General Census of Population and Housing, 1976 DDI_CMR_1976_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. General Census of Population and Housing, 1976 - IPUMS Subset PHC cm1976a (IPUMS Harmonized Subset) CMR_1976_PHC_v01_M_v7.6_A_IPUMS Direction de la Statistique et de la Compatabilité Nationale IPUMS (c) Copyright 1976, Direction de la Statistique et de la Compatabilité Nationale and Minnesota Population Center Direction de la Statistique et de la Compatabilité Nationale 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 Other Household Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Geography: A-E Variables -- HOUSEHOLD Nativity and Birthplace Variables -- PERSON Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Utilities Variables -- HOUSEHOLD Dwelling Characteristics Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Migration: A-E Variables -- PERSON Household Economic Variables -- HOUSEHOLD Technical Person Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Geography: A-E Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Demographic Variables -- PERSON Nativity and Birthplace Variables -- PERSON Education Variables -- PERSON Work Variables -- PERSON Work: Occupation Variables -- PERSON April 9-24, 1976 April 9-24, 1976 Cameroon Arrondissement Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: No - Households: Yes - Group quarters: Yes All persons present in Cameroon at the time of the census, including visitors from other countries. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Cameroon 1976 MICRODATA SOURCE: Direction de la Statistique et de la Compatabilité Nationale SAMPLE SIZE (person records): 736514. SAMPLE DESIGN: Systematic sample of every 10th dwelling with a random start, drawn by IPUMS Face-to-face [f2f] Two forms: Dwelling units and collective households both, CENSUS DAY: April 9-24, 1976 Self-weighting (expansion factor=10) 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. Direction de la Statistique et de la Compatabilité Nationale 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: Cameroon, Direction de la Statistique et de la Compatabilité Nationale. General Census of Population and Housing, 1976 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 cm1976a, 2025 CMR1976_PHC-H-H.dat Household records 160,144 ascii Minnesota Population Center Version 7.5, IPUMS sample CMR1976_PHC-P-H.dat Person records 736514 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 Donated household HHDONATE identifies households that were donated during the IPUMS data editing process. 0 Not donated 1 Donated 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 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 Cameroon, Province 1976 - 2005 [Level 1; consistent boundaries, GIS] GEO1_CM identifies the household's province within Cameroon in all sample years. Provinces are the first administrative units of the country. GEO1_CM 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_CM can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Cameroon 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. 120002 Centre, Sud 120003 Est 120004 Nord, Adamoua, Extrème Nord 120005 Littoral 120007 Nord Ouest 120008 Ouest 120010 Sud Ouest Geography: A-E Variables -- HOUSEHOLD Cameroon, Province 1976 [Level 1, GIS] GEO1_CM1976 identifies the household's province within Cameroon in 1976. Provinces are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_CM1976 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Cameroon 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. 001 Centre-Sud 002 Est 003 Littoral 004 Nord 005 Nord-Ouest 006 Ouest 007 Sud-Ouest Geography: A-E Variables -- HOUSEHOLD Cameroon, Department 1976 - 2005 [Level 2; consistent boundaries, GIS] GEO2_CM identifies the household's department within Cameroon in all sample years. Departments are the second level administrative units of the country, after provinces. GEO2_CM 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 GEO2_CM can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Cameroon 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. 120002001 Haute Sanaga 120002002 Lekié 120002003 Mbam et Inoubou, Mbam et Kim 120002004 Mefou et Akono, Mefou et Afamba 120002005 Mfoundi 120002006 Nyong et Kéllé 120002007 Nyong et Mfoumou 120002008 Nyong et So'o 120002009 Dja et Lobo 120002010 Mvilla, Vallée du Ntem, Océan 120003001 Boumba et Ngoko 120003002 Haut Nyong 120003003 Kadey 120003004 Lom et Djerem 120004001 Vina, Djerem, Faro et Déo, Mayo Banyo, Mbéré 120004002 Diamaré, Mayo Kani 120004003 Logone et Chari 120004004 Mayo Danay 120004005 Mayo Tsanaga, Mayo Sava 120004006 Mayo Louti, Bénoué, Faro, Mayo Rey 120005001 Moungo 120005002 Nkam 120005003 Sanaga Maritime 120005004 Wouri 120007001 Menchum, Boyo 120007002 Bui 120007003 Donga Mantung 120007004 Mezam, Ngo Ketungja 120007005 Momo 120008001 Bamboutos 120008002 Haut Nkam 120008003 Mifi, Hauts Plateaux, Koung Khi 120008004 Menoua 120008005 Ndé 120008006 Noun 120010001 Fako 120010002 Koupe et Manengouba, Meme 120010003 Manyu, Lebialem 120010004 Ndian Geography: A-E Variables -- HOUSEHOLD Cameroon, Department 1976 [Level 2, GIS] GEO2_CM1976 identifies the household's department within Cameroon in 1976. Departments are the second level administrative units of the country, after provinces. A GIS map (in shapefile format), corresponding to GEO2_CM1976 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Cameroon 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. 001101 Dja and Lobo 001102 Haute-Sanaga 001103 Lekié 001104 Mbam 001105 Méfou 001106 Mfoundi 001107 Ntem and Océan 001108 Nyong and Kéllé 001109 Nyong and Mfoumou 001110 Nyong and So 002201 Boumba and Ngoko 002202 Haut-Nyong 002203 Kadey 002204 Lom and Djerem 003301 Moungo 003302 Nkam 003303 Sanaga-Maritme 003304 Wouri 004401 Adamaoua 004402 Bénoué 004403 Diamaré 004404 Logone and Chari 004405 Margui-Wandala 004406 Mayo Danay 005501 Bui 005502 Donga-Mantung 005503 Menchum 005504 Mezam 005505 Momo 006601 Bamboutos 006602 Bamoun 006603 Haut-Kam 006604 Menoua 006605 Mifi 006606 Ndé 007701 Fako 007702 Manyu 007703 Meme 007704 Ndian Geography: A-E Variables -- HOUSEHOLD Cameroon, Arrondissement ARRNDCM identifies the household's arrondissement (subdivision) within Cameroon in all sample years. Arrondissements are the third level administrative units of the country, after department. ARRNDCM is harmonized by name and does not account for boundary changes over time. The full set of geography variables for Cameroon 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. 0101 Ngaoundal 0102 Tibati 0201 Galim Tignere 0202 Tignere 0299 Arrondissements with lower than 20,000 population in Faro et Deo department 0301 Bankim 0302 Banyo and Mayo Darlé 0308 " 0401 Dir 0402 Meiganga 0403 Belel 0499 Arrondissements with lower than 20,000 population in Mbere department 0501 Ngaoundéré and Mbe 0601 Mbandjock 0602 Nanga Eboko 0603 Nkoteng 0699 Arrondissements with lower than 20,000 population in Haute Sanaga department 0701 Ebebda 0702 Monatele 0703 Obala 0704 Okola 0705 Saa 0799 Arrondissements with lower than 20,000 population in Lekié department 0801 Bafia 0802 Bokito 0803 Ombessa 0899 Arrondissements with lower than 20,000 population in Mbam et Inoubou department 0901 Mbangassina 0902 Ntui 0999 Arrondissements with lower than 20,000 population in Mbam et Kim department 1001 Mfou 1002 Soa 1099 Arrondissements with lower than 20,000 population in Mefou et Afamba department 1101 Mbankomo 1199 Arrondissements with lower than 20,000 population in Mefou et Akono department 1201 Yaounde I 1202 Yaounde II 1203 Yaounde III 1204 Yaounde IV 1205 Yaounde V 1206 Yaounde VI 1301 Eseka 1302 Makak 1399 Arrondissements with lower than 20,000 population in Nyong et Kelle department 1401 Akonolinga 1402 Ayos 1499 Arrondissements with lower than 20,000 population in Nyong et Mfoumou department 1501 Mbalmayo 1599 Arrondissements with lower than 20,000 population in Nyong et So'o department 1601 Yokadouma 1602 Abong Mbang 1699 Arrondissements with lower than 20,000 population in Boumba et Ngoko department 1701 Messamena 1702 Nguelemedouka 1799 Arrondissements with lower than 20,000 population in Haut Nyong department 1801 Batouri 1802 Kette 1803 Mbang 1804 Ndelele 1805 Belabo 1899 Arrondissements with lower than 20,000 population in Kadey department 1901 Bétaré-Oya 1902 Ngoura 1903 Bertoua and Diang 1904 Garoua-Boulaï 2001 Bogo 2002 Gazawa 2003 Maroua 2004 Dargala 2005 Ndoukoula 2006 Meri 2007 Pette 2101 Blangoua 2102 Darak 2103 Fotokol 2104 Goulfey 2105 Kousseri 2106 Logone-Birni 2107 Zina 2108 Makari 2199 Arrondissements with lower than 20,000 population in Logone et Chari department 2201 Datcheka 2202 Gobo 2203 Guere 2204 Kaïkaï 2205 Kalfou 2206 Kar-Hay 2207 Maga 2208 Tchatibali 2209 Vele 2210 Wina 2211 Yagoua 2301 Guidiguis 2302 Kaele 2303 Mindif 2304 Moulvoudaye 2305 Moutourwa 2306 Porhi 2307 Taïbong 2401 Kolofata 2402 Mora 2403 Tokombere 2501 Bourrha 2502 Hina 2503 Koza 2504 Mayo-Moskota 2505 Mogode 2506 Mokolo 2507 Soulede Roua 2601 Fiko 2602 Loum 2603 Manjo 2604 Mbanga 2605 Melong 2606 Njombe-Penja 2607 Nkongsamba 2699 Arrondissements with lower than 20,000 population in Moungo department 2799 Arrondissements with lower than 20,000 population in Nkam department 2801 Edéa 2802 Ngambe or Bambini 2899 Arrondissements with lower than 20,000 population in Sanaga Maritime department 2901 Douala 1 2902 Douala 2 2903 Douala 3 2904 Douala 4 2905 Douala 5 3001 Bibemi and Dembo 3002 Lagdo 3003 Garoua and Dembo 3004 Bascheo 3005 Demsa 3006 Touroua 3007 Pitoua 3008 Tcheboa 3009 Maroua 3101 Beka 3102 Poli 3201 Figuil 3202 Guider 3203 Mayo-Oulo 3301 Rey-Bouba 3302 Tcholliré 3303 Madingring 3304 Touboro 3305 Tchollire or Rey-Bouba 3401 Belo 3402 Fundong 3499 Arrondissements with lower than 20,000 population in Boyo department 3501 Jakiri 3502 Kumbo and Mbven 3503 Noni 3504 Oku 3505 Ako 3601 Misaje 3602 Ndu 3603 Nkambe 3604 Nwa 3605 Donga Matung department, district unknown 3701 Fungom 3702 Menchum-Valley and Furu-Awa 3703 Wum 3704 Menchum department district unknown 3801 Bafut 3802 Bali 3803 Bamenda 3804 Santa 3805 Tubah 3901 Batibo 3902 Mbengwi 3903 Widikum-Menka 3999 Arrondissements with lower than 20,000 population in Momo department 4001 Babessi 4002 Balikumbat 4003 Ndop 4004 Banjoun 4101 Babadjou 4102 Batcham 4103 Galim 4104 Mbouda 4201 Bafang 4202 Bandja 4203 Kekem 4204 Company 4299 Arrondissements with lower than 20,000 population in Haut Nkam department 4301 Baham 4302 Bamendjou 4399 Arrondissements with lower than 20,000 population in Hauts Plateaux department 4401 Poumougne 4499 Arrondissements with lower than 20,000 population in Koung Khi department 4501 Dschang 4502 Nkong-Ni 4503 Penka-Michel 4504 Santchou and Fokoue 4601 Bafoussam 4602 Baleng 4603 Bamougoum 4604 Penka-Michel or Bansoa 4701 Bangangte 4799 Arrondissements with lower than 20,000 population in Nde department 4801 Bangourain 4802 Foumban 4803 Foumbot 4804 Kouoptamo 4805 Koutaba 4806 Magba 4807 Malentouen 4808 Massangan 4901 Meyomessala 4902 Sangmelima 4903 Zoetele 4999 Arrondissements with lower than 20,000 population in Dja et Lobo department 5001 Ebolowa 5099 Arrondissements with lower than 20,000 population in Mvilla department 5101 Niete 5102 Kribi 5199 Arrondissements with lower than 20,000 population in Océan department 5201 Ambam 5202 Olamze and Ma'an 5301 Buea 5302 Limbe and West-Coast 5303 Muyuka 5304 Tiko 5305 Victoria 5401 Banguem 5402 Nguti 5403 Tombel 5501 Fontem 5502 Wabane and Alou 5599 " 5601 Akwaya 5602 Eyumodjock 5603 Mamfe 5604 Upper Bayang 5701 Kumba 5702 Konye 5703 Mbonge 5801 Bamusso 5802 Ekondo Titi 5899 Arrondissements with lower than 20,000 population in Ndian department Geography: A-E Variables -- HOUSEHOLD DHS-IPUMS-I Cameroon regions, 1976-2018 [consistent boundaries, GIS] DHS_IPUMSI_CM provides geographic codes for Cameroon that match those in the DHS and IPUMS-International databases. This variable can be used to link contextual area data from IPUMS-DHS to IPUMS-International or vice versa. The codes in DHS_IPUMSI_CM indicate the major administrative unit in which the household was enumerated or surveyed. GIS shapefiles for Cameroon can be downloaded here. 02 Centre, Sud 03 Est 04 Nord, Adamoua , Extrème Nord 05 Littoral, Douala 06 Nord Ouest 07 Ouest 10 Sud Ouest Geography: IPUMS-I, IPUMS-DHS 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 Number of rooms ROOMS indicates the number of rooms occupied by the housing unit. 00 Part of a room; no rooms 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) Dwelling Characteristics Variables -- HOUSEHOLD Toilet TOILET indicates whether the household had access to a toilet and, in most cases, whether it was a flush toilet or other type of installation. 00 NIU (not in universe) 10 No toilet 11 No flush toilet 20 Have toilet, type not specified 21 Flush toilet 22 Non-flush, latrine 23 Non-flush, other and unspecified 99 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 Number of deaths in household last year MORTNUM indicates the number of deaths in the household in the past year. 0 None 1 1 death 2 2 deaths 3 3 deaths 4 4 deaths 5 5 deaths 6 6 deaths 7 7 or more deaths 8 Unknown 9 NIU (not in universe) Other Household Variables -- HOUSEHOLD Any deaths in household last year ANYMORT indicates whether there were any deaths in the household in the past year. 1 Yes 2 No 8 Unknown/missing 9 NIU (not in universe) Other Household 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 Dwelling number Cameroon 1976: All records This variable indicates the dwelling number. This is a 7-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Type of dwelling Cameroon 1976: All households This variable indicates the type of dwelling. 1 Private household 2 Collective household 3 Unoccupied household Group Quarters Variables -- HOUSEHOLD Number of units Cameroon 1976: Occupied households [discrepancies: type I none; type II trace] This variable indicates the number of units. 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+ 98 Unknown 99 NIU (not in universe) Other Household Variables -- HOUSEHOLD Type of structure <svar v="CM76A044" a="all"><span class="em">28)Type of structure</span><br />Circle the corresponding number to the structure occupied by the household.<br /><div class="i1">[] 1 Isolated compartment/structure<br />[] 2 House with several compartments/accommodations<br />[] 3 Modern villa<br />[] 4 Apartment building (with floors)<br />[] 5 Religious space. Number of compartments _____<br />[] 6 Other</div><br /></svar></p> <p>Characteristics of the housing unit (Circle the number in each column: when it is a religious space, use the physical characteristics of the main compartment other than the number of rooms) Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.1%] This variable indicates the type of structure. 1 Isolated 2 Multi-unit 3 Modern villa 4 Apartment building 5 Concessions 6 Other 8 Unknown 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Number of huts <svar v="CM76A045 CM76A046 CM76A047 CM76A048 CM76A049 CM76A050 CM76A051 CM76A052"><span class="h2">Questions on housing</span><br /><br /><span class="h3">Columns 28 to 36: </span><br /><br />To answer these questions on housing, in each column circle the number of the characteristic corresponding to the structure and the housing unit which you are visiting. Only circle one number per column. <br /></svar></p> <p>[Example omitted]</p> <p><svar v="CM76A045">If the structure is a religious structure, you additionally mark the number of accommodations of the concession in column 28.<br /><br />If it is a religious space, the physical characteristics to reveal are those in the main accommodation (materials of the walls, the roof, floor, and lighting). Yet, the number of rooms to mark in column 32 is the total number of rooms used by the household, all accommodations included. As such, in the case of a religious space composed only of round accommodations/huts, the number of rooms (column 32) is most frequently equal to the number of accommodations (column 28). <br /></svar> Cameroon 1976: Concessions [discrepancies: type I 0.4%; type II 0.3%] This variable indicates the number of huts. 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) Other Household Variables -- HOUSEHOLD Wall material <svar v="CM76A046" a="all"><span class="em">29) What materials are the walls?</span><br /><div class="i1">[] 1 Concrete, concrete blocks, bricks<br />[] 2 Stone tiles<br />[] 3 Planking<br />[] 4 <span class="lang">Carabot</span> <br />[] 5 Clay, unbaked<br />[] 6 Adobe<br />[] 7 Mats, leaves or straw<br />[] 8 Other</div><br /></svar> <svar v="CM76A045 CM76A046 CM76A047 CM76A048 CM76A049 CM76A050 CM76A051 CM76A052"><span class="h2">Questions on housing</span><br /><br /><span class="h3">Columns 28 to 36: </span><br /><br />To answer these questions on housing, in each column circle the number of the characteristic corresponding to the structure and the housing unit which you are visiting. Only circle one number per column. <br /></svar></p> <p>[Example omitted]</p> <p><svar v="CM76A045">If the structure is a religious structure, you additionally mark the number of accommodations of the concession in column 28.<br /><br />If it is a religious space, the physical characteristics to reveal are those in the main accommodation (materials of the walls, the roof, floor, and lighting). Yet, the number of rooms to mark in column 32 is the total number of rooms used by the household, all accommodations included. As such, in the case of a religious space composed only of round accommodations/huts, the number of rooms (column 32) is most frequently equal to the number of accommodations (column 28). <br /></svar></p> <p><svar v="CM76A046" a="all"><span class="em">Wall materials</span> <br /><div class="i1">For a wall made of a partly hard material (adobe covered in cement), you keep 'adobe'.</div><br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.3%] This variable indicates the wall material. 0 NIU (not in universe) 1 Concrete, concrete blocks, bricks 2 Stone tiles 3 Planking 4 Carabot 5 Clay (unbaked) 6 Adobe 7 Mats, leaves or straw 8 Other 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Roof material <svar v="CM76A047" a="all"><span class="em">30) What material is the roof?</span><br /><div class="i1">[]1 Hard Cement<br />[] 2 Tile<br />[] 3 Earth<br />[] 4 Mats, thatch or leaves<br />[] 5 Other</div><br /></svar> <svar v="CM76A045 CM76A046 CM76A047 CM76A048 CM76A049 CM76A050 CM76A051 CM76A052"><span class="h2">Questions on housing</span><br /><br /><span class="h3">Columns 28 to 36: </span><br /><br />To answer these questions on housing, in each column circle the number of the characteristic corresponding to the structure and the housing unit which you are visiting. Only circle one number per column. <br /></svar></p> <p>[Example omitted]</p> <p><svar v="CM76A045">If the structure is a religious structure, you additionally mark the number of accommodations of the concession in column 28.<br /><br />If it is a religious space, the physical characteristics to reveal are those in the main accommodation (materials of the walls, the roof, floor, and lighting). Yet, the number of rooms to mark in column 32 is the total number of rooms used by the household, all accommodations included. As such, in the case of a religious space composed only of round accommodations/huts, the number of rooms (column 32) is most frequently equal to the number of accommodations (column 28). <br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.3%] This variable indicates the roof material. 1 Hard Cement 2 Tile 3 Earth 4 Mats, thatch or leaves 5 Other 8 Unknown 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Floor material <svar v="CM76A048" a="all"><span class="em">31) What is the material of the floors?</span><br /><div class="i1">[] 1 Cement<br />[] 2 Planking<br />[] 3 Earth<br />[] 4 Other</div><br /></svar> <svar v="CM76A045 CM76A046 CM76A047 CM76A048 CM76A049 CM76A050 CM76A051 CM76A052"><span class="h2">Questions on housing</span><br /><br /><span class="h3">Columns 28 to 36: </span><br /><br />To answer these questions on housing, in each column circle the number of the characteristic corresponding to the structure and the housing unit which you are visiting. Only circle one number per column. <br /></svar></p> <p>[Example omitted]</p> <p><svar v="CM76A045">If the structure is a religious structure, you additionally mark the number of accommodations of the concession in column 28.<br /><br />If it is a religious space, the physical characteristics to reveal are those in the main accommodation (materials of the walls, the roof, floor, and lighting). Yet, the number of rooms to mark in column 32 is the total number of rooms used by the household, all accommodations included. As such, in the case of a religious space composed only of round accommodations/huts, the number of rooms (column 32) is most frequently equal to the number of accommodations (column 28). <br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.3%] This variable indicates the floor material. 1 Cement 2 Planking 3 Earth 4 Other 8 Unknown 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Number of rooms <svar v="CM76A049" a="all"><span class="em">32) What is the total number of rooms in the housing unit?</span><br /><br />(Mark the total number of rooms) _ _<br /></svar> <svar v="CM76A045 CM76A046 CM76A047 CM76A048 CM76A049 CM76A050 CM76A051 CM76A052"><span class="h2">Questions on housing</span><br /><br /><span class="h3">Columns 28 to 36: </span><br /><br />To answer these questions on housing, in each column circle the number of the characteristic corresponding to the structure and the housing unit which you are visiting. Only circle one number per column. <br /></svar></p> <p>[Example omitted]</p> <p><svar v="CM76A045">If the structure is a religious structure, you additionally mark the number of accommodations of the concession in column 28.<br /><br />If it is a religious space, the physical characteristics to reveal are those in the main accommodation (materials of the walls, the roof, floor, and lighting). Yet, the number of rooms to mark in column 32 is the total number of rooms used by the household, all accommodations included. As such, in the case of a religious space composed only of round accommodations/huts, the number of rooms (column 32) is most frequently equal to the number of accommodations (column 28). <br /></svar></p> <p><svar v="CM76A045 CM76A049" a="all"><span class="em">Total number of rooms</span><br /><div class="i1">- You count: bedrooms, dining room, servant bedrooms, kitchen, and rooms used for professional operations, offices.<br /><br />- Hallways, verandas, vestibules, bathrooms, and outhouses should not be counted as rooms.<br /><br />- If a room is communal to 2 or more households, only assign it to one household between them.</div><br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.3%] This variable indicates the number of rooms. 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 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50+ 98 Unknown 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Type of lighting <svar v="CM76A050" a="all"><span class="em">33) What is the type of lighting?</span><br /><div class="i1">[] 1 Electricity<br />[] 2 Kerosene<br />[] 3 Oil<br />[] 4 Firwood<br />[] 5 Resin<br />[] 6 Other</div><br /></svar> <svar v="CM76A045 CM76A046 CM76A047 CM76A048 CM76A049 CM76A050 CM76A051 CM76A052"><span class="h2">Questions on housing</span><br /><br /><span class="h3">Columns 28 to 36: </span><br /><br />To answer these questions on housing, in each column circle the number of the characteristic corresponding to the structure and the housing unit which you are visiting. Only circle one number per column. <br /></svar></p> <p>[Example omitted]</p> <p><svar v="CM76A045">If the structure is a religious structure, you additionally mark the number of accommodations of the concession in column 28.<br /><br />If it is a religious space, the physical characteristics to reveal are those in the main accommodation (materials of the walls, the roof, floor, and lighting). Yet, the number of rooms to mark in column 32 is the total number of rooms used by the household, all accommodations included. As such, in the case of a religious space composed only of round accommodations/huts, the number of rooms (column 32) is most frequently equal to the number of accommodations (column 28). <br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.3%] This variable indicates the type of lighting. 1 Electric 2 Kerosene 3 Oil 4 Firewood 5 Resin 6 Other 8 Unknown 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Source of water <svar v="CM76A051" a="all"><span class="em">34) What is the source of water?</span><br /><div class="i1">[] 1 Running water<br />[] 2 Hydrant<br />[] 3 Well<br />[] 4 Spring<br />[] 5 River or marsh/backwater<br />[] 6 Other</div><br /></svar> <svar v="CM76A045 CM76A046 CM76A047 CM76A048 CM76A049 CM76A050 CM76A051 CM76A052"><span class="h2">Questions on housing</span><br /><br /><span class="h3">Columns 28 to 36: </span><br /><br />To answer these questions on housing, in each column circle the number of the characteristic corresponding to the structure and the housing unit which you are visiting. Only circle one number per column. <br /></svar></p> <p>[Example omitted]</p> <p><svar v="CM76A045">If the structure is a religious structure, you additionally mark the number of accommodations of the concession in column 28.<br /><br />If it is a religious space, the physical characteristics to reveal are those in the main accommodation (materials of the walls, the roof, floor, and lighting). Yet, the number of rooms to mark in column 32 is the total number of rooms used by the household, all accommodations included. As such, in the case of a religious space composed only of round accommodations/huts, the number of rooms (column 32) is most frequently equal to the number of accommodations (column 28). <br /></svar></p> <p><svar v="CM76A051" a="all"><span class="em">Water supply</span><br /><div class="i1">- Running water: regarding the building or the structure supplied with water by interior water pipes (interior to the structure) which are permanent. <br /><br />- Outdoor public faucets are drinking fountains. For a household that gets its water at wells during the dry season and at the marshland or in another pond in rainy seasons, keep river or marshland.</div><br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.3%] This variable indicates the source of water. 1 Running water 2 Hydrant 3 Well 4 Spring 5 River, creek 6 Other 8 Unknown 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Type of toilet facility <svar v="CM76A052" a="all"><span class="em">35) What is the type of toilet facility?</span><br /><div class="i1">[] 1 Flush toilet<br />[] 2 Latrine<br />[] 3 Other</div><br /></svar> <svar v="CM76A045 CM76A046 CM76A047 CM76A048 CM76A049 CM76A050 CM76A051 CM76A052"><span class="h2">Questions on housing</span><br /><br /><span class="h3">Columns 28 to 36: </span><br /><br />To answer these questions on housing, in each column circle the number of the characteristic corresponding to the structure and the housing unit which you are visiting. Only circle one number per column. <br /></svar></p> <p>[Example omitted]</p> <p><svar v="CM76A045">If the structure is a religious structure, you additionally mark the number of accommodations of the concession in column 28.<br /><br />If it is a religious space, the physical characteristics to reveal are those in the main accommodation (materials of the walls, the roof, floor, and lighting). Yet, the number of rooms to mark in column 32 is the total number of rooms used by the household, all accommodations included. As such, in the case of a religious space composed only of round accommodations/huts, the number of rooms (column 32) is most frequently equal to the number of accommodations (column 28). <br /></svar></p> <p><svar v="CM76A052" a="all"><span class="em">Type of toilet</span><br /><br />This is about the type of toilet used by the household that can be different from installations used by other households in the same structure as the first. <br /><div class="i1">-With a flush: This is regarding all the modern installations with a flush.<br /><br />-Latrine: all installations that do not have a flush, including simple holes<br /><br />- Other: installations other than those listed above.</div><br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.3%] This variable indicates the type of toilet facility. 1 Flush toilet 2 Pit latrine 3 Other 8 Unknown 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Type of occupancy <svar v="CM76A053" a="all"><span class="em">38) What is the ownership status of the dwelling?</span><br /><div class="i1">[] 1 Owned<br />[] 2 Rented<br />[] 3 Employer provided lodging, with contribution<br />[] 4 Employer provided lodging, free<br />[] 5 Free from another source besides employer</div><br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.3%] This variable indicates the type of occupancy. 1 Owner 2 Renting 3 Employer provided lodging with contribution 4 Employer provided lodging, free 5 Free from another source besides employer 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Total births (males) <svar v="CM76A425 CM76A426 CM76A054 CM76A055" a="all"><span class="h3">26) Births</span><br /><br />Have there been any births in this household during the period from ______ to _______<br />Mark an x in the proper box<br /><br />Yes [ ] No [ ]<br /><br /><div class="i1">If yes, specify the sex of the child, the order number and the age of the mother.</div><br /><div class="i2">Order number of mother ____<br />Sex of child __<br />Age of mother _ _</div><br /></svar> <svar v="CM76A054 CM76A055" a="all"><span class="em">Column 26: Births:</span><br /><br />Ask if there were any births in this household from April 9, 1975 to April 8, 1976 (make an effort to respect this period), whether the child is currently present or absent, living or deceased. Only consider live births (children who cried after birth). <br /><br />Mark a cross in the square corresponding to the correct answer (if a cross was inadvertently marked in the wrong square, black out this square completely and mark the cross in the square corresponding to the correct response.)<br /><br /><div class="i1">If NO: go to the next question.<br /><br />If YES: mark in the corresponding columns the order number of the mother, the sex of the child (M for male, F for female) and the age of the mother in years passed.</div><br /><br />The other number of the mother is the number marked in column 1 of the questionnaire and the age of the mother is the age marked in column 9.<br /><br />[Example omitted]<br /><br />N.B. A birth should only be marked on the household sheet where the mother was living during the event. <br /><br />Meanwhile, if the mother and her baby no longer live in the household where the birth took place at the time of the survey, they will not be surveyed in this household, but in the household where they currently live. <br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.2%] This variable indicates the total number of male births in the household during the reference period. 00 0 01 1 02 2 03 3 04 4 05 5 06 6+ 98 Unknown 99 NIU (not in universe) Other Household Variables -- HOUSEHOLD Total births (females) <svar v="CM76A425 CM76A426 CM76A054 CM76A055" a="all"><span class="h3">26) Births</span><br /><br />Have there been any births in this household during the period from ______ to _______<br />Mark an x in the proper box<br /><br />Yes [ ] No [ ]<br /><br /><div class="i1">If yes, specify the sex of the child, the order number and the age of the mother.</div><br /><div class="i2">Order number of mother ____<br />Sex of child __<br />Age of mother _ _</div><br /></svar> <svar v="CM76A054 CM76A055" a="all"><span class="em">Column 26: Births:</span><br /><br />Ask if there were any births in this household from April 9, 1975 to April 8, 1976 (make an effort to respect this period), whether the child is currently present or absent, living or deceased. Only consider live births (children who cried after birth). <br /><br />Mark a cross in the square corresponding to the correct answer (if a cross was inadvertently marked in the wrong square, black out this square completely and mark the cross in the square corresponding to the correct response.)<br /><br /><div class="i1">If NO: go to the next question.<br /><br />If YES: mark in the corresponding columns the order number of the mother, the sex of the child (M for male, F for female) and the age of the mother in years passed.</div><br /><br />The other number of the mother is the number marked in column 1 of the questionnaire and the age of the mother is the age marked in column 9.<br /><br />[Example omitted]<br /><br />N.B. A birth should only be marked on the household sheet where the mother was living during the event. <br /><br />Meanwhile, if the mother and her baby no longer live in the household where the birth took place at the time of the survey, they will not be surveyed in this household, but in the household where they currently live. <br /></svar> Cameroon 1976: Occupied households [discrepancies: type I none; type II 0.2%] This variable indicates the total number of female births in the household for the reference period. 00 0 01 1 02 2 03 3 04 4 05 5 06 6+ 98 Unknown 99 NIU (not in universe) Other Household Variables -- HOUSEHOLD Sex (first death) <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="h3">27) Deaths</span><br />Have there been any deaths in this household during the period from _____ to _______<br />Mark an x in the proper box<br /><br />Yes [ ] No [ ]<br /><br /><div class="i1">If yes, specify the sex and the age of the deceased</div><br /><div class="i2">Sex of the deceased __<br />Age of the deceased _ _</div><br /></svar> <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="em">Column 27: Deaths.</span><br /><br />Ask if there has been a death in this household over the course of the period from April 9 1975 to April 8 1976 (take care to respect this period). <br /><br />Mark a cross in the square corresponding to the correct answer. <br /><div class="i1">If NO: go to the question on housing.<br />If YES: mark the sex of the deceased (M for male, F for female) and the age of the deceased (in years passed) in the corresponding columns.</div><br /><br />N.B. If a child is born during the period of reference and died between the moment of his or her birth and the beginning of the survey period, he or she must count both in 'births' and 'deaths'.<br /><br />If a child is born during the period of reference and he or she doesn't count among the deceased or among the household members, this means either he left the household, or he died between April 9 1976 and the time of the your visit to this household. In this case, mark him in "observations": this will show that you didn't make an error in filling out the questionnaire. <br /></svar> Cameroon 1976: Occupied households with at least 1 death [universe unverifiable] This variable indicates the sex of the first deceased person in the household. 1 Male 2 Female 8 Unknown 9 NIU (not in universe) Other Household Variables -- HOUSEHOLD Age (first death) <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="h3">27) Deaths</span><br />Have there been any deaths in this household during the period from _____ to _______<br />Mark an x in the proper box<br /><br />Yes [ ] No [ ]<br /><br /><div class="i1">If yes, specify the sex and the age of the deceased</div><br /><div class="i2">Sex of the deceased __<br />Age of the deceased _ _</div><br /></svar> <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="em">Column 27: Deaths.</span><br /><br />Ask if there has been a death in this household over the course of the period from April 9 1975 to April 8 1976 (take care to respect this period). <br /><br />Mark a cross in the square corresponding to the correct answer. <br /><div class="i1">If NO: go to the question on housing.<br />If YES: mark the sex of the deceased (M for male, F for female) and the age of the deceased (in years passed) in the corresponding columns.</div><br /><br />N.B. If a child is born during the period of reference and died between the moment of his or her birth and the beginning of the survey period, he or she must count both in 'births' and 'deaths'.<br /><br />If a child is born during the period of reference and he or she doesn't count among the deceased or among the household members, this means either he left the household, or he died between April 9 1976 and the time of the your visit to this household. In this case, mark him in "observations": this will show that you didn't make an error in filling out the questionnaire. <br /></svar> Cameroon 1976: Occupied households with at least 1 death [discrepancies: type I trace; type II 0.9%] This variable indicates the age of the first deceased person in the household. 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 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 and above 98 Unknown 99 NIU (not in universe) Other Household Variables -- HOUSEHOLD Sex (second death) <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="h3">27) Deaths</span><br />Have there been any deaths in this household during the period from _____ to _______<br />Mark an x in the proper box<br /><br />Yes [ ] No [ ]<br /><br /><div class="i1">If yes, specify the sex and the age of the deceased</div><br /><div class="i2">Sex of the deceased __<br />Age of the deceased _ _</div><br /></svar> <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="em">Column 27: Deaths.</span><br /><br />Ask if there has been a death in this household over the course of the period from April 9 1975 to April 8 1976 (take care to respect this period). <br /><br />Mark a cross in the square corresponding to the correct answer. <br /><div class="i1">If NO: go to the question on housing.<br />If YES: mark the sex of the deceased (M for male, F for female) and the age of the deceased (in years passed) in the corresponding columns.</div><br /><br />N.B. If a child is born during the period of reference and died between the moment of his or her birth and the beginning of the survey period, he or she must count both in 'births' and 'deaths'.<br /><br />If a child is born during the period of reference and he or she doesn't count among the deceased or among the household members, this means either he left the household, or he died between April 9 1976 and the time of the your visit to this household. In this case, mark him in "observations": this will show that you didn't make an error in filling out the questionnaire. <br /></svar> Cameroon 1976: Occupied households with at least 2 deaths [universe unverifiable] This variable indicates the sex of the second deceased person in the household. 1 Male 2 Female 8 Unknown 9 NIU (not in universe) Other Household Variables -- HOUSEHOLD Age (second death) <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="h3">27) Deaths</span><br />Have there been any deaths in this household during the period from _____ to _______<br />Mark an x in the proper box<br /><br />Yes [ ] No [ ]<br /><br /><div class="i1">If yes, specify the sex and the age of the deceased</div><br /><div class="i2">Sex of the deceased __<br />Age of the deceased _ _</div><br /></svar> <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="em">Column 27: Deaths.</span><br /><br />Ask if there has been a death in this household over the course of the period from April 9 1975 to April 8 1976 (take care to respect this period). <br /><br />Mark a cross in the square corresponding to the correct answer. <br /><div class="i1">If NO: go to the question on housing.<br />If YES: mark the sex of the deceased (M for male, F for female) and the age of the deceased (in years passed) in the corresponding columns.</div><br /><br />N.B. If a child is born during the period of reference and died between the moment of his or her birth and the beginning of the survey period, he or she must count both in 'births' and 'deaths'.<br /><br />If a child is born during the period of reference and he or she doesn't count among the deceased or among the household members, this means either he left the household, or he died between April 9 1976 and the time of the your visit to this household. In this case, mark him in "observations": this will show that you didn't make an error in filling out the questionnaire. <br /></svar> Cameroon 1976: Occupied households with at least 2 deaths [discrepancies: type I trace; type II 0.1%] This variable indicates the age of the second deceased person in the household. 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 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 33 33 34 34 35 35 36 36 38 38 39 39 40 40 41 41 43 43 45 45 46 46 47 47 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 63 63 64 64 65 65 66 66 68 68 69 69 70 70+ 99 NIU (not in universe) Other Household Variables -- HOUSEHOLD Sex (third death) <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="h3">27) Deaths</span><br />Have there been any deaths in this household during the period from _____ to _______<br />Mark an x in the proper box<br /><br />Yes [ ] No [ ]<br /><br /><div class="i1">If yes, specify the sex and the age of the deceased</div><br /><div class="i2">Sex of the deceased __<br />Age of the deceased _ _</div><br /></svar> <svar v="CM76A056 CM76A057 CM76A058 CM76A059 CM76A060 CM76A061 CM76A062 CM76A063 CM76A064 CM76A065 CM76A066 CM76A067 CM76A068 CM76A069 CM76A070 CM76A071 CM76A072 CM76A073 CM76A074 CM76A075" a="all"><span class="em">Column 27: Deaths.</span><br /><br />Ask if there has been a death in this household over the course of the period from April 9 1975 to April 8 1976 (take care to respect this period). <br /><br />Mark a cross in the square corresponding to the correct answer. <br /><div class="i1">If NO: go to the question on housing.<br />If YES: mark the sex of the deceased (M for male, F for female) and the age of the deceased (in years passed) in the corresponding columns.</div><br /><br />N.B. If a child is born during the period of reference and died between the moment of his or her birth and the beginning of the survey period, he or she must count both in 'births' and 'deaths'.<br /><br />If a child is born during the period of reference and he or she doesn't count among the deceased or among the household members, this means either he left the household, or he died between April 9 1976 and the time of the your visit to this household. In this case, mark him in "observations": this will show that you didn't make an error in filling out the questionnaire. <br /></svar> Cameroon 1976: Occupied households with at least 3 deaths [universe unverifiable] This variable indicates the sex of the third deceased person in the household. 1 Male 2 Female 9 NIU (not in universe) Other Household Variables -- HOUSEHOLD Strata Cameroon 1976: All households This variable is the strata identifier for the sample. Strata is a constructed variable that captures the 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 5-digit numeric variable with 0 implied decimal places Geography: A-E 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 Residence status: de facto, de jure RESIDENT identifies whether an enumerated person is a household resident or a visitor and whether she or he was present at the time of enumeration. This variable is available only in samples that enumerated both de facto and de jure residents. It can be used to eliminate the double-counting of persons who were enumerated both at their permanent residence and at the residence they were visiting on census night. De jure population: present residents and absent residents. De facto population: present residents and visitors/non-residents. 1 Present resident 2 Absent resident 3 Visitor/non-resident 4 De facto population (present persons) 9 Unknown/missing 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 Polygamous union POLYGAM indicates whether the respondent was in a polygamous union and, in some samples, the number of wives or the rank order of the wife. 00 NIU (not in universe) 01 No, in monogamous union 02 Yes, in polygamous union 03 Man in polygamous union 04 Polygamous man, 2 wives 05 Polygamous man, 3 or more wives 06 Woman in polygamous union 07 Polygamous marriage, 2 wives 08 Polygamous marriage, 3 or more wives 09 First wife 10 Second wife 11 Third or higher order wife 99 Unknown/missing 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 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 Country of birth BPLCOUNTRY indicates the person's country of birth. 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11005 British Indian Ocean Territory 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11051 Ethiopia (including Eritrea) 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 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 15021 Upper Volta 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15081 Guinea-Bissau and Cape Verde 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15180 Canary Islands 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 21200 St. Croix 21210 St. John 21220 St. Lucia 21230 St Thomas 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21991 Caribbean commonwealth, n.s. 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 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 32042 India/Pakistan/Bangladesh/Sri Lanka 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32101 Pakistan/Bangladesh 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 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 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 34071 Israel/Palestine 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34111 West Bank 34112 Gaza Strip 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 41991 Albania, Bulgaria, Czech, Hungary, Romania, Yugoslavia 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 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 43121 Spain/Portugal 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43991 Gibraltar/Malta 43992 Portugal/Greece 43993 Italy, Holy See, San Marino 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44021 Belgium/Luxemburg 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44042 West Germany 44043 Germany/Austria 44044 Mecklenburg-Schwerin 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44991 Belgium, Denmark, Luxembourg, Netherlands 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (original 15) 49994 Other European Union (not original 15) 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 53060 Federated States of Micronesia 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. 80000 AT SEA 90000 Other countries n.s. 99999 Unknown 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, Cameroon; [Level 1: consistent boundaries, GIS] BPL1_CM indicates the person's province of birth within Cameroon. Birthplace province codes for BPL1_CM are compatible with codes for GEO1_CM. Refer to BPL2_CM for a person's department of birth. 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. 120002 Centre, Sud 120003 Est 120004 Nord, Adamoua, Extrème Nord 120005 Littoral 120007 Nord Ouest 120008 Ouest 120010 Sud Ouest 120097 Foreign country 120098 Unknown Nativity and Birthplace Variables -- PERSON Department of birth, Cameroon; [Level 2: consistent boundaries, GIS] BPL2_CM indicates the person's department of birth within Cameroon. Birthplace department codes for BPL2_CM are compatible with codes for GEO2_CM. Refer to BPL1_CM for a person's province of birth. 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. 120002001 Haute Sanaga 120002002 Lekié 120002003 Mbam et Inoubou, Mbam et Kim 120002004 Mefou et Akono, Mefou et Afamba 120002005 Mfoundi 120002006 Nyong et Kéllé 120002007 Nyong et Mfoumou 120002008 Nyong et So'o 120002009 Dja et Lobo 120002010 Mvilla, Vallée du Ntem, Océan 120003001 Boumba et Ngoko 120003002 Haut Nyong 120003003 Kadey 120003004 Lom et Djerem 120004001 Vina, Djerem, Faro et Déo, Mayo Banyo, Mbéré 120004002 Diamaré, Mayo Kani 120004003 Logone et Chari 120004004 Mayo Danay 120004005 Mayo Tsanaga, Mayo Sava 120004006 Mayo Louti, Bénoué, Faro, Mayo Rey 120005001 Moungo 120005002 Nkam 120005003 Sanaga Maritime 120005004 Wouri 120007001 Menchum, Boyo 120007002 Bui 120007003 Donga Mantung 120007004 Mezam, Ngo Ketungja 120007005 Momo 120008001 Bamboutos 120008002 Haut Nkam 120008003 Mifi, Hauts Plateaux, Koung Khi 120008004 Menoua 120008005 Ndé 120008006 Noun 120010001 Fako 120010002 Koupe et Manengouba, Meme 120010003 Manyu, Lebialem 120010004 Ndian 120097097 Abroad 120098098 Unknown Nativity and Birthplace Variables -- PERSON Arrondissement of birth, Cameroon BPLCM indicates the district in Cameroon in which the person was born. 0101 Ngaoundal 0102 Tibati 0201 Galim Tignere 0202 Tignere 0203 Mayo Baleo 0204 Kontcha 0301 Bankim 0302 Banyo 0303 Mayo Darlé 0401 Dir 0402 Meiganga 0403 Belel 0404 Djohong 0405 Ngaoui 0501 Mbe 0502 Ngaoundéré 0601 Mbandjock 0602 Nanga Eboko 0603 Nkoteng 0604 Minta 0605 Bibey 0606 Lembe Yezoum 0607 Nsem 0701 Ebebda 0702 Monatele 0703 Obala 0704 Batchenga 0705 Okola 0706 Lobo 0707 Saa 0708 Elig Mfomo 0709 Evodoula 0801 Bafia 0802 Bokito 0803 Makenene 0804 Ombessa 0805 Deuk 0806 Ndikinimiki 0807 Nitoukou 0901 Mbangassina 0902 Ntui 0903 Ngambe Tikar 0904 Ngoro 0905 Yoko 1001 Mfou 1002 Soa 1003 Awae 1004 Assamba 1005 Esse 1006 Afanloum 1007 Edzendouan 1008 Nkolafamba 1101 Mbankomo 1102 Akono 1103 Bikok 1104 Ngoumou 1201 Yaounde I 1202 Yaounde II 1203 Yaounde III 1204 Yaounde IV 1205 Yaounde V 1206 Yaounde VI 1301 Eseka 1302 Makak 1303 Bot Makak 1304 Nguibassal 1305 Dibang 1306 Bondjock 1307 Matomb 1308 Messondo 1309 Biyouha 1310 Ngok Mapubi 1401 Akonolinga 1402 Ayos 1403 Mengang 1404 Nyakombo 1405 Endom 1501 Mbalmayo 1502 Dzeng 1503 Akoeman 1504 Mengueme 1505 Nkolmetet 1506 Ngomedzap 1601 Yokadouma 1602 Abong Mbang 1603 Gari Gombo 1604 Moloundou 1605 Salapoumbe 1701 Bebeng 1702 Dja 1703 Mboanz 1704 Dimako 1705 Doume 1706 Doumaintang 1707 Lomie 1708 Messok 1709 Messamena 1710 Salalomo 1711 Ngoyla 1712 Nguelemedouka 1713 Mboma 1801 Batouri 1802 Kette 1803 Mbang 1804 Ndelele 1805 Belabo 1806 Ndem-Nam 1807 Mbotoro 1808 Bombe 1901 Bétaré-Oya 1902 Ngoura 1903 Bertoua 1904 Diang 1905 Garoua-Boulaï 2001 Bogo 2002 Gazawa 2003 Maroua 2004 Dargala 2005 Ndoukoula 2006 Meri 2007 Pette 2101 Blangoua 2102 Darak 2103 Fotokol 2104 Goulfey 2105 Kousseri 2106 Logone-Birni 2107 Makari 2108 Hile-Halifa 2109 Zina 2110 Waza 2201 Datcheka 2202 Gobo 2203 Guere 2204 Kaïkaï 2205 Kalfou 2206 Kar-Hay 2207 Maga 2208 Tchatibali 2209 Vele 2210 Wina 2211 Yagoua 2301 Guidiguis 2302 Kaele 2303 Mindif 2304 Moulvoudaye 2305 Moutourwa 2306 Porhi 2307 Taïbong 2401 Kolofata 2402 Mora 2403 Tokombere 2501 Bourrha 2502 Hina 2503 Koza 2504 Mayo-Moskota 2505 Mogode 2506 Mokolo 2507 Soulede Roua 2601 Bare-Bakem 2602 Dibombari 2603 Fiko 2604 Loum 2605 Manjo 2606 Mbanga 2607 Melong 2608 Njombe-Penja 2609 Nkongsamba 2610 Mombo 2611 Nlonako 2701 Nkondjock 2702 Nord-Makombe 2703 Yabassi 2704 Yingui 2801 Dizangue 2802 Edéa 2803 Ngambe or Bambini 2804 Mouanko 2805 Ndom 2806 Nyanon 2807 Ngambe 2808 Massok-Songloulou 2809 Pouma 2901 Douala 1 2902 Douala 2 2903 Douala 3 2904 Douala 4 2905 Douala 5 2906 Manoka 3001 Bibemi 3002 Dembo 3003 Lagdo 3004 Garoua 3005 Bascheo 3006 Demsa 3007 Touroua 3008 Pitoua 3009 Tcheboa 3101 Beka 3102 Poli 3201 Figuil 3202 Guider 3203 Mayo-Oulo 3301 Rey-Bouba 3302 Tcholliré 3303 Madingring 3304 Touboro 3305 Tchollire or Rey-Bouba 3401 Belo 3402 Fundong 3403 Bum 3404 Njinikom 3501 Jakiri 3502 Kumbo 3503 Mbven 3504 Noni 3505 Oku 3506 Ako 3601 Misaje 3602 Ndu 3603 Nkambe 3604 Nwa 3701 Fungom 3702 Furu-Awa 3703 Menchum-Valley 3704 Wum 3801 Bafut 3802 Bali 3803 Bamenda 3804 Santa 3805 Tubah 3901 Batibo 3902 Mbengwi 3903 Widikum-Menka 3904 Ngie 3905 Njikwa 4001 Babessi 4002 Balikumbat 4003 Ndop 4004 Banjoun 4101 Babadjou 4102 Batcham 4103 Galim 4104 Mbouda 4201 Bafang 4202 Bandja 4203 Kekem 4204 Company 4205 Bakou 4206 Bana 4207 Banwa 4301 Baham 4302 Bamendjou 4303 Batie 4304 Bangou 4401 Poumougne 4402 Bayangam 4403 Djebem 4501 Dschang 4502 Fokoue 4503 Nkong-Ni 4504 Penka-Michel 4505 Santchou 4601 Bafoussam 4602 Baleng 4603 Bamougoum 4604 Penka-Michel or Bansoa (1976) 4701 Bangangte 4702 Bassamba 4703 Bazou 4704 Tonga 4801 Bangourain 4802 Foumban 4803 Foumbot 4804 Kouoptamo 4805 Koutaba 4806 Magba 4807 Malentouen 4808 Massangan 4901 Djoum 4902 Meyomessala 4903 Sangmelima 4904 Zoetele 4905 Bengbis 4906 Mintom 4907 Oveng 5001 Ebolowa 5002 Mengong 5003 Mvangan 5004 Biwong-Bane 5005 Ngoulemakong 5101 Niete 5102 Kribi 5103 Akom II 5104 Bipindi 5105 Campo 5106 Lolodorf 5107 Mvengue 5201 Ambam 5202 Ma'an 5203 Olamze 5301 Buea 5302 West-Coast 5303 Limbe 5304 Muyuka 5305 Tiko 5306 Victoria 5401 Banguem 5402 Nguti 5403 Tombel 5501 Alou 5502 Fontem 5503 Wabane 5601 Akwaya 5602 Eyumodjock 5603 Mamfe 5604 Upper Bayang 5701 Kumba 5702 Konye 5703 Mbonge 5801 Bamusso 5802 Ekondo Titi 5803 Dikome-Balue 5804 Idabato 5805 Isanguele 5806 Kombo Abedimo 5807 Kombo-Itindi 5808 Mumdemba 5809 Toko 9997 Cameroon - unknown arrondissement 9998 Foreign country 9999 Unknown Nativity and Birthplace 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 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, Cameroon EDUCCM indicates the person's educational attainment in Cameroon in terms of the level of schooling completed. 100 No education 200 Preschool 201 Preschool, year 1 202 Preschool, year 2 203 Preschool, year 3 204 Preschool, year unknown 310 Primary, French system 311 Primary, French system, grade 1 312 Primary, French system, grade 2 313 Primary, French system, grade 3 314 Primary, French system, grade 4 315 Primary, French system, grade 5 316 Primary, French system, grade 6 317 Primary, French system, grade unknown 320 Primary, English system 321 Primary, English system, grade 1 322 Primary, English system, grade 2 323 Primary, English system, grade 3 324 Primary, English system, grade 4 325 Primary, English system, grade 5 326 Primary, English system, grade 6 327 Primary, English system, grade 7 328 Primary, English system, grade unknown 330 Primary, French or English system 331 Primary, French or English system, grade 1 332 Primary, French or English system, grade 2 333 Primary, French or English system, grade 3 334 Primary, French or English system, grade 4 335 Primary, French or English system, grade 5 336 Primary, French or English system, grade 6 337 Primary, French or English system, grade 7 340 Primary, other system 341 Primary, other system, grade 1 342 Primary, other system, grade 2 343 Primary, other system, grade 3 344 Primary, other system, grade 4 345 Primary, other system, grade 5 346 Primary, other system, grade 6 347 Primary, other system, grade unknown 410 Secondary, French system 411 Secondary, French system, grade 1 412 Secondary, French system, grade 2 413 Secondary, French system, grade 3 414 Secondary, French system, grade 4 415 Secondary, French system, grade 5 416 Secondary, French system, grade 6 417 Secondary, French system, grade 7 418 Secondary, French system, grade unknown 420 Secondary, English system 421 Secondary, English system, grade 1 422 Secondary, English system, grade 2 423 Secondary, English system, grade 3 424 Secondary, English system, grade 4 425 Secondary, English system, grade 5 426 Secondary, English system, grade 6 427 Secondary, English system, grade 7 428 Secondary, English system, grade unknown 430 Secondary, French or English system 431 Secondary, French or English system, grade 1 432 Secondary, French or English system, grade 2 433 Secondary, French or English system, grade 3 434 Secondary, French or English system, grade 4 435 Secondary, French or English system, grade 5 436 Secondary, French or English system, grade 6 437 Secondary, French or English system, grade 7 438 Secondary, French or English system, first cycle, grade unknown 439 Secondary, French or English system, second cycle, grade unknown 440 Secondary techinical, French system 441 Secondary technical, French system, grade 1 442 Secondary technical, French system, grade 2 443 Secondary technical, French system, grade 3 444 Secondary technical, French system, grade 4 445 Secondary technical, French system, grade 5 446 Secondary technical, French system, grade 6 447 Secondary technical, French system, grade 7 448 Secondary technical, French system, grade unknown 450 Secondary technical, English system 451 Secondary technical, English system, grade 1 452 Secondary technical, English system, grade 2 453 Secondary technical, English system, grade 3 454 Secondary technical, English system, grade 4 455 Secondary technical, English system, grade 5 456 Secondary technical, English system, grade 6 457 Secondary technical, English system, grade 7 458 Secondary technical, English system, grade unknown 460 Secondary technical, French or English system 461 Secondary technical, French or English system, grade 1 462 Secondary technical, French or English system, grade 2 463 Secondary technical, French or English system, grade 3 464 Secondary technical, French or English system, grade 4 465 Secondary technical, French or English system, grade 5 466 Secondary technical, French or English system, grade 6 467 Secondary technical, French or English system, grade 7 468 Secondary technical, French or English system, first cycle, grade unknown 469 Secondary technical, French or English system, second cycle, grade unknown 510 Technical post-primary 511 Technical post-primary, year 1 512 Technical post-primary, year 2 513 Technical post-primary, year 3 514 Technical post-primary, year 4 515 Technical post-primary, year unknown 520 Technical post-CEP 521 Technical post-CEP, year 1 522 Technical post-CEP, year 2 523 Technical post-CEP, year 3 524 Technical post-CEP, year unknown 530 Technical post-BEPC 531 Technical post-BEPC, year 1 532 Technical post-BEPC, year 1 533 Technical post-BEPC, year 3 534 Technical post-BEPC, year unknown 540 Technical post-probation 541 Technical post-probation, year 1 542 Technical post-probation, year 2 543 Technical post-probation, year 3 544 Technical post-probation, year unknown 550 Technical post-baccalaureate and higher 551 Technical post-BAC and higher, year 1 552 Technical post-BAC and higher, year 2 553 Technical post-BAC and higher, year 3 554 Technical post-BAC and higher, year 4 555 Technical post-BAC and higher, year 5 556 Technical post-BAC and higher, year 6 557 Technical post-BAC and higher, year unknown 560 Old teacher's school 561 Old teacher's school, year 1 562 Old teacher's school, year 2 563 Old teacher's school, year 3 564 Old teacher's school, year 4 565 Old teacher's school, year unknown 570 Teacher's school 571 Teacher's school, year 1 572 Teacher's school, year 2 573 Teacher's school, year 3 574 Teacher's school, year 4 575 Teacher's school, year 5 576 Teacher's school, year unknown 610 Higher specialized education 611 Higher specialized education, year 1 612 Higher specialized education, year 2 613 Higher specialized education, year 3 614 Higher specialized education, year 4 615 Higher specialized education, year 5 616 Higher specialized education, year 6 617 Higher specialized education, year 7 618 Higher specialized education, year unknown 620 University 621 University, year 1 622 University, year 2 623 University, year 3 624 University, year 4 625 University, year 5 626 University, year 6 627 University, year 7 628 Year 8+ 629 University, year unknown 710 Koranic school 711 Koranic school, grade 1 712 Koranic school, grade 2 713 Koranic school, grade 3 714 Koranic school, grade 4 715 Koranic school, grade 5 716 Koranic school, grade 6 717 Koranic school, grade 7 718 Koranic school, grade unknown 998 Unknown 999 NIU (not in universe) 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 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 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 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, Cameroon; consistent boundaries, GIS MIG1_P_CM indicates the person's previous province of residence within Cameroon. 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. 120002 Centre, Sud 120003 Est 120004 Nord, Adamoua, Extrème Nord 120005 Littoral 120007 Nord Ouest 120008 Ouest 120010 Sud Ouest 120096 Cameroon - unknown arrondissement 120097 Foreign country 120098 Unknown 120099 NIU (not in universe) Migration: A-E Variables -- PERSON Arrondissement/Department of previous residence, Cameroon; consistent boundaries, GIS MIG2_P_CM indicates the person's department of previous residence within Cameroon. Migration department codes for MIG2_P_CM are compatible with codes for GEO2_CM. 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. 120002001 Haute Sanaga 120002002 Lekié 120002003 Mbam et Inoubou, Mbam et Kim 120002004 Mefou et Akono, Mefou et Afamba 120002005 Mfoundi 120002006 Nyong et Kéllé 120002007 Nyong et Mfoumou 120002008 Nyong et So'o 120002009 Dja et Lobo 120002010 Mvilla, Vallée du Ntem, Océan 120002099 Centre, Sud provinces, unknown department 120003001 Boumba et Ngoko 120003002 Haut Nyong 120003003 Kadey 120003004 Lom et Djerem 120003099 Est province, unknown department 120004001 Vina, Djerem, Faro et Déo, Mayo Banyo, Mbéré 120004002 Diamaré, Mayo Kani 120004003 Logone et Chari 120004004 Mayo Danay 120004005 Mayo Tsanaga, Mayo Sava 120004006 Mayo Louti, Bénoué, Faro, Mayo Rey 120004099 Nord, Adamoua , Extrème Nord provinces, unknown department 120005001 Moungo 120005002 Nkam 120005003 Sanaga Maritime 120005004 Wouri 120005099 Littoral province, department unknown 120007001 Menchum, Boyo 120007002 Bui 120007003 Donga Mantung 120007004 Mezam, Ngo Ketungja 120007005 Momo 120007099 Nord Ouest province, unknown department 120008001 Bamboutos 120008002 Haut Nkam 120008003 Mifi, Hauts Plateaux, Koung Khi 120008004 Menoua 120008005 Ndé 120008006 Noun 120008099 Ouest province, unknown department 120010001 Fako 120010002 Koupe et Manengouba, Meme 120010003 Manyu, Lebialem 120010004 Ndian 120010099 Sud Ouest, unknown department 120097097 Abroad 120098098 Unknown 120099099 NIU (not in universe) Migration: A-E 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 Person number (within household) Cameroon 1976: 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 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 Technical Person Variables -- PERSON Resident type Cameroon 1976: All persons This variable indicates the resident type. 1 Resident 2 Visitor 3 Birth, mother absent 8 Unknown Migration: Global Variables -- PERSON Relationship to household head <svar v="CM76A402" a="all"><span class="em">3) Family relationship with the head of household</span><br />Mark one of the following relationships<br /><div class="i1">[] 1 HH (Head of household)<br />[] 2 EP (Spouse)<br />[] 3 Son, daughter<br />[] 4 Father, mother<br />[] 5 Other (for other relative)<br />[] 6 None (for no relationship)</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A402" a="all"><span class="em">Column 3: Family connection with the head of household.</span><br /><br />The head of household is recognized as such by the other members of the household; it's the person who has the responsibility of taking care of the economic needs of the household. <br /><br />The family connection between the members of the household should only be determined in relation to the head of household and you should only mark one of the following indications:<br /><div class="i1">-H.H (for head of household)<br /><br />-SP (for spouse)<br /><br />-Son or daughter<br /><br />-Mother or father<br /><br />-Other (for other relative: blood relative or by marriage)<br /><br />-Without (for no relation)</div><br /><br />Example: For a brother of the head of household, mark 'other'<br /></svar> Cameroon 1976: All persons This variable indicates the relationship to household head. 1 Head of the household 2 Spouse 3 Son/daughter 4 Father/mother 5 Other relative 6 Unrelated 8 Unknown Demographic Variables -- PERSON Sex <svar v="CM76A403" a="all"><span class="em">4) Sex</span><br />Mark <br /><div class="i1">[] 1 Male <br />[] 2 Female</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A403" a="all"><span class="em">Column 4: sex</span><br /><br />Mark:<br /><div class="i1">-M for people of the masculine sex<br /><br />-F for people of the feminine sex</div><br /><br /></svar> Cameroon 1976: All persons This variable indicates the sex. 1 Male 2 Female 8 Unknown Demographic Variables -- PERSON Resident status <svar v="CM76A404" a="all"><span class="em">5) Housing situation</span><br />Mark <br /><div class="i1">[] 1 P for the present residents or <br />[] 2 A for the absent residents</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A404" a="all"><span class="em">Column 5: living situation:</span><br /><br />Mark, for the members of the household, if they are present or absent:<br /><div class="i1">-P for present residents<br /><br />-A for absent residents</div><br /></svar> Cameroon 1976: All persons This variable indicates the resident status. 1 Present resident 2 Absent resident 3 Visitor 8 Unknown Migration: Global Variables -- PERSON Length of absence or visit <svar v="CM76A405" a="all"><span class="em">6) Length of absence or visit</span><br />Mark the length of time passed since the departure of absent residence or the arrival of visitors. For present residents, mark a line.<br /><div class="i1">Months _ _</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A405" a="all"><span class="em">Column 6: Length of absence or visit</span><br /><br />Mark how long ago the absent residents left the household and the length of time since the visitors arrived. For the present residents, mark a line.<br /><br />This length of time should be marked in months passed.<br /><br />[Example omitted]<br /><br />N.B. Residents who have been absent for more than 6 months do not need to be surveyed with the household who declares them absent, they will be surveyed where they are staying.<br /><br />On the other hand, visitors present for more than 6 moths should be surveyed as residents.<br /></svar> Cameroon 1976: Absent residents or visitors [discrepancies: type I 0.1%; type II 0.9%] This variable indicates the length of absence or visit. 0 NIU (not in universe) 1 1 month or less 2 1-2 months 3 2-3 months 4 3-4 months 5 4-5 months 6 5-6 months 7 6 or more months 8 Unknown Migration: Global Variables -- PERSON Month of birth <svar v="CM76A406 CM76A407" a="all"><span class="em">Date of Birth</span><br />7) Mark the number of the month of birth (01 to 12). If the person doesn't know their birth month, mark a line.<br /><div class="i1">Month number _ _</div><br />8) Mark the year of birth. If the person doesn't know his month of birth, mark a line in column 8 and mark the estimated age in column 9. <br /><div class="i1">Year _ _ _ _</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A406 CM76A407" a="all"><span class="em">Column 7 and 8: Date of birth:</span><br /><br />Mark the month of birth in numbers in column 7 and the year of birth in numbers in the column 8.<br /><br />[Month numbers and examples omitted]<br /><br />If someone doesn't know their month of birth, mark a line in column 7 and mark their year of birth in column 8.<br /><br />If someone doesn't know either their month of birth or their year of birth, mark a line in column 7 and 8 and go on to column 9<br /></svar> Cameroon 1976: All persons This variable indicates the 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 99 Unknown Demographic Variables -- PERSON Year of birth <svar v="CM76A406 CM76A407" a="all"><span class="em">Date of Birth</span><br />7) Mark the number of the month of birth (01 to 12). If the person doesn't know their birth month, mark a line.<br /><div class="i1">Month number _ _</div><br />8) Mark the year of birth. If the person doesn't know his month of birth, mark a line in column 8 and mark the estimated age in column 9. <br /><div class="i1">Year _ _ _ _</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A406 CM76A407" a="all"><span class="em">Column 7 and 8: Date of birth:</span><br /><br />Mark the month of birth in numbers in column 7 and the year of birth in numbers in the column 8.<br /><br />[Month numbers and examples omitted]<br /><br />If someone doesn't know their month of birth, mark a line in column 7 and mark their year of birth in column 8.<br /><br />If someone doesn't know either their month of birth or their year of birth, mark a line in column 7 and 8 and go on to column 9<br /></svar> Cameroon 1976: All persons This variable indicates the year of birth. 1878 1878 or earlier 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 9999 Unknown Demographic Variables -- PERSON Age <svar v="CM76A408" a="all"><span class="em">9) Age </span><br />Mark the age in years passed for all these people. _ _<br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A408" a="all"><span class="em">Column 9: age: </span><br /><br />Mark the age in years passed (age at last birthday)<br /><br />[Example omitted]<br /><br />If someone doesn't know his or her age, do you best to estimate their age based on the other people whose ages you know, the age of his or her children, or other information that they can give you.<br /><br />You can also use historic events. <br />[Example omitted]<br /></svar> Cameroon 1976: All persons This variable indicates the age. 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 56 057 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 and above 999 Unknown Demographic Variables -- PERSON Country or arrondisement of birth <svar v="CM76A409" a="all"><span class="em">Place of birth</span><br />Where were you born? <br />For a person born in Cameroon, mark the location (city or village) of birth in column 10 and the district where the location is in column 11.<br /><br />For a person born outside of Cameroon, mark a line in column 10 and mark the birth country in column 11.<br /><br /><div class="i1">10) Location<br />11) District or country</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A409" a="all"><span class="em">Column 10 and 11: place of birth:</span><br /><br />For those born in Cameroon, mark the name of the town in which the person was born in column 10 and the name of the district of the town in column 11.<br /><br />For those born abroad, mark a line in column 10 and mark the name of the country of birth in column 11. <br /></svar> Cameroon 1976: All persons This variable indicates the place of birth. 00002 Congo 00003 Gabon 00004 RCA 00005 Chad 00006 Zaire 00011 Nigeria 00012 Niger 00013 Dahomey 00014 Togo 00015 Senegal 00016 Mali 00018 Ghana 00019 Cote D'Ivoire 00020 Guinea 00029 West Africa - Other countries 00049 Africa - Other countries 00050 France 00051 Great Britain 00052 Germany (West) 00053 Italy 00054 Belgium 00055 Netherlands 00057 Greece 00059 Europe - Other countries 00061 United States 00069 Other Americas 00080 China 00089 Asia - Other countries 10101 Sangmelina 10102 Djoum 10103 Bengbis 10104 Zoetele 10201 Naga-Eboko 10202 Minta 10203 Mbandjock 10301 Monatele 10302 Obala 10303 Okola 10304 Saa 10305 Evodoula 10401 Bafia 10402 Bokito 10403 Ndikiniminki 10404 Ntui 10405 Yoko 10406 Ombessa 10501 Mfou 10502 Akono 10503 Esse 10504 Awae 10505 Ngoumou 10506 Bikok 10507 Mbankomo 10601 Yaounde I 10602 Yaounde II 10603 Yaounde III 10604 Yaounde IV 10701 Ebolowa 10702 Ambam 10703 Ngoulemakong 10801 Eseka 10802 Ngog-Mapubi 10803 Messondo 10804 Bot-Makak 10805 Maka 10901 Akonolinga 10902 Ayos 11001 Mbalmayo 11002 Ngomedzap 11102 Lolodorf 11103 Campo 11104 Akom II 20101 Yokadouma 20102 Moloudou 20201 Abong-Mbang 20202 Doume 20203 Lomie 20204 Massamena 20205 Nguelemedouka 20301 Batouri 20302 Ndelele 20401 Bertoua 20402 Betare-Oya 30101 Nkongsamba 30102 Mbanga 30103 Dibombari 30104 Melong 30105 Manjo 30106 Loum 30201 Yabassi 30202 Yingui 30203 Nkondjock 30301 Edea 30302 Ngambe or Bambini 30303 Ndom 30304 Dizangue 30305 Pouma 30401 Douala I 30402 Douala II 30403 Douala III 30404 Douala IV 40101 Ngaoundere 40102 Banyo 40103 Meiganga 40104 Tibati 40105 Tignere 40201 Maroua 40202 Guider 40203 Poli 40204 Tchollire or Rey-Bouba 40301 Maroua 40302 Kaele 40303 Meri 40304 Bogo 40305 Mindif 40401 Kousseri 40402 Makari or Serbewel 40501 Mokolo 40502 Mora 40601 Yagoua 40602 Kar-Hay 50101 Kumbo 50102 Jakiri 50201 Nkambe 50301 Wum 50401 Bamenda 50402 Ndop 50501 Mbengwi 50502 Batibo 60101 Mbouda 60102 Batcham 60103 Galim 60201 Foumban 60202 Foumbot 60301 Bafang 60302 Bana 60303 Company 60304 Kekem 60401 Dschang 60402 Penka-Michel or Bansoa 60501 Bafoussam 60502 Bandjoun 60503 Bamendjou 60504 Bangou 60601 Bangangte 60602 Bazou 60603 Tonga 70101 Victoria 70102 Muyuka 70103 Tiko 70201 Mamfe 70202 Akwaya 70203 Fontem 70301 Kumba 70302 Bangem 70303 Nguti 70304 Tombel 70401 Mundemba 70402 Ekondo-Titi 70403 Bamusso 70404 Isanguele 99998 Cameroon - Unknown arrondisement 99999 Unknown Nativity and Birthplace Variables -- PERSON Country or arrondisement of usual residence <svar v="CM76A410" a="all"><span class="em">Usual residence</span><br /><span class="em">12) Location</span><br />Ask only the visitors: Where do you usually live?<br /><br />Mark the name of the district if it's in Cameroon or the name of the country if it's outside of Cameroon.<br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A410" a="all"><span class="em">Column 12: Usual residence (location):</span><br /><br />The usual location of residence is the district in which the person normally lives, meaning at least for 6 months, or else the district where the individual decides to stay if she has lived there for less than 6 months.<br /><br />The usual location of residence is already marked on the first page of the questionnaire, so the column 12 is only for visitors for whom you mark the name of the district, if their usual location of residence is in Cameroon or the name of the country if the usual location of residence is outside of Cameroon. <br /></svar> Cameroon 1976: Visitors [discrepancies: type I trace; type II 0.1%] This variable indicates the usual residence. 00003 Gabon 00004 RCA 00005 Chad 00011 Nigeria 00029 Africa - Other countries 00050 France 00089 Other foreign countries 10101 Sangmelina 10102 Djoum 10103 Bengbis 10104 Zoetele 10201 Naga-Eboko 10202 Minta 10203 Mbandjock 10301 Monatele 10302 Obala 10303 Okola 10304 Saa 10305 Evodoula 10401 Bafia 10402 Bokito 10403 Ndikiniminki 10404 Ntui 10405 Yoko 10406 Ombessa 10501 Mfou 10502 Akono 10503 Esse 10504 Awae 10505 Ngoumou 10506 Bikok 10507 Mbankomo 10601 Yaounde I 10602 Yaounde II 10603 Yaounde III 10604 Yaounde IV 10701 Ebolowa 10702 Ambam 10703 Ngoulemakong 10801 Eseka 10802 Ngog-Mapubi 10803 Messondo 10804 Bot-Makak 10805 Maka 10901 Akonolinga 10902 Ayos 11001 Mbalmayo 11002 Ngomedzap 11102 Lolodorf 11103 Campo and Akom II 20101 Yokadouma 20102 Moloudou 20201 Abong-Mbang 20202 Doume 20203 Lomie 20204 Massamena 20205 Nguelemedouka 20301 Batouri 20302 Ndelele 20401 Bertoua 20402 Betare-Oya 30101 Nkongsamba 30102 Mbanga 30103 Dibombari 30104 Melong 30105 Manjo 30106 Loum 30201 Yabassi 30202 Yingui 30203 Nkondjock 30301 Edea 30302 Ngambe or Bambini 30303 Ndom 30304 Dizangue 30305 Pouma 30401 Douala I 30402 Douala II 30403 Douala III 30404 Douala IV 40101 Ngaoundere 40102 Banyo 40103 Meiganga 40104 Tibati 40105 Tignere 40201 Maroua 40202 Guider 40203 Poli 40204 Tchollire or Rey-Bouba 40301 Maroua 40302 Kaele 40303 Meri 40304 Bogo 40305 Mindif 40401 Kousseri 40402 Makari or Serbewel 40501 Mokolo 40502 Mora 40601 Yagoua 40602 Kar-Hay 50101 Kumbo 50102 Jakiri 50201 Nkambe 50301 Wum 50401 Bamenda 50402 Ndop 50501 Mbengwi 50502 Batibo 60101 Mbouda 60102 Batcham 60103 Galim 60201 Foumban 60202 Foumbot 60301 Bafang 60302 Bana 60303 Company 60304 Kekem 60401 Dschang 60402 Penka-Michel or Bansoa 60501 Bafoussam 60502 Bandjoun 60503 Bamendjou 60504 Bangou 60601 Bangangte 60602 Bazou 60603 Tonga 70101 Victoria 70102 Muyuka 70103 Tiko 70201 Mamfe 70202 Akwaya 70203 Fontem 70301 Kumba 70302 Bangem 70303 Nguti 70304 Tombel 70401 Mundemba 70402 Ekondo-Titi 70403 Bamusso and Isanguele 99997 Cameroon - Unknown arrondisement 99998 Unknown 99999 NIU (not in universe) Migration: Global Variables -- PERSON Length of residence <svar v="CM76A411" a="all"><span class="em">13) Length of residence</span><br />Have you ever lived in another district for more than 6 months?<br /><br />Mark yes or no in column 13.<br /><br /><div class="i1">If yes, for how much time have you lived in the current district? Mark the number of years in 14a or the number of months in 14b for those who have lived there for less than a year. <br />If no, mark a line in 14a, 14b, and 15.</div><br /><div class="i2">14a) Years<br />14b) Months</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A411" a="all"><span class="em">Column 13, 14a, 14b: Usual residence (length of time):</span><br /><br />Column 13-ask if the person has already lived for more than 6 months in another district than the district that is his or her usual residence, meaning if she already lived in another district. Mark YES or NO.<br /><div class="i1">-If YES, ask how long the person lived in the district where she currently lives (since the last change of residence). If it's for more than a year mark the number of years passed in 14a and mark a line in 14b. If it's less than a year, mark a line in 14a and mark the number of months passed in 14b. <br /><br />-If NO, mark a line in the columns 14a and 14b and 15. In fact, if the individual has always lived in the same district, she didn't formerly live anywhere else.</div><br /><br /></svar> Cameroon 1976: Persons who have changed residence [Universe unverifiable] This variable indicates the length of residence. 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 56 057 57 058 58 059 59 060 60+ 998 Unknown 999 NIU (not in universe) Migration: Global Variables -- PERSON Country or arrondisement of previous residence <svar v="CM76A412" a="all"><span class="em">15) Previous Residence</span><br />Where did you live before you moved to this district?<br />Mark the name of the district if it is in Cameroon, or the name of the country if it's outside of Cameroon.<br /><br /><div class="i1">Residents (Mark all the people who usually live in the household, whether they are present or absent. <br /><br />Visitors (mark all the people who do not usually live in the household, but who spent the night before the interview in the household.</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A412" a="all"><span class="em">Column 15: Former residence:</span><br /><br />For those who already lived in another district (for the others, you have marked a line).<br /><br />The location of former residence is the district where the person lived for more than 6 months immediately before having moved to the district where she is now usually living. Mark the name of the district if the former residence is in Cameroon or country if it is outside of Cameroon. <br /><br /></svar> Cameroon 1976: Persons who have changed residence [discrepancies: type I 0.1%; type II 1.7%]] This variable indicates the previous residence. 00002 Congo 00003 Gabon 00004 RCA 00005 Chad 00006 Zaire 00029 [no label] 00011 Nigeria 00012 Niger 00013 Dahomey 00014 Togo 00015 Senegal 00019 Ivory Coast 00020 Guinea 00031 Moroco 00032 Algeria 00033 Tunisie 00034 Lybia 00035 Egypt 00036 Sudan 00049 North Africa - Other countries 00050 France 00051 Great Britain 00052 Germany (West) 00053 Italy 00059 Belgium 00061 United States 00069 Americas - Other countries 00089 Asia - Other countries 10101 Sangmelina 10102 Djoum 10103 Bengbis 10104 Zoetele 10201 Naga-Eboko 10202 Minta 10203 Mbandjock 10301 Monatele 10302 Obala 10303 Okola 10304 Saa 10305 Evodoula 10401 Bafia 10402 Bokito 10403 Ndikiniminki 10404 Ntui 10405 Yoko 10406 Ombessa 10501 Mfou 10502 Akono 10503 Esse 10504 Awae 10505 Ngoumou 10506 Bikok 10507 Mbankomo 10601 Yaounde I 10602 Yaounde II 10603 Yaounde III 10604 Yaounde IV 10701 Ebolowa 10702 Ambam 10703 Ngoulemakong 10801 Eseka 10802 Ngog-Mapubi 10803 Messondo 10804 Bot-Makak 10805 Maka 10901 Akonolinga 10902 Ayos 11001 Mbalmayo 11002 Ngomedzap 11102 Lolodorf 11103 Campo 11104 Akom II 20101 Yokadouma 20102 Moloudou 20201 Abong-Mbang 20202 Doume 20203 Lomie 20204 Massamena 20205 Nguelemedouka 20301 Batouri 20302 Ndelele 20401 Bertoua 20402 Betare-Oya 30101 Nkongsamba 30102 Mbanga 30103 Dibombari 30104 Melong 30105 Manjo 30106 Loum 30201 Yabassi 30202 Yingui 30203 Nkondjock 30301 Edea 30302 Ngambe or Bambini 30303 Ndom 30304 Dizangue 30305 Pouma 30401 Douala I 30402 Douala II 30403 Douala III 30404 Douala IV 40101 Ngaoundere 40102 Banyo 40103 Meiganga 40104 Tibati 40105 Tignere 40201 Maroua 40202 Guider 40203 Poli 40204 Tchollire or Rey-Bouba 40301 Maroua 40302 Kaele 40303 Meri 40304 Bogo 40305 Mindif 40401 Kousseri 40402 Makari or Serbewel 40501 Mokolo 40502 Mora 40601 Yagoua 40602 Kar-Hay 50101 Kumbo 50102 Jakiri 50201 Nkambe 50301 Wum 50401 Bamenda 50402 Ndop 50501 Mbengwi 50502 Batibo 60101 Mbouda 60102 Batcham 60103 Galim 60201 Foumban 60202 Foumbot 60301 Bafang 60302 Bana 60303 Company 60304 Kekem 60401 Dschang 60402 Penka-Michel or Bansoa 60501 Bafoussam 60502 Bandjoun 60503 Bamendjou 60504 Bangou 60601 Bangangte 60602 Bazou 60603 Tonga 70101 Victoria 70102 Muyuka 70103 Tiko 70201 Mamfe 70202 Akwaya 70203 Fontem 70301 Kumba 70302 Bangem 70303 Nguti 70304 Tombel 70401 Mundemba 70402 Ekondo-Titi 70403 Bamusso 70404 Isanguele 99997 Cameroon - Unknown arrondissement 99998 Unknown 99999 NIU (not in universe) Migration: Global Variables -- PERSON Country or department of previous residence <svar v="CM76A412" a="all"><span class="em">15) Previous Residence</span><br />Where did you live before you moved to this district?<br />Mark the name of the district if it is in Cameroon, or the name of the country if it's outside of Cameroon.<br /><br /><div class="i1">Residents (Mark all the people who usually live in the household, whether they are present or absent. <br /><br />Visitors (mark all the people who do not usually live in the household, but who spent the night before the interview in the household.</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A412" a="all"><span class="em">Column 15: Former residence:</span><br /><br />For those who already lived in another district (for the others, you have marked a line).<br /><br />The location of former residence is the district where the person lived for more than 6 months immediately before having moved to the district where she is now usually living. Mark the name of the district if the former residence is in Cameroon or country if it is outside of Cameroon. <br /><br /></svar> Cameroon 1976: Persons who have changed residence [discrepancies: type I 0.1%; type II 1.7%]] This variable indicates the country or department of previous residence. 00002 Congo 00003 Gabon 00004 RCA 00005 Chad 00006 Zaire 00011 Nigeria 00012 Niger 00013 Dahomey 00014 Togo 00015 Senegal 00019 Ivory Coast 00020 Guinea 00029 [no label] 00031 Moroco 00032 Algeria 00033 Tunisie 00034 Lybia 00035 Egypt 00036 Sudan 00049 North Africa - Other countries 00050 France 00051 Great Britain 00052 Germany (West) 00053 Italy 00059 Belgium 00061 United States 00069 Americas - Other countries 00089 Asia - Other countries 00101 Dja and Lobo 00102 Haute-Sanaga 00103 Monatele 00104 Mbam 00105 Mefou 00106 Mfoundi 00107 Ntem 00108 Nyong and Kelle 00109 Nyong and Mfoumou 00110 Nyong and So 00111 Ocean 00199 Centre-Sud, department unknown 00201 Boumba and Ngoko 00202 Haut-Nyong 00203 Kadey 00204 Lom and Djerem 00299 Est, department unknown 00301 Moungo 00302 Nkam 00303 Sanaga-Maritme 00304 Wouri 00399 Littoral, department unknown 00401 Adamaoua 00402 Benoue 00403 Diamare 00404 Logone and Chari 00405 Margui-Wandala 00406 Mayo Danay 00499 Nord, department unknown 00501 Bui 00502 Donga-Mantung 00503 Menchum 00504 Mezam 00505 Momo 00599 Nord-Ouest, department unknown 00601 Bamboutos 00602 Bamoun 00603 Haut-Kam 00604 Menoua 00605 Mifi 00606 Nde 00699 Ouest, department unknown 00701 Fako 00702 Manyu 00703 Meme 00704 Ndian 00799 Sud-Ouest, department unknown 99998 Cameroon, unknown arrondissement 99999 NIU (not in universe) Migration: Global Variables -- PERSON Nationality <svar v="CM76A413" a="all"><span class="em">16) Nationality</span><br />What is your nationality?<br />Mark the nationality declared by the person: ____<br /><div class="i1">'C' for the Cameroonian nationality and the nationality in plain language for the others.</div><br /></svar> <svar v="CM76A400 CM76A401 CM76A402 CM76A403 CM76A404 CM76A405 CM76A406 CM76A407 CM76A408 CM76A409 CM76A410 CM76A411 CM76A412 CM76A413"><span class="h3">a) Columns 1 to 16:</span><br /><br />Fill out for each person.<br /><br />First take inventory of all the people to mark by filling out columns 1 to 6 for each person. Next ask the other individual questions (columns 7 to 25), filling out line by line. <br /></svar></p> <p><svar v="CM76A413" a="all"><span class="em">Column 16: Nationality:</span><br /><br />Nationality designates the legal nationality of an individual. All people in possession of the legal nationality of Cameroon are considered as "Cameroonian."<br /><br />In all cases, mark the declared nationality of each person.<br /><br />Mark "C" for the Cameroonians and the full name of the nationality of the non-Cameroonians. <br /><br />[Examples omitted]<br /></svar> Cameroon 1976: All persons This variable indicates the nationality. 001 Cameroon 002 Congo 003 Gabon 004 RCA 005 Chad 011 Nigeria 012 Niger 013 Dahomey 014 Togo 015 Senegal 016 Mali 018 Ghana 029 West Africa - Other countries 049 Africa - Other countries 050 France 051 Great Britain 052 Germany (West) 053 Italy 055 Netherlands 057 Greece 059 Europe - Other countries 061 United States 069 Americas - Other countries 071 Lebanon 080 China 089 Asia - Other countries 099 Oceania - Other countries 999 Unknown Nativity and Birthplace Variables -- PERSON Type of instruction <svar v="CM76A414 CM76A415 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">Population 4 years old or older</span><br /></svar></p> <p><svar v="CM76A414 CM76A415 CM76A427"><span class="em">Education</span><br />Have you ever been to school?<br /><div class="i1">If no, mark "No" in column 17 and draw a line in column 18. <br />If yes, mark in column 17 the abbreviation corresponding to the type of education based on the instructions on the bottom of the page. In column 18, mark the last grade they attended in this type of education.</div><br /></svar></p> <p><svar v="CM76A414 CM76A427" a=" CM76A414"><span class="em">17) Type</span><br /><div class="i1">[] 1 NO-Never went to school<br />[] 2 MAT-Kindergarten or nursery school<br />[] 3 COR-Islamic religious school <br />[] 4 PF-Elementary school (Francophone system)<br />[] 5 PE-Elementary school (Anglophone system)<br />[] 6 POST- Post Elementary school (SAR, SM, etc.)<br />[] 7 EPS-Higher elementary school<br />[] 8 GEF- General high school (Francophone system)<br />[] 9 GEE-General high school (Anglophone system)<br />[] 10 TEF-Technical high school (Francophone system)<br />[] 11 TEE- Technical high school (Anglophone system)<br />[] 12 EN-Elite schools<br />[] 13 ESS Higher specialized education<br />[] 14 UNIV-University</div><br /></svar> <svar v="CM76A414 CM76A415 CM76A427 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">b) Column 17 to 25:</span><br /><br />To be filled out individually for the people ages 4 and over (mark a line in column 17 to 25 for children under 4. <br /></svar></p> <p><svar v="CM76A414 CM76A427" a="all"><span class="em">Column 17: Education (type)</span><br />Mark one of the following abbreviations, corresponding to the last type of education received:<br /><div class="i1">NO: for a person who never when to school;<br /><br />MAT: for a person who when to kindergarten or nursery school<br /><br />COR: for a person who only when to a Muslim religious school<br /><br />PF: for a person who went to elementary school (Francophone system)<br /><br />PF: for a person who when to elementary school (Anglophone system)<br /><br />POST: Fro a person who when to middle school (SAR, SM, etc)<br /><br />EPS: For a person who went to a higher elementary school (slightly more education than regular elementary school, for people not going to a University)<br /><br />GEF: for a person who went to high school (Francophone system)<br /><br />GEE: for a person who went to high school (Anglophone system)<br /><br />TEF: for a person who went to a technical high school (Francophone system)<br /><br />TEE: for a person who went to a technical high school (Anglophone system)<br /><br />EN: for a person who went to a teacher training college<br /><br />ESS: for a person who took specialized university classes (elite university, specialized higher learning institution connected or not to a university)<br /><br />UNIV: for a person who went to the University</div><br /><br />For all education systems other than Francophone and Anglophone, mark <span class="em">PR</span> for elementary school education, <span class="em">GE</span> for high school education, and <span class="em">TF</span> for technical high school education.<br /></svar> Cameroon 1976: Persons age 4+ [discrepancies: type I 0.1%; type II 0.8%] This variable indicates the type of instruction. 01 No schooling 02 Kindergarten 03 Koranic school 04 Primary school, French-speaking 05 Primary school, English-speaking 06 Post primary 07 Old teacher's school 08 General high school, French-speaking 09 General high school, English-speaking 10 Technical high school, French-speaking 11 Technical high school, English-speaking 12 Teacher's school 13 Higher specialized education 14 University 98 Unknown 99 NIU (not in universe) Education Variables -- PERSON Class <svar v="CM76A414 CM76A415 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">Population 4 years old or older</span><br /></svar></p> <p><svar v="CM76A414 CM76A415 CM76A427"><span class="em">Education</span><br />Have you ever been to school?<br /><div class="i1">If no, mark "No" in column 17 and draw a line in column 18. <br />If yes, mark in column 17 the abbreviation corresponding to the type of education based on the instructions on the bottom of the page. In column 18, mark the last grade they attended in this type of education.</div><br /></svar></p> <p><svar v="CM76A415 CM76A427" a="all"><span class="em">18) Grade</span><br /></svar> <svar v="CM76A414 CM76A415 CM76A427 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">b) Column 17 to 25:</span><br /><br />To be filled out individually for the people ages 4 and over (mark a line in column 17 to 25 for children under 4. <br /></svar></p> <p><svar v="CM76A414 CM76A427" a="all"><span class="em">Column 17: Education (type)</span><br />Mark one of the following abbreviations, corresponding to the last type of education received:<br /><div class="i1">NO: for a person who never when to school;<br /><br />MAT: for a person who when to kindergarten or nursery school<br /><br />COR: for a person who only when to a Muslim religious school<br /><br />PF: for a person who went to elementary school (Francophone system)<br /><br />PF: for a person who when to elementary school (Anglophone system)<br /><br />POST: Fro a person who when to middle school (SAR, SM, etc)<br /><br />EPS: For a person who went to a higher elementary school (slightly more education than regular elementary school, for people not going to a University)<br /><br />GEF: for a person who went to high school (Francophone system)<br /><br />GEE: for a person who went to high school (Anglophone system)<br /><br />TEF: for a person who went to a technical high school (Francophone system)<br /><br />TEE: for a person who went to a technical high school (Anglophone system)<br /><br />EN: for a person who went to a teacher training college<br /><br />ESS: for a person who took specialized university classes (elite university, specialized higher learning institution connected or not to a university)<br /><br />UNIV: for a person who went to the University</div><br /><br />For all education systems other than Francophone and Anglophone, mark <span class="em">PR</span> for elementary school education, <span class="em">GE</span> for high school education, and <span class="em">TF</span> for technical high school education.<br /></svar></p> <p><svar v="CM76A415 CM76A427" a=" CM76A415"><span class="em">Column 18: Education (class)</span><br /><br /><span class="em">N.B. Only worry about the individuals who went to school; for the others (NO in column 17) mark a line. Mark the last grade level in the type of institution indicated in column 17 according to the following instructions: </span><br /><br />Simple cases:<br /><br />Mark the number of the last year spent in the institution. [Example omitted]<br /><br />N.B. This applies to nursery school (MAT), to Anglophone elementary school (PE), to a private elementary school (EPS) and to a teacher training college (EN) and to systems other than Francophone or Anglophone.<br /><br />Special cases:<br /><div class="i1">Muslim religious school (COR): Mark the number of book studied<br /><br />Example: 3 for three books studied.<br /><br />Elementary school: mark the response given by the person:</div><br />[Levels omitted]<br /><div class="i1">High school, Francophone system (GEF): Mark the response given by the person (6th, 5th, 4th, 3rd, 2nd, 1st, T (for final year)<br /><br />Technical high school Francophone system (TEF): <br /><br />Mark the response given by the person: 1st for first year, 2nd for second year, etc?<br /><br />All the while, in the case of the technical high schools (2nd cycle of high school), mark:<br /><br />5th for the third to last year (it's the 5th year of high school);<br /><br />6th for the penultimate year (it's the 6th year of high school)<br /><br />7th for final year (it's the 7th year of high school)<br /><br />High school, Anglophone system (GEE and TEE): mark the last year spent in high school as it is provided by the person you are interviewing. <br /><br />1st for class one, that's the first year spent in high school or at the "Cameroon College of Arts, Science and Technology":<br /><br />7th for class seven, that's the 7th year spend at the same schools.<br /><br />Higher education (ESS and UNIV): mark the number of years of study spent after high school graduation or the general certificate of education, advanced level:<br /><br />1 for one year of study after high school graduation<br /><br />4 for four years of study after high school graduation (don't count years taken twice)</div><br /></svar> Cameroon 1976: Persons age 4+ who have attended school [discrepancies: type I 0.1%; type II 1.4%] This variable indicates the class. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 98 Unknown 99 NIU (not in universe) Education Variables -- PERSON Educational attainment <svar v="CM76A414 CM76A415 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">Population 4 years old or older</span><br /></svar></p> <p><svar v="CM76A414 CM76A415 CM76A427"><span class="em">Education</span><br />Have you ever been to school?<br /><div class="i1">If no, mark "No" in column 17 and draw a line in column 18. <br />If yes, mark in column 17 the abbreviation corresponding to the type of education based on the instructions on the bottom of the page. In column 18, mark the last grade they attended in this type of education.</div><br /></svar></p> <p><svar v="CM76A415 CM76A427" a="all"><span class="em">18) Grade</span><br /></svar> <svar v="CM76A414 CM76A415 CM76A427 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">b) Column 17 to 25:</span><br /><br />To be filled out individually for the people ages 4 and over (mark a line in column 17 to 25 for children under 4. <br /></svar></p> <p><svar v="CM76A414 CM76A427" a="all"><span class="em">Column 17: Education (type)</span><br />Mark one of the following abbreviations, corresponding to the last type of education received:<br /><div class="i1">NO: for a person who never when to school;<br /><br />MAT: for a person who when to kindergarten or nursery school<br /><br />COR: for a person who only when to a Muslim religious school<br /><br />PF: for a person who went to elementary school (Francophone system)<br /><br />PF: for a person who when to elementary school (Anglophone system)<br /><br />POST: Fro a person who when to middle school (SAR, SM, etc)<br /><br />EPS: For a person who went to a higher elementary school (slightly more education than regular elementary school, for people not going to a University)<br /><br />GEF: for a person who went to high school (Francophone system)<br /><br />GEE: for a person who went to high school (Anglophone system)<br /><br />TEF: for a person who went to a technical high school (Francophone system)<br /><br />TEE: for a person who went to a technical high school (Anglophone system)<br /><br />EN: for a person who went to a teacher training college<br /><br />ESS: for a person who took specialized university classes (elite university, specialized higher learning institution connected or not to a university)<br /><br />UNIV: for a person who went to the University</div><br /><br />For all education systems other than Francophone and Anglophone, mark <span class="em">PR</span> for elementary school education, <span class="em">GE</span> for high school education, and <span class="em">TF</span> for technical high school education.<br /></svar></p> <p><svar v="CM76A415 CM76A427" a=" CM76A415"><span class="em">Column 18: Education (class)</span><br /><br /><span class="em">N.B. Only worry about the individuals who went to school; for the others (NO in column 17) mark a line. Mark the last grade level in the type of institution indicated in column 17 according to the following instructions: </span><br /><br />Simple cases:<br /><br />Mark the number of the last year spent in the institution. [Example omitted]<br /><br />N.B. This applies to nursery school (MAT), to Anglophone elementary school (PE), to a private elementary school (EPS) and to a teacher training college (EN) and to systems other than Francophone or Anglophone.<br /><br />Special cases:<br /><div class="i1">Muslim religious school (COR): Mark the number of book studied<br /><br />Example: 3 for three books studied.<br /><br />Elementary school: mark the response given by the person:</div><br />[Levels omitted]<br /><div class="i1">High school, Francophone system (GEF): Mark the response given by the person (6th, 5th, 4th, 3rd, 2nd, 1st, T (for final year)<br /><br />Technical high school Francophone system (TEF): <br /><br />Mark the response given by the person: 1st for first year, 2nd for second year, etc?<br /><br />All the while, in the case of the technical high schools (2nd cycle of high school), mark:<br /><br />5th for the third to last year (it's the 5th year of high school);<br /><br />6th for the penultimate year (it's the 6th year of high school)<br /><br />7th for final year (it's the 7th year of high school)<br /><br />High school, Anglophone system (GEE and TEE): mark the last year spent in high school as it is provided by the person you are interviewing. <br /><br />1st for class one, that's the first year spent in high school or at the "Cameroon College of Arts, Science and Technology":<br /><br />7th for class seven, that's the 7th year spend at the same schools.<br /><br />Higher education (ESS and UNIV): mark the number of years of study spent after high school graduation or the general certificate of education, advanced level:<br /><br />1 for one year of study after high school graduation<br /><br />4 for four years of study after high school graduation (don't count years taken twice)</div><br /></svar> Cameroon 1976: Persons age 4+ [discrepancies: type I 0.1%; type II 0.8%] This variable indicates the educational attainment. 000 No schooling 010 Kindergarten 020 Koranic school, grade unknown 021 Koranic school, grade 1 022 Koranic school, grade 2 023 Koranic school, grade 3 024 Koranic school, grade 4 025 Koranic school, grade 5 026 Koranic school, grade 6 027 Koranic school, grade 7 030 Primary school, French-speaking, grade unknown 031 Primary school, French-speaking, grade 1 032 Primary school, French-speaking, grade 2 033 Primary school, French-speaking, grade 3 034 Primary school, French-speaking, grade 4 035 Primary school, French-speaking, grade 5 036 Primary school, French-speaking, grade 6 040 Primary school, English-speaking, grade unknown 041 Primary school, English-speaking, grade 1 042 Primary school, English-speaking, grade 2 043 Primary school, English-speaking, grade 3 044 Primary school, English-speaking, grade 4 045 Primary school, English-speaking, grade 5 046 Primary school, English-speaking, grade 6 047 Primary school, English-speaking, grade 7 050 Post primary, grade unknown 051 Post primary, grade 1 052 Post primary, grade 2 053 Post primary, grade 3 060 Old teacher's school, grade unknown 061 Old teacher's school, grade 1 062 Old teacher's school, grade 2 063 Old teacher's school, grade 3 064 Old teacher's school, grade 4 070 General high school, French-speaking, grade unknown 071 General high school, French-speaking, grade 1 072 General high school, French-speaking, grade 2 073 General high school, French-speaking, grade 3 074 General high school, French-speaking, grade 4 075 General high school, French-speaking, grade 5 076 General high school, French-speaking, grade 6 077 General high school, French-speaking, grade 7 080 General high school, English-speaking, grade unknown 081 General high school, English-speaking, grade 1 082 General high school, English-speaking, grade 2 083 General high school, English-speaking, grade 3 084 General high school, English-speaking, grade 4 085 General high school, English-speaking, grade 5 086 General high school, English-speaking, grade 6 087 General high school, English-speaking, grade 7 090 Technical high school, French-speaking, grade unknown 091 Technical high school, French-speaking, grade 1 092 Technical high school, French-speaking, grade 2 093 Technical high school, French-speaking, grade 3 094 Technical high school, French-speaking, grade 4 095 Technical high school, French-speaking, grade 5 096 Technical high school, French-speaking, grade 6 097 Technical high school, French-speaking, grade 7 100 Technical high school, English-speaking, grade unknown 101 Technical high school, English-speaking, grade 1 102 Technical high school, English-speaking, grade 2 103 Technical high school, English-speaking, grade 3 104 Technical high school, English-speaking, grade 4 105 Technical high school, English-speaking, grade 5 110 Teacher's school, grade unknown 111 Teacher's school, grade 1 112 Teacher's school, grade 2 113 Teacher's school, grade 3 114 Teacher's school, grade 4 115 Teacher's school, grade 5 120 Higher specialized education, grade unkown 121 Higher specialized education, grade 1 122 Higher specialized education, grade 2 123 Higher specialized education, grade 3 124 Higher specialized education, grade 4 125 Higher specialized education, grade 5 126 Higher specialized education, grade 6 127 Higher specialized education, grade 7 130 University, grade unknown 131 University, grade 1 132 University, grade 2 133 University, grade 3 134 University, grade 4 135 University, grade 5 136 University, grade 6 137 University, grade 7 998 Unknown 999 NIU (not in universe) Education Variables -- PERSON School attendance <svar v="CM76A414 CM76A415 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">Population 4 years old or older</span><br /></svar></p> <p><svar v="CM76A417" a="all"><span class="em">20) Attendance</span><br />Do you currently attend a learning establishment, whether full time or part time?<br />Mark 'yes' or 'no'<br /></svar> <svar v="CM76A414 CM76A415 CM76A427 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">b) Column 17 to 25:</span><br /><br />To be filled out individually for the people ages 4 and over (mark a line in column 17 to 25 for children under 4. <br /></svar></p> <p><svar v="CM76A417" a="all"><span class="em">Column 20: School Attendance:</span><br /><br />Ask if the person currently goes to the learning establishment, whether it is full time or part time, whether the person works or not.<br /><br />Mark 'YES' or 'NO'<br /><br />A learning establishment is an establishment whose function is to dispense learning. This means that it must exclude all courses or formations, professional or not, that provide job training. Conversely, it is necessary to count establishments that do learning by correspondence. <br /></svar> Cameroon 1976: Persons age 4+ [discrepancies: type I 0.1%, type II 3.6%] This variable indicates the school attendance. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Education Variables -- PERSON Activity situation <svar v="CM76A414 CM76A415 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">Population 4 years old or older</span><br /></svar></p> <p><svar v="CM76A418" a="all"><span class="em">21) Economic activity</span><br />Did you work during the period from _______ to _______? <br />Mark the abbreviation corresponding to the work based on the instructions at the bottom of the page.<br /><div class="i1">[] 1 WK= Has worked<br />[] 2 UN= Without a job but has already worked<br />[] 3 LK= Looking for a job for the first time<br />[] 4 HK= Housewife<br />[] 5 ST= Student<br />[] 6 REN= Person of independent means<br />[] 7 RET= Retiree, old person<br />[] 8 HAN= Handicapped<br />[] 9 OIS= Idle</div><br /></svar> <svar v="CM76A414 CM76A415 CM76A427 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">b) Column 17 to 25:</span><br /><br />To be filled out individually for the people ages 4 and over (mark a line in column 17 to 25 for children under 4. <br /></svar></p> <p><svar v="CM76A418" a="all"><span class="em">Column 21: Employment status (1)</span> <br /><br />The purpose of this question is to determine the economic activity of each person aged 4 and over during the week preceding the beginning of the surveying (week of April 2 to 8 1976).<br /><br />First mark the dates below on the instruction insert in column 19 under the following form: "period from April 2 to April 8." Then mark<br /><br /><div class="i1">WK: for all the individuals having worked at some point during the week of reference. This category is made up of family workers who work under the authority of the head of household, with or without remuneration (for example wives who farm while taking care of the household) and individuals who have a permanent job but haven't worked during the reference period because of illness, off agricultural season, vacation, etc?<br /><br />[Codes omitted]<br /><br />UN for individuals who were without employment during the week of reference who already had worked and who are looking for another job<br /><br />LK for individuals who have never worked and who are looking for their first job.<br /><br />HK for women who perform only the housework at their home without other economic activity. Consider rather as WK women who do another job, either with an employer, or at her home: for example a farmer, a tailor, a factory worker, a sales clerk, etc.<br /><br />ST for students who don't work. Consider rather as WK students who also work<br /><br />REN for persons of independent means: people living off regular revenue from capital or all other annuity (revenue not coming from work)<br /><br />RENT for retirees and old people who can no longer work.<br /><br />HAND for those with physical and mental handicaps who cannot work because of their handicap (class in another category those handicapped individuals likely to work)<br /><br />OIS for person who cannot be classed in the above categories (idle). In these situations, provide explains in "observations" if needed.</div><br /></svar> Cameroon 1976: Persons age 4+ [discrepancies: type I trace, type II 5%] This variable indicates the activity situation. 01 Working 02 Unemployed, having worked in past 03 Looking for first job 04 Homemaker 05 Student 06 Pensioner 07 Retired 08 Disabled/handicapped 09 Inactive 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Occupation (1 digit) <svar v="CM76A414 CM76A415 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">Population 4 years old or older</span><br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421 CM76A422 CM76A423"><span class="h3">Ask only those who have worked during the reference period (WK) and those without work having already worked (UN). For the others, mark with the line. </span><br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421" a="all"><span class="em">22) Employment</span><br /><div class="i1">- For those who have worked during the reference period (WK): What job did you have during this period? ____<br />- For those without a job having already worked (UN): "What was your last job?" ____</div><br />Mark clearly the job occupied [Example omitted]<br /></svar> <svar v="CM76A414 CM76A415 CM76A427 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">b) Column 17 to 25:</span><br /><br />To be filled out individually for the people ages 4 and over (mark a line in column 17 to 25 for children under 4. <br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421 CM76A422 CM76A423">N.B. Columns on employment (columns 22 to 24)<br /><br />These columns are only to be filled out for people having worked during the reference week (WK in column 21) and for people without employment already having worked, in search of a new job (UN in column 21). For all others, mark a line from column 22 to column 24.<br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421" a="all"><span class="em">Column 22: Employment:</span><br /><br />For people having worked during the week of reference (WK), mark the job done during this period.<br /><br />For people without jobs, having already worked and looking for another job (UN), mark the last job done.<br /><br />The response to column 22 (what job do you do?) should specify the nature of the task accomplished by the person.<br /><br />Generally, the best description of the occupation of the person is the name of the task; for example, "auto mechanic". When the title of the occupation or the job is vague, do not hesitate to ask for more information to better mark his job: for example if the person tells you he or she is a doctor, ask him if he is a medical doctor, a veterinarian, or a dentist.<br /><br />If you do not know a job title that you are given by a person you are interviewing or if you find it strange, you should mark it as such, if the person is certain that the title is correct.<br /><br />Clearly mark the job of each person. Example: coffee planter (for a person who gets a large part of their income from the cultivation of coffee);<br /><br /><div class="i1">-Cocoa planter (for a person who gets a large part of their income from the cultivation of cocoa);<br /><br />-Rice farmer (for a person who lives primarily lives off of the cultivation of rice, this product being destined for sale);<br /><br />-Farmer (for a person who lives primarily off of mixed farming and self-sufficiency farming for home consumption, meaning they feed themselves from what they cultivate)<br /><br />-Livestock farmer (for a person who lives primarily off breeding)<br /><br />-Shepherd (for a person who watches over a flock);<br /><br />-Teacher (for a person who has the job of teaching)<br /><br />-Agricultural engineer (for a person who has the job of agricultural engineer)</div><br /><br />N.B. Responses like the responses below should not be allowed. <br /><div class="i1">-"Farmer" for anyone who cultivates the earth<br /><br />-"Engineer" for any engineer<br /><br />- "Government employee" for any government employee</div><br /></svar> Cameroon 1976: Persons age 4+ who ever worked [discrepancies: type I 0.1%; type II 0.7%] This variable indicates the occupation (1 digit). 1 Professional, Technical and Related Workers 2 Administrative and Managerial Workers 3 Clerical and Related Workers 4 Sales Workers 5 Service Workers 6 Agricultural, Animal Husbandry and Forestry Workers, Fishermen and Hunters 7 Production and Related Workers, Transport Equipment Operators and Labourers 8 Unknown 9 NIU (not in universe) Work: Occupation Variables -- PERSON Occupation (2 digits) <svar v="CM76A414 CM76A415 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">Population 4 years old or older</span><br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421 CM76A422 CM76A423"><span class="h3">Ask only those who have worked during the reference period (WK) and those without work having already worked (UN). For the others, mark with the line. </span><br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421" a="all"><span class="em">22) Employment</span><br /><div class="i1">- For those who have worked during the reference period (WK): What job did you have during this period? ____<br />- For those without a job having already worked (UN): "What was your last job?" ____</div><br />Mark clearly the job occupied [Example omitted]<br /></svar> <svar v="CM76A414 CM76A415 CM76A427 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">b) Column 17 to 25:</span><br /><br />To be filled out individually for the people ages 4 and over (mark a line in column 17 to 25 for children under 4. <br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421 CM76A422 CM76A423">N.B. Columns on employment (columns 22 to 24)<br /><br />These columns are only to be filled out for people having worked during the reference week (WK in column 21) and for people without employment already having worked, in search of a new job (UN in column 21). For all others, mark a line from column 22 to column 24.<br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421" a="all"><span class="em">Column 22: Employment:</span><br /><br />For people having worked during the week of reference (WK), mark the job done during this period.<br /><br />For people without jobs, having already worked and looking for another job (UN), mark the last job done.<br /><br />The response to column 22 (what job do you do?) should specify the nature of the task accomplished by the person.<br /><br />Generally, the best description of the occupation of the person is the name of the task; for example, "auto mechanic". When the title of the occupation or the job is vague, do not hesitate to ask for more information to better mark his job: for example if the person tells you he or she is a doctor, ask him if he is a medical doctor, a veterinarian, or a dentist.<br /><br />If you do not know a job title that you are given by a person you are interviewing or if you find it strange, you should mark it as such, if the person is certain that the title is correct.<br /><br />Clearly mark the job of each person. Example: coffee planter (for a person who gets a large part of their income from the cultivation of coffee);<br /><br /><div class="i1">-Cocoa planter (for a person who gets a large part of their income from the cultivation of cocoa);<br /><br />-Rice farmer (for a person who lives primarily lives off of the cultivation of rice, this product being destined for sale);<br /><br />-Farmer (for a person who lives primarily off of mixed farming and self-sufficiency farming for home consumption, meaning they feed themselves from what they cultivate)<br /><br />-Livestock farmer (for a person who lives primarily off breeding)<br /><br />-Shepherd (for a person who watches over a flock);<br /><br />-Teacher (for a person who has the job of teaching)<br /><br />-Agricultural engineer (for a person who has the job of agricultural engineer)</div><br /><br />N.B. Responses like the responses below should not be allowed. <br /><div class="i1">-"Farmer" for anyone who cultivates the earth<br /><br />-"Engineer" for any engineer<br /><br />- "Government employee" for any government employee</div><br /></svar> Cameroon 1976: Persons age 4+ who ever worked [discrepancies: type I 0.1%; type II 0.4%] This variable indicates the occupation (2 digits). 001 Physical Scientists and Related Technicians 002 Architects, Engineers and Related Technicians 004 Aircraft and Ships' Officers 005 Life Scientists and Related Technicians 006 Medical, Dental, Veterinary and Related Workers 008 Statisticians, Mathematicians, Economists, Systems Analysts and Related Technicians 011 Accountants 012 Jurists 013 Teachers 014 Workers in Religion 015 Authors, Journalists and Related Writers 016 Sculptors, Painters, Photographers and Related Creative Artists 017 Composers and Performing Artists 018 Athletes, Sportsmen and Related Workers 019 Professional, Technical and Related Workers Not Elsewhere Classified 020 Legislative Officials and Government Administrators 021 Managers 023 Unknown - Administrative and Managerial Workers 030 Clerical Supervisors 031 Government Executive Officials 032 Stenographers, Typists and Card and TapePunching Machine Operators 033 Bookkeepers, Cashiers and Related Workers 034 Computing Machine Operators 035 Transport and Communications Supervisors 036 Transport Conductors 038 Telephone and Telegraph Operators 039 Clerical and Related Workers Not Elsewhere Classified 040 Managers (Wholesale and Retail Trade) 041 Working Proprietors (Wholesale and Retail Trade) 042 Sales Supervisors and Buyers 043 Technical Salesmen, Commercial Travellers and Manufacturers' Agents 044 Insurance, Real Estate, Securities and Business Services Salesmen and Auctioneers 045 Salesmen, Shop Assistants and Related Workers 049 Sales Workers Not Elsewhere Classified 050 Managers (Catering and Lodging Services) 051 Working Proprietors (Catering and Lodging Services) 052 Housekeeping and Related Service Supervisors 053 Cooks, Waiters, Bartenders and Relaters Workers 054 Maids and Related Housekeeping Service Workers Not Elsewhere Classified 055 Building Caretakers, Charworkers, Cleaners and Related Workers 056 Launderers, DryCleaners and Pressers 057 Hairdressers, Barbers, Beauticians and Related Workers 058 Protective Service Workers 059 Service Workers Not Elsewhere Classified 060 Farm Managers and Supervisors 061 Farmers 062 Agricultural and Animal Husbandry Workers 063 Forestry Workers 064 Fishermen, Hunters and Related Workers 070 Production Supervisors and General Foremen 071 Miners, Quarrymen, Well Drillers and Related Workers 072 Metal Processers 073 Wood Preparation Workers and Paper Makers 074 Chemical Processers and Related Workers 075 Spinners, Weavers, Knitters, Dyers and Related Workers 077 Food and Beverage Processers 078 Tobacco Preparers and Tobacco Product Makers 079 Tailors, Dressmakers, Sewers, Upholsterers, Tanners, Fellmongers, Pelt dressers and Related Workers 080 Shoemakers and Leather Goods Makers 081 Cabinetmakers and Related Woodworkers 083 Stone Cutters, Carvers, Blacksmiths, Toolmakers, and Machine Tool Operators 084 Machinery Fitters, Machine Assemblers and Precision Instrument Makers (except Electrical) 085 Electrical Fitters and Related Electrical and Electronics Workers 086 Broadcasting Station and Sound Equipment Operators and Cinema Projectionists 087 Plumbers, Welders, Sheet Metal and Structural Metal Preparers and Erectors 088 Jewellery and Precious Metal Workers 089 Glass Formers, Potters and Related Workers 090 Rubber and Plastics Product Makers 092 Paper Makers, Printers and Related Workers 093 Painters 094 Production and Related Workers Not Elsewhere Classified 095 Bricklayers, Carpenters and Other Construction Workers 096 Stationary Engine and Related Equipment Operators 097 MaterialHandling and Related Equipment Operators, Dockers and Freight Handlers 098 Transport Equipment Operators 099 Labourers Not Elsewhere Classified 998 Unknown 999 NIU (not in universe) Work: Occupation Variables -- PERSON Employment status <svar v="CM76A414 CM76A415 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">Population 4 years old or older</span><br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421 CM76A422 CM76A423"><span class="h3">Ask only those who have worked during the reference period (WK) and those without work having already worked (UN). For the others, mark with the line. </span><br /></svar></p> <p><svar v="CM76A422" a="all"><span class="em">23) Employment status</span><br />Mark one of the abbreviations from the bottom of the page regarding the status.<br /><div class="i1">[] 1 IND= Independent worker<br />[] 2 EMP= Employer<br />[] 4 SAP= Permanent salaried employee<br />[] 5 SAT= Temporary salaried employee<br />[] 6 APP= Apprentice<br />[] 7 AF= Family aid</div><br /></svar> <svar v="CM76A414 CM76A415 CM76A427 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">b) Column 17 to 25:</span><br /><br />To be filled out individually for the people ages 4 and over (mark a line in column 17 to 25 for children under 4. <br /></svar></p> <p><svar v="CM76A419 CM76A420 CM76A421 CM76A422 CM76A423">N.B. Columns on employment (columns 22 to 24)<br /><br />These columns are only to be filled out for people having worked during the reference week (WK in column 21) and for people without employment already having worked, in search of a new job (UN in column 21). For all others, mark a line from column 22 to column 24.<br /></svar></p> <p><svar v="CM76A422" a="all"><span class="em">Column 23: Employment status</span><br /><br />This is the situation of a person (his status) relating to his current or former employment.<br /><br /><div class="i1">IND for an independent worker (self employed person working alone or with family helpers)<br /><br />EMP For an employer (person who runs his own business with the help of workers or employees, meaning all people working for any type of remuneration: salary, commission, payment in kind, etc?.)<br /><br />SAP for a permanent salaried employee (person who works for a public or private employer for any type of remuneration and has a permanent status)<br /><br />SAT for a temporary salaried employee (person who works for a public or private employer, for any type of remuneration, but only has a temporary status)<br /><br />APP for an apprentice (person who learns a trade from a boss and who doesn't fit into the above categories)<br /><br />AF for a family helper (person participating in the work of a family business without remuneration)</div><br /><br />[Examples omitted]<br /></svar> Cameroon 1976: Personsage 4+ who ever worked [discrepancies: type I 0.1%; type II 0.6%] This variable indicates the work situation. 1 Independent or self-employed 2 Employer 3 Permanent, salaried 4 Temporary, salaried 5 Apprentice 6 Family helper 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Marital status <svar v="CM76A414 CM76A415 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">Population 4 years old or older</span><br /></svar></p> <p><svar v="CM76A424" a="all"><span class="em">25) Marital status</span><br /><div class="i1">[] 10 Single<br />[] 20 Married (woman)<br />[] 21 Man married to 1 woman<br />[] 22 Man married to 2 women<br />[] 23 Man married to 3 women<br />[] 24 Man married to 4 women<br />[] 25 Man married to 5 women<br />[] 26 Man married to 6 women<br />[] 27 Man married to 7 women<br />[] 28 Man married to 8 women<br />[] 29 Man married to 9+ women<br />[] 30 Widowed<br />[] 40 Divorced</div><br /></svar> <svar v="CM76A414 CM76A415 CM76A427 CM76A416 CM76A417 CM76A418 CM76A419 CM76A420 CM76A421 CM76A422 CM76A423 CM76A424"><span class="h3">b) Column 17 to 25:</span><br /><br />To be filled out individually for the people ages 4 and over (mark a line in column 17 to 25 for children under 4. <br /></svar></p> <p><svar v="CM76A424" a="all"><span class="em">Column 25: Marital status</span><br />Mark:<br /><div class="i1">-C for a single person (person who was never married)<br /><br />-M for a married woman<br /><br />-M1 for a man married with 1 wife<br /><br />-M2 for a man married with 2 wives, and so on<br /><br />-V for a widow (person whose partner is deceased and who isn't remarried)<br /><br />-D for a divorced person (person divorced from his/her partner and who isn't remarried) or separated from his/her spouse</div><br /><br />In all cases you should consider statements from the concerned party: a married person is someone who declares himself/herself as such<br /><br />The number of wives to mark for each married man is the number of current wives.<br /><br />[Example omitted]<br /></svar></p> <p>The fourth page of the questionnaire: to be filled out for each household.</p> <p>N.B. These questions should be asked once per household. In cases where several sheets are used for the same household, only fill out the back of the first sheet and mark a line on the back of the extra sheets that are already filed on the inside of the first sheet once the household has been surveyed.</p> <p>Events occurring in the household over the last 12 months.</p> <p>These questions are meant to create an inventory of the births and deaths that occurred in the household over the course of the 12 months that came before the first day of surveying, meaning from April 9 1975 to April 8 1976.</p> <p>Mark this period once in its reserved space, under the following form: "period from 4/9/75 to 4/8/76". Cameroon 1976: Persons age 4+ [discrepancies: type I 0.1%; type II 0.8%] This variable indicates the marital status. 10 Single 20 Married (woman) 21 Man married to 1 woman 22 Man married to 2 women 23 Man married to 3 women 24 Man married to 4 women 25 Man married to 5 women 26 Man married to 6 women 27 Man married to 7 women 28 Man married to 8 women 29 Man married to 9+ women 30 Widow(er) 40 Divorced or separated 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON