: F-N Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Demographic Variables -- PERSON Other Person Variables -- PERSON Ethnicity and Language Variables -- PERSON Nativity and Birthplace Variables -- PERSON Migration: Global Variables -- PERSON Disability Variables -- PERSON Work: Occupation Variables -- PERSON Work: Industry Variables -- PERSON Work Variables -- PERSON Work: Industry Variables -- PERSON Demographic Variables -- PERSON Fertility and Mortality Variables -- PERSON Technical Person Variables -- PERSON Ethnicity and Language Variables -- PERSON October 31, 1980 Indonesia Regency Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: Not available - Households: An individual or group of people living who inhabit part or all of the physical or census building who make common provisions for food and other living essentials. - Group quarters: Institutional households consist of individuals in a residence that manages everyday needs, usually arranged by an organization such as a non-profit institution, school, the military, etc. Includes reformatories, prisons and similar living quarters. Also includes households that rent rooms or parts of buildings lodging ten or more people. All persons who reside in the geographical area of the Republic of Indonesia at the time of the census. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Indonesia 1980 MICRODATA SOURCE: Central Bureau of Statistics SAMPLE SIZE (person records): 7234577. SAMPLE DESIGN: Data are derived from the sample of census blocks that received the long form questionnaire. The sample of census blocks that received the long form was stratified by urban-rural status, with special census blocks containing large numbers of persons in institutions comprising a separate stratum. Face-to-face [f2f] Long form questionnaire SP80-S containing housing and individual questions. de jure, CENSUS DAY: October 31, 1980 Computed by census agency and should be used for most types of analysis. 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. Central Bureau of Statistics Steven Ruggles, Lara Cleveland, Rodrigo Lovaton, Sula Sarkar, Matthew Sobek, Derek Burk, Dan Ehrlich, Quinn Heimann, Jane Lee, and Nate Merrill. Integrated Public Use Microdata Series, International: Version 7.6 [dataset]. Minneapolis, MN: IPUMS, 2025. https://doi.org/10.18128/D020.V7.6 Researchers should also acknowledge the statistical agency that originally produced the data: Indonesia, Central Bureau of Statistics. 1980 Census of Population 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. User-provided description: DOI:10.18128/D020.V7.6 Extract for id1980a, 2025 IDN1980_PHC-H-H.dat Household records 1,505,893 ascii Minnesota Population Center Version 7.5, IPUMS sample IDN1980_PHC-P-H.dat Person records 7234577 ascii Minnesota Population Center Version 7.5, IPUMS sample 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. H Household P Person Technical Household Variables -- HOUSEHOLD Country 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). 032 Argentina 051 Armenia 040 Austria 050 Bangladesh 112 Belarus 204 Benin 068 Bolivia 072 Botswana 076 Brazil 854 Burkina Faso 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 208 Denmark 214 Dominican Republic 218 Ecuador 818 Egypt 222 El Salvador 231 Ethiopia 242 Fiji 246 Finland 250 France 276 Germany 288 Ghana 300 Greece 320 Guatemala 324 Guinea 332 Haiti 340 Honduras 348 Hungary 352 Iceland 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 384 Côte d'Ivoire 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 418 Laos 426 Lesotho 430 Liberia 454 Malawi 458 Malaysia 466 Mali 480 Mauritius 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 104 Myanmar 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 578 Norway 586 Pakistan 275 Palestine 591 Panama 598 Papua New Guinea 600 Paraguay 604 Peru 608 Philippines 616 Poland 620 Portugal 630 Puerto Rico 642 Romania 643 Russia 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 703 Slovak Republic 705 Slovenia 710 South Africa 728 South Sudan 724 Spain 729 Sudan 740 Suriname 752 Sweden 756 Switzerland 834 Tanzania 764 Thailand 768 Togo 780 Trinidad and Tobago 792 Turkey 800 Uganda 804 Ukraine 826 United Kingdom 840 United States 858 Uruguay 862 Venezuela 704 Vietnam 894 Zambia 716 Zimbabwe Technical Household Variables -- HOUSEHOLD Year YEAR gives the year in which the census or survey was taken. For samples that span years, the midpoint or first year of the interval is reported. 1703 1703 1729 1729 1787 1787 1801 1801 1819 1819 1845 1845 1848 1848 1850 1850 1851 1851 1852 1852 1860 1860 1861 1861 1865 1865 1868 1868 1870 1870 1871 1871 1875 1875 1880 1880 1881 1881 1885 1885 1890 1890 1891 1891 1900 1900 1901 1901 1910 1910 1911 1911 1960 1960 1961 1961 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 1978 1978 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 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 Technical Household Variables -- HOUSEHOLD IPUMS sample identifier 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). 032197001 Argentina 1970 032198001 Argentina 1980 032199101 Argentina 1991 032200101 Argentina 2001 032201001 Argentina 2010 051200101 Armenia 2001 051201101 Armenia 2011 040197101 Austria 1971 040198101 Austria 1981 040199101 Austria 1991 040200101 Austria 2001 040201101 Austria 2011 050199101 Bangladesh 1991 050200101 Bangladesh 2001 050201101 Bangladesh 2011 112199901 Belarus 1999 112200901 Belarus 2009 204197901 Benin 1979 204199201 Benin 1992 204200201 Benin 2002 204201301 Benin 2013 068197601 Bolivia 1976 068199201 Bolivia 1992 068200101 Bolivia 2001 068201201 Bolivia 2012 072198101 Botswana 1981 072199101 Botswana 1991 072200101 Botswana 2001 072201101 Botswana 2011 076196001 Brazil 1960 076197001 Brazil 1970 076198001 Brazil 1980 076199101 Brazil 1991 076200001 Brazil 2000 076201001 Brazil 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 116199801 Cambodia 1998 116200401 Cambodia 2004 116200801 Cambodia 2008 116201301 Cambodia 2013 116201901 Cambodia 2019 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124185201 Canada 1852 124187101 Canada 1871 124188101 Canada 1881 124189101 Canada 1891 124190101 Canada 1901 124191101 Canada 1911 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 124201101 Canada 2011 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 152201701 Chile 2017 156198201 China 1982 156199001 China 1990 156200001 China 2000 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 192201201 Cuba 2012 208178701 Denmark 1787 208180101 Denmark 1801 208184501 Denmark 1845 208188001 Denmark 1880 208188501 Denmark 1885 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 818184801 Egypt 1848 818186801 Egypt 1868 818198601 Egypt 1986 818199601 Egypt 1996 818200601 Egypt 2006 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 242201401 Fiji 2014 246201001 Finland 2010 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 276181901 Germany 1819 (Mecklenburg) 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 300201101 Greece 2011 320196401 Guatemala 1964 320197301 Guatemala 1973 320198101 Guatemala 1981 320199401 Guatemala 1994 320200201 Guatemala 2002 324198301 Guinea 1983 324199601 Guinea 1996 324201401 Guinea 2014 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 340196101 Honduras 1961 340197401 Honduras 1974 340198801 Honduras 1988 340200101 Honduras 2001 340201301 Honduras 2013 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 348201101 Hungary 2011 352170301 Iceland 1703 352172901 Iceland 1729 352180101 Iceland 1801 352190101 Iceland 1901 352191001 Iceland 1910 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 356200941 India 2009 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 364201101 Iran 2011 368199701 Iraq 1997 372190101 Ireland 1901 372191101 Ireland 1911 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 372201601 Ireland 2016 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 376200801 Israel 2008 380200101 Italy 2001 380201101 Italy 2011 380201121 Italy 2011 Q1 LFS 380201221 Italy 2012 Q1 LFS 380201321 Italy 2013 Q1 LFS 380201421 Italy 2014 Q1 LFS 380201521 Italy 2015 Q1 LFS 380201621 Italy 2016 Q1 LFS 380201721 Italy 2017 Q1 LFS 380201821 Italy 2018 Q1 LFS 380201921 Italy 2019 Q1 LFS 380202021 Italy 2020 Q1 LFS 384198801 Côte d'Ivoire 1988 384199801 Côte d'Ivoire 1998 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 404201901 Kenya 2019 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 418199501 Laos 1995 418200501 Laos 2005 418201501 Laos 2015 426199601 Lesotho 1996 426200601 Lesotho 2006 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 454201801 Malawi 2018 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 480199001 Mauritius 1990 480200001 Mauritius 2000 480201101 Mauritius 2011 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 484201501 Mexico 2015 484202001 Mexico 2020 484200521 Mexico 2005 Q1 LFS 484200522 Mexico 2005 Q2 LFS 484200523 Mexico 2005 Q3 LFS 484200524 Mexico 2005 Q4 LFS 484200621 Mexico 2006 Q1 LFS 484200622 Mexico 2006 Q2 LFS 484200623 Mexico 2006 Q3 LFS 484200624 Mexico 2006 Q4 LFS 484200721 Mexico 2007 Q1 LFS 484200722 Mexico 2007 Q2 LFS 484200723 Mexico 2007 Q3 LFS 484200724 Mexico 2007 Q4 LFS 484200821 Mexico 2008 Q1 LFS 484200822 Mexico 2008 Q2 LFS 484200823 Mexico 2008 Q3 LFS 484200824 Mexico 2008 Q4 LFS 484200921 Mexico 2009 Q1 LFS 484200922 Mexico 2009 Q2 LFS 484200923 Mexico 2009 Q3 LFS 484200924 Mexico 2009 Q4 LFS 484201021 Mexico 2010 Q1 LFS 484201022 Mexico 2010 Q2 LFS 484201023 Mexico 2010 Q3 LFS 484201024 Mexico 2010 Q4 LFS 484201121 Mexico 2011 Q1 LFS 484201122 Mexico 2011 Q2 LFS 484201123 Mexico 2011 Q3 LFS 484201124 Mexico 2011 Q4 LFS 484201221 Mexico 2012 Q1 LFS 484201222 Mexico 2012 Q2 LFS 484201223 Mexico 2012 Q3 LFS 484201224 Mexico 2012 Q4 LFS 484201321 Mexico 2013 Q1 LFS 484201322 Mexico 2013 Q2 LFS 484201323 Mexico 2013 Q3 LFS 484201324 Mexico 2013 Q4 LFS 484201421 Mexico 2014 Q1 LFS 484201422 Mexico 2014 Q2 LFS 484201423 Mexico 2014 Q3 LFS 484201424 Mexico 2014 Q4 LFS 484201521 Mexico 2015 Q1 LFS 484201522 Mexico 2015 Q2 LFS 484201523 Mexico 2015 Q3 LFS 484201524 Mexico 2015 Q4 LFS 484201621 Mexico 2016 Q1 LFS 484201622 Mexico 2016 Q2 LFS 484201623 Mexico 2016 Q3 LFS 484201624 Mexico 2016 Q4 LFS 484201721 Mexico 2017 Q1 LFS 484201722 Mexico 2017 Q2 LFS 484201723 Mexico 2017 Q3 LFS 484201724 Mexico 2017 Q4 LFS 484201821 Mexico 2018 Q1 LFS 484201822 Mexico 2018 Q2 LFS 484201823 Mexico 2018 Q3 LFS 484201824 Mexico 2018 Q4 LFS 484201921 Mexico 2019 Q1 LFS 484201922 Mexico 2019 Q2 LFS 484201923 Mexico 2019 Q3 LFS 484201924 Mexico 2019 Q4 LFS 484202021 Mexico 2020 Q1 LFS 484202023 Mexico 2020 Q3 LFS 496198901 Mongolia 1989 496200001 Mongolia 2000 496201001 Mongolia 2010 496202001 Mongolia 2020 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 508201701 Mozambique 2017 104201401 Myanmar 2014 524200101 Nepal 2001 524201101 Nepal 2011 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 528201101 Netherlands 2011 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 578180101 Norway 1801 578186501 Norway 1865 578187501 Norway 1875 578190001 Norway 1900 578191001 Norway 1910 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 275199701 Palestine 1997 275200701 Palestine 2007 275201701 Palestine 2017 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 598198001 Papua New Guinea 1980 598199001 Papua New Guinea 1990 598200001 Papua New Guinea 2000 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 604201701 Peru 2017 608199721 Philippines 1997 Q1 LFS 608199722 Philippines 1997 Q2 LFS 608199723 Philippines 1997 Q3 LFS 608199724 Philippines 1997 Q4 LFS 608199821 Philippines 1998 Q1 LFS 608199822 Philippines 1998 Q2 LFS 608199823 Philippines 1998 Q3 LFS 608199824 Philippines 1998 Q4 LFS 608199921 Philippines 1999 Q1 LFS 608199922 Philippines 1999 Q2 LFS 608199923 Philippines 1999 Q3 LFS 608199924 Philippines 1999 Q4 LFS 608200021 Philippines 2000 Q1 LFS 608200022 Philippines 2000 Q2 LFS 608200023 Philippines 2000 Q3 LFS 608200024 Philippines 2000 Q4 LFS 608200121 Philippines 2001 Q1 LFS 608200122 Philippines 2001 Q2 LFS 608200123 Philippines 2001 Q3 LFS 608200124 Philippines 2001 Q4 LFS 608200221 Philippines 2002 Q1 LFS 608200222 Philippines 2002 Q2 LFS 608200223 Philippines 2002 Q3 LFS 608200224 Philippines 2002 Q4 LFS 608200321 Philippines 2003 Q1 LFS 608200322 Philippines 2003 Q2 LFS 608200323 Philippines 2003 Q3 LFS 608200324 Philippines 2003 Q4 LFS 608200421 Philippines 2004 Q1 LFS 608200422 Philippines 2004 Q2 LFS 608200423 Philippines 2004 Q3 LFS 608200424 Philippines 2004 Q4 LFS 608200521 Philippines 2005 Q1 LFS 608200522 Philippines 2005 Q2 LFS 608200523 Philippines 2005 Q3 LFS 608200524 Philippines 2005 Q4 LFS 608200621 Philippines 2006 Q1 LFS 608200622 Philippines 2006 Q2 LFS 608200623 Philippines 2006 Q3 LFS 608200624 Philippines 2006 Q4 LFS 608200721 Philippines 2007 Q1 LFS 608200722 Philippines 2007 Q2 LFS 608200723 Philippines 2007 Q3 LFS 608200724 Philippines 2007 Q4 LFS 608200821 Philippines 2008 Q1 LFS 608200822 Philippines 2008 Q2 LFS 608200823 Philippines 2008 Q3 LFS 608200824 Philippines 2008 Q4 LFS 608200921 Philippines 2009 Q1 LFS 608200922 Philippines 2009 Q2 LFS 608200923 Philippines 2009 Q3 LFS 608200924 Philippines 2009 Q4 LFS 608201021 Philippines 2010 Q1 LFS 608201022 Philippines 2010 Q2 LFS 608201023 Philippines 2010 Q3 LFS 608201024 Philippines 2010 Q4 LFS 608201121 Philippines 2011 Q1 LFS 608201122 Philippines 2011 Q2 LFS 608201123 Philippines 2011 Q3 LFS 608201124 Philippines 2011 Q4 LFS 608201221 Philippines 2012 Q1 LFS 608201222 Philippines 2012 Q2 LFS 608201223 Philippines 2012 Q3 LFS 608201224 Philippines 2012 Q4 LFS 608201321 Philippines 2013 Q1 LFS 608201322 Philippines 2013 Q2 LFS 608201323 Philippines 2013 Q3 LFS 608201324 Philippines 2013 Q4 LFS 608201421 Philippines 2014 Q1 LFS 608201422 Philippines 2014 Q2 LFS 608201423 Philippines 2014 Q3 LFS 608201424 Philippines 2014 Q4 LFS 608201521 Philippines 2015 Q1 LFS 608201522 Philippines 2015 Q2 LFS 608201523 Philippines 2015 Q3 LFS 608201524 Philippines 2015 Q4 LFS 608201621 Philippines 2016 Q1 LFS 608201622 Philippines 2016 Q2 LFS 608201623 Philippines 2016 Q3 LFS 608201624 Philippines 2016 Q4 LFS 608201721 Philippines 2017 Q1 LFS 608201722 Philippines 2017 Q2 LFS 608201723 Philippines 2017 Q3 LFS 608201724 Philippines 2017 Q4 LFS 608201821 Philippines 2018 Q1 LFS 608201822 Philippines 2018 Q2 LFS 608201823 Philippines 2018 Q3 LFS 608201824 Philippines 2018 Q4 LFS 608201921 Philippines 2019 Q1 LFS 608201922 Philippines 2019 Q2 LFS 608201923 Philippines 2019 Q3 LFS 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 608201001 Philippines 2010 616197801 Poland 1978 616198801 Poland 1988 616200201 Poland 2002 616201101 Poland 2011 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 630201501 Puerto Rico 2015 630202001 Puerto Rico 2020 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 642201101 Romania 2011 643200201 Russia 2002 643201001 Russia 2010 646199101 Rwanda 1991 646200201 Rwanda 2002 646201201 Rwanda 2012 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 686201301 Senegal 2013 694200401 Sierra Leone 2004 694201501 Sierra Leone 2015 703199101 Slovak Republic 1991 703200101 Slovak Republic 2001 703201101 Slovak Republic 2011 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 710201601 South Africa 2016 728200801 South Sudan 2008 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 724200521 Spain 2005 Q1 LFS 724200522 Spain 2005 Q2 LFS 724200523 Spain 2005 Q3 LFS 724200524 Spain 2005 Q4 LFS 724200621 Spain 2006 Q1 LFS 724200622 Spain 2006 Q2 LFS 724200623 Spain 2006 Q3 LFS 724200624 Spain 2006 Q4 LFS 724200721 Spain 2007 Q1 LFS 724200722 Spain 2007 Q2 LFS 724200723 Spain 2007 Q3 LFS 724200724 Spain 2007 Q4 LFS 724200821 Spain 2008 Q1 LFS 724200822 Spain 2008 Q2 LFS 724200823 Spain 2008 Q3 LFS 724200824 Spain 2008 Q4 LFS 724200921 Spain 2009 Q1 LFS 724200922 Spain 2009 Q2 LFS 724200923 Spain 2009 Q3 LFS 724200924 Spain 2009 Q4 LFS 724201021 Spain 2010 Q1 LFS 724201022 Spain 2010 Q2 LFS 724201023 Spain 2010 Q3 LFS 724201024 Spain 2010 Q4 LFS 724201121 Spain 2011 Q1 LFS 724201122 Spain 2011 Q2 LFS 724201123 Spain 2011 Q3 LFS 724201124 Spain 2011 Q4 LFS 724201221 Spain 2012 Q1 LFS 724201222 Spain 2012 Q2 LFS 724201223 Spain 2012 Q3 LFS 724201224 Spain 2012 Q4 LFS 724201321 Spain 2013 Q1 LFS 724201322 Spain 2013 Q2 LFS 724201323 Spain 2013 Q3 LFS 724201324 Spain 2013 Q4 LFS 724201421 Spain 2014 Q1 LFS 724201422 Spain 2014 Q2 LFS 724201423 Spain 2014 Q3 LFS 724201424 Spain 2014 Q4 LFS 724201521 Spain 2015 Q1 LFS 724201522 Spain 2015 Q2 LFS 724201523 Spain 2015 Q3 LFS 724201524 Spain 2015 Q4 LFS 724201621 Spain 2016 Q1 LFS 724201622 Spain 2016 Q2 LFS 724201623 Spain 2016 Q3 LFS 724201624 Spain 2016 Q4 LFS 724201721 Spain 2017 Q1 LFS 724201722 Spain 2017 Q2 LFS 724201723 Spain 2017 Q3 LFS 724201724 Spain 2017 Q4 LFS 724201821 Spain 2018 Q1 LFS 724201822 Spain 2018 Q2 LFS 724201823 Spain 2018 Q3 LFS 724201824 Spain 2018 Q4 LFS 724201921 Spain 2019 Q1 LFS 724201922 Spain 2019 Q2 LFS 724201923 Spain 2019 Q3 LFS 724201924 Spain 2019 Q4 LFS 724202021 Spain 2020 Q1 LFS 724202022 Spain 2020 Q2 LFS 724202023 Spain 2020 Q3 LFS 724202024 Spain 2020 Q4 LFS 729200801 Sudan 2008 740200401 Suriname 2004 740201201 Suriname 2012 752188001 Sweden 1880 752189001 Sweden 1890 752190001 Sweden 1900 752191001 Sweden 1910 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 756201101 Switzerland 2011 834198801 Tanzania 1988 834200201 Tanzania 2002 834201201 Tanzania 2012 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 768196001 Togo 1960 768197001 Togo 1970 768201001 Togo 2010 780197001 Trinidad and Tobago 1970 780198001 Trinidad and Tobago 1980 780199001 Trinidad and Tobago 1990 780200001 Trinidad and Tobago 2000 780201101 Trinidad and Tobago 2011 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 800201401 Uganda 2014 804200101 Ukraine 2001 826185101 United Kingdom 1851 (England and Wales) 826185102 United Kingdom 1851 (Scotland) 826185103 United Kingdom 1851 (2% sample) 826186101 United Kingdom 1861 (England and Wales) 826186102 United Kingdom 1861 (Scotland) 826187101 United Kingdom 1871 (Scotland) 826188101 United Kingdom 1881 (England and Wales) 826188102 United Kingdom 1881 (Scotland) 826189101 United Kingdom 1891 (England and Wales) 826189102 United Kingdom 1891 (Scotland) 826190101 United Kingdom 1901 (England and Wales) 826190102 United Kingdom 1901 (Scotland) 826191101 United Kingdom 1911 (England and Wales) 826196101 United Kingdom 1961 826197101 United Kingdom 1971 826199101 United Kingdom 1991 826200101 United Kingdom 2001 840185001 United States 1850 (100%) 840185002 United States 1850 (1%) 840186001 United States 1860 (1%) 840187001 United States 1870 (1%) 840188001 United States 1880 (100%) 840188002 United States 1880 (10%) 840190001 United States 1900 (5%) 840191001 United States 1910 (1%) 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 840201501 United States 2015 840202001 United States 2020 858196301 Uruguay 1963 858196302 Uruguay 1963 (full count) 858197501 Uruguay 1975 858197502 Uruguay 1975 (full count) 858198501 Uruguay 1985 858198502 Uruguay 1985 (full count) 858199601 Uruguay 1996 858199602 Uruguay 1996 (full count) 858200621 Uruguay 2006 858201101 Uruguay 2011 858201102 Uruguay 2011 (full count) 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 704201901 Vietnam 2019 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 716201201 Zimbabwe 2012 Technical Household Variables -- HOUSEHOLD 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, 2002Colombia 1993, 2005Costa Rica 1984, 2000Cuba 2002Dominican Republic 1981, 2002, 2010Ecuador 1990, 2001Germany 1971Hungary 1980, 1990, 2001Jamaica 1982, 1991, 2001Malaysia 1970, 1991, 2000Mexico 1995, 1990, 2000, 2005Nigeria 2006Panama 2000Peru 1993, 2007Portugal 1981, 1991, 2001Spain 1991Uruguay 2011Venezuela 1990, 2001Vietnam 1989In 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. The U.S. 1900 sample and 1880 10% sample have multi-household dwellings that can be identified using the last 3 digits of SERIAL. 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. Technical Household Variables -- 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 4-digit numeric variable. Technical Household Variables -- HOUSEHOLD 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. Technical Household Variables -- HOUSEHOLD Subsample number 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. 00 1st 1% subsample 01 2nd 1% subsample 02 3rd 1% subsample 03 4th 1% subsample 04 5th 1% subsample 05 6th 1% subsample 06 7th 1% subsample 07 8th 1% subsample 08 9th 1% subsample 09 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 Technical Household Variables -- HOUSEHOLD Strata identifier This variable is the strata identifier for the sample. The STRATA variable provides information about the sample design that can be used to improve estimation. STRATA is a 12-digit numeric variable. Technical Household Variables -- HOUSEHOLD Group quarters (collective dwelling) status 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. 00 Vacant 10 Households 20 Group quarters (collective), n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified Group Quarters Variables -- HOUSEHOLD Number of unrelated persons UNREL indicates the number of persons in the household who are unrelated to the head as defined in the variable RELATE. 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ Group Quarters Variables -- HOUSEHOLD Urban-rural status URBAN indicates whether the household was located in a place designated as urban or as rural. 1 Rural 2 Urban 9 Unknown Geography: Global Variables -- HOUSEHOLD Continent and region of country REGIONW identifies the continent and region of each 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 Geography: Global Variables -- HOUSEHOLD 1st subnational geographic level, world [consistent boundaries over time] 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. GEOLEV1 is a 6-digit numeric variable. GEOLEV1 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO1_BR. Geography: Global Variables -- HOUSEHOLD 2nd subnational geographic level, world [consistent boundaries over time] GEOLEV2 indicates the second 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. Second administrative units in GEOLEV2 have been spatio-temporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV2 is a 9-digit numeric variable. GEOLEV2 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO2_BR. Geography: Global Variables -- HOUSEHOLD Population density of GEOLEV1 unit, in persons per square kilometer POPDENSGEO1 indicates the population density in persons per square kilometer of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to 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. POPDENSGEO1 is an 8-digit numeric variable listing the population density in persons per square kilometer. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Population density of GEOLEV2 unit, in persons per square kilometer POPDENSGEO2 indicates the population density in persons per square kilometer of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to 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. POPDENSGEO2 is a 12-digit numeric variable listing the population density in persons per square kilometer. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Area of GEOLEV1 unit in square kilometers AREAMOLLWGEO1 indicates the area in square kilometers of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to 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. AREAMOLLWGEO1 is a 10-digit numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Area of GEOLEV2 unit in square kilometers AREAMOLLWGEO2 indicates the area in square kilometers of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to 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. AREAMOLLWGEO2 is a 10-digit numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Indonesia, Province 1971 - 2010 [Level 1; consistent boundaries, GIS] GEO1_ID identifies the household's province within Indonesia in all sample years. Provinces are the first level administrative units of the country. GEO1_ID 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_ID can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Indonesia 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. 360011 Nanggroe Aceh Darussalam 360012 Sumatera Utara 360013 Sumatera Barat 360014 Kepulauan Riau, Riau 360015 Jambi 360016 Bangka Belitung, Sumatera Selatan 360017 Bengkulu 360018 Lampung 360031 DKI Jakarta 360032 Banten, Jawa Barat 360033 Jawa Tengah 360034 DKI Yogyakarta 360035 Jawa Timur 360051 Bali 360052 Nusa Tenggara Barat 360053 Nusa Tenggara Timur 360061 Kalimantan Barat 360062 Kalimantan Tengah 360063 Kalimantan Selatan 360064 Kalimantan Timur 360071 Gorontalo, Sulawesi Utara 360072 Sulawesi Tengah 360073 Sulawesi Barat, Sulawesi Selatan 360074 Sulawesi Tenggara 360081 Maluku, Maluku Utara 360094 Papua, Papua Barat 360626 East Timor Geography: F-N Variables -- HOUSEHOLD Indonesia, Province 1980 [Level 1, GIS] GEO1_ID1980 identifies the household's provinces within Indonesia in 1980. Provinces are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_ ID1980 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Indonesia 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. 011 Special region of Aceh 012 Sumatra Utara 013 Sumatra Barat 014 Riau 015 Jambi 016 Sumatra Selatan 017 Bengkulu 018 Lampung 031 Special capital region of Jakarta 032 Jawa Barat 033 Jawa Tengah 034 Special region of Yogyakarta 035 Jawa Timur 051 Bali 052 Nusa Tenggara Barat 053 Nusa Tenggara Timur 054 East Timor 061 Kalimantan Barat 062 Kalimantan Tengah 063 Kalimantan Salatan 064 Kalimantan Timur 071 Sulawesi Utara 072 Sulawesi Tengah 073 Sulawesi Selatan 074 Sulawesi Tenggara 081 Maluku 082 Irian Jaya Geography: F-N Variables -- HOUSEHOLD Indonesia, Regency 1971 - 2010 [Level 2; consistent boundaries, GIS] GEO2_ID indicates the household's regency (kapupaten) within Indonesia in all sample years. It is also known as municipality (kotamadya). The difference between regency and a municipality is dependent on the population density of the geographical unit. A primarily rural area would be known as regency and a primarily urban area would be known as a municipality. Regencies/municipalities are the second level administrative units of the country, after provinces. GEOG2_ID is spatially harmonized accounting 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 GEOG2_ID can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Indonesia 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. 360011001 Simeulue, Aceh Barat, Aceh Jaya, Nagan Raya 360011002 Aceh Singkil, Aceh Selatan, Aceh Barat Daya, Subulussalam 360011003 Aceh Tenggara, Aceh Tengah, Gayo Lues, Bener Meriah 360011004 Aceh Tamiang, Aceh Timur, Kota Langsa 360011005 Aceh Besar 360011006 Pidie, Pidie Jaya 360011007 Bireuen, Kota Lhoksumawe, Aceh Utara 360011008 Kota Banda Aceh 360011009 Kota Sabang 360012001 Nias, Nias Selatan, Nias Utara, Nias Barat, Kota Gunungsitoli 360012002 Mandailing Natal, Tapanuli Selatan, Padang Lawas Utara, Padang Lawas, Kota Padang Sidempuan 360012003 Tapanuli Tengah 360012004 Tapanuli Utara, Toba Samosir, Humbang Hasundutan, Samosir 360012005 Labuhan Batu, Labuhan Batu Selatan, Labuhan Batu Utara 360012006 Asahan, Batu Bara 360012007 Simalungun 360012008 Dairi, Papak Bharat 360012009 Karo 360012010 Serdang Bedagai, Deli Serdang 360012011 Langkat 360012012 Kota Sibolga 360012013 Tanjung Balai 360012014 Kota Pematang Siantar 360012015 Kota Tebing Tinggi 360012016 Medan 360012017 Kota Binjai 360013001 Kepulauan Mentawai, Padang Pariaman, Kota Pariaman 360013002 Pesisir Selatan 360013003 Solok, Solok Selatan, Kota Solok 360013004 Sawahlunto/Sijunjung, Dharmasraya, Kota Sawah Lunto 360013005 Tanah Datar 360013006 Agam 360013007 Lima Puluh Koto, Kota Payakumbuh 360013008 Pasaman, Pasaman Barat 360013009 Kota Padang 360013010 Kota Padang Panjang 360013011 Kota Bukittinggi 360014001 Kuantan Singingi, Indragiri Hulu 360014002 Indragiri Hilir 360014003 Pelalawan, Kampar, Rokan Hulu 360014004 Siak, Bengkalis, Rokan Hilir, Kepulauan Meranti, Dumai 360014005 Pekan Baru 360014006 Karimun, Kepulauan Riau, Natuna, Lingga, Kepulauan Anambas, Batam, Tanjung Pinang 360015001 Kerinci, Kota Sungai Penuh 360015002 Merangin, Sarolangun 360015003 Batanghari, Muaro Jambi 360015004 Tanjung Jabung Timur, Tanjung Jabung Barat 360015005 Tebo, Bungo 360015006 Jambi 360016001 Oku, Oku Selatan, Oku Timur 360016002 Oki, Ogan Ilir 360016003 Muara Enim, Prabumulih 360016004 Lahat, Empat Lawang, Pagar Alam 360016005 Musi Rawas, Lubuk Lingga 360016006 Musi Banyu Asin, Banyu Asin 360016007 Palembang 360016008 Bangka, Bangka Barat, Bangka Tengah, Bangka Selatan 360016009 Belitung, Belitung Timur 360016010 Pangkal Pinang 360017001 Bengkulu Selatan, Kaur, Seluma 360017002 Rejang Lebong, Lebong, Kepahing 360017003 Bengkulu Utara, Mukomuko, Bengkulu Tengah 360017004 Bengkulu 360018001 Lampung Barat, Lampung Utara, Way Kanan, Tulang Bawang, Mesuji, Tulangbawang Barat 360018002 Tanggamus, Lampung Selatan, Pesawaran, Pringsewu 360018003 Lampung Timur, Lampung Tengah, Metro 360018004 Bandar Lampung 360031001 Kepulauan Seribu, Jakarta Utara 360031002 Jakarta Selatan 360031003 Jakarta Timur 360031004 Jakarta Pusat 360031005 Jakarta Barat 360032001 Bogor, Depok 360032002 Sukabumi (Regency) 360032003 Cianjur 360032004 Bandung (Regency), Bandung Barat, Cimahi 360032005 Garut 360032006 Tasikmalaya (Regency), Tasikmalaya 360032007 Ciamis, Banjar 360032008 Kuningan 360032009 Cirebon (Regency) 360032010 Majalengka 360032011 Sumedang 360032012 Indramayu 360032013 Subang 360032014 Purwakarta 360032015 Karawang 360032016 Bekasi (Regency), Bekasi 360032017 Bogor 360032018 Sukabumi City 360032019 Bandung 360032020 Cirebon City 360032021 Pandeglang 360032022 Lebak 360032023 Tangerang (Regency), Tangerang, Kota Tangerang Selatan 360032024 Serang (Regency), Cilegon, Serang 360033001 Cilacap 360033002 Banyumas 360033003 Purbalingga 360033004 Banjarnegara 360033005 Kebumen 360033006 Purworejo 360033007 Wonosobo 360033008 Magelang (Regency) 360033009 Boyolali 360033010 Klaten 360033011 Sukoharjo 360033012 Wonogiri 360033013 Karanganyar 360033014 Sragen 360033015 Grobogan 360033016 Blora 360033017 Rembang 360033018 Pati 360033019 Kudus 360033020 Jepara 360033021 Demak 360033022 Semarang (Regency) 360033023 Temanggung 360033024 Kendal 360033025 Batang 360033026 Pekalongan (Regency) 360033027 Pemalang 360033028 Tegal (Regency) 360033029 Brebes 360033030 Magelang City 360033031 Surakarta 360033032 Salatiga 360033033 Semarang City 360033034 Pekalongan City 360033035 Tegal City 360034001 Kulon Progo 360034002 Bantul 360034003 Gunung Kidul 360034004 Sleman 360034005 Yogyakarta 360035001 Pacitan 360035002 Ponorogo 360035003 Trenggalek 360035004 Tulungagung 360035005 Kab. Blitar 360035006 Kab. Kediri 360035007 Kab. Malang, Batu 360035008 Lumajang 360035009 Jember 360035010 Banyuwangi 360035011 Bondowoso 360035012 Situbondo 360035013 Kab. Probolinggo 360035014 Kab. Pasuruan 360035015 Sidoarjo 360035016 Kab. Mojokerto 360035017 Jombang 360035018 Nganjuk 360035019 Kab. Madiun 360035020 Magetan 360035021 Ngawi 360035022 Bojonegoro 360035023 Tuban 360035024 Lamongan 360035025 Gresik 360035026 Bangkalan 360035027 Sampang 360035028 Pamekasan 360035029 Sumenep 360035030 Kota Kediri 360035031 Kota Blitar 360035032 Kota Malang 360035033 Kota Probolinggo 360035034 Kota Pasuruan 360035035 Kota Mojokerto 360035036 Kota Madiun 360035037 Surabaya 360051001 Jembrana 360051002 Tabanan 360051003 Badung, Denpasar 360051004 Gianyar 360051005 Klungkung 360051006 Bangli 360051007 Karangasem 360051008 Buleleng 360052001 Lombok Barat, Lombok Utara, Mataram 360052002 Lombok Tengah 360052003 Lombok Timur 360052004 Sumbawa, Sumbawa Barat 360052005 Dompu 360052006 Bima (Regency), Bima 360053001 Sumba Tengah, Sumba Barat Daya, Sumba Barat 360053002 Sumba Timur 360053003 Rote Ndao, Sabu Raijua, Kupang (Regency), Kupang 360053004 Timor Tengah Selatan 360053005 Timor Tengah Utara 360053006 Belu 360053007 Alor 360053008 Lembata, Flores Timur 360053009 Sikka 360053010 Ende 360053011 Ngada, Nagekeo 360053012 Manggarai, Manggarai Barat, Manggarai Timur 360061001 Sambas, Bengkayang, Singkawang 360061002 Landak, Pontianak, Kubu Raya, Kodya Pontianak 360061003 Sanggau, Sekadau 360061004 Ketapang, Kayong Utara 360061005 Sintang, Melawai 360061006 Kapuas Hulu 360062001 Kotawaringin Barat, Sukamara, Lamandau 360062002 Kotawaringin Timur, Seruyan, Katingan 360062003 Kapuas, Pulang Pisau, Gunung Mas 360062004 Barito Selatan, Barito Timur 360062005 Barito Utara, Murung Raya 360062006 Palangka Raya 360063001 Tanah Laut 360063002 Tanah Bumbu, Kotabaru 360063003 Banjar, Banjarbaru 360063004 Barito Kuala 360063005 Tapin 360063006 Hulu Sungai Selatan 360063007 Hulu Sungai Tengah 360063008 Hulu Sungai Utara, Balangan 360063009 Tabalong 360063010 Banjarmasin 360064001 Pasir, Penajam Paser Utara 360064002 Kutai Barat, Kutai Kartanegara, Kutai Timur, Balikpapan, Bontang 360064003 Berau 360064004 Malinau, Tarakan, Bulongan, Nunukan, Tana Tidung 360064005 Samarinda 360071001 Bolaang Mongondow, Bolaang Mongondow Utara, Bolaang Mongondow Selatan, Bolaang Mongondow Timur, Kotamobagu 360071002 Minahasa, Minahasa Selatan, Minahasa Tenggara, Tomohon, Bitung, Minahasa Utara 360071003 Kepulauan Sangihe, Kepualuan Talaud, Siau Tagulandang Biaro 360071004 Manado 360071005 Boalemo, Gorontalo, Pohuwato, Bone Bolango, Gorontalo Utara 360071006 Kota Gorontalo 360072001 Banggai Kepulauan, Banggai 360072002 Morowali, Poso, Tojo Una-Una 360072003 Donggala, Parigi Moutong, Sigi, Palu 360072004 Toli-Toli, Buol 360073001 Selayar 360073002 Bulukumba 360073003 Bantaeng 360073004 Jeneponto 360073005 Takalar 360073006 Gowa 360073007 Sinjai 360073008 Maros 360073009 Pangkajene Kepulauan 360073010 Barru 360073011 Bone 360073012 Soppeng 360073013 Wajo 360073014 Sidenreng Rappang 360073015 Pinrang 360073016 Enrekang 360073017 Luwu, Luwu Utara, Luwu Timur, Palopo 360073018 Tana Toraja, Toraja Utara 360073019 Ujung Pandang 360073020 Pare-Pare 360073021 Majene 360073022 Polewali Mandar, Mamasa 360073023 Mamuju, Mamuju Utara 360074001 Buton, Bombana, Wakatobi, Bau Bau 360074002 Muna, Buton Utara 360074003 Konawe, Konawe Selatan, Konawe Utara, Kendari 360074004 Kolaka, Kolaka Utara 360081001 Maluku Tengah, Buru, Seram Bagian Barat, Seram Bagian Timur, Buru Selatan 360081002 Ambon 360081003 Halmahera Barat, Halmahera Tengah, Kepulauan Sula, Halmahera Selatan, Halmahera Utara, Halmahera Timur, Pulau Morotai, Ternate, Tidore Kepulauan 360081004 Maluku Tenggara Barat, Maluku Tenggara, Kepulauan Aru, Tual, Maluku Barat Daya 360094001 Fakfak, Kaimana, T Wondama, T Bintuni, Manokwari, Sorong S, Raja Ampat, Tambrauw, Maybrat, Merauke, Jayawijaya, Jayapura, Nabire, Yapen Waropen, Biak Numfor, Paniai, Puncak Jaya, Mimika, Boven Digoel, Mappi, Yahukimo, Pegunungan B, Tolikara, Sarmi, Keerom, Waropen, Supiori, Jayapura, Sorong C, Sorong R, Asmat Fakfak, Kaimana, T Wondama, T Bintuni, Manokwari, Sorong S, Raja Ampat, Tambrauw, Maybrat, Merauke, Jayawijaya, Jayapura, Nabire, Yapen Waropen, Biak Numfor, Paniai, Puncak Jaya, Mimika, Boven Digoel, Mappi, Yahukimo, Pegunungan B, Tolikara, Sarmi, Keerom, Waropen, Supiori, Jayapura, Sorong C, Sorong R, Asmat 360626000 East Timor Geography: F-N Variables -- HOUSEHOLD Indonesia, Regency 1980 [Level 2, GIS] GEO2_ ID1980 identifies the household's regency (kapupaten) within Indonesia in 1980. It is also known as municipality (kotamadya). The difference between regency and a municipality is dependent on the population density of the geographical unit. A primarily rural area would be known as regency and a primarily urban area would be known as a municipality. Regencies/municipalities are the second level administrative units of the country, after provinces. A GIS map (in shapefile format), corresponding to GEO2_ ID1980 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Indonesia can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 011001 South Aceh 011002 Southeast Aceh 011003 East Aceh 011004 Central Aceh 011005 West Aceh 011006 Greater Aceh 011007 Regency of Pidie 011008 North Aceh 011071 Banda Aceh (A) 011072 Sabang (B) 012001 Nias 012002 South Tapanuli 012003 Central Tapanuli 012004 North Tapanuli 012005 Labuhan Batu 012006 Grindings 012007 Simalungun 012008 Dairi 012009 Karo 012010 Deli Serdang 012011 Langkat 012071 Sibolga (A) 012072 Tanjung Balai (B) 012073 Kota Siantar (C) 012074 Tebing Tinggi (D) 012075 Medan (E) 012076 Binjai (F) 013001 South Pesisir 013002 Solok 013003 Sawahlunto/Sijunjung 013004 Tanah Datar 013005 Padang Pariaman 013006 Agam 013007 Lima Puluh Kota 013008 Pasaman 013071 Padang (A) 013072 Solok (B) 013074 Padang Panjang (D) 013075 Bukit Tinggi (E) 013076 Payakumbuh (F) 014001 Indragiri Hulu 014002 Indragiri Hilir 014003 Kapulauan Riau 014004 Kampar 014005 Bengkalis 014071 Pekan Baru (A) 015001 Kerinci 015002 Sarko 015003 Batanghari 015004 Tanjung Jabung 015005 Bungo Tebo 015071 Jambi (A) 016001 Ogan Komering Ulu 016002 Ogan Komering Ilir 016003 Lematang Ilir Ogan Teng . 016004 Lahat 016005 Musi Rawas 016006 Musi Banyu Asin 016007 Bangka 016008 Belitung 016071 Palembang (A) 016072 Pangkal Pinang (B) 017001 South Bengkulu 017002 Rejang Lebong 017003 North Bengkulu 017071 Bengkulu (A) 018001 South Lampung 018002 Central Lampung 018003 North Lampung 018071 Tanjung Karang (A) 031071 South Jakarta 031072 East Jakarta 031073 Central Jakarta 031074 West Jakarta 031075 North Jakarta 032001 Pandeglang 032002 Lebak 032003 Bogor 032004 Sukabumi 032005 Cianjur 032006 Bandung 032007 Garut 032008 Tasikmalaya 032009 Ciamis 032010 Kuningan 032011 Cirebon 032012 Majalengka 032013 Sumedang 032014 Indramayu 032015 Subang 032016 Purwakarta 032017 Karawang 032018 Bekasi 032019 Tangerang 032020 Serang 032071 Bogor (A) 032072 Sukabumi (B) 032073 Bandung (C) 032074 Cirebon (D) 033001 Cilacap 033002 Banyumas 033003 Purbalingga 033004 Banjarnegara 033005 Kebumen 033006 Purworejo 033007 Wonosobo 033008 Magelang 033009 Boyolali 033010 Klaten 033011 Sukoharjo 033012 Wonogiri 033013 Karanganyar 033014 Sragen 033015 Grobogan 033016 Blora 033017 Rembang 033018 Pati 033019 Kudus 033020 Jepara 033021 Demak 033022 Semarang 033023 Temanggung 033024 Kendal 033025 Batanghari 033026 Pekalongan 033027 Pemalang 033028 Tegal 033029 Brebes 033071 Magelang (A) 033072 Surakarta (B) 033073 Salatiga (C) 033074 Semarang (D) 033075 Pekalongan (E) 033076 Tegal (F) 034001 Kulon Progo 034002 Bantul 034003 Gunung Kidul 034004 Sleman 034071 Yogyakarta (A) 035001 Pacitan 035002 Ponorogo 035003 Trenggalek 035004 Tulungagung 035005 Blitar 035006 Kediri 035007 Malang 035008 Lumajang 035009 Jember 035010 Banyuwangi 035011 Bondowoso 035012 Situbondo 035013 Probolinggo 035014 Pasuruan 035015 Sidoarjo 035016 Mojokerto 035017 Jombang 035018 Nganjuk 035019 Madiun 035020 Magetan 035021 Ngawi 035022 Bojonegoro 035023 Tuban 035024 Lamongan 035025 Gresik (Surabaya) 035026 Bangkalan 035027 Sampang 035028 Pamekasan 035029 Sumenep 035071 Kediri (A) 035072 Blitar (B) 035073 Malang (C) 035074 Probolinggo (D) 035075 Pasuruan (E) 035076 Mojokerto (F) 035077 Madiun (G) 035078 Surabaya (H) 051001 Jembrana 051002 Tabanan 051003 Badung 051004 Gianyar 051005 Klungkung 051006 Bangli 051007 Karang Asem 051008 Buleleng 052001 West Lombok 052002 Central Lombok 052003 East Lombok 052004 Sumbawa 052005 Dompu 052006 Bima 053001 West Sumbawa 053002 East Sumba 053003 Kupang 053004 South Timor Tengah 053005 North Timor Tengah 053006 Belu 053007 Alor 053008 East Flores 053009 Sikka 053010 Ende 053011 Ngada 053012 Manggarai 054001 Cova Lima 054002 Bobonaro 054003 Manufahi 054004 Ainaro 054005 Viqueque 054006 Lautem 054007 Baucau 054008 Manatuto 054009 Alileu 054010 Dili 054011 Ermera 054012 Liquica 054013 Ambeno 061001 Sambas 061002 Pontianak 061003 Sanggau 061004 Ketapang 061005 Sintang 061006 Kapuas Hulu 061071 Pontianak (A) 062001 West Kotawaringin 062002 East Kotawaringin 062003 Katingan 062004 Kapuas 062005 South Barito 062006 East Barito 062007 North Barito 062008 Kahayan Hulu / G. Mas 062009 Murung Raya 062071 Palangka Raya (A) 063001 Tanah Laut 063002 Kota Baru 063003 Banjar 063004 Barito Kuala 063005 Tapin 063006 South Hulu Sei 063007 Central Hulu Sei 063008 North Hulu Sei 063009 Tabalong 063071 Banjarmasin (A) 064001 Pasir 064002 Kutai 064003 Berau 064004 Bulongan 064071 Balikpapan (A) 064072 Samarinda (B) 071001 Gorontalo 071002 Bolaang Mengondow 071003 Minahasa 071004 Sangihe Talaut 071071 Gorontalo (A) 071072 Manado (B) 072001 Luwuk/Banggai 072002 Poso 072003 Donggala 072004 Toli-Toli 073001 Selayar 073002 Bulukumba 073003 Bantaeng 073004 Jeneponto 073005 Takalar 073006 Gowa 073007 Sinjai 073008 Bone 073009 Maros 073010 Pangkajene Kepulauan 073011 Barru 073012 Soppeng 073013 Wajo 073014 Sidenreng Rappang 073015 Pinrang 073016 Enrekang 073017 Luwu 073018 Tana Toraja 073019 Polewali Mamasa 073020 Majene 073021 Mamuju 073071 Ujung Pandang (A) 073072 Pare-Pare (B) 074001 Buton 074002 Muna 074003 Kendari 074004 Kolaka 081001 Southeast Moluku 081002 Central Moluku 081003 Halmahera Tengah 081004 North Moluku 081071 Ambon (A) 082001 Peg. Jaya Wijaya 082002 Jayapura 082003 Paniai 082004 Fak-Fak 082005 Sorong 082006 Manokwari 082007 Tel-Cenderawasih 082008 Merauke 082009 Yapen Waropen Geography: F-N Variables -- HOUSEHOLD Ownership of dwelling [general version] OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. 0 NIU (not in universe) 1 Owned 2 Not owned 9 Unknown Household Economic Variables -- HOUSEHOLD Ownership of dwelling [detailed version] OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. 000 NIU (not in universe) 100 Owned 110 Owned, already paid 120 Owned, still paying 130 Owned, constructed 140 Owned, inherited 190 Owned, other 191 Owned, house 192 Owned, condominium 193 Apartment proprietor 194 Shared ownership 200 Not owned 210 Renting, not specified 211 Renting, government 212 Renting, local authority 213 Renting, parastatal 214 Renting, private 215 Renting, private company 216 Renting, individual 217 Renting, collective 218 Renting, joint state and individual 219 Renting, public subsidized 220 Renting, private subsidized 221 Renting, co-tenant 222 Renting, relative of tenant 223 Renting, cooperative 224 Renting, with a job or business 225 Renting, loan-backed habitation 226 Renting, mixed contract 227 Furnished dwelling 228 Sharecropping 230 Subletting 231 Rent to own 239 Renting, other 240 Occupied de facto/squatting 250 Free/usufruct (no cash rent) 251 Free, provided by employer 252 Free, without work or services 253 Free, provided by family or friend 254 Free, private 255 Free, public 256 Free, condemned 257 Free, other 260 Endowment, Waqf (Egypt historical) 290 Not owned, other 999 Unknown Household Economic Variables -- HOUSEHOLD Electricity ELECTRIC indicates whether the household had access to electricity. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Utilities Variables -- HOUSEHOLD Water supply 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. 00 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 Utilities Variables -- HOUSEHOLD Sewage SEWAGE indicates whether the household has access to a sewage system or septic tank. 00 NIU (not in universe) 10 Connected to sewage system or septic tank 11 Sewage system (public sewage disposal) 12 Septic tank (private sewage disposal) 20 Not connected to sewage disposal system 99 Unknown Utilities Variables -- HOUSEHOLD Cooking fuel FUELCOOK indicates the predominant type of fuel or energy used for cooking. 00 NIU (not in universe) 10 None 20 Electricity 30 Petroleum gas, unspecified 31 Gas -- piped/utility 32 Gas -- tanked or bottled 33 Propane 34 Liquefied petroleum gas 35 Gas -- piped and bottled 40 Petroleum liquid 41 Oil, kerosene, and other liquid fuels 42 Kerosene/paraffin 43 Kerosene or oil 44 Kerosene or gasoline 45 Gasoline 46 Cocinol 47 Diesel 50 Wood, coal, and other solid fuels 51 Wood and other plant fuels 52 Non-wood plant materials 53 Coal or charcoal 54 Charcoal 55 Coal 56 Wood or charcoal 60 Multiple fuels 61 Bottled gas and wood 62 Propane and electricity 63 Propane, kerosene, and electricity 64 Propane and kerosene 65 Kerosene and electrictiy 66 Other combinations 70 Other 71 Alcohol 72 Biogas 73 Discarded or waste material 74 Dung/manure 75 Other combined organic waste materials 76 Solar energy 77 Candle 99 Unknown/missing Utilities Variables -- HOUSEHOLD Television set TV indicates whether the household had a television. 00 NIU (not in universe) 10 No 20 Yes, color or black-and-white not specified 21 1 television 22 2 televisions 23 3 televisions 24 4 televisions 25 5 televisions 26 6 televisions 27 7 televisions 28 8 televisions 29 9+ televisions 30 Yes, at least one color tv 31 1 color tv 32 2 color tvs 33 3+ televisions 40 Yes, black-and-white only 41 1 black-white tv 42 2 black-white tvs 43 3+ black-white tvs 99 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Radio in household RADIO indicates whether the household had a radio. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Bathing facilities BATH indicates whether the household had access to bathing facilities and, in most cases, whether it had exclusive access. 0 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 Dwelling Characteristics Variables -- HOUSEHOLD Floor material FLOOR indicates the dwelling's predominant flooring material. 000 NIU (not in universe) 100 None/unfinished (earth) 110 Sand 120 Dung 200 Finished 201 Cement, tile, or brick 202 Cement 203 Concrete 204 Cement screed 205 Ceramic tile 206 Paving stone, cement tile 207 Stone 208 Brick 209 Brick or stone 210 Brick or cement 211 Block 212 Terrazzo 213 Wood 214 Palm, bamboo 215 Parquet 216 Parquet, tile, vinyl 217 Parquet, tile, marble 218 Ceramic, marble, granite 219 Ceramic, marble, tile, or vinyl 220 Marble 221 Mosaic 222 Tile 223 Tile, linoleum, ceramic, etc 224 Tile, cement 225 Tile, stone 226 Tile, stone, brick 227 Tile, stone, vinyl, brick 228 Tile, vinyl, brick 229 Tile, vinyl 230 Vinyl, linoleum, etc 231 Asphalt sheet, vinyl, etc 232 Synthetic, plastic 233 Cane 234 Carpet, rug 235 Scrap material 236 Other finished, n.e.c. 999 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Wall or building material This variable indicates the primary material used in the construction of the dwelling, particularly the dwelling's exterior walls. 000 NIU (not in universe) 100 No walls 200 Cardboard, scrap, and miscellaneous materials 201 Waste, scrap, or discarded material 202 Fabric or discarded material 203 Zinc, fabric, cardboard, tins, and waste material 204 Cardboard sheet 205 Plastic sheeting, cardboard 206 Makeshift, salvaged, or improvised materials 207 Reused materials 300 Wood 310 Rough wood 320 Wood, fibercement or plywood 330 Wood, formica, and other 340 Wood or bamboo 350 Wood or straw 400 Other plant-based materials 401 Plantain leaves and similar material 402 Bamboo or cane 403 Bamboo, sawali, cogon, nipa 404 Straw or bamboo 405 Grass, straw or reed 406 Reed, bamboo, or palm 407 Cane, palm leaves, logs 408 Palm leaves or palm planks 409 Bark, sticks, or cane 500 Masonry, stone, cement, adobe, metal, glass, and other fabricated materials (sometimes mixed with wood) 501 Brick, block, stone, or cement 502 Brick, stone, concrete 503 Brick, stone, or substitutes (dividing panels made of reinforced concrete) 504 Brick, stone, or substitutes (dividing panels made of wood) 505 Brick or tile 506 Brick or stone 507 Brick or cement block 508 Brick with plaster exterior 509 Brick without plaster exterior 510 Burnt or stabilized brick 511 Covered brick 512 Brick 513 Unburnt brick 514 Unburnt brick with cement 515 Unburnt brick with mud 516 Concrete 517 Landcrete, sandcrete 518 Cement blocks 519 Cement blocks or brick 520 Cement blocks or brick, unfinished 521 Cement and adobe bricks 522 Cement and stone block 523 Cement and tiles 524 Reinforced concrete, pre-cast concrete panels, or steel skeleton framed concrete 525 Concrete, reinforced concrete, blocks, panels 526 Fibercement 527 Adobe 528 Adobe walls with plaster exterior 529 Adobe walls without plaster exterior 530 Adobe with cement exterior 531 Wood and earth adobe 532 Wood and cement adobe 533 Mud or adobe 534 Pressed dirt 535 Clay 536 Coated clay/mud with sticks/cane 537 Clay or clay-covered sticks 538 Netted bamboo or cane with mud 539 Bundle of mud, straw, other materials 540 Mud with wood/wattle 541 Pole and mud 542 Mud with cement 543 Unfinished lathe and plaster, stucco, etc. 544 Stone 545 Hand-laid stone 546 Quarried stone 547 Cut stone and concrete 548 Cemented stone 549 Stone with clay 550 Blocks of light material 551 Prefabricated material 552 Asbestos 553 Metal or asbestos sheet 554 Metal or iron sheet 555 Metal or fibercement sheeting 556 Galvanized iron or aluminum 557 Tin 558 Glass 559 Cloth 560 Covintec panels 561 Mixed material 562 Mixed material: part wood; part concrete, brick, or stone 563 Wood plastered with clay, adobe, other materials; wood pressed panels; rolled mud bricks; etc. 564 Mixed material: wood or galvanized metal 570 Mainly permanent materials 600 Other material 601 Partition wall, lined with wood or steel 602 Partition wall, unlined 999 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Roof material This variable indicates the dwelling's predominant roofing material. 00 NIU (not in universe) 10 Masonry, concrete, clay tile, or tiles of unspecified type 11 Concrete or cement 12 Reinforced concrete (slab) 13 Cement or sheet metal 14 Tile, unspecified material 15 Clay tile 16 Tile or cement 17 Modern tiles, industrial 18 Traditional tiles, locally made 19 Tile or flat stone 20 Tile, unspecified or mixed materials 21 Fibercement or plastic 22 Fibercement or metal sheets 23 Asphalt or laminate cover 24 Tile, cement, asphalt 25 Asphalt tile 26 Slate or tile 27 Slate or asbestos 28 Asbestos 29 Adobe 30 Tiles or wood planks 31 Roofing shingles 32 Tar paper 33 Metal 34 Sheet metal 35 Zinc or tin 36 Tin 37 Sheet metal or other sheet material 38 Sheet metal, tile, slate 40 Wood and other plant materials 41 Wood 42 Wood, including bamboo 43 Bamboo 44 Cogon, nipa, anahaw 45 Thatch (straw, grass, leaves, palm, etc.) 46 Cane, wood, straw 47 Grass or straw 48 Papyrus 49 Banana leaves or fiber 50 Palm or makuti 51 Straw, bamboo, polythene 52 Wood with clay 53 Grass and mud 54 Rustic mat 60 Mud or earth 61 Clay 70 Cardboard, scrap, and miscellaneous materials 71 Discarded or scrap material 72 Cardboard 73 Plastic, tarpaulin 80 Other, unspecified 90 No roof 99 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Stories in structure STORIES indicates the number of floors or levels in the building containing the responding housing unit. 00 NIU (not in universe) 01 1 story 02 2 stories 03 3 stories 04 4 stories 05 5 stories 06 6 stories 07 7 stories 08 8 stories 09 9 stories 10 10 stories 11 11 stories 12 12 stories 13 13 stories 14 14 stories 15 15 stories 16 16 stories 17 17 stories 18 18 stories 19 19 stories 20 20 stories 21 21 stories 22 22 stories 23 23 stories 24 24 stories 25 25+ stories 99 Unknown Dwelling Characteristics Variables -- HOUSEHOLD 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. Codes000 = NIU (not in universe) 999 = Unknown Top codes:Unless otherwise specified: 998+ Austria 1991-2001: 150+ Belarus 1999: 201+ Belarus 2009: 250+ Germany 1987: 361+ Hungary 2001: 260+ Hungary 2011: 301+ Iran 2006: 501+ Italy 2001: 150+ Italy 2011: 145+ Laos 2005: 200+ Philippines 1990-2010: 200+ Poland 2002: 200+ Romania 2002: 221+ Romania 2011: 500+ Slovenia 2002: 101+ Spain 1991: 181+ Spain 2001-2011: 900+ Switzerland 1980-1990: 400+ Switzerland 2000: 500+ Dwelling Characteristics Variables -- HOUSEHOLD Household classification 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. 00 Vacant household 01 One-person household 02 Married/cohab couple, no children 03 Married/cohab couple with children 04 Single-parent family 05 Polygamous family 06 Extended family, relatives only 07 Composite household, family and non-relatives 08 Non-family household 09 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable Constructed Household Variables -- HOUSEHOLD Number of families in household NFAMS is a constructed variable that indicates the number of families within each household. Family membership is defined by FAMUNIT. 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 a domestic employee contains two families; a household consisting of a large, multi-generation extended family with no persons unrelated to the head counts 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. 0 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 Constructed Household Variables -- HOUSEHOLD Number of married couples in household 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). 0 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 Constructed Household Variables -- HOUSEHOLD Number of 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). 0 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 Constructed Household Variables -- HOUSEHOLD Number of 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). 0 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 Constructed Household Variables -- HOUSEHOLD Head's location in household HEADLOC gives the person number (PERNUM) of the head of household in samples in which persons are organized into households. HEADLOC is a 3-digit numeric variable. Constructed Household Variables -- HOUSEHOLD Household number (within dwelling) Indonesia 1980: All records This variable indicates the household number (within dwelling). 1 [no label] Technical Household Variables -- HOUSEHOLD Number of persons in dwelling Indonesia 1980: All records This variable indicates the number of persons in the dwelling. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 Technical Household Variables -- HOUSEHOLD Number of persons in household Indonesia 1980: All records This variable indicates the number of persons in the household. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 Technical Household Variables -- HOUSEHOLD Urban rural <span class="h3">I. Location Identification</span><div class="i1">1. Province ____<br />2. Regency / municipality ____<br />3. Sub-regency / sub-district ____<br />4. Island ____<br />5 Village ____</div> Indonesia 1980: All households This variable indicates whether the household is located in an urban or rural area. 1 Urban 2 Rural Geography: F-N Variables -- HOUSEHOLD Household serial number <span class="h3">I. Location Identification</span><div class="i1">9. Sample code ____<br />10. Physical building no. ____<br />11. Census building no. ____<br />12. Household serial no. ____</div> Indonesia 1980: All households This variable indicates the household serial number. Other Household Variables -- HOUSEHOLD Type of household <div class="i1">13. Household</div><div class="i2">[] Private<br />[] Institutional</div> Indonesia 1980: All households This variable indicates the type of household. 1 Private household 2 Institutional household Group Quarters Variables -- HOUSEHOLD Type of census block Indonesia 1980: All households This variable indicates the type of census block. 1 Ordinary 2 Special Other Household Variables -- HOUSEHOLD Type of physical building <svar v="ID80A031 ID80A032 ID80A068" a="all">1. Type of physical building<br /><div class="i1">1 Independent building with single dwelling unit</div><br /><div class="i2">[] 1 Multistory<br />[] 2 Single story</div><br /><div class="i1">2 Independent building with two dwelling units</div><br /><div class="i2">[] 1 Multistory<br />[] 2 Single story</div><br /><div class="i1">[] 3 Independent building with more than two dwelling units</div><br /></svar> Indonesia 1980: All households This variable indicates the type of physical building. 1 Independent building with single dwelling unit 2 Independent building with two dwelling units 3 Independent building with more than two dwelling units 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Multi-floor building <svar v="ID80A031 ID80A032 ID80A068" a="all">1. Type of physical building<br /><div class="i1">1 Independent building with single dwelling unit</div><br /><div class="i2">[] 1 Multistory<br />[] 2 Single story</div><br /><div class="i1">2 Independent building with two dwelling units</div><br /><div class="i2">[] 1 Multistory<br />[] 2 Single story</div><br /><div class="i1">[] 3 Independent building with more than two dwelling units</div><br /></svar> Indonesia 1980: All households This variable indicates whether or not the dwelling is a multifloor building. 1 Multi-floor building 2 Single level building 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Number of census buildings in this physical building <svar v="ID80A033" a="all">2. Number of census buildings in this physical building<br /><div class="i1">Census buildings _</div><br /></svar> Indonesia 1980: All households This variable indicates the number of census buildings in this physical building. 01 1 census building 02 2 census buildings 03 3 census buildings 04 4 05 5 06 6 07 7 08 8 09 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 or more cenus buildings 99 Unknown Other Household Variables -- HOUSEHOLD Number of households in this census building <svar v="ID80A034" a="all">3. Number of households in this census building<br /><div class="i1">Households _ _</div><br /></svar> Indonesia 1980: All households This variable indicates the number of households in this census building. 01 1 household 02 2 households 03 3 households 04 4 05 5 06 6 07 7 08 8 09 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 68 68 69 69 70 70 71 71 72 72 73 73 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 87 87 88 88 90 90 92 92 93 93 99 Unknown Other Household Variables -- HOUSEHOLD Status of ownership <svar v="ID80A035" a="all">4. Status of ownership<br /><div class="i1">[] 1 Self-owned<br />[] 2 Rent (contract/long term basis)<br />[] 3 Rent (monthly basis)<br />[] 4 Installment purchase<br />[] 5 Provided by employer<br />[] 6 Other</div><br /></svar> Indonesia 1980: All households This variable indicates the status of ownership of the dwelling. 1 Self-owned 2 Rent (contract/long term) 3 Rent (monthly basis) 4 Rent to buy (installment purchase) 5 Provided by employer 6 Other 9 Unknown Household Economic Variables -- HOUSEHOLD Primary construction material of roof <svar v="ID80A036" a="all">5. Primary construction material of roof<br /><div class="i1">[] 1 Concrete<br />[] 2 Wood<br />[] 3 Corrugated zinc/asbestos<br />[] 4 Tile<br />[] 5 Sugar palm fiber<br />[] 6 Leaves<br />[] 7 Other</div><br /></svar> Indonesia 1980: All households This variable indicates the primary construction material of the roof of a dwelling. 1 Concrete 2 Wood 3 Corrugated zinc/asbestos 4 Tile 5 Sugar palm fiber 6 Leaves 7 Other 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Primary construction material of wall <svar v="ID80A037" a="all">6. Primary construction material of wall<br /><div class="i1">[] 1 Brick<br />[] 2 Wood<br />[] 3 Bamboo<br />[] 4 Other</div><br /></svar> Indonesia 1980: All households This variable indicates the primary construction material of the walls of a dwelling. 1 Brick 2 Wood 3 Bamboo 4 Other 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Primary construction material of floor <svar v="ID80A038" a="all">7. Primary construction material of floor<br /><div class="i1">[] 1 Tile<br />[] 2 Concrete/brick<br />[] 3 Wood<br />[] 4 Bamboo<br />[] 5 Earth<br />[] 6 Other</div><br /></svar> Indonesia 1980: All households This variable indicates the primary construction material of the floor of a dwelling. 1 Tile 2 Cement/brick 3 Wood 4 Bamboo 5 Earth 6 Other 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Floor area (square meters) <svar v="ID80A039 ID80A065 ID80A071" a="all">8. Floor area<br /><div class="i1">____ square meters</div><br /></svar> Indonesia 1980: All households This variable indicates the floor area (square meters) of the dwelling. 998 998 or more 999 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Type of lighting <svar v="ID80A040" a="all">9. Type of lighting<br /><div class="i1">[] 1 Electric<br />[] 2 Pumped lamp<br />[] 3 Kerosene lamp<br />[] 4 Other</div><br /></svar> Indonesia 1980: All households This variable indicates the type of lighting in the dwelling. 1 Electric 2 Pumped lamp 3 Kerosene lamp 4 Other 9 Unknown Utilities Variables -- HOUSEHOLD Type of cooking fuel <svar v="ID80A041" a="all">10. Type of cooking fuel<br /><div class="i1">[] 1 Electric<br />[] 2 Gas<br />[] 3 Kerosene<br />[] 4 Wood<br />[] 5 Charcoal<br />[] 6 Other</div><br /></svar> Indonesia 1980: All households This variable indicates the type of cooking fuel used in the dwelling. 1 Electric 2 Gas 3 Kerosene 4 Wood 5 Charcoal 6 Other 9 Unknown Utilities Variables -- HOUSEHOLD Source of drinking water <svar v="ID80A042" a="all">11. Source of drinking water<br /><div class="i1">[] 1 Pipe<br />[] 2 Pump<br />[] 3 Well<br />[] 4 Spring<br />[] 5 River<br />[] 6 Rain<br />[] 7 Other</div><br /></svar> Indonesia 1980: All households This variable indicates the source of drinking water for the dwelling. 1 Pipes 2 Pump 3 Well 4 Spring 5 River 6 Rain 7 Other 9 Unknown Utilities Variables -- HOUSEHOLD Source of water for bathing/washing <svar v="ID80A043" a="all">12. Source of water for bathing/washing<br /><div class="i1">[] 1 Pipe<br />[] 2 Pump<br />[] 3 Well<br />[] 4 Spring<br />[] 5 River<br />[] 6 Rain<br />[] 7 Other</div><br /></svar> Indonesia 1980: All households This variable indicates the source of water for bathing/washing for the dwelling. 1 Pipes 2 Pump 3 Well 4 Spring 5 River 6 Rain 7 Other 9 Unknown Utilities Variables -- HOUSEHOLD Bathing facility <svar v="ID80A044" a="all">13. Bathing facility<br /><div class="i1">[] 1 Private<br />[] 2 Shared/private<br />[] 3 Public<br />[] 4 Other</div><br /></svar> Indonesia 1980: All households This variable indicates the type of bathing facility a household uses. 1 Private 2 Shared (private facility) 3 Public 4 Other 9 Unknown Utilities Variables -- HOUSEHOLD Toilet facility <svar v="ID80A045" a="all">14. Toilet facility<br /><div class="i1">[] 1 Private, with septic tank<br />[] 2 Private, without septic tank<br />[] 3 Shared/public/other</div><br /></svar> Indonesia 1980: All households This variable indicates the type of toilet facility a household uses. 1 Private, with septic tank 2 Private, without septic tank 3 Shared/public/other 9 Unknown Utilities Variables -- HOUSEHOLD Own buffet (sideboard) 15. Does this household own:</p> <div class="i1">a. Buffet (side board)?</div><div class="i2">[] 1 Yes<br />[] 2 No</div> Indonesia 1980: All households This variable indicates whether or not a household owns a buffet (sideboard). 1 Yes 2 No 9 Unknown Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Own stove 15. Does this household own:</p> <div class="i1">b. Stove?</div><div class="i2">[] 1 Yes<br />[] 2 No</div> Indonesia 1980: All households This variable indicates whether or not the household owns a stove. 1 Yes 2 No 9 Unknown Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Own bicycle 15. Does this household own:</p> <div class="i1">c. Bicycle?</div><div class="i2">[] 1 Yes<br />[] 2 No</div> Indonesia 1980: All households This variable indicates whether or not the household owns a bicycle. 1 Yes 2 No 9 Unknown Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Own radio/cassete recorder 15. Does this household own:</p> <div class="i1">d. Radio/cassette recorder?</div><div class="i2">[] 1 Yes<br />[] 2 No</div> Indonesia 1980: All households This variable indicates whether or not the household owns a radio and or a cassette recorder. 1 Yes 2 No 9 Unknown Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Own TV set 15. Does this household own:</p> <div class="i1">e. T.V. set?</div><div class="i2">[] 1 Yes<br />[] 2 No</div> Indonesia 1980: All households This variable indicates whether or not the household owns a TV set. 1 Yes 2 No 9 Unknown Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Self-owned agricultural land (hectares) <span class="h3">V. Agricultural land tenure</span><div class="i1">16. Self-owned</div><div class="i2">____ Ha</div> Indonesia 1980: All households This variable indicates self-owned agricultural land (hectares). 9999 Unknown Household Economic Variables -- HOUSEHOLD Agricultural land obtained from others (hectares) <span class="h3">V. Agricultural land tenure</span><div class="i1">17. Obtained from others</div><div class="i2">____ Ha</div> Indonesia 1980: All households This variable indicates agricultural land obtained from others (hectares). 9999 Unknown Household Economic Variables -- HOUSEHOLD Agricultural land operated by others (hectares) <span class="h3">V. Agricultural land tenure</span><div class="i1">18. Operated by others</div><div class="i2">____ Ha</div> Indonesia 1980: All households This variable indicates agricultural land operated by others (hectares). 9999 Unknown Household Economic Variables -- HOUSEHOLD Total agricultural land (hectares) <span class="h3">V. Agricultural land tenure</span><div class="i1">19. Total (Q16 + Q17 + Q18)</div><div class="i2">____ Ha</div> Indonesia 1980: All households This variable indicates total agricultural land (hectares). 9999 Unknown Household Economic Variables -- HOUSEHOLD Number of dairy cows raised <span class="h3">VI. Livestock/poultry raised by household</span></p> <p>20. Dairy cow</p> <div class="i1">_ _ _ unit</div> Indonesia 1980: All households This variable indicates the number of dairy cows owned by a household. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 039 39 040 40 041 41 042 42 044 44 045 45 048 48 050 50 051 51 053 53 054 54 056 56 057 57 060 60 061 61 062 62 063 63 064 64 065 65 066 66 068 68 070 70 072 72 074 74 075 75 078 78 080 80 081 81 082 82 083 83 084 84 086 86 090 90 093 93 108 108 138 138 150 150 200 200 500 500 998 Unknown Household Economic Variables -- HOUSEHOLD Number of cows raised <span class="h3">VI. Livestock/poultry raised by household</span></p> <p>21. Cow</p> <div class="i1">_ _ _ unit</div> Indonesia 1980: All households This variable indicates the number of cows owned by a household. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 047 47 048 48 050 50 052 52 053 53 054 54 055 55 056 56 057 57 058 58 060 60 061 61 063 63 065 65 070 70 071 71 072 72 075 75 077 77 080 80 084 84 089 89 090 90 092 92 095 95 100 100 200 200 220 220 239 239 250 250 610 610 998 Unknown Household Economic Variables -- HOUSEHOLD Number of buffalos raised <span class="h3">VI. Livestock/poultry raised by household</span></p> <p>22. Buffalo</p> <div class="i1">_ _ _ unit</div> Indonesia 1980: All households This variable indicates the number of buffalos owned by a household. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 032 32 033 33 034 34 035 35 036 36 037 37 040 40 043 43 044 44 045 45 048 48 050 50 054 54 060 60 064 64 070 70 075 75 096 96 100 100 150 150 200 200 295 295 998 Unknown Household Economic Variables -- HOUSEHOLD Number of horses raised <span class="h3">VI. Livestock/poultry raised by household</span></p> <p>23. Horse</p> <div class="i1">_ _ _ unit</div> Indonesia 1980: All households This variable indicates the number of horses owned by a household. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 022 22 023 23 025 25 026 26 027 27 028 28 029 29 030 30 032 32 035 35 045 45 046 46 050 50 070 70 074 74 080 80 100 100 117 117 196 196 400 400 998 Unknown Household Economic Variables -- HOUSEHOLD Number of goats/sheep raised <span class="h3">VI. Livestock/poultry raised by household</span></p> <p>24. Goat/sheep</p> <div class="i1">_ _ _ unit</div> Indonesia 1980: All households This variable indicates the number of goats and or sheep owned by a household. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 058 58 059 59 060 60 061 61 063 63 065 65 066 66 070 70 075 75 078 78 080 80 087 87 090 90 098 98 100 100 103 103 110 110 111 111 112 112 125 125 129 129 150 150 156 156 163 163 200 200 240 240 300 300 400 400 500 500 998 Unknown Household Economic Variables -- HOUSEHOLD Number of pigs raised <span class="h3">VI. Livestock/poultry raised by household</span></p> <p>25. Pig</p> <div class="i1">_ _ _ unit</div> Indonesia 1980: All households This variable indicates the number of pigs owned by a household. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0060 60 0062 62 0063 63 0070 70 0073 73 0074 74 0075 75 0080 80 0085 85 0089 89 0090 90 0095 95 0097 97 0100 100 0101 101 0104 104 0112 112 0120 120 0132 132 0150 150 0158 158 0170 170 0200 200 0250 250 0300 300 0400 400 0450 450 0500 500 0800 800 0801 801 0999 999 1000 1000 4000 4000 9998 Unknown Household Economic Variables -- HOUSEHOLD Number of chickens (imported variety) raised <span class="h3">VI. Livestock/poultry raised by household</span></p> <p>26. Chicken (imported variety)</p> <div class="i1">_ _ _ unit</div> Indonesia 1980: All households This variable indicates the number of chickens (imported variety) owned by a household. 9998 Unknown Household Economic Variables -- HOUSEHOLD Number of chickens (local variety) raised <span class="h3">VI. Livestock/poultry raised by household</span></p> <p>27. Chicken (local variety)</p> <div class="i1">_ _ _ unit</div> Indonesia 1980: All households This variable indicates the number of chickens (local variety) owned by a household. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 0100 100 0101 101 0102 102 0103 103 0105 105 0106 106 0107 107 0108 108 0110 110 0111 111 0112 112 0113 113 0114 114 0115 115 0116 116 0120 120 0121 121 0122 122 0123 123 0124 124 0125 125 0126 126 0128 128 0130 130 0132 132 0136 136 0138 138 0140 140 0141 141 0142 142 0143 143 0145 145 0148 148 0150 150 0151 151 0152 152 0155 155 0156 156 0160 160 0165 165 0169 169 0170 170 0174 174 0176 176 0180 180 0182 182 0185 185 0187 187 0189 189 0190 190 0198 198 0200 200 0202 202 0205 205 0206 206 0210 210 0213 213 0214 214 0220 220 0224 224 0225 225 0230 230 0235 235 0250 250 0252 252 0260 260 0300 300 0315 315 0332 332 0350 350 0400 400 0402 402 0440 440 0450 450 0482 482 0500 500 0510 510 0522 522 0550 550 0600 600 0603 603 0613 613 0700 700 0765 765 0800 800 0801 801 1000 1000 1020 1020 1500 1500 9998 Unknown Household Economic Variables -- HOUSEHOLD Number of ducks raised <span class="h3">VI. Livestock/poultry raised by household</span></p> <p>28. Duck</p> <div class="i1">_ _ _ unit</div> Indonesia 1980: All households This variable indicates the number of ducks owned by a household. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 0100 100 0101 101 0102 102 0103 103 0104 104 0105 105 0106 106 0107 107 0108 108 0109 109 0110 110 0112 112 0113 113 0114 114 0115 115 0116 116 0117 117 0120 120 0121 121 0122 122 0124 124 0125 125 0126 126 0127 127 0128 128 0130 130 0132 132 0133 133 0135 135 0136 136 0137 137 0138 138 0140 140 0144 144 0145 145 0147 147 0150 150 0151 151 0152 152 0153 153 0154 154 0158 158 0159 159 0160 160 0163 163 0170 170 0173 173 0175 175 0177 177 0178 178 0180 180 0185 185 0186 186 0190 190 0191 191 0195 195 0198 198 0200 200 0201 201 0204 204 0205 205 0212 212 0216 216 0220 220 0230 230 0235 235 0240 240 0245 245 0250 250 0270 270 0275 275 0289 289 0295 295 0300 300 0305 305 0312 312 0313 313 0320 320 0330 330 0335 335 0340 340 0350 350 0360 360 0369 369 0400 400 0401 401 0450 450 0465 465 0500 500 0510 510 0517 517 0567 567 0600 600 0714 714 0812 812 1000 1000 1600 1600 2000 2000 9998 Unknown Household Economic Variables -- HOUSEHOLD Household weight Indonesia 1980: All households This variable indicates the household weight. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 39 39 40 40 41 41 43 43 44 44 45 45 52 52 53 53 Technical Household Variables -- HOUSEHOLD Number of household members working during the previous week Indonesia 1980: All households This variable indicates the number of household members working during the previous week. 1 1 2 2 3 3 4 4 5 5 Constructed Household Variables -- HOUSEHOLD Type of physical building <svar v="ID80A031 ID80A032 ID80A068" a="all">1. Type of physical building<br /><div class="i1">1 Independent building with single dwelling unit</div><br /><div class="i2">[] 1 Multistory<br />[] 2 Single story</div><br /><div class="i1">2 Independent building with two dwelling units</div><br /><div class="i2">[] 1 Multistory<br />[] 2 Single story</div><br /><div class="i1">[] 3 Independent building with more than two dwelling units</div><br /></svar> Indonesia 1980: All households This variable indicates the type of physical building. 1 Multistory independent building with single dwelling unit 2 Multistory independent building with two dwelling units 3 Multistory Independent building with more than two dwelling units 4 Single story independent building with single dwelling unit 5 Single story independent building with two dwelling units 6 Single story independent building with more than two dwelling units 7 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Social-economic classification of household Indonesia 1980: All households This variable indicates the social-economic classification of the household. 01 Fewer than 0.01 hectares 02 0.01 to 0.10 hectares 03 0.11 to 0.20 hectares 04 0.21 to 0.25 hectares 05 0.26 to 0.30 hectares 06 0.31 to 0.40 hectares 07 0.41 to 0.50 hectares 08 0.51 to 0.75 hectares 09 0.76 to 1.00 hectares 10 1.01 to 1.50 hectares 11 1.51 to 2.00 hectares 12 2.01 to 3.00 hectares 13 3.01 to 5.00 hectares 14 5.00 or more hectares 15 Fewer than 0.01 hectare 16 0.01 to 0.10 hectares 17 0.11 to 0.20 hectares 18 0.21 to 0.25 hectares 19 0.26 to 0.30 hectares 20 0.31 to 0.40 hectares 21 0.41 to 0.50 hectares 22 0.51 to 0.75 hectares 23 0.76 to 1.00 hectares 24 1.01 to 1.50 hectares 25 1.51 to 2.00 hectares 26 2.01 to 3.00 hectares 27 3.01 to 5.00 hectares 28 5.00 or more hectares 29 Fewer than 0.01 hectares 30 0.01 to 0.10 hectares 31 0.11 to0.20 hectares 32 0.21 to 0.25 hectares 33 0.26 to 0.30 hectares 34 0.31 to 040 hectares 35 0.41 to 050 hectares 36 0.51 to 0.75 hectares 37 0.76 to 1.00 hectares 38 1.01 to 1.50 hectares 39 1.51 to 2.00 hectares 40 2.01 to 3.00 hectares 41 3.01 to 5.00 hectares 42 5.00 or more hectares 43 Head of household worked as employee in crop farming 44 Head of household worked as employee in gardening 45 Head of household worked as employee in animal husbandry 46 Head of household worked as employee in services related to farming crops and animal husbandry 47 Head of household worked as employee in forestry and hunting 48 Head of household worked as employee in fishing 49 Head of household worked as employee in other agricultural activities with employees 50 Head of household worked as employee in non-agricultural work, without permanent employees in (a) large scale commerce, hotels or inns or b) in trade, insurance, rental properties or land, or services, or in professional, technical and related work 51 Head of household worked in nontoagricultural work, without permanent employees, in areas other than those described above in code 50 52 Professional, technical and related fields 53 Guidance and counseling, public administration and organization, catering and food service, managerial work related to farming and animal husbandry 54 Work other than those described in code 53 and in transportation and postal services, sales other than those described in code 53, barbers/hairdressers and other beauty‑related work 55 Land transportation and postal services, sales other than those described above, services other than those described above; hairdressing and beautytorelated services 56 Production and related work, operatives and manual labor 57 Members of the armed forces 58 10 to 24 years 59 25 to 54 years 60 55 and older 61 Not classified Constructed Household Variables -- HOUSEHOLD Strata Indonesia 1980: All households This variable is the strata identifier for the sample. Strata is a constructed variable that captures implicit geographic stratification resulting from the sample design. It is created by assigning a unique identifier to groups of between 10 and 19 adjacent households. Additional documentation is available on the Variance Estimation page. This is a 6-digit numeric variable with 0 implied decimal places Geography: F-N Variables -- HOUSEHOLD 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 4-digit numeric variable. Technical Person Variables -- PERSON 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. Technical Person Variables -- PERSON 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. For more details on the construction of MOMLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. 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. To restrict MOMLOC to biological mothers, such as for own children fertility estimation, MOMLOC should be reset to zero when STEPMOM is greater than zero. MOMLOC is a 3-digit numeric variable. Codes0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother Constructed Family Interrelationship Variables -- PERSON 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. For more details on the construction of POPLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. 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. To restrict POPLOC to biological mothers, such as for own children fertility estimation, POPLOC should be reset to zero when STEPPOP is greater than zero. POPLOC is a 3-digit numeric variable. Codes0 = No father of this person present in the household. 1 or higher = The person number of this person's father Constructed Family Interrelationship Variables -- PERSON 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. For more details on the construction of SPLOC, see the Comparability section of SPRULE and this paper on IPUMSI family linking methodology. SPLOC is a 3-digit numeric variable. Codes0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse Constructed Family Interrelationship Variables -- PERSON Rule for linking parent 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. 00 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 Constructed Family Interrelationship Variables -- PERSON Rule for linking spouse 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. 00 No spouse present 01 Rule 1: strong relationship pairing, couple adjacent 02 Rule 2: strong relationship pairing, couple not adjacent 03 Rule 3: weak relationship pairing, couple adjacent 04 Rule 4: weak relationship pairing, couple not adjacent 05 Rule 5: weak consensual union pairings 06 Rule 6: sample-specific rules (usually child-to-child) Constructed Family Interrelationship Variables -- PERSON Probable stepmother 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 born 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. In cases where more than one criterion for a likely stepmother is met, STEPMOM will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. In cases where a mother is linked to more children than she reports in CHBORN or CHSURV, the determination of which children to flag as probable stepchildren is based first on the strength of the child-mother pairing (see PARRULE), and then on the order of children in the household roster. Since most links to a given mother will be made at the same strength level, order will often be the decisive factor in flagging probable stepmother relationships. 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. 0 Biological mother or no mother present 1 Mother has no children born 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 Constructed Family Interrelationship Variables -- PERSON Probable stepfather 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. In cases where more than one criterion for a likely stepfather is met, STEPPOP will take the value of the criterion with the lowest code. 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. 0 Biological father or no father present 1 Child reports father is deceased 2 Explicitly identified step relationship 3 Age difference implausible 4 Spouse of mother 5 Identified as adopted 6 Surname difference -- male child or never-married female Constructed Family Interrelationship Variables -- PERSON Man with more than one wife linked 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. 0 No more than one wife linked via SPLOC 1 More than one wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON Woman is second or higher order wife 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. 0 Person is not the 2nd or higher order wife linked via SPLOC 1 Person is the 2nd or higher order wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON 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 4-digit numeric variable. CodesIf 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. Constructed Family Interrelationship Variables -- PERSON Number of own family members in household 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 membership). 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). 0001 1 family member present 0002 2 family members present 0003 3 family members present 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 or more persons Constructed Family Interrelationship Variables -- PERSON Number of own 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. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children in household Constructed Family Interrelationship Variables -- PERSON Number of 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. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more own children under age 5 in household 98 One or more children have unknown age Constructed Family Interrelationship Variables -- PERSON Age of eldest 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. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Age of youngest 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. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Relationship to household head [general version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown Demographic Variables -- PERSON Relationship to household head [detailed version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 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's 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 Demographic Variables -- PERSON Age AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. 000 Less than 1 year 001 1 year 002 2 years 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100+ 999 Not reported/missing Demographic Variables -- PERSON Age, grouped into intervals AGE2 gives computed years of age grouped into intervals. 01 0 to 4 02 5 to 9 03 10 to 14 04 15 to 19 05 0 to 5 06 6 to 10 07 10 to 15 08 11 to 14 09 15 to 17 10 16 to 19 11 18 to 24 12 20 to 24 13 25 to 29 14 30 to 34 15 35 to 39 16 40 to 44 17 45 to 49 18 50 to 54 19 55 to 59 20 60 to 64 21 65 to 69 22 70 to 74 23 75 to 79 24 80 to 84 25 85+ 98 Unknown Demographic Variables -- PERSON Sex SEX reports the sex (gender) of the respondent. 1 Male 2 Female 9 Unknown Demographic Variables -- PERSON Marital status [general version] 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. 0 NIU (not in universe) 1 Single/never married 2 Married/in union 3 Separated/divorced/spouse absent 4 Widowed 9 Unknown/missing Demographic Variables -- PERSON Marital status [detailed version] 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. 000 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 219 Married, spouse absent (historical samples) 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 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 Demographic Variables -- PERSON Age at first marriage or union AGEMARR indicates the person's age at first marriage or consensual union. 00 NIU (not in universe) 10 10 or younger 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 Unknown Demographic Variables -- PERSON Year of first marriage MARRYR reports the year of first marriage. 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 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 Unknown 9999 NIU (not in universe) Demographic Variables -- PERSON Number of marriages or unions MARRNUM records the number of marital unions the respondent has ever been in. 0 NIU (not in universe) 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8+ 9 Unknown Demographic Variables -- PERSON Year of birth BIRTHYR gives the person's year of birth. 0000 NIU (not in universe) 1628 1628 1629 1629 1630 1630 1631 1631 1634 1634 1635 1635 1636 1636 1637 1637 1638 1638 1639 1639 1640 1640 1641 1641 1642 1642 1643 1643 1644 1644 1645 1645 1646 1646 1647 1647 1648 1648 1649 1649 1650 1650 1651 1651 1652 1652 1653 1653 1654 1654 1655 1655 1656 1656 1657 1657 1658 1658 1659 1659 1660 1660 1661 1661 1662 1662 1663 1663 1664 1664 1665 1665 1666 1666 1667 1667 1668 1668 1669 1669 1670 1670 1671 1671 1672 1672 1673 1673 1674 1674 1675 1675 1676 1676 1677 1677 1678 1678 1679 1679 1680 1680 1681 1681 1682 1682 1683 1683 1684 1684 1685 1685 1686 1686 1687 1687 1688 1688 1689 1689 1690 1690 1691 1691 1692 1692 1693 1693 1694 1694 1695 1695 1696 1696 1697 1697 1698 1698 1699 1699 1700 1700 1701 1701 1702 1702 1703 1703 1704 1704 1705 1705 1706 1706 1707 1707 1708 1708 1709 1709 1710 1710 1711 1711 1712 1712 1713 1713 1714 1714 1715 1715 1716 1716 1717 1717 1718 1718 1719 1719 1720 1720 1721 1721 1722 1722 1723 1723 1724 1724 1725 1725 1726 1726 1727 1727 1728 1728 1729 1729 1730 1730 1731 1731 1732 1732 1733 1733 1734 1734 1735 1735 1736 1736 1737 1737 1738 1738 1739 1739 1740 1740 1741 1741 1742 1742 1743 1743 1744 1744 1745 1745 1746 1746 1747 1747 1748 1748 1749 1749 1750 1750 1751 1751 1752 1752 1753 1753 1754 1754 1755 1755 1756 1756 1757 1757 1758 1758 1759 1759 1760 1760 1761 1761 1762 1762 1763 1763 1764 1764 1765 1765 1766 1766 1767 1767 1768 1768 1769 1769 1770 1770 1771 1771 1772 1772 1773 1773 1774 1774 1775 1775 1776 1776 1777 1777 1778 1778 1779 1779 1780 1780 1781 1781 1782 1782 1783 1783 1784 1784 1785 1785 1786 1786 1787 1787 1788 1788 1789 1789 1790 1790 1791 1791 1792 1792 1793 1793 1794 1794 1795 1795 1796 1796 1797 1797 1798 1798 1799 1799 1800 1800 1801 1801 1802 1802 1803 1803 1804 1804 1805 1805 1806 1806 1807 1807 1808 1808 1809 1809 1810 1810 1811 1811 1812 1812 1813 1813 1814 1814 1815 1815 1816 1816 1817 1817 1818 1818 1819 1819 1820 1820 1821 1821 1822 1822 1823 1823 1824 1824 1825 1825 1826 1826 1827 1827 1828 1828 1829 1829 1830 1830 1831 1831 1832 1832 1833 1833 1834 1834 1835 1835 1836 1836 1837 1837 1838 1838 1839 1839 1840 1840 1841 1841 1842 1842 1843 1843 1844 1844 1845 1845 1846 1846 1847 1847 1848 1848 1849 1849 1850 1850 1851 1851 1852 1852 1853 1853 1854 1854 1855 1855 1856 1856 1857 1857 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 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9999 Unknown Demographic Variables -- PERSON Month of birth BIRTHMO indicates the person's month of birth. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Children ever born 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. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 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) Fertility and Mortality Variables -- PERSON Children surviving CHSURV reports the number of children born to a woman who were still living at the time of the census. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 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) Fertility and Mortality Variables -- PERSON Month of last birth LASTBMO indicates the month of birth of the last child born by the respondent. The data refer to live births. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Year of last birth LASTBYR indicates the year of birth of the last child born by the respondent. The data refer to live births. 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 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 Unknown 9999 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of children dead CHDEAD reports how many of the children ever born to a woman were no longer living at the time of the census. Women were to consider all live births by all fathers; they were to exclude still births. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown/missing 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Mortality status of last birth LASTBMORT indicates the mortality status of the last child born to a woman. There is no constraint on how long ago the child may have been born. Only live births are considered. 0 NIU (not in universe) 1 Alive 2 Dead 9 Unknown Fertility and Mortality Variables -- PERSON Number of own children in household HOMECHILD indicates the number of surviving biological children living in the household with their mother (the respondent) at the time of the census. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own children living elsewhere AWAYCHILD indicates the number of surviving biological children not living in the household with their mother (the respondent) at the time of the census. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Nativity status NATIVITY indicates whether the person was native-born or foreign-born. 0 NIU (not in universe) 1 Native-born 2 Foreign-born 9 Unknown/missing Nativity and Birthplace Variables -- PERSON Citizenship CITIZEN indicates the person's citizenship status within the country in which they were enumerated. 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) Nativity and Birthplace Variables -- PERSON Country of citizenship NATION indicates the person's country of citizenship. 00000 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 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or 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, other or 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, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or 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 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 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 21220 St. Lucia 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21999 Caribbean, other or 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, other or 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 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24021 Canada, First Nations 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or 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, other or 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, other or 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, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 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 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 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 41992 Central-Eastern Europe 41999 Eastern Europe, other or 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 42121 Britain 42122 Scotland 42123 Wales 42990 Nordic countries 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 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, other or n.s. 44000 Western Europe 44010 Austria 44011 Austro-Hungarian 44020 Belgium 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44041 East Germany 44042 West Germany 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (Original 15) 49994 Other European Union 49999 Europe, other or n.s. 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, other or n.s. 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, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 90000 Other countries n.s. 99998 No citizenship/nationality 99999 Unknown Nativity and Birthplace Variables -- PERSON Province of birth, Indonesia BPLID indicates the person's province of birth within Indonesia. 11 Special Region of Aceh 12 North Sumatra 13 West Sumatra 14 Riau and Kepulauan Riau 15 Jambi 16 South Sumatra and Bangka Belitung 17 Bengkulu 18 Lampung 31 Special Capital Region of Jakarta 32 West Java and Banten 33 Central Java 34 Special Region of Jogyakarta 35 East Java 51 Bali 52 West Nusa Tenggara 53 East Nusa Tenggara 54 East Timor 61 West Kalimantan 62 Central Kalimantan 63 South Kalimantan 64 East Kalimantan 71 North Sulawesi and Gorontalo 72 Central Sulawesi 73 South Sulawesi and West Sulawesi 74 Southeast Sulawesi 81 Maluku and North Maluku 94 Papua and West Papua 98 Abroad 99 Unknown Nativity and Birthplace Variables -- PERSON Religion [general version] RELIGION indicates the person's religion, including "none." 0 NIU (not in universe) 1 No religion 2 Buddhist 3 Hindu 4 Jewish 5 Muslim 6 Christian 7 Other 9 Unknown Ethnicity and Language Variables -- PERSON Religion [detailed version] RELIGION indicates the person's religion, including "none." 0000 NIU (not in universe) 1000 No religion 1001 Atheist 1002 Agnostic 1003 Without religion 2000 Buddhist 3000 Hindu 4000 Jewish 5000 Muslim 5005 Ahmadis 5006 Sunni 6000 Christian 6001 Catholic (Roman or unspecified) 6002 Orthodox 6003 Protestant 6004 Evangelical protestant 6005 Pentecostal 6006 Adventist / Seventh-day adventist 6007 Anglican 6008 Assembly of God 6009 Baptist 6010 Church of the Nazarene 6011 Congregational 6012 Dutch Reformed 6013 Episcopalian 6014 Jehovah's Witnesses 6015 Latter Day Saints (Mormon) 6016 Lutheran 6017 Mennonite 6018 Methodist 6019 New Apostolic 6020 Presbyterian 6021 Zion Christian 6022 Moravian 6090 Other Christian, historical 6100 Other Christian, Armenia 6101 Armenia apostolic 6102 Nestorian 6103 Molokai 6104 Other Christian, Austria 6105 Old Catholic 6106 Protestant, Augsburg confession 6107 Protestant, Westminster confession 6108 Protestant, Helvetic confession 6109 Greek Oriental 6110 Armenian Apostolic 6111 Other Protestant 6112 Christian Community for renewal 6113 Christian Community, not specified 6114 Other Christian, Benin 6115 Other Christian 6116 Celestial 6117 Other Christian, Brazil 6118 Christian Congregation of Brazil 6119 Brazilian Catholic Apostolic 6120 Brazil for Christ 6121 Foursquare Gospel 6122 Universal of the Kingdom of God 6123 House of the Blessing 6124 House of Prayer 6125 God is Love 6126 Maranata 6127 Other Christian, Brazil 1991 6128 Undetermined Protestant 6129 Other traditional Protestant 6130 Neo-Christian 6131 Other Neo-Christian 6132 Undetermined Christian 6133 Other Christian, Brazil 2000 6134 Other Catholic 6135 Renewed Evangelical Protestant without institutional ties 6136 Pentecostal Evangelical without institutional ties 6137 New Life Evangelical Protestant Pentecostal 6138 Evangelical Protestant Biblical Revival Pentecostal 6139 Chain Of Prayer Pentecostal 6140 Undetermined Evangelical Protestant 6141 Religion Of God 6142 Christian without institutional ties 6143 Other Christian, Brazil 2010 6144 Salvation Army 6145 Other Christian, Canada 6146 Other Catholic 6147 United Church 6148 Protestant, not specified 6149 Other Protestant 6150 Other Christian, Cameroon 6151 Other Christian, Fiji 6152 Christian undefined 6153 Church of England 6154 Gospel Hall and Brethern 6155 Christian Mission Fellowship (CMF) or Every Home 6156 Salvation Army 6157 All Nations Christian Fellowship 6158 Apostles Gospel Outreach Fellowship 6159 Christian Outreach Centre 6160 Other Christian 6161 Other Christian, Germany 6162 Oriental Christian 6163 Other Christian, Ghana 6164 Other Christian, Iran 6165 Assyrian or Chaldean 6166 Armenian 6167 Other Christians 6168 Other Christian, Indonesia 6169 Other Christian 6170 Protestant/Other Christian 6171 Other Christian, Ireland 6172 Church of Ireland 6173 Church of Scotland 6174 Independent 6175 Unitarian 6176 Salvation Army 6177 Free Church 6178 Brethren 6179 Christian Brethren 6180 Plymouth Brethren 6181 Quaker 6182 Other Christians 6183 Other Christian, Ivory Coast 6184 Other Christian, Jamaica 6185 Brethren 6186 Church of God 6187 Church of God of Prophecy 6188 Other Church of God 6189 United Church 6190 Salvation Army 6191 New Testament 6192 Disciples of Christ 6193 Other Christian, Mauritius 6194 Christian Tamil 6195 Salvation and Healing Mission 6196 Voice of Deliverance 6197 Other Christian 6198 Other Christian, Mexico 6199 Anabaptist 6200 Calvinist 6201 Cuaquera 6202 Disciples of Christ 6203 Christian Friendship Church 6204 Prayer House Church 6205 Faith Center 6206 Agape Force Church 6207 Alpha and Omega Church 6208 Living Water Church 6209 Apostolic Church 6210 Church of God 6211 Church of God of Prophecy 6212 Complete Gospel Church 6213 Evangelical Siblings Church 6214 Upper Room Church 6215 Pentecostal Indigenous Church 6216 Angular Stone Voice Church 6217 Pentecostal Missionary 6218 Christian 6219 Christian Societies 6220 Evangelical 6221 Evangelical Societies 6222 New Testament Evangelical 6223 Pentecostal 6224 Pentecostal Societies 6225 Independent Pentecostal 6226 Evangelical Christian Societies 6227 Pentecostal Christian Societies 6228 Evangelical Pentecostal Societies 6229 Evangelical Pentecostal Christian Societies 6230 Soldiers of Christ's Cross Church 6231 Tabernacle 6232 Traditionalists 6233 Other Evangelical Pentecostal Societies 6234 Pentecostal not clearly specified 6235 Living God, Light of the World 6236 Christian and Missionary Alliance 6237 Non-Pentecostal Apostolic 6238 Evangelical Associations 6239 Biblical 6240 Confraternities 6241 Christ Church 6242 Peace Grace and Misericordia Church 6243 Open Bible Church 6244 Holiness Church 6245 Evangelical Salem Church 6246 Beautiful Woman Dressed in the Sun 6247 Messianic Church 6248 Evangelical Ministers 6249 Evangelical Missionaries 6250 Evangelical Movements 6251 New Jerusalem 6252 World Vision Church 6253 Evangelical not clearly specified 6254 Biblical - non-evangelicals 6255 Other Christians not clearly specified 6256 Assumptionist 6257 Carmelite 6258 Claretian 6259 Conception Franciscan 6260 Maronite Diocese of Mexico 6261 Dominican 6262 Servants of Mary Immaculate 6263 Franciscan 6264 Guadalupan 6265 Daughters of the Immaculate Conception 6266 Jesuit 6267 Legionaries of Christ 6268 Divine Word Missionary 6269 Pauline 6270 Sacred Heart 6271 Saint Joseph of Tarbes 6272 Servant of the Lord and the Virgin 6273 Servant of Jesus 6274 Greek Catholic Church 6275 Reformed Roman Catholic Church 6276 Mexican National Catholic Church 6277 Tridentine Latin Rite Catholic Church 6278 Priestly Society Trento 6279 Mexican Catholic Union of Trento 6280 Anabaptist / Memnonite 6281 Anglican / Episcopal 6282 House of Prayer 6283 Center of Faith, Hope and Love of the Missionary Revival Crusade 6284 Center of Faith, Hope and Love Agape Force 6285 Salvation Army 6286 Independent Pentecostal Fellowship 6287 Upper Chamber Church 6288 Faith Apostolic Church of Jesus Christ 6289 Spiritual Christian Church 6290 Pentecostal Evangelical Christian Church 6291 Interdenominational Christian Church 6292 Church of God Full Gospel in Mexico 6293 Church of Jesus Christ on the Rock 6294 Christ Evangelical Pentecostal Church Rock of my Salvation 6295 Mexican Church of Christ's Gospel Pentecost 6296 United Pentecostal Church of Mexico 6297 Universal Church of the Kingdom of God 6298 Only Christ Savior Christian Church 6299 Independent Evangelical Pentecostal Movement 6300 Prince of Peace 6301 National Union of Evangelical Christian Churches (UNICE) 6302 Union of Independent Evangelical Churches 6303 Other associations Pentecostal 6304 Church of the Living God, Pillar and Support of Truth, the Light of the World 6305 Bible Church 6306 Interdenominational Christian Church in Mexico 6307 Church of Christ 6308 Honey Church of Christ 6309 Independent Evangelical Church in Mexico 6310 Renewed Church of Jesus Christ and the Apostles of Divine Love 6311 Other Christian and Evangelical associations without Pentecostal support 6312 Faith Christian Church 6313 Traditional Apostolic Catholic Holy Church Mexico-USA 6314 Mexican Apostolic Catholic Church 6315 Elias 6316 Spiritualistic 6317 Spiritualist 6318 Marian Trinitarian Spirituality 6319 Spirituality of the Third Age 6320 Christian Spiritual 6321 Judiciary Society Reign of Leonardo Alcalá Leos 6322 Spirituality for the Divine Master and the purity of Mary 6323 Light and Hope 6324 Holy Spirit, Purity, Love and Light 6325 Christian Science 6326 Neo-Israelite Jewish Syncretic Movements 6327 Other Christian, Netherlands 6328 Reformed Churches in The Netherlands 6329 Other Reformed 6330 Other Christian, Papua New Guinea 6331 Asian Pacific Christian Mission 6332 Asutalian Church 6333 Bamu River Mission 6334 Christian Brethren Church of PNG 6335 Christian Mission of Many Lands 6336 Christian Revival Crusade 6337 Christain Union Mission 6338 Church of Christ of PNG 6339 Faith mission 6340 Four Square Gospel Mission 6341 Kwato Church 6342 Life Center 6343 Lighthouse church 6344 New Guinea Gospel Mission 6345 New Life Mission 6346 New tribes Mission 6347 Paliau Christian Native Church 6348 Rhema Fellowship 6349 Salvation Army 6350 Sovereign Grace 6351 United Church 6352 Wewak Fellowship 6353 Western Highland 6354 Independent 6355 Plymouth Brethern 6356 Tiliba Mission 6357 Tokarara Christian Fellowship 6358 Village Mission 6359 Other Christian 6360 Other Christian, Paraguay 6361 Christian Community 6362 Free Brothers 6363 Church of God 6364 Church of God of Prophecy 6365 New testament 6366 God is love 6367 Universal Church of the Kingdom of God 6368 People of God 6369 Family worship center 6370 Pseudo-Christian groups 6371 Other Christian, Philippines 6372 Aglipay 6373 Bible Christian Committees 6374 Born-again Christian 6375 Bread of Life Ministries 6376 Cathedral of Praise, Incorporated 6377 Charismatic Full Gospel Ministries 6378 Christ the Living Stone Fellowship 6379 Christian and Missionary Alliance 6380 Christians Missions 6381 Christian Reformed Church in the Philippines, Incorporated 6382 Church of Christ 6383 Crusaders of the Divine Church of Christ, Incorporated 6384 Evangelical Christian Outreach Foundation 6385 Evangelical Free Church 6386 Filipino Assemblies of the First Born Inc. 6387 Foursquare Gospel 6388 Free Believers in Christ Fellowship 6389 Free Mission in the Philippines Inc. 6390 God World Mission 6391 Good News Christian Churches 6392 IEMELIF Reform Movement 6393 Iglesia Evangelista Methodista en Las 6394 Iglesia Evangelica Unida de Cristo 6395 Iglesia ni Cristo 6396 Iglesia sa Dios Espiritu Santo, Incorporated 6397 Jesus Christ Saves Global Outreach 6398 Jesus is Alive Community, Incorporated 6399 Jesus is Lord Church 6400 Jesus Reigns Ministries 6401 Love of Christ International Ministries 6402 Other Evangelical 6403 Other Evangelical Church 6404 Other Protestants 6405 Philippine Ecumenical Christian Church 6406 Philippine Evangelical Mission 6407 Philippine Grace Gospel Fellowship 6408 Philippines Benevolent Missionaries 6409 Philippines General Council of the Assemblies of God 6410 Potter's House Christian Center 6411 Salvation Army Philippines 6412 Take the Nation for Jesus Global Ministries (Corpus Christi) 6413 UNIDA Evangelical Church 6414 Union Espiritista Cristiana de Filipinas, Incorporated 6415 United Church of Christ in the Philippines 6416 United Evangelical Church of the Philippines (Chinese) 6417 Victory Chapel Christian Fellowship 6418 Wesleyan Church 6419 World Missionary Evangelism 6420 Worldwide Church of God 6421 Zion Christian Community Church 6422 Other Christian, Portugal 6423 Other Christian, Romania 6424 Greek Catholic 6425 Reformed Church 6426 Evangelic of Augustan Confession 6427 Evangelic Synodo-Presbyterian 6428 Christian of Old Rite 6429 Christian by Gospel 6430 Evangelic 6431 Other Christian, Rwanda 2002 6432 Other Christian, Sierra Leone 6433 Other Christian, Slovak Republic 6434 Old Catholic 6435 Greek Catholic 6436 Christian Reformed 6437 Other Christian, South Africa 6438 Reformed 6439 International Fellowship of Christian Churches 6440 Apostolic Faith Mission of SA 6441 Other Apostolic Churches 6442 Pinkster Protestant Church 6443 Afrikaanse Protestant Church 6444 Full Gospel Church of God in Southern Africa 6445 Pentecostal Churches 6446 Salvation Army 6447 Bandla Lama Nazaretha 6448 African Methodist Episcopal Church 6449 St John's Apostolic Church 6450 International Pentecost Church 6451 Ethiopian type churches 6452 Ethnic churches 6453 Other African Independent Churches 6454 Other Christian Churches 6455 Other Catholic Churches 6456 Other Pentecostal Churches 6457 Other Orthodox Churches 6458 Other African Apostolic churches 6459 Other Assemblies 6460 Christian Scientist 6461 Christian Centres 6462 Other Evangelical Churches 6463 Other Charismatic Churches 6464 Just a Christian or non-denominational 6465 Other 6466 Other Christian, Suriname 6467 Other Christian 6468 Other Christian, Saint Lucia 6469 Church of God 6470 Other Christian, Senegal 6471 Other Christian 6472 Other Christian, Switzerland 6473 Other protestant churches and communities 6474 Christ-Catholic church 6475 Other Christian communities 6476 Other Christian, Trinidad and Tobago 6477 Church of God 6478 African Methodist Espiscopalians 6479 Brethren, Christian or Plymouth 6480 Church of Christ 6481 Gospel Hall or Gospel Missionary 6482 Nazarenes 6483 Pilgrim Holiness 6484 Ethiopian Orthodox 6485 Open Bible Church 6486 Assemblies of Yahweh 6487 Evangelical Church of West Indies 6488 Christadelphian 6489 Full Gospel Fellowship 6490 Dutch Reform 6491 Christian Brotherhood Assembly 6492 Other Christian, Uganda 6493 Other Christian 6494 Salvation Army 6495 Other Christian non-Catholic, Uruguay 6496 Other Christian non-Catholic, Guatemala 6497 Other Christian, Togo 7000 Other 7001 Bahai 7002 Sikh 7003 Rastafarian 7100 Other, Armenia 7101 Pagan 7102 Shar-fadinian 7103 Other, Austria 7104 Unification Church, Austria 7105 Other, Benin 7106 Traditional 7107 Vodoun 7108 Other, Botswana 7109 Badimo 7110 Other, Brazil 7111 Spiritist 7112 Kardecist Spiritist 7113 Afro Spiritist 7114 Mediumistic Spiritist 7115 Umbandist Mediumistic 7116 Candomblecist Mediumistic 7117 Other Afro-Brazilian 7118 Oriental, Brazil 7119 New Oriental 7120 Oriental Seicho No-le 7121 Other Oriental, Brazil 7122 Esoteric, Brazil 7123 Indigenous, Brazil 7124 Other minority groups, Brazil 7125 Other, Burkina Faso 7126 Animist 7127 Other, Cameroon 7128 Animist 7129 Other, Canada 7130 Eastern religions, Canada 7131 Other, Chile 7132 Theosophism 7133 Shintoism 7134 Other, Ethiopia 7135 Traditional 7136 Other, Ethiopia 7137 Other, Fiji 7138 Confucian 7139 Kabir Panthi 7140 Satya Sai Baba 7141 Bahai 7142 Other non-Christian, Fiji 7143 Other, Germany 7144 Other, Germany 7145 Other, Ghana 7146 Traditional, Ghana 7147 Other, Guinea 7148 Animist 7149 Other, Guinea 7150 Other, Haiti 7151 Voodoo 7152 Other, India 7153 Jainism 7154 Zoroastrianism 7155 Other, India 7156 Other, Indonesia 7157 Confucianism 7158 Other, Indonesia 7159 Other, Iran 7160 Zoroastrian 7161 Other, Iran 7162 Other, Ivory Coast 7163 Animist 7164 Harrist 7165 Other, Jamaica 7166 Muslim/Hindu 7167 Other, Israel 7168 Druse 7169 Other, Israel 7170 Other, Laos 7171 Animist 7172 Other, Liberia 7173 Traditional 7174 Other, Malaysia 7175 Confucianism/Taoism 7176 Tribal/Folk religion, Malaysia 7177 Other, Mali 7178 Animist 7179 Other, Mexico 7180 Brahmanism 7181 Hare Krishna 7182 Shintoism 7183 Taoism 7184 Mexican Movements 7185 Ananda Marga 7186 Church of Scientology 7187 Masons 7188 Raelian Movement 7189 New Age Movement 7190 Neoisraelites 7191 Occultists 7192 Palmar of Troya 7193 Rose Cross 7194 Theosophism 7195 Spiritualist Special Keys 7196 Onkaranada Center 7197 Confucianism 7198 Shia 7199 Universal Great Brotherhood 7200 Esoteric Science 7201 Gnosticism 7202 Metaphysics 7203 Wicca 7204 Shamanism 7205 The Custom 7206 Mexicayotl 7207 Restorative Confederate Movement of Anahuac Culture 7208 African Origin 7209 Indigenous Religions 7210 Growing in Grace 7211 Eckankar 7212 Transcendental Meditation 7213 Mission Branch 7214 Children of God 7215 Sri Sathya Sai Baba 7216 Other religions from Asia 7217 Ethnic roots 7218 Afro roots 7219 Popular cults 7220 Other new religious movements 7221 Other, Nepal 7222 Kirat 7223 Jain 7224 Garaute 7225 Tap jura 7226 Bon 7227 Prakriti 7228 Other, Nigeria 7229 Traditional 7230 Other, Pakistan 7231 Ahmadi 7232 Parsi 7233 Scheduled caste 7234 Other, Paraguay 7235 Philosophical revelations 7236 Indigenous religion 7237 Reyukai 7238 Other, Paraguay 7239 Other, Philippines 7240 Door of Faith 7241 Faith Tabernacle Church (Living Rock Ministries) 7242 Iglesia Filipina Independiente 7243 International One Way Outreach 7244 Miracle Life Fellowship International 7245 Miracle Revival Church of the Philippines 7246 Philippine Good News Ministries 7247 Philippine Missionary fellowship 7248 Things to Come 7249 Way of Salvation 7250 Word of the World 7251 Word International Ministries 7252 Tribal Religions, Philippines 7253 Other, Romania 7254 Unitarian 7255 Armenian 7256 Mosaic 7257 Other, Romania 7258 Other, Rwanda 7259 Traditional religion, Rwanda 7260 Other, Rwanda 7261 Other, Sierra Leone 7262 Traditional religion, Sierra Leone 7263 Other, South Africa 7264 African traditional belief 7265 Taoist 7266 Confucian 7267 New Age 7268 Winti 7269 Javanism 7270 Other non-Christian, S. Africa 7271 Other, Suriname 7272 Javanism 7273 Traditional 7274 Winti 7275 Other, Thailand 7276 Confucian 7277 Other, Trinidad and Tobago 7278 Pocamania or Shango 7279 Orisha 7280 Other, Uganda 7281 Traditional religion 7282 Mammon 7283 Other non-Christian, Uganda 7284 Other, United Kindom 7285 Other, Uruguay 7286 Umbanda/other Afro-American 7287 Other, Uruguay 7288 Other, Vietnam 7289 Cao Dai 7290 Cham Brahmin 7296 Other, Togo 7297 Animist 7900 Other, not elsewhere classified 9999 Unknown Ethnicity and Language Variables -- PERSON Language spoken at home, Indonesia LANGID indicates the language or spoken by the respondent at home. 1 Indonesian 2 Local language 3 Foreign 8 Unknown 9 NIU (not in universe) Ethnicity and Language Variables -- PERSON School attendance SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census. 0 NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing Education Variables -- PERSON Literacy 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. 0 NIU (not in universe) 1 No, illiterate 2 Yes, literate 9 Unknown/missing Education Variables -- PERSON Educational attainment, international recode [general version] 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. 0 NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown Education Variables -- PERSON Educational attainment, international recode [detailed version] 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. 000 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 Education Variables -- PERSON Years of schooling YRSCHOOL indicates the highest grade/level of schooling the person had completed, in years. Only formal schooling is counted. YRSCHOOL accounts for the number of years of study, regardless of the track or kind of study. Information on degree and/or technical track is available in EDATTAIN. Years of schooling for Israel, categorized into intervals, are given in YRSCHOOL2. Users should pay close attention to the top-codes in each sample, as discussed in the comparability section. 00 None or pre-school 01 1 year 02 2 years 03 3 years 04 4 years 05 5 years 06 6 years 07 7 years 08 8 years 09 9 years 10 10 years 11 11 years 12 12 years 13 13 years 14 14 years 15 15 years 16 16 years 17 17 years 18 18 years or more 90 Not specified 91 Some primary 92 Some technical after primary 93 Some secondary 94 Some tertiary 95 Adult literacy 96 Special education 98 Unknown/missing 99 NIU (not in universe) Education Variables -- PERSON Educational attainment, Indonesia EDUCID indicates the person's educational attainment in Indonesia in terms of the level of schooling completed. 000 NIU (not in universe) 010 None 011 No schooling or primary not completed 020 Preschool 021 Preschool, not completed 022 Preschool, completed 030 Primary education (6 years) 031 Primary education (6 years), grade 1 032 Primary education (6 years), grade 2 033 Primary education (6 years), grade 3 034 Primary education (6 years), grade 4 035 Primary education (6 years), grade 5 036 Primary education (6 years), grade 6 037 Primary education (6 years), grade unknown 038 Primary education (6 years), not completed 039 Primary education (6 years), completed 040 Primary education (3 years) 041 Primary education (3 years), grade 1 042 Primary education (3 years), grade 2 043 Primary education (3 years), grade 3 044 Primary education (3 years), completed 050 Junior high school 051 Junior high school, grade 1 052 Junior high school, grade 2 053 Junior high school, grade 3 054 Junior high school, grade unknown 055 Junior high school, completed 060 Junior vocational school 061 Junior vocational school, grade 1 062 Junior vocational school, grade 2 063 Junior vocational school, grade 3 064 Junior vocational school, grade unknown 065 Junior vocational school, completed 070 Senior high school 071 Senior high school, grade 1 072 Senior high school, grade 2 073 Senior high school, grade 3 074 Senior high school, grade unknown 075 Senior high school, completed 080 Senior vocational school 081 Senior vocational school, grade 1 082 Senior vocational school, grade 2 083 Senior vocational school, grade 3 084 Senior vocational school, grade unknown 086 Senior vocational school, completed 090 Diploma I/II 091 Diploma I/II, year 1 092 Diploma I/II, year 2 093 Diploma I/II, completed 100 Academy/Diploma III 101 Academy/Diploma III, year 1 102 Academy/Diploma III, year 2 103 Academy/Diploma III, year 3 104 Academy/Diploma III, year 4 105 Academy/Diploma III, year unknown 106 Academy/Diploma III, completed 110 University/Diploma IV 111 University/Diploma IV, year 1 112 University/Diploma IV, year 2 113 University/Diploma IV, year 3 114 University/Diploma IV, year 4 115 University/Diploma IV, year 5 116 University/Diploma IV, year 6 117 University/Diploma IV, year 7 118 University/Diploma IV, year unknown 119 University/Diploma IV, completed 120 Graduate school 121 Graduate school, not completed 122 Graduate school, completed 123 Masters 124 Doctoral program 998 Unknown Education Variables -- PERSON Activity status (employment status) [general version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 0 NIU (not in universe) 1 Employed 2 Unemployed 3 Inactive 9 Unknown/missing Work Variables -- PERSON Activity status (employment status) [detailed version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 000 NIU (not in universe) 100 Employed, not specified 110 At work 111 At work, and 'student' 112 At work, and 'housework' 113 At work, and 'seeking work' 114 At work, and 'retired' 115 At work, and 'no work' 116 At work, and other situation 117 At work, family holding, not specified 118 At work, family holding, not agricultural 119 At work, family holding, agricultural 120 Have job, not at work in reference period 130 Armed forces 131 Armed forces, at work 132 Armed forces, not at work in reference period 133 Military trainee 140 Marginally employed 200 Unemployed, not specified 201 Unemployed 6 or more months 202 Worked fewer than 6 months, permanent job 203 Worked fewer than 6 months, temporary job 210 Unemployed, experienced worker 220 Unemployed, new worker 230 No work available 240 Inactive unemployed 300 Inactive (not in labor force) 301 Unavailable jobseekers 302 Available potential jobseekers 310 Housework 320 Health reasons, unable to work, or disabled 321 Permanent disability 322 Temporary illness 323 Disabled or imprisoned 330 In school 340 Retirees and living on rent 341 Living on rents 342 Living on rents or pension 343 Retirees/pensioners 344 Retired 345 Pensioner 346 Non-retirement pension 347 Disability pension 348 Retired without benefits 350 Elderly 351 Elderly or disabled 360 Institutionalized 361 Prisoner 370 Intermittent worker 371 Not working, seasonal worker 372 Not working, occasional worker 380 Other income recipient 390 Inactive, other reasons 391 Too young to work 392 Dependent 999 Unknown/missing Work Variables -- PERSON Labor force participation LABFORCE is a dichotomous variable identifying whether a person participated in the labor force. Labor force participation generally means working or seeking work within a specified reference period. For most samples LABFORCE is a recode of EMPSTAT (employment status). A consistent lower age universe of 15 or older has been applied to increase comparability across samples. Full detail is retained in EMPSTAT, which should be used for any study of child labor. 1 No, not in the labor force 2 Yes, in the labor force 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Occupation, ISCO general OCCISCO records the person's primary occupation, coded according to the major categories in the International Standard Classification of Occupations (ISCO) scheme for 1988. For someone with more than one job, the primary occupation is typically the one in which the person had spent the most time or earned the most money. 01 Legislators, senior officials and managers 02 Professionals 03 Technicians and associate professionals 04 Clerks 05 Service workers and shop and market sales 06 Skilled agricultural and fishery workers 07 Crafts and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 10 Armed forces 11 Other occupations, unspecified or n.e.c. 97 Response suppressed 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Occupation, unrecoded OCC records the person's primary occupation, classified according to the system used by the respective national census office at the time. For someone with more than one job, the primary occupation is usually the one in which the person spent the most time or earned the most money, although this may not have been explicit in the instructions for a specific census. To ensure confidentiality, very small occupations are recoded to a residual category indicating the persons had an occupation, but the job title is not identified. The number of cases recoded should be too small to affect analyses. OCC is a 4-digit numeric variable. Some samples use fewer than 4 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_OCC3 - Occupation [3 digit] Argentina 1980 - see Variable: AR1980A_OCC - Occupation Argentina 1991 - see Variable: AR1991A_OCC - Occupation Argentina 2001 - see Variable: AR2001A_OCC4 - Occupation (4-digits) Armenia 2011 - see Variable: AM2011A_OCC - Occupation Austria 1971 - see Variable: AT1971A_OCCSM - Occupation of supporter: sub-major groups Austria 1981 - see Variable: AT1981A_OCCSM - Occupation of supporter: sub-major groups Austria 1991 - see Variable: AT1991A_OCCSM - Occupation of supporter: sub-major groups Austria 2001 - see Variable: AT2001A_OCCSM - Occupation of supporter: sub-major groups Belarus 1999 - see Variable: BY1999A_OCC2 - Occupation, 2 digits Belarus 2009 - see Variable: BY2009A_OCC - Occupation Benin 1979 - see Variable: BJ1979A_OCC - Occupation (2-digits) Benin 1992 - see Variable: BJ1992A_OCC3 - Occupation (3-digits) Benin 2002 - see Variable: BJ2002A_OCC - Occupation (3-digits) Benin 2013 - see Variable: BJ2013A_OCC - Occupation (3-digit) Bolivia 1976 - see Variable: BO1976A_OCC2 - Occupation, 2 digits Bolivia 1992 - see Variable: BO1992A_OCC - Occupation Bolivia 2001 - see Variable: BO2001A_OCC - Occupation, 3 digits Bolivia 2012 - see Variable: BO2012A_OCC2 - Occupation (3 digit) Botswana 1981 - see Variable: BW1981A_OCC - Occupation Botswana 1991 - see Variable: BW1991A_OCC - Occupation (last 30 days) Botswana 2001 - see Variable: BW2001A_OCC - Occupation in the past 7 days, 3 digit Botswana 2011 - see Variable: BW2011A_OCC - Occupation, 3-digits Brazil 1960 - see Variable: BR1960A_USUALOCC - Usual occupation Brazil 1970 - see Variable: BR1970A_MAINOCC - Principal occupation Brazil 1980 - see Variable: BR1980A_OCC - Occupation Brazil 1991 - see Variable: BR1991A_OCC - Occupation Brazil 2000 - see Variable: BR2000A_OCC - Occupation, 4 digits Brazil 2010 - see Variable: BR2010A_OCC - Occupation held from July 25 to July 31, 2010 Burkina Faso 1985 - see Variable: BF1985A_OCC - Principal occupation Burkina Faso 1996 - see Variable: BF1996A_OCC - Principal occupation Cambodia 1998 - see Variable: KH1998A_OCC - Occupation Cambodia 2004 - see Variable: KH2004A_OCC3 - Occupation (3-digits) Cambodia 2008 - see Variable: KH2008A_OCC - Occupation Cambodia 2013 - see Variable: KH2013A_OCC - Occupation (3-digits) Cambodia 2019 - see Variable: KH2019A_OCC1 - Occupation, 1-digit Cameroon 1976 - see Variable: CM1976A_OCC2 - Occupation (2 digits) Cameroon 2005 - see Variable: CM2005A_OCC - Occupation Canada 1971 - see Variable: CA1971A_OCC - Occupation Canada 1981 - see Variable: CA1981A_OCC - Occupation (1981 classification basis) Canada 1991 - see Variable: CA1991A_OCC80 - Occupation (1980 classification basis) Canada 2001 - see Variable: CA2001A_NOCS01P - Occupation (2001 national occupational classification for statistics) Canada 2011 - see Variable: CA2011A_OCC - Occupation Chile 1960 - see Variable: CL1960A_OCC - Occupation Chile 1970 - see Variable: CL1970A_OCC3 - Occupation (3-digit) Chile 1982 - see Variable: CL1982A_OCC3 - Occupation (3-digit) Chile 1992 - see Variable: CL1992A_OCC3 - Occupation (3-digit) Chile 2002 - see Variable: CL2002A_OCC - Occupation China 1982 - see Variable: CN1982A_OCC - Occupation China 1990 - see Variable: CN1990A_OCC - Occupation China 2000 - see Variable: CN2000A_OCC - Occupation (2-digit) Colombia 1964 - see Variable: CO1964A_OCC2 - Occupation (COTA, 4 digits) Colombia 1973 - see Variable: CO1973A_OCC - Occupation last week Costa Rica 1973 - see Variable: CR1973A_OCC3 - Occupation, 3 digits Costa Rica 1984 - see Variable: CR1984A_OCC - Occupation, 3 digits Costa Rica 2000 - see Variable: CR2000A_OCC3 - Occupation, 3 digits Costa Rica 2011 - see Variable: CR2011A_OCC - Occupation, 2-digit Cuba 2002 - see Variable: CU2002A_OCC - Occupation Cuba 2012 - see Variable: CU2012A_OCC3 - Main occupation (3-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_OCC2 - Current occupation (2-digit) Dominican Republic 1960 - see Variable: DO1960A_OCC - Occupation Dominican Republic 1970 - see Variable: DO1970A_OCC1 - Current occupation, 3 digits Dominican Republic 1981 - see Variable: DO1981A_OCC - Occupation Dominican Republic 2002 - see Variable: DO2002A_OCC - Occupation Dominican Republic 2010 - see Variable: DO2010A_OCC - Occupation Ecuador 1962 - see Variable: EC1962A_OCC - Occupation Ecuador 1974 - see Variable: EC1974A_OCC3 - Occupation, three digits Ecuador 1982 - see Variable: EC1982A_OCC3 - Occupation, 3 digits Ecuador 1990 - see Variable: EC1990A_OCC3 - Occupation, 3 digits Ecuador 2001 - see Variable: EC2001A_OCC - Occupation, 3 digits Ecuador 2010 - see Variable: EC2010A_OCC3 - Occupation (3 digits, ISCO 08) Egypt 1986 - see Variable: EG1986A_OCC3 - Occupation (3-digit) Egypt 2006 - see Variable: EG2006A_OCC - Primary occupation, 3-digit El Salvador 1992 - see Variable: SV1992A_OCC - Occupation (3-digit) El Salvador 2007 - see Variable: SV2007A_OCC3DIG - Occupation (3-digit) Ethiopia 1984 - see Variable: ET1984A_OCC2 - Occupation (2-digit) Ethiopia 1994 - see Variable: ET1994A_OCC - Occupation Fiji 1976 - see Variable: FJ1976A_OCC - Occupation Fiji 1986 - see Variable: FJ1986A_OCC - Occupation Fiji 1996 - see Variable: FJ1996A_OCC3 - Occupation (3 digits) Fiji 2007 - see Variable: FJ2007A_OCC3 - Occupation, 3 digits Fiji 2014 - see Variable: FJ2014A_OCC3 - Occupation (3 digits) Finland 2010 - see Variable: FI2010A_OCC - Occupation France 1962 - see Variable: FR1962A_SOCCUP - SAPHIR occupation France 1968 - see Variable: FR1968A_SOCC - SAPHIR occupation France 1975 - see Variable: FR1975A_SOCC - SAPHIR occupation France 1982 - see Variable: FR1982A_SOCC - SAPHIR occupation France 1990 - see Variable: FR1990A_SOCC - Saphir occupation France 1999 - see Variable: FR1999A_OCC - Occupation, ISCO France 2006 - see Variable: FR2006A_PROF486 - Detailed profession (4-digit) France 2011 - see Variable: FR2011A_PROF - Profession, 486 categories Germany 1970 - see Variable: DE1970A_OCC - Occupation Germany 1981 - see Variable: DE1981A_OCC - Occupation Germany 1987 - see Variable: DE1987A_OCC - Occupation Ghana 1984 - see Variable: GH1984A_OCC2 - Occupation, 2 digits Ghana 2000 - see Variable: GH2000A_OCC - Occupation Ghana 2010 - see Variable: GH2010A_OCC - Occupation (major groups) Greece 1971 - see Variable: GR1971A_OCC - Occupation Greece 1981 - see Variable: GR1981A_OCC - Occupation Greece 1991 - see Variable: GR1991A_OCC - Occupation Greece 2001 - see Variable: GR2001A_OCC - Occupation Greece 2011 - see Variable: GR2011A_OCC - Occupation Guatemala 1964 - see Variable: GT1964A_OCC3 - Occupation (3-digits) Guatemala 1973 - see Variable: GT1973A_OCC3 - Principal occupation (3-digits) Guatemala 1981 - see Variable: GT1981A_OCC3 - Principal occupation (3-digits) Guatemala 1994 - see Variable: GT1994A_OCC - Principal occupation (1-digit) Guatemala 2002 - see Variable: GT2002A_OCC3 - Principal occupation (3-digits) Guinea 1983 - see Variable: GN1983A_OCC2 - Occupation, 2 digits Guinea 1996 - see Variable: GN1996A_OCC - Occupation Guinea 2014 - see Variable: GN2014A_OCC - Occupation (3-digit) Haiti 1982 - see Variable: HT1982A_OCC - Main occupation or profession Haiti 2003 - see Variable: HT2003A_OCC2 - Occupation, 3 digits Honduras 1961 - see Variable: HN1961A_OCC - Occupation (2-digits) Honduras 1974 - see Variable: HN1974A_OCC2 - Occupation (3-digits) Honduras 1988 - see Variable: HN1988A_OCC4 - Occupation (4-digits) Honduras 2001 - see Variable: HN2001A_OCC - Occupation (4-digit) Honduras 2013 - see Variable: HN2013A_OCC3 - Occupation (3-digit) Hungary 1970 - see Variable: HU1970A_OCC - Occupation Hungary 1980 - see Variable: HU1980A_OCC - Occupation, scope of activity Hungary 1990 - see Variable: HU1990A_OCC - Occupation Hungary 2001 - see Variable: HU2001A_OCC - Occupation Hungary 2011 - see Variable: HU2011A_OCC - Occupation Indonesia 1971 - see Variable: ID1971A_OCC - Occupation Indonesia 1976 - see Variable: ID1976A_OCC - Primary occupation during past week Indonesia 1980 - see Variable: ID1980A_OCC - Primary occupation during the previous week (3 digit version) Indonesia 1985 - see Variable: ID1985A_OCC - Primary occupation Indonesia 1990 - see Variable: ID1990A_OCC - Main occupation last week Indonesia 1995 - see Variable: ID1995A_OCC - Occupation Indonesia 2005 - see Variable: ID2005A_OCC - Occupation Iran 2006 - see Variable: IR2006A_OCC4 - Occupation Iran 2011 - see Variable: IR2011A_OCC - Occupation (3-digit) Iraq 1997 - see Variable: IQ1997A_OCC - Occupation Ireland 1971 - see Variable: IE1971A_OCC - Occupation Ireland 1981 - see Variable: IE1981A_OCC - Occupation Ireland 1986 - see Variable: IE1986A_OCC - Occupation group Ireland 1991 - see Variable: IE1991A_OCC - Occupation group Ireland 1996 - see Variable: IE1996A_OCC - Occupation Ireland 2002 - see Variable: IE2002A_OCC - Occupation Ireland 2006 - see Variable: IE2006A_OCC - Occupation group Ireland 2011 - see Variable: IE2011A_OCC - Occupation (shuffled) Ireland 2016 - see Variable: IE2016A_OCC - Occupation (groups) Israel 1972 - see Variable: IL1972A_OCC - Occupation Israel 1983 - see Variable: IL1983A_OCC - Occupation Israel 1995 - see Variable: IL1995A_OCC - Occupation Israel 2008 - see Variable: IL2008A_OCC - Occupation Italy 2001 - see Variable: IT2001A_OCC - Occupation Italy 2011 - see Variable: IT2011A_WKTYPE - Type of work Jamaica 1982 - see Variable: JM1982A_OCC - Occupation during past week / in last job Jamaica 1991 - see Variable: JM1991A_OCC - Occupation during past week/in last job Jamaica 2001 - see Variable: JM2001A_OCC3 - Occupation 3-digit Jordan 2004 - see Variable: JO2004A_OCC3 - Major current occupation (3-digit) Kenya 1989 - see Variable: KE1989A_OCC4 - Occupation, 4 digits Kenya 2019 - see Variable: KE2019A_OCC3 - Occupation (3-digit) Kyrgyzstan 1999 - see Variable: KG1999A_OCC - Main activity Laos 1995 - see Variable: LA1995A_OCC1 - Main occupation in the last 12 months (1-digit) Lesotho 1996 - see Variable: LS1996A_OCC - Occupation (2-digits) Lesotho 2006 - see Variable: LS2006A_OCC - Occupation (2-digits) Liberia 1974 - see Variable: LR1974A_OCC2 - Occupation (2-digit) Liberia 2008 - see Variable: LR2008A_OCC - Occupation Malawi 1987 - see Variable: MW1987A_OCC2 - Occupation, 2 digit Malawi 1998 - see Variable: MW1998A_OCC2 - Occupation, 2-digit Malawi 2008 - see Variable: MW2008A_OCC2 - Occupation (2 digits) Malawi 2018 - see Variable: MW2018A_OCC1 - Main occupation (1-digit) Malaysia 1970 - see Variable: MY1970A_OCC - Occupation last week Malaysia 1980 - see Variable: MY1980A_OCC3 - Principal occupation last week (3 digits) Malaysia 1991 - see Variable: MY1991A_OCC3 - Principal occupation (3 digits) Malaysia 2000 - see Variable: MY2000A_OCC3 - Occupation -- 3 digits Mali 1987 - see Variable: ML1987A_OCC - Occupation last month Mali 1998 - see Variable: ML1998A_OCC - Main occupation Mali 2009 - see Variable: ML2009A_OCC - Principal occupation Mauritius 1990 - see Variable: MU1990A_OCC3 - Occupation (3-digit) Mauritius 2000 - see Variable: MU2000A_OCC4 - Occupation (4 digit) Mauritius 2011 - see Variable: MU2011A_OCC4 - Occupation (4-digit) Mexico 1960 - see Variable: MX1960A_OCC2 - Principal occupation, 2 digits Mexico 1970 - see Variable: MX1970A_OCC3 - Occupation 3 digit Mexico 1990 - see Variable: MX1990A_OCC - Occupation, 4 digits Mexico 1995 - see Variable: MX1995A_OCC - Occupation Mexico 2000 - see Variable: MX2000A_OCC4 - Occupation, 4 digits Mexico 2010 - see Variable: MX2010A_OCC - Occupation or trade Mexico 2015 - see Variable: MX2015A_OCC - Occupation Mexico 2020 - see Variable: MX2020A_OCC3 - Occupation (3-digits) Mongolia 2000 - see Variable: MN2000A_OCC - Occupation Mongolia 2010 - see Variable: MN2010A_OCC3 - Occupation 3 digits (ISCO-2008) Mongolia 2020 - see Variable: MN2020A_OCC3 - Occupation (3-digit) Morocco 1982 - see Variable: MA1982A_OCC3 - Occupation (3-digit) Morocco 1994 - see Variable: MA1994A_OCC3 - Occupation, 3-digit Morocco 2004 - see Variable: MA2004A_OCC3 - Occupation (3-digit) Morocco 2014 - see Variable: MA2014A_OCC2 - Occupation (2-digit) Mozambique 1997 - see Variable: MZ1997A_OCC2 - Occupation 3-digit Mozambique 2007 - see Variable: MZ2007A_OCC - Occupation Mozambique 2017 - see Variable: MZ2017A_OCC3 - Main occupation (3-digits ISCO 2008) Myanmar 2014 - see Variable: MM2014A_OCC - Occupation Nepal 2001 - see Variable: NP2001A_OCC - Usual occupation Nepal 2011 - see Variable: NP2011A_OCC1 - Occupation (1-digit) Netherlands 1960 - see Variable: NL1960A_OCC - Occupation Netherlands 1971 - see Variable: NL1971A_OCC - Occupation Netherlands 2001 - see Variable: NL2001A_OCC - Occupation Netherlands 2011 - see Variable: NL2011A_OCC - Occupation (1-digit) Nicaragua 1971 - see Variable: NI1971A_OCC - Occupation Nicaragua 1995 - see Variable: NI1995A_OCC - Occupation (ISCO 88, 3 digits) Nicaragua 2005 - see Variable: NI2005A_OCC3 - Occupation (ISCO 88, 3 digits) Pakistan 1973 - see Variable: PK1973A_OCC3 - Occupation Palestine 1997 - see Variable: PS1997A_OCC - Main occupation Palestine 2007 - see Variable: PS2007A_OCC - Main occupation Palestine 2017 - see Variable: PS2017A_OCC - Occupation Panama 1960 - see Variable: PA1960A_OCC4 - Occupation (4-digit) Panama 1970 - see Variable: PA1970A_OCC2 - Occupation, 2-digit Panama 1980 - see Variable: PA1980A_OCC2 - Occupation (3-digit) Panama 1990 - see Variable: PA1990A_OCC - Occupation Panama 2000 - see Variable: PA2000A_OCC - Occupation Panama 2010 - see Variable: PA2010A_OCC - Occupation, 3 digits Papua New Guinea 1980 - see Variable: PG1980A_OCC - Occupation, 3 digits Papua New Guinea 1990 - see Variable: PG1990A_OCC - Occupation Papua New Guinea 2000 - see Variable: PG2000A_OCC - Occupation (4-digit) Paraguay 1962 - see Variable: PY1962A_OCC1 - Occupation (1-digit) Paraguay 1972 - see Variable: PY1972A_OCC3 - Occupation (3 digits) Paraguay 1982 - see Variable: PY1982A_OCC3 - Occupation, 3-digits Paraguay 1992 - see Variable: PY1992A_OCC2 - Main occupation, 3 digits Paraguay 2002 - see Variable: PY2002A_OCC - Occupation (4 digits) Peru 1993 - see Variable: PE1993A_OCC - Occupation (3 digits) Peru 2007 - see Variable: PE2007A_OCC - Main occupation last week (3 digits) Peru 2017 - see Variable: PE2017A_OCC1 - Occupation (1-digit, in primary job last week) Philippines 1990 - see Variable: PH1990A_OCC - Occupation Philippines 2000 - see Variable: PH2000A_OCC - Occupation Philippines 2010 - see Variable: PH2010A_OCC3 - Usual occupation (3-digit) Poland 1978 - see Variable: PL1978A_OCC - Occupation Poland 1988 - see Variable: PL1988A_OCC - Main occupation Poland 2002 - see Variable: PL2002A_OCC - Occupation Portugal 1981 - see Variable: PT1981A_OCC - Main occupation Portugal 1991 - see Variable: PT1991A_OCC - Main occupation Portugal 2001 - see Variable: PT2001A_OCC - Main occupation Portugal 2011 - see Variable: PT2011A_OCC - Main occupation Puerto Rico 1970 - see Variable: PR1970A_OCC - Occupation Puerto Rico 1980 - see Variable: PR1980A_OCC - Occupation Puerto Rico 1990 - see Variable: PR1990A_OCC - Occupation Puerto Rico 2000 - see Variable: PR2000A_OCC - Occupation Puerto Rico 2005 - see Variable: PR2005A_OCC - Occupation Puerto Rico 2010 - see Variable: PR2010A_OCC - Occupation Puerto Rico 2015 - see Variable: PR2015A_OCC - Occupation last week Puerto Rico 2020 - see Variable: PR2020A_OCC2010 - Occupation last week, 2010 basis Romania 1992 - see Variable: RO1992A_OCC - Occupation Romania 2002 - see Variable: RO2002A_OCC4 - Occupation, 4 digits Romania 2011 - see Variable: RO2011A_OCC - Occupation (unrecoded) Rwanda 2002 - see Variable: RW2002A_OCC - Occupation Rwanda 2012 - see Variable: RW2012A_OCC2 - Occupation (3-digit) Saint Lucia 1991 - see Variable: LC1991A_OCC - Occupation Senegal 1988 - see Variable: SN1988A_OCC - Occupation Senegal 2002 - see Variable: SN2002A_OCC3 - Occupation, 3 digits Senegal 2013 - see Variable: SN2013A_OCC3 - Profession or occupation (3-digit) Sierra Leone 2004 - see Variable: SL2004A_OCC - Occupation Sierra Leone 2015 - see Variable: SL2015A_OCC - Main occupation in the past 12 months Slovakia 1991 - see Variable: SK1991A_OCC - Occupation (2-digit) Slovakia 2001 - see Variable: SK2001A_OCC2 - Occupation (2-digit) Slovakia 2011 - see Variable: SK2011A_OCC2 - Occupation (2-digit) Slovenia 2002 - see Variable: SI2002A_OCC - Occupation South Africa 1996 - see Variable: ZA1996A_OCC3 - Occupation, 3 digits South Africa 2001 - see Variable: ZA2001A_OCC - Occupation, 3 digit South Africa 2007 - see Variable: ZA2007A_OCC3 - Occupation, 3 digits South Sudan 2008 - see Variable: SS2008A_OCC - Occupation Spain 1981 - see Variable: ES1981A_OCC - Occupation Spain 1991 - see Variable: ES1991A_OCC - Occupation Spain 2001 - see Variable: ES2001A_OCC - Occupation Spain 2011 - see Variable: ES2011A_OCC - Occupation, 2-digits Sudan 2008 - see Variable: SD2008A_OCC - Occupation Suriname 2004 - see Variable: SR2004A_OCC - Occupation Suriname 2012 - see Variable: SR2012A_OCC - Occupation (groups) Switzerland 1970 - see Variable: CH1970A_ISCO - Present occupation (ISCO) Switzerland 1980 - see Variable: CH1980A_ISCO - Present occupation (ISCO-COM) Switzerland 1990 - see Variable: CH1990A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2000 - see Variable: CH2000A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2011 - see Variable: CH2011A_OCC - Current occupation (1-digit, ISCO-08) Tanzania 1988 - see Variable: TZ1988A_OCC - Occupation Tanzania 2002 - see Variable: TZ2002A_OCC - Occupation last week Tanzania 2012 - see Variable: TZ2012A_OCC - Occupation Thailand 1970 - see Variable: TH1970A_OCC - Principal occupation last year Thailand 1980 - see Variable: TH1980A_OCC - Occupation last year Thailand 1990 - see Variable: TH1990A_OCC3 - Occupation last year Thailand 2000 - see Variable: TH2000A_OCC3 - Occupation last year, 3 digits Togo 1960 - see Variable: TG1960A_OCC - Occupation (3-digits) Togo 1970 - see Variable: TG1970A_OCC3 - Occupation (3-digits) Togo 2010 - see Variable: TG2010A_OCC2 - Occupation (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_OCC - Main occupation (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_OCC - Main occupation during previous week (three digits) Trinidad and Tobago 2000 - see Variable: TT2000A_OCC - Main occupation (3 digits) Turkey 1985 - see Variable: TR1985A_OCC2 - Occupation (2-digit) Turkey 1990 - see Variable: TR1990A_OCC2 - Current occupation (2 digits) Turkey 2000 - see Variable: TR2000A_OCC2 - Current occupation, 2 digit Uganda 1991 - see Variable: UG1991A_OCC - Occupation, 3 digits Uganda 2002 - see Variable: UG2002A_OCC - Occupation, 3 digits Uganda 2014 - see Variable: UG2014A_OCC - Occupation (2-digits) United Kingdom 1961 - see Variable: UK1961A_OCC - Occupation United Kingdom 1971 - see Variable: UK1971A_OCC - Occupation United Kingdom 1991 - see Variable: UK1991A_OCC - Occupational classification United Kingdom 2001 - see Variable: UK2001A_OCC3 - Standard occupational classification 2000-minor United States 1960 - see Variable: US1960A_OCC - Occupation United States 1970 - see Variable: US1970A_OCC - Occupation United States 1980 - see Variable: US1980A_OCC - Occupation United States 1990 - see Variable: US1990A_OCC - Occupation United States 2000 - see Variable: US2000A_OCC - Occupation United States 2005 - see Variable: US2005A_OCC2000M - Occupation, 2000 basis, modal category assignment United States 2010 - see Variable: US2010A_OCC - Occupation United States 2015 - see Variable: US2015A_OCC - Occupation last week United States 2020 - see Variable: US2020A_OCC - Occupation last week Uruguay 1963 - see Variable: UY1963A_OCC2 - Primary occupation [2-digit] Uruguay 1975 - see Variable: UY1975A_OCC - Occupation (COTA, 3 digits) Uruguay 1985 - see Variable: UY1985A_OCC - Occupation during the past week Uruguay 1996 - see Variable: UY1996A_OCC - Occupation (ISCO 88, 3 digits) Uruguay 2006 - see Variable: UY2006A_OCC3 - Occupation (ISCO-88, 3 digits) Venezuela 1981 - see Variable: VE1981A_OCC3 - Occupation, 3 digits Venezuela 1990 - see Variable: VE1990A_OCC - Occupation, 3 digits Venezuela 2001 - see Variable: VE2001A_OCC - Occupation Vietnam 1989 - see Variable: VN1989A_OCC2 - Occupation, 2 digits Vietnam 1999 - see Variable: VN1999A_OCC3 - Occupation, 3 digit Vietnam 2009 - see Variable: VN2009A_OCC - Occupation Vietnam 2019 - see Variable: VN2019A_OCC1 - Occupation, 1 digit Zambia 1990 - see Variable: ZM1990A_OCC - Occupation Zambia 2000 - see Variable: ZM2000A_OCC - Main occupation last 12 months, 3 digits Zambia 2010 - see Variable: ZM2010A_OCC2 - Main occupation last 12 months, 3 digits Zimbabwe 2012 - see Variable: ZW2012A_OCC - Occupation (3-digits) Work Variables -- PERSON Occupation, ISCO-1968, 3-digit ISCO68A provides the 3-digit occupation code for the respondent using the ISCO-1968 occupation classification. 011 Chemists 012 Physicists 013 Physical scientists not elsewhere classified 014 Physical science technicians 021 Architects and town planners 022 Civil engineers 023 Electrical and electronics engineers 024 Mechanical engineers 025 Chemical engineers 026 Metallurgists 027 Mining engineers 028 Industrial engineers 029 Engineers not elsewhere classified 031 Surveyors 032 Draughtsmen 033 Civil engineering technicians 034 Electrical and electronics engineering technicians 035 Mechanical engineering technicians 036 Chemical engineering technicians 037 Metallurgical technicians 038 Mining technicians 039 Engineering technicians not elsewhere classified 041 Aircraft pilots, navigators and flight engineers 042 Ships' deck officers and pilots 043 Ships' engineers 049 Aircraft and ships officers, n.e.c. 051 Biologists, zoologists and related scientists 052 Bacteriologists, pharmacologists and related scientists 053 Agronomists and related scientists 054 Life sciences technicians 059 Life sciences technicians and related technicians, n.e.c. 061 Medical doctors 062 Medical assistants 063 Dentists 064 Dental assistants 065 Veterinarians 066 Veterinary assistants 067 Pharmacists 068 Pharmaceutical assistants 069 Dietitians and public health nutritionists 071 Professional nurses 072 Nursing personnel not elsewhere classified 073 Professional midwives 074 Midwifery personnel not elsewhere classified 075 Optometrists and opticians 076 Physiotherapists and occupational therapists 077 Medical Xray technicians 079 Medical, dental, veterinary and related workers not elsewhere classified 081 Statisticians 082 Mathematicians and actuaries 083 Systems Analysts 084 Statistical and mathematical technicians 089 Statisticians, mathematicians, systems analysts and related technicians, n.e.c. 090 Economists 099 Other social scientists, n.e.c. 110 Accountants 121 Lawyers 122 Judges 129 Jurists not elsewhere classified 131 University and higher education teachers 132 Secondary education teachers 133 Primary education teachers 134 Preprimary education teachers 135 Special education teachers 139 Teachers not elsewhere classified 141 Ministers of religion and related members of religious orders 149 Workers in religion not elsewhere classified 151 Authors and critics 159 Authors, journalists and related writers not elsewhere classified 161 Sculptors, painters and related artists 162 Commercial artists and designers 163 Photographers and cameramen 169 Sculptors, painters and related artists, n.e.c. 171 Composers, musicians and singers 172 Choreographers and dancers 173 Actors and stage directors 174 Producers, performing arts 175 Circus performers 179 Performing artists not elsewhere classified 180 Athletes, sportsmen and related workers 191 Librarians, archivists and curators 192 Sociologists, anthropologists and related scientists 193 Social workers 194 Personnel and occupational specialists 195 Philologists, translators and interpreters 199 Other professional, technical and related workers 201 Legislative officials 202 Government administrators 211 General managers 212 Production managers (except farm) 219 Managers not elsewhere classified 299 Administrative and managerial, n.e.c. 300 Clerical supervisors 310 Government executive officials 321 Stenographers, typists and teletypists 322 Card and tapepunching machine operators 323 Telex operators 329 Stenegraphers, typists and teletypists, n.e.d. 331 Bookkeepers and cashiers 339 Bookkeepers, cashiers and related workers not elsewhere classified 341 Bookkeeping and calculating machine operators 342 Automatic dataprocessing machine operators 349 Computing machine operators, n.e.c. 351 Railway station masters 352 Postmasters 359 Transport and communications supervisors not elsewhere classified 360 Transport conductors 370 Mail distribution clerks 380 Telephone and telegraph operators 391 Stock clerks 392 Material and production planning clerks 393 Correspondence and reporting clerks 394 Receptionists and travel agency clerks 395 Library and filing clerks 399 Clerks not elsewhere classified 400 Managers (wholesale and retail trade) 410 Working proprietors (wholesale and retail trade) 421 Sales supervisors 422 Buyers 431 Technical salesmen and service advisers 432 Commercial travellers and Manufacturers' agents 439 Technical salesmen, commercial travellers and manufacturers' agents, n.e.c. 441 Insurance, real estate and securities salesmen 442 Business services salesmen 443 Auctioneers 451 Salesmen, shop assistants and demonstrators 452 Street vendors, canvassers and newsvendors 454 Itinerant traders 459 Salesmen, shop assistants and demonstrators, n.e.c. 490 Sales workers not elsewhere classified 500 Managers (catering and lodging services) 510 Working proprietors (catering and lodging services) 520 Housekeeping and related service supervisors 531 Cooks 532 Waiters, bartenders and related workers 540 Maids and related housekeeping service workers not elsewhere classified 551 Building caretakers 552 Charworkers, cleaners and related workers 560 Launderers, drycleaners and pressers 570 Hairdressers, barbers, beauticians and related workers 581 Firefighters 582 Policemen and detectives 589 Protective service workers not elsewhere classified 591 Guides 592 Undertakers and embalmers 599 Other service workers 600 Farm managers and supervisors 611 General farmers 612 Specialised farmers 621 General farm workers 622 Field crop and vegetable farm workers 623 Orchard, vineyard and related tree and shrub crop workers 624 Livestock workers 625 Dairy farm workers 626 Poultry farm workers 627 Nursery workers and gardeners 628 Farm machinery operators 629 Agricultural and animal husbandry workers not elsewhere classified 631 Loggers 632 Forestry workers (except logging) 639 Forestry and loggers, n.e.c. 641 Fishermen 649 Fishermen, hunters and related workers not elsewhere classified 700 Production supervisors and general foremen 711 Miners and quarrymen 712 Mineral and stone treaters 713 Well drillers, borers and related workers 721 Metal smelting, converting and refining furnacemen 722 Metal rollingmill workers 723 Metal melters and reheaters 724 Metal casters 725 Metal moulders and coremakers 726 Metal annealers, temperers and casehardeners 727 Metal drawers and extruders 728 Metal platers and coaters 729 Metal processers not elsewhere classified 731 Wood treaters 732 Sawyers, plywood makers and related woodprocessing workers 733 Paper pulp preparers 734 Paper makers 739 Wood preparation workers and paper makers, n.e.c. 741 Crushers, grinders and mixers 742 Cookers, roasters and related heattreaters 743 Filter and separator operators 744 Still and reactor operators 745 Petroleum refining workers 749 Chemical processers and related workers not elsewhere classified 751 Fibre preparers 752 Spinners and winders 753 Weaving and knittingmachine setters and patterncard preparers 754 Weavers and related workers 755 Knitters 756 Bleachers, dyers and textile product finishers 759 Spinners, weavers, knitters, dyers and related workers not elsewhere classified 761 Tanners and fellmongers 762 Pelt dressers 769 Tanners, fellmongers and pelt dressers, n.e.c. 771 Grain millers and related workers 772 Sugar processers and refiners 773 Butchers and meat preparers 774 Food preservers 775 Dairy product processers 776 Bakers, pastrycooks and confectionery makers 777 Tea, coffee and cocoa preparers 778 Brewers, wine and beverage makers 779 Food and beverage processers not elsewhere classified 781 Tobacco preparers 782 Cigar makers 783 Cigarette makers 789 Tobacco preparers and tobacco product makers not elsewhere classified 791 Tailors and dressmakers 792 Fur tailors and related workers 793 Milliners and hatmakers 794 Patternmakers and cutters 795 Sewers and embroiderers 796 Upholsterers and related workers 799 Tailors, dressmakers, sewers, upholsterers and related workers not elsewhere classified 801 Shoemakers and shoe repairers 802 Shoe cutters, lasters, sewers and related workers 803 Leather goods makers 811 Cabinetmakers 812 Woodworking machine operators 819 Cabinetmakers and related woodworkers not elsewhere classified 820 Stone cutters and carvers 831 Blacksmiths, hammersmiths and forgingpress operators 832 Toolmakers, metal patternmakers and metal markers 833 Machinetool setteroperators 834 Machinetool operators 835 Metal grinders, polishers and tool sharpeners 839 Blacksmiths, toolmakers and machinetool operators not elsewhere classified 841 Machinery fitters and machine assemblers 842 Watch, clock and precision instrument makers 843 Motor vehicle mechanics 844 Aircraft engine mechanics 849 Machinery fitters, machine assemblers and precision instrument makers (except electrical) not elsewhere classified 851 Electrical fitters 852 Electronics fitters 853 Electrical and electronics equipment assemblers 854 Radio and television repairmen 855 Electrical wiremen 856 Telephone and telegraph installers 857 Electric linemen and cable jointers 859 Electrical fitters and related electrical and electronics workers not elsewhere classified 861 Broadcasting station operators 862 Sound equipment operators and cinema projectionists 871 Plumbers and pipe fitters 872 Welders and flamecutters 873 Sheetmetal workers 874 Structural metal preparers and erectors 879 Other plumbers, welders, sheet metal and structural metal preparers and erectors 880 Jewellery and precious metal workers 891 Glass formers, cutters, grinders and finishers 892 Potters and related clay and abrasive formers 893 Glass and ceramics kilnmen 894 Glass engravers and etchers 895 Glass and ceramics painters and decorators 899 Glass formers, potters and related workers not elsewhere classified 901 Rubber and plastics product makers (except tire makers and tire vulcanisers) 902 Tire makers and vulcanisers 910 Paper and paperboard products makers 921 Compositors and typesetters 922 Printing pressmen 923 Stereotypers and electrotypers 924 Printing engravers (except photoengravers) 925 Photoengravers 926 Bookbinders and related workers 927 Photographic darkroom workers 929 Printers and related workers not elsewhere classified 931 Painters, construction 939 Painters not elsewhere classified 941 Musical instrument makers and tuners 942 Basketry weavers and brush makers 943 Nonmetallic mineral product makers 949 Other production and related workers 951 Bricklayers, stonemasons and tile setters 952 Reinforced concreters, cement finishers and terrazzo workers 953 Roofers 954 Carpenters, joiners and parquetry workers 955 Plasterers 956 Insulators 957 Glaziers 959 Construction workers not elsewhere classified 961 Power generating machinery operators 969 Stationary engine and related equipment operators not elsewhere classified 971 Dockers and freight handlers 972 Riggers and cable splicers 973 Crane and hoist operators 974 Earthmoving and related machinery operators 979 Material handling equipment operators not elsewhere classified 981 Ships' deck ratings, barge crews and boatmen 982 Ships' engineroom ratings 983 Railway engine drivers and firemen 984 Railway brakemen, signalmen and shunters 985 Motor vehicle drivers 986 Animal and animaldrawn vehicle drivers 989 Transport equipment operators not elsewhere classified 990 Labourers not elsewhere classified 995 Armed forces 997 Response suppressed 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Industry, general recode INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown Work Variables -- PERSON Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_IND4 - Industry [4 digit] Argentina 1980 - see Variable: AR1980A_IND - Industry Argentina 1991 - see Variable: AR1991A_IND - Industry Argentina 2001 - see Variable: AR2001A_IND - Industry Armenia 2001 - see Variable: AM2001A_IND - Principal activity at place of work Armenia 2011 - see Variable: AM2011A_IND - Industry Austria 1971 - see Variable: AT1971A_INDBR - Economic activity of supporter: branch Austria 1981 - see Variable: AT1981A_INDBR - Economic activity of supporter: branch Austria 1991 - see Variable: AT1991A_INDBR - Economic activity of supporter: branch Austria 2001 - see Variable: AT2001A_INDBR - Economic activity of supporter: branch Austria 2011 - see Variable: AT2011A_IND - Industry Bangladesh 1991 - see Variable: BD1991A_IND - Industry Bangladesh 2001 - see Variable: BD2001A_IND - Main work field Bangladesh 2011 - see Variable: BD2011A_IND - Industry Belarus 2009 - see Variable: BY2009A_ECONACT - Industry Benin 1979 - see Variable: BJ1979A_IND - Industry (1-digit) Benin 1992 - see Variable: BJ1992A_IND3 - Industry (2-digits) Benin 2002 - see Variable: BJ2002A_IND2 - Industry (2-digits) Benin 2013 - see Variable: BJ2013A_IND3 - Industry (3-digit) Bolivia 1976 - see Variable: BO1976A_IND - Industry Bolivia 1992 - see Variable: BO1992A_IND3 - Activity, 3 digits Bolivia 2001 - see Variable: BO2001A_IND3 - Industry, 3 digits Bolivia 2012 - see Variable: BO2012A_IND2 - Industry (2 digit) Botswana 1981 - see Variable: BW1981A_IND - Industry Botswana 1991 - see Variable: BW1991A_IND - Industry Botswana 2001 - see Variable: BW2001A_IND - Industry Botswana 2011 - see Variable: BW2011A_IND - Industry, 3-digits Brazil 1960 - see Variable: BR1960A_INDUSTRY - Industry Brazil 1970 - see Variable: BR1970A_INDUSTRY - Industry Brazil 1980 - see Variable: BR1980A_INDUSTRY - Industry Brazil 1991 - see Variable: BR1991A_IND - Industry Brazil 2000 - see Variable: BR2000A_IND - Industry, 5 digits Brazil 2010 - see Variable: BR2010A_IND - Industry of work from July 25 to July 31, 2010 Burkina Faso 1996 - see Variable: BF1996A_IND - Branch of activity Cambodia 1998 - see Variable: KH1998A_IND - Industry Cambodia 2004 - see Variable: KH2004A_IND3 - Industry (3-digits) Cambodia 2008 - see Variable: KH2008A_IND - Industry Cambodia 2013 - see Variable: KH2013A_IND - Industry (3-digits) Cambodia 2019 - see Variable: KH2019A_IND3 - Industy (ISIC rev 4, 3-digit) Cameroon 2005 - see Variable: CM2005A_IND - Industry Canada 1971 - see Variable: CA1971A_IND - Industry Canada 1981 - see Variable: CA1981A_IND - Industry (1981 standard industrial classification) Canada 1991 - see Variable: CA1991A_IND80 - Industry (1980 standard industrial classification) Canada 2001 - see Variable: CA2001A_IND80P - Industry (1980 Standard Industrial Classification) Canada 2011 - see Variable: CA2011A_IND - Industry Chile 1960 - see Variable: CL1960A_IND - Industry Chile 1970 - see Variable: CL1970A_IND4 - Industry (4-digit) Chile 1982 - see Variable: CL1982A_IND4 - Industry (4-digit) Chile 1992 - see Variable: CL1992A_IND - Industry Chile 2002 - see Variable: CL2002A_IND - Industry Chile 2017 - see Variable: CL2017A_IND - Industry (1-digit) China 1982 - see Variable: CN1982A_INDUSTRY - Industry China 1990 - see Variable: CN1990A_IND - Industry China 2000 - see Variable: CN2000A_IND - Industry (2-digit) Colombia 1964 - see Variable: CO1964A_IND4 - Industry, 4 digits Colombia 1973 - see Variable: CO1973A_IND - Industry Colombia 1993 - see Variable: CO1993A_IND - Industry Colombia 2005 - see Variable: CO2005A_IND - Industry (2-digit) Costa Rica 1963 - see Variable: CR1963A_IND3 - Industry, 3 digits Costa Rica 1973 - see Variable: CR1973A_IND4 - Industry, 4 digits Costa Rica 1984 - see Variable: CR1984A_IND4 - Industry, 4 digits Costa Rica 2000 - see Variable: CR2000A_IND3 - Industry, 3 digits Costa Rica 2011 - see Variable: CR2011A_IND - Industry 2-digit Cuba 2002 - see Variable: CU2002A_IND - Industry Cuba 2012 - see Variable: CU2012A_IND - Industry Côte d'Ivoire 1988 - see Variable: CI1988A_IND - Industry (1-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_IND2 - Industry sector (detailed) Dominican Republic 1960 - see Variable: DO1960A_IND - Industry Dominican Republic 1970 - see Variable: DO1970A_IND1 - Industry, 3 digits Dominican Republic 1981 - see Variable: DO1981A_IND - Industry (3-digit) Dominican Republic 2002 - see Variable: DO2002A_IND - Industry Dominican Republic 2010 - see Variable: DO2010A_IND - Main activity of business Ecuador 1962 - see Variable: EC1962A_IND3 - Industry, 3 digits Ecuador 1982 - see Variable: EC1982A_IND3 - Industry Ecuador 1990 - see Variable: EC1990A_IND3 - Industry, 3 digits Ecuador 2001 - see Variable: EC2001A_IND - Industry, 3 digits Ecuador 2010 - see Variable: EC2010A_IND3 - Industry (3 digits, ISIC rev 4) Egypt 1986 - see Variable: EG1986A_IND3 - Industry (3-digit) Egypt 1996 - see Variable: EG1996A_IND3 - Industry (ISIC) Egypt 2006 - see Variable: EG2006A_IND - Industry, 3-digit El Salvador 1992 - see Variable: SV1992A_IND - Industry (3-digit) El Salvador 2007 - see Variable: SV2007A_IND3DIG - Industry (3-digit) Ethiopia 1984 - see Variable: ET1984A_IND2 - Industry Ethiopia 1994 - see Variable: ET1994A_IND - Industry Fiji 1966 - see Variable: FJ1966A_IND - Industry Fiji 1976 - see Variable: FJ1976A_IND - Industry Fiji 1986 - see Variable: FJ1986A_IND - Industry 3 digits Fiji 1996 - see Variable: FJ1996A_IND2DIG - Industry (2 digits) Fiji 2007 - see Variable: FJ2007A_IND2 - Industry, 2 digits Fiji 2014 - see Variable: FJ2014A_IND - Industry Finland 2010 - see Variable: FI2010A_IND - Industry France 1962 - see Variable: FR1962A_IND - Industry France 1968 - see Variable: FR1968A_IND41 - Industry, 41 categories France 1975 - see Variable: FR1975A_INDUN - Industry, UNO France 1982 - see Variable: FR1982A_INDUN - Industry, United Nations nomenclature France 1990 - see Variable: FR1990A_IND15 - Industry, 15 categories France 1999 - see Variable: FR1999A_INDCITI - Industry, ISIC France 2006 - see Variable: FR2006A_IND700N - Economic activity in 700 categories (2003 classification) numeric recode France 2011 - see Variable: FR2011A_IND - Industry, 732 categories Germany 1970 - see Variable: DE1970A_IND - Industry Germany 1971 - see Variable: DE1971A_IND - Industry Germany 1981 - see Variable: DE1981A_IND - Industry Germany 1987 - see Variable: DE1987A_IND - Industry Ghana 2000 - see Variable: GH2000A_IND - Industry Ghana 2010 - see Variable: GH2010A_IND - Industry (major groups) Greece 1971 - see Variable: GR1971A_IND - Industry Greece 1981 - see Variable: GR1981A_IND - Industry Greece 1991 - see Variable: GR1991A_IND - Industry Greece 2001 - see Variable: GR2001A_IND - Industry Greece 2011 - see Variable: GR2011A_IND - Industry Guatemala 1964 - see Variable: GT1964A_IND3 - Field of economic activity (3-digits) Guatemala 1973 - see Variable: GT1973A_IND3 - Industry (3-digits) Guatemala 1981 - see Variable: GT1981A_IND3 - Industry (3-digits) Guatemala 1994 - see Variable: GT1994A_IND2 - Field of economic activity (2-digits) Guatemala 2002 - see Variable: GT2002A_IND1 - Field of economic activity (1-digit) Guinea 1983 - see Variable: GN1983A_IND2 - Branch of economic activity, 2 digits Guinea 2014 - see Variable: GN2014A_IND - Industry (3-digit) Haiti 1982 - see Variable: HT1982A_IND - Branch of work Haiti 2003 - see Variable: HT2003A_IND2 - Industry, 3 digits Honduras 1961 - see Variable: HN1961A_IND - Industry (2-digits) Honduras 1974 - see Variable: HN1974A_IND - Industry (3-digits) Honduras 2001 - see Variable: HN2001A_IND - Industry (4-digit) Honduras 2013 - see Variable: HN2013A_IND3 - Economic activity (3-digit) Hungary 2001 - see Variable: HU2001A_IND - Industry, branch of economy Hungary 2011 - see Variable: HU2011A_IND - Industry Indonesia 1971 - see Variable: ID1971A_IND - Industry Indonesia 1976 - see Variable: ID1976A_IND - Industry Indonesia 1980 - see Variable: ID1980A_IND - Industry Indonesia 1985 - see Variable: ID1985A_IND - Industry of primary occupation Indonesia 1990 - see Variable: ID1990A_IND - Industry of main occupation last week Indonesia 1995 - see Variable: ID1995A_IND - Industry Indonesia 2000 - see Variable: ID2000A_IND - Industry of primary occupation Indonesia 2005 - see Variable: ID2005A_IND - Industry Indonesia 2010 - see Variable: ID2010A_IND - Industry Iran 2006 - see Variable: IR2006A_IND4 - Industry Iran 2011 - see Variable: IR2011A_IND - Industry (3-digit) Iraq 1997 - see Variable: IQ1997A_IND - Industry Ireland 1971 - see Variable: IE1971A_IND - Industry Ireland 1981 - see Variable: IE1981A_IND - Industry class Ireland 1986 - see Variable: IE1986A_IND - Industry class Ireland 1991 - see Variable: IE1991A_IND - Industry class Ireland 1996 - see Variable: IE1996A_IND - Industry class Ireland 2002 - see Variable: IE2002A_IND - Industry class Ireland 2006 - see Variable: IE2006A_IND - Industry class Ireland 2011 - see Variable: IE2011A_IND - Industry Ireland 2016 - see Variable: IE2016A_IND - Industry Israel 1972 - see Variable: IL1972A_IND - Industry Israel 1983 - see Variable: IL1983A_IND - Industry Israel 1995 - see Variable: IL1995A_IND - Industry Israel 2008 - see Variable: IL2008A_IND - Branch of economy Italy 2001 - see Variable: IT2001A_IND - Industry Italy 2011 - see Variable: IT2011A_IND - Sector of economic activity Jamaica 1982 - see Variable: JM1982A_IND - Industry or type of business during past week / in last job Jamaica 1991 - see Variable: JM1991A_IND3 - Industry during past week or in last job, 3 digits Jamaica 2001 - see Variable: JM2001A_IND3 - Industry 3-digit Jordan 2004 - see Variable: JO2004A_IND - Major current economic activity of the establishment Kenya 2019 - see Variable: KE2019A_IND1 - Industry, ISIC section Kyrgyzstan 1999 - see Variable: KG1999A_IND - Activity type of an enterprise you are working in Kyrgyzstan 2009 - see Variable: KG2009A_IND - Type of industry, enterprise or organization Laos 1995 - see Variable: LA1995A_IND2 - Main industry in the last 12 months (2-digit) Laos 2005 - see Variable: LA2005A_IND3 - Industry (ISIC 3-digit) Laos 2015 - see Variable: LA2015A_IND2 - Industry (2-digit ISIC Rev. 4) Lesotho 2006 - see Variable: LS2006A_IND - Industry (2-digits) Liberia 1974 - see Variable: LR1974A_IND - Industry (3-digit) Liberia 2008 - see Variable: LR2008A_IND - Industry Malawi 1987 - see Variable: MW1987A_IND2 - Industry, 2 digit Malawi 1998 - see Variable: MW1998A_IND4 - Industry, 4-digit Malawi 2008 - see Variable: MW2008A_IND2 - Main industry Malawi 2018 - see Variable: MW2018A_IND3 - Main industry (ISIC 2008 3-digit) Malaysia 1970 - see Variable: MY1970A_IND3 - Industry last week Malaysia 1980 - see Variable: MY1980A_IND3 - Industry last week (3 digits) Malaysia 1991 - see Variable: MY1991A_IND3 - Main industry (3 digits) Malaysia 2000 - see Variable: MY2000A_IND3 - Main industry - 3 digits Mali 1987 - see Variable: ML1987A_IND - Principal branch of employment last month Mali 1998 - see Variable: ML1998A_IND - Branch of economic activity Mali 2009 - see Variable: ML2009A_IND - Industry Mauritius 1990 - see Variable: MU1990A_IND - Industry (1-digit) Mauritius 2000 - see Variable: MU2000A_IND1 - Industry (1 digit) Mauritius 2011 - see Variable: MU2011A_IND2 - Industry (2-digit) Mexico 1960 - see Variable: MX1960A_IND - Industry Mexico 1970 - see Variable: MX1970A_IND - Industry Mexico 1990 - see Variable: MX1990A_IND5 - Industry, 5 digits Mexico 1995 - see Variable: MX1995A_IND - Industry Mexico 2000 - see Variable: MX2000A_IND3 - Industry, 3 digits Mexico 2010 - see Variable: MX2010A_IND - Industry Mexico 2015 - see Variable: MX2015A_IND - Industry Mexico 2020 - see Variable: MX2020A_IND - Industry (4-digits) Mongolia 2000 - see Variable: MN2000A_IND - Industry Mongolia 2010 - see Variable: MN2010A_IND2 - Industry, division (ISIC Revision 4) Mongolia 2020 - see Variable: MN2020A_IND3 - Main industry (3-digit) Morocco 1982 - see Variable: MA1982A_IND3 - Industry (3-digit) Morocco 1994 - see Variable: MA1994A_IND2 - Industry (2 digits) Morocco 2004 - see Variable: MA2004A_IND2 - Sector of economic activity (2-digit) Morocco 2014 - see Variable: MA2014A_IND2 - Industry (2-digit) Mozambique 1997 - see Variable: MZ1997A_IND1 - Industry Mozambique 2007 - see Variable: MZ2007A_IND - Industry Mozambique 2017 - see Variable: MZ2017A_IND2 - Main economic activity (2-digits CAE Rev.2) Myanmar 2014 - see Variable: MM2014A_IND - Industry Nepal 2001 - see Variable: NP2001A_IND - Usual industry Nepal 2011 - see Variable: NP2011A_IND - Industry (2-digit) Netherlands 1960 - see Variable: NL1960A_IND - Industry Netherlands 1971 - see Variable: NL1971A_IND - Industry Netherlands 2001 - see Variable: NL2001A_IND - Industry Netherlands 2011 - see Variable: NL2011A_IND - Industry (1-digit) Nicaragua 1971 - see Variable: NI1971A_IND3 - Industry (ISIC2), 3 digits Nicaragua 1995 - see Variable: NI1995A_IND - Industry (ISIC 3.1, 3 digits) Nicaragua 2005 - see Variable: NI2005A_IND3 - Industry (ISIC 3.1, 3 digits)) Pakistan 1973 - see Variable: PK1973A_IND2 - Industry, 2 digit Palestine 1997 - see Variable: PS1997A_IND - Industry Palestine 2007 - see Variable: PS2007A_IND - Industry Palestine 2017 - see Variable: PS2017A_IND - Industry Panama 1960 - see Variable: PA1960A_IND3 - Industry (3 digit) Panama 1970 - see Variable: PA1970A_IND3 - Industry [3 digit] Panama 1980 - see Variable: PA1980A_IND - Industry, 3-digit Panama 1990 - see Variable: PA1990A_IND3 - Industry - 3 Digits Panama 2000 - see Variable: PA2000A_IND - Economic activity, 3 digits Panama 2010 - see Variable: PA2010A_IND - Economic activity, 4 digits Papua New Guinea 1980 - see Variable: PG1980A_IND - Industry, 3 digits Papua New Guinea 2000 - see Variable: PG2000A_IND3 - Industry (3-digit) Paraguay 1962 - see Variable: PY1962A_IND3 - Industry (3 digits) Paraguay 1972 - see Variable: PY1972A_IND3 - Industry (3 digits) Paraguay 1982 - see Variable: PY1982A_IND3 - Industry, 3-digits Paraguay 1992 - see Variable: PY1992A_IND3 - Industry, 3 digits Paraguay 2002 - see Variable: PY2002A_IND - Industry (4 digits) Peru 1993 - see Variable: PE1993A_IND - Economic activity (4 digits) Peru 2007 - see Variable: PE2007A_IND - Economic activity (4-digits) Peru 2017 - see Variable: PE2017A_IND4 - Economic activity (4-digits, in primary job last week) Philippines 1990 - see Variable: PH1990A_IND - Industry Philippines 1995 - see Variable: PH1995A_IND - Industry Philippines 2000 - see Variable: PH2000A_IND - Industry Philippines 2010 - see Variable: PH2010A_IND3 - Kind of business or industry (3-digit) Poland 1978 - see Variable: PL1978A_IND - Industry (of person providing support) Poland 2002 - see Variable: PL2002A_IND - Industry (main employer) Portugal 1981 - see Variable: PT1981A_IND - Industry Portugal 1991 - see Variable: PT1991A_IND - Industry Portugal 2001 - see Variable: PT2001A_IND - Industry Portugal 2011 - see Variable: PT2011A_IND - Industry Puerto Rico 1970 - see Variable: PR1970A_IND1990 - Industry, 1990 basis Puerto Rico 1980 - see Variable: PR1980A_IND1990 - Industry, 1990 basis Puerto Rico 1990 - see Variable: PR1990A_IND - Industry Puerto Rico 2000 - see Variable: PR2000A_IND1990 - Industry, 1990 basis Puerto Rico 2005 - see Variable: PR2005A_IND1990 - Industry, 1990 basis Puerto Rico 2010 - see Variable: PR2010A_IND - Industry Puerto Rico 2015 - see Variable: PR2015A_IND - Industry Puerto Rico 2020 - see Variable: PR2020A_IND - Industry Romania 1977 - see Variable: RO1977A_IND - Industry of supporter Romania 1977 - see Variable: RO1977A_WKACT - Activity category Romania 1992 - see Variable: RO1992A_IND - Industry Romania 2002 - see Variable: RO2002A_IND - Industry Romania 2011 - see Variable: RO2011A_INDGEN - Industry (general categories) Rwanda 2002 - see Variable: RW2002A_IND - Industry Rwanda 2012 - see Variable: RW2012A_IND2 - Industry (3-digit) Saint Lucia 1991 - see Variable: LC1991A_IND3 - Industry, 2 digit Senegal 1988 - see Variable: SN1988A_IND - Industry Senegal 2013 - see Variable: SN2013A_IND3 - Industry (3-digit) Sierra Leone 2004 - see Variable: SL2004A_IND - Industry Slovenia 2002 - see Variable: SI2002A_IND - Industry South Africa 1996 - see Variable: ZA1996A_IND2 - Industry, 2 digits South Africa 2001 - see Variable: ZA2001A_IND3 - Industry, 3 digit South Africa 2007 - see Variable: ZA2007A_IND3 - Industry, 3 digit South Sudan 2008 - see Variable: SS2008A_IND - Industry Spain 1981 - see Variable: ES1981A_IND - Industry Spain 1991 - see Variable: ES1991A_IND - Activity of the establishment Spain 2001 - see Variable: ES2001A_IND - Industry Spain 2011 - see Variable: ES2011A_IND - Industry, 2-digits Sudan 2008 - see Variable: SD2008A_IND - Industry Suriname 2004 - see Variable: SR2004A_IND - Industry Suriname 2012 - see Variable: SR2012A_IND - Industry (groups) Switzerland 1970 - see Variable: CH1970A_IND - Branch of economic activity (industry) Switzerland 1980 - see Variable: CH1980A_IND - Branch of economic activity (industry) Switzerland 1990 - see Variable: CH1990A_IND - Branch of economic activity (industry) Switzerland 2000 - see Variable: CH2000A_IND - Branch of economic activity (industry) Switzerland 2011 - see Variable: CH2011A_IND2 - Industry of local unit, workplace (NOGA 2-digit) Tanzania 2002 - see Variable: TZ2002A_IND - Industry last week Tanzania 2012 - see Variable: TZ2012A_IND - Industry Thailand 1970 - see Variable: TH1970A_IND - Principal industry last year Thailand 1980 - see Variable: TH1980A_IND - Principal industry last year Thailand 1990 - see Variable: TH1990A_IND3 - Principal industry last year, 3 digits Thailand 2000 - see Variable: TH2000A_IND3 - Industry last year, 3 digits Togo 1970 - see Variable: TG1970A_IND - Industry (1-digit) Togo 2010 - see Variable: TG2010A_IND3 - Industry (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_IND - Industry (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_IND - Industry Trinidad and Tobago 2000 - see Variable: TT2000A_IND - Industry (2 digits) Turkey 1985 - see Variable: TR1985A_INDALT - Industry (2-digit) Turkey 1990 - see Variable: TR1990A_IND2 - Industry (2 digits) Turkey 2000 - see Variable: TR2000A_IND2 - Industry, 2 digit Uganda 2002 - see Variable: UG2002A_IND - Industry United Kingdom 1961 - see Variable: UK1961A_IND - Industry United Kingdom 1971 - see Variable: UK1971A_IND - Industry United Kingdom 1991 - see Variable: UK1991A_IND - Industrial classification United Kingdom 2001 - see Variable: UK2001A_IND - Industry classification United States 1960 - see Variable: US1960A_IND - Industry United States 1970 - see Variable: US1970A_IND - Industry United States 1980 - see Variable: US1980A_IND - Industry United States 1990 - see Variable: US1990A_IND - Industry United States 2000 - see Variable: US2000A_IND - Industry United States 2005 - see Variable: US2005A_IND - Industry United States 2010 - see Variable: US2010A_IND - Industry United States 2015 - see Variable: US2015A_IND - Industry United States 2020 - see Variable: US2020A_IND - Industry Uruguay 1963 - see Variable: UY1963A_IND2 - Primary industry [2-digit] Uruguay 1985 - see Variable: UY1985A_IND - Industry during the past week Uruguay 1996 - see Variable: UY1996A_IND2 - Industry (ISIC 3, 2 digits) Uruguay 2006 - see Variable: UY2006A_IND3 - Industry (ISIC rev 3, 3 digits) Venezuela 1981 - see Variable: VE1981A_IND - Industry Venezuela 1990 - see Variable: VE1990A_IND - Industry Venezuela 2001 - see Variable: VE2001A_IND - Industry Vietnam 1989 - see Variable: VN1989A_IND2 - Industry, 2 digits Vietnam 1999 - see Variable: VN1999A_IND3 - Industry, 3 digit Vietnam 2009 - see Variable: VN2009A_IND - Industry Vietnam 2019 - see Variable: VN2019A_IND3 - Industry, 3 digit Zambia 1990 - see Variable: ZM1990A_IND - Industry Zambia 2000 - see Variable: ZM2000A_IND - Type of industry, 3 digits Zambia 2010 - see Variable: ZM2010A_IND2 - Industry, 3 digits Work Variables -- PERSON Status in employment (class of worker) [general version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 0 NIU (not in universe) 1 Self-employed 2 Wage/salary worker 3 Unpaid worker 4 Other 9 Unknown/missing Work Variables -- PERSON Status in employment (class of worker) [detailed version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 000 NIU (not in universe) 100 Self-employed 101 Self-employed, unincorporated 102 Self-employed, incorporated 110 Employer 111 Sharecropper, employer 120 Working on own account 121 Own account, agriculture 122 Domestic worker, self-employed 123 Subsistence worker, own consumption 124 Own account, other 125 Own account, without temporary/unpaid help 126 Own account, with temporary/unpaid help 130 Member of cooperative 140 Sharecropper 141 Sharecropper, self-employed 142 Sharecropper, employee 150 Kibbutz member 199 Self-employed, not specified 200 Wage/salary worker 201 Management 202 Non-management 203 White collar (non-manual) 204 Blue collar (manual) 205 White or blue collar 206 Day laborer 207 Employee, with a permanent job 208 Employee, occasional, temporary, contract 209 Employee without legal contract 210 Wage/salary worker, private employer 211 Apprentice 212 Religious worker 213 Wage/salary worker, non-profit, NGO 214 White collar, private 215 Blue collar, private 216 Paid family worker 217 Cooperative employee 220 Wage/salary worker, government or public sector 221 Federal, government employee 222 State government employee 223 Local government employee 224 White collar, public 225 Blue collar, public 226 Public companies 227 Civil servants, local collectives 230 Domestic worker (work for private household) 240 Seasonal migrant 241 Seasonal migrant, no broker 242 Seasonal migrant, uses broker 250 Other wage and salary 251 Canal zone/commission employee 252 Government employment/training program 253 Mixed state/private enterprise/parastatal 254 Government public work program 255 State enterprise employee 256 Coordinated and continuous collaboration job 300 Unpaid worker 310 Unpaid family worker 320 Apprentice, unpaid or unspecified 330 Trainee 340 Apprentice or trainee 350 Works for others without wage 400 Other 999 Unknown/missing Work Variables -- PERSON Has a secondary or additional jobs WRKADD indicates whether the respondent has more than one job. 1 No, only 1 job 2 Yes, has 2+ jobs 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Days worked last week DAYSWRK indicates the number of days worked by the person during the week preceding the enumeration. 0 Did not work 1 1 day 2 2 days 3 3 days 4 4 days 5 5 days 6 6 days 7 7 days 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Hours worked per week HRSWORK1 indicates the number of hours the respondent worked per week at all jobs. 000 0 hours 001 1 hour 002 2 hours 003 3 hours 004 4 hours 005 5 hours 006 6 hours 007 7 hours 008 8 hours 009 9 hours 010 10 hours 011 11 hours 012 12 hours 013 13 hours 014 14 hours 015 15 hours 016 16 hours 017 17 hours 018 18 hours 019 19 hours 020 20 hours 021 21 hours 022 22 hours 023 23 hours 024 24 hours 025 25 hours 026 26 hours 027 27 hours 028 28 hours 029 29 hours 030 30 hours 031 31 hours 032 32 hours 033 33 hours 034 34 hours 035 35 hours 036 36 hours 037 37 hours 038 38 hours 039 39 hours 040 40 hours 041 41 hours 042 42 hours 043 43 hours 044 44 hours 045 45 hours 046 46 hours 047 47 hours 048 48 hours 049 49 hours 050 50 hours 051 51 hours 052 52 hours 053 53 hours 054 54 hours 055 55 hours 056 56 hours 057 57 hours 058 58 hours 059 59 hours 060 60 hours 061 61 hours 062 62 hours 063 63 hours 064 64 hours 065 65 hours 066 66 hours 067 67 hours 068 68 hours 069 69 hours 070 70 hours 071 71 hours 072 72 hours 073 73 hours 074 74 hours 075 75 hours 076 76 hours 077 77 hours 078 78 hours 079 79 hours 080 80 hours 081 81 hours 082 82 hours 083 83 hours 084 84 hours 085 85 hours 086 86 hours 087 87 hours 088 88 hours 089 89 hours 090 90 hours 091 91 hours 092 92 hours 093 93 hours 094 94 hours 095 95 hours 096 96 hours 097 97 hours 098 98 hours 099 99 hours 100 100 hours 101 101 hours 102 102 hours 103 103 hours 104 104 hours 105 105 hours 106 106 hours 107 107 hours 108 108 hours 109 109 hours 110 110 hours 111 111 hours 112 112 hours 113 113 hours 114 114 hours 115 115 hours 116 116 hours 117 117 hours 118 118 hours 119 119 hours 120 120 hours 121 121 hours 122 122 hours 123 123 hours 124 124 hours 125 125 hours 126 126 hours 127 127 hours 128 128 hours 129 129 hours 130 130 hours 131 131 hours 132 132 hours 133 133 hours 134 134 hours 135 135 hours 136 136 hours 137 137 hours 138 138 hours 139 139 hours 140 140+ hours 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Hours worked per week, categorized HRSWORK2 indicates the number of hours the respondent worked per week at all jobs, categorized into intervals. 0 None 1 1 to 14 hours (except tt1980, tt1990 and tt2000) 2 15 to 29 hours (except de1970, ps2017, tt1980, tt1990, tt2000, and ve1971) 3 30 to 39 hours (except de1970, ps2017, tt1980, tt1990, tt2000, and ve1971) 4 40-48 hours (except il1972, tt1980, tt1990, and tt2000) 5 49 hours or more (except il1972 and tt2000) 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Actual hours worked per week HRSACTUAL1 indicates the actual number of hours the respondent worked per week at all jobs. 000 0 hours 001 1 hour 002 2 hours 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100 101 101 102 102 103 103 104 104 105 105 106 106 107 107 108 108 109 109 110 110 111 111 112 112 113 113 114 114 115 115 116 116 117 117 118 118 119 119 120 120 121 121 122 122 123 123 124 124 125 125 126 126 127 127 128 128 129 129 130 130 131 131 132 132 133 133 134 134 135 135 136 136 137 137 138 138 139 139 140 140+ hours 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Actual hours worked per week, categorized HRSACTUAL2 indicates the actual number of hours the respondent worked per week at all jobs, categorized into intervals. 0 None 1 1 to 14 hours (except tt1980, tt1990, and tt2000) 2 15 to 29 hours (except ps2017, tt1980, tt1990, tt2000, and ve1971) 3 30 to 39 hours (except ps2017, tt1980, tt1990, tt2000, and ve1971) 4 40 to 48 hours (except tt1980, tt1990, and tt2000) 5 49 hours or more (except tt2000) 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Hours worked in main occupation HRSMAIN indicates the number of hours the respondent worked per week in jobs related to their primary occupation. 000 0 hours 001 1 hour 002 2 hours 003 3 hours 004 4 hours 005 5 hours 006 6 hours 007 7 hours 008 8 hours 009 9 hours 010 10 hours 011 11 hours 012 12 hours 013 13 hours 014 14 hours 015 15 hours 016 16 hours 017 17 hours 018 18 hours 019 19 hours 020 20 hours 021 21 hours 022 22 hours 023 23 hours 024 24 hours 025 25 hours 026 26 hours 027 27 hours 028 28 hours 029 29 hours 030 30 hours 031 31 hours 032 32 hours 033 33 hours 034 34 hours 035 35 hours 036 36 hours 037 37 hours 038 38 hours 039 39 hours 040 40 hours 041 41 hours 042 42 hours 043 43 hours 044 44 hours 045 45 hours 046 46 hours 047 47 hours 048 48 hours 049 49 hours 050 50 hours 051 51 hours 052 52 hours 053 53 hours 054 54 hours 055 55 hours 056 56 hours 057 57 hours 058 58 hours 059 59 hours 060 60 hours 061 61 hours 062 62 hours 063 63 hours 064 64 hours 065 65 hours 066 66 hours 067 67 hours 068 68 hours 069 69 hours 070 70 hours 071 71 hours 072 72 hours 073 73 hours 074 74 hours 075 75 hours 076 76 hours 077 77 hours 078 78 hours 079 79 hours 080 80 hours 081 81 hours 082 82 hours 083 83 hours 084 84 hours 085 85 hours 086 86 hours 087 87 hours 088 88 hours 089 89 hours 090 90 hours 091 91 hours 092 92 hours 093 93 hours 094 94 hours 095 95 hours 096 96 hours 097 97 hours 098 98 hours 099 99 hours 100 100 hours 101 101 hours 102 102 hours 103 103 hours 104 104 hours 105 105 hours 106 106 hours 107 107 hours 108 108 hours 109 109 hours 110 110 hours 111 111 hours 112 112 hours 113 113 hours 114 114 hours 115 115 hours 116 116 hours 117 117 hours 118 118 hours 119 119 hours 120 120 hours 121 121 hours 122 122 hours 123 123 hours 124 124 hours 125 125 hours 126 126 hours 127 127 hours 128 128 hours 129 129 hours 130 130 hours 131 131 hours 132 132 hours 133 133 hours 134 134 hours 135 135 hours 136 136 hours 137 137 hours 138 138 hours 139 139 hours 140 140+ hours 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Migration status, 5 years MIGRATE5 indicates the person's place of residence 5 years ago. The first digit records movement across major administrative divisions and countries. The second digit reports movement across minor administrative divisions, for samples in which that detail is available. 00 NIU (not in universe) 10 Same major administrative unit 11 Same major, same minor administrative unit 12 Same major, different minor administrative unit 20 Different major administrative unit 30 Abroad 99 Unknown/missing Migration: Global Variables -- PERSON Migration status, previous residence MIGRATEP indicates whether the person's most recent move (if any) was between minor administrative units, major units, or countries. 00 NIU (not in universe) 10 Same major administrative unit 11 Same major, same minor administrative unit 12 Same major, different minor administrative unit 20 Different major administrative unit 30 Abroad 98 Response suppressed 99 Not reported/missing/unknown Migration: Global Variables -- PERSON 1st subnational geographic level of previous residence, world [consistent boundaries over time] GEOMIG1_P indicates the major administrative unit in which the person previously resided prior to the survey. Only intra-national migrations are recorded; however, the variable incorporates geographies for every country that lists place of previous residence, to enable comparative analysis of subnational migration. Foreign migrants are coded 097 or 997. Codes for GEOMIG1_1 match the geographic codes in GEOLEV1 (current place of residence). For similar information for different time intervals since migration, see variables GEOMIG1_1, GEOMIG1_5, and GEOMIG1_10. More on migration and geography can be found here. 051901 Yerevan [Province: Armenia] 051902 Aragatsotn [Province: Armenia] 051903 Ararat [Province: Armenia] 051904 Armavir [Province: Armenia] 051905 Gegharkunik [Province: Armenia] 051906 Lori [Province: Armenia] 051907 Kotayk [Province: Armenia] 051908 Shirak [Province: Armenia] 051909 Syunik [Province: Armenia] 051910 Vayots Dzor [Province: Armenia] 051911 Tavush [Province: Armenia] 051912 Nagorno-Karabagh [Province: Armenia] 051997 Foreign country [Province: Armenia] 051998 Unknown [Province: Armenia] 051999 NIU (not in universe) [Province: Armenia] 112001 Brest [Region: Belarus] 112002 Vitebsk [Region: Belarus] 112003 Gomel [Region: Belarus] 112004 Grodno [Region: Belarus] 112006 Minsk, Minsk City [Region: Belarus] 112007 Mogilev [Region: Belarus] 112097 Foreign country [Region: Belarus] 112098 Unknown [Region: Belarus] 112099 NIU (not in universe) [Region: Belarus] 204001 Alibori [Department: Benin] 204002 Atacora [Department: Benin] 204003 Atlantique [Department: Benin] 204004 Borgou [Department: Benin] 204005 Collines [Department: Benin] 204006 Couffo [Department: Benin] 204007 Donga [Department: Benin] 204008 Littoral [Department: Benin] 204009 Mono [Department: Benin] 204010 Oueme [Department: Benin] 204011 Plateau [Department: Benin] 204012 Zou [Department: Benin] 204097 Abroad [Department: Benin] 204098 Unknown [Department: Benin] 204099 NIU (not in universe) [Department: Benin] 076011 Rondônia [State: Brazil] 076012 Acre [State: Brazil] 076013 Amazonas [State: Brazil] 076014 Roraima [State: Brazil] 076015 Pará [State: Brazil] 076016 Amapá [State: Brazil] 076021 Maranhão [State: Brazil] 076022 Piauí [State: Brazil] 076023 Ceará [State: Brazil] 076024 Rio Grande do Norte [State: Brazil] 076025 Paraíba [State: Brazil] 076026 Pernambuco, Arquipelago de Fernando de Noronha [State: Brazil] 076027 Alagoas [State: Brazil] 076028 Sergipe [State: Brazil] 076029 Bahia [State: Brazil] 076031 Minas Gerais [State: Brazil] 076032 Espírito Santo [State: Brazil] 076033 Rio de Janeiro, Guanabara [State: Brazil] 076035 São Paulo [State: Brazil] 076036 Serra dos Aimorés [State: Brazil] 076041 Paraná [State: Brazil] 076042 Santa Catarina [State: Brazil] 076043 Rio Grande do Sul [State: Brazil] 076051 Mato Grosso do Sul, Mato Grosso [State: Brazil] 076052 Goiás, Tocantins [State: Brazil] 076053 Distrito Federal [State: Brazil] 076054 Brazil, unspecified [State: Brazil] 076097 Abroad [State: Brazil] 076098 Unknown [State: Brazil] 076099 NIU (not in universe) [State: Brazil] 116001 Banteay Meanchey [Province: Cambodia] 116002 Battambang [Province: Cambodia] 116003 Kampong Cham, Tbong Khmum [Province: Cambodia] 116004 Kampong Chhnang [Province: Cambodia] 116005 Kampong Speu [Province: Cambodia] 116006 Kampong Thom [Province: Cambodia] 116007 Kampot [Province: Cambodia] 116008 Phnom Penh, Kandal [Province: Cambodia] 116009 Koh Kong, Preah Sihanouk [Province: Cambodia] 116010 Kratie [Province: Cambodia] 116011 Mondul Kiri [Province: Cambodia] 116013 Preah Vihear [Province: Cambodia] 116014 Prey Veng [Province: Cambodia] 116015 Pursat [Province: Cambodia] 116016 Ratanak Kiri [Province: Cambodia] 116017 Siem Reap, Otdar Meanchey [Province: Cambodia] 116019 Stung Treng [Province: Cambodia] 116020 Svay Rieng [Province: Cambodia] 116021 Takeo [Province: Cambodia] 116023 Kep [Province: Cambodia] 116024 Pailin [Province: Cambodia] 116097 Foreign country [Province: Cambodia] 116098 Unknown [Province: Cambodia] 116099 NIU (not in universe) [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] 120096 Cameroon - unknown arrondissement [Province: Cameroon] 120097 Foreign country [Province: Cameroon] 120098 Unknown [Province: Cameroon] 120099 NIU (not in universe) [Province: Cameroon] 152001 Tarapaca [Province: Chile] 152002 Antofagasta [Province: Chile] 152003 Atacama [Province: Chile] 152004 Coquimbo [Province: Chile] 152005 Aconcagua [Province: Chile] 152006 Valparaíso [Province: Chile] 152007 Santiago [Province: Chile] 152008 O'Higgins [Province: Chile] 152009 Colchagua [Province: Chile] 152010 Curicó [Province: Chile] 152011 Talca [Province: Chile] 152012 Maule [Province: Chile] 152013 Linares [Province: Chile] 152014 Ñuble [Province: Chile] 152015 Concepción [Province: Chile] 152016 Arauco [Province: Chile] 152017 Bío Bío [Province: Chile] 152018 Malleco [Province: Chile] 152019 Cautín [Province: Chile] 152020 Valdivia [Province: Chile] 152021 Osorno [Province: Chile] 152022 Llanquihue [Province: Chile] 152023 Chiloé [Province: Chile] 152024 Aysén [Province: Chile] 152025 Magallanes [Province: Chile] 152097 Foreign country [Province: Chile] 152098 Unknown [Province: Chile] 152099 NIU (not in universe) [Province: Chile] 170005 Antioquia [Department: Colombia] 170008 Atlántico [Department: Colombia] 170011 Bogotá D.C., Cundinamarca [Department: Colombia] 170013 Bolívar, Sucre [Department: Colombia] 170015 Boyacá, Casanare [Department: Colombia] 170018 Caquetá [Department: Colombia] 170019 Cauca [Department: Colombia] 170023 Córdoba [Department: Colombia] 170027 Chocó [Department: Colombia] 170041 Huila [Department: Colombia] 170044 La Guajira [Department: Colombia] 170050 Meta [Department: Colombia] 170052 Nariño [Department: Colombia] 170054 Cesar, Norte De Santander, Magdalena [Department: Colombia] 170066 Caldas, Quindío, Risaralda [Department: Colombia] 170068 Santander [Department: Colombia] 170073 Tolima [Department: Colombia] 170076 Valle Del Cauca [Department: Colombia] 170081 Arauca [Department: Colombia] 170086 Putumayo [Department: Colombia] 170088 Archipiélago De San Andrés Y Providencia [Department: Colombia] 170095 Amazonas, Guaviare, Vaupés, Vichada, Guainía [Department: Colombia] 170097 Abroad [Department: Colombia] 170098 Unknown [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] 188097 Foreign country [Province: Costa Rica] 188098 Unknown [Province: Costa Rica] 192021 Pinar del Río, Artemisa, Mayabeque [Province: Cuba] 192023 La Habana [Province: Cuba] 192025 Matanzas [Province: Cuba] 192026 Villa Clara [Province: Cuba] 192027 Cienfuegos [Province: Cuba] 192028 Sancti Spíritus [Province: Cuba] 192029 Ciego de Ávila [Province: Cuba] 192030 Camagüey [Province: Cuba] 192031 Las Tunas [Province: Cuba] 192032 Holguín [Province: Cuba] 192033 Granma [Province: Cuba] 192034 Santiago de Cuba [Province: Cuba] 192035 Guantánamo [Province: Cuba] 192040 Isla de la Juventud [Province: Cuba] 192997 Abroad [Province: Cuba] 192998 Unknown [Province: Cuba] 192999 NIU (not in universe) [Province: Cuba] 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 [Province: Ecuador] 218010 Imbabura, Las Golondrinas [Disputed canton] [Province: Ecuador] 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] 218097 Foreign country [Province: Ecuador] 218098 Unknown and Disputed Zones [Province: Ecuador] 218999 NIU (not in universe) [Province: Ecuador] 818000 Reported same governorate as household location [Governorate: Egypt] 818001 Giza, 6th October City, Cairo, Helwan [Governorate: Egypt] 818002 Alexandria [Governorate: Egypt] 818003 Port Said [Governorate: Egypt] 818004 Suez [Governorate: Egypt] 818011 Demietta [Governorate: Egypt] 818012 Dakahlia [Governorate: Egypt] 818013 Sharkia [Governorate: Egypt] 818014 Kaliobia [Governorate: Egypt] 818015 Kafr Sheikh [Governorate: Egypt] 818016 Gharbia [Governorate: Egypt] 818018 Menoufia, Behera [Governorate: Egypt] 818019 Ismailia [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, Luxor [Governorate: Egypt] 818028 Aswan [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] 818097 Abroad [Governorate: Egypt] 818098 Unknown [Governorate: Egypt] 818099 NIU (not in universe) [Governorate: Egypt] 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] 222098 Abroad [Department: El Salvador] 222099 NIU (not in universe) [Department: El Salvador] 231001 Tigray [Region: Ethiopia] 231002 Affar [Region: Ethiopia] 231003 Amhara [Region: Ethiopia] 231004 Oromia, Somali [Region: Ethiopia] 231006 Benishangul-Gumuz [Region: Ethiopia] 231007 Southern Nations, Nationalities, and Peoples (SNNP) [Region: Ethiopia] 231012 Gambela [Region: Ethiopia] 231013 Harari [Region: Ethiopia] 231014 Addis Ababa [Region: Ethiopia] 231015 Dire Dawa [Region: Ethiopia] 231097 Abroad [Region: Ethiopia] 231099 NIU [Region: Ethiopia] 250001 Guadeloupe [Region: France] 250002 Martinique [Region: France] 250003 French Guyana [Region: France] 250004 Réunion Island [Region: 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] 250097 Abroad [Region: France] 320001 Guatemala [Department: Guatemala] 320002 El Progreso [Department: Guatemala] 320003 Sacatepéquez [Department: Guatemala] 320004 Chimaltenango [Department: Guatemala] 320005 Escuintla [Department: Guatemala] 320006 Santa Rosa [Department: Guatemala] 320007 Sololá [Department: Guatemala] 320008 Totonicapán [Department: Guatemala] 320009 Quetzaltenango [Department: Guatemala] 320010 Suchitepéquez [Department: Guatemala] 320011 Retalhuleu [Department: Guatemala] 320012 San Marcos [Department: Guatemala] 320013 Huehuetenango [Department: Guatemala] 320014 Quiché [Department: Guatemala] 320015 Baja Verapaz [Department: Guatemala] 320016 Alta Verapaz [Department: Guatemala] 320017 Petén [Department: Guatemala] 320018 Izabal [Department: Guatemala] 320019 Zacapa [Department: Guatemala] 320020 Chiquimula [Department: Guatemala] 320021 Jalapa [Department: Guatemala] 320022 Jutiapa [Department: Guatemala] 320097 Foreign Country [Department: Guatemala] 320098 Unknown [Department: Guatemala] 320099 NIU [Department: Guatemala] 324011 Boffa [Region: Guinea] 324012 Boké [Region: Guinea] 324013 Fria [Region: Guinea] 324014 Gaoual [Region: Guinea] 324015 Koundara [Region: Guinea] 324021 Conakry [Region: Guinea] 324031 Dabola [Region: Guinea] 324032 Dinguiraye [Region: Guinea] 324033 Faranah [Region: Guinea] 324034 Kissidougou [Region: Guinea] 324041 Kankan [Region: Guinea] 324042 Kérouané [Region: Guinea] 324043 Kouroussa [Region: Guinea] 324044 Mandiana [Region: Guinea] 324045 Siguiri [Region: Guinea] 324051 Coyah, Dubréka [Region: Guinea] 324053 Forécariah [Region: Guinea] 324054 Kindia [Region: Guinea] 324055 Télimélé [Region: Guinea] 324061 Koubia [Region: Guinea] 324062 Labé [Region: Guinea] 324063 Lélouma [Region: Guinea] 324064 Mali [Region: Guinea] 324065 Tougué [Region: Guinea] 324071 Dalaba [Region: Guinea] 324072 Mamou [Region: Guinea] 324073 Pita [Region: Guinea] 324081 Beyla [Region: Guinea] 324082 Guéckédou [Region: Guinea] 324083 Lola [Region: Guinea] 324084 Macenta [Region: Guinea] 324085 Nzerekore [Region: Guinea] 324086 Yomou [Region: Guinea] 324096 Guinea, place unknown [Region: Guinea] 324097 Foreign country [Region: Guinea] 324098 Unknown [Region: Guinea] 324099 NIU (not in universe) [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] 332097 Foreign Country [Department: Haiti] 332098 Unknown [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, Uttaranchal [State: India] 356010 Bihar, 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 Madhya Pradesh, Chhattisgarh [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 Goa, Daman and Diu [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] 356097 Abroad [State: India] 356098 Unknown [State: India] 356099 NIU (not in universe) [State: India] 360011 Nanggroe Aceh Darussalam [Province: Indonesia] 360012 Sumatera Utara [Province: Indonesia] 360013 Sumatera Barat [Province: Indonesia] 360014 Kepulauan Riau, Riau [Province: Indonesia] 360015 Jambi [Province: Indonesia] 360016 Bangka Belitung, Sumatera Selatan [Province: Indonesia] 360017 Bengkulu [Province: Indonesia] 360018 Lampung [Province: Indonesia] 360031 DKI Jakarta [Province: Indonesia] 360032 Banten, Jawa Barat [Province: Indonesia] 360033 Jawa Tengah [Province: Indonesia] 360034 DKI Yogyakarta [Province: Indonesia] 360035 Jawa Timur [Province: Indonesia] 360051 Bali [Province: Indonesia] 360052 Nusa Tenggara Barat [Province: Indonesia] 360053 Nusa Tenggara Timur [Province: Indonesia] 360061 Kalimantan Barat [Province: Indonesia] 360062 Kalimantan Tengah [Province: Indonesia] 360063 Kalimantan Selatan [Province: Indonesia] 360064 Kalimantan Timur [Province: Indonesia] 360071 Gorontalo, Sulawesi Utara [Province: Indonesia] 360072 Sulawesi Tengah [Province: Indonesia] 360073 Sulawesi Barat, Sulawesi Selatan [Province: Indonesia] 360074 Sulawesi Tenggara [Province: Indonesia] 360081 Maluku, Maluku Utara [Province: Indonesia] 360094 Papua, Papua Barat [Province: Indonesia] 360097 Abroad [Province: Indonesia] 360098 Unknown [Province: Indonesia] 360099 NIU (not in universe) [Province: Indonesia] 360626 East Timor [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 Razavi Khorasan [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, Alborz [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] 364098 Unknown [Province: Iran] 364099 NIU (not in universe) [Province: Iran] 368000 Always lived in residential place of birth [Governorate: Iraq] 368001 In this governorate [Governorate: Iraq] 368011 Dahuk [Governorate: Iraq] 368012 Nineveh [Governorate: Iraq] 368013 Sulaymaniyah [Governorate: Iraq] 368014 Al-Tameem [Governorate: Iraq] 368015 Erbil [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] 368097 Other countries [Governorate: Iraq] 368098 Unknown [Governorate: Iraq] 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] 388098 Unknown [Parish: Jamaica] 388099 NIU (Not in universe) [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] 400997 Foreign Country [Governorate: Jordan] 400998 Unknown [Governorate: Jordan] 404001 Nairobi [Province: Kenya] 404002 Central [Province: Kenya] 404003 Coast [Province: Kenya] 404004 Eastern [Province: Kenya] 404005 Northeastern [Province: Kenya] 404006 Nyanza [Province: Kenya] 404007 Rift Valley [Province: Kenya] 404008 Western [Province: Kenya] 404097 Abroad [Province: Kenya] 404098 Unknown [Province: Kenya] 404099 NIU (not in universe) [Province: Kenya] 417001 Bishkek [Region: Kyrgyz Republic] 417002 Issyk-Kul region [Region: Kyrgyz Republic] 417003 Dzhalal-Abad region [Region: Kyrgyz Republic] 417004 Naryn region [Region: Kyrgyz Republic] 417005 Batken region [Region: Kyrgyz Republic] 417006 Oshskaya region, City of Osh [Region: Kyrgyz Republic] 417007 Talasskaya region [Region: Kyrgyz Republic] 417008 Chuya region [Region: Kyrgyz Republic] 417096 Other Kyrgyz Republic, not specified [Region: Kyrgyz Republic] 417097 Foreign country [Region: Kyrgyz Republic] 417098 Unknown [Region: Kyrgyz Republic] 417099 NIU (not in universe) [Region: Kyrgyz Republic] 418001 Vientiane Capital [Province: Laos] 418002 Phongsaly [Province: Laos] 418003 Luangnamtha [Province: Laos] 418004 Oudomxay [Province: Laos] 418005 Bokeo [Province: Laos] 418006 Luangprabang [Province: Laos] 418007 Huaphanh [Province: Laos] 418008 Xayaboury [Province: Laos] 418009 Xienkhuang [Province: Laos] 418010 Vientiane Province [Province: Laos] 418011 Borikhamxay [Province: Laos] 418012 Khammuane [Province: Laos] 418013 Savanakhet [Province: Laos] 418014 Saravane [Province: Laos] 418015 Sekong [Province: Laos] 418016 Champasack [Province: Laos] 418017 Attapeu [Province: Laos] 418018 Xaysomboune [Province: Laos] 418097 Foreign Country [Province: Laos] 418098 Unknown [Province: Laos] 418099 NIU [Province: Laos] 662003 Castries city, Castries rural, Castries suburban [District: Saint Lucia] 662009 Choiseul, Laborie, Vieux-Fort [District: Saint Lucia] 662010 Anse-la-Raye, Canaries, Micoud, Soufriere [District: Saint Lucia] 662012 Dennery, Gros-Islet [District: Saint Lucia] 662098 Unknown [District: Saint Lucia] 662099 NIU [District: Saint Lucia] 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 Nkhotakota [District: Malawi] 454203 Ntchisi [District: Malawi] 454204 Dowa [District: Malawi] 454205 Salima [District: Malawi] 454206 Lilongwe, Lilongwe City [District: Malawi] 454207 Mchinji [District: Malawi] 454208 Dedza [District: Malawi] 454209 Ntcheu [District: Malawi] 454301 Mangochi [District: Malawi] 454302 Machinga [District: Malawi] 454303 Zomba, Zomba City [District: Malawi] 454304 Chiradzulu [District: Malawi] 454305 Blantyre, Blantyre City [District: Malawi] 454306 Mwanza, Neno [District: Malawi] 454307 Thyolo [District: Malawi] 454308 Mulanje [District: Malawi] 454309 Phalombe [District: Malawi] 454310 Chikwawa [District: Malawi] 454311 Nsanje [District: Malawi] 454312 Balaka [District: Malawi] 454997 Abroad [District: Malawi] 454999 NIU (not in universe) [District: Malawi] 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, Kidal [Region: Mali] 466009 Bamako [Region: Mali] 466096 Mali, province unspecified [Region: Mali] 466097 Foreign country [Region: Mali] 466098 Unknown [Region: Mali] 466999 NIU (not in universe) [Region: Mali] 484001 Aguascalientes [State: Mexico] 484002 Baja California [State: Mexico] 484003 Baja California Sur [State: Mexico] 484004 Campeche [State: Mexico] 484005 Coahuila de Zaragoza [State: Mexico] 484006 Colima [State: Mexico] 484007 Chiapas [State: Mexico] 484008 Chihuahua [State: Mexico] 484009 Distrito Federal [State: Mexico] 484010 Durango [State: Mexico] 484011 Guanajuato [State: Mexico] 484012 Guerrero [State: Mexico] 484013 Hidalgo [State: Mexico] 484014 Jalisco [State: Mexico] 484015 México [State: Mexico] 484016 Michoacán de Ocampo [State: Mexico] 484017 Morelos [State: Mexico] 484018 Nayarit [State: Mexico] 484019 Nuevo León [State: Mexico] 484020 Oaxaca [State: Mexico] 484021 Puebla [State: Mexico] 484022 Querétaro [State: Mexico] 484023 Quintana Roo [State: Mexico] 484024 San Luis Potosí [State: Mexico] 484025 Sinaloa [State: Mexico] 484026 Sonora [State: Mexico] 484027 Tabasco [State: Mexico] 484028 Tamaulipas [State: Mexico] 484029 Tlaxcala [State: Mexico] 484030 Veracruz de Ignacio de la Llave [State: Mexico] 484031 Yucatán [State: Mexico] 484032 Zacatecas [State: Mexico] 484097 Abroad [State: Mexico] 484098 Unknown [State: Mexico] 484099 NIU (not in universe) [State: Mexico] 496011 Ulaanbaatar [Province: Mongolia] 496021 Dornod [Province: Mongolia] 496022 Sukhbaatar [Province: Mongolia] 496023 Khentii [Province: Mongolia] 496041 Tuv [Province: Mongolia] 496043 Selenge [Province: Mongolia] 496044 Dornogobi [Province: Mongolia] 496045 Darkhan-Uul [Province: Mongolia] 496046 Umnugobi [Province: Mongolia] 496048 Dundgobi, Gobisumber [Province: Mongolia] 496061 Orkhon [Province: Mongolia] 496062 Uvurkhangai [Province: Mongolia] 496063 Bulgan [Province: Mongolia] 496064 Bayankhongor [Province: Mongolia] 496065 Arkhangai [Province: Mongolia] 496067 Khuvsgul [Province: Mongolia] 496081 Zavkhan [Province: Mongolia] 496082 Gobi-Altai [Province: Mongolia] 496083 Bayan-Ulgii [Province: Mongolia] 496084 Khovd [Province: Mongolia] 496085 Uvs [Province: Mongolia] 496097 Abroad [Province: Mongolia] 496099 NIU (not in universe) [Province: Mongolia] 104001 Kachin [State: Myanmar] 104002 Kayah [State: Myanmar] 104003 Kayin [State: Myanmar] 104004 Chin [State: Myanmar] 104005 Sagaing [State: Myanmar] 104006 Tanintharyi [State: Myanmar] 104007 Bago [State: Myanmar] 104008 Magway [State: Myanmar] 104009 Mandalay [State: Myanmar] 104010 Mon [State: Myanmar] 104011 Rakhine [State: Myanmar] 104012 Yangon [State: Myanmar] 104013 Shan [State: Myanmar] 104014 Ayeyawady [State: Myanmar] 104015 Nay Pyi Taw [State: Myanmar] 104097 Abroad [State: Myanmar] 104099 NIU [State: Myanmar] 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] 591009 Unknown district in Panamá province [Province: Panama] 591097 Foreign country [Province: Panama] 591098 Unknown [Province: Panama] 591099 NIU (not in universe) [Province: Panama] 608001 Abra [Province: Philippines] 608002 Agusan del norte [Province: Philippines] 608003 Agusan del sur [Province: Philippines] 608004 Aklan [Province: Philippines] 608005 Albay [Province: Philippines] 608006 Antique [Province: Philippines] 608007 Basilan, City Of Isabela [Province: Philippines] 608008 Bataan [Province: Philippines] 608010 Batangas [Province: Philippines] 608011 Benguet [Province: Philippines] 608012 Bohol [Province: Philippines] 608013 Bukidnon [Province: Philippines] 608014 Bulacan [Province: Philippines] 608015 Cagayan, Batanes [Province: Philippines] 608016 Camarines norte [Province: Philippines] 608017 Camarines Sur [Province: Philippines] 608018 Camiguin [Province: Philippines] 608019 Capiz [Province: Philippines] 608020 Catanduanes [Province: Philippines] 608021 Cavite [Province: Philippines] 608022 Cebu [Province: Philippines] 608023 Davao (Davao del Norte) [Province: Philippines] 608024 Davao del Sur, Davao Occidental [Province: Philippines] 608025 Davao Oriental [Province: Philippines] 608026 Eastern Samar [Province: Philippines] 608027 Ifugao [Province: Philippines] 608028 Ilocos Norte [Province: Philippines] 608029 Ilocos Sur [Province: Philippines] 608030 Iloilo, Guimaras [Province: Philippines] 608031 Isabela [Province: Philippines] 608032 Kalinga-Apayao, Apayo, Kalinga [Province: Philippines] 608033 La Union [Province: Philippines] 608034 Laguna [Province: Philippines] 608035 Lanao del Norte [Province: Philippines] 608036 Lanao del Sur, Maguindanao, Marawi City and Cotabato city [Province: Philippines] 608037 Leyte, Biliran [Province: Philippines] 608039 Manila [Province: Philippines] 608040 Marinduque [Province: Philippines] 608041 Masbate [Province: Philippines] 608042 Misamis Occidental [Province: Philippines] 608043 Misamis Oriental [Province: Philippines] 608044 Mountain Province [Province: Philippines] 608045 Negros Occidental [Province: Philippines] 608046 Negros Oriental [Province: Philippines] 608047 Cotabato (North Cotabato) [Province: Philippines] 608048 Northern Samar [Province: Philippines] 608049 Nueva Ecija [Province: Philippines] 608050 Nueva Vizcaya [Province: Philippines] 608051 Occidental Mindoro [Province: Philippines] 608052 Oriental Mindoro [Province: Philippines] 608053 Palawan [Province: Philippines] 608054 Pampanga [Province: Philippines] 608055 Pangasinan [Province: Philippines] 608056 Quezon [Province: Philippines] 608057 Quirino [Province: Philippines] 608058 Rizal [Province: Philippines] 608059 Romblon [Province: Philippines] 608060 Samar (Western Samar) [Province: Philippines] 608061 Siquijor [Province: Philippines] 608062 Sorsogon [Province: Philippines] 608063 South Cotabato, Sarangani [Province: Philippines] 608064 Southern Leyte [Province: Philippines] 608065 Sultan Kudarat [Province: Philippines] 608066 Sulu [Province: Philippines] 608067 Surigao Del Norte, Dinagat islands [Province: Philippines] 608068 Surigao del Sur [Province: Philippines] 608069 Tarlac [Province: Philippines] 608070 Tawi-Tawi [Province: Philippines] 608071 Zambales [Province: Philippines] 608072 Zamboanga Norte [Province: Philippines] 608073 Zamboanga del Sur, Zamboanga Sibugay [Province: Philippines] 608074 Manila Metro, 2nd District [Province: Philippines] 608075 Manila Metro, 3rd District [Province: Philippines] 608076 Manila Metro, 4th District [Province: Philippines] 608077 Aurora [Province: Philippines] 608097 Foreign country [Province: Philippines] 608098 Unknown [Province: Philippines] 608099 NIU (not in universe) [Province: Philippines] 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 Dambovita [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] 642097 Foreign country [County: Romania] 642098 Unknown [County: Romania] 642099 NIU (not in universe) [County: Romania] 646002 Byumba, Kigali Ngali, Kigali Ville, Kibungo, Umutara [Province: Rwanda] 646003 Gitarama [Province: Rwanda] 646004 Butare [Province: Rwanda] 646005 Gikongoro [Province: Rwanda] 646006 Cyangugu [Province: Rwanda] 646007 Kibuye [Province: Rwanda] 646008 Gisenyi [Province: Rwanda] 646009 Ruhengeri [Province: Rwanda] 646097 Foreign Countries [Province: Rwanda] 646098 Unknown [Province: Rwanda] 646099 NIU [Province: Rwanda] 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] 705097 Abroad [Region: Slovenia] 705999 NIU (not in universe) [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] 710097 Foreign country [Province: South Africa] 710098 Unknown [Province: South Africa] 710099 NIU (not in universe) [Province: South Africa] 724011 Galicia [Communities & autonomous city: Spain] 724012 Principado de Asturias [Communities & autonomous city: Spain] 724013 Cantabria [Communities & autonomous city: Spain] 724021 País Vasco [Communities & autonomous city: Spain] 724022 Comunidad Foral de Navarra [Communities & autonomous city: Spain] 724023 La Rioja [Communities & autonomous city: Spain] 724024 Aragón [Communities & autonomous city: Spain] 724030 Comunidad de Madrid [Communities & autonomous city: Spain] 724041 Castilla y León [Communities & autonomous city: Spain] 724042 Castilla-La Mancha [Communities & autonomous city: Spain] 724043 Extremadura [Communities & autonomous city: Spain] 724051 Cataluña [Communities & autonomous city: Spain] 724052 Comunidad Valenciana [Communities & autonomous city: Spain] 724053 Islas Baleares [Communities & autonomous city: Spain] 724061 Andalucía [Communities & autonomous city: Spain] 724062 Región de Murcia [Communities & autonomous city: Spain] 724063 Ciudad Autónoma de Ceuta [Communities & autonomous city: Spain] 724064 Ciudad Autónoma de Melilla [Communities & autonomous city: Spain] 724070 Canarias [Communities & autonomous city: Spain] 724097 Abroad [Communities & autonomous city: Spain] 724999 NIU (not in universe) [Communities & autonomous city: Spain] 740001 Paramaribo [District: Suriname] 740002 Wanica [District: Suriname] 740003 Nickerie [District: Suriname] 740005 Saramacca, Coronie [District: Suriname] 740006 Marowijne, Commewijne [District: Suriname] 740008 Brokopondo, Para [District: Suriname] 740010 Sipaliwini [District: Suriname] 740096 Suriname, district unknown [District: Suriname] 740097 Foreign [District: Suriname] 740098 Unknown [District: Suriname] 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 Sa Kaeo, Prachin Buri [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, Amnat Charoen [Province: Thailand] 764036 Chaiyaphum [Province: Thailand] 764039 Nong Bua Lam Phu, Udon Thani [Province: Thailand] 764040 Khon Kaen [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, 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 Phayao, Chiang Rai [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] 764082 Phangnga [Province: Thailand] 764083 Phuket [Province: Thailand] 764084 Krabi, Surat Thani [Province: Thailand] 764086 Ranong, 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] 764097 Same province [Province: Thailand] 764098 Unknown province, but within Thaliand [Province: Thailand] 764997 Abroad [Province: Thailand] 764998 Unknown [Province: Thailand] 764999 NIU (not in universe) [Province: Thailand] 768001 Maritime, Lomé [Region: Togo] 768002 Plateaux, Centrale, Kara [Region: Togo] 768003 Savanes [Region: Togo] 768097 Foreign Country [Region: Togo] 768098 Unknown [Region: Togo] 768099 NIU [Region: Togo] 780010 Port of Spain [Region: Trinidad and Tobago] 780020 San Fernando [Region: Trinidad and Tobago] 780080 Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] 780094 St. Paul, St. Mary, St. David, St. George, St. Patrick, St. Andrew, St. John, Tobago [Region: Trinidad and Tobago] 780098 Unknown [Region: Trinidad and Tobago] 800101 Kalangala [District: Uganda] 800102 Kampala [District: Uganda] 800103 Kiboga, Kyankwanzi [District: Uganda] 800104 Luwero, Nakasongola, Nakaseke [District: Uganda] 800105 Masaka, Ssembabule, Bukomansimbi, Kalungu, Lwengo [District: Uganda] 800106 Mpigi, Wakiso, Butambala, Gomba [District: Uganda] 800107 Mubende, Mityana [District: Uganda] 800108 Mukono, Kayunga, Buikwe, Buvuma [District: Uganda] 800110 Rakai, Lyantonde [District: Uganda] 800201 Bugiri, Iganga, Mayuge, Namutumba, Luuka, Namayingo [District: Uganda] 800202 Busia, Tororo, Butaleja [District: Uganda] 800204 Jinja [District: Uganda] 800205 Kamuli, Kaliro, Buyende [District: Uganda] 800206 Kapchorwa, Bukwo, Kween [District: Uganda] 800207 Katakwi, Soroti, Kaberamaido, Amuria, Serere [District: Uganda] 800208 Kumi, Bukedea, Ngora [District: Uganda] 800209 Mbale, Sironko, Bududa, Manafwa, Bulambuli [District: Uganda] 800210 Pallisa, Budaka, Kibuku [District: Uganda] 800301 Adjumani, Moyo [District: Uganda] 800302 Apac, Oyam, Kole [District: Uganda] 800303 Arua, Yumbe, Koboko, Maracha [District: Uganda] 800304 Gulu, Amuru, Nwoya, Omoro [District: Uganda] 800305 Kitgum, Pader, Agago, Lamwo [District: Uganda] 800306 Kotido, Moroto, Nakapiripirit, Abim, Kaabong, Amudat, Napak [District: Uganda] 800307 Lira, Amolatar, Dokolo, Alebtong, Otuke [District: Uganda] 800310 Nebbi, Zombo [District: Uganda] 800401 Bundibugyo, Ntoroko [District: Uganda] 800402 Bushenyi, Mbarara, Ntungamo, Ibanda, Isingiro, Kiruhura, Buhweju, Mitooma, Rubirizi, Sheema [District: Uganda] 800403 Hoima [District: Uganda] 800404 Kabale, Rubanda [District: Uganda] 800405 Kabarole, Kamwenge, Kyenjojo, Kyegegwa [District: Uganda] 800406 Kasese [District: Uganda] 800407 Kibaale, Kagadi, Kakumiro [District: Uganda] 800408 Kisoro [District: Uganda] 800409 Masindi, Buliisa, Kiryandongo [District: Uganda] 800412 Rukungiri, Kanungu [District: Uganda] 800096 Visitor [District: Uganda] 800097 Foreign country [District: Uganda] 800098 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 (independent city) [Region: Ukraine] 804085 Sevastopol (independent city) [Region: Ukraine] 804097 Foreign country [Region: Ukraine] 804098 Unknown [Region: Ukraine] 804099 NIU (not in universe) [Region: Ukraine] 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] 858097 Abroad [Department: Uruguay] 858098 Unknown [Department: Uruguay] 858999 NIU (not in universe) [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] 862097 Foreign country [State: Venezuela] 862098 Unknown [State: Venezuela] 862099 NIU (not in universe) [State: Venezuela] Migration: Global Variables -- PERSON 1st subnational geographic level of residence 5 years prior to survey, world [consistent boundaries over time] GEOMIG1_5 indicates the major administrative unit in which the person resided five years prior to the survey. Only intra-national migrations are recorded; however, the variable incorporates geographies for every country that lists place of residence five years ago, to enable comparative analysis of subnational migration. Foreign migrants are coded 097 or 997. Codes for GEOMIG1_5 match the geographic codes in GEOLEV1 (current place of residence). For similar information for different time intervals since migration, see variables GEOMIG1_P, GEOMIG1_1, and GEOMIG1_10. More on migration and geography can be found here. 032002 City of Buenos Aires [Province: Argentina] 032006 Buenos Aires province [Province: Argentina] 032010 Catamarca [Province: Argentina] 032014 Córdoba [Province: Argentina] 032018 Corrientes [Province: Argentina] 032022 Chaco [Province: Argentina] 032026 Chubut [Province: Argentina] 032030 Entre Ríos [Province: Argentina] 032034 Formosa [Province: Argentina] 032038 Jujuy [Province: Argentina] 032042 La Pampa [Province: Argentina] 032046 La Rioja [Province: Argentina] 032050 Mendoza [Province: Argentina] 032054 Misiones [Province: Argentina] 032058 Neuquén [Province: Argentina] 032062 Río Negro [Province: Argentina] 032066 Salta [Province: Argentina] 032070 San Juan [Province: Argentina] 032074 San Luis [Province: Argentina] 032078 Santa Cruz [Province: Argentina] 032082 Santa Fe [Province: Argentina] 032086 Santiago del Estero [Province: Argentina] 032090 Tucumán [Province: Argentina] 032094 Tierra del Fuego [Province: Argentina] 032096 Argentina, unknown [Province: Argentina] 032097 Foreign country [Province: Argentina] 032098 Unknown [Province: Argentina] 032999 NIU (not in universe) [Province: Argentina] 068001 Chuquisaca [Department: Bolivia] 068002 La Paz [Department: Bolivia] 068003 Cochabamba [Department: Bolivia] 068004 Oruro [Department: Bolivia] 068005 Potosí [Department: Bolivia] 068006 Tarija [Department: Bolivia] 068007 Santa Cruz [Department: Bolivia] 068008 Beni [Department: Bolivia] 068009 Pando [Department: Bolivia] 068096 Bolivia, province unknown [Department: Bolivia] 068097 Foreign country [Department: Bolivia] 068098 Unknown [Department: Bolivia] 068099 NIU (not in universe) [Department: Bolivia] 072001 Gaborone [District: Botswana] 072002 Francistown [District: Botswana] 072003 Lobatse [District: Botswana] 072004 Selebi Phikwe [District: Botswana] 072007 Central Tutume, Sowa [District: Botswana] 072010 Ngwaketse, Ngwaketse West, Ngwaketse Southern, Southern, Jwaneng [District: Botswana] 072011 Borolong [District: Botswana] 072020 South East [District: Botswana] 072030 Kweneng, Kweneng South, Kweneng North [District: Botswana] 072040 Kgatleng [District: Botswana] 072050 Central Serowe/Palapye [District: Botswana] 072051 Central Mahalapye [District: Botswana] 072052 Central Bobonong [District: Botswana] 072053 Central Boteti, Orapa [District: Botswana] 072060 North East [District: Botswana] 072070 Ngamiland East [District: Botswana] 072071 Ngamiland West, Delta [District: Botswana] 072072 Chobe [District: Botswana] 072080 Ghanzi, Central Kgalagadi Game Reserve (CKGR) [District: Botswana] 072090 Tshabong (Kgalagadi South) [District: Botswana] 072091 Hukunsti (Kgalagadi North) [District: Botswana] 072092 Botswana, district unknown [District: Botswana] 072097 Abroad [District: Botswana] 072098 Unknown [District: Botswana] 072099 NIU (not in universe) [District: Botswana] 076011 Rondônia [State: Brazil] 076012 Acre [State: Brazil] 076013 Amazonas [State: Brazil] 076014 Roraima [State: Brazil] 076015 Pará [State: Brazil] 076016 Amapá [State: Brazil] 076021 Maranhão [State: Brazil] 076022 Piauí [State: Brazil] 076023 Ceará [State: Brazil] 076024 Rio Grande do Norte [State: Brazil] 076025 Paraíba [State: Brazil] 076026 Pernambuco, Arquipelago de Fernando de Noronha [State: Brazil] 076027 Alagoas [State: Brazil] 076028 Sergipe [State: Brazil] 076029 Bahia [State: Brazil] 076031 Minas Gerais [State: Brazil] 076032 Espírito Santo [State: Brazil] 076033 Rio de Janeiro, Guanabara [State: Brazil] 076035 São Paulo [State: Brazil] 076036 Serra dos Aimorés [State: Brazil] 076041 Paraná [State: Brazil] 076042 Santa Catarina [State: Brazil] 076043 Rio Grande do Sul [State: Brazil] 076051 Mato Grosso do Sul, Mato Grosso [State: Brazil] 076052 Goiás, Tocantins [State: Brazil] 076053 Distrito Federal [State: Brazil] 076054 Brazil, unspecified [State: Brazil] 076097 Abroad [State: Brazil] 076098 Unknown [State: Brazil] 076099 NIU (not in universe) [State: Brazil] 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] 120096 Cameroon - unknown arrondissement [Province: Cameroon] 120097 Foreign country [Province: Cameroon] 120098 Unknown [Province: Cameroon] 120099 NIU (not in universe) [Province: Cameroon] 124010 Newfoundland and Labrador [Province: Canada] 124011 Prince Edward Island, Yukon Territory, Northwest Territories, 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] 124099 NIU (not in universe) [Province: Canada] 152014 Iquique, Tamarugal [Province: Chile] 152021 Antofagasta [Province: Chile] 152022 El Loa [Province: Chile] 152023 Tocopilla [Province: Chile] 152031 Copiapó [Province: Chile] 152032 Chañaral [Province: Chile] 152033 Huasco [Province: Chile] 152041 Elqui [Province: Chile] 152042 Choapa [Province: Chile] 152043 Limarí [Province: Chile] 152051 Valparaíso, Quillota, Marga Marga, Isla de Pascua [Province: Chile] 152053 Los Andes [Province: Chile] 152054 Petorca [Province: Chile] 152056 San Antonio [Province: Chile] 152057 San Felipe de Aconcagüa [Province: Chile] 152061 Cachapoal [Province: Chile] 152062 Cardenal Caro [Province: Chile] 152063 Colchagua [Province: Chile] 152071 Talca [Province: Chile] 152072 Cauquenes [Province: Chile] 152073 Curicó [Province: Chile] 152074 Linares [Province: Chile] 152081 Concepción [Province: Chile] 152082 Arauco [Province: Chile] 152083 Biobío [Province: Chile] 152091 Cautín [Province: Chile] 152092 Malleco [Province: Chile] 152101 Llanquihue [Province: Chile] 152102 Chiloé, Palena [Province: Chile] 152103 Osorno [Province: Chile] 152111 Coihaique [Province: Chile] 152112 Aisén, General Carrera, Capitan Prat [Province: Chile] 152121 Magallanes, Tierra del Fuego, Antártica Chilena [Province: Chile] 152124 Última Esperanza [Province: Chile] 152131 Santiago [Province: Chile] 152132 Cordillera [Province: Chile] 152133 Chacabuco [Province: Chile] 152134 Maipo [Province: Chile] 152135 Melipilla [Province: Chile] 152136 Talagante [Province: Chile] 152141 Valdivia, Ranco [Province: Chile] 152151 Arica, Parinacota [Province: Chile] 152163 Diguillín, Itata, Punilla [Province: Chile] 152997 Foreign country [Province: Chile] 152998 Unknown [Province: Chile] 152999 NIU (not in universe) [Province: Chile] 156011 Beijing [Province: China] 156012 Tianjin [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 [Province: China] 156032 Jiangsu [Province: China] 156033 Zhejiang [Province: China] 156034 Anhui [Province: China] 156035 Fujian [Province: China] 156036 Jiangxi [Province: China] 156037 Shandong [Province: China] 156041 Henan [Province: China] 156042 Hubei [Province: China] 156043 Hunan [Province: China] 156044 Guangdong, Hainan [Province: China] 156045 Guangxi [Province: China] 156051 Sichuan, Chongqing [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] 156071 Taiwan [China] 156072 Hong Kong [China] 156073 Macao [China] 156097 Other countries [Province: China] 156099 NIU (not in universe) [Province: China] 170005 Antioquia [Department: Colombia] 170008 Atlántico [Department: Colombia] 170011 Bogotá D.C., Cundinamarca [Department: Colombia] 170013 Bolívar, Sucre [Department: Colombia] 170015 Boyacá, Casanare [Department: Colombia] 170018 Caquetá [Department: Colombia] 170019 Cauca [Department: Colombia] 170023 Córdoba [Department: Colombia] 170027 Chocó [Department: Colombia] 170041 Huila [Department: Colombia] 170044 La Guajira [Department: Colombia] 170050 Meta [Department: Colombia] 170052 Nariño [Department: Colombia] 170054 Cesar, Norte De Santander, Magdalena [Department: Colombia] 170066 Caldas, Quindío, Risaralda [Department: Colombia] 170068 Santander [Department: Colombia] 170073 Tolima [Department: Colombia] 170076 Valle Del Cauca [Department: Colombia] 170081 Arauca [Department: Colombia] 170086 Putumayo [Department: Colombia] 170088 Archipiélago De San Andrés Y Providencia [Department: Colombia] 170095 Amazonas, Guaviare, Vaupés, Vichada, Guainía [Department: Colombia] 170097 Abroad, [Department: Colombia] 170098 Unknown, [Department: Colombia] 170099 NIU (not in universe), [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] 188097 Foreign country [Province: Costa Rica] 188098 Unknown [Province: Costa Rica] 188099 NIU (not in universe) [Province: Costa Rica] 214001 Distrito Nacional, Santo Domingo [Province: Dominican Republic] 214002 Azua [Province: Dominican Republic] 214003 Baoruco, Barahona, Independencia [Province: Dominican Republic] 214005 Dajabón [Province: Dominican Republic] 214006 Duarte [Province: Dominican Republic] 214007 Elías Piña [Province: Dominican Republic] 214008 El Seibo, Hato Mayor [Province: Dominican Republic] 214009 Espaillat [Province: Dominican Republic] 214011 La Altagracia, La Romana [Province: Dominican Republic] 214013 Monseñor Nouel, La Vega [Province: Dominican Republic] 214014 María Trinidad Sánchez [Province: Dominican Republic] 214015 Monte Cristi [Province: Dominican Republic] 214016 Pedernales [Province: Dominican Republic] 214017 San José de Ocoa, Peravia [Province: Dominican Republic] 214018 Puerto Plata, Santiago [Province: Dominican Republic] 214019 Hermanas Mirabal [Province: Dominican Republic] 214020 Samaná [Province: Dominican Republic] 214021 San Cristóbal, 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] 214026 Santiago Rodríguez [Province: Dominican Republic] 214027 Valverde [Province: Dominican Republic] 214097 Foreign country [Province: Dominican Republic] 214098 Unknown [Province: Dominican Republic] 214099 NIU (not in universe) [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 [Province: Ecuador] 218010 Imbabura, Las Golondrinas [Disputed canton] [Province: Ecuador] 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] 218097 Foreign country [Province: Ecuador] 218098 Unknown and Disputed Zones [Province: Ecuador] 218999 NIU (not in universe) [Province: Ecuador] 242001 Central [Province: Fiji] 242002 Eastern [Province: Fiji] 242003 Northern [Province: Fiji] 242004 Western [Province: Fiji] 242097 Foreign country [Province: Fiji] 242098 Unknown [Province: Fiji] 242999 NIU (not in universe) [Province: Fiji] 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] 288098 Unknown [Region: Ghana] 288099 NIU (not in universe) [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 Agion 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] 300996 Foreign country [Department: Greece] 300997 Response suppressed [Department: Greece] 300998 Unknown [Department: Greece] 300999 NIU (not in universe) [Department: Greece] 320001 Guatemala [Department: Guatemala] 320002 El Progreso [Department: Guatemala] 320003 Sacatepéquez [Department: Guatemala] 320004 Chimaltenango [Department: Guatemala] 320005 Escuintla [Department: Guatemala] 320006 Santa Rosa [Department: Guatemala] 320007 Sololá [Department: Guatemala] 320008 Totonicapán [Department: Guatemala] 320009 Quetzaltenango [Department: Guatemala] 320010 Suchitepéquez [Department: Guatemala] 320011 Retalhuleu [Department: Guatemala] 320012 San Marcos [Department: Guatemala] 320013 Huehuetenango [Department: Guatemala] 320014 Quiché [Department: Guatemala] 320015 Baja Verapaz [Department: Guatemala] 320016 Alta Verapaz [Department: Guatemala] 320017 Petén [Department: Guatemala] 320018 Izabal [Department: Guatemala] 320019 Zacapa [Department: Guatemala] 320020 Chiquimula [Department: Guatemala] 320021 Jalapa [Department: Guatemala] 320022 Jutiapa [Department: Guatemala] 320097 Foreign Country [Department: Guatemala] 320098 Unknown [Department: Guatemala] 320099 NIU [Department: Guatemala] 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] 332097 Foreign Country [Department: Haiti] 332098 Unknown [Department: Haiti] 332099 NIU (not in universe) [Department: Haiti] 340001 Atlántida [Department: Honduras] 340002 Colón [Department: Honduras] 340003 Comayagua [Department: Honduras] 340004 Copán [Department: Honduras] 340005 Cortés [Department: Honduras] 340006 Choluteca [Department: Honduras] 340007 El Paraíso [Department: Honduras] 340008 Francisco Morazán [Department: Honduras] 340009 Gracias a Dios [Department: Honduras] 340010 Intibucá [Department: Honduras] 340011 Islas de la Bahía [Department: Honduras] 340012 La Paz [Department: Honduras] 340013 Lempira [Department: Honduras] 340014 Ocotepeque [Department: Honduras] 340015 Olancho [Department: Honduras] 340016 Santa Bárbara [Department: Honduras] 340017 Valle [Department: Honduras] 340018 Yoro [Department: Honduras] 340097 Abroad [Department: Honduras] 340098 Unknown [Department: Honduras] 340999 NIU (not in universe) [Department: Honduras] 360011 Nanggroe Aceh Darussalam [Province: Indonesia] 360012 Sumatera Utara [Province: Indonesia] 360013 Sumatera Barat [Province: Indonesia] 360014 Kepulauan Riau, Riau [Province: Indonesia] 360015 Jambi [Province: Indonesia] 360016 Bangka Belitung, Sumatera Selatan [Province: Indonesia] 360017 Bengkulu [Province: Indonesia] 360018 Lampung [Province: Indonesia] 360031 DKI Jakarta [Province: Indonesia] 360032 Banten, Jawa Barat [Province: Indonesia] 360033 Jawa Tengah [Province: Indonesia] 360034 DKI Yogyakarta [Province: Indonesia] 360035 Jawa Timur [Province: Indonesia] 360051 Bali [Province: Indonesia] 360052 Nusa Tenggara Barat [Province: Indonesia] 360053 Nusa Tenggara Timur [Province: Indonesia] 360061 Kalimantan Barat [Province: Indonesia] 360062 Kalimantan Tengah [Province: Indonesia] 360063 Kalimantan Selatan [Province: Indonesia] 360064 Kalimantan Timur [Province: Indonesia] 360071 Gorontalo, Sulawesi Utara [Province: Indonesia] 360072 Sulawesi Tengah [Province: Indonesia] 360073 Sulawesi Barat, Sulawesi Selatan [Province: Indonesia] 360074 Sulawesi Tenggara [Province: Indonesia] 360081 Maluku, Maluku Utara [Province: Indonesia] 360094 Papua, Papua Barat [Province: Indonesia] 360097 Abroad [Province: Indonesia] 360098 Unknown [Province: Indonesia] 360099 NIU (not in universe) [Province: Indonesia] 360626 East Timor [Province: Indonesia] 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] 376071 Golan [District: Israel] 376072 Judea, Samaria and Gaza areas [District: Israel] 376098 Unknown [District: Israel] 376099 NIU (not in universe) [District: Israel] 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, Kuala Lumpur Federal Territory [State: Malaysia] 458011 Terengganu [State: Malaysia] 458012 Sabah, Labuan Federal Territory [State: Malaysia] 458013 Sarawak [State: Malaysia] 458097 Other countries [State: Malaysia] 458098 Unknown [State: Malaysia] 480011 Port Louis [District: Mauritius] 480012 Pamplemousses [District: Mauritius] 480013 Rivière du Rempart [District: Mauritius] 480014 Flacq [District: Mauritius] 480015 Grand Port [District: Mauritius] 480016 Savanne [District: Mauritius] 480017 Plaines Wilhems [District: Mauritius] 480018 Moka [District: Mauritius] 480019 Black River [District: Mauritius] 480020 Rodrigues, Agaléga Islands, Saint Brandon [District: Mauritius] 480097 Abroad [District: Mauritius] 480098 Unknown [District: Mauritius] 480099 NIU [District: Mauritius] 484001 Aguascalientes [State: Mexico] 484002 Baja California [State: Mexico] 484003 Baja California Sur [State: Mexico] 484004 Campeche [State: Mexico] 484005 Coahuila de Zaragoza [State: Mexico] 484006 Colima [State: Mexico] 484007 Chiapas [State: Mexico] 484008 Chihuahua [State: Mexico] 484009 Distrito Federal [State: Mexico] 484010 Durango [State: Mexico] 484011 Guanajuato [State: Mexico] 484012 Guerrero [State: Mexico] 484013 Hidalgo [State: Mexico] 484014 Jalisco [State: Mexico] 484015 México [State: Mexico] 484016 Michoacán de Ocampo [State: Mexico] 484017 Morelos [State: Mexico] 484018 Nayarit [State: Mexico] 484019 Nuevo León [State: Mexico] 484020 Oaxaca [State: Mexico] 484021 Puebla [State: Mexico] 484022 Querétaro [State: Mexico] 484023 Quintana Roo [State: Mexico] 484024 San Luis Potosí [State: Mexico] 484025 Sinaloa [State: Mexico] 484026 Sonora [State: Mexico] 484027 Tabasco [State: Mexico] 484028 Tamaulipas [State: Mexico] 484029 Tlaxcala [State: Mexico] 484030 Veracruz de Ignacio de la Llave [State: Mexico] 484031 Yucatán [State: Mexico] 484032 Zacatecas [State: Mexico] 484097 Abroad [State: Mexico] 484098 Unknown [State: Mexico] 484099 NIU (not in universe) [State: Mexico] 496011 Ulaanbaatar [Province: Mongolia] 496021 Dornod [Province: Mongolia] 496022 Sukhbaatar [Province: Mongolia] 496023 Khentii [Province: Mongolia] 496041 Tuv [Province: Mongolia] 496043 Selenge [Province: Mongolia] 496044 Dornogobi [Province: Mongolia] 496045 Darkhan-Uul [Province: Mongolia] 496046 Umnugobi [Province: Mongolia] 496048 Dundgobi, Gobisumber [Province: Mongolia] 496061 Orkhon [Province: Mongolia] 496062 Uvurkhangai [Province: Mongolia] 496063 Bulgan [Province: Mongolia] 496064 Bayankhongor [Province: Mongolia] 496065 Arkhangai [Province: Mongolia] 496067 Khuvsgul [Province: Mongolia] 496081 Zavkhan [Province: Mongolia] 496082 Gobi-Altai [Province: Mongolia] 496083 Bayan-Ulgii [Province: Mongolia] 496084 Khovd [Province: Mongolia] 496085 Uvs [Province: Mongolia] 496097 Abroad [Province: Mongolia] 496098 Unknown [Province: Mongolia] 496099 NIU (not in universe) [Province: Mongolia] 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: Mozambique] 508011 Cidade de Maputo [Province: Mozambique] 508097 Foreign Country [Province: Mozambique] 508098 Unknown [Province: Mozambique] 508099 NIU (not in universe) [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] 524097 Foreign Country [Administrative Zone: Nepal] 524098 Unknown [Administrative Zone: Nepal] 524099 NIU [Administrative Zone: Nepal] 558005 Nueva Segovia, Jinotega [Department: Nicaragua] 558020 Madriz [Department: Nicaragua] 558025 Estelí, León [Department: Nicaragua] 558030 Chinandega [Department: Nicaragua] 558040 Matagalpa, Atlantico Norte, Atlantico Sur, Zelaya [Department: Nicaragua] 558050 Boaco [Department: Nicaragua] 558055 Managua, 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] 558097 Abroad [Department: Nicaragua] 558098 Unknown [Department: Nicaragua] 558999 NIU (not in universe) [Department: Nicaragua] 598001 Western [Province: Papua New Guinea] 598002 Gulf [Province: Papua New Guinea] 598003 Central [Province: Papua New Guinea] 598004 National Capital District [Province: Papua New Guinea] 598005 Milne Bay [Province: Papua New Guinea] 598006 Northern [Province: Papua New Guinea] 598007 Southern Highlands, Hela [Province: Papua New Guinea] 598008 Enga [Province: Papua New Guinea] 598009 Western Highlands, Jiwaka [Province: Papua New Guinea] 598010 Chimbu [Province: Papua New Guinea] 598011 Eastern Highlands [Province: Papua New Guinea] 598012 Morobe [Province: Papua New Guinea] 598013 Madang [Province: Papua New Guinea] 598014 East Sepik [Province: Papua New Guinea] 598015 West Sepik [Province: Papua New Guinea] 598016 Manus [Province: Papua New Guinea] 598017 New Ireland [Province: Papua New Guinea] 598018 East New Britain [Province: Papua New Guinea] 598019 West New Britain [Province: Papua New Guinea] 598020 Autonomous Region of Bougainville [Province: Papua New Guinea] 598097 Foreign country [Province: Papua New Guinea] 598098 Unknown [Province: Papua New Guinea] 598099 NIU (not in universe) [Province: Papua New Guinea] 600001 Concepción [Department: Paraguay] 600002 San Pedro [Department: Paraguay] 600003 Cordillera [Department: Paraguay] 600004 Guaira [Department: Paraguay] 600005 Caaguazú, Canindeyú, Alto Paraná [Department: Paraguay] 600006 Caazapá [Department: Paraguay] 600007 Itapúa [Department: Paraguay] 600008 Misiones, Ñeembucú [Department: Paraguay] 600009 Paraguarí [Department: Paraguay] 600011 Central [Department: Paraguay] 600013 Amambay [Department: Paraguay] 600015 Alto Paraguay, Boquerón, Presidente Hayes [Department: Paraguay] 600019 Asunción [Department: Paraguay] 600097 Foreign Country [Department: Paraguay] 600098 Unknown [Department: Paraguay] 600999 NIU (not in universe) [Department: Paraguay] 604001 Amazonas [Department: Peru] 604002 Ancash [Department: Peru] 604003 Apurímac [Department: Peru] 604004 Arequipa [Department: Peru] 604005 Ayacucho [Department: Peru] 604006 Cajamarca [Department: Peru] 604007 Callao [Department: Peru] 604008 Cusco [Department: Peru] 604009 Huancavelica [Department: Peru] 604010 Huánuco [Department: Peru] 604011 Ica [Department: Peru] 604012 Junín [Department: Peru] 604013 La Libertad [Department: Peru] 604014 Lambayeque [Department: Peru] 604015 Lima [Department: Peru] 604016 Loreto [Department: Peru] 604017 Madre de Dios [Department: Peru] 604018 Moquegua [Department: Peru] 604019 Pasco [Department: Peru] 604020 Piura [Department: Peru] 604021 Puno [Department: Peru] 604022 San Martín [Department: Peru] 604023 Tacna [Department: Peru] 604024 Tumbes [Department: Peru] 604025 Ucayali [Department: Peru] 604097 Abroad [Department: Peru] 604099 NIU (not in universe) [Department: Peru] 608001 Abra [Province: Philippines] 608002 Agusan del norte [Province: Philippines] 608003 Agusan del sur [Province: Philippines] 608004 Aklan [Province: Philippines] 608005 Albay [Province: Philippines] 608006 Antique [Province: Philippines] 608007 Basilan, City Of Isabela [Province: Philippines] 608008 Bataan [Province: Philippines] 608010 Batangas [Province: Philippines] 608011 Benguet [Province: Philippines] 608012 Bohol [Province: Philippines] 608013 Bukidnon [Province: Philippines] 608014 Bulacan [Province: Philippines] 608015 Cagayan, Batanes [Province: Philippines] 608016 Camarines norte [Province: Philippines] 608017 Camarines Sur [Province: Philippines] 608018 Camiguin [Province: Philippines] 608019 Capiz [Province: Philippines] 608020 Catanduanes [Province: Philippines] 608021 Cavite [Province: Philippines] 608022 Cebu [Province: Philippines] 608023 Davao (Davao del Norte) [Province: Philippines] 608024 Davao del Sur, Davao Occidental [Province: Philippines] 608025 Davao Oriental [Province: Philippines] 608026 Eastern Samar [Province: Philippines] 608027 Ifugao [Province: Philippines] 608028 Ilocos Norte [Province: Philippines] 608029 Ilocos Sur [Province: Philippines] 608030 Iloilo, Guimaras [Province: Philippines] 608031 Isabela [Province: Philippines] 608032 Kalinga-Apayao, Apayo, Kalinga [Province: Philippines] 608033 La Union [Province: Philippines] 608034 Laguna [Province: Philippines] 608035 Lanao del Norte [Province: Philippines] 608036 Lanao del Sur, Maguindanao, Marawi City and Cotabato city [Province: Philippines] 608037 Leyte, Biliran [Province: Philippines] 608039 Manila [Province: Philippines] 608040 Marinduque [Province: Philippines] 608041 Masbate [Province: Philippines] 608042 Misamis Occidental [Province: Philippines] 608043 Misamis Oriental [Province: Philippines] 608044 Mountain Province [Province: Philippines] 608045 Negros Occidental [Province: Philippines] 608046 Negros Oriental [Province: Philippines] 608047 Cotabato (North Cotabato) [Province: Philippines] 608048 Northern Samar [Province: Philippines] 608049 Nueva Ecija [Province: Philippines] 608050 Nueva Vizcaya [Province: Philippines] 608051 Occidental Mindoro [Province: Philippines] 608052 Oriental Mindoro [Province: Philippines] 608053 Palawan [Province: Philippines] 608054 Pampanga [Province: Philippines] 608055 Pangasinan [Province: Philippines] 608056 Quezon [Province: Philippines] 608057 Quirino [Province: Philippines] 608058 Rizal [Province: Philippines] 608059 Romblon [Province: Philippines] 608060 Samar (Western Samar) [Province: Philippines] 608061 Siquijor [Province: Philippines] 608062 Sorsogon [Province: Philippines] 608063 South Cotabato, Sarangani [Province: Philippines] 608064 Southern Leyte [Province: Philippines] 608065 Sultan Kudarat [Province: Philippines] 608066 Sulu [Province: Philippines] 608067 Surigao Del Norte, Dinagat islands [Province: Philippines] 608068 Surigao del Sur [Province: Philippines] 608069 Tarlac [Province: Philippines] 608070 Tawi-Tawi [Province: Philippines] 608071 Zambales [Province: Philippines] 608072 Zamboanga Norte [Province: Philippines] 608073 Zamboanga del Sur, Zamboanga Sibugay [Province: Philippines] 608074 Manila Metro, 2nd District [Province: Philippines] 608075 Manila Metro, 3rd District [Province: Philippines] 608076 Manila Metro, 4th District [Province: Philippines] 608077 Aurora [Province: Philippines] 608097 Foreign country [Province: Philippines] 608098 Unknown [Province: Philippines] 608099 NIU (not in universe) [Province: Philippines] 620111 Minho-Lima [Subregion (NUTS-3): Portugal] 620112 Cávado [Subregion (NUTS-3): Portugal] 620113 Ave [Subregion (NUTS-3): Portugal] 620114 Grande Porto [Subregion (NUTS-3): Portugal] 620115 Tâmega [Subregion (NUTS-3): Portugal] 620116 Entre Douro e Vouga [Subregion (NUTS-3): Portugal] 620117 Douro [Subregion (NUTS-3): Portugal] 620118 Alto Trás-os-Montes [Subregion (NUTS-3): Portugal] 620150 Algarve [Subregion (NUTS-3): Portugal] 620161 Baixo Vouga [Subregion (NUTS-3): Portugal] 620162 Baixo Mondego [Subregion (NUTS-3): Portugal] 620163 Pinhal Litoral [Subregion (NUTS-3): Portugal] 620165 Dão-Lafões [Subregion (NUTS-3): Portugal] 620166 Oeste [Subregion (NUTS-3): Portugal] 620167 Médio Tejo [Subregion (NUTS-3): Portugal] 620169 Other Center [Subregion (NUTS-3): Portugal] 620171 Grande Lisboa [Subregion (NUTS-3): Portugal] 620172 Península de Setúbal [Subregion (NUTS-3): Portugal] 620185 Lezíria do Tejo [Subregion (NUTS-3): Portugal] 620189 Other Alentejo [Subregion (NUTS-3): Portugal] 620200 Região Autónoma dos Açores [Subregion (NUTS-3): Portugal] 620300 Região Autónoma da Madeira [Subregion (NUTS-3): Portugal] 620998 Foreign country [Subregion (NUTS-3): Portugal] 620999 NIU (not in universe) [Subregion (NUTS-3): Portugal] 686001 Dakar [Region: Senegal] 686002 Ziguinchor [Region: Senegal] 686003 Diourbel [Region: Senegal] 686004 Saint Louis, Louga, Matam [Region: Senegal] 686005 Tambacounda, Kedougou [Region: Senegal] 686006 Kaolack, Fatick, Kaffrine [Region: Senegal] 686007 Thiès [Region: Senegal] 686010 Kolda, Sedhiou [Region: Senegal] 686097 Abroad [Region: Senegal] 686098 Unknown [Region: Senegal] 686099 NIU (not in universe) [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] 694097 Abroad [District: Sierra Leone] 694098 Unknown [District: Sierra Leone] 694099 NIU [District: Sierra Leone] 704001 Thành Phố Hà Nội, Vĩnh Phúc, Hoà Bình, Phú Thọ [Province: Vietnam] 704002 Hà Giang, Tuyên Quang [Province: Vietnam] 704003 Cao Bằng, Bắc Kạn, Thái Nguyên [Province: Vietnam] 704010 Lào Cai, Điện Biên, Lai Châu, Yên Bái [Province: Vietnam] 704014 Sơn La [Province: Vietnam] 704020 Lạng Sơn [Province: Vietnam] 704022 Quảng Ninh [Province: Vietnam] 704024 Bắc Giang, Bắc Ninh [Province: Vietnam] 704030 Hải Dương, Hưng Yên [Province: Vietnam] 704031 Thành Phố Hải Phòng [Province: Vietnam] 704034 Thái Bình [Province: Vietnam] 704035 Hà Nam, Nam Định, Ninh Bình [Province: Vietnam] 704038 Thanh Hoá [Province: Vietnam] 704040 Nghệ An, Hà Tĩnh [Province: Vietnam] 704044 Quảng Bình [Province: Vietnam] 704045 Quảng Trị [Province: Vietnam] 704046 Thừa Thiên Huế [Province: Vietnam] 704048 Thành Phố Đà Nẵng, Quảng Nam [Province: Vietnam] 704051 Quảng Ngãi [Province: Vietnam] 704052 Bình Định [Province: Vietnam] 704054 Phú Yên [Province: Vietnam] 704056 Khánh Hoà [Province: Vietnam] 704058 Ninh Thuận, Bình Thuận [Province: Vietnam] 704062 Kon Tum, Gia Lai [Province: Vietnam] 704066 Đắk Lắk, Đắk Nông [Province: Vietnam] 704068 Lâm Đồng [Province: Vietnam] 704070 Bình Phước, Bình Dương [Province: Vietnam] 704072 Tây Ninh [Province: Vietnam] 704075 Đồng Nai, Bà Rịa - Vũng Tàu [Province: Vietnam] 704079 Thành Phố Hồ Chí Minh [Province: Vietnam] 704080 Long An [Province: Vietnam] 704082 Tiền Giang [Province: Vietnam] 704083 Bến Tre [Province: Vietnam] 704084 Trà Vinh, Vĩnh Long [Province: Vietnam] 704087 Đồng Tháp [Province: Vietnam] 704089 An Giang [Province: Vietnam] 704091 Kiên Giang [Province: Vietnam] 704092 Thành Phố Cần Thơ, Hậu Giang, Sóc Trăng [Province: Vietnam] 704095 Bạc Liêu, Cà Mau [Province: Vietnam] 704097 Foreign Country [Province: Vietnam] 704098 Unknown [Province: Vietnam] 704099 NIU [Province: Vietnam] 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] 710097 Foreign country [Province: South Africa] 710098 Unknown [Province: South Africa] 710099 NIU (not in universe) [Province: South Africa] 724011 Galicia [Communities & autonomous city: Spain] 724012 Principado de Asturias [Communities & autonomous city: Spain] 724013 Cantabria [Communities & autonomous city: Spain] 724021 País Vasco [Communities & autonomous city: Spain] 724022 Comunidad Foral de Navarra [Communities & autonomous city: Spain] 724023 La Rioja [Communities & autonomous city: Spain] 724024 Aragón [Communities & autonomous city: Spain] 724030 Comunidad de Madrid [Communities & autonomous city: Spain] 724041 Castilla y León [Communities & autonomous city: Spain] 724042 Castilla-La Mancha [Communities & autonomous city: Spain] 724043 Extremadura [Communities & autonomous city: Spain] 724051 Cataluña [Communities & autonomous city: Spain] 724052 Comunidad Valenciana [Communities & autonomous city: Spain] 724053 Islas Baleares [Communities & autonomous city: Spain] 724061 Andalucía [Communities & autonomous city: Spain] 724062 Región de Murcia [Communities & autonomous city: Spain] 724063 Ciudad Autónoma de Ceuta [Communities & autonomous city: Spain] 724064 Ciudad Autónoma de Melilla [Communities & autonomous city: Spain] 724070 Canarias [Communities & autonomous city: Spain] 724097 Foreign country [Communities & autonomous city: Spain] 724999 NIU [Communities & autonomous city: Spain] 780010 Port of Spain [Region: Trinidad and Tobago] 780020 San Fernando [Region: Trinidad and Tobago] 780080 Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] 780094 St. Paul, St. Mary, St. David, St. George, St. Patrick, St. Andrew, St. John, Tobago [Region: Trinidad and Tobago] 780098 Unknown [Region: Trinidad and Tobago] 780099 NIU (not in universe) [Region: Trinidad and Tobago] 840001 Alabama [State: United States] 840002 Alaska [State: United States] 840004 Arizona [State: United States] 840005 Arkansas [State: United States] 840006 California [State: United States] 840008 Colorado [State: United States] 840009 Connecticut [State: United States] 840010 Delaware [State: United States] 840011 District of Columbia [State: United States] 840012 Florida [State: United States] 840013 Georgia [State: United States] 840015 Hawaii [State: United States] 840016 Idaho [State: United States] 840017 Illinois [State: United States] 840018 Indiana [State: United States] 840019 Iowa [State: United States] 840020 Kansas [State: United States] 840021 Kentucky [State: United States] 840022 Louisiana [State: United States] 840023 Maine [State: United States] 840024 Maryland [State: United States] 840025 Massachusetts [State: United States] 840026 Michigan [State: United States] 840027 Minnesota [State: United States] 840028 Mississippi [State: United States] 840029 Missouri [State: United States] 840030 Montana [State: United States] 840031 Nebraska [State: United States] 840032 Nevada [State: United States] 840033 New Hampshire [State: United States] 840034 New Jersey [State: United States] 840035 New Mexico [State: United States] 840036 New York [State: United States] 840037 North Carolina [State: United States] 840038 North Dakota [State: United States] 840039 Ohio [State: United States] 840040 Oklahoma [State: United States] 840041 Oregon [State: United States] 840042 Pennsylvania [State: United States] 840044 Rhode Island [State: United States] 840045 South Carolina [State: United States] 840046 South Dakota [State: United States] 840047 Tennessee [State: United States] 840048 Texas [State: United States] 840049 Utah [State: United States] 840050 Vermont [State: United States] 840051 Virginia [State: United States] 840053 Washington [State: United States] 840054 West Virginia [State: United States] 840055 Wisconsin [State: United States] 840056 Wyoming [State: United States] 840097 Abroad [State: United States] 840098 Unknown [State: United States] 840999 NIU (not in universe) [State: United States] 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] 858097 Abroad [Department: Uruguay] 858098 Unknown [Department: Uruguay] 858999 NIU (not in universe) [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] 862097 Foreign country [State: Venezuela] 862098 Unknown [State: Venezuela] 862099 NIU (not in universe) [State: Venezuela] Migration: Global Variables -- PERSON Years residing in current locality MIGYRS1 indicates how many years the person has resided in their current locality of residence. 00 Less than 1 year 01 1 year (or 1 year or less) 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 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+ years 96 Less than 5 years 97 More than 5 years 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Province of previous residence, Indonesia; consistent boundaries, GIS MIG1_P_ID indicates the person's province of previous residence within Indonesia. The migration could have occurred at any time in the past. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. 360011 Nanggroe Aceh Darussalam 360012 Sumatera Utara 360013 Sumatera Barat 360014 Kepulauan Riau, Riau 360015 Jambi 360016 Bangka Belitung, Sumatera Selatan 360017 Bengkulu 360018 Lampung 360031 DKI Jakarta 360032 Banten, Jawa Barat 360033 Jawa Tengah 360034 DKI Yogyakarta 360035 Jawa Timur 360051 Bali 360052 Nusa Tenggara Barat 360053 Nusa Tenggara Timur 360061 Kalimantan Barat 360062 Kalimantan Tengah 360063 Kalimantan Selatan 360064 Kalimantan Timur 360071 Gorontalo, Sulawesi Utara 360072 Sulawesi Tengah 360073 Sulawesi Barat, Sulawesi Selatan 360074 Sulawesi Tenggara 360081 Maluku, Maluku Utara 360094 Papua, Papua Barat 360626 East Timor 360097 Abroad 360098 Unknown 360099 NIU (not in universe) Migration: F-N Variables -- PERSON Province of residence 5 years ago, Indonesia; consistent boundaries, GIS MIG1_5_ID indicates the person's province of residence five years prior to the census within Indonesia. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. 360011 Nanggroe Aceh Darussalam 360012 Sumatera Utara 360013 Sumatera Barat 360014 Kepulauan Riau, Riau 360015 Jambi 360016 Bangka Belitung, Sumatera Selatan 360017 Bengkulu 360018 Lampung 360031 DKI Jakarta 360032 Banten, Jawa Barat 360033 Jawa Tengah 360034 DKI Yogyakarta 360035 Jawa Timur 360051 Bali 360052 Nusa Tenggara Barat 360053 Nusa Tenggara Timur 360061 Kalimantan Barat 360062 Kalimantan Tengah 360063 Kalimantan Selatan 360064 Kalimantan Timur 360071 Gorontalo, Sulawesi Utara 360072 Sulawesi Tengah 360073 Sulawesi Barat, Sulawesi Selatan 360074 Sulawesi Tenggara 360081 Maluku, Maluku Utara 360094 Papua, Papua Barat 360626 East Timor 360097 Abroad 360098 Unknown 360099 NIU (not in universe) Migration: F-N Variables -- PERSON Disability status DISABLED indicates whether the person reported a disability of any kind. 0 NIU (not in universe) 1 Yes, disabled 2 No, not disabled 9 Unknown Disability Variables -- PERSON Employment disability DISEMP indicates if the respondent was economically inactive because of disabilities or, in some instances, other health-related reasons. 1 Disabled 2 Not disabled 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Blind or vision-impaired DISBLND indicates whether the person was blind or had limited vision. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Deaf or hearing-impaired DISDEAF indicates whether the person was deaf or had limited hearing. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Mute or speech impaired DISMUTE indicates if the person could not speak or had a significant speech impediment. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Person number (within household) Indonesia 1980: All records This variable indicates the person number (within household). 00 Household record 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 Technical Person Variables -- PERSON Relationship to head of household All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A400" a="all">1. Relationship to head of household<br /><div class="i1">[] 1 Head of household<br />[] 2 Wife<br />[] 3 Son or daughter<br />[] 4 Son or daughter-in-law<br />[] 5 Grandchild<br />[] 6 Parent or parent-in-law<br />[] 7 Other relative<br />[] 8 Servant<br />[] 9 Other</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's relationship to the head of household. 1 Head of household 2 Wife 3 Son or daughter 4 Son or daughter-in-law 5 Grandchild 6 Parent or parent-in-law 7 Other relative 8 Servant 9 Other Demographic Variables -- PERSON Sex All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A401" a="all ">2. Sex<br /><div class="i1">[] 1 Male<br />[] 2 Female</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's sex. 1 Male 2 Female Demographic Variables -- PERSON Own mother living in this household All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A402 ID80A403" a="all">3. Own mother living in this household?<br /><div class="i1">[] 1 Yes</div><br /><div class="i2">[Question 4 was asked only of those persons who responded "Yes" in question 3.]<br />4. Serial number _ _</div><br /><div class="i1">[] 2 No (go to question 5)</div><br /></svar> Indonesia 1980: All persons This variable indicates whether or not the respondent's own mother is living in this household. 1 Yes 2 No Other Person Variables -- PERSON Serial number of own mother All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A402 ID80A403" a="all">3. Own mother living in this household?<br /><div class="i1">[] 1 Yes</div><br /><div class="i2">[Question 4 was asked only of those persons who responded "Yes" in question 3.]<br />4. Serial number _ _</div><br /><div class="i1">[] 2 No (go to question 5)</div><br /></svar> Indonesia 1980: Persons whose mother lives in their household [discrepencies: none] This variable indicates the serial number of the respondent's own mother. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 26 26 28 28 99 NIU (not in universe) Other Person Variables -- PERSON Age All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A404" a="all">5. Age<br /><div class="i1">_ _ years</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's age. 00 Younger than 1 year 01 1 year old 02 2 years 03 3 years 04 4 05 5 06 6 07 7 08 8 09 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 years or older 99 Unknown Demographic Variables -- PERSON Month and year of birth known All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A405" a="all">6. Month and year of birth known?<br /><div class="i1">[] 1 Yes<br />[] 2 No (go to question 8)</div><br /></svar></p> <p><svar v="ID80A406 ID80A506 ID80A507" a="all">7. Month and year of birth<br /><div class="i1">[Question 7 was asked of persons who know their month and year of birth, per question 6.]<br /><br />Month ____<br />Year 19 _ _</div><br /></svar> Indonesia 1980: All persons This variable indicates whether the respondent's month and year of birth are known. 1 Yes 2 No Other Person Variables -- PERSON Month of birth All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A405" a="all">6. Month and year of birth known?<br /><div class="i1">[] 1 Yes<br />[] 2 No (go to question 8)</div><br /></svar></p> <p><svar v="ID80A406 ID80A506 ID80A507" a="all">7. Month and year of birth<br /><div class="i1">[Question 7 was asked of persons who know their month and year of birth, per question 6.]<br /><br />Month ____<br />Year 19 _ _</div><br /></svar> Indonesia 1980: Persons who know their month and year of birth [discrepencies: none] This variable indicates the respondent's month of birth. 0001 January 0002 February 0003 March 0004 April 0005 May 0006 June 0007 July 0008 August 0009 September 0010 October 0011 November 0012 December 0099 Unknown 9999 NIU (not in universe) Demographic Variables -- PERSON Year of birth All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A405" a="all">6. Month and year of birth known?<br /><div class="i1">[] 1 Yes<br />[] 2 No (go to question 8)</div><br /></svar></p> <p><svar v="ID80A406 ID80A506 ID80A507" a="all">7. Month and year of birth<br /><div class="i1">[Question 7 was asked of persons who know their month and year of birth, per question 6.]<br /><br />Month ____<br />Year 19 _ _</div><br /></svar> Indonesia 1980: Persons who know their month and year of birth [discrepencies: none] This variable indicates the respondent's year of birth. 00 1900 01 1901 02 1902 03 1903 04 1904 05 1905 06 1906 07 1907 08 1908 09 1909 10 1910 11 1911 12 1912 13 1913 14 1914 15 1915 16 1916 17 1917 18 1918 19 1919 20 1920 21 1921 22 1922 23 1923 24 1924 25 1925 26 1926 27 1927 28 1928 29 1929 30 1930 31 1931 32 1932 33 1933 34 1934 35 1935 36 1936 37 1937 38 1938 39 1939 40 1940 41 1941 42 1942 43 1943 44 1944 45 1945 46 1946 47 1947 48 1948 49 1949 50 1950 51 1951 52 1952 53 1953 54 1954 55 1955 56 1956 57 1957 58 1958 59 1959 60 1960 61 1961 62 1962 63 1963 64 1964 65 1965 66 1966 67 1967 68 1968 69 1969 70 1970 71 1971 72 1972 73 1973 74 1974 75 1975 76 1976 77 1977 78 1978 79 1979 80 1980 99 NIU (not in universe) Demographic Variables -- PERSON Marital status All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A407" a="all">8. Marital status<br /><div class="i1">[] 1 Single (not yet married)<br />[] 2 Married<br />[] 3 Widowed<br />[] 4 Divorced</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's marital status. 1 Single (never married) 2 Married 3 Widowed 4 Divorced Demographic Variables -- PERSON Religion All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A408" a="all">9. Religion<br /><div class="i1">[] 1 Muslim<br />[] 2 Protestant/other Christian<br />[] 3 Catholic<br />[] 4 Hindu<br />[] 5 Buddhist<br />[] 6 Other</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's religion. 1 Muslim 2 Protestant/other Christian 3 Catholic 4 Hindu 5 Buddhist 6 Other Ethnicity and Language Variables -- PERSON Citizenship All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A409" a="all">10. Citizenship<br /><div class="i1">[] 1 Indonesian<br />[] 2 Chinese (People's Republic of China, Taiwan, Stateless)<br />[] 3 Other foreigner</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's country of citizenship. 1 Indonesian 2 Chinese (People's Republic of China, Taiwan, stateless) 3 Other foreigner Nativity and Birthplace Variables -- PERSON Province of birth All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A410" a="all">11. Place of birth<br /><div class="i1">Province ____</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's province of birth. 11 Special region of Aceh 12 North Sumatra 13 West Sumatra 14 Riau 15 Jambi 16 South Sumatra 17 Bengkulu 18 Lampung 31 Special capital region of Jakarta 32 West Java 33 Central Java 34 Special region of Yogyakarta 35 East Java 51 Bali 52 West Nusa Tenggara 53 East Nusa Tenggara 54 East Timor 61 West Kalimantan 62 Central Kalimantan 63 South Kalimantan 64 East Kalimantan 71 North Sulawesi 72 Central Sulawesi 73 South Sulawesi 74 Southeast Sulawesi 81 Maluku 82 Irian Jaya 98 Overseas 99 Unknown Nativity and Birthplace Variables -- PERSON Duration of residence in present province All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A411" a="all">12. Duration of residence in present province<br /><div class="i1">Years _ _</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's duration of residence in present province (years). 00 Shorter than 1 year 01 1 year 02 2 years 03 3 years 04 4 05 5 06 6 07 7 08 8 09 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 years or longer 99 Unknown Migration: Global Variables -- PERSON Province of previous residence All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A412" a="all">13. Place of previous residence<br /><div class="i1">Province ____</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's province of previous residence. 11 Special region of Aceh 12 North Sumatra 13 West Sumatra 14 Riau 15 Jambi 16 South Sumatra 17 Bengkulu 18 Lampung 31 Special capital region of Jakarta 32 West Java 33 Central Java 34 Special region of Yogyakarta 35 East Java 51 Bali 52 West Nusa Tenggara 53 East Nusa Tenggara 54 East Timor 61 West Kalimantan 62 Central Kalimantan 63 South Kalimantan 64 East Kalimantan 71 North Sulawesi 72 Central Sulawesi 73 South Sulawesi 74 Southeast Sulawesi 81 Maluku 82 Irian Jaya 98 Overseas 99 Unknown Migration: Global Variables -- PERSON Province of residence 5 years ago All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A413" a="all">14. Place of residence 5 years ago<br /><div class="i1">Province ____</div><br /></svar> Indonesia 1980: Persons age 5+ This variable indicates the respondent's province of residence 5 years ago. 11 Special region of Aceh 12 North Sumatra 13 West Sumatra 14 Riau 15 Jambi 16 South Sumatra 17 Bengkulu 18 Lampung 31 Special capital region of Jakarta 32 West Java 33 Central Java 34 Special region of Yogyakarta 35 East Java 51 Bali 52 West Nusa Tenggara 53 East Nusa Tenggara 54 East Timor 61 West Kalimantan 62 Central Kalimantan 63 South Kalimantan 64 East Kalimantan 71 North Sulawesi 72 Central Sulawesi 73 South Sulawesi 74 Southeast Sulawesi 81 Maluku 82 Irian Jaya 97 Overseas 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Sick last week All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A414" a="all">15. Have you felt unwell during the past week?<br /><div class="i1">[] 1 Yes<br />[] 2 No (go to question 17)</div><br /></svar> Indonesia 1980: All persons This variable indicates whether or not the respondent was sick last week. 1 Yes 2 No Other Person Variables -- PERSON Medical service used All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A415" a="all">16. Medical service used<br /><div class="i1">[Question 16 was asked of persons who felt unwell during the past week, per question 15.]<br /><br />[] 1 General practitioner<br />[] 2 Hospital<br />[] 3 Public Health Center<br />[] 4 Polyclinic<br />[] 5 Health service extension worker<br />[] 6 Traditional doctor<br />[] 7 Self treated<br />[] 8 Not treated</div><br /></svar> Indonesia 1980: Persons who were sick last week [discrepencies: none] This variable indicates the medical service used by the respondent if he or she were sick last week. 01 General practitioner 02 Hospital 03 Public health center 04 Polyclinic 05 Health service extension worker 06 Traditional doctor 07 Self-treatment 08 No treatment 09 Unknown 99 NIU (not in universe) Other Person Variables -- PERSON Handicapped All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A416" a="all">17. Handicapped?<br /><div class="i1">[] 1 Yes<br />[] 2 No (go to question 19)</div><br /></svar> Indonesia 1980: All persons This variable indicates whether or not the respondent is handicapped. 1 Yes 2 No Disability Variables -- PERSON Type of handicap All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A416" a="all">17. Handicapped?<br /><div class="i1">[] 1 Yes<br />[] 2 No (go to question 19)</div><br /></svar></p> <p><svar v="ID80A417" a="all">18. Type of handicap<br /><div class="i1">[Question 18 was asked of persons who are handicapped, per question 17.]<br /><br />[] 1 Blind<br />[] 2 Deaf/mute<br />[] 4 Physical<br />[] 8 Mental</div><br /></svar> Indonesia 1980: Persons who are handicapped [discrepencies: none] This variable indicates the respondent's type of handicap. 1 Blind 2 Deaf and mute 3 Physical 4 Mental 8 Other 9 NIU (not in universe) Disability Variables -- PERSON Current school attendance All persons <br /><span class="h3">VII. Characteristics of individual household members</span></p> <p><svar v="ID80A418" a="all">19. School attendance<br /><div class="i1">[] 1 Does not attend school or has not started school (go to question 24)<br />[] 2 Attending school<br />[] 3 Previously attended, but does not attend school anymore</div><br /></svar> Indonesia 1980: All persons This variable indicates the respondent's current status of school attendance. 1 Never attended or has not yet started school 2 Attending achool 3 Not attending anymore (attended before) Education Variables -- PERSON Highest type of school attended <svar v="ID80A419" a="all">20. Type of highest school attended or currently attending<br /><div class="i1">[Question 20 was asked of persons who have ever attended school, per question 19.]<br /><br />[] 1 Kindergarten<br />[] 2 Primary school (3 years)<br />[] 3 Primary school (6 years)<br />[] 4 General JHS<br />[] 5 General SHS<br />[] 6 Vocational JHS<br />[] 7 Vocational SHS<br />[] 8 Academy<br />[] 9 University</div><br /></svar> Indonesia 1980: Persons who either are attending school or had attended school before but not anymore [discrepencies: none] This variable indicates the highest type of school attended by the respondent. 01 Kindergarten 02 Primary school (3 years) 03 Primary school (6 years) 04 General junior high school 05 General senior high school 06 Vocational junior high school 07 Vocational senior high school 08 Academy 09 University 98 Unknown 99 NIU (not in universe) Education Variables -- PERSON Highest grade attended/attending <svar v="ID80A420 ID80A421" a="all">21. Highest grade attended/attending<br /><div class="i1">[Question 21 was asked of persons who have ever attended school, as per question 19.]<br /><br />[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8 (completed)</div><br /></svar> Indonesia 1980: Persons who either are attending school or had attended school before but not anymore [discrepencies: none] This variable indicates the respondent's highest grade attended or currently attending. 00 None 01 One year 02 Two years 03 Three years 04 Four years 05 Five years 06 Six years 07 Seven years 08 Completed 09 Unknown 99 NIU (not in universe) Education Variables -- PERSON Highest grade attended/attending in highest type of school attended <svar v="ID80A420 ID80A421" a="all">21. Highest grade attended/attending<br /><div class="i1">[Question 21 was asked of persons who have ever attended school, as per question 19.]<br /><br />[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8 (completed)</div><br /></svar> Indonesia 1980: Persons who either are attending school or had attended school before but not anymore [discrepencies: none] Highest grade attended/attending. 010 Some kindergarten 018 Completed kindgergarten 021 First year of primary school (3 years) 022 Second year of primary school (3 years) 023 Third year of primary school (3 years) 028 Completed primary school (3 years) 031 First year of primary school (6 years) 032 Second year of primary school (6 years) 033 Third year of primary school (6 years) 034 Fourth year of primary school (6 years) 035 Fifth year of primary school (6 years) 036 Sixth year of primary school (6 years) 038 Completed primary school (6 years) 041 First year of general junior high school 042 Second year of general junior high school 043 Third year of general junior high school 048 Completed general junior high school 051 First year of general senior high school 052 Second year of general senior high school 053 Third year of general senior high school 058 Completed general senior high school 061 First year of vocational junior high school 062 Second year of vocational junior high school 063 Third year of vocational junior high school 064 Fourth year of vocational junior high school 068 Completed vocational junior high school 071 First year of vocational senior high school 072 Second year of vocational senior high school 073 Third year of vocational senior high school 074 Fourth year of vocational senior high school 078 Completed vocational senior high school 081 First year of academy 082 Second year of academy 083 Third year of academy 084 Fourth year of academy 088 Completed academy 091 First year of university 092 Second year of university 093 Third year of university 094 Fourth year of university 095 Fifth year of university 096 Sixth year of university 097 Seventh year of university 098 Completed university 998 Unknown 999 NIU (not in universe) Education Variables -- PERSON Highest level of education completed <svar v="ID80A422" a="all">22. Highest level of education completed<br /><div class="i1">[Question 22 was asked of persons who have ever attended school, as per question 19.]<br /><br />[] 1 Not completed primary school (go to question 24)<br />[] 2 Primary school (go to question 24)<br />[] 3 General JHS (go to question 24)<br />[] 4 General SHS (go to question 24)<br />[] 5 Vocational JHS<br />[] 6 Vocational SHS<br />[] 7 Academy<br />[] 8 University</div><br /></svar> Indonesia 1980: Persons who either are attending school or had attended school before but not anymore [discrepencies: none] This variable indicates the highest level of education completed by the respondent. 01 None/less than primary school 02 Primary school 03 General junior high school 04 General senior high school 05 Vocational junior high school 06 Vocational senior high school 07 Academy 08 University 09 Unknown 99 NIU (not in universe) Education Variables -- PERSON Able to speak Indonesian <svar v="ID80A425" a="all">25. Able to speak Indonesian?<br /><div class="i1">[Question 25 was asked of persons who do not speak Indonesian at home, per question 24.]<br /><br />[] 1 Yes<br />[] 2 No</div><br /></svar> Indonesia 1980: Persons who do not use Indonesian as a language at home [discrepencies: none] This variable indicates whether or not the respondent is able to speak Indonesian. 1 Yes 2 No 9 NIU (not in universe) Ethnicity and Language Variables -- PERSON Able to read and write <svar v="ID80A426" a="all">26. Able to read and write?<br /><div class="i1">[] 1 Latin alphabet<br />[] 2 Other alphabet<br />[] 3 Unable</div><br /></svar> Indonesia 1980: All persons This variable indicates whether or not the respondent is able to read and write. 1 Yes, latin alphabet 2 Yes, other alphabet 3 No 9 Unknown Education Variables -- PERSON Primary activity during the previous week <svar v="ID80A427 ID80A428 ID80A429 ID80A430 ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">Persons 10 years or older<br /><span class="h3">VIII. Activities of persons aged 10 years or older</span><br />[Questions 27-42.]<br /></svar></p> <p><svar v="ID80A427" a="all">27. Primary activity during the previous week<br /><div class="i1">[] 1 Working (go to question 31)<br />[] 2 Attending school<br />[] 3 Housekeeping<br />[] 4 Other</div><br /></svar> Indonesia 1980: Persons age 10+ [discrepencies: type I none; type II trace] This variable indicates the respondent's primary activity during the previous week. 1 Working 2 Attending school 3 Housekeeping 4 Other 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Worked last week <svar v="ID80A427 ID80A428 ID80A429 ID80A430 ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">Persons 10 years or older<br /><span class="h3">VIII. Activities of persons aged 10 years or older</span><br />[Questions 27-42.]<br /></svar></p> <p><svar v="ID80A427" a="all">27. Primary activity during the previous week<br /><div class="i1">[] 1 Working (go to question 31)<br />[] 2 Attending school<br />[] 3 Housekeeping<br />[] 4 Other</div><br /></svar></p> <p><svar v="ID80A428" a="all">28. In addition to 2, 3, or 4 [answer choices in the previous question], also worked for at least one hour during the previous week?<br /><div class="i1">[Question 28 was asked of persons who did not work last week [chose any option other than 1 Working], as per question 27.]<br /><br />[] 1 Yes (go to question 31)<br />[] 2 No</div><br /></svar> Indonesia 1980: Persons age 10+ whose primary activity during the previous week was not work [discrepencies: none] This variable indicates whether or not the respondent worked last week. 1 Yes 2 No 9 NIU (not in universe) Work Variables -- PERSON Holds a job but absent during the previous week <svar v="ID80A427 ID80A428 ID80A429 ID80A430 ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">Persons 10 years or older<br /><span class="h3">VIII. Activities of persons aged 10 years or older</span><br />[Questions 27-42.]<br /></svar></p> <p><svar v="ID80A429" a="all">29. Holds a job but was absent during the previous week?<br /><div class="i1">[Question 29 was asked of persons who did not work for even one hour last week, per questions 27 and 28.]<br /><br />[] 1 Yes (go to question 31)<br />[] 2 No</div><br /></svar> Indonesia 1980: Persons age 10+ who did not work for even one hour last week [discrepencies: none] This variable indicates whether or not the respondent holds a job but was absent during the previous week. 1 Yes 2 No 9 NIU (not in universe) Work Variables -- PERSON Ever worked <svar v="ID80A427 ID80A428 ID80A429 ID80A430 ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">Persons 10 years or older<br /><span class="h3">VIII. Activities of persons aged 10 years or older</span><br />[Questions 27-42.]<br /></svar> Indonesia 1980: Persons age 10+ who did not work for even one hour last week and were not absent from their job last week [discrepencies: none] This variable indicates whether or not the respondent has ever worked. 1 Yes 2 No 9 NIU (not in universe) Work Variables -- PERSON Numbers of days worked during the previous week <svar v="ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">[Questions 31-37 were asked of persons who worked for at least one hour last week or had a job to go to, as per questions 27, 28 and 29.]<br /></svar></p> <p><svar v="ID80A431" a="all">31. Number of days worked during the previous week<br /><div class="i1">____ days</div><br /></svar> Indonesia 1980: Persons age 10+ who worked for at least one hour last week or had a job but were absent during the previous week [discrepencies: none] This variable indicates the numbers of days the respondent worked during the previous week. 0 Did not work (temporarily absent) 1 1 day 2 2 days 3 3 days 4 4 days 5 5 days 6 6 days 7 7 days 8 Unknown, but worked 9 NIU (not in universe) Work Variables -- PERSON Numbers of hours worked during the previous week <svar v="ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">[Questions 31-37 were asked of persons who worked for at least one hour last week or had a job to go to, as per questions 27, 28 and 29.]<br /></svar></p> <p><svar v="ID80A432" a="all">32. Number of hours worked during the previous week<br /><div class="i1">____ hours</div><br /></svar> Indonesia 1980: Persons age 10+ who worked for at least one hour last week or had a job but were absent during the previous week [discrepencies: none] This variable indicates the number of hours the respondent worked during the previous week. 000 0 (temporarily absent) 001 1 hour 002 2 hours 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98+ 099 Unknown but had worked 999 NIU (not in universe) Work Variables -- PERSON Number of hours worked in primary activity during the previous week <svar v="ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">[Questions 31-37 were asked of persons who worked for at least one hour last week or had a job to go to, as per questions 27, 28 and 29.]<br /></svar></p> <p><svar v="ID80A433" a="all">33. Number of hours worked in primary activity during the previous week<br /><div class="i1">____ hours</div><br /></svar> Indonesia 1980: Persons age 10+ who worked for at least one hour last week or had a job but were absent during the previous week [discrepencies: none] This variable indicates the number of hours the respondent worked in their primary activity during the previous week. 000 Did not work 001 1 hour 002 2 hours 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 Unknown, but worked 999 NIU (not in universe) Work Variables -- PERSON Primary occupation during the previous week (3 digit version) <svar v="ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">[Questions 31-37 were asked of persons who worked for at least one hour last week or had a job to go to, as per questions 27, 28 and 29.]<br /></svar></p> <p><svar v="ID80A434" a="all">34. Specify your primary occupation during the previous week<br /><div class="i1">____</div><br /></svar> Indonesia 1980: Persons age 10+ who worked for at least one hour last week or had a job but were absent during the previous week [discrepencies: none] This variable indicates the respondent's primary occupation during the previous week (3 digit version). 0001 Armed forces occupations 0011 Chemists 0012 Physicists 0013 Physical scientists nec 0014 Science technicians 0021 Architects and town planners 0022 Civil engineers 0023 Electrical and electronics engineers 0024 Mechanical engineers 0025 Chemical engineers 0026 Metallurgists 0027 Mining engineers 0028 Industrial engineers 0029 Engineers nec 0031 Surveyors 0032 Draughtsmen 0033 Civil engineering technicians 0034 Electrical and electronics engineering technicians 0035 Mechanical engineering technicians 0036 Chemical engineering technicians 0037 Metallurgical technicians 0038 Mining technicians 0039 Engineering technicians nec 0041 Aircraft pilots, navigators and flight engineers 0042 Ships' deck officers and pilots 0043 Ships' engineers 0051 Biologists, zoologists and related scientists 0052 Bacteriologists, pharmacologists and related scientists 0053 Livestock researcher 0054 Agronomy researcher and other researchers 0061 Medical doctors 0062 Medical assistants 0063 Dentists 0064 Dental assistants 0065 Veterinarians 0066 Veterinary assistants 0067 Pharmacists 0068 Pharmaceutical assistants 0069 Dietitians and public health nutritionists 0071 Professional nurses 0072 Nursing personnel nec 0073 Professional midwives 0074 Midwifery personnel nec 0075 Optometrists and opticians 0076 Physiotherapists and occupational therapists 0077 Medical x-ray technicians 0079 Medical, dental, veterinary and related workers nec 0081 Statisticians 0082 Mathematicians and actuaries 0083 Systems analysts 0084 Statistical and mathematical technicians 0090 Economists 0110 Accountants 0121 Lawyers 0122 Judges 0123 Attorney 0129 Jurists nec 0131 University and higher education teachers 0132 Secondary education teachers 0133 Junior high teachers 0134 Primary education teachers 0135 Preprimary education teachers 0136 Outer school education teacher 0137 Special education teachers 0139 Teachers nec 0141 Ulema and leaders in Islamic religions 0142 Pastors and leaders in Protestant religions 0143 Fathers and leaders in Catholic religions 0144 Buddhist priest and leaders in Buddhist religion 0149 Workers in religion nec 0151 Authors and critics 0152 Journalists, reporters, news commentators, etc. 0159 Authors, journalists and related writers nec 0161 Sculptors, painters and related artists 0162 Commercial artists and designers 0163 Photographers and cameramen 0171 Composers, musicians and singers 0172 Choreographers and dancers 0173 Actors and stage directors 0174 Producers, performing arts 0175 Circus performers 0179 Performing artists nec 0180 Athletes, sportsmen and related workers 0191 Librarians, archivists and curators 0192 Sociologists, anthropologists and related scientists 0193 Social workers 0194 Personnel and occupational specialists 0195 Philologists, translators and interpreters 0199 Other professional, technical and related workers 0201 Legislative officials 0202 Government administrators 0211 General managers 0212 Production managers (except farm) 0213 Marketing managers 0214 Financial managers 0215 Administrative managers 0219 Managers nec 0300 Clerical supervisors 0310 Government executive officials 0321 Stenographers, typists and teletypists 0322 Card and tapepunching machine operators 0331 Bookkeepers and cashiers 0339 Bookkeepers, cashiers and related workers nec 0341 Bookkeeping and calculating machine operators 0342 Automatic dataprocessing machine operators 0351 Railway station masters 0352 Postmasters 0353 Airport supervisor 0359 Transport and communications supervisors nec 0360 Land transportation conductors 0371 Mail distribution clerks 0372 Administration workers of commodity goods 0380 Telephone and telegraph operators 0391 Stock clerks 0392 Material and production planning clerks 0393 Correspondence and reporting clerks 0394 Receptionists and travel agency clerks 0395 Library and filing clerks 0399 Clerks nec 0400 Managers (wholesale and retail trade) 0410 Working proprietors (wholesale and retail trade) 0421 Sales supervisors 0422 Buyers 0431 Technical salesmen and service advisers 0432 Commercial travellers and manufacturers' agents 0441 Insurance, real estate and securities salesmen 0442 Business services salesmen 0443 Auctioneers 0451 Salesmen, shop assistants and demonstrators 0452 Street vendors, canvassers and newsvendors 0453 Merchants 0454 Itinerant traders 0455 Junior newsvendors 0490 Sales and purchase workers, nec 0500 Managers (catering and lodging services) 0510 Working proprietors (catering and lodging services) 0520 Housekeeping and related service supervisors 0531 Cooks 0532 Waiters, bartenders and related workers 0540 Maids and related housekeeping service workers nec 0551 Building caretakers 0552 Charworkers, cleaners and related workers 0560 Launderers, drycleaners and pressers 0570 Hairdressers, barbers, beauticians and related workers 0581 Firefighters 0582 Policemen and detectives 0589 Protective service workers nec 0591 Guides 0592 Undertakers and embalmers 0593 Masseurs 0599 Other service workers 0600 Farm managers and supervisors 0611 General farmers 0612 Specialised farmers 0621 General farm workers 0622 Field crop and vegetable farm workers (seasonal crop) 0623 Orchard, vineyard and related tree and shrub crop workers (yearly crop) 0624 Livestock workers 0625 Dairy farm workers 0626 Poultry farm workers 0627 Seeding worker, gardener 0628 Farm machinery operators 0629 Agricultural and animal husbandry workers nec 0631 Loggers, wood cutters, wood choppers 0632 Forestry establishment workers 0639 Forestry and logging, nfs 0641 Fishermen 0642 Marine workers 0643 Hunters 0649 Fishermen, hunters and related workers nec 0700 Production supervisors and general foremen 0711 Miners and quarrymen 0712 Mineral and stone treaters 0713 Well drillers, borers and related workers 0721 Metal smelting, converting and refining furnacemen 0722 Metal rollingmill workers 0723 Metal melters and reheaters 0724 Metal casters 0725 Metal moulders and coremakers 0726 Metal annealers, temperers and casehardeners 0727 Metal drawers and extruders 0728 Metal platers and coaters 0729 Metal processers nec 0731 Paper makers 0732 Paper pulp preparers and other paper material processing 0733 Wood processing (including wood perservatives) 0734 Sawyers, plywood makers and related wood processing workers 0735 Wood carvers and handicrafters 0736 Makers of bamboo goods 0737 Makers of rattan goods 0739 Paper makers, wood processors, and other wood working professions 0741 Crushers, grinders and mixers 0742 Cookers, roasters and related heattreaters 0743 Filter and separator operators 0744 Still and reactor operators 0745 Petroleumrefining workers 0749 Chemical processers and related workers nec 0751 Fibre preparers 0752 Spinners and winders 0753 Weaving and knittingmachine setters and patterncard preparers 0754 Weavers and related workers 0755 Knitters 0756 Bleachers, dyers and textile product finishers 0757 Batik traditional painter 0759 Spinners, weavers, knitters, dyers and related workers nec 0761 Tanners and fellmongers 0762 Pelt dressers 0771 Grain millers and related workers 0772 Sugar processers and refiners 0773 Butchers and meat preparers 0774 Food preservers 0775 Dairy product processers 0776 Bakers, pastrycooks and confectionery makers 0777 Tea, coffee and cocoa preparers 0778 Brewers, wine and beverage makers 0779 Food and beverage processers nec 0781 Tobacco preparers 0782 Cigar makers 0783 Cigarette makers 0789 Tobacco preparers and tobacco product makers nec 0791 Tailors and dressmakers 0792 Fur tailors and related workers 0793 Milliners and hatmakers 0794 Patternmakers and cutters 0795 Sewers and embroiderers 0796 Upholsterers and related workers 0799 Tailors, dressmakers, sewers, upholsterers and related workers nec 0801 Shoemakers and shoe repairers 0802 Shoe cutters, lasters, sewers and related workers 0803 Leather goods makers 0811 Cabinetmakers 0812 Woodworkingmachine operators 0819 Cabinetmakers and related woodworkers nec 0820 Stone cutters and carvers 0831 Blacksmiths, hammersmiths and forgingpress operators 0832 Toolmakers, metal patternmakers and metal markers 0833 Machinetool setteroperators 0834 Machinetool operators 0835 Metal grinders, polishers and tool sharpeners 0839 Blacksmiths, toolmakers and machinetool operators nec 0841 Machinery fitters and machine assemblers 0842 Watch, clock and precision instrument makers 0843 Motor vehicle mechanics 0844 Aircraft engine mechanics 0849 Machinery fitters, machine assemblers and precision instrument makers (except electrical) nec 0851 Electrical fitters 0852 Electronics fitters 0853 Electrical and electronics equipment assemblers 0854 Radio and television repairmen 0855 Electrical wiremen 0856 Telephone and telegraph installers 0857 Electric linemen and cable jointers 0859 Electrical fitters and related electrical and electronics workers nec 0861 Broadcasting station operators 0862 Sound equipment operators and cinema projectionists 0871 Plumbers and pipe fitters 0872 Welders and flamecutters 0873 Sheetmetal workers 0874 Structural metal preparers and erectors 0880 Jewellery and precious metal workers 0891 Glass formers, cutters, grinders and finishers 0892 Potters and related clay and abrasive formers 0893 Glass and ceramics kilnmen 0894 Glass engravers and etchers 0895 Glass and ceramics painters and decorators 0899 Glass formers, potters and related workers nec 0901 Rubber and plastics product makers (except tire makers and tire vulcanisers) 0902 Tire makers and vulcanisers 0910 Paper and paperboard products makers 0921 Compositors and typesetters 0922 Printing pressmen 0923 Stereotypers and electrotypers 0924 Printing engravers (except photoengravers) 0925 Photoengravers 0926 Bookbinders and related workers 0927 Photographic darkroom workers 0929 Printers and related workers nec 0931 Painters, construction 0939 Painters nec 0941 Musical instrument makers and tuners 0942 Basketry weavers and brush makers 0943 Non-metallic mineral product makers 0949 Other production and related workers 0951 Bricklayers, stonemasons and tile setters 0952 Reinforced concrete, cement finishers and terrazzo workers 0953 Roofers 0954 Carpenters, joiners and parquetry workers 0955 Plasterers 0956 Insulators 0957 Glaziers 0959 Construction workers nec 0961 Powergenerating machinery operators 0969 Stationary engine and related equipment operators nec 0971 Dockers and freight handlers 0972 Riggers and cable splicers 0973 Crane and hoist operators 0974 Earthmoving and related machinery operators 0979 Material handling equipment operators nec 0981 Ships' deck ratings, barge crews and boatmen 0982 Ships' engineroom ratings 0983 Railway engine drivers and firemen 0984 Railway brakemen, signalmen and shunters 0985 Motor vehicle drivers 0986 Animal and animaldrawn vehicle drivers 0987 Pedal vehicle drivers 0989 Transport equipment operators nec 0999 Labourers nec 1010 New workers seeking employment 1020 Workers reporting occupations unidentifiable or inadequately described 1030 Workers not reporting any occupation 9998 Unknown 9999 NIU (not in universe) Work: Occupation Variables -- PERSON Industry <svar v="ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">[Questions 31-37 were asked of persons who worked for at least one hour last week or had a job to go to, as per questions 27, 28 and 29.]<br /></svar></p> <p><svar v="ID80A435" a="all">35. Type of industry in which primary activity of the previous week was carried out<br /><div class="i1">________</div><br /></svar> Indonesia 1980: Persons age 10+ who worked for at least one hour last week or had a job but were absent during the previous week [discrepencies: none] This variable indicates the industry the respondent works in. 00 Activities not adequately defined 11 Agriculture of food crops and horticulture 12 Agriculture of plantation plants and plants other 13 Animal husbandry 14 Agricultural and animal husbandry support services 15 Forestry and logging 16 Hunting/fishing, fish breeding 17 Fishery 21 Coal mining 22 Crude petroleum and natural gas production 23 Metal ore mining 29 Other mining 31 Manufacture of food, beverages and tobacco 32 Manufacture of textiles, apparel and leather 33 Manufacture of wood and wood products, including furniture 34 Manufacture of paper and paper products, printing and publishing 35 Manufacture of chemicals and chemical, petroleum, coal, rubber and plastic products 36 Manufacture of non-metallic mineral products, except products of petroleum and coal 37 Manufacture of basic metals 38 Manufacture of fabricated metal products, machinery and equipmen 39 Other manufacturing industries 41 Electricity, gas and steam 42 Water works and supply 50 Construction 61 Wholesale trade 62 Retail trade 63 Restaurants 64 Hotels and lodging establishments 71 Surface transportation (including pipeline) 72 Water transportation 73 Air transportation 74 Other transportation and supporting services 75 Communications 81 Financial institutions 82 Insurance 83 Real estate, land rental businesses and services 91 Public administration and defence 92 Sanitary and similar services 93 Social and related community services 94 Recreational and cultural services 95 Personal and household services 96 International agencies and other extra-territorial bodies 98 Unknown 99 NIU (not in universe) Work: Industry Variables -- PERSON Employment status in primary activity during the previous week <svar v="ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">[Questions 31-37 were asked of persons who worked for at least one hour last week or had a job to go to, as per questions 27, 28 and 29.]<br /></svar></p> <p><svar v="ID80A436" a="all">36. Employment status in primary activity during the previous week<br /><div class="i1">[] 1 Self-employed<br />[] 2 Self-employed assisted by family member/temporary help<br />[] 3 Employer<br />[] 4 Employee<br />[] 5 Family worker</div><br /></svar> Indonesia 1980: Persons age 10+ who worked for at least one hour last week or had a job but were absent during the previous week [discrepencies: none] This variable indicates the respondent's employment status in his or her primary activity during the previous week. 1 Self-employed 2 Self-employed, assisted by family members or temporary help 3 Employer 4 Employee 5 Family worker 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Additional job during the previous week <svar v="ID80A431 ID80A432 ID80A433 ID80A434 ID80A435 ID80A436 ID80A437 ID80A438 ID80A439 ID80A440 ID80A441 ID80A442">[Questions 31-37 were asked of persons who worked for at least one hour last week or had a job to go to, as per questions 27, 28 and 29.]<br /></svar></p> <p><svar v="ID80A437" a="all">37. Did you have an additional job during the previous week?<br /><div class="i1">[] 1 Yes<br />[] 2 No (go to question 39)</div><br /></svar> Indonesia 1980: Persons age 10+ who worked for at least one hour last week or had a job but were absent during the previous week [discrepencies: none] This variable indicates whether or not the respondent had an additional job during the previous week. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Industry of additional job during the previous week <svar v="ID80A438" a="all">38. Type of industry of additional job during the previous week<br /><div class="i1">[Question 38 was asked of persons age 10 or older who had an additional job last week, as per questions 27, 28, 29 and 37.]<br /><br />[] 1 Agriculture<br />[] 2 Mining or quarrying<br />[] 3 Manufacturing<br />[] 4 Electricity, gas and water<br />[] 5 Construction<br />[] 6 Trade<br />[] 7 Transportation and communication<br />[] 8 Finance<br />[] 9 Services<br />[] 10 Other</div><br /></svar> Indonesia 1980: Persons age 10+ who had an additional job during the previous week [discrepencies: type I trace; type II none] This variable indicates the industry of the respondent's additional job during the previous week. 01 Agriculture 02 Mining or quarrying 03 Manufacturing 04 Electricity, gas and water 05 Construction 06 Trade 07 Tansport and communication 08 Finance 09 Services 10 Other/not classifiable 98 Unknown 99 NIU (not in universe) Work: Industry Variables -- PERSON Looked for work during the previous week <svar v="ID80A439" a="all">39. Did you look for work during the previous week?<br /><div class="i1">[] 1 Yes (go to question 41)<br />[] 2 No</div><br /></svar> Indonesia 1980: Persons age 10+ [discrepencies: type I none; type II trace] This variable indicates whether or not the respondent looked for work during the previous week. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Primary reason for not seeking work during the previous week <svar v="ID80A440" a="all">40. Primary reason for not seeking for work during the previous week<br /><div class="i1">[Question 40 was asked of persons who did not look for work during the previous week.]<br /><br />[] 1 Did not need work<br />[] 2 Waiting for the outcome of an application<br />[] 3 Gave up trying<br />[] 4 Attending school<br />[] 5 Housekeeping<br />[] 6 Not able to work<br />[] 7 Other</div><br /></svar> Indonesia 1980: Persons age 10+ who did not look for work during the previous week [discrepencies: none] This variable indicates the respondent's primary reason for not seeking work during the previous week. 1 Did not need work 2 Waiting for the outcome of a job application 3 Gave up trying 4 Attending school 5 Housekeeping 6 Not able to work 7 Other 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Worked during the previous year <svar v="ID80A440" a="all">40. Primary reason for not seeking for work during the previous week<br /><div class="i1">[Question 40 was asked of persons who did not look for work during the previous week.]<br /><br />[] 1 Did not need work<br />[] 2 Waiting for the outcome of an application<br />[] 3 Gave up trying<br />[] 4 Attending school<br />[] 5 Housekeeping<br />[] 6 Not able to work<br />[] 7 Other</div><br /></svar></p> <p><svar v="ID80A441" a="all">41. Did you work during the previous year?<br /><div class="i1">[] 1 Yes<br />[] 2 No (go to section IX)</div><br /></svar> Indonesia 1980: Persons age 10+ [discrepencies: type I none; type II trace] This variable indicates whether or not the respondent worked during the previous year. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Industry worked during the previous year <svar v="ID80A442" a="all">42. In what type of industry did you work during the previous year?<br /><div class="i1">[Question 42 was asked of persons age 10 or older who worked during the previous year, per question 41.]<br /><br />(Specify) ____</div><br /></svar> Indonesia 1980: Persons age 10+ who worked during the previous year [discrepencies: none] This variable indicates the industry the respondent worked during the previous year. 00 Activities not adequately defined 11 Agriculture and hunting 12 Plantation agriculture 13 Farming 14 Agriculture and animal husbandry services 15 Forestry and logging 16 Wild game hunting, trapping, and breeding 17 Fishery 21 Coal mining 22 Crude petroleum and natural gas production 23 Metal ore mining 29 Other mining 31 Manufacture of food, beverages and tobacco 32 Textile, wearing apparel and leather industries 33 Manufacture of wood and wood products, including furniture 34 Manufacture of paper and paper products, printing and publishing 35 Manufacture of chemicals and chemical, petroleum, coal, rubber and plastic products 36 Manufacture of non-metallic mineral products, except products of petroleum and coal 37 Basic metal industries 38 Manufacture of fabricated metal products, machinery and equipmen 39 Other manufacturing industries 41 Electricity, gas and steam 42 Water works and supply 50 Construction 61 Wholesale trade 62 Retail trade 63 Eating and drinking establishments 64 Hotels and lodging establishments 71 Land transportation including transportation by pipeline 72 Water transportation 73 Air transportation 74 Transportation and supporting services 75 Communications 81 Financial institutions 82 Insurance 83 Real estate and business services 91 Public administration and defence 92 Sanitary and similar services 93 Social and related community services 94 Recreational and cultural services 95 Personal and household services 96 International and other extra-territorial bodies 98 Unknown 99 NIU (not in universe) Work: Industry Variables -- PERSON Month and year of first marriage <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A443 ID80A508 ID80A509" a="all">43. Month and year of first marriage<br /><div class="i1">Month _ _<br />Year 19 _ _</div><br /></svar> Indonesia 1980: Ever-married women [discrepencies: none] This variable indicates the month and year of the respondent's first marriage. 9998 Unknown 9999 NIU (not in universe) Demographic Variables -- PERSON Month of first marriage <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A443 ID80A508 ID80A509" a="all">43. Month and year of first marriage<br /><div class="i1">Month _ _<br />Year 19 _ _</div><br /></svar> Indonesia 1980: Ever-married women [discrepencies: none] This variable indicates the respondent's month of first marriage. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Year of first marriage <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A443 ID80A508 ID80A509" a="all">43. Month and year of first marriage<br /><div class="i1">Month _ _<br />Year 19 _ _</div><br /></svar> Indonesia 1980: Ever-married women [discrepencies: none] This variable indicates the respondent's year of first marriage. 00 1900 01 1901 02 1902 03 1903 04 1904 05 1905 06 1906 07 1907 08 1908 09 1909 10 1910 11 1911 12 1912 13 1913 14 1914 15 1915 16 1916 17 1917 18 1918 19 1919 20 1920 21 1921 22 1922 23 1923 24 1924 25 1925 26 1926 27 1927 28 1928 29 1929 30 1930 31 1931 32 1932 33 1933 34 1934 35 1935 36 1936 37 1937 38 1938 39 1939 40 1940 41 1941 42 1942 43 1943 44 1944 45 1945 46 1946 47 1947 48 1948 49 1949 50 1950 51 1951 52 1952 53 1953 54 1954 55 1955 56 1956 57 1957 58 1958 59 1959 60 1960 61 1961 62 1962 63 1963 64 1964 65 1965 66 1966 67 1967 68 1968 69 1969 70 1970 71 1971 72 1972 73 1973 74 1974 75 1975 76 1976 77 1977 78 1978 79 1979 80 1980 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Age at first marriage <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A444" a="all">44. Age at first marriage<br /><div class="i1">_ _ years</div><br /></svar> Indonesia 1980: Ever-married women [discrepencies: none] This variable indicates the respondent's age at first marriage. 010 10 years old 011 11 years old 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 096 96 098 98 years or older 099 Unknown 999 NIU (not in universe) Demographic Variables -- PERSON Number of marriages <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A445" a="all">45. Number of marriages<br /><div class="i1">_ times</div><br /></svar> Indonesia 1980: Ever-married women [discrepencies: none] This variable indicates the respondent's number of marriages. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 or more 09 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Total number of living children <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A446 ID80A447 ID80A448" a="all">46. Number of living children<br /><div class="i1">a. Total</div><br /><div class="i2">_ _ children</div><br /><br /><div class="i1">b. Living at home</div><br /><div class="i2">_ _ children</div><br /><br /><div class="i1">c. Living away</div><br /><div class="i2">_ _ children</div><br /></svar> Indonesia 1980: Ever-married women [discrepencies: none] This variable indicates total number of the respondent's living children. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of children living at home <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A446 ID80A447 ID80A448" a="all">46. Number of living children<br /><div class="i1">a. Total</div><br /><div class="i2">_ _ children</div><br /><br /><div class="i1">b. Living at home</div><br /><div class="i2">_ _ children</div><br /><br /><div class="i1">c. Living away</div><br /><div class="i2">_ _ children</div><br /></svar> Indonesia 1980: Ever-married women [discrepencies: none] This variable indicates the number of the respondent's children living at home. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 30 30+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of children living away <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A446 ID80A447 ID80A448" a="all">46. Number of living children<br /><div class="i1">a. Total</div><br /><div class="i2">_ _ children</div><br /><br /><div class="i1">b. Living at home</div><br /><div class="i2">_ _ children</div><br /><br /><div class="i1">c. Living away</div><br /><div class="i2">_ _ children</div><br /></svar> Indonesia 1980: Ever-married women [discrepencies: none] This variable indicates the number of the respondent's children living away from home. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 29 29 30 30+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of dead children <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A449" a="all">47. Number of dead children<br /><div class="i1">_ _ children</div><br /></svar> Indonesia 1980: Ever-married women [discrepencies: none] This variable indicates the number of the respondent's dead children. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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) Fertility and Mortality Variables -- PERSON Month of birth of last child <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A450 ID80A510 ID80A511" a="all">48. Month and year of birth of last child<br /><div class="i1">Month ____<br />Year 19 _ _</div><br /></svar> Indonesia 1980: Ever-married females with children ever born This variable indicates the month of birth of the respondent's last child. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Year of birth of last child <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A450 ID80A510 ID80A511" a="all">48. Month and year of birth of last child<br /><div class="i1">Month ____<br />Year 19 _ _</div><br /></svar> Indonesia 1980: Ever-married females with children ever born This variable indicates the year of birth of the respondent's last child. 00 1900 01 1901 02 1902 04 1904 05 1905 06 1906 07 1907 08 1908 09 1909 10 1910 11 1911 12 1912 13 1913 14 1914 15 1915 16 1916 17 1917 18 1918 19 1919 20 1920 21 1921 22 1922 23 1923 24 1924 25 1925 26 1926 27 1927 28 1928 29 1929 30 1930 31 1931 32 1932 33 1933 34 1934 35 1935 36 1936 37 1937 38 1938 39 1939 40 1940 41 1941 42 1942 43 1943 44 1944 45 1945 46 1946 47 1947 48 1948 49 1949 50 1950 51 1951 52 1952 53 1953 54 1954 55 1955 56 1956 57 1957 58 1958 59 1959 60 1960 61 1961 62 1962 63 1963 64 1964 65 1965 66 1966 67 1967 68 1968 69 1969 70 1970 71 1971 72 1972 73 1973 74 1974 75 1975 76 1976 77 1977 78 1978 79 1979 80 1980 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Last child still alive <svar v="ID80A443 ID80A444 ID80A445 ID80A446 ID80A447 ID80A448 ID80A449 ID80A450 ID80A451 ID80A508 ID80A509 ID80A510 ID80A511"><span class="h3">IX. Ever married women</span><br /> [Questions 43-49.]<br /></svar></p> <p><svar v="ID80A450 ID80A510 ID80A511" a="all">48. Month and year of birth of last child<br /><div class="i1">Month ____<br />Year 19 _ _</div><br /></svar></p> <p><svar v="ID80A451" a="all">49. Is your last child still alive?<br /><div class="i1">1 Yes<br />2 No</div><br /></svar> Indonesia 1980: Ever-married females with children ever born This variable indicates whether or not the last child is still alive. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Contraceptive method(s) ever used <svar v="ID80A452 ID80A453"><span class="h3">X. Currently married women younger than 50</span><br /> [Questions 50-51.]<br /></svar></p> <p><svar v="ID80A452" a="all">50. Contraceptive methods (ever used)<br /><div class="i1">[] 1 Pill<br />[] 2 I. U. D.<br />[] 4 Condom<br />[] 0 Other<br />[] 8 Never used</div><br /></svar> Indonesia 1980: Currently married women under the age of 50 [discrepencies: type I trace; type II none] This variable indicates the contraceptive method(s) ever used by the respondent. 0 Other 1 Pill 2 IUD 3 Pill and IUD 4 Condom 5 Pill and condom 6 IUD and condom 7 Pill, IUD, and condom 8 Never used 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Contraceptive method(s) currently being used <svar v="ID80A452 ID80A453"><span class="h3">X. Currently married women younger than 50</span><br /> [Questions 50-51.]<br /></svar></p> <p><svar v="ID80A453" a="all">51. Contraceptive method(s) currently being used<br /><div class="i1">[] 1 Pill<br />[] 2 I. U. D.<br />[] 4 Condom<br />[] 0 Other<br />[] 8 Not using</div><br /></svar> Indonesia 1980: Currently married women under the age of 50 who have ever used any form of contraceptive methods [discrepencies: type I trace; type II none] This variable indicates the contraceptive method(s) currently being used by the respondent. 00 Other 01 Pill 02 IUD 03 Pill and IUD 04 Condom 05 Pill and condom 06 IUD and condom 07 Pill, IUD and condom 08 Not using 09 Unknown but using contraception 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Person weight Indonesia 1980: All persons This variable indicates the person weight. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 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 Technical Person Variables -- PERSON Language used at home (10 groups) Indonesia 1980: All persons This variable indicates the language used at home by the respondent (10 groups). 01 Indonesian 02 Jawa 03 Sunda 04 Madura 05 Batak 06 Minang 07 Bali 08 Bugis 09 Banjar 10 Other 11 Unknown, but not Indonesian Ethnicity and Language Variables -- PERSON