General Census of Population and Housing 1998 DDI_MLI_1998_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 1998 - IPUMS Subset PHC ml1998a (IPUMS Harmonized Subset) MLI_1998_PHC_v01_M_v7.6_A_IPUMS Central Bureau of the Census IPUMS (c) Copyright 1998, Central Bureau of the Census and Minnesota Population Center Central Bureau of the Census 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 Nativity and Birthplace Variables -- PERSON Fertility and Mortality 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 Geography: F-N Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Ethnicity and Language Variables -- PERSON Migration: F-N Variables -- PERSON Household Economic Variables -- HOUSEHOLD Technical Person Variables -- PERSON Technical Person Variables -- PERSON Technical Household Variables -- HOUSEHOLD Geography: F-N Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Dwelling Characteristics Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Demographic Variables -- PERSON Other Person Variables -- PERSON Nativity and Birthplace Variables -- PERSON Disability Variables -- PERSON Migration: Global Variables -- PERSON Fertility and Mortality Variables -- PERSON Education Variables -- PERSON Ethnicity and Language Variables -- PERSON Work Variables -- PERSON Work: Occupation Variables -- PERSON Work: Industry Variables -- PERSON April 14, 1998 Mali District Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: A structure used for habitation with walls and a roof or mobile housing such as a nomad tent, boat, or train car occupied at the time of the census. - Households: A household is a group of individuals, related or not, who are living together under the same roof and under the responsibility of a head of household whose authority is recognized by all members of the household. - Group quarters: An institutional household is a group of persons living together for reasons of study, health, work, travel, discipline or common interest. All persons residing in the national territory, excluding diplomats and their families temporarily in Mali, foreign diplomats and their families, army personnel and military police, household members who left more than six months prior to the census. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Mali 1998 MICRODATA SOURCE: Central Bureau of the Census SAMPLE SIZE (person records): 991330. SAMPLE DESIGN: Systematic sample of every 10th household with a random start, drawn by the IPUMS Face-to-face [f2f] A single form with sections on dwellings, individuals, and birth and death events. both, CENSUS DAY: April 14, 1998 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. Central Bureau of the Census 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: Mali, Central Bureau of the Census. General Census of Population and Housing 1998 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 ml1998a, 2025 MLI1998_PHC-H-H.dat Household records 161,880 ascii Minnesota Population Center Version 7.5, IPUMS sample MLI1998_PHC-P-H.dat Person records 991330 ascii Minnesota Population Center Version 7.5, IPUMS sample Record type RECTYPE identifies the type of record for the case: household or person. NOTE: RECTYPE is an alphabetic (character string) variable with a value of 'H' for household records and 'P' for person records. RECTYPE will not appear as a variable in the default rectangular extracts produced by the data extract system. It is only available in hierarchical extracts, to distinguish between the two record types. H Household P Person Technical Household Variables -- HOUSEHOLD Country COUNTRY gives the country from which the sample was drawn. The codes assigned to each country are those used by the UN Statistics Division and the ISO (International Organization for Standardization). 032 Argentina 051 Armenia 040 Austria 050 Bangladesh 112 Belarus 204 Benin 068 Bolivia 072 Botswana 076 Brazil 854 Burkina Faso 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 208 Denmark 214 Dominican Republic 218 Ecuador 818 Egypt 222 El Salvador 231 Ethiopia 242 Fiji 246 Finland 250 France 276 Germany 288 Ghana 300 Greece 320 Guatemala 324 Guinea 332 Haiti 340 Honduras 348 Hungary 352 Iceland 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 384 Côte d'Ivoire 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 418 Laos 426 Lesotho 430 Liberia 454 Malawi 458 Malaysia 466 Mali 480 Mauritius 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 104 Myanmar 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 578 Norway 586 Pakistan 275 Palestine 591 Panama 598 Papua New Guinea 600 Paraguay 604 Peru 608 Philippines 616 Poland 620 Portugal 630 Puerto Rico 642 Romania 643 Russia 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 703 Slovak Republic 705 Slovenia 710 South Africa 728 South Sudan 724 Spain 729 Sudan 740 Suriname 752 Sweden 756 Switzerland 834 Tanzania 764 Thailand 768 Togo 780 Trinidad and Tobago 792 Turkey 800 Uganda 804 Ukraine 826 United Kingdom 840 United States 858 Uruguay 862 Venezuela 704 Vietnam 894 Zambia 716 Zimbabwe Technical Household Variables -- HOUSEHOLD Year YEAR gives the year in which the census or survey was taken. For samples that span years, the midpoint or first year of the interval is reported. 1703 1703 1729 1729 1787 1787 1801 1801 1819 1819 1845 1845 1848 1848 1850 1850 1851 1851 1852 1852 1860 1860 1861 1861 1865 1865 1868 1868 1870 1870 1871 1871 1875 1875 1880 1880 1881 1881 1885 1885 1890 1890 1891 1891 1900 1900 1901 1901 1910 1910 1911 1911 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1966 1966 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 Technical Household Variables -- HOUSEHOLD IPUMS sample identifier SAMPLE identifies the IPUMS sample from which the case is drawn. Each sample receives a unique 9-digit code. The code is structured as follows: The first 3 digits are the ISO/UN codes used in COUNTRY The next 4 digits are the year of the census/survey The final 2 digits identify the sample within the year. For the last two digits, censuses or large census-like surveys have a value "0" (e.g, 01) in the second-to-last digit, household surveys have a value of "2" (e.g., 21), and employment surveys have a value of "4" (e.g., 41). 032197001 Argentina 1970 032198001 Argentina 1980 032199101 Argentina 1991 032200101 Argentina 2001 032201001 Argentina 2010 051200101 Armenia 2001 051201101 Armenia 2011 040197101 Austria 1971 040198101 Austria 1981 040199101 Austria 1991 040200101 Austria 2001 040201101 Austria 2011 050199101 Bangladesh 1991 050200101 Bangladesh 2001 050201101 Bangladesh 2011 112199901 Belarus 1999 112200901 Belarus 2009 204197901 Benin 1979 204199201 Benin 1992 204200201 Benin 2002 204201301 Benin 2013 068197601 Bolivia 1976 068199201 Bolivia 1992 068200101 Bolivia 2001 068201201 Bolivia 2012 072198101 Botswana 1981 072199101 Botswana 1991 072200101 Botswana 2001 072201101 Botswana 2011 076196001 Brazil 1960 076197001 Brazil 1970 076198001 Brazil 1980 076199101 Brazil 1991 076200001 Brazil 2000 076201001 Brazil 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 116199801 Cambodia 1998 116200401 Cambodia 2004 116200801 Cambodia 2008 116201301 Cambodia 2013 116201901 Cambodia 2019 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124185201 Canada 1852 124187101 Canada 1871 124188101 Canada 1881 124189101 Canada 1891 124190101 Canada 1901 124191101 Canada 1911 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 124201101 Canada 2011 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 152201701 Chile 2017 156198201 China 1982 156199001 China 1990 156200001 China 2000 170196401 Colombia 1964 170197301 Colombia 1973 170198501 Colombia 1985 170199301 Colombia 1993 170200501 Colombia 2005 188196301 Costa Rica 1963 188197301 Costa Rica 1973 188198401 Costa Rica 1984 188200001 Costa Rica 2000 188201101 Costa Rica 2011 192200201 Cuba 2002 192201201 Cuba 2012 208178701 Denmark 1787 208180101 Denmark 1801 208184501 Denmark 1845 208188001 Denmark 1880 208188501 Denmark 1885 214196001 Dominican Republic 1960 214197001 Dominican Republic 1970 214198101 Dominican Republic 1981 214200201 Dominican Republic 2002 214201001 Dominican Republic 2010 218196201 Ecuador 1962 218197401 Ecuador 1974 218198201 Ecuador 1982 218199001 Ecuador 1990 218200101 Ecuador 2001 218201001 Ecuador 2010 818184801 Egypt 1848 818186801 Egypt 1868 818198601 Egypt 1986 818199601 Egypt 1996 818200601 Egypt 2006 222199201 El Salvador 1992 222200701 El Salvador 2007 231198401 Ethiopia 1984 231199401 Ethiopia 1994 231200701 Ethiopia 2007 242196601 Fiji 1966 242197601 Fiji 1976 242198601 Fiji 1986 242199601 Fiji 1996 242200701 Fiji 2007 242201401 Fiji 2014 246201001 Finland 2010 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 276181901 Germany 1819 (Mecklenburg) 276197001 Germany 1970 (West) 276197101 Germany 1971 (East) 276198101 Germany 1981 (East) 276198701 Germany 1987 (West) 288198401 Ghana 1984 288200001 Ghana 2000 288201001 Ghana 2010 300197101 Greece 1971 300198101 Greece 1981 300199101 Greece 1991 300200101 Greece 2001 300201101 Greece 2011 320196401 Guatemala 1964 320197301 Guatemala 1973 320198101 Guatemala 1981 320199401 Guatemala 1994 320200201 Guatemala 2002 324198301 Guinea 1983 324199601 Guinea 1996 324201401 Guinea 2014 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 340196101 Honduras 1961 340197401 Honduras 1974 340198801 Honduras 1988 340200101 Honduras 2001 340201301 Honduras 2013 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 348201101 Hungary 2011 352170301 Iceland 1703 352172901 Iceland 1729 352180101 Iceland 1801 352190101 Iceland 1901 352191001 Iceland 1910 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 356200941 India 2009 360197101 Indonesia 1971 360197601 Indonesia 1976 360198001 Indonesia 1980 360198501 Indonesia 1985 360199001 Indonesia 1990 360199501 Indonesia 1995 360200001 Indonesia 2000 360200501 Indonesia 2005 360201001 Indonesia 2010 364200601 Iran 2006 364201101 Iran 2011 368199701 Iraq 1997 372190101 Ireland 1901 372191101 Ireland 1911 372197101 Ireland 1971 372197901 Ireland 1979 372198101 Ireland 1981 372198601 Ireland 1986 372199101 Ireland 1991 372199601 Ireland 1996 372200201 Ireland 2002 372200601 Ireland 2006 372201101 Ireland 2011 372201601 Ireland 2016 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 376200801 Israel 2008 380200101 Italy 2001 380201101 Italy 2011 380201121 Italy 2011 Q1 LFS 380201221 Italy 2012 Q1 LFS 380201321 Italy 2013 Q1 LFS 380201421 Italy 2014 Q1 LFS 380201521 Italy 2015 Q1 LFS 380201621 Italy 2016 Q1 LFS 380201721 Italy 2017 Q1 LFS 380201821 Italy 2018 Q1 LFS 380201921 Italy 2019 Q1 LFS 380202021 Italy 2020 Q1 LFS 384198801 Côte d'Ivoire 1988 384199801 Côte d'Ivoire 1998 388198201 Jamaica 1982 388199101 Jamaica 1991 388200101 Jamaica 2001 400200401 Jordan 2004 404196901 Kenya 1969 404197901 Kenya 1979 404198901 Kenya 1989 404199901 Kenya 1999 404200901 Kenya 2009 404201901 Kenya 2019 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 418199501 Laos 1995 418200501 Laos 2005 418201501 Laos 2015 426199601 Lesotho 1996 426200601 Lesotho 2006 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 454201801 Malawi 2018 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 480199001 Mauritius 1990 480200001 Mauritius 2000 480201101 Mauritius 2011 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 484201501 Mexico 2015 484202001 Mexico 2020 484200521 Mexico 2005 Q1 LFS 484200522 Mexico 2005 Q2 LFS 484200523 Mexico 2005 Q3 LFS 484200524 Mexico 2005 Q4 LFS 484200621 Mexico 2006 Q1 LFS 484200622 Mexico 2006 Q2 LFS 484200623 Mexico 2006 Q3 LFS 484200624 Mexico 2006 Q4 LFS 484200721 Mexico 2007 Q1 LFS 484200722 Mexico 2007 Q2 LFS 484200723 Mexico 2007 Q3 LFS 484200724 Mexico 2007 Q4 LFS 484200821 Mexico 2008 Q1 LFS 484200822 Mexico 2008 Q2 LFS 484200823 Mexico 2008 Q3 LFS 484200824 Mexico 2008 Q4 LFS 484200921 Mexico 2009 Q1 LFS 484200922 Mexico 2009 Q2 LFS 484200923 Mexico 2009 Q3 LFS 484200924 Mexico 2009 Q4 LFS 484201021 Mexico 2010 Q1 LFS 484201022 Mexico 2010 Q2 LFS 484201023 Mexico 2010 Q3 LFS 484201024 Mexico 2010 Q4 LFS 484201121 Mexico 2011 Q1 LFS 484201122 Mexico 2011 Q2 LFS 484201123 Mexico 2011 Q3 LFS 484201124 Mexico 2011 Q4 LFS 484201221 Mexico 2012 Q1 LFS 484201222 Mexico 2012 Q2 LFS 484201223 Mexico 2012 Q3 LFS 484201224 Mexico 2012 Q4 LFS 484201321 Mexico 2013 Q1 LFS 484201322 Mexico 2013 Q2 LFS 484201323 Mexico 2013 Q3 LFS 484201324 Mexico 2013 Q4 LFS 484201421 Mexico 2014 Q1 LFS 484201422 Mexico 2014 Q2 LFS 484201423 Mexico 2014 Q3 LFS 484201424 Mexico 2014 Q4 LFS 484201521 Mexico 2015 Q1 LFS 484201522 Mexico 2015 Q2 LFS 484201523 Mexico 2015 Q3 LFS 484201524 Mexico 2015 Q4 LFS 484201621 Mexico 2016 Q1 LFS 484201622 Mexico 2016 Q2 LFS 484201623 Mexico 2016 Q3 LFS 484201624 Mexico 2016 Q4 LFS 484201721 Mexico 2017 Q1 LFS 484201722 Mexico 2017 Q2 LFS 484201723 Mexico 2017 Q3 LFS 484201724 Mexico 2017 Q4 LFS 484201821 Mexico 2018 Q1 LFS 484201822 Mexico 2018 Q2 LFS 484201823 Mexico 2018 Q3 LFS 484201824 Mexico 2018 Q4 LFS 484201921 Mexico 2019 Q1 LFS 484201922 Mexico 2019 Q2 LFS 484201923 Mexico 2019 Q3 LFS 484201924 Mexico 2019 Q4 LFS 484202021 Mexico 2020 Q1 LFS 484202023 Mexico 2020 Q3 LFS 496198901 Mongolia 1989 496200001 Mongolia 2000 496201001 Mongolia 2010 496202001 Mongolia 2020 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 508201701 Mozambique 2017 104201401 Myanmar 2014 524200101 Nepal 2001 524201101 Nepal 2011 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 528201101 Netherlands 2011 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 578180101 Norway 1801 578186501 Norway 1865 578187501 Norway 1875 578190001 Norway 1900 578191001 Norway 1910 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 275199701 Palestine 1997 275200701 Palestine 2007 275201701 Palestine 2017 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 598198001 Papua New Guinea 1980 598199001 Papua New Guinea 1990 598200001 Papua New Guinea 2000 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 604201701 Peru 2017 608199721 Philippines 1997 Q1 LFS 608199722 Philippines 1997 Q2 LFS 608199723 Philippines 1997 Q3 LFS 608199724 Philippines 1997 Q4 LFS 608199821 Philippines 1998 Q1 LFS 608199822 Philippines 1998 Q2 LFS 608199823 Philippines 1998 Q3 LFS 608199824 Philippines 1998 Q4 LFS 608199921 Philippines 1999 Q1 LFS 608199922 Philippines 1999 Q2 LFS 608199923 Philippines 1999 Q3 LFS 608199924 Philippines 1999 Q4 LFS 608200021 Philippines 2000 Q1 LFS 608200022 Philippines 2000 Q2 LFS 608200023 Philippines 2000 Q3 LFS 608200024 Philippines 2000 Q4 LFS 608200121 Philippines 2001 Q1 LFS 608200122 Philippines 2001 Q2 LFS 608200123 Philippines 2001 Q3 LFS 608200124 Philippines 2001 Q4 LFS 608200221 Philippines 2002 Q1 LFS 608200222 Philippines 2002 Q2 LFS 608200223 Philippines 2002 Q3 LFS 608200224 Philippines 2002 Q4 LFS 608200321 Philippines 2003 Q1 LFS 608200322 Philippines 2003 Q2 LFS 608200323 Philippines 2003 Q3 LFS 608200324 Philippines 2003 Q4 LFS 608200421 Philippines 2004 Q1 LFS 608200422 Philippines 2004 Q2 LFS 608200423 Philippines 2004 Q3 LFS 608200424 Philippines 2004 Q4 LFS 608200521 Philippines 2005 Q1 LFS 608200522 Philippines 2005 Q2 LFS 608200523 Philippines 2005 Q3 LFS 608200524 Philippines 2005 Q4 LFS 608200621 Philippines 2006 Q1 LFS 608200622 Philippines 2006 Q2 LFS 608200623 Philippines 2006 Q3 LFS 608200624 Philippines 2006 Q4 LFS 608200721 Philippines 2007 Q1 LFS 608200722 Philippines 2007 Q2 LFS 608200723 Philippines 2007 Q3 LFS 608200724 Philippines 2007 Q4 LFS 608200821 Philippines 2008 Q1 LFS 608200822 Philippines 2008 Q2 LFS 608200823 Philippines 2008 Q3 LFS 608200824 Philippines 2008 Q4 LFS 608200921 Philippines 2009 Q1 LFS 608200922 Philippines 2009 Q2 LFS 608200923 Philippines 2009 Q3 LFS 608200924 Philippines 2009 Q4 LFS 608201021 Philippines 2010 Q1 LFS 608201022 Philippines 2010 Q2 LFS 608201023 Philippines 2010 Q3 LFS 608201024 Philippines 2010 Q4 LFS 608201121 Philippines 2011 Q1 LFS 608201122 Philippines 2011 Q2 LFS 608201123 Philippines 2011 Q3 LFS 608201124 Philippines 2011 Q4 LFS 608201221 Philippines 2012 Q1 LFS 608201222 Philippines 2012 Q2 LFS 608201223 Philippines 2012 Q3 LFS 608201224 Philippines 2012 Q4 LFS 608201321 Philippines 2013 Q1 LFS 608201322 Philippines 2013 Q2 LFS 608201323 Philippines 2013 Q3 LFS 608201324 Philippines 2013 Q4 LFS 608201421 Philippines 2014 Q1 LFS 608201422 Philippines 2014 Q2 LFS 608201423 Philippines 2014 Q3 LFS 608201424 Philippines 2014 Q4 LFS 608201521 Philippines 2015 Q1 LFS 608201522 Philippines 2015 Q2 LFS 608201523 Philippines 2015 Q3 LFS 608201524 Philippines 2015 Q4 LFS 608201621 Philippines 2016 Q1 LFS 608201622 Philippines 2016 Q2 LFS 608201623 Philippines 2016 Q3 LFS 608201624 Philippines 2016 Q4 LFS 608201721 Philippines 2017 Q1 LFS 608201722 Philippines 2017 Q2 LFS 608201723 Philippines 2017 Q3 LFS 608201724 Philippines 2017 Q4 LFS 608201821 Philippines 2018 Q1 LFS 608201822 Philippines 2018 Q2 LFS 608201823 Philippines 2018 Q3 LFS 608201824 Philippines 2018 Q4 LFS 608201921 Philippines 2019 Q1 LFS 608201922 Philippines 2019 Q2 LFS 608201923 Philippines 2019 Q3 LFS 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 608201001 Philippines 2010 616197801 Poland 1978 616198801 Poland 1988 616200201 Poland 2002 616201101 Poland 2011 620198101 Portugal 1981 620199101 Portugal 1991 620200101 Portugal 2001 620201101 Portugal 2011 630197001 Puerto Rico 1970 630198001 Puerto Rico 1980 630199001 Puerto Rico 1990 630200001 Puerto Rico 2000 630200501 Puerto Rico 2005 630201001 Puerto Rico 2010 630201501 Puerto Rico 2015 630202001 Puerto Rico 2020 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 642201101 Romania 2011 643200201 Russia 2002 643201001 Russia 2010 646199101 Rwanda 1991 646200201 Rwanda 2002 646201201 Rwanda 2012 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 686201301 Senegal 2013 694200401 Sierra Leone 2004 694201501 Sierra Leone 2015 703199101 Slovak Republic 1991 703200101 Slovak Republic 2001 703201101 Slovak Republic 2011 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 710201601 South Africa 2016 728200801 South Sudan 2008 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 724200521 Spain 2005 Q1 LFS 724200522 Spain 2005 Q2 LFS 724200523 Spain 2005 Q3 LFS 724200524 Spain 2005 Q4 LFS 724200621 Spain 2006 Q1 LFS 724200622 Spain 2006 Q2 LFS 724200623 Spain 2006 Q3 LFS 724200624 Spain 2006 Q4 LFS 724200721 Spain 2007 Q1 LFS 724200722 Spain 2007 Q2 LFS 724200723 Spain 2007 Q3 LFS 724200724 Spain 2007 Q4 LFS 724200821 Spain 2008 Q1 LFS 724200822 Spain 2008 Q2 LFS 724200823 Spain 2008 Q3 LFS 724200824 Spain 2008 Q4 LFS 724200921 Spain 2009 Q1 LFS 724200922 Spain 2009 Q2 LFS 724200923 Spain 2009 Q3 LFS 724200924 Spain 2009 Q4 LFS 724201021 Spain 2010 Q1 LFS 724201022 Spain 2010 Q2 LFS 724201023 Spain 2010 Q3 LFS 724201024 Spain 2010 Q4 LFS 724201121 Spain 2011 Q1 LFS 724201122 Spain 2011 Q2 LFS 724201123 Spain 2011 Q3 LFS 724201124 Spain 2011 Q4 LFS 724201221 Spain 2012 Q1 LFS 724201222 Spain 2012 Q2 LFS 724201223 Spain 2012 Q3 LFS 724201224 Spain 2012 Q4 LFS 724201321 Spain 2013 Q1 LFS 724201322 Spain 2013 Q2 LFS 724201323 Spain 2013 Q3 LFS 724201324 Spain 2013 Q4 LFS 724201421 Spain 2014 Q1 LFS 724201422 Spain 2014 Q2 LFS 724201423 Spain 2014 Q3 LFS 724201424 Spain 2014 Q4 LFS 724201521 Spain 2015 Q1 LFS 724201522 Spain 2015 Q2 LFS 724201523 Spain 2015 Q3 LFS 724201524 Spain 2015 Q4 LFS 724201621 Spain 2016 Q1 LFS 724201622 Spain 2016 Q2 LFS 724201623 Spain 2016 Q3 LFS 724201624 Spain 2016 Q4 LFS 724201721 Spain 2017 Q1 LFS 724201722 Spain 2017 Q2 LFS 724201723 Spain 2017 Q3 LFS 724201724 Spain 2017 Q4 LFS 724201821 Spain 2018 Q1 LFS 724201822 Spain 2018 Q2 LFS 724201823 Spain 2018 Q3 LFS 724201824 Spain 2018 Q4 LFS 724201921 Spain 2019 Q1 LFS 724201922 Spain 2019 Q2 LFS 724201923 Spain 2019 Q3 LFS 724201924 Spain 2019 Q4 LFS 724202021 Spain 2020 Q1 LFS 724202022 Spain 2020 Q2 LFS 724202023 Spain 2020 Q3 LFS 724202024 Spain 2020 Q4 LFS 729200801 Sudan 2008 740200401 Suriname 2004 740201201 Suriname 2012 752188001 Sweden 1880 752189001 Sweden 1890 752190001 Sweden 1900 752191001 Sweden 1910 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 756201101 Switzerland 2011 834198801 Tanzania 1988 834200201 Tanzania 2002 834201201 Tanzania 2012 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 768196001 Togo 1960 768197001 Togo 1970 768201001 Togo 2010 780197001 Trinidad and Tobago 1970 780198001 Trinidad and Tobago 1980 780199001 Trinidad and Tobago 1990 780200001 Trinidad and Tobago 2000 780201101 Trinidad and Tobago 2011 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 800201401 Uganda 2014 804200101 Ukraine 2001 826185101 United Kingdom 1851 (England and Wales) 826185102 United Kingdom 1851 (Scotland) 826185103 United Kingdom 1851 (2% sample) 826186101 United Kingdom 1861 (England and Wales) 826186102 United Kingdom 1861 (Scotland) 826187101 United Kingdom 1871 (Scotland) 826188101 United Kingdom 1881 (England and Wales) 826188102 United Kingdom 1881 (Scotland) 826189101 United Kingdom 1891 (England and Wales) 826189102 United Kingdom 1891 (Scotland) 826190101 United Kingdom 1901 (England and Wales) 826190102 United Kingdom 1901 (Scotland) 826191101 United Kingdom 1911 (England and Wales) 826196101 United Kingdom 1961 826197101 United Kingdom 1971 826199101 United Kingdom 1991 826200101 United Kingdom 2001 840185001 United States 1850 (100%) 840185002 United States 1850 (1%) 840186001 United States 1860 (1%) 840187001 United States 1870 (1%) 840188001 United States 1880 (100%) 840188002 United States 1880 (10%) 840190001 United States 1900 (5%) 840191001 United States 1910 (1%) 840196001 United States 1960 840197001 United States 1970 840198001 United States 1980 840199001 United States 1990 840200001 United States 2000 840200501 United States 2005 840201001 United States 2010 840201501 United States 2015 840202001 United States 2020 858196301 Uruguay 1963 858196302 Uruguay 1963 (full count) 858197501 Uruguay 1975 858197502 Uruguay 1975 (full count) 858198501 Uruguay 1985 858198502 Uruguay 1985 (full count) 858199601 Uruguay 1996 858199602 Uruguay 1996 (full count) 858200621 Uruguay 2006 858201101 Uruguay 2011 858201102 Uruguay 2011 (full count) 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 704201901 Vietnam 2019 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 716201201 Zimbabwe 2012 Technical Household Variables -- HOUSEHOLD Household serial number SERIAL is an identifying number unique to each household in a given sample. All person records are assigned the same serial number as the household record that they follow. (Person records also have their own unique identifiers -- see PERNUM.) The combination of SAMPLE and SERIAL provides a unique identifier for every household in the IPUMS-International database; SAMPLE, SERIAL and PERNUM uniquely identify every person in the database. SERIAL can be used to identify dwellings in some samples. In these samples, the first 7 digits of SERIAL provide the dwelling number common to all households that were sampled from the same structure. The last three digits give the sequence of the household within the dwelling. The following is a list of samples in which dwellings can be inferred: Chile 1970, 1992, 2002Colombia 1993, 2005Costa Rica 1984, 2000Cuba 2002Dominican Republic 1981, 2002, 2010Ecuador 1990, 2001Germany 1971Hungary 1980, 1990, 2001Jamaica 1982, 1991, 2001Malaysia 1970, 1991, 2000Mexico 1995, 1990, 2000, 2005Nigeria 2006Panama 2000Peru 1993, 2007Portugal 1981, 1991, 2001Spain 1991Uruguay 2011Venezuela 1990, 2001Vietnam 1989In all other samples, the last 3 digits are always zeroes. SERIAL was constructed for IPUMS-International, and has no relation to the serial number in the original datasets. The U.S. 1900 sample and 1880 10% sample have multi-household dwellings that can be identified using the last 3 digits of SERIAL. SERIAL is a 10-digit numeric variable. The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes. Technical Household Variables -- HOUSEHOLD Number of person records in the household PERSONS indicates how many person records are included in the household (i.e., the number of person records associated with the household record in the sample). These person records will all have the same serial number (SERIAL) as the household record. The information contained in the household record will normally apply to all of these persons. PERSONS is a 4-digit numeric variable. Technical Household Variables -- HOUSEHOLD Household weight HHWT indicates the number of households in the population represented by the household in the sample. For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics. NOTE: HHWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Household Variables -- HOUSEHOLD Subsample number SUBSAMP allocates each case to one of 100 subsample replicates, randomly numbered from 0 to 99. Each subsample is nationally representative and preserves any stratification of the sample from which it is drawn. Users who need a representative subset of a sample can use SUBSAMP to select their cases. For example, to randomly extract 10% of the cases from a sample, select any 10 of the 100 subsamples. 00 1st 1% subsample 01 2nd 1% subsample 02 3rd 1% subsample 03 4th 1% subsample 04 5th 1% subsample 05 6th 1% subsample 06 7th 1% subsample 07 8th 1% subsample 08 9th 1% subsample 09 10th 1% subsample 10 11th 1% subsample 11 12th 1% subsample 12 13th 1% subsample 13 14th 1% subsample 14 15th 1% subsample 15 16th 1% subsample 16 17th 1% subsample 17 18th 1% subsample 18 19th 1% subsample 19 20th 1% subsample 20 21st 1% subsample 21 22nd 1% subsample 22 23rd 1% subsample 23 24th 1% subsample 24 25th 1% subsample 25 26th 1% subsample 26 27th 1% subsample 27 28th 1% subsample 28 29th 1% subsample 29 30th 1% subsample 30 31st 1% subsample 31 32nd 1% subsample 32 33rd 1% subsample 33 34th 1% subsample 34 35th 1% subsample 35 36th 1% subsample 36 37th 1% subsample 37 38th 1% subsample 38 39th 1% subsample 39 40th 1% subsample 40 41st 1% subsample 41 42nd 1% subsample 42 43rd 1% subsample 43 44th 1% subsample 44 45th 1% subsample 45 46th 1% subsample 46 47th 1% subsample 47 48th 1% subsample 48 49th 1% subsample 49 50th 1% subsample 50 51st 1% subsample 51 52nd 1% subsample 52 53rd 1% subsample 53 54th 1% subsample 54 55th 1% subsample 55 56th 1% subsample 56 57th 1% subsample 57 58th 1% subsample 58 59th 1% subsample 59 60th 1% subsample 60 61st 1% subsample 61 62nd 1% subsample 62 63rd 1% subsample 63 64th 1% subsample 64 65th 1% subsample 65 66th 1% subsample 66 67th 1% subsample 67 68th 1% subsample 68 69th 1% subsample 69 70th 1% subsample 70 71st 1% subsample 71 72nd 1% subsample 72 73rd 1% subsample 73 74th 1% subsample 74 75th 1% subsample 75 76th 1% subsample 76 77th 1% subsample 77 78th 1% subsample 78 79th 1% subsample 79 80th 1% subsample 80 81st 1% subsample 81 82nd 1% subsample 82 83rd 1% subsample 83 84th 1% subsample 84 85th 1% subsample 85 86th 1% subsample 86 87th 1% subsample 87 88th 1% subsample 88 89th 1% subsample 89 90th 1% subsample 90 91st 1% subsample 91 92nd 1% subsample 92 93rd 1% subsample 93 94th 1% subsample 94 95th 1% subsample 95 96th 1% subsample 96 97th 1% subsample 97 98th 1% subsample 98 99th 1% subsample 99 100th 1% subsample Technical Household Variables -- HOUSEHOLD Strata identifier This variable is the strata identifier for the sample. The STRATA variable provides information about the sample design that can be used to improve estimation. STRATA is a 12-digit numeric variable. Technical Household Variables -- HOUSEHOLD Group quarters (collective dwelling) status GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools. Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification. Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions. 00 Vacant 10 Households 20 Group quarters (collective), n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified Group Quarters Variables -- HOUSEHOLD Number of unrelated persons UNREL indicates the number of persons in the household who are unrelated to the head as defined in the variable RELATE. 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ Group Quarters Variables -- HOUSEHOLD Urban-rural status URBAN indicates whether the household was located in a place designated as urban or as rural. 1 Rural 2 Urban 9 Unknown Geography: Global Variables -- HOUSEHOLD Continent and region of country REGIONW identifies the continent and region of each country. 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia Geography: Global Variables -- HOUSEHOLD 1st subnational geographic level, world [consistent boundaries over time] GEOLEV1 indicates the major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. First administrative units in GEOLEV1 have been spatiotemporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV1 is a 6-digit numeric variable. GEOLEV1 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO1_BR. Geography: Global Variables -- HOUSEHOLD 2nd subnational geographic level, world [consistent boundaries over time] GEOLEV2 indicates the second major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. Second administrative units in GEOLEV2 have been spatio-temporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV2 is a 9-digit numeric variable. GEOLEV2 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO2_BR. Geography: Global Variables -- HOUSEHOLD Population density of GEOLEV1 unit, in persons per square kilometer POPDENSGEO1 indicates the population density in persons per square kilometer of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO1 is an 8-digit numeric variable listing the population density in persons per square kilometer. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Population density of GEOLEV2 unit, in persons per square kilometer POPDENSGEO2 indicates the population density in persons per square kilometer of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO2 is a 12-digit numeric variable listing the population density in persons per square kilometer. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Area of GEOLEV1 unit in square kilometers AREAMOLLWGEO1 indicates the area in square kilometers of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO1 is a 10-digit numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Area of GEOLEV2 unit in square kilometers AREAMOLLWGEO2 indicates the area in square kilometers of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO2 is a 10-digit numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Mali, Region 1987 - 2009 [Level 1; consistent boundaries, GIS] GEO1_ML identifies the household's region within Mali in all sample years. Regions are the first level administrative units of the country. GEO1_ML 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 GEO1A_ML codes can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Mali 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. 466001 Kayes 466002 Koulikoro 466003 Sikasso 466004 Ségou 466005 Mopti 466006 Tombouctou 466007 Gao, Kidal 466009 Bamako 466099 Unknown Geography: F-N Variables -- HOUSEHOLD Mali, Region 1998 [Level 1, GIS] GEO1_ ML1998 identifies the household's region within Mali in 1998. Regions are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_ ML1998 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Mali 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 Kayes 002 Koulikoro 003 Sikasso 004 Ségou 005 Mopti 006 Tombouctou 007 Gao 008 Kidal 009 Bamako Geography: F-N Variables -- HOUSEHOLD Mali, Circle 1987 - 2009 [Level 2; consistent boundaries, GIS] GEO2_ML identifies the household’s circle (cercle) within Mali in all sample years. Circles are the second level administrative units of the country, after regions. GEO2_ML 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_ML can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Mali 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. 466001001 Kayes 466001002 Bafoulabé 466001003 Diéma 466001004 Kéniéba 466001005 Kita 466001006 Nioro 466001007 Yélimané 466002001 Koulikoro 466002002 Banamba 466002003 Dioïla 466002004 Kangaba 466002005 Kati 466002006 Kolokani 466002007 Nara 466003001 Sikasso 466003002 Bougouni 466003003 Kadiolo 466003004 Kolondiéba 466003005 Koutiala 466003006 Yanfolila 466003007 Yorosso 466004001 Ségou 466004002 Barouéli 466004003 Bla 466004004 Macina 466004005 Niono 466004006 San 466004007 Tominian 466005001 Mopti 466005002 Bandiagara 466005003 Bankass 466005004 Djenné 466005005 Douentza 466005006 Koro 466005007 Ténenkou 466005008 Youwarou 466006001 Tombouctou 466006002 Diré 466006003 Goundam 466006004 Gourma-Rharous 466006005 Niafunké 466007001 Gao 466007002 Ansongo 466007003 Bourem 466007004 Ménaka 466007005 Kidal, Abéïbara, Tessalit, Tin-Essako 466009001 District of Bamako 466099999 Unknown Geography: F-N Variables -- HOUSEHOLD Mali, Circle 1998 [Level 2, GIS] GEO2_ ML1998 identifies the household's circle within Mali in 1998. Circles are the second level administrative units of the country, after regions. A GIS map (in shapefile format), corresponding to GEO2_ ML1998 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Mali 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. 001001 Kayes 001002 Bafoulabé 001003 Diéma 001004 Kéniéba 001005 Kita 001006 Nioro 001007 Yélimané 002001 Koulikoro 002002 Banamba 002003 Dioïla 002004 Kangaba 002005 Kati 002006 Kolokani 002007 Nara 003001 Sikasso 003002 Bougouni 003003 Kadiolo 003004 Kolondiéba 003005 Koutiala 003006 Yanfolila 003007 Yorosso 004001 Ségou 004002 Barouéli 004003 Bla 004004 Macina 004005 Niono 004006 San 004007 Tominian 005001 Mopti 005002 Bandiagara 005003 Bankass 005004 Djenné 005005 Douentza 005006 Koro 005007 Ténenkou 005008 Youvarou 006001 Tombouctou 006002 Diré 006003 Goundam 006004 Gourma-Rharous 006005 Niafunké 007001 Gao 007002 Ansongo 007003 Bourem 007004 Ménaka 008001 Abéïbara, Kidal, Tessalit, Tin Essako 009001 Bamako district Geography: F-N Variables -- HOUSEHOLD Mali, District 1998 [Level 2, GIS] GEO3_ML1998 identifies the household's district within Mali in 1998. Districts are the third level administrative units of the country, after regions and cercles. A GIS map (in shapefile format), corresponding to GEO3_ML1998 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Mali 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. 001001001 Kayes 001001002 Segala 001001003 Ambidedi 001001004 Lontou, Kayes Central 001001005 Aourou 001001006 Sadiola 001001007 Samé 001001008 Diadioumera 001001009 Koussane 001001010 Diamou 001002001 Koundian, Mahina 001002002 Oussoubidiagna, Diallan 001002003 Diakon 001002004 Bamafélé 001002005 Bafoulabé Central 001002006 Goundara 001002007 Oualia 001003001 Diangounte camar 001003002 Bema 001003003 Diema central 001003004 Lakamane 001003005 Dioumara 001004001 Kéniéba Central 001004002 Faraba, Falea 001004003 Dialafara, Kassama 001004004 Dombia 001005001 Kita Central 001005002 Sebekoro 001005003 Séféto 001005004 Kita 001005005 Djidian 001005006 Kokofata 001005007 Sagabari 001005008 Sirakoro 001005009 Toukoto 001006001 Korera Kore, Troungoumbe, Gogui 001006002 Nioro Central 001006003 Sandaré, Simbi 001006004 Gavinane 001006005 Nioro 001007001 Yélimané Central, Marena 001007002 Kirane 001007003 Tambacara 002001001 Tougouni, Tienfala, Koulikoro Central 002001002 Commune Koulikoro 002001003 Koula-koulikoro 002001004 Niamina 002001005 Sirakorola 002001006 Kénékou 002002001 Banamba Central 002002002 Toubacoura 002002003 Boron 002002004 Sébété, Toukoroba 002002005 Madina Sacko 002003001 Fana 002003002 Dioïla Central 002003003 Massigui 002003004 Beleko 002003005 Banco 002003006 Ména 002004001 Kangaba Central 002004002 Narena 002005001 Kalabancoro 002005002 Baguineda 002005003 Kati Central 002005004 Kati 002005005 Siby 002005006 Neguela 002005007 Sanankoroba 002005008 Ouelessebougou 002005009 Kourouba 002006001 Kolokani Central 002006002 Nonssombougou 002006003 Djidieni 002006004 Massantola 002007001 Nara Central 002007002 Ballé 002007003 Mourdiah, Guiré 002007004 Dilly 002007005 Fallou 003001001 Commune Sikasso 003001002 Sikasso Central 003001003 Kignan 003001004 Finkolo, Niéna 003001005 Klela 003001006 Blendio 003001007 Danderesso 003001008 Lobougoula 003001009 N'kourala 003001010 Dogoni 003002001 Garalo 003002002 Dogo-bougouni 003002003 Koumantou 003002004 Sanso 003002005 Bougouni Central 003002006 Keleya 003002007 Commune Bougouni 003002008 Manankoro 003002009 Zantiebougou 003002010 Faragouaran 003003001 Kadiolo Central 003003002 Loulouni 003003003 Misseni, Fourou 003004001 Kolondiéba Central, Tonssékéla 003004002 Kadiona 003004003 Fakola 003004004 Kebila 003005001 M'pessoba 003005002 Commune Koutiala 003005003 Koutiala Central 003005004 Molobala 003005005 Kouniana 003005006 Konsseguela 003005007 Zangasso 003006001 Doussoudiana, Yanfolila Central 003006002 Kangaré 003006003 Filamana, Yorobougoula 003006004 Siékorolé 003006005 Gueleninkoro 003006006 Kalana 003007001 Kouri, Mahou 003007002 Yorosso Central 003007003 Boura 004001001 Ségou 004001002 Ségou Central 004001003 Dioro 004001004 Markala 004001005 Katiena 004001006 Farako 004001007 Sinzana 004001008 Sansanding 004001009 Doura 004002001 Barouéli central 004002002 Tamani 004002003 Sanando 004002004 Konobougou 004003001 Bla Central 004003002 Yangasso 004003003 Touna 004003004 Falo 004003005 Diaramana 004004001 Sarro 004004002 Kologotomo 004004003 Saye 004004004 Macina Central 004004005 Monipe 004005001 Niono Central, Pogo 004005002 Sokolo, Nampala 004006001 San 004006002 San Central 004006003 Diéli 004006004 Sy 004006005 Kimparana 004006006 Kassorola 004006007 Tene 004006008 Sourountouna 004007001 Mandiakuy 004007002 Tominian Central 004007003 Fangasso 004007004 Koula 004007005 Timissa 004007006 Mafoune 005001001 Mopti 005001002 Konna, Sendegue 005001003 Ouromodi, Soye 005001004 Dialloubé 005001005 Mopti central 005001006 Fatoma 005001007 Korientzé 005001008 Soufouroulaye 005002001 Bandiagara Central 005002002 Ningari 005002003 Kendie 005002004 Ouo 005002005 Goundaka 005002006 Sangha 005002007 Kani-gogouna 005002008 Dourou 005003001 Dialassagou 005003002 Sokoura 005003003 Baye 005003004 Bankass Central 005003005 Kani-bonzon 005003006 Ségué 005003007 Ouenkoro 005004001 Djenné Central, Taga 005004002 Mougnan, Konio 005004003 Sofara 005004004 Kouakourou 005005001 Douentza Central 005005002 Boni, Hombori 005005003 N'gouma 005005004 Mondoro 005005005 Boré 005006001 Koro Central 005006002 Koporo Kénièna 005006003 Dinangourou 005006004 Madougou 005006005 Diankabou 005006006 Toroli 005006007 Dioungani 005007001 Diafarabe, Ténenkou Central 005007002 Sossobé, Toguerécoumbé 005007003 Diondiori 005007004 Dioura 005008001 Guidio, Gathi loumo, Dogo 005008002 Youwarou Central 005008003 Sah 005008004 Ambiri 006001001 Commune Tombouctou 006001002 Tombouctou Central, Tinaguelhoy, Ber 006001003 Aglal, Bourem Inaly 006002001 Diré central, Danga, Haïbongo 006002002 Sareymou 006003001 Douekise, Goundam Central 006003002 Tonka 006003003 Raz-el-ma, Farach, Bintagoundou 006003004 Gargando, Tilemsi 006004001 Haribomo, Bambara Maoude, Mandiakoye 006004002 Gourma-Rharous Central 006004003 Ouinarden, Gossi, Inadiatafane 006005001 Sarafere, Koumaira 006005002 Léré, Soumpi 006005003 Niafunké Central 006005004 Banikané 006005005 N'gorkou 007001001 Gao central 007001002 Gao 007001003 Djébock, Haoussa Foulane, In-tillit 007002001 Talataye, Ansongo Central 007002002 Tessit, Ouatagouna 007003001 Bourem Central 007003002 Almoustarat, Temera 007003003 Bamba 007004001 Waritoufoulout ou Inekar, Tindarmene, Ménaka Central, Anderaboukane 008001001 Abéïbara Central, Tessalit Central, Tin-essako Central, Aguel-hoc, Timetrine, Tin-zaouatene, Bouressa, Abiyou, Essouk, Tinesserine 008001002 Kidal Central, Annefis, Kidal 009001001 Commune VI 009001002 Commune I 009001003 Commune V 009001004 Commune IV 009001005 Commune II 009001006 Commune III Geography: F-N Variables -- HOUSEHOLD DHS-IPUMS-I Mali regions, 1987-2012 [consistent boundaries, GIS] DHS_IPUMSI_ML provides geographic codes for Mali 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_ML indicate the major administrative unit in which the household was enumerated or surveyed. GIS shapefiles for Mali can be downloaded here. 01 Kayes 02 Koulikoro 03 Sikasso 04 Ségou 05 Mopti 06 Tombouctou 07 Gao and Kidal 09 Bamako 99 Unknown 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 Cooking fuel FUELCOOK indicates the predominant type of fuel or energy used for cooking. 00 NIU (not in universe) 10 None 20 Electricity 30 Petroleum gas, unspecified 31 Gas -- piped/utility 32 Gas -- tanked or bottled 33 Propane 34 Liquefied petroleum gas 35 Gas -- piped and bottled 40 Petroleum liquid 41 Oil, kerosene, and other liquid fuels 42 Kerosene/paraffin 43 Kerosene or oil 44 Kerosene or gasoline 45 Gasoline 46 Cocinol 47 Diesel 50 Wood, coal, and other solid fuels 51 Wood and other plant fuels 52 Non-wood plant materials 53 Coal or charcoal 54 Charcoal 55 Coal 56 Wood or charcoal 60 Multiple fuels 61 Bottled gas and wood 62 Propane and electricity 63 Propane, kerosene, and electricity 64 Propane and kerosene 65 Kerosene and electrictiy 66 Other combinations 70 Other 71 Alcohol 72 Biogas 73 Discarded or waste material 74 Dung/manure 75 Other combined organic waste materials 76 Solar energy 77 Candle 99 Unknown/missing Utilities Variables -- HOUSEHOLD 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 Mali 1998: All households This variable indicates the dwelling number. This is a 7-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Number of persons in household Mali 1998: All households This variable indicates the number of persons in the household. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 34 34 36 36 37 37 38 38 40 40 41 41 42 42 43 43 46 46 47 47 48 48 49 49 51 51 52 52 54 54 55 55 58 58 59 59 68 68 69 69 70 70 84 84 33 33 35 35 39 39 44 44 45 45 50 50 53 53 56 56 57 57 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 94 94 95 95 96 96 97 97 98 98 99 99 Technical Household Variables -- HOUSEHOLD Donated dwelling Mali 1998: All households This variable indicates the donated dwelling. 0 No problem 1 Donated Technical Household Variables -- HOUSEHOLD Donation strata: strata number Mali 1998: All households This variable indicates the donation strata: strata number. 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 Technical Household Variables -- HOUSEHOLD Hamlet or gathering point <svar v="ML98A029 ML98A030 ML98A031 ML98A035 ML98A038 ML98A039 ML98A040 ML98A050 ML98A051 ML98A052 ML98A053 ML98A054 ML98A055 ML98A056"><span class="em">Section A: Geographic characteristics</span><br /></svar></p> <p><svar v="ML98A039" a="all">6. Hamlet or gathering point [<span class="lang">point de regroupement</span>] (for rural areas and nomadic areas)<br /><div class="i1">[] 0 No<br />[] 1 Yes</div><br /></svar> <svar v="ML98A029 ML98A030 ML98A039 ML98A041" a="all"><span class="em">1.1. First Section -- Geographical Characteristics</span><br /><br />This section contains the geographical information identifying the household. The census enumerator must follow the following guidelines for filling the form.<br /><br />Do not write anything in the boxes located right to the geographical information. They are reserved for the coding. Use capital letters to fill in the left hand side.<br /><br />Example:<br /><div class="i1">Region: Mopti.<br />Province: Djenne 1 1<br />District: Djenne<br />Township: Taga<br />Village: Konda<br />Hamlet:<br />Neighborhood (for townships only):<br />Census district: 2<br />Census track: 010<br />Compound: 027<br />Household: 06</div><br /></svar> Mali 1998: All households This variable indicates whether the household is located in a hamlet or gathering point. 0 No 1 Yes 9 Unknown Geography: F-N Variables -- HOUSEHOLD Urban <svar v="ML98A029 ML98A030 ML98A039 ML98A041" a="all"><span class="em">1.1. First Section -- Geographical Characteristics</span><br /><br />This section contains the geographical information identifying the household. The census enumerator must follow the following guidelines for filling the form.<br /><br />Do not write anything in the boxes located right to the geographical information. They are reserved for the coding. Use capital letters to fill in the left hand side.<br /><br />Example:<br /><div class="i1">Region: Mopti.<br />Province: Djenne 1 1<br />District: Djenne<br />Township: Taga<br />Village: Konda<br />Hamlet:<br />Neighborhood (for townships only):<br />Census district: 2<br />Census track: 010<br />Compound: 027<br />Household: 06</div><br /></svar> Mali 1998: All households This variable indicates whether the dwelling is in an urban or rural area. 1 Urban 2 Rural Geography: F-N Variables -- HOUSEHOLD Residents present, male <svar v="ML98A051 ML98A052"><span class="em">RP: Resident, Present </span><br /></svar> <br /><svar v="ML98A051" a="all">RP: Males<br /><div class="i1">_ _</div><br /></svar> Mali 1998: All households This variable indicates the total male residents present in the dwelling. 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+ Other Household Variables -- HOUSEHOLD Residents present, female <svar v="ML98A051 ML98A052"><span class="em">RP: Resident, Present </span><br /></svar> <br /><svar v="ML98A051" a="all">RP: Males<br /><div class="i1">_ _</div><br /></svar></p> <p><svar v="ML98A052" a="all">RP: Females<br /><div class="i1">_ _</div><br /></svar> Mali 1998: All households This variable indicates the total female residents present in the dwelling. 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+ Other Household Variables -- HOUSEHOLD Residents absent, male <svar v="ML98A053 ML98A054"><span class="em">RA: Resident, Absent </span><br /></svar></p> <p><svar v="ML98A053" a="all">RA: Males<br /><div class="i1">_ _</div><br /></svar> Mali 1998: All households This variable indicates the total male residents absent from the dwelling. 0 0 1 1 2 2 3 3 4 4 5 5+ Other Household Variables -- HOUSEHOLD Residents absent, female <svar v="ML98A053 ML98A054"><span class="em">RA: Resident, Absent </span><br /></svar></p> <p><svar v="ML98A054" a="all">RA: Females<br /><div class="i1">_ _</div><br /></svar> Mali 1998: All households This variable indicates the total female residents absent from the dwelling. 0 0 1 1 2 2 3 3 4 4 5 5+ Other Household Variables -- HOUSEHOLD Visitors, male <svar v="ML98A055 ML98A056"><span class="em">V: Visitor</span><br /></svar></p> <p><svar v="ML98A055" a="all">V: Males<br /><div class="i1">_ _</div><br /></svar> Mali 1998: All households This variable indicates the total male visitors in the dwelling. 0 0 1 1 2 2 3 3 4 4 5 5 6 6+ Other Household Variables -- HOUSEHOLD Visitors, female <svar v="ML98A055 ML98A056"><span class="em">V: Visitor</span><br /></svar></p> <p><svar v="ML98A056" a="all">V: Females<br /><div class="i1">_ _</div><br /></svar> Mali 1998: All households This variable indicates the total female visitors in the dwelling. 0 0 1 1 2 2 3 3 4 4 5 5 6 6+ Other Household Variables -- HOUSEHOLD Type of household <svar v="ML98A057" a="all">[] 1 Sedentary household<br />[] 2 Nomadic household<br /></svar> <svar v="ML98A057" a="all"><span class="em">Types of households</span><br /><br />Sedentary or Nomadic Households: When the household is sedentary, write code 1 in the right hand side bow, and when the household is nomadic write code 2 in the box.<br /><br /><div class="i1">[] 1 Sedentary<br />[] 2 Nomadic</div><br /></svar></p> <p><span class="em">1.4.4. Filling the questions on housing </span></p> <p>After this introduction, we shall now come to the filling of the housing questionnaire per se.</p> <p>These questions are also to be asked to the household head. However, if the latter is not available, any person usually belonging to the household may answer the questions. For this housing questionnaire, no priority is given to the questions on housing units or on households. All questions deal with the dwelling units in the same way. In all events, the answers to the questions will be given by the person who is closest in rank to the household head.</p> <p>However, the census enumerator shall strictly follow the order in which the questions are displayed, so that to not miss any of them.</p> <p>Circle the number corresponding to the answer, when applicable.</p> <p>In the case of a compound occupied by a single household, consider the characteristics of the main hut, without taking into account the number of rooms.</p> <p>N.B: One shall never circle more than one number for a given question. Mali 1998: All households This variable indicates whether the dwelling is a sedentary, nomadic or collective. 1 Sedentary 2 Nomadic 3 Collective (institution) 9 Unknown Group Quarters Variables -- HOUSEHOLD Type of dwelling unit <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A058" a="all">1. Type of dwelling unit<br /><div class="i1">[] Fixed (sedentary)<br />[] Mobile (nomadic)</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A058" a="all">1. Column H15: Type of housing unit<br /><br />This information deals with the type of dwelling unit occupied by the household. At this level, one shall determine whether the dwelling unit concerned is a fixed housing or a mobile home.<br /><br />Depending on the case, circle (1) for fixed housing and (2) for mobile home. This question shall be documented, in principle, for all households.<br /><br />N.B.: The institutional households are not concerned by this question. However, the private households lodged in houses located in the same yard as an institutional household shall be identified and enumerated on the private household enumeration forms.<br /></svar> Mali 1998: All households This variable indicates whether it is a fixed or mobile dwelling. 1 Fixed 2 Mobile 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Type of building <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A059" a="all">2. Type of housing<br /><div class="i1">[] Isolated building<br />[] Compound, with several dwelling units<br />[] Modern house<br />[] Apartment building<br />[] Other type</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A059" a="all">2. Column H16: Type of building<br /><br />This is the structure that shelters the dwelling unit of a household. This can be deduced from direct observation while visiting the household.<br /><br />In general, this structure will be a compound; however, the structure may also be an apartment building, a detached house, or another type. Circle the number corresponding to the result of your observation.<br /><div class="i1">[] 1 Isolated building<br />[] 2 Compound with several buildings<br />[] 3 Modern villa, detached house<br />[] 4 Apartment building<br />[] 5 Other type</div><br /></svar> Mali 1998: All households This variable indicates the type of building (isolated, compound, apartment, etc.). 1 Isolated building 2 Compound, with several dwelling units 3 Modern house (villa) 4 Apartment building 5 Others 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Wall materials <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A060" a="all">5. Wall materials<br /><div class="i1">[] Hard<br />[] Semi-hard<br />[] Adobe<br />[] Wood or straw<br />[] Other</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A060" a="all">3. Column H17: Main wall materials<br /><br />The aim is to describe the materials utilized for the external wall of the dwelling unit. If the dwelling unit itself is composed of several buildings, then a question is about the choice of the building to describe.<br /><br />Two cases do exist:<br /><div class="i1">a. The dwelling unit for the household has only one building; therefore this is this building that shall be described<br />b. The dwelling unit for the household is made of several independent buildings. In this case, choose the building that you will consider the main building, while referring for instance to a durability criteria. However, this building shall be used as a housing unit to be chosen. Once the building has been chosen, try to determine the materials of which the external walls are made, while asking the household head.</div><br /><br />Possible cases selected are:<br /><div class="i1">[] 1 Hard wall<br />[] 2 Semi-hard wall<br />[] 3 Mud brick (adobe)<br />[] 4 Wood or straw<br />[] 5 Other material</div><br /><br /><span class="pg">[Page 41]</span><br /><br />The definitions are the following:<br /><div class="i1">Hard wall: Walls are said to be "hard" when they are made of bricks, stone, or cement, or even when they are made of concrete (a mix of cement, gravel or stone), and covered or not with cement.<br /><br />Semi-hard wall: Walls are said to be "semi-hard" when they are made of mud bricks, covered with cement.<br /><br />Mud brick (adobe or banco): Walls are said to be "adobe" when they are made of mud bricks, covered or not by a mud coating.<br /><br />Wood or straw: Walls are made of straw, wood, bamboo, palm leaves, herb sticks plait, etc..., covered or not by a mud coating or by cement.<br /><br />Other materials: The walls do not fit in any of the above categories.</div><br /><br />Ask the following question to the household head: "What are the materials used for the construction of the walls?"<br /><br />Refer to the above definitions, and circle the number corresponding to the given answer.<br /><br />Example 1. The household head says that the building was made of a mix of cement and gravel. The walls are covered with cement, and whitewashed. COLUMN H17 is therefore filled in by circling number (1): Hard walls<br /><br />Example 2: The building to be described is a tent. One must then circle number (5): Other material.<br /><br />Example 3: The building to be described is made of mud bricks, covered with a mud coating.<br />Here, one shall circle number (3): Adobe<br />N.B: Institutional households are also concerned with the question on wall material. However, the dwelling units of the private households located within the same yard as these institutions shall be considered separately, on a private household census form.<br /></svar> Mali 1998: All households This variable indicates the type of material used for the wall of the household. 1 Hard 2 Semi-hard 3 Adobe 4 Wood or straw 5 Others 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Roof materials <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A061" a="all">6. Roof material<br /><div class="i1">[] Corrugated iron<br />[] Tiles<br />[] Concrete<br />[] Adobe<br />[] Straw<br />[] Other type</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A061" a="all">4. Column H18: Main roof materials<br /><br />Likewise, one shall describe the material used for the roof of the chosen building. Possible cases selected are: iron sheets, tiles, concrete, adobe, straw, other. The terms "concrete", "adobe" have already been defined above. For "iron sheets" and "tiles", count only in these categories the houses of acceptable quality. Informal shelters, covered or not with iron sheets, shall be classified in the "Other material" category.<br /><br />Circle the number corresponding to the answer, while referring to the above definitions, such as:<br /><div class="i1">Thatched roof: A thatched roof is a roof made of straw, bamboo, palm leaves or any other vegetative material. Generally, this is the most common cover for traditional round huts.<br /><br />Other materials: Roof that does not present any other characteristics: iron sheets, tiles, concrete, adobe, thatch.</div><br /><br /><span class="pg">[Page 42]</span><br /><br />Codes selected for the various items are the following:<br /><div class="i1">[] 1 Iron sheet<br />[] 2 Tiles<br />[] 3 Concrete<br />[] 4 Adobe<br />[] 5 Thatch<br />[] 6 Other material<br /><br />Example 1: The building to be described is an apartment building, with several floors, and the roof is made of concrete. Then, one must circle the number (3): Concrete.<br /><br />Example 2: The building is made of concrete, and the roof is built in wood, covered with a layer of adobe. Here, one circles the number (4): Adobe.</div><br /><br />The institutional households are also concerned with this question.<br /></svar> Mali 1998: All households This variable indicates the type of materials used for the roof of the household. 1 Iron sheet 2 Tile 3 Concrete 4 Adobe 5 Straw 6 Others 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Floor materials <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A062" a="all">7. Floor material<br /><div class="i1">[] Cement<br />[] Tiles<br />[] Earth<br />[] Other type</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A062" a="all">5. Column H19: Main floor materials<br /><br />In this section, one has to describe the floor of the selected building. The possible cases selected are:<br /><div class="i1">[] 1 Cement<br />[] 2 Tiles<br />[] 3 Earth<br />[] 4 Other material</div><br /><br />One will consider as "Cement" or "Tiles" all floors in hard material: cement, concrete, floor tiles, stone, etc.<br /><br />Always observe by yourself the floor of the building, otherwise ask the question to the household head: "What are the floor materials?" Then circle the answer corresponding to the designated case.<br /><br />Example 1: The building to be described is a round hut, of which the floor is nevertheless made of cement. Then one must circle number (1): Cement.<br /><br />Example 2: The building to be described is a tent, a boat, a pirogue, etc. In this case, the number (4) "Other material" must be circled.<br /><br />This question also applies to institutional households. The private households who are housed in the same yard as an institutional household are to be considered separately.<br /></svar> Mali 1998: All households This variable indicates the materials used for the floor of the household. 1 Cement 2 Tiles 3 Earth 4 Others 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Type of lighting <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A063" a="all">10. Type of lighting<br /><div class="i1">[] Electricity<br />[] Gas<br />[] Petrol lamp<br />[] Other type</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A063" a="all">6. Column H20: Main mode of lighting<br /><br />This question indicates what type of energy utilized for lighting the household (electricity, gas, petrol lamp, others).<br /><div class="i1">Electricity: The household has a permanent installation for lighting, of which the wires are connected to a source of electricity distribution (Energie du Mali, power plant, mines, etc.) or on a private source, such as a battery.<br /><br />Gas: This type of lighting is an installation fuelled by natural gas.<br /><br />Petrol lamp: The household uses petrol lamps.<br /><br />Others: oil lamps, wood fire, other, none.</div><br /><br />The question to be asked to gather the type of lighting used by the household will be: "What type of lighting?"<br /><br />Depending on the answer, refer to the above definition, then circle the number of the relevant case corresponding to the type used. Codes to be circled are:<br /><div class="i1">[] 1 Electricity<br />[] 2 Gas<br />[] 3 Petrol lamp<br />[] 4 Others</div><br /></svar> Mali 1998: All households This variable indicates the type of lighting used in the dwelling. 1 Electricity 2 Gas lamp 3 Petrol lamp 4 Others 9 Unknown Utilities Variables -- HOUSEHOLD Main source of water <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A064" a="all">8. Source of water<br /><div class="i1">[] Public tap<br />[] Deep well<br />[] Shallow well<br />[] Public fountain<br />[] River, stream, spring<br />[] Other type</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A064" a="all">7. Column H21: Main source of water<br /><br />This question is to be asked to every household.<br /><br />This type might be a public system of water supply (public tap, public well, tank, public fountain), or a private source, such as a well, or a natural source (small or large river, spring, etc...).<br /><br />The source of water is determined by the coverage of the essential needs in water, for cooking, for laundry, and not only for bathing.<br /><br />Circle the number corresponding to the case.<br /><div class="i1">[] 1 Public tap<br />[] 2 Deep well<br />[] 3 Shallow well<br />[] 4 Public fountain<br />[] 5 Surface water<br />[] 6 Others</div><br /><br />The question to be asked to the household head will be: "What is the main source of water for drinking?"<br /><br />Example 1. The household gets its water from a public well, of the operation "Well with a pump". Then, one shall circle number (3): Shallow well<br /><br />Example 2. The household gets its water from a public tap in the street. Then, shall circle number (1): Public tap<br /></svar> Mali 1998: All households This variable indicates the main source of water for drinking for the household. 1 Tap 2 Deep well 3 Shallow well 4 Public tap 5 Surface water 6 Others 9 Unknown Utilities Variables -- HOUSEHOLD Main fuel for cooking <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A065" a="all">11. Type of fuel for cooking<br /><div class="i1">[] Electricity<br />[] Gas<br />[] Petrol<br />[] Wood, Coal<br />[] Other type</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A065" a="all">8. Column H22: Main fuel for cooking<br /><br />This is the fuel used for cooking and for heating the household. Possible cases selected are:<br /><div class="i1">[] 1 Electricity<br />[] 2 Gas<br />[] 3 Petrol<br />[] 4 Wood, charcoal<br />[] 5 Others</div><br /></svar> Mali 1998: All households This variable indicates the main fuel used for cooking for the household. 1 Electricity 2 Gas 3 Petrol 4 Wood or charcoal 5 Others 9 Unknown Utilities Variables -- HOUSEHOLD Type of toilet <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A066" a="all">9. Type of toilet facility<br /><div class="i1">[] Private flush toilet, internal<br />[] Private flush toilet, external<br />[] Flush toilet, communal<br />[] Pit latrine, private<br />[] Pit latrine, communal<br />[] Other type</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A066" a="all">9. Column H23: Type of toilet facility<br /><br />This Column helps to indicate whether the household has a toilet facility or not. For the institutional household (see concepts), indicate the number of toilets.<br /><br />Definition: A "toilet facility", also called Water Closet (WC), is a specific installation made to evacuate waste or human feces. It can be a flushing toilet or a latrine:<br /><br /><div class="i1">a. flushing toilet: a flushing toilet, or a modern water closet (WC), is an installation connected to a water source through a pipe, and through which the human feces are evacuated.</div><br /><br /><span class="pg">[Page 44]</span><br /><br /><div class="i1">b. latrine: this is the most common type of toilet facility. It presents itself as a hole, the walls of which being cemented or not, and located in a small separate building in a corner of the compound. It may also be used, in addition, for the bathing of household members.</div><br /><br />The 1998 census has selected the following items for the type of toilet facility:<br /><div class="i1">[] 1 Private flushing toilet, located inside<br />[] 2 Private flushing toilet, located outside<br />[] 3 Flushing toilet, common to several households<br />[] 4 Private latrine<br />[] 5 Latrine, common to several households<br />[] 6 Others</div><br /><br />Refer to the above definitions to ask the household head [C.M.] the following question: "Does the household have a toilet facility?" Depending on the answer, circle the corresponding number.<br /><br />Example 1: The household uses, as toilet facility, a pit latrine located in a corner of the compound. It is a simple cemented hole, fenced with a wall. In this example, circle the number (5): Latrine, common to several households<br /></svar> Mali 1998: All households This variable indicates whether the dwelling has a toilet. 1 Private flush toilet, inside house 2 Private flush toilet, outside house 3 Common flush toilet 4 Private cesspool 5 Common cesspool 6 Others 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Ownership status <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A067" a="all">4. Type of occupation<br /><div class="i1">[] Landlord, with official documentation<br />[] Landlord, without official documentation<br />[] Co-owner<br />[] Tenant<br />[] Leasing<br />[] Free lodger<br />[] Other type</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A067" a="all">10. Column H24: Type of occupancy<br /><br />One shall determine in what capacity the household head occupies the dwelling unit. Possible cases are:<br /><div class="i1">[] 1 Landlord, with a deed<br />[] 2 Landlord, without a deed<br />[] 3 Condominium (shared property)<br />[] 4 Tenant (Renting)<br />[] 5 Leasing<br />[] 6 Free lodging<br />[] 7 Others</div><br /><br />The main following definitions may be useful to you:<br /><br /><div class="i1">a. Landlord: this is the person who owns the dwelling unit concerned. He or she is the legal owner of the real estate, and may, as a consequence, rent or sell the whole or parts of the dwelling unit.<br /><br />b. Tenant: This is a person who occupies a dwelling unit while paying periodically (per week, per month, etc...) a given amount of money, called the rent.<br /><br />c. Others: This category includes the persons housed for free, the households who occupy the dwelling unit of an absentee landlord without paying a rent, or without the authorization of the latter, as well as the other cases not defined in the above categories.</div><br /><br />Refer to these definitions, and go ask to the household head the following question: "In which title does the household occupy the dwelling unit?" Circle the number corresponding to the typical case.<br /><br />Example 1: A household rents in a compound a 3-rooms dwelling unit. Then Column H24 will be filled as (4): Tenant<br /></svar> Mali 1998: All households This variable indicates the ownership status of the dwelling unit. 1 Landlord, with official document 2 Landlord, without official document 3 Co-owner 4 Tenant 5 Leasing 6 Free lodging 7 Others 9 Unknown Household Economic Variables -- HOUSEHOLD Number of rooms occupied <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A068" a="all">3. Number of rooms occupied<br /><div class="i1">_ _</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A068" a="all">11. Column H25: Number of rooms occupied<br /><br />This means the total number of rooms occupied by the household.<br /><br />A room is defined as a housing space, enclosed with walls, from floor to ceiling, large enough to contain one "adult bed", and with the purpose of being used as a dwelling unit. Are counted as separate rooms:<br /><div class="i1">- Sleeping rooms<br />- Eating rooms and living rooms<br />- Rooms for servants<br />- Rooms used for traders,<br />- Any other area used as a dwelling, and corresponding to the definition of a room.</div><br /><br />On the opposite, the verandahs, the corridors, the halls, the vestibules, the kitchen, the toilets (WC), the granaries and other storage rooms, etc. will be excluded.<br /><br />However, when kitchens and halls are usually used for housing, they should be counted. Given these guidelines, count the total number of rooms occupied by the household, and write it in the box prepared for it in Column H25.<br /><br />Example 1: The dwelling unit for the household has 8 rooms inhabited, plus two granaries and a kitchen (which will not be counted in the computation of the total number of rooms).<br /><br />N.B.: In nomadic areas, consider each tent as a room, and provide the total number of occupied rooms.<br /></svar> Mali 1998: All households This variable indicates the number of rooms occupied by the household. A room is defined as a housing space, enclosed with walls, from floor to ceiling, large enough to contain one "adult bed", and with the purpose of being used as a dwelling unit. Kitchen and halls are not counted as 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+ 99 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Improved fireplace <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069"><span class="em">Section "D": Housing</span><br /></svar></p> <p><svar v="ML98A069" a="all">12. Improved stove<br /><div class="i1">[] Yes<br />[] No</div><br /></svar> <svar v="ML98A058 ML98A059 ML98A060 ML98A061 ML98A062 ML98A063 ML98A064 ML98A065 ML98A066 ML98A067 ML98A068 ML98A069" a="all"><span class="em">1.4. Housing </span><br /><br />This second part is devoted to housing, and aims at listing all housing units for the households at time of the census, at gathering information on building characteristics, and to obtain indicators on the conditions in which the population is housed.<br /></svar></p> <p><svar v="ML98A069" a="all">12. Column H26: Existence of an improved fireplace<br /><br />Ask the question to the household head, about the possible existence of an improved fire place. Circle 1 for "Yes" if it exists, 2 for "No" otherwise.<br /></svar> Mali 1998: All households This variable indicates whether the dwelling has an improved fire place. 1 Yes 2 No 9 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Number of mortality records <svar v="ML98A071" a="all"><span class="em">Deaths in past 12 months</span><br />Sequential number<br /><div class="i1">_ _</div><br /><br />First name and last name ____<br /><br />Sex<br /><div class="i1">[] 1 Male<br />[] 2 Female</div><br /><br />Age at death<br /><div class="i1">_ _</div><br /></svar> <span class="em">1.3. Event of the past 12 months -- Births and Deaths</span></p> <p>This section is devoted to the [demographic] events that occurred in the past 12 months. That is, the births and the deaths that occurred in this household during the 12 months prior to the visit of the census enumerator.</p> <p>These events must be registered faithfully, and with great accuracy, in order to avoid omissions that could affect the quality of the data. In addition, the accuracy of the results that will be obtained will be a function of the rigorous consideration of the recall period of 12 months, taken as the reference period. The census enumerator date of visit in the household is the milestone for determining this period.</p> <p>For instance, if the date of visit of the census enumerator in the household is April 6, 1998, only the events between April 6, 1997 and this date shall be registered. A birth or a death that occurred prior to April 6, 1997 will not be registered.</p> <p>One could use as a landmark the month of the previous Muslim festival [Tabaski], which occurred on April 18, 1997, or the date of the first round of parliament elections of April 13, 1997, which has been cancelled, to specify the previous 12 months period.</p> <p>A seasonal calendar was elaborated (see Annex), to help the illiterate persons to better define this 12 months period prior to the census date. This seasonal calendar provides correspondences between the dates on the Gregorian calendar and the Muslim calendar with the lunar months translated into Bambara.</p> <p><svar v="ML98A071" a="all"><span class="em">1.3.2. Deaths during the past 12 months</span><br /><br />This summary table deals with all deaths that occurred in the household during the past 12 months (children, adults, elderly persons).<br /><br />The deaths will be also registered according to the general principle mentioned above.<br /><br />The census enumerator will proceed as follows:<br /><br />- Write down on a spare sheet your date of visit in the household. Example: April 6, 1998.<br /><br />Then ask to the household head: "Has there been any death in this household over the past 12 months, that is, since April 6, 1997?"<br /><br />For an illiterate household head, this will be the lunar month in the Muslim calendar corresponding to April 1997 (see Annex).<br /><br />Circle the number corresponding to the answer given, in the following way:<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /><br />a. If the answer to the question asked is "no", circle number 2, and cross-out the summary table of the deaths in the last 12 months.<br /><br />b. If the answer to the question is "yes", circle number 1, and fill in the summary table on deaths that occurred during the past 12 months.<br /><br />However, before filling in this table, check one more time that the death well occurred during the reference period, that is during the 12 months prior to your visit in the household.<br /><br />Filling in the summary table is done Column by Column.<br /></svar> Mali 1998: All households This variable indicates the number of mortality records. 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 Constructed Household Variables -- HOUSEHOLD Strata Mali 1998: All households This variable is the strata identifier for the sample. Strata is a constructed variable that captures implicit geographic stratification resulting from the sample design. It is created by assigning a unique identifier to groups of between 10 and 19 adjacent households. Additional documentation is available on the Variance Estimation page. This is a 5-digit numeric variable with 0 implied decimal places Geography: F-N Variables -- HOUSEHOLD Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. Technical Person Variables -- PERSON Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Person Variables -- PERSON 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 Children ever born CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children surviving CHSURV reports the number of children born to a woman who were still living at the time of the census. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Mortality status of mother MORTMOT indicates whether the person's biological mother was still living at the time of the census. 1 Alive 2 Dead 7 Does not know 8 Missing 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Mortality status of father MORTFAT indicates whether the person's biological father was still living. 1 Alive 2 Dead 7 Does not know 8 Missing 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Nativity status NATIVITY indicates whether the person was native-born or foreign-born. 0 NIU (not in universe) 1 Native-born 2 Foreign-born 9 Unknown/missing Nativity and Birthplace Variables -- PERSON 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 Circle of birth, Mali BPLML indicates the person's circle of birth within Mali. 010 Kayes region, unknown circle 011 Kayes 012 Bafoulabé 013 Diéma 014 Kéniéba 015 Kita 016 Nioro 017 Yélimané 020 Koulikoro region, unknown circle 021 Koulikoro 022 Banamba 023 Dioila 024 Kangaba 025 Kati 026 Kolokani 027 Nara 030 Sikasso region, unknown circle 031 Sikasso 032 Bougouni 033 Kadiolo 034 Kolondiéba 035 Koutiala 036 Yanfolila 037 Yorosso 040 Ségou region, unknown circle 041 Ségou 042 Baraouéli 043 Bla 044 Macina 045 Niono 046 San 047 Tominian 050 Mopti region, unknown circle 051 Mopti 052 Bandiagara 053 Bankass 054 Djénné 055 Douentza 056 Koro 057 Ténenkou 058 Youvarou 060 Tombouctou region, unknown circle 061 Tombouctou 062 Diré 063 Goundam 064 Gourma Rharous 065 Niafunké 070 Gao region, unknown circle 071 Gao 072 Ansongo 073 Bourem 074 Ménaka 080 Kidal region, unknown circle 081 Kidal 082 Abéibara 083 Téssalit 084 Tin Essako 090 District of Bamako, unknown commune 091 Commune I of the District of Bamako 092 Commune II of the District of Bamako 093 Commune III of the District of Bamako 094 Commune IV of the District of Bamako 095 Commune V of the District of Bamako 096 Commune VI of the District of Bamako 097 District Bamako 098 Mali, province unspecified 099 Foreign country 998 Unknown Nativity and Birthplace Variables -- PERSON Language spoken at home, Mali LANGML indicates the language spoken in everyday life by the person in Mali. 00 NIU (not in universe) 01 Bambara, Malinke 02 Peul, Foulfoube 03 Sonrhaï, Djerma 04 Maraka, Soninke 05 Kassonke 06 Senoufo 07 Dogon 08 Mauritanian 09 Tamacheq 10 Bobo Dafing 11 Minianka 12 Haoussa 13 Samogo 14 Bozo 15 Other Malian language 16 Arabic 17 Other African language 18 Other foreign language 19 French 20 English 99 Unknown Ethnicity and Language Variables -- PERSON Maternal language, Mali MTONGML indicates the person's mother tongue: the language spoken in the respondent's infancy or by their mother. 00 NIU (not in universe) 01 Bambara, Malinké, Dioula 02 Pulaar, Peulh, Foulfoulbé 03 Songhai, Djerma 04 Marka, Soninké 05 Kassongé 06 Senoufo 07 Dogon, Kado 08 Mauritanian, Maure 09 Tamasheq, Bellah 10 Bobo, Dafing 11 Minianka 12 Haussa 13 Samogo 14 Bozo, Somono 15 Other language from Mali 16 Arabic 17 Other African language 18 French 19 English 20 Other non-African language 99 Unknown Ethnicity and Language Variables -- PERSON School attendance SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census. 0 NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing Education Variables -- PERSON Literacy LIT indicates whether or not the respondent could read and write in any language. A person is typically considered literate if he or she can both read and write. All other persons are illiterate, including those who can either read or write but cannot do both. 0 NIU (not in universe) 1 No, illiterate 2 Yes, literate 9 Unknown/missing Education Variables -- PERSON Educational attainment, international recode [general version] EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. 0 NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown Education Variables -- PERSON Educational attainment, international recode [detailed version] EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. 000 NIU (not in universe) 100 Less than primary completed (n.s.) 110 No schooling 120 Some primary completed 130 Primary (4 yrs) completed 211 Primary (5 yrs) completed 212 Primary (6 yrs) completed 221 Lower secondary general completed 222 Lower secondary technical completed 311 Secondary, general track completed 312 Some college completed 320 Secondary or post-secondary technical completed 321 Secondary, technical track completed 322 Post-secondary technical education 400 University completed 999 Unknown/missing Education Variables -- PERSON Years of schooling YRSCHOOL indicates the highest grade/level of schooling the person had completed, in years. Only formal schooling is counted. YRSCHOOL accounts for the number of years of study, regardless of the track or kind of study. Information on degree and/or technical track is available in EDATTAIN. Years of schooling for Israel, categorized into intervals, are given in YRSCHOOL2. Users should pay close attention to the top-codes in each sample, as discussed in the comparability section. 00 None or pre-school 01 1 year 02 2 years 03 3 years 04 4 years 05 5 years 06 6 years 07 7 years 08 8 years 09 9 years 10 10 years 11 11 years 12 12 years 13 13 years 14 14 years 15 15 years 16 16 years 17 17 years 18 18 years or more 90 Not specified 91 Some primary 92 Some technical after primary 93 Some secondary 94 Some tertiary 95 Adult literacy 96 Special education 98 Unknown/missing 99 NIU (not in universe) Education Variables -- PERSON Educational attainment, Mali EDUCML indicates the person's educational attainment in Mali in terms of the level of schooling completed. 000 NIU (not in universe) 100 None 110 Literacy education 111 Literacy education, one round 112 Literacy education, two or more rounds 120 Preschool 121 Preschool, year 1 122 Preschool, year 2 123 Preschool, year 3 200 Fundamental school, first cycle 210 Fundamental, first cycle 211 Fundamental, first cycle, year 1 212 Fundamental, first cycle, year 2 213 Fundamental, first cycle, year 3 214 Fundamental, first cycle, year 4 215 Fundamental, first cycle, year 5 216 Fundamental, first cycle, year 6 217 Fundamental, first cycle, year unknown 220 Medersa, first cycle 221 Medersa, first cycle, year 1 222 Medersa, first cycle, year 2 223 Medersa, first cycle, year 3 224 Medersa, first cycle, year 4 225 Medersa, first cycle, year 5 226 Medersa, first cycle, year 6 227 Medersa, first cycle, year unknown 300 Fundamental school, second cycle 310 Fundamental, second cycle 311 Fundamental, second cycle, year 7 312 Fundamental, second cycle, year 8 313 Fundamental, second cycle, year 9 314 Fundamental, second cycle, year unknown 320 Medersa, second cycle 321 Medersa, second cycle, year 7 322 Medersa, second cycle, year 8 323 Medersa, second cycle, year 9 324 Medersa, second cycle, year unknown 400 Secondary school, general or technical 410 Secondary school, general 411 Secondary general, year 10 412 Secondary general, year 11 413 Secondary general, year 12 414 Secondary general, year unknown 420 Secondary school, technical 421 Secondary technical, year 10 422 Secondary technical, year 11 423 Secondary technical, year 12 424 Secondary technical, year unknown 500 Vocational school or teachers school 510 School for teachers 511 School for teachers, year 1 512 School for teachers, year 2 513 School for teachers, year 3 514 School for teachers, year 4 515 School for teachers, year 5 516 School for teachers, year unknown 520 Vocational school 521 Vocational, year 1 522 Vocational, year 2 523 Vocational, year 3 524 Vocational, year 4 525 Vocational, year unknown 530 Vocational school, entry requiring primary school certificate [CEP] 531 Vocational, entry level CEP, year 1 532 Vocational, entry level CEP, year 2 533 Vocational, entry level CEP, year 3 534 Vocational, entry level CEP, year 4 535 Vocational, entry level CEP, year unknown 540 Vocational school, entry requiring fundamental studies diploma [DEF] 541 Vocational, entry level DEF, year 1 542 Vocational, entry level DEF, year 2 543 Vocational, entry level DEF, year 3 544 Vocational, entry level DEF, year 4 545 Vocational, entry level DEF, year 5 546 Vocational, entry level DEF, year unknown 550 Vocational school, entry requiring baccalaureate [BAC] or more 551 Vocational, entrey level BAC, year 1 552 Vocational, entrey level BAC, year 2 553 Vocational, entrey level BAC, year 3 554 Vocational, entrey level BAC, year 4 555 Vocational, entrey level BAC, year 5 556 Vocational, entrey level BAC, year unknown 600 Higher education, university 610 University 611 University, year 1 612 University, year 2 613 University, year 3 614 University, year 4 615 University, year 5 616 University, year 6 617 University, year 7+ 618 University, year unknown 620 Post-university 621 Post-university, year 1 or 2 622 Post-university, year 3 623 Post-university, year 4 624 Post-university, year 5 625 Post-university, year 6 626 Post-university, year 7+ 627 Post-university, year unknown 700 Other 999 Unknown Education Variables -- PERSON Activity status (employment status) [general version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 0 NIU (not in universe) 1 Employed 2 Unemployed 3 Inactive 9 Unknown/missing Work Variables -- PERSON Activity status (employment status) [detailed version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 000 NIU (not in universe) 100 Employed, not specified 110 At work 111 At work, and 'student' 112 At work, and 'housework' 113 At work, and 'seeking work' 114 At work, and 'retired' 115 At work, and 'no work' 116 At work, and other situation 117 At work, family holding, not specified 118 At work, family holding, not agricultural 119 At work, family holding, agricultural 120 Have job, not at work in reference period 130 Armed forces 131 Armed forces, at work 132 Armed forces, not at work in reference period 133 Military trainee 140 Marginally employed 200 Unemployed, not specified 201 Unemployed 6 or more months 202 Worked fewer than 6 months, permanent job 203 Worked fewer than 6 months, temporary job 210 Unemployed, experienced worker 220 Unemployed, new worker 230 No work available 240 Inactive unemployed 300 Inactive (not in labor force) 301 Unavailable jobseekers 302 Available potential jobseekers 310 Housework 320 Health reasons, unable to work, or disabled 321 Permanent disability 322 Temporary illness 323 Disabled or imprisoned 330 In school 340 Retirees and living on rent 341 Living on rents 342 Living on rents or pension 343 Retirees/pensioners 344 Retired 345 Pensioner 346 Non-retirement pension 347 Disability pension 348 Retired without benefits 350 Elderly 351 Elderly or disabled 360 Institutionalized 361 Prisoner 370 Intermittent worker 371 Not working, seasonal worker 372 Not working, occasional worker 380 Other income recipient 390 Inactive, other reasons 391 Too young to work 392 Dependent 999 Unknown/missing Work Variables -- PERSON Labor force participation LABFORCE is a dichotomous variable identifying whether a person participated in the labor force. Labor force participation generally means working or seeking work within a specified reference period. For most samples LABFORCE is a recode of EMPSTAT (employment status). A consistent lower age universe of 15 or older has been applied to increase comparability across samples. Full detail is retained in EMPSTAT, which should be used for any study of child labor. 1 No, not in the labor force 2 Yes, in the labor force 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Occupation, ISCO general OCCISCO records the person's primary occupation, coded according to the major categories in the International Standard Classification of Occupations (ISCO) scheme for 1988. For someone with more than one job, the primary occupation is typically the one in which the person had spent the most time or earned the most money. 01 Legislators, senior officials and managers 02 Professionals 03 Technicians and associate professionals 04 Clerks 05 Service workers and shop and market sales 06 Skilled agricultural and fishery workers 07 Crafts and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 10 Armed forces 11 Other occupations, unspecified or n.e.c. 97 Response suppressed 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Occupation, unrecoded OCC records the person's primary occupation, classified according to the system used by the respective national census office at the time. For someone with more than one job, the primary occupation is usually the one in which the person spent the most time or earned the most money, although this may not have been explicit in the instructions for a specific census. To ensure confidentiality, very small occupations are recoded to a residual category indicating the persons had an occupation, but the job title is not identified. The number of cases recoded should be too small to affect analyses. OCC is a 4-digit numeric variable. Some samples use fewer than 4 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_OCC3 - Occupation [3 digit] Argentina 1980 - see Variable: AR1980A_OCC - Occupation Argentina 1991 - see Variable: AR1991A_OCC - Occupation Argentina 2001 - see Variable: AR2001A_OCC4 - Occupation (4-digits) Armenia 2011 - see Variable: AM2011A_OCC - Occupation Austria 1971 - see Variable: AT1971A_OCCSM - Occupation of supporter: sub-major groups Austria 1981 - see Variable: AT1981A_OCCSM - Occupation of supporter: sub-major groups Austria 1991 - see Variable: AT1991A_OCCSM - Occupation of supporter: sub-major groups Austria 2001 - see Variable: AT2001A_OCCSM - Occupation of supporter: sub-major groups Belarus 1999 - see Variable: BY1999A_OCC2 - Occupation, 2 digits Belarus 2009 - see Variable: BY2009A_OCC - Occupation Benin 1979 - see Variable: BJ1979A_OCC - Occupation (2-digits) Benin 1992 - see Variable: BJ1992A_OCC3 - Occupation (3-digits) Benin 2002 - see Variable: BJ2002A_OCC - Occupation (3-digits) Benin 2013 - see Variable: BJ2013A_OCC - Occupation (3-digit) Bolivia 1976 - see Variable: BO1976A_OCC2 - Occupation, 2 digits Bolivia 1992 - see Variable: BO1992A_OCC - Occupation Bolivia 2001 - see Variable: BO2001A_OCC - Occupation, 3 digits Bolivia 2012 - see Variable: BO2012A_OCC2 - Occupation (3 digit) Botswana 1981 - see Variable: BW1981A_OCC - Occupation Botswana 1991 - see Variable: BW1991A_OCC - Occupation (last 30 days) Botswana 2001 - see Variable: BW2001A_OCC - Occupation in the past 7 days, 3 digit Botswana 2011 - see Variable: BW2011A_OCC - Occupation, 3-digits Brazil 1960 - see Variable: BR1960A_USUALOCC - Usual occupation Brazil 1970 - see Variable: BR1970A_MAINOCC - Principal occupation Brazil 1980 - see Variable: BR1980A_OCC - Occupation Brazil 1991 - see Variable: BR1991A_OCC - Occupation Brazil 2000 - see Variable: BR2000A_OCC - Occupation, 4 digits Brazil 2010 - see Variable: BR2010A_OCC - Occupation held from July 25 to July 31, 2010 Burkina Faso 1985 - see Variable: BF1985A_OCC - Principal occupation Burkina Faso 1996 - see Variable: BF1996A_OCC - Principal occupation Cambodia 1998 - see Variable: KH1998A_OCC - Occupation Cambodia 2004 - see Variable: KH2004A_OCC3 - Occupation (3-digits) Cambodia 2008 - see Variable: KH2008A_OCC - Occupation Cambodia 2013 - see Variable: KH2013A_OCC - Occupation (3-digits) Cambodia 2019 - see Variable: KH2019A_OCC1 - Occupation, 1-digit Cameroon 1976 - see Variable: CM1976A_OCC2 - Occupation (2 digits) Cameroon 2005 - see Variable: CM2005A_OCC - Occupation Canada 1971 - see Variable: CA1971A_OCC - Occupation Canada 1981 - see Variable: CA1981A_OCC - Occupation (1981 classification basis) Canada 1991 - see Variable: CA1991A_OCC80 - Occupation (1980 classification basis) Canada 2001 - see Variable: CA2001A_NOCS01P - Occupation (2001 national occupational classification for statistics) Canada 2011 - see Variable: CA2011A_OCC - Occupation Chile 1960 - see Variable: CL1960A_OCC - Occupation Chile 1970 - see Variable: CL1970A_OCC3 - Occupation (3-digit) Chile 1982 - see Variable: CL1982A_OCC3 - Occupation (3-digit) Chile 1992 - see Variable: CL1992A_OCC3 - Occupation (3-digit) Chile 2002 - see Variable: CL2002A_OCC - Occupation China 1982 - see Variable: CN1982A_OCC - Occupation China 1990 - see Variable: CN1990A_OCC - Occupation China 2000 - see Variable: CN2000A_OCC - Occupation (2-digit) Colombia 1964 - see Variable: CO1964A_OCC2 - Occupation (COTA, 4 digits) Colombia 1973 - see Variable: CO1973A_OCC - Occupation last week Costa Rica 1973 - see Variable: CR1973A_OCC3 - Occupation, 3 digits Costa Rica 1984 - see Variable: CR1984A_OCC - Occupation, 3 digits Costa Rica 2000 - see Variable: CR2000A_OCC3 - Occupation, 3 digits Costa Rica 2011 - see Variable: CR2011A_OCC - Occupation, 2-digit Cuba 2002 - see Variable: CU2002A_OCC - Occupation Cuba 2012 - see Variable: CU2012A_OCC3 - Main occupation (3-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_OCC2 - Current occupation (2-digit) Dominican Republic 1960 - see Variable: DO1960A_OCC - Occupation Dominican Republic 1970 - see Variable: DO1970A_OCC1 - Current occupation, 3 digits Dominican Republic 1981 - see Variable: DO1981A_OCC - Occupation Dominican Republic 2002 - see Variable: DO2002A_OCC - Occupation Dominican Republic 2010 - see Variable: DO2010A_OCC - Occupation Ecuador 1962 - see Variable: EC1962A_OCC - Occupation Ecuador 1974 - see Variable: EC1974A_OCC3 - Occupation, three digits Ecuador 1982 - see Variable: EC1982A_OCC3 - Occupation, 3 digits Ecuador 1990 - see Variable: EC1990A_OCC3 - Occupation, 3 digits Ecuador 2001 - see Variable: EC2001A_OCC - Occupation, 3 digits Ecuador 2010 - see Variable: EC2010A_OCC3 - Occupation (3 digits, ISCO 08) Egypt 1986 - see Variable: EG1986A_OCC3 - Occupation (3-digit) Egypt 2006 - see Variable: EG2006A_OCC - Primary occupation, 3-digit El Salvador 1992 - see Variable: SV1992A_OCC - Occupation (3-digit) El Salvador 2007 - see Variable: SV2007A_OCC3DIG - Occupation (3-digit) Ethiopia 1984 - see Variable: ET1984A_OCC2 - Occupation (2-digit) Ethiopia 1994 - see Variable: ET1994A_OCC - Occupation Fiji 1976 - see Variable: FJ1976A_OCC - Occupation Fiji 1986 - see Variable: FJ1986A_OCC - Occupation Fiji 1996 - see Variable: FJ1996A_OCC3 - Occupation (3 digits) Fiji 2007 - see Variable: FJ2007A_OCC3 - Occupation, 3 digits Fiji 2014 - see Variable: FJ2014A_OCC3 - Occupation (3 digits) Finland 2010 - see Variable: FI2010A_OCC - Occupation France 1962 - see Variable: FR1962A_SOCCUP - SAPHIR occupation France 1968 - see Variable: FR1968A_SOCC - SAPHIR occupation France 1975 - see Variable: FR1975A_SOCC - SAPHIR occupation France 1982 - see Variable: FR1982A_SOCC - SAPHIR occupation France 1990 - see Variable: FR1990A_SOCC - Saphir occupation France 1999 - see Variable: FR1999A_OCC - Occupation, ISCO France 2006 - see Variable: FR2006A_PROF486 - Detailed profession (4-digit) France 2011 - see Variable: FR2011A_PROF - Profession, 486 categories Germany 1970 - see Variable: DE1970A_OCC - Occupation Germany 1981 - see Variable: DE1981A_OCC - Occupation Germany 1987 - see Variable: DE1987A_OCC - Occupation Ghana 1984 - see Variable: GH1984A_OCC2 - Occupation, 2 digits Ghana 2000 - see Variable: GH2000A_OCC - Occupation Ghana 2010 - see Variable: GH2010A_OCC - Occupation (major groups) Greece 1971 - see Variable: GR1971A_OCC - Occupation Greece 1981 - see Variable: GR1981A_OCC - Occupation Greece 1991 - see Variable: GR1991A_OCC - Occupation Greece 2001 - see Variable: GR2001A_OCC - Occupation Greece 2011 - see Variable: GR2011A_OCC - Occupation Guatemala 1964 - see Variable: GT1964A_OCC3 - Occupation (3-digits) Guatemala 1973 - see Variable: GT1973A_OCC3 - Principal occupation (3-digits) Guatemala 1981 - see Variable: GT1981A_OCC3 - Principal occupation (3-digits) Guatemala 1994 - see Variable: GT1994A_OCC - Principal occupation (1-digit) Guatemala 2002 - see Variable: GT2002A_OCC3 - Principal occupation (3-digits) Guinea 1983 - see Variable: GN1983A_OCC2 - Occupation, 2 digits Guinea 1996 - see Variable: GN1996A_OCC - Occupation Guinea 2014 - see Variable: GN2014A_OCC - Occupation (3-digit) Haiti 1982 - see Variable: HT1982A_OCC - Main occupation or profession Haiti 2003 - see Variable: HT2003A_OCC2 - Occupation, 3 digits Honduras 1961 - see Variable: HN1961A_OCC - Occupation (2-digits) Honduras 1974 - see Variable: HN1974A_OCC2 - Occupation (3-digits) Honduras 1988 - see Variable: HN1988A_OCC4 - Occupation (4-digits) Honduras 2001 - see Variable: HN2001A_OCC - Occupation (4-digit) Honduras 2013 - see Variable: HN2013A_OCC3 - Occupation (3-digit) Hungary 1970 - see Variable: HU1970A_OCC - Occupation Hungary 1980 - see Variable: HU1980A_OCC - Occupation, scope of activity Hungary 1990 - see Variable: HU1990A_OCC - Occupation Hungary 2001 - see Variable: HU2001A_OCC - Occupation Hungary 2011 - see Variable: HU2011A_OCC - Occupation Indonesia 1971 - see Variable: ID1971A_OCC - Occupation Indonesia 1976 - see Variable: ID1976A_OCC - Primary occupation during past week Indonesia 1980 - see Variable: ID1980A_OCC - Primary occupation during the previous week (3 digit version) Indonesia 1985 - see Variable: ID1985A_OCC - Primary occupation Indonesia 1990 - see Variable: ID1990A_OCC - Main occupation last week Indonesia 1995 - see Variable: ID1995A_OCC - Occupation Indonesia 2005 - see Variable: ID2005A_OCC - Occupation Iran 2006 - see Variable: IR2006A_OCC4 - Occupation Iran 2011 - see Variable: IR2011A_OCC - Occupation (3-digit) Iraq 1997 - see Variable: IQ1997A_OCC - Occupation Ireland 1971 - see Variable: IE1971A_OCC - Occupation Ireland 1981 - see Variable: IE1981A_OCC - Occupation Ireland 1986 - see Variable: IE1986A_OCC - Occupation group Ireland 1991 - see Variable: IE1991A_OCC - Occupation group Ireland 1996 - see Variable: IE1996A_OCC - Occupation Ireland 2002 - see Variable: IE2002A_OCC - Occupation Ireland 2006 - see Variable: IE2006A_OCC - Occupation group Ireland 2011 - see Variable: IE2011A_OCC - Occupation (shuffled) Ireland 2016 - see Variable: IE2016A_OCC - Occupation (groups) Israel 1972 - see Variable: IL1972A_OCC - Occupation Israel 1983 - see Variable: IL1983A_OCC - Occupation Israel 1995 - see Variable: IL1995A_OCC - Occupation Israel 2008 - see Variable: IL2008A_OCC - Occupation Italy 2001 - see Variable: IT2001A_OCC - Occupation Italy 2011 - see Variable: IT2011A_WKTYPE - Type of work Jamaica 1982 - see Variable: JM1982A_OCC - Occupation during past week / in last job Jamaica 1991 - see Variable: JM1991A_OCC - Occupation during past week/in last job Jamaica 2001 - see Variable: JM2001A_OCC3 - Occupation 3-digit Jordan 2004 - see Variable: JO2004A_OCC3 - Major current occupation (3-digit) Kenya 1989 - see Variable: KE1989A_OCC4 - Occupation, 4 digits Kenya 2019 - see Variable: KE2019A_OCC3 - Occupation (3-digit) Kyrgyzstan 1999 - see Variable: KG1999A_OCC - Main activity Laos 1995 - see Variable: LA1995A_OCC1 - Main occupation in the last 12 months (1-digit) Lesotho 1996 - see Variable: LS1996A_OCC - Occupation (2-digits) Lesotho 2006 - see Variable: LS2006A_OCC - Occupation (2-digits) Liberia 1974 - see Variable: LR1974A_OCC2 - Occupation (2-digit) Liberia 2008 - see Variable: LR2008A_OCC - Occupation Malawi 1987 - see Variable: MW1987A_OCC2 - Occupation, 2 digit Malawi 1998 - see Variable: MW1998A_OCC2 - Occupation, 2-digit Malawi 2008 - see Variable: MW2008A_OCC2 - Occupation (2 digits) Malawi 2018 - see Variable: MW2018A_OCC1 - Main occupation (1-digit) Malaysia 1970 - see Variable: MY1970A_OCC - Occupation last week Malaysia 1980 - see Variable: MY1980A_OCC3 - Principal occupation last week (3 digits) Malaysia 1991 - see Variable: MY1991A_OCC3 - Principal occupation (3 digits) Malaysia 2000 - see Variable: MY2000A_OCC3 - Occupation -- 3 digits Mali 1987 - see Variable: ML1987A_OCC - Occupation last month Mali 1998 - see Variable: ML1998A_OCC - Main occupation Mali 2009 - see Variable: ML2009A_OCC - Principal occupation Mauritius 1990 - see Variable: MU1990A_OCC3 - Occupation (3-digit) Mauritius 2000 - see Variable: MU2000A_OCC4 - Occupation (4 digit) Mauritius 2011 - see Variable: MU2011A_OCC4 - Occupation (4-digit) Mexico 1960 - see Variable: MX1960A_OCC2 - Principal occupation, 2 digits Mexico 1970 - see Variable: MX1970A_OCC3 - Occupation 3 digit Mexico 1990 - see Variable: MX1990A_OCC - Occupation, 4 digits Mexico 1995 - see Variable: MX1995A_OCC - Occupation Mexico 2000 - see Variable: MX2000A_OCC4 - Occupation, 4 digits Mexico 2010 - see Variable: MX2010A_OCC - Occupation or trade Mexico 2015 - see Variable: MX2015A_OCC - Occupation Mexico 2020 - see Variable: MX2020A_OCC3 - Occupation (3-digits) Mongolia 2000 - see Variable: MN2000A_OCC - Occupation Mongolia 2010 - see Variable: MN2010A_OCC3 - Occupation 3 digits (ISCO-2008) Mongolia 2020 - see Variable: MN2020A_OCC3 - Occupation (3-digit) Morocco 1982 - see Variable: MA1982A_OCC3 - Occupation (3-digit) Morocco 1994 - see Variable: MA1994A_OCC3 - Occupation, 3-digit Morocco 2004 - see Variable: MA2004A_OCC3 - Occupation (3-digit) Morocco 2014 - see Variable: MA2014A_OCC2 - Occupation (2-digit) Mozambique 1997 - see Variable: MZ1997A_OCC2 - Occupation 3-digit Mozambique 2007 - see Variable: MZ2007A_OCC - Occupation Mozambique 2017 - see Variable: MZ2017A_OCC3 - Main occupation (3-digits ISCO 2008) Myanmar 2014 - see Variable: MM2014A_OCC - Occupation Nepal 2001 - see Variable: NP2001A_OCC - Usual occupation Nepal 2011 - see Variable: NP2011A_OCC1 - Occupation (1-digit) Netherlands 1960 - see Variable: NL1960A_OCC - Occupation Netherlands 1971 - see Variable: NL1971A_OCC - Occupation Netherlands 2001 - see Variable: NL2001A_OCC - Occupation Netherlands 2011 - see Variable: NL2011A_OCC - Occupation (1-digit) Nicaragua 1971 - see Variable: NI1971A_OCC - Occupation Nicaragua 1995 - see Variable: NI1995A_OCC - Occupation (ISCO 88, 3 digits) Nicaragua 2005 - see Variable: NI2005A_OCC3 - Occupation (ISCO 88, 3 digits) Pakistan 1973 - see Variable: PK1973A_OCC3 - Occupation Palestine 1997 - see Variable: PS1997A_OCC - Main occupation Palestine 2007 - see Variable: PS2007A_OCC - Main occupation Palestine 2017 - see Variable: PS2017A_OCC - Occupation Panama 1960 - see Variable: PA1960A_OCC4 - Occupation (4-digit) Panama 1970 - see Variable: PA1970A_OCC2 - Occupation, 2-digit Panama 1980 - see Variable: PA1980A_OCC2 - Occupation (3-digit) Panama 1990 - see Variable: PA1990A_OCC - Occupation Panama 2000 - see Variable: PA2000A_OCC - Occupation Panama 2010 - see Variable: PA2010A_OCC - Occupation, 3 digits Papua New Guinea 1980 - see Variable: PG1980A_OCC - Occupation, 3 digits Papua New Guinea 1990 - see Variable: PG1990A_OCC - Occupation Papua New Guinea 2000 - see Variable: PG2000A_OCC - Occupation (4-digit) Paraguay 1962 - see Variable: PY1962A_OCC1 - Occupation (1-digit) Paraguay 1972 - see Variable: PY1972A_OCC3 - Occupation (3 digits) Paraguay 1982 - see Variable: PY1982A_OCC3 - Occupation, 3-digits Paraguay 1992 - see Variable: PY1992A_OCC2 - Main occupation, 3 digits Paraguay 2002 - see Variable: PY2002A_OCC - Occupation (4 digits) Peru 1993 - see Variable: PE1993A_OCC - Occupation (3 digits) Peru 2007 - see Variable: PE2007A_OCC - Main occupation last week (3 digits) Peru 2017 - see Variable: PE2017A_OCC1 - Occupation (1-digit, in primary job last week) Philippines 1990 - see Variable: PH1990A_OCC - Occupation Philippines 2000 - see Variable: PH2000A_OCC - Occupation Philippines 2010 - see Variable: PH2010A_OCC3 - Usual occupation (3-digit) Poland 1978 - see Variable: PL1978A_OCC - Occupation Poland 1988 - see Variable: PL1988A_OCC - Main occupation Poland 2002 - see Variable: PL2002A_OCC - Occupation Portugal 1981 - see Variable: PT1981A_OCC - Main occupation Portugal 1991 - see Variable: PT1991A_OCC - Main occupation Portugal 2001 - see Variable: PT2001A_OCC - Main occupation Portugal 2011 - see Variable: PT2011A_OCC - Main occupation Puerto Rico 1970 - see Variable: PR1970A_OCC - Occupation Puerto Rico 1980 - see Variable: PR1980A_OCC - Occupation Puerto Rico 1990 - see Variable: PR1990A_OCC - Occupation Puerto Rico 2000 - see Variable: PR2000A_OCC - Occupation Puerto Rico 2005 - see Variable: PR2005A_OCC - Occupation Puerto Rico 2010 - see Variable: PR2010A_OCC - Occupation Puerto Rico 2015 - see Variable: PR2015A_OCC - Occupation last week Puerto Rico 2020 - see Variable: PR2020A_OCC2010 - Occupation last week, 2010 basis Romania 1992 - see Variable: RO1992A_OCC - Occupation Romania 2002 - see Variable: RO2002A_OCC4 - Occupation, 4 digits Romania 2011 - see Variable: RO2011A_OCC - Occupation (unrecoded) Rwanda 2002 - see Variable: RW2002A_OCC - Occupation Rwanda 2012 - see Variable: RW2012A_OCC2 - Occupation (3-digit) Saint Lucia 1991 - see Variable: LC1991A_OCC - Occupation Senegal 1988 - see Variable: SN1988A_OCC - Occupation Senegal 2002 - see Variable: SN2002A_OCC3 - Occupation, 3 digits Senegal 2013 - see Variable: SN2013A_OCC3 - Profession or occupation (3-digit) Sierra Leone 2004 - see Variable: SL2004A_OCC - Occupation Sierra Leone 2015 - see Variable: SL2015A_OCC - Main occupation in the past 12 months Slovakia 1991 - see Variable: SK1991A_OCC - Occupation (2-digit) Slovakia 2001 - see Variable: SK2001A_OCC2 - Occupation (2-digit) Slovakia 2011 - see Variable: SK2011A_OCC2 - Occupation (2-digit) Slovenia 2002 - see Variable: SI2002A_OCC - Occupation South Africa 1996 - see Variable: ZA1996A_OCC3 - Occupation, 3 digits South Africa 2001 - see Variable: ZA2001A_OCC - Occupation, 3 digit South Africa 2007 - see Variable: ZA2007A_OCC3 - Occupation, 3 digits South Sudan 2008 - see Variable: SS2008A_OCC - Occupation Spain 1981 - see Variable: ES1981A_OCC - Occupation Spain 1991 - see Variable: ES1991A_OCC - Occupation Spain 2001 - see Variable: ES2001A_OCC - Occupation Spain 2011 - see Variable: ES2011A_OCC - Occupation, 2-digits Sudan 2008 - see Variable: SD2008A_OCC - Occupation Suriname 2004 - see Variable: SR2004A_OCC - Occupation Suriname 2012 - see Variable: SR2012A_OCC - Occupation (groups) Switzerland 1970 - see Variable: CH1970A_ISCO - Present occupation (ISCO) Switzerland 1980 - see Variable: CH1980A_ISCO - Present occupation (ISCO-COM) Switzerland 1990 - see Variable: CH1990A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2000 - see Variable: CH2000A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2011 - see Variable: CH2011A_OCC - Current occupation (1-digit, ISCO-08) Tanzania 1988 - see Variable: TZ1988A_OCC - Occupation Tanzania 2002 - see Variable: TZ2002A_OCC - Occupation last week Tanzania 2012 - see Variable: TZ2012A_OCC - Occupation Thailand 1970 - see Variable: TH1970A_OCC - Principal occupation last year Thailand 1980 - see Variable: TH1980A_OCC - Occupation last year Thailand 1990 - see Variable: TH1990A_OCC3 - Occupation last year Thailand 2000 - see Variable: TH2000A_OCC3 - Occupation last year, 3 digits Togo 1960 - see Variable: TG1960A_OCC - Occupation (3-digits) Togo 1970 - see Variable: TG1970A_OCC3 - Occupation (3-digits) Togo 2010 - see Variable: TG2010A_OCC2 - Occupation (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_OCC - Main occupation (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_OCC - Main occupation during previous week (three digits) Trinidad and Tobago 2000 - see Variable: TT2000A_OCC - Main occupation (3 digits) Turkey 1985 - see Variable: TR1985A_OCC2 - Occupation (2-digit) Turkey 1990 - see Variable: TR1990A_OCC2 - Current occupation (2 digits) Turkey 2000 - see Variable: TR2000A_OCC2 - Current occupation, 2 digit Uganda 1991 - see Variable: UG1991A_OCC - Occupation, 3 digits Uganda 2002 - see Variable: UG2002A_OCC - Occupation, 3 digits Uganda 2014 - see Variable: UG2014A_OCC - Occupation (2-digits) United Kingdom 1961 - see Variable: UK1961A_OCC - Occupation United Kingdom 1971 - see Variable: UK1971A_OCC - Occupation United Kingdom 1991 - see Variable: UK1991A_OCC - Occupational classification United Kingdom 2001 - see Variable: UK2001A_OCC3 - Standard occupational classification 2000-minor United States 1960 - see Variable: US1960A_OCC - Occupation United States 1970 - see Variable: US1970A_OCC - Occupation United States 1980 - see Variable: US1980A_OCC - Occupation United States 1990 - see Variable: US1990A_OCC - Occupation United States 2000 - see Variable: US2000A_OCC - Occupation United States 2005 - see Variable: US2005A_OCC2000M - Occupation, 2000 basis, modal category assignment United States 2010 - see Variable: US2010A_OCC - Occupation United States 2015 - see Variable: US2015A_OCC - Occupation last week United States 2020 - see Variable: US2020A_OCC - Occupation last week Uruguay 1963 - see Variable: UY1963A_OCC2 - Primary occupation [2-digit] Uruguay 1975 - see Variable: UY1975A_OCC - Occupation (COTA, 3 digits) Uruguay 1985 - see Variable: UY1985A_OCC - Occupation during the past week Uruguay 1996 - see Variable: UY1996A_OCC - Occupation (ISCO 88, 3 digits) Uruguay 2006 - see Variable: UY2006A_OCC3 - Occupation (ISCO-88, 3 digits) Venezuela 1981 - see Variable: VE1981A_OCC3 - Occupation, 3 digits Venezuela 1990 - see Variable: VE1990A_OCC - Occupation, 3 digits Venezuela 2001 - see Variable: VE2001A_OCC - Occupation Vietnam 1989 - see Variable: VN1989A_OCC2 - Occupation, 2 digits Vietnam 1999 - see Variable: VN1999A_OCC3 - Occupation, 3 digit Vietnam 2009 - see Variable: VN2009A_OCC - Occupation Vietnam 2019 - see Variable: VN2019A_OCC1 - Occupation, 1 digit Zambia 1990 - see Variable: ZM1990A_OCC - Occupation Zambia 2000 - see Variable: ZM2000A_OCC - Main occupation last 12 months, 3 digits Zambia 2010 - see Variable: ZM2010A_OCC2 - Main occupation last 12 months, 3 digits Zimbabwe 2012 - see Variable: ZW2012A_OCC - Occupation (3-digits) Work Variables -- PERSON Industry, general recode INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown Work Variables -- PERSON Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_IND4 - Industry [4 digit] Argentina 1980 - see Variable: AR1980A_IND - Industry Argentina 1991 - see Variable: AR1991A_IND - Industry Argentina 2001 - see Variable: AR2001A_IND - Industry Armenia 2001 - see Variable: AM2001A_IND - Principal activity at place of work Armenia 2011 - see Variable: AM2011A_IND - Industry Austria 1971 - see Variable: AT1971A_INDBR - Economic activity of supporter: branch Austria 1981 - see Variable: AT1981A_INDBR - Economic activity of supporter: branch Austria 1991 - see Variable: AT1991A_INDBR - Economic activity of supporter: branch Austria 2001 - see Variable: AT2001A_INDBR - Economic activity of supporter: branch Austria 2011 - see Variable: AT2011A_IND - Industry Bangladesh 1991 - see Variable: BD1991A_IND - Industry Bangladesh 2001 - see Variable: BD2001A_IND - Main work field Bangladesh 2011 - see Variable: BD2011A_IND - Industry Belarus 2009 - see Variable: BY2009A_ECONACT - Industry Benin 1979 - see Variable: BJ1979A_IND - Industry (1-digit) Benin 1992 - see Variable: BJ1992A_IND3 - Industry (2-digits) Benin 2002 - see Variable: BJ2002A_IND2 - Industry (2-digits) Benin 2013 - see Variable: BJ2013A_IND3 - Industry (3-digit) Bolivia 1976 - see Variable: BO1976A_IND - Industry Bolivia 1992 - see Variable: BO1992A_IND3 - Activity, 3 digits Bolivia 2001 - see Variable: BO2001A_IND3 - Industry, 3 digits Bolivia 2012 - see Variable: BO2012A_IND2 - Industry (2 digit) Botswana 1981 - see Variable: BW1981A_IND - Industry Botswana 1991 - see Variable: BW1991A_IND - Industry Botswana 2001 - see Variable: BW2001A_IND - Industry Botswana 2011 - see Variable: BW2011A_IND - Industry, 3-digits Brazil 1960 - see Variable: BR1960A_INDUSTRY - Industry Brazil 1970 - see Variable: BR1970A_INDUSTRY - Industry Brazil 1980 - see Variable: BR1980A_INDUSTRY - Industry Brazil 1991 - see Variable: BR1991A_IND - Industry Brazil 2000 - see Variable: BR2000A_IND - Industry, 5 digits Brazil 2010 - see Variable: BR2010A_IND - Industry of work from July 25 to July 31, 2010 Burkina Faso 1996 - see Variable: BF1996A_IND - Branch of activity Cambodia 1998 - see Variable: KH1998A_IND - Industry Cambodia 2004 - see Variable: KH2004A_IND3 - Industry (3-digits) Cambodia 2008 - see Variable: KH2008A_IND - Industry Cambodia 2013 - see Variable: KH2013A_IND - Industry (3-digits) Cambodia 2019 - see Variable: KH2019A_IND3 - Industy (ISIC rev 4, 3-digit) Cameroon 2005 - see Variable: CM2005A_IND - Industry Canada 1971 - see Variable: CA1971A_IND - Industry Canada 1981 - see Variable: CA1981A_IND - Industry (1981 standard industrial classification) Canada 1991 - see Variable: CA1991A_IND80 - Industry (1980 standard industrial classification) Canada 2001 - see Variable: CA2001A_IND80P - Industry (1980 Standard Industrial Classification) Canada 2011 - see Variable: CA2011A_IND - Industry Chile 1960 - see Variable: CL1960A_IND - Industry Chile 1970 - see Variable: CL1970A_IND4 - Industry (4-digit) Chile 1982 - see Variable: CL1982A_IND4 - Industry (4-digit) Chile 1992 - see Variable: CL1992A_IND - Industry Chile 2002 - see Variable: CL2002A_IND - Industry Chile 2017 - see Variable: CL2017A_IND - Industry (1-digit) China 1982 - see Variable: CN1982A_INDUSTRY - Industry China 1990 - see Variable: CN1990A_IND - Industry China 2000 - see Variable: CN2000A_IND - Industry (2-digit) Colombia 1964 - see Variable: CO1964A_IND4 - Industry, 4 digits Colombia 1973 - see Variable: CO1973A_IND - Industry Colombia 1993 - see Variable: CO1993A_IND - Industry Colombia 2005 - see Variable: CO2005A_IND - Industry (2-digit) Costa Rica 1963 - see Variable: CR1963A_IND3 - Industry, 3 digits Costa Rica 1973 - see Variable: CR1973A_IND4 - Industry, 4 digits Costa Rica 1984 - see Variable: CR1984A_IND4 - Industry, 4 digits Costa Rica 2000 - see Variable: CR2000A_IND3 - Industry, 3 digits Costa Rica 2011 - see Variable: CR2011A_IND - Industry 2-digit Cuba 2002 - see Variable: CU2002A_IND - Industry Cuba 2012 - see Variable: CU2012A_IND - Industry Côte d'Ivoire 1988 - see Variable: CI1988A_IND - Industry (1-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_IND2 - Industry sector (detailed) Dominican Republic 1960 - see Variable: DO1960A_IND - Industry Dominican Republic 1970 - see Variable: DO1970A_IND1 - Industry, 3 digits Dominican Republic 1981 - see Variable: DO1981A_IND - Industry (3-digit) Dominican Republic 2002 - see Variable: DO2002A_IND - Industry Dominican Republic 2010 - see Variable: DO2010A_IND - Main activity of business Ecuador 1962 - see Variable: EC1962A_IND3 - Industry, 3 digits Ecuador 1982 - see Variable: EC1982A_IND3 - Industry Ecuador 1990 - see Variable: EC1990A_IND3 - Industry, 3 digits Ecuador 2001 - see Variable: EC2001A_IND - Industry, 3 digits Ecuador 2010 - see Variable: EC2010A_IND3 - Industry (3 digits, ISIC rev 4) Egypt 1986 - see Variable: EG1986A_IND3 - Industry (3-digit) Egypt 1996 - see Variable: EG1996A_IND3 - Industry (ISIC) Egypt 2006 - see Variable: EG2006A_IND - Industry, 3-digit El Salvador 1992 - see Variable: SV1992A_IND - Industry (3-digit) El Salvador 2007 - see Variable: SV2007A_IND3DIG - Industry (3-digit) Ethiopia 1984 - see Variable: ET1984A_IND2 - Industry Ethiopia 1994 - see Variable: ET1994A_IND - Industry Fiji 1966 - see Variable: FJ1966A_IND - Industry Fiji 1976 - see Variable: FJ1976A_IND - Industry Fiji 1986 - see Variable: FJ1986A_IND - Industry 3 digits Fiji 1996 - see Variable: FJ1996A_IND2DIG - Industry (2 digits) Fiji 2007 - see Variable: FJ2007A_IND2 - Industry, 2 digits Fiji 2014 - see Variable: FJ2014A_IND - Industry Finland 2010 - see Variable: FI2010A_IND - Industry France 1962 - see Variable: FR1962A_IND - Industry France 1968 - see Variable: FR1968A_IND41 - Industry, 41 categories France 1975 - see Variable: FR1975A_INDUN - Industry, UNO France 1982 - see Variable: FR1982A_INDUN - Industry, United Nations nomenclature France 1990 - see Variable: FR1990A_IND15 - Industry, 15 categories France 1999 - see Variable: FR1999A_INDCITI - Industry, ISIC France 2006 - see Variable: FR2006A_IND700N - Economic activity in 700 categories (2003 classification) numeric recode France 2011 - see Variable: FR2011A_IND - Industry, 732 categories Germany 1970 - see Variable: DE1970A_IND - Industry Germany 1971 - see Variable: DE1971A_IND - Industry Germany 1981 - see Variable: DE1981A_IND - Industry Germany 1987 - see Variable: DE1987A_IND - Industry Ghana 2000 - see Variable: GH2000A_IND - Industry Ghana 2010 - see Variable: GH2010A_IND - Industry (major groups) Greece 1971 - see Variable: GR1971A_IND - Industry Greece 1981 - see Variable: GR1981A_IND - Industry Greece 1991 - see Variable: GR1991A_IND - Industry Greece 2001 - see Variable: GR2001A_IND - Industry Greece 2011 - see Variable: GR2011A_IND - Industry Guatemala 1964 - see Variable: GT1964A_IND3 - Field of economic activity (3-digits) Guatemala 1973 - see Variable: GT1973A_IND3 - Industry (3-digits) Guatemala 1981 - see Variable: GT1981A_IND3 - Industry (3-digits) Guatemala 1994 - see Variable: GT1994A_IND2 - Field of economic activity (2-digits) Guatemala 2002 - see Variable: GT2002A_IND1 - Field of economic activity (1-digit) Guinea 1983 - see Variable: GN1983A_IND2 - Branch of economic activity, 2 digits Guinea 2014 - see Variable: GN2014A_IND - Industry (3-digit) Haiti 1982 - see Variable: HT1982A_IND - Branch of work Haiti 2003 - see Variable: HT2003A_IND2 - Industry, 3 digits Honduras 1961 - see Variable: HN1961A_IND - Industry (2-digits) Honduras 1974 - see Variable: HN1974A_IND - Industry (3-digits) Honduras 2001 - see Variable: HN2001A_IND - Industry (4-digit) Honduras 2013 - see Variable: HN2013A_IND3 - Economic activity (3-digit) Hungary 2001 - see Variable: HU2001A_IND - Industry, branch of economy Hungary 2011 - see Variable: HU2011A_IND - Industry Indonesia 1971 - see Variable: ID1971A_IND - Industry Indonesia 1976 - see Variable: ID1976A_IND - Industry Indonesia 1980 - see Variable: ID1980A_IND - Industry Indonesia 1985 - see Variable: ID1985A_IND - Industry of primary occupation Indonesia 1990 - see Variable: ID1990A_IND - Industry of main occupation last week Indonesia 1995 - see Variable: ID1995A_IND - Industry Indonesia 2000 - see Variable: ID2000A_IND - Industry of primary occupation Indonesia 2005 - see Variable: ID2005A_IND - Industry Indonesia 2010 - see Variable: ID2010A_IND - Industry Iran 2006 - see Variable: IR2006A_IND4 - Industry Iran 2011 - see Variable: IR2011A_IND - Industry (3-digit) Iraq 1997 - see Variable: IQ1997A_IND - Industry Ireland 1971 - see Variable: IE1971A_IND - Industry Ireland 1981 - see Variable: IE1981A_IND - Industry class Ireland 1986 - see Variable: IE1986A_IND - Industry class Ireland 1991 - see Variable: IE1991A_IND - Industry class Ireland 1996 - see Variable: IE1996A_IND - Industry class Ireland 2002 - see Variable: IE2002A_IND - Industry class Ireland 2006 - see Variable: IE2006A_IND - Industry class Ireland 2011 - see Variable: IE2011A_IND - Industry Ireland 2016 - see Variable: IE2016A_IND - Industry Israel 1972 - see Variable: IL1972A_IND - Industry Israel 1983 - see Variable: IL1983A_IND - Industry Israel 1995 - see Variable: IL1995A_IND - Industry Israel 2008 - see Variable: IL2008A_IND - Branch of economy Italy 2001 - see Variable: IT2001A_IND - Industry Italy 2011 - see Variable: IT2011A_IND - Sector of economic activity Jamaica 1982 - see Variable: JM1982A_IND - Industry or type of business during past week / in last job Jamaica 1991 - see Variable: JM1991A_IND3 - Industry during past week or in last job, 3 digits Jamaica 2001 - see Variable: JM2001A_IND3 - Industry 3-digit Jordan 2004 - see Variable: JO2004A_IND - Major current economic activity of the establishment Kenya 2019 - see Variable: KE2019A_IND1 - Industry, ISIC section Kyrgyzstan 1999 - see Variable: KG1999A_IND - Activity type of an enterprise you are working in Kyrgyzstan 2009 - see Variable: KG2009A_IND - Type of industry, enterprise or organization Laos 1995 - see Variable: LA1995A_IND2 - Main industry in the last 12 months (2-digit) Laos 2005 - see Variable: LA2005A_IND3 - Industry (ISIC 3-digit) Laos 2015 - see Variable: LA2015A_IND2 - Industry (2-digit ISIC Rev. 4) Lesotho 2006 - see Variable: LS2006A_IND - Industry (2-digits) Liberia 1974 - see Variable: LR1974A_IND - Industry (3-digit) Liberia 2008 - see Variable: LR2008A_IND - Industry Malawi 1987 - see Variable: MW1987A_IND2 - Industry, 2 digit Malawi 1998 - see Variable: MW1998A_IND4 - Industry, 4-digit Malawi 2008 - see Variable: MW2008A_IND2 - Main industry Malawi 2018 - see Variable: MW2018A_IND3 - Main industry (ISIC 2008 3-digit) Malaysia 1970 - see Variable: MY1970A_IND3 - Industry last week Malaysia 1980 - see Variable: MY1980A_IND3 - Industry last week (3 digits) Malaysia 1991 - see Variable: MY1991A_IND3 - Main industry (3 digits) Malaysia 2000 - see Variable: MY2000A_IND3 - Main industry - 3 digits Mali 1987 - see Variable: ML1987A_IND - Principal branch of employment last month Mali 1998 - see Variable: ML1998A_IND - Branch of economic activity Mali 2009 - see Variable: ML2009A_IND - Industry Mauritius 1990 - see Variable: MU1990A_IND - Industry (1-digit) Mauritius 2000 - see Variable: MU2000A_IND1 - Industry (1 digit) Mauritius 2011 - see Variable: MU2011A_IND2 - Industry (2-digit) Mexico 1960 - see Variable: MX1960A_IND - Industry Mexico 1970 - see Variable: MX1970A_IND - Industry Mexico 1990 - see Variable: MX1990A_IND5 - Industry, 5 digits Mexico 1995 - see Variable: MX1995A_IND - Industry Mexico 2000 - see Variable: MX2000A_IND3 - Industry, 3 digits Mexico 2010 - see Variable: MX2010A_IND - Industry Mexico 2015 - see Variable: MX2015A_IND - Industry Mexico 2020 - see Variable: MX2020A_IND - Industry (4-digits) Mongolia 2000 - see Variable: MN2000A_IND - Industry Mongolia 2010 - see Variable: MN2010A_IND2 - Industry, division (ISIC Revision 4) Mongolia 2020 - see Variable: MN2020A_IND3 - Main industry (3-digit) Morocco 1982 - see Variable: MA1982A_IND3 - Industry (3-digit) Morocco 1994 - see Variable: MA1994A_IND2 - Industry (2 digits) Morocco 2004 - see Variable: MA2004A_IND2 - Sector of economic activity (2-digit) Morocco 2014 - see Variable: MA2014A_IND2 - Industry (2-digit) Mozambique 1997 - see Variable: MZ1997A_IND1 - Industry Mozambique 2007 - see Variable: MZ2007A_IND - Industry Mozambique 2017 - see Variable: MZ2017A_IND2 - Main economic activity (2-digits CAE Rev.2) Myanmar 2014 - see Variable: MM2014A_IND - Industry Nepal 2001 - see Variable: NP2001A_IND - Usual industry Nepal 2011 - see Variable: NP2011A_IND - Industry (2-digit) Netherlands 1960 - see Variable: NL1960A_IND - Industry Netherlands 1971 - see Variable: NL1971A_IND - Industry Netherlands 2001 - see Variable: NL2001A_IND - Industry Netherlands 2011 - see Variable: NL2011A_IND - Industry (1-digit) Nicaragua 1971 - see Variable: NI1971A_IND3 - Industry (ISIC2), 3 digits Nicaragua 1995 - see Variable: NI1995A_IND - Industry (ISIC 3.1, 3 digits) Nicaragua 2005 - see Variable: NI2005A_IND3 - Industry (ISIC 3.1, 3 digits)) Pakistan 1973 - see Variable: PK1973A_IND2 - Industry, 2 digit Palestine 1997 - see Variable: PS1997A_IND - Industry Palestine 2007 - see Variable: PS2007A_IND - Industry Palestine 2017 - see Variable: PS2017A_IND - Industry Panama 1960 - see Variable: PA1960A_IND3 - Industry (3 digit) Panama 1970 - see Variable: PA1970A_IND3 - Industry [3 digit] Panama 1980 - see Variable: PA1980A_IND - Industry, 3-digit Panama 1990 - see Variable: PA1990A_IND3 - Industry - 3 Digits Panama 2000 - see Variable: PA2000A_IND - Economic activity, 3 digits Panama 2010 - see Variable: PA2010A_IND - Economic activity, 4 digits Papua New Guinea 1980 - see Variable: PG1980A_IND - Industry, 3 digits Papua New Guinea 2000 - see Variable: PG2000A_IND3 - Industry (3-digit) Paraguay 1962 - see Variable: PY1962A_IND3 - Industry (3 digits) Paraguay 1972 - see Variable: PY1972A_IND3 - Industry (3 digits) Paraguay 1982 - see Variable: PY1982A_IND3 - Industry, 3-digits Paraguay 1992 - see Variable: PY1992A_IND3 - Industry, 3 digits Paraguay 2002 - see Variable: PY2002A_IND - Industry (4 digits) Peru 1993 - see Variable: PE1993A_IND - Economic activity (4 digits) Peru 2007 - see Variable: PE2007A_IND - Economic activity (4-digits) Peru 2017 - see Variable: PE2017A_IND4 - Economic activity (4-digits, in primary job last week) Philippines 1990 - see Variable: PH1990A_IND - Industry Philippines 1995 - see Variable: PH1995A_IND - Industry Philippines 2000 - see Variable: PH2000A_IND - Industry Philippines 2010 - see Variable: PH2010A_IND3 - Kind of business or industry (3-digit) Poland 1978 - see Variable: PL1978A_IND - Industry (of person providing support) Poland 2002 - see Variable: PL2002A_IND - Industry (main employer) Portugal 1981 - see Variable: PT1981A_IND - Industry Portugal 1991 - see Variable: PT1991A_IND - Industry Portugal 2001 - see Variable: PT2001A_IND - Industry Portugal 2011 - see Variable: PT2011A_IND - Industry Puerto Rico 1970 - see Variable: PR1970A_IND1990 - Industry, 1990 basis Puerto Rico 1980 - see Variable: PR1980A_IND1990 - Industry, 1990 basis Puerto Rico 1990 - see Variable: PR1990A_IND - Industry Puerto Rico 2000 - see Variable: PR2000A_IND1990 - Industry, 1990 basis Puerto Rico 2005 - see Variable: PR2005A_IND1990 - Industry, 1990 basis Puerto Rico 2010 - see Variable: PR2010A_IND - Industry Puerto Rico 2015 - see Variable: PR2015A_IND - Industry Puerto Rico 2020 - see Variable: PR2020A_IND - Industry Romania 1977 - see Variable: RO1977A_IND - Industry of supporter Romania 1977 - see Variable: RO1977A_WKACT - Activity category Romania 1992 - see Variable: RO1992A_IND - Industry Romania 2002 - see Variable: RO2002A_IND - Industry Romania 2011 - see Variable: RO2011A_INDGEN - Industry (general categories) Rwanda 2002 - see Variable: RW2002A_IND - Industry Rwanda 2012 - see Variable: RW2012A_IND2 - Industry (3-digit) Saint Lucia 1991 - see Variable: LC1991A_IND3 - Industry, 2 digit Senegal 1988 - see Variable: SN1988A_IND - Industry Senegal 2013 - see Variable: SN2013A_IND3 - Industry (3-digit) Sierra Leone 2004 - see Variable: SL2004A_IND - Industry Slovenia 2002 - see Variable: SI2002A_IND - Industry South Africa 1996 - see Variable: ZA1996A_IND2 - Industry, 2 digits South Africa 2001 - see Variable: ZA2001A_IND3 - Industry, 3 digit South Africa 2007 - see Variable: ZA2007A_IND3 - Industry, 3 digit South Sudan 2008 - see Variable: SS2008A_IND - Industry Spain 1981 - see Variable: ES1981A_IND - Industry Spain 1991 - see Variable: ES1991A_IND - Activity of the establishment Spain 2001 - see Variable: ES2001A_IND - Industry Spain 2011 - see Variable: ES2011A_IND - Industry, 2-digits Sudan 2008 - see Variable: SD2008A_IND - Industry Suriname 2004 - see Variable: SR2004A_IND - Industry Suriname 2012 - see Variable: SR2012A_IND - Industry (groups) Switzerland 1970 - see Variable: CH1970A_IND - Branch of economic activity (industry) Switzerland 1980 - see Variable: CH1980A_IND - Branch of economic activity (industry) Switzerland 1990 - see Variable: CH1990A_IND - Branch of economic activity (industry) Switzerland 2000 - see Variable: CH2000A_IND - Branch of economic activity (industry) Switzerland 2011 - see Variable: CH2011A_IND2 - Industry of local unit, workplace (NOGA 2-digit) Tanzania 2002 - see Variable: TZ2002A_IND - Industry last week Tanzania 2012 - see Variable: TZ2012A_IND - Industry Thailand 1970 - see Variable: TH1970A_IND - Principal industry last year Thailand 1980 - see Variable: TH1980A_IND - Principal industry last year Thailand 1990 - see Variable: TH1990A_IND3 - Principal industry last year, 3 digits Thailand 2000 - see Variable: TH2000A_IND3 - Industry last year, 3 digits Togo 1970 - see Variable: TG1970A_IND - Industry (1-digit) Togo 2010 - see Variable: TG2010A_IND3 - Industry (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_IND - Industry (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_IND - Industry Trinidad and Tobago 2000 - see Variable: TT2000A_IND - Industry (2 digits) Turkey 1985 - see Variable: TR1985A_INDALT - Industry (2-digit) Turkey 1990 - see Variable: TR1990A_IND2 - Industry (2 digits) Turkey 2000 - see Variable: TR2000A_IND2 - Industry, 2 digit Uganda 2002 - see Variable: UG2002A_IND - Industry United Kingdom 1961 - see Variable: UK1961A_IND - Industry United Kingdom 1971 - see Variable: UK1971A_IND - Industry United Kingdom 1991 - see Variable: UK1991A_IND - Industrial classification United Kingdom 2001 - see Variable: UK2001A_IND - Industry classification United States 1960 - see Variable: US1960A_IND - Industry United States 1970 - see Variable: US1970A_IND - Industry United States 1980 - see Variable: US1980A_IND - Industry United States 1990 - see Variable: US1990A_IND - Industry United States 2000 - see Variable: US2000A_IND - Industry United States 2005 - see Variable: US2005A_IND - Industry United States 2010 - see Variable: US2010A_IND - Industry United States 2015 - see Variable: US2015A_IND - Industry United States 2020 - see Variable: US2020A_IND - Industry Uruguay 1963 - see Variable: UY1963A_IND2 - Primary industry [2-digit] Uruguay 1985 - see Variable: UY1985A_IND - Industry during the past week Uruguay 1996 - see Variable: UY1996A_IND2 - Industry (ISIC 3, 2 digits) Uruguay 2006 - see Variable: UY2006A_IND3 - Industry (ISIC rev 3, 3 digits) Venezuela 1981 - see Variable: VE1981A_IND - Industry Venezuela 1990 - see Variable: VE1990A_IND - Industry Venezuela 2001 - see Variable: VE2001A_IND - Industry Vietnam 1989 - see Variable: VN1989A_IND2 - Industry, 2 digits Vietnam 1999 - see Variable: VN1999A_IND3 - Industry, 3 digit Vietnam 2009 - see Variable: VN2009A_IND - Industry Vietnam 2019 - see Variable: VN2019A_IND3 - Industry, 3 digit Zambia 1990 - see Variable: ZM1990A_IND - Industry Zambia 2000 - see Variable: ZM2000A_IND - Type of industry, 3 digits Zambia 2010 - see Variable: ZM2010A_IND2 - Industry, 3 digits Work Variables -- PERSON Status in employment (class of worker) [general version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 0 NIU (not in universe) 1 Self-employed 2 Wage/salary worker 3 Unpaid worker 4 Other 9 Unknown/missing Work Variables -- PERSON Status in employment (class of worker) [detailed version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 000 NIU (not in universe) 100 Self-employed 101 Self-employed, unincorporated 102 Self-employed, incorporated 110 Employer 111 Sharecropper, employer 120 Working on own account 121 Own account, agriculture 122 Domestic worker, self-employed 123 Subsistence worker, own consumption 124 Own account, other 125 Own account, without temporary/unpaid help 126 Own account, with temporary/unpaid help 130 Member of cooperative 140 Sharecropper 141 Sharecropper, self-employed 142 Sharecropper, employee 150 Kibbutz member 199 Self-employed, not specified 200 Wage/salary worker 201 Management 202 Non-management 203 White collar (non-manual) 204 Blue collar (manual) 205 White or blue collar 206 Day laborer 207 Employee, with a permanent job 208 Employee, occasional, temporary, contract 209 Employee without legal contract 210 Wage/salary worker, private employer 211 Apprentice 212 Religious worker 213 Wage/salary worker, non-profit, NGO 214 White collar, private 215 Blue collar, private 216 Paid family worker 217 Cooperative employee 220 Wage/salary worker, government or public sector 221 Federal, government employee 222 State government employee 223 Local government employee 224 White collar, public 225 Blue collar, public 226 Public companies 227 Civil servants, local collectives 230 Domestic worker (work for private household) 240 Seasonal migrant 241 Seasonal migrant, no broker 242 Seasonal migrant, uses broker 250 Other wage and salary 251 Canal zone/commission employee 252 Government employment/training program 253 Mixed state/private enterprise/parastatal 254 Government public work program 255 State enterprise employee 256 Coordinated and continuous collaboration job 300 Unpaid worker 310 Unpaid family worker 320 Apprentice, unpaid or unspecified 330 Trainee 340 Apprentice or trainee 350 Works for others without wage 400 Other 999 Unknown/missing Work Variables -- PERSON 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 Country of previous residence MIGCTRYP indicates the country of previous residence of international migrants. Persons who never lived abroad are coded to the "non-migrant" category. 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, n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12100 Sao Tome and Principe 12999 Middle Africa, n.s. 13000 Northern Africa 13010 Algeria 13020 Egypt/United Arab Rep. 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13990 Northern Africa, n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15150 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 15160 Sierra Leone 15170 Togo 19999 Africa, 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 and the Grenadines 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21999 Caribbean, n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23990 South America, n.s. 23991 Central and Latin America 24000 North America 24010 Bermuda 24020 Canada 24030 Greenland 24040 Saint Pierre and Miquelon 24050 United States 24051 U.S. Outlying Areas and Territories 24999 U.S.A, Canada, Mexico 29999 Americas, 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 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 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33061 Malaysia and Singapore 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34060 Iraq 34070 Israel 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34190 Middle East, not specified 34191 Arabia 34199 Gulf countries 39999 Asia, n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Albania/Bulgaria/Romania 41030 Czech Republic 41031 Czechoslovakia/Yugoslavia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41999 Eastern Europe, n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42110 Sweden 42120 United Kingdom 42199 Scandinavia 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia 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 Serbia and Montenegro 43999 Southern Europe, n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44021 Belgium/Luxemburg 44022 Benelux (Belgium/Netherlands/Luxemburg) 44030 France 44040 Germany 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 49990 Europe, n.s. 49991 Central and Eastern Europe 49992 European Union 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51021 New Zealand/New Guinea 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) 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53999 Micronesia, n.e.c. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Samoa 54060 Tokelau 54070 Tonga 54080 Tuvalu 54090 Wallis and Futuna Isls. 59999 Oceania, n.s. 60000 Other 60010 Europe, Australia, New Zealand 60020 Asia and Oceania, n.s. 90000 Non-migrants (International) 99998 Response suppressed 99999 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 Region of previous residence, Mali; consistent boundaries, GIS MIG1_P_ML indicates the person's region of previous residence within Mali. The person may have moved at any time in their life. 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. 466001 Kayes 466002 Koulikoro 466003 Sikasso 466004 Ségou 466005 Mopti 466006 Tombouctou 466007 Gao, Kidal 466009 Bamako 466096 Mali, province unspecified 466097 Foreign country 466098 Unknown 466999 NIU (not in universe) Migration: F-N Variables -- PERSON Circle of previous residence, Mali; consistent boundaries, GIS MIG2_P_ML indicates the person's circle of previous residence within Mali. Migration cercle codes from MIG2_P_ML are compatible with codes from GEO2_ML. The person may have moved at any time in their life. 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. 466001001 Kayes 466001002 Bafoulabé 466001003 Diéma 466001004 Kéniéba 466001005 Kita 466001006 Nioro 466001007 Yélimané 466001099 Kayes region, unknown circle 466002001 Koulikoro 466002002 Banamba 466002003 Dioila 466002004 Kangaba 466002005 Kati 466002006 Kolokani 466002007 Nara 466002099 Koulikoro region, unknown circle 466003001 Sikasso 466003002 Bougouni 466003003 Kadiolo 466003004 Kolondiéba 466003005 Koutiala 466003006 Yanfolila 466003007 Yorosso 466003099 Sikasso region, unknown circle 466004001 Ségou 466004002 Barouéli 466004003 Bla 466004004 Macina 466004005 Niono 466004006 San 466004007 Tominian 466004099 Ségou region, unknown circle 466005001 Mopti 466005002 Bandiagara 466005003 Bankass 466005004 Djénné 466005005 Douentza 466005006 Koro 466005007 Ténenkou 466005008 Youwarou 466005099 Mopti region, unknown circle 466006001 Tombouctou 466006002 Diré 466006003 Goundam 466006004 Gourma-Rharous 466006005 Niafunké 466006099 Tombouctou region, unknown circle 466007001 Gao 466007002 Ansongo 466007003 Bourem 466007004 Ménaka 466007005 Kidal, Abéïbara, Tessalit, Tin-Essako 466007098 Gao region, unknown circle 466007099 Kidal region, unknown circle 466009001 District of Bamako 466096096 Mali, province unspecified 466097097 Foreign country 466098098 Unknown 466099099 NIU (not in universe) Migration: F-N Variables -- PERSON Disability status DISABLED indicates whether the person reported a disability of any kind. 0 NIU (not in universe) 1 Yes, disabled 2 No, not disabled 9 Unknown Disability Variables -- PERSON Blind or vision-impaired DISBLND indicates whether the person was blind or had limited vision. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Deaf or hearing-impaired DISDEAF indicates whether the person was deaf or had limited hearing. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Mute or speech impaired DISMUTE indicates if the person could not speak or had a significant speech impediment. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Psychological disability DISPSYC indicates whether the person was disabled due to mental illness. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Person number (within household) Mali 1998: All persons 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 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98 99 99 Technical Person Variables -- PERSON Relationship to head of household <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A404" a="all">3. Relationship to head of household<br /><div class="i1">[] 1 Head of household<br />[] 2 Spouse of head<br />[] 3 Child of head<br />[] 4 Parent of head<br />[] 5 Sibling of head<br />[] 6 Other relative of head<br />[] 7 No family relationship to head</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A402 ML98A403 ML98A404" a="all">2. Column P2: First name and last name<br /><br />Write in Column P2 the first names and last names of all the household members, starting with the head of household, as mentioned on the principle for listing the household members. Before starting to ask other questions, write first all the first names and last names. This is done to avoid the possible memory failures of the head of household. Write the usual first name of each household member, followed with his family name. When several members in the household bear the same last name and first name, use surnames when needed.<br /><br />N.B: When, in a household, one finds a new born not yet baptized, write as a first name the term "boy" or "girl", depending on his or her sex, followed by the family name.<br /><br />Example:<br />Boy TRAORE = is a newborn male child, not yet baptized, whose father is Mr. TRAORE.<br />Girl TRAORE = is a newborn female child, not yet baptized, whose father is Mr. TRAORE.<br /></svar> Mali 1998: All persons This variable indicates the person's relationship to head of household. 1 Head 2 Spouse 3 Son or daughter 4 Father or mother 5 Brother or sister 6 Other relatives 7 Not related 8 Unknown Demographic Variables -- PERSON Sex <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A405" a="all">4. Sex<br /><div class="i1">[] 1 Male<br />[] 2 Female</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A405" a="all">4. Column P4: Sex<br /><br />Note the sex of each household member. Circle the number in front of the letter corresponding to the sex:<br /><div class="i1">[] 1 Male<br />[] 2 Female</div><br /><br />Never try to infer the sex from the person's first name, but always ask the question, in a way so that the interviewed person is not hurt. Indeed, persons from different sexes might have the same first name.<br /><br />Example: Adama, Sadio, Konimba, Massiré, Fily, etc...<br /></svar> Mali 1998: All persons This variable indicates the person's gender. 1 Male 2 Female Demographic Variables -- PERSON Residence status <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A406" a="all">5. Residence status<br /><div class="i1">[] 1 RP<br />[] 2 RA<br />[] 3 V</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A406" a="all">5. Column P5: Residence status<br /><br />The reference date for collecting the data on the situation of residence is the night preceding the visit of the census enumerator in the household.<br /><br />The various categories of resident, and the visitor status, will be determined according to this reference night. Then, refer to the definitions of Resident and of Visitor given in the concept section, and circle the number located before the letter corresponding to the situation:<br /><br /><div class="i1">[] 1 RP (Resident Present)<br />[] 2 RA (Resident Absent)<br />[] 3 V (visitor).</div><br /><br />Special Cases:<br /><br /><div class="i1">- The census field personnel (census enumerators, team leaders, controllers, etc.) will be enumerated as R.P. in their respective families.<br /><br />- The civil servants newly transferred to a new place will be enumerated as R.P. (code 1) in that place.<br /><br />- Wives who left to deliver at their parent's homes shall be counted as Visitor in their parent's household, and R.A. to their husband household, then circle number 2.<br /><br />- Pupils and students who live in boarding schools, hospitalized persons, convicts and people in re-education centers (jails, Bollé Center etc.), monks living in convents, will be enumerated in these institutions, as part of the institutional households.</div><br /><br />Situation of Residence for Nomadic Households<br /><br />Any nomadic household, grouped in a given location outside of his normal nomadic route will be considered as RP (code 1), even when the duration of stay is shorter than 6 months.<br /><br />However, a member of a household in the case noted above will be considered R.A. if he or she lives outside of the household. Likewise, an isolated member of a household living outside of his or her household will be considered as a visitor in his or her place of enumeration (where he or she will be seen).<br /><br />It should be specified that households living in their normal zone of nomadism will be treated as sedentary households, only the geographical area changes [sic].<br /></svar> Mali 1998: All persons This variable indicates the person's residence status (present or absent). 1 Resident present 2 Resident absent 3 Visitor Other Person Variables -- PERSON Year of birth <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A409 ML98A410 ML98A411 ML98A436" a="all">7. Age<br /><div class="i1">Day ____<br />Month ____<br />Year ____<br />Age _ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A407 ML98A408 ML98A409 ML98A410 ML98A411 ML98A436">6. and 7. Column P6 and P7: Date of birth and age<br /><br />The census enumerator should devote to this part a special care, since these questions are by themselves of utmost importance, since the age variable will play a major role in the analysis of the data collected.<br /></svar></p> <p><svar v="ML98A407 ML98A408 ML98A409" a="all">6. Column P6: Date of birth<br /><br />The date of birth in written in Column P6 for the household members who have an official document certifying their date of birth. This date of birth will be converted into integer number of years in Column P7, as explained in the example below. For the under-five children, one shall insist to obtain the proper date of birth.<br /></svar></p> <p><svar v="ML98A407 ML98A408 ML98A409 ML98A410 ML98A411 ML98A436">Principles for determining age from the correspondence tables:<br /><br />Determining the age shall be done, whenever possible, from a birth certificate. If this is true that in urban areas most children will have a birth certificate, this is however not the case in rural areas. Indeed, the high rate of illiteracy is a major handicap for the functioning of vital registration in rural areas. Therefore, in these areas, the age is expressed as the number of rainy seasons seen by the person.<br /><br />Furthermore, one should note that in rural areas, references are made to the lunar calendar, translated into vernacular languages.<br /><br />This is why a correspondence table was established, in order to allow the precise determination of the date of birth for children less than 10 years of age, according to the Gregorian calendar. This technique is based on the knowledge by the respondent of three elements:<br /><div class="i1">1. The number of rainy seasons lived by the child;<br />2. The name of the lunar month of the birth of the child;<br />3. The day of birth of the child in the lunar calendar.</div><br /><br />Example: A respondent tells you that his or her child has lived 6 rainy seasons, that he or she was born on Ramadan 27. What is the exact date of birth of the child?<br /><br /><span class="pg">[Page 23]</span><br /><br />Response: Refer to the correspondence table provided in Annex 2. Read the intersection of line "sounkalo" and Column "6 rainy seasons". You will find that the date of birth lies between February 23, 1993 and March 23, 1993. To obtain the precise date, add 26 (that is 27 - 1) to February 23, which gives 49. Then Subtract 28, corresponding to the number of days in February, and one obtains 21. The child is therefore born on March 21, 1993. Then, one can calculate the age of the child, as if he or she had a birth certificate. If the date of enumeration is March 16, 1998, the child's age is therefore: 4 years and 11 months, or 59 months.<br /><br />If the child is born on Ramadan 3, the precise date of birth will be obtained as 23+3-1 = 25, and the child's birth date would be February 25, 1993.<br /><br />In general, if the result of the computation for days is higher than the number of days in the months, one shall subtract this number from the result to obtain the corresponding date.<br /><br />If the first element of the calendar is known, and the two others are unknown, one could use, when needed, the approximate agricultural calendar (see Annex 3), for an estimation of the child's date of birth.<br /></svar> Mali 1998: All persons This variable indicates the person's year of birth. 1909 1909 or earlier 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 9999 Unknown Demographic Variables -- PERSON Unit for reporting age <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A409 ML98A410 ML98A411 ML98A436" a="all">7. Age<br /><div class="i1">Day ____<br />Month ____<br />Year ____<br />Age _ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A407 ML98A408 ML98A409 ML98A410 ML98A411 ML98A436">6. and 7. Column P6 and P7: Date of birth and age<br /><br />The census enumerator should devote to this part a special care, since these questions are by themselves of utmost importance, since the age variable will play a major role in the analysis of the data collected.<br /></svar></p> <p><svar v="ML98A407 ML98A408 ML98A409 ML98A410 ML98A411 ML98A436">Principles for determining age from the correspondence tables:<br /><br />Determining the age shall be done, whenever possible, from a birth certificate. If this is true that in urban areas most children will have a birth certificate, this is however not the case in rural areas. Indeed, the high rate of illiteracy is a major handicap for the functioning of vital registration in rural areas. Therefore, in these areas, the age is expressed as the number of rainy seasons seen by the person.<br /><br />Furthermore, one should note that in rural areas, references are made to the lunar calendar, translated into vernacular languages.<br /><br />This is why a correspondence table was established, in order to allow the precise determination of the date of birth for children less than 10 years of age, according to the Gregorian calendar. This technique is based on the knowledge by the respondent of three elements:<br /><div class="i1">1. The number of rainy seasons lived by the child;<br />2. The name of the lunar month of the birth of the child;<br />3. The day of birth of the child in the lunar calendar.</div><br /><br />Example: A respondent tells you that his or her child has lived 6 rainy seasons, that he or she was born on Ramadan 27. What is the exact date of birth of the child?<br /><br /><span class="pg">[Page 23]</span><br /><br />Response: Refer to the correspondence table provided in Annex 2. Read the intersection of line "sounkalo" and Column "6 rainy seasons". You will find that the date of birth lies between February 23, 1993 and March 23, 1993. To obtain the precise date, add 26 (that is 27 - 1) to February 23, which gives 49. Then Subtract 28, corresponding to the number of days in February, and one obtains 21. The child is therefore born on March 21, 1993. Then, one can calculate the age of the child, as if he or she had a birth certificate. If the date of enumeration is March 16, 1998, the child's age is therefore: 4 years and 11 months, or 59 months.<br /><br />If the child is born on Ramadan 3, the precise date of birth will be obtained as 23+3-1 = 25, and the child's birth date would be February 25, 1993.<br /><br />In general, if the result of the computation for days is higher than the number of days in the months, one shall subtract this number from the result to obtain the corresponding date.<br /><br />If the first element of the calendar is known, and the two others are unknown, one could use, when needed, the approximate agricultural calendar (see Annex 3), for an estimation of the child's date of birth.<br /></svar></p> <p><svar v="ML98A410 ML98A411 ML98A436" a="all">7. Column P7: Age<br /><br />Age will be determined for the individuals who know their date of birth, as well as for those who do not have any official document, with their month and year of birth.<br /><br />Ask for the age of the person, and write it in the two boxes located in Column P7. Do not forget to circle the number of the unit in which the age is expressed: 1 = Days, 2= Months, 3= Years.<br /><br />Age will be determined in integer number of years for the persons aged 1 year of more, and in integer number of months for the infants (less than 1 year or less than 12 months). For example:<br /><div class="i1">- A person aged 30 years and 8 months will be written:<br />- A person born in 1950 will be written: 1998 - 1950 = 48 years<br />- A baby aged 4 months and 28 days will be written.<br />- A new born baby aged 15 days will be written = 15 days</div><br /><br />Please pay special attention to the writing of the age of infants (less than 1 year of age). The age of these children shall be determined in integer number of months. Use, when possible, the seasonal calendar in Annex, for which the principle of use has been described in the "Date of birth" section.<br /><span class="pg">[Page 24]</span><br /><br />N.B. The age in integer number of years is obtained the following way:<br /><div class="i1">a) By subtracting the year of birth from 1998, if the birthday date (day and month) is already passed at time of the interview.<br /><br />b) By subtracting the year of birth from 1997, if the birthday date (day and month) is not yet passed at time of the interview.</div><br /></svar></p> <p><svar v="ML98A410 ML98A411 ML98A436" a="all">Remark: Providing the date of birth does not exclude mentioning the age.<br /></svar></p> <p><svar v="ML98A410 ML98A411 ML98A436">Persons who do not know their age:<br /><br />It might happen that during the census operations, that you encounter persons who do not know their age. You shall then help these persons to estimate their age, using one of the following methods:<br /><br /><div class="i1">Method 1: Historical calendar<br /><br />The historical calendar is a list of noticeable events (national or local), with their dates, which have a special influence on national life in general, or on the life of local communities in particular.<br /><br />The determination of the age of a person using the historical calendar is done by estimating his or her age at time of one of these events, and as a consequence to estimate his or her date of birth. Then one subtracts it from the census date in order to obtain an approximate age.<br /><br />For using this historical calendar, one shall proceed as such:<br /><br />- One starts with a rough estimation of his or her age, by looking at the person.<br /><br />- Let us assume "30 years". To obtain the departing point on the calendar, one adds 5 years to the age, that is, 30 + 5 = 35 years. Then one subtracts this number from the census year, that is: 1998 - 35 = 1963.<br /><br />- One then looks in the historical calendar for events located around 1963, and one quotes the event to the person, asking: "Do you remember this event?"<br /><br />a) If the answer is "yes", then one asks: how old were you at that time?<br />Assume that the person answers with certainty "10 years". Then this person is born around 1963 -- 10 = 1953, and his or her age is then = 1998 - 1953 = 45 years.<br /><br />b) If the answer is "no", then go to another event.<br /><br />Method 2: Classifying persons among themselves<br /><br />Some household members do not know accurately their age, but may remember being somewhat older or younger than other household members, or in the neighborhood.<br /><br />If one can determine with precision the age of one or several of these persons, then one could deduce an estimation or the age of the person who does not know his or her age.</div><br /></svar> Mali 1998: All persons This variable indicates the person's unit for age (day, month or year). This variable should be used with the variable ML98A411. 1 Day 2 Month 3 Year Demographic Variables -- PERSON Age in days, months or years <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A409 ML98A410 ML98A411 ML98A436" a="all">7. Age<br /><div class="i1">Day ____<br />Month ____<br />Year ____<br />Age _ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A407 ML98A408 ML98A409 ML98A410 ML98A411 ML98A436">6. and 7. Column P6 and P7: Date of birth and age<br /><br />The census enumerator should devote to this part a special care, since these questions are by themselves of utmost importance, since the age variable will play a major role in the analysis of the data collected.<br /></svar></p> <p><svar v="ML98A407 ML98A408 ML98A409 ML98A410 ML98A411 ML98A436">Principles for determining age from the correspondence tables:<br /><br />Determining the age shall be done, whenever possible, from a birth certificate. If this is true that in urban areas most children will have a birth certificate, this is however not the case in rural areas. Indeed, the high rate of illiteracy is a major handicap for the functioning of vital registration in rural areas. Therefore, in these areas, the age is expressed as the number of rainy seasons seen by the person.<br /><br />Furthermore, one should note that in rural areas, references are made to the lunar calendar, translated into vernacular languages.<br /><br />This is why a correspondence table was established, in order to allow the precise determination of the date of birth for children less than 10 years of age, according to the Gregorian calendar. This technique is based on the knowledge by the respondent of three elements:<br /><div class="i1">1. The number of rainy seasons lived by the child;<br />2. The name of the lunar month of the birth of the child;<br />3. The day of birth of the child in the lunar calendar.</div><br /><br />Example: A respondent tells you that his or her child has lived 6 rainy seasons, that he or she was born on Ramadan 27. What is the exact date of birth of the child?<br /><br /><span class="pg">[Page 23]</span><br /><br />Response: Refer to the correspondence table provided in Annex 2. Read the intersection of line "sounkalo" and Column "6 rainy seasons". You will find that the date of birth lies between February 23, 1993 and March 23, 1993. To obtain the precise date, add 26 (that is 27 - 1) to February 23, which gives 49. Then Subtract 28, corresponding to the number of days in February, and one obtains 21. The child is therefore born on March 21, 1993. Then, one can calculate the age of the child, as if he or she had a birth certificate. If the date of enumeration is March 16, 1998, the child's age is therefore: 4 years and 11 months, or 59 months.<br /><br />If the child is born on Ramadan 3, the precise date of birth will be obtained as 23+3-1 = 25, and the child's birth date would be February 25, 1993.<br /><br />In general, if the result of the computation for days is higher than the number of days in the months, one shall subtract this number from the result to obtain the corresponding date.<br /><br />If the first element of the calendar is known, and the two others are unknown, one could use, when needed, the approximate agricultural calendar (see Annex 3), for an estimation of the child's date of birth.<br /></svar></p> <p><svar v="ML98A410 ML98A411 ML98A436" a="all">7. Column P7: Age<br /><br />Age will be determined for the individuals who know their date of birth, as well as for those who do not have any official document, with their month and year of birth.<br /><br />Ask for the age of the person, and write it in the two boxes located in Column P7. Do not forget to circle the number of the unit in which the age is expressed: 1 = Days, 2= Months, 3= Years.<br /><br />Age will be determined in integer number of years for the persons aged 1 year of more, and in integer number of months for the infants (less than 1 year or less than 12 months). For example:<br /><div class="i1">- A person aged 30 years and 8 months will be written:<br />- A person born in 1950 will be written: 1998 - 1950 = 48 years<br />- A baby aged 4 months and 28 days will be written.<br />- A new born baby aged 15 days will be written = 15 days</div><br /><br />Please pay special attention to the writing of the age of infants (less than 1 year of age). The age of these children shall be determined in integer number of months. Use, when possible, the seasonal calendar in Annex, for which the principle of use has been described in the "Date of birth" section.<br /><span class="pg">[Page 24]</span><br /><br />N.B. The age in integer number of years is obtained the following way:<br /><div class="i1">a) By subtracting the year of birth from 1998, if the birthday date (day and month) is already passed at time of the interview.<br /><br />b) By subtracting the year of birth from 1997, if the birthday date (day and month) is not yet passed at time of the interview.</div><br /></svar></p> <p><svar v="ML98A410 ML98A411 ML98A436" a="all">Remark: Providing the date of birth does not exclude mentioning the age.<br /></svar></p> <p><svar v="ML98A410 ML98A411 ML98A436">Persons who do not know their age:<br /><br />It might happen that during the census operations, that you encounter persons who do not know their age. You shall then help these persons to estimate their age, using one of the following methods:<br /><br /><div class="i1">Method 1: Historical calendar<br /><br />The historical calendar is a list of noticeable events (national or local), with their dates, which have a special influence on national life in general, or on the life of local communities in particular.<br /><br />The determination of the age of a person using the historical calendar is done by estimating his or her age at time of one of these events, and as a consequence to estimate his or her date of birth. Then one subtracts it from the census date in order to obtain an approximate age.<br /><br />For using this historical calendar, one shall proceed as such:<br /><br />- One starts with a rough estimation of his or her age, by looking at the person.<br /><br />- Let us assume "30 years". To obtain the departing point on the calendar, one adds 5 years to the age, that is, 30 + 5 = 35 years. Then one subtracts this number from the census year, that is: 1998 - 35 = 1963.<br /><br />- One then looks in the historical calendar for events located around 1963, and one quotes the event to the person, asking: "Do you remember this event?"<br /><br />a) If the answer is "yes", then one asks: how old were you at that time?<br />Assume that the person answers with certainty "10 years". Then this person is born around 1963 -- 10 = 1953, and his or her age is then = 1998 - 1953 = 45 years.<br /><br />b) If the answer is "no", then go to another event.<br /><br />Method 2: Classifying persons among themselves<br /><br />Some household members do not know accurately their age, but may remember being somewhat older or younger than other household members, or in the neighborhood.<br /><br />If one can determine with precision the age of one or several of these persons, then one could deduce an estimation or the age of the person who does not know his or her age.</div><br /></svar> Mali 1998: All persons This variable indicates the person's number of age units. This variable should be used with the variable ML98A410. 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 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98+ 99 Unknown Demographic Variables -- PERSON Province or country of birth <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A412" a="all">8. Place of birth (district [<span class="lang">cercle</span>] or country)____<br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A412" a="all">8. Column P8: Place of birth, district or country<br /><br />This question aims at recording the place of birth of household members. For this, the census enumerator will ask a question to the household head, such: "Where was <span class="em">name</span> born?"<br /><span class="pg">[Page 26]</span><br /><br />a) The census enumerator will write down the name of the province of birth, if the person was born in Mali. But, be careful: when a respondent give you as place of birth the name of a village or town, make sure to first find out the administrative province in Mali to which this place belongs, before writing the answer.<br /><br />N.B.: If the person ignores the province, and if you cannot find it by yourself, write down the name of the region.<br /><br />b) When the person is born abroad, that is outside of Mali, write down the name of the country of birth (Senegal, Gambia, Guinea, France, etc.).<br /><br />Practical example:<br /><br />Mamadou Diarra was born in the village of Toyoge - district of Taga - Province of Djenne - Region of Mopti. The place of birth will be "Djenne", and will be written in Column P8.<br /></svar> Mali 1998: All persons This variable indicates the person's province or country of birth. 000 Mali, province unspecified 011 Kayes 012 Bafoulabe 013 Diema 014 Kenieba 015 Kita 016 Nioro 017 Yelimane 021 Koulikoro 022 Banamba 023 Dioila 024 Kangaba 025 Kati 026 Kolokani 027 Nara 031 Sikasso 032 Bougouni 033 Kadiolo 034 Kolondièba 035 Koutiala 036 Yanfolila 037 Yorosso 041 Segou 042 Baroueli 043 Bla 044 Macina 045 Niono 046 San 047 Tominian 051 Mopti 052 Bandiagara 053 Bankass 054 Djenne 055 Douentza 056 Koro 057 Tenenkou 058 Youwarou 061 Timbuktu 062 Dire 063 Goundam 064 Gourma-Rharous 065 Niafunke 071 Gao 072 Ansongo 073 Bourem 074 Menaka 081 Kidal 082 Tessalit 083 Abeibara 084 Tin-Essako 091 Bamako 101 Guinea 102 Cote d'Ivoire 103 Burkina Faso 104 Niger 105 Mauritania 106 Algeria 107 Senegal 108 Ghana 109 Gambia 110 Gabon 111 Nigeria 112 Benin 113 Togo 114 Liberia 115 Congo Brazzaville 118 Zaire (Congo Kinshasa) 119 Sierra Leone 120 Cameroon 199 Other African country 201 France 202 USA 299 Other country in the world 999 Unknown Nativity and Birthplace Variables -- PERSON Nationality <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A413" a="all">9. Nationality<br /><div class="i1">_ _ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A413" a="all">9. Column P9: Country of citizenship<br /><br />Here, the aim is to determine the nationality, for Malians and for the citizens of other countries. For this, the question to be asked to record the nationality will be: "What is the country of citizenship of name?"<br /><br />Then, write the declared answer in Column P9:<br /><div class="i1">a) Mali for Malians.<br />b) The name of the country for the foreigners (Côte d'Ivoire, Senegal, Cameroon, Togo, France etc...).</div><br /><br />Persons who enjoy a double nationality, those who have applied for a new nationality, or those whose nationality is ill defined, will be identified, case by case, by the most recent country of citizenship, or by the country of birth.<br /></svar> Mali 1998: All persons This variable indicates the person's nationality (country of citizenship). 000 Mali 101 Guinea 102 Cote d'Ivoire 103 Burkina Faso 104 Niger 105 Mauritania 107 Senegal 108 Ghana 110 Gabon 111 Nigeria 113 Togo 115 Congo Brazzaville 118 Zaire (Congo Kinshasa) 119 Sierra Leone 199 Other African country 201 France 202 USA 299 Other country in the world 999 Unknown Nativity and Birthplace Variables -- PERSON Disability / handicap <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A414" a="all">10. Disability / Handicap<br /><div class="i1">[] 00 Nothing<br />[] 01 Blindness<br />[] 02 Difficult seeing<br />[] 03 Leprosy<br />[] 04 Tryponosomiasis<br />[] 05 Tuberculosis<br />[] 06 Mental disorder<br />[] 07 Onchocerciasis<br />[] 08 Deaf, mute, deaf and mute<br />[] 09 Difficult hearing<br />[] 10 Disability in the limbs</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A414" a="all">10. Column P10: Handicaps<br /><br />This question deals with the main disease source of disability or handicap that the Malian population is suffering from. These diseases are labeled "Handicap" because they contribute to ill health of the individual, to a slower economic activity, and to a lower level of productivity. In some cases they may even prevent any production effort. For this, the question to be asked to the household head for each household member will be: "Does name have any disability or handicap?"<br /><br />The number corresponding to the given answer must be written in Column P10, while following the instructions given below [none was specified in this document].<br /></svar> Mali 1998: All persons This variable indicates the type of disability the person has. 00 None 01 Blindness 02 Difficult seeing 03 Leprosy 04 Tryponosomiasis 05 Tuberculosis 06 Mental disorder 07 Onchocerciasis 08 Deaf, mute, deaf and mute 09 Difficult hearing 10 Disability in the limbs Disability Variables -- PERSON Duration of residence <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A415" a="all">11. Duration of residence, in years<br /><div class="i1">_ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A415" a="all">11. Column P11: duration of residence<br /><br />This questions applies only to the household members who are Resident-Present (RP) or Resident-Absent (RA). The duration of residence is the length of the period during which the interviewed person has stayed in the place of the census.<br /><br />This duration is expressed in integer number of years. The question to be asked for asking about the duration of residence is: "For how many years has name been usually living here?"<br /><br /><span class="pg">[Page 27]</span><br /><br />Then write the answer as such:<br /><br />a. For the persons born in the same province as that of the census, and who have never lived in another province nor abroad, write "not applicable" as a hyphen (--) in Column P11.<br /><br />b. For the persons born in the same province as that of the census, but who have lived at least six (6) months outside of the province, the duration of residence will be the time spent in integer number of years since the last move into the province of the census.<br /><br />c. For the persons born outside of the province of the census or abroad, the duration of residence will be the time spent in integer number of years since the last move into the province of the census.<br /><br />Note that all durations of residence shall be counted in integer number of years.<br /><br />Example: write:<br /><div class="i1">00 -- persons whose duration of residence in the province is less than one year.<br />08 -- persons whose duration of residence in the province is equal to 8 years.<br />16 -- persons whose duration of residence in the province is equal to 16 years and 5 months, etc...</div><br /></svar> Mali 1998: Non-visitors [discrepancies: type I none; type II 2.6%] This variable indicates the person's duration of residence in the present province. 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 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Province or country of previous residence <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A417" a="all">13. [Respondent] has lived elsewhere more than 6 months?<br /><div class="i1">[] No<br />[] Yes - if yes,</div><br /><div class="i2">Where did [respondent] live immediately before this address? ____<br />Where does [respondent] currently live? ____</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A417" a="all">13. Column P13: place of previous residence<br /><br />For this, the question to be asked to the household head to determine this place is the following: "Did name ever live elsewhere for at least six months?"<br /><br />If the answer is no, write "no" in Column P13.<br />If the answer is yes, ask then: "Where did name live immediately before moving where he or she currently lives?"<br /><br />Write the name of the province if it is known, or the name of the region otherwise. Write the name of the country if the persons lived abroad.<br /></svar> Mali 1998: Non-visitors [discrepancies: type I none; type II 2.6%] This variable indicates the person's province or country of previous residence. 000 Mali, province unspecified 011 Kayes 012 Bafoulabe 013 Diema 014 Kenieba 015 Kita 016 Nioro 017 Yelimane 021 Koulikoro 022 Banamba 023 Dioila 024 Kangaba 025 Kati 026 Kolokani 027 Nara 031 Sikasso 032 Bougouni 033 Kadiolo 034 Kolondièba 035 Koutiala 036 Yanfolila 037 Yorosso 041 Segou 042 Baroueli 043 Bla 044 Macina 045 Niono 046 San 047 Tominian 051 Mopti 052 Bandiagara 053 Bankass 054 Djenne 055 Douentza 056 Koro 057 Tenenkou 058 Youwarou 061 Timbuktu 062 Dire 063 Goundam 064 Gourma-Rharous 065 Niafunke 071 Gao 072 Ansongo 073 Bourem 074 Menaka 081 Kidal 082 Tessalit 083 Abeibara 084 Tin-Essako 091 District Bamako 101 Guinea 102 Cote d'Ivoire 103 Burkina Faso 104 Niger 105 Mauritania 106 Algeria 107 Senegal 108 Ghana 109 Gambia 110 Gabon 111 Nigeria 112 Benin 113 Togo 114 Liberia 115 Congo Brazzaville 118 Zaire (Congo Kinshasa) 119 Sierra Leone 120 Cameroon 199 Other African country 201 France 202 USA 204 Russia 299 Other country in the world 998 Unknown 999 NIU (not in universe) Migration: Global Variables -- PERSON Father's survival <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A418" a="all">14. [Respondent's] father is alive<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 Unknown</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A418" a="all">14. Column P14: Father alive<br /><br />Ask the question the following way: "Is the father of name still alive?"<br /><br />Circle the number located left of the answer given:<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 Unknown</div><br /><br />NB: Whether or not the father is present in the household, if the father is alive, the answer is "yes", then circle code (1)<br /></svar> Mali 1998: All persons This variable indicates whether the person's father is still alive. 1 Yes 2 No 8 Do not know Fertility and Mortality Variables -- PERSON Mother's survival <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A419" a="all">15. [Respondent's] mother is alive<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 Unknown</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A419" a="all">15. Column P15: Mother alive<br /><br />The procedure is the same for the mother:<br /><br />Circle the number located left of the answer given:<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 Unknown</div><br /></svar> Mali 1998: All persons This variable indicates whether the person's mother is still alive. 1 Yes 2 No 8 Do not know Fertility and Mortality Variables -- PERSON Level of education <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423"><span class="em">Education</span><br /></svar></p> <p><svar v="ML98A420" a="all">16. Level of education<br /><div class="i1">[] 00 Not applicable<br />[] 01 Fundamental, first cycle<br />[] 02 Fundamental, second cycle<br />[] 03 Medersa, first cycle<br />[] 04 Medersa, second cycle<br />[] 05 Secondary school, general<br />[] 06 Secondary school, technical<br />[] 07 School for teachers<br />[] 08 Vocational school, grade 5 (CEPE)<br />[] 09 Vocational school, grade 9 (DEF)<br />[] 10 Vocational school, grade 12+ (BAC)<br />[] 11 University<br />[] 13 Post-university [code 12 is absent from the original form]<br />[] 14 Koranic school<br />[] 15 Center for adult literacy</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424" a="all"><span class="em">Column P16-P18: Level of education</span><br /><br />This group of questions provides together an idea on the level of education of the population.<br /><br />16. Column P16 -- the level of education attained<br />17. Column P17 -- highest grade completed<br />18. Column P18 -- highest diploma obtained<br /><br />The question to be asked to the household members aged 6 years and above will be: "Has name ever been to school?"<br />If no, then write (00) in Columns P16, P17 and P18.<br /><br />If yes, then write:<br /><div class="i1">In Column P16 le number corresponding to the level attained<br />In Column P17 the last grade attended in this level of education<br />In Column P18 the highest diploma obtained, while using the instructions at the bottom of the questionnaire.</div><br /></svar> Mali 1998: Persons age 6+ [discrepancies: type I none; type II 58.2%] This variable indicates the level of education attained by the person. 00 None 01 Fundamental, first cycle 02 Fundamental, second cycle 03 Medersa, first cycle 04 Medersa, second cycle 05 Secondary school, general 06 Secondary school, technical 07 School for teachers 08 Vocational school, grade 5 09 Vocational school, grade 9 10 Vocational school, grade 12+ 11 University 13 Post-university 14 Koranic school 15 Center for adult literacy 98 Unknown 99 NIU (not in universe) Education Variables -- PERSON Last grade completed <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423"><span class="em">Education</span><br /></svar></p> <p><svar v="ML98A422" a="all">17. Last school grade completed<br /><div class="i1">_ _ _ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424" a="all"><span class="em">Column P16-P18: Level of education</span><br /><br />This group of questions provides together an idea on the level of education of the population.<br /><br />16. Column P16 -- the level of education attained<br />17. Column P17 -- highest grade completed<br />18. Column P18 -- highest diploma obtained<br /><br />The question to be asked to the household members aged 6 years and above will be: "Has name ever been to school?"<br />If no, then write (00) in Columns P16, P17 and P18.<br /><br />If yes, then write:<br /><div class="i1">In Column P16 le number corresponding to the level attained<br />In Column P17 the last grade attended in this level of education<br />In Column P18 the highest diploma obtained, while using the instructions at the bottom of the questionnaire.</div><br /></svar> Mali 1998: Persons age 6+ who went to regular schools [discrepancies: none] This variable indicates the last grade completed by the person. This variable should be used with ML98A420 00 NIU (not in universe) 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) Education Variables -- PERSON Last school grade completed <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423"><span class="em">Education</span><br /></svar></p> <p><svar v="ML98A420" a="all">16. Level of education<br /><div class="i1">[] 00 Not applicable<br />[] 01 Fundamental, first cycle<br />[] 02 Fundamental, second cycle<br />[] 03 Medersa, first cycle<br />[] 04 Medersa, second cycle<br />[] 05 Secondary school, general<br />[] 06 Secondary school, technical<br />[] 07 School for teachers<br />[] 08 Vocational school, grade 5 (CEPE)<br />[] 09 Vocational school, grade 9 (DEF)<br />[] 10 Vocational school, grade 12+ (BAC)<br />[] 11 University<br />[] 13 Post-university [code 12 is absent from the original form]<br />[] 14 Koranic school<br />[] 15 Center for adult literacy</div><br /></svar></p> <p><svar v="ML98A422" a="all">17. Last school grade completed<br /><div class="i1">_ _ _ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424" a="all"><span class="em">Column P16-P18: Level of education</span><br /><br />This group of questions provides together an idea on the level of education of the population.<br /><br />16. Column P16 -- the level of education attained<br />17. Column P17 -- highest grade completed<br />18. Column P18 -- highest diploma obtained<br /><br />The question to be asked to the household members aged 6 years and above will be: "Has name ever been to school?"<br />If no, then write (00) in Columns P16, P17 and P18.<br /><br />If yes, then write:<br /><div class="i1">In Column P16 le number corresponding to the level attained<br />In Column P17 the last grade attended in this level of education<br />In Column P18 the highest diploma obtained, while using the instructions at the bottom of the questionnaire.</div><br /></svar> Mali 1998: Persons age 6+ who went to regular schools [discrepancies: none] This variable indicates the person's level of education and grades completed by the person. 0000 None 0101 Fundamental, first cycle, first year 0102 Fundamental, first cycle, second year 0103 Fundamental, first cycle, third year 0104 Fundamental, first cycle, fourth year 0105 Fundamental, first cycle, fifth year 0106 Fundamental, first cycle, sixth year 0107 Fundamental, first cycle, unknown year 0201 Fundamental, second cycle, seventh year 0202 Fundamental, second cycle, eighth year 0203 Fundamental, second cycle, ninth year 0204 Fundamental, second cycle, unknown year 0301 Medersa, first cycle, first year 0302 Medersa, first cycle, second year 0303 Medersa, first cycle, third year 0304 Medersa first cycle, fourth year 0305 Medersa first cycle, fifth year 0306 Medersa, first cycle, sixth year 0307 Medersa, first cycle, unknown year 0401 Medersa, second cycle, seventh year 0402 Medersa, second cycle, eighth year 0403 Medersa, second cycle, ninth year 0404 Medersa, second cycle, unknown year 0501 Secondary school, general, tenth year 0502 Secondary school, general, eleventh year 0503 Secondary school, general, twelfth year 0504 Secondary school, general, unknown year 0601 Secondary school, technical, tenth year 0602 Secondary school, technical, eleventh year 0603 Secondary school, technical, twelfth year 0604 Secondary school, technical, unknown year 0701 School for teachers, first year 0702 School for teachers, second year 0703 School for teachers, third year 0704 School for teachers, fourth year 0705 School for teachers, fifth year 0706 School for teachers, unknown year 0801 Vocational school, entry level CEP, first year 0802 Vocational school, entry level CEP, second year 0803 Vocational school, entry level CEP, third year 0804 Vocational school, entry level CEP, fourth year 0805 Vocational school, entry level CEP, unknown year 0901 Vocational school, entry level DEF, first year 0902 Vocational school, entry level DEF, second year 0903 Vocational school, entry level DEF, third year 0904 Vocational school, entry level DEF, fourth year 0905 Vocational school, entry level DEF, fifth year 0906 Vocational school, entry level DEF, unknown year 1001 Vocational school, entry level BAC+, first year 1002 Vocational school, entry level BAC+, second year 1003 Vocational school, entry level BAC+, third year 1004 Vocational school, entry level BAC+, fourth year 1005 Vocational school, entry level BAC+, fifth year 1006 Vocational school, entry level BAC+, unknown year 1101 University, first year 1102 University, second year 1103 University, third year 1104 University, fourth year 1105 University, fifth year 1106 University, sixth year 1107 University, seventh year 1108 University, unknown year 1301 Post-university, first or second year 1303 Post-university, third year 1304 Post-university, fourth year 1305 Post-university, fifth year 1306 Post-university, unknown year 1400 Koranic school 1500 Center for adult literacy 9998 Unknown 9999 NIU (not in universe) Education Variables -- PERSON Highest diploma <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423"><span class="em">Education</span><br /></svar></p> <p><svar v="ML98A423" a="all">18. Degree obtained [see bottom of this document]<br /><div class="i1">[] 00 None, Koranic school, not applicable<br />[] 01 Certificate primary school (CEPE)<br />[] 02 Diploma fundamental studies (DEF)<br />[] 03 Diploma, higher technician (BTS)<br />[] 05 Diploma, teaching aptitude (CAPE)<br />[] 06 Matrics, baccalaureate, first part<br />[] 07 Matrics, baccalaureate, second part<br />[] 08 Bachelors, license, etc.<br />[] 09 Masters, DEA, etc.<br />[] 10 First adult literacy campaign<br />[] 11 Second adult literacy campaigns</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424" a="all"><span class="em">Column P16-P18: Level of education</span><br /><br />This group of questions provides together an idea on the level of education of the population.<br /><br />16. Column P16 -- the level of education attained<br />17. Column P17 -- highest grade completed<br />18. Column P18 -- highest diploma obtained<br /><br />The question to be asked to the household members aged 6 years and above will be: "Has name ever been to school?"<br />If no, then write (00) in Columns P16, P17 and P18.<br /><br />If yes, then write:<br /><div class="i1">In Column P16 le number corresponding to the level attained<br />In Column P17 the last grade attended in this level of education<br />In Column P18 the highest diploma obtained, while using the instructions at the bottom of the questionnaire.</div><br /></svar> Mali 1998: Persons age 6+ who went to regular schools [discrepancies: type I none; type II 4.5%] This variable indicates the highest diploma obtained by the person. 00 None, Koranic school, not applicable 01 Certificate primary school 02 Diploma fundamental studies 03 Certificate vocational school 04 Diploma, higher technician 05 Certificate, teaching aptitude 06 Matrics, baccalaureate, first part 07 Matrics, baccalaureate, second part 08 Bachelors / license 09 Masters / DEA, etc. 10 First adult literacy campaign 11 Second adult literacy campaign 98 Unknown 99 NIU (not in universe) Education Variables -- PERSON School attendance <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A424" a="all"><span class="em">Schooling</span><br /></svar></p> <p><svar v="ML98A424" a="all">19. School attendance<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424" a="all"><span class="em">Column P16-P18: Level of education</span><br /><br />This group of questions provides together an idea on the level of education of the population.<br /><br />16. Column P16 -- the level of education attained<br />17. Column P17 -- highest grade completed<br />18. Column P18 -- highest diploma obtained<br /><br />The question to be asked to the household members aged 6 years and above will be: "Has name ever been to school?"<br />If no, then write (00) in Columns P16, P17 and P18.<br /><br />If yes, then write:<br /><div class="i1">In Column P16 le number corresponding to the level attained<br />In Column P17 the last grade attended in this level of education<br />In Column P18 the highest diploma obtained, while using the instructions at the bottom of the questionnaire.</div><br /></svar> Mali 1998: Persons age 6+ [discrepancies: type I none; type II 67.8%] This variable indicates whether the person has ever attended school. 1 Yes 2 No 9 NIU (not in universe) Education Variables -- PERSON Mother's tongue <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A425 ML98A426"><span class="em">Languages</span><br /></svar></p> <p><svar v="ML98A425" a="all">20. Maternal language<br /><div class="i1">[] 00 Not applicable<br />[] 01 Bambara, Malinke<br />[] 02 Peul, Foulfouble<br />[] 03 Sonrhai, Djerma<br />[] 04 Maraka, Soninke<br />[] 05 Kassonke<br />[] 06 Senoufo<br />[] 07 Dogon<br />[] 08 Mauritanian<br />[] 09 Tamacheq<br />[] 10 Bobo Dafing<br />[] 11 Minianka<br />[] 12 Haoussa<br />[] 13 Samogo<br />[] 14 Bozo<br />[] 15 Other Malian language<br />[] 16 Arabic<br />[] 17 Other African language<br />[] 18 Other foreign language</div><br /></svar> Mali 1998: Persons age 6+ [discrepancies: type I none; type II trace] This variable indicates the person's mother tongue. 00 NIU (not in universe) 01 Bambara, Malinke 02 Peul, Foulfoube 03 Sonrhaï, Djerma 04 Maraka, Soninke 05 Kassonke 06 Senoufo 07 Dogon 08 Mauritanian 09 Tamacheq 10 Bobo Dafing 11 Minianka 12 Haoussa 13 Samogo 14 Bozo 15 Other Malian language 16 Arabic 17 Other African language 18 Other foreign language 99 Unknown Ethnicity and Language Variables -- PERSON Language spoken <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A425 ML98A426"><span class="em">Languages</span><br /></svar></p> <p><svar v="ML98A426" a="all">21. Language spoken<br /><div class="i1">[] 00 Not applicable<br />[] 01 Bambara, Malinke<br />[] 02 Peul, Foulfouble<br />[] 03 Sonrhai, Djerma<br />[] 04 Maraka, Soninke<br />[] 05 Kassonke<br />[] 06 Senoufo<br />[] 07 Dogon<br />[] 08 Mauritanian<br />[] 09 Tamacheq<br />[] 10 Bobo Dafing<br />[] 11 Minianka<br />[] 12 Haoussa<br />[] 13 Samogo<br />[] 14 Bozo<br />[] 15 Other Malian language<br />[] 16 Arabic<br />[] 17 Other African language<br />[] 18 Other foreign language</div><br /></svar> Mali 1998: Persons age 6+ [discrepancies: type I none; type II trace] This variable indicates the language spoken by the person. 00 NIU (not in universe) 01 Bambara, Malinke 02 Peul, Foulfoube 03 Sonrhaï, Djerma 04 Maraka, Soninke 05 Kassonke 06 Senoufo 07 Dogon 08 Mauritanian 09 Tamacheq 10 Bobo Dafing 11 Minianka 12 Haoussa 13 Samogo 14 Bozo 15 Other Malian language 16 Arabic 17 Other African language 18 Other foreign language 99 Unknown Ethnicity and Language Variables -- PERSON Employment status <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">Activity type</span><br /></svar></p> <p><svar v="ML98A427" a="all">22. Employment status [see bottom of this document]<br /><div class="i1">[] 0 Not applicable<br />[] 1 Currently working<br />[] 2 Unemployed, has already worked<br />[] 3 Searching for first employment<br />[] 4 Housewife<br />[] 5 Student, pupil<br />[] 6 Living on private means<br />[] 7 Retired, elderly<br />[] 8 Does not work</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431" a="all"><span class="em">Columns P23-P25: Economic Activities</span><br /><br />Question P22 to P26 deal with the economic activity of the enumerated persons, that is: the occupation of the interviewed persons. For filling this question, please follow carefully the following guidelines.<br /><br />a. The questions shall be asked only to household members aged 6 years of more. For others, write a hyphen (-) in Columns P23 and P25; and write (0) in Columns P22, P24, and P26.<br /><br />b. To record the data on economic activity, the census enumerator shall refer to the reference period of one month (30 days) preceding the date of visit in the household.<br /><br />However, for the persons who work in the agricultural sector (beekeeping, husbandry, fishing, forestry, etc.), this reference period is extended to one year (12 months), because of the seasonal character of this type of employment. Indeed, works in agriculture are done during a well defined period during the year, which may not correspond with the census date.<br /></svar></p> <p><svar v="ML98A427" a="all">22. Column P22: type of economic activity<br /><br />This part deals with the relationship between a person and his or her current economic activity. Determining such information will lead to the distribution of the population between the active population and the non-active population.<br /><br />a. Active population<br /><br />The active population includes the employed active persons and the jobless (unemployed) persons.<br /><div class="i1">- Active, employed. The employed active population includes all the persons who were employed for any type of employment during the month preceding the census date. For workers in the agricultural sector (farming, husbandry, fishing, forestry, etc.), the reference period is extended to the year preceding the census.<br /><br />- Unemployed. The unemployed population includes the persons who were not employed during the month preceding the census, but who were looking for paid work or for a lucrative activity, including the persons who had never worked before.</div><br /><br />b. Inactive population<br /><br />The inactive population includes the persons who do not have any type of economic activity. It includes:<br /><div class="i1">- Housewives, and people in service, who do not have any economic activity, and who are doing house work at home. On the contrary, women who have an economic activity providing an income (petty trade, handicraft, etc.), and paid servants are classified in the active population.<br /><br />- Pupils and students. Persons of either sex who devote their time to studies, in a public or a private institution, and do not have any economic activity. For Koranic schools, and adult literacy schools, persons will be classified as either inactive or active, depending whether or not they devote more time to studies or to other lucrative activities.<br /><br />- Retired persons, or persons with independent private means: persons of either sex, who do not have any economic activity, and who perceive an income from a capital or from royalties, or a pension from previous activity.<br /><br />- Physically handicapped persons, whose physical status do not allow them to have an economic activity.</div><br /><br />The question to be asked to household members aged 6 years of more is:<br />"During the past month, that is from ___ to ___, what type of work was NAME doing?"<br /><br /><span class="pg">[Page 30]</span><br /><br />Write the number corresponding to the answer given, while following the guidelines given at the bottom of the page of the questionnaire:<br /><div class="i1">[] 0 Not applicable (person not concerned)<br />[] 1 Has worked<br />[] 2 Unemployed, has already worked<br />[] 3 Searching for first job<br />[] 4 Housewife<br />[] 5 Pupil, student<br />[] 6 Private means<br />[] 7 Retired, old age<br />[] 8 Does not work (idle life)</div><br /></svar> Mali 1998: Persons age 6+ [discrepancies: type I none; type II trace] This variable indicates the person's employment status. 0 NIU (not in universe) 1 Currently working 2 Unemployed, has already worked 3 Searching for first job 4 Housewife 5 Student, pupil 6 Living on private means 7 Retired, elderly 8 Does not work 9 Unknown Work Variables -- PERSON Main occupation <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">Activity type</span><br /></svar></p> <p><svar v="ML98A428" a="all">23. Main occupation<br /><div class="i1">_ _ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431" a="all"><span class="em">Columns P23-P25: Economic Activities</span><br /><br />Question P22 to P26 deal with the economic activity of the enumerated persons, that is: the occupation of the interviewed persons. For filling this question, please follow carefully the following guidelines.<br /><br />a. The questions shall be asked only to household members aged 6 years of more. For others, write a hyphen (-) in Columns P23 and P25; and write (0) in Columns P22, P24, and P26.<br /><br />b. To record the data on economic activity, the census enumerator shall refer to the reference period of one month (30 days) preceding the date of visit in the household.<br /><br />However, for the persons who work in the agricultural sector (beekeeping, husbandry, fishing, forestry, etc.), this reference period is extended to one year (12 months), because of the seasonal character of this type of employment. Indeed, works in agriculture are done during a well defined period during the year, which may not correspond with the census date.<br /></svar></p> <p><svar v="ML98A428" a="all">23. Column P23: Main occupation<br /><br />This is the main occupation of the interviewed person during the past month.<br /><br />For those who have worked during the reference month, the question will be: "What was the occupation of NAME?"<br /><br />For those without occupation during the reference period, the question will be: "What was the last occupation of NAME?"<br /><br />In Column P23, write down in words the declared occupation. Write a hyphen (--) for the inactive, the unemployed and the persons under age 6 years.<br /></svar> Mali 1998: Persons age 6+ and currently working [discrepancies: none] This variable indicates the person's main occupation (3-digit). 000 NIU (not in universe) 001 Farmer (cereals, rice, peanuts) 002 Vegetable gardener 003 Gardener 004 Fruit tree famer 005 Other agricultural worker not elsewhere classified 006 Animal farmer 007 Shepherd 008 Fisherman 009 Hunter 010 Other similar worker not elsewhere classified 201 Bricklayer 202 Worker 204 Other construction worker 301 Transportation company 302 Conveyor 303 Driver, light vehicle 304 Driver, heavy vehicle 305 Driver, agricultural machine 306 Driver, animal cart 307 Boat pilot (pirogue) 308 Other driver of transportation means not elsewhere classified 401 University professor, teacher higher education 402 Teacher, secondary school, general, technical, vocational 403 Teacher, secondary school, first cycle 404 Teacher, primary school 405 Teacher, pre-school, kindergarten 406 Teacher, specialized education 407 Other teaching personnel, and assimilated 501 Physician 505 Nurse 506 Midwife 507 Traditional birth attendant 510 Nurse aid 512 Veterinary 513 Pharmacist 515 Traditional healer, quack 516 Other health personnel, and assimilated, not elsewhere classified 601 Director and manager, for trade 602 Trader, salesman 603 Shopkeeper 604 Window dresser 605 Buyer 606 Seller 608 Canvasser 611 Sales representative 612 Other personnel in trade and sales and assimilated 613 Auto mechanics 614 Repairer, bicycle and motorcycle 615 Clockmaker / watchmaker 616 Electrician 617 Repairer, radio and television receiver 618 Hotel manager 619 Restaurant manager 622 Other personnel in services and assimilated not elsewhere classified 701 Drycleaner 702 Potter 703 Jeweler 704 Weaver 705 Blacksmith 706 Sculptor, painter 707 Other handicraft and assimilated, not elsewhere classified 708 Artist, traditional singer, story teller 711 Photograph 712 Tailor, dress maker 713 Other artists, not elsewhere classified 801 Director general (public sector) 802 Acting directors 803 Higher level manager 804 Middle level manager 805 Support staff 806 Other administrative personnel 810 Director general (private sector) 812 Higher level manager (private sector) 813 Middle level manager (private sector) 814 Support staff (private sector) 815 Other administrative personnel (private sector) 901 Solicitor 903 Lawyer / jurist 904 Lawyer / advocate 907 Other employee in law services 910 Koranic school teacher 915 Mosque preacher (Imam) 920 Traditional religious leader (Marabou) 930 Beggar 940 Other clergyman 945 Maid, servant 950 Boy, domestic 951 Undocumented 955 Other unskilled worker not elsewhere classified 999 Unknown Work: Occupation Variables -- PERSON Work status in main activity <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">Activity type</span><br /></svar></p> <p><svar v="ML98A429" a="all">24. Work status in main activity<br /><div class="i1">[] 0 Not applicable<br />[] 1 Self employed<br />[] 2 Employer<br />[] 3 Salaried, regular<br />[] 4 Salaried, temporary<br />[] 5 Apprentice, paid<br />[] 6 Apprentice, not paid<br />[] 7 Family help</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431" a="all"><span class="em">Columns P23-P25: Economic Activities</span><br /><br />Question P22 to P26 deal with the economic activity of the enumerated persons, that is: the occupation of the interviewed persons. For filling this question, please follow carefully the following guidelines.<br /><br />a. The questions shall be asked only to household members aged 6 years of more. For others, write a hyphen (-) in Columns P23 and P25; and write (0) in Columns P22, P24, and P26.<br /><br />b. To record the data on economic activity, the census enumerator shall refer to the reference period of one month (30 days) preceding the date of visit in the household.<br /><br />However, for the persons who work in the agricultural sector (beekeeping, husbandry, fishing, forestry, etc.), this reference period is extended to one year (12 months), because of the seasonal character of this type of employment. Indeed, works in agriculture are done during a well defined period during the year, which may not correspond with the census date.<br /></svar></p> <p><svar v="ML98A429" a="all">24. Column P24: Work status<br /><br />The work status in the main occupation of an active employed person is his or her situation with respect to other persons in her type of employment or her business.<br /><br />The question to be asked will be: "What was the status of name in his or her economic activity?" Depending on the answer given write in Column P24 the code corresponding to the answer, and according to the list provided below:<br /><div class="i1">[] 0 Not applicable (person not concerned)<br />[] 1 Self employed (persons working on his or her own, and not employing any salaried worker)<br />[] 2 Employer (any person who works on his or her own, and employing one or several salaried workers). Includes any active person employed in at least one salaried work.<br />[] 3 Permanent salaried (any person who works regularly and perceives a salary)<br />[] 4 Temporary salaried (any person receiving a salary, but not regularly)<br />[] 5 Apprentice, paid (person in training for an occupation, and paid)<br />[] 6 Apprentice, unpaid<br />[] 7 Family aid (person who works for free for a relative in the same household. Includes young adults and children who help their parents work in the fields or in other works).</div><br /></svar> Mali 1998: Persons age 6+ and currently working [discrepancies: none] This variable indicates the person’s class of worker. 0 NIU (not in universe) 1 Self employed 2 Employer 3 Salaried, regular 4 Salaried, temporary 5 Apprentice, paid 6 Apprentice, not paid 7 Family aid 9 Unknown Work Variables -- PERSON Branch of economic activity <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">Activity type</span><br /></svar></p> <p><svar v="ML98A430" a="all">25. Branch of economic activity<br /><div class="i1">_ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431" a="all"><span class="em">Columns P23-P25: Economic Activities</span><br /><br />Question P22 to P26 deal with the economic activity of the enumerated persons, that is: the occupation of the interviewed persons. For filling this question, please follow carefully the following guidelines.<br /><br />a. The questions shall be asked only to household members aged 6 years of more. For others, write a hyphen (-) in Columns P23 and P25; and write (0) in Columns P22, P24, and P26.<br /><br />b. To record the data on economic activity, the census enumerator shall refer to the reference period of one month (30 days) preceding the date of visit in the household.<br /><br />However, for the persons who work in the agricultural sector (beekeeping, husbandry, fishing, forestry, etc.), this reference period is extended to one year (12 months), because of the seasonal character of this type of employment. Indeed, works in agriculture are done during a well defined period during the year, which may not correspond with the census date.<br /></svar></p> <p><svar v="ML98A430" a="all">25. Column P25: Branch of economic activity<br /><br />The question to be asked to the household members aged 6 years of more will be: "In what type of activity was the occupation of name?" or "What was the type of economic activity, modern or traditional, in which name was occupied?"<br /><br />Write down in words what was doing the firm, the society, the institution or the employer of the concerned person.<br /><br />Example: restaurant, Pottery, farming, factory, shop, Office du Niger, Sonatam, Usine Sada Diallo [Factory], Total, Shell, public service, etc...<br /></svar> Mali 1998: Persons age 6+ and currently working [discrepancies: none] This variable indicates the person's industry. 01 Farming, animal husbandry, fishing, forestry 02 Handicraft 03 Mining industry 04 Manufacturing industry 05 Trade 06 Bank, insurance 07 Electricity, gas, water 08 Transportation, communication 09 Public administration 10 Private administration 11 Other services 12 Construction 98 Unknown 99 NIU (not in universe) Work: Industry Variables -- PERSON Agricultural activity <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431">For persons aged 6 years and above<br />[Questions 16-26]<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">Activity type</span><br /></svar></p> <p><svar v="ML98A431" a="all">26. Agricultural activity<br /><div class="i1">[] 0 Not applicable<br />[] 1 Cereals drop<br />[] 2 Cash crop<br />[] 3 Vegetable farming<br />[] 4 Fruit tree farming<br />[] 5 Animal husbandry<br />[] 6 Fishing<br />[] 7 Forestry<br />[] 8 Others</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A420 ML98A421 ML98A422 ML98A423 ML98A424 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431"><span class="em">1.2.2. Questions for persons aged 6 years and above </span><br /><br />This is the second group of questions, concerning the characteristics of household members. They concern only the persons aged 6 years and above.<br /><br />For persons aged less than 6 years (children), write (0) or (00) depending on column width in Columns P16 to P30.<br /></svar></p> <p><svar v="ML98A427 ML98A428 ML98A429 ML98A430 ML98A431" a="all"><span class="em">Columns P23-P25: Economic Activities</span><br /><br />Question P22 to P26 deal with the economic activity of the enumerated persons, that is: the occupation of the interviewed persons. For filling this question, please follow carefully the following guidelines.<br /><br />a. The questions shall be asked only to household members aged 6 years of more. For others, write a hyphen (-) in Columns P23 and P25; and write (0) in Columns P22, P24, and P26.<br /><br />b. To record the data on economic activity, the census enumerator shall refer to the reference period of one month (30 days) preceding the date of visit in the household.<br /><br />However, for the persons who work in the agricultural sector (beekeeping, husbandry, fishing, forestry, etc.), this reference period is extended to one year (12 months), because of the seasonal character of this type of employment. Indeed, works in agriculture are done during a well defined period during the year, which may not correspond with the census date.<br /></svar></p> <p><svar v="ML98A431" a="all">26. Column P26: Agricultural activity<br /><br />You will ask the question the following way: "What was the main type of agricultural activity done by name?"<br /><br />Write down the number corresponding to the answer given, while following the guideline written at the bottom of the page of the questionnaire.<br /><div class="i1">[] 0 Not applicable, person not concerned<br />[] 1 Food crops, cereals<br />[] 2 Cash crops, industrial agriculture<br />[] 3 Market gardening<br />[] 4 Tree growing, cultivation<br />[] 5 Animal husbandry<br />[] 6 Fishing<br />[] 7 Forestry<br />[] 8 Others</div><br /></svar> Mali 1998: Persons age 6+ who have ever worked in farming sector [discrepancies: none] This variable indicates the main type of agricultural activity done by the person. 0 NIU (not in universe) 1 Cereals crop 2 Cash crop 3 Vegetable farming 4 Fruit tree farming 5 Animal husbandry 6 Fishing 7 Forestry 8 Others 9 Unknown Work Variables -- PERSON Marital status <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A432 ML98A433">For persons aged 12 years and above<br />[Questions 27-28]<br /></svar></p> <p><svar v="ML98A432" a="all">27. Marital status<br /><div class="i1">[] 0 Not applicable<br />[] 1 Single<br />[] 2 Monogamous (man), first marriage (woman)<br />[] 3 Polygamous 2 women (man), second marriage (woman)<br />[] 4 Polygamous 3 women (man), third marriage (woman)<br />[] 5 Polygamous 4 women (man), fourth marriage (woman)<br />[] 6 Widowed<br />[] 7 Divorced or separated</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A432 ML98A433"><span class="em">1.2.3. Population aged 12 years and more</span><br /></svar></p> <p><svar v="ML98A432" a="all">27. Column P27: Marital status<br /><br />The marital status of a person is his or her current status with respect to marriage, given the laws and customs of his or her country. Its determination leads to the distribution of the population between: single (never married), married, widowed, divorced.<br /><br />The question to be asked to the household members, aged 12 year or more, on their marital status is: "Have you ever been married?"<br /><br />In Column P27, write down the number corresponding to the answer.<br /><div class="i1">[] 1 Single (never married person)<br />[] 2 Married man, one wife, or married woman, first marriage<br />[] 3 Married man, two wives (currently), or married woman, second marriage</div><br /><br /><span class="pg">[Page 32]</span><br /><br /><div class="i1">[] 4 Married man, three wives (currently), or married woman, third marriage<br />[] 5 Married man, four wives (currently), or married woman, fourth marriage<br />[] 6 Widowed person (person for whom the unique marriage or the last marriage was dissolved by the death of the spouse)<br />[] 7 Divorced or separated (person for whom the one marriage or the last marriage was dissolved by divorce)</div><br /><br />N.B. Marital status always refers to the current status of the person [at time of census], equivalent to his or her last situation.<br /><br />Particular cases:<br /><div class="i1">a. A man who was married to two wives, who lost the first by death and the second by divorce will be noted (7), that is "divorced".<br /><br />b. A man who was married to two wives, who lost one of the two by death, must be written as "married to one wife", which corresponds to code (2).<br /><br />c. A man who was married to three wives, who lost one first by divorce and another one by death, will be noted as married to one wife, and therefore will have code (2), since one marriage still exists.<br /><br />d. A man who was married to only one wife, who died shortly before, will be noted as "widowed", which corresponds to code (6).</div><br /></svar> Mali 1998: Persons age 12+ [discrepancies: type I none; type II trace] This variable indicates the person's marital status. 0 NIU (not in universe) 1 Single 2 Monogamous (man), first marriage (woman) 3 Polygamous 2 wives (man), second marriage (woman) 4 Polygamous 3 wives (man), third marriage (woman) 5 Polygamous 4 wives (man), fourth marriage (woman) 6 Widowed 7 Divorced or separated 8 Unknown Demographic Variables -- PERSON Literacy <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A432 ML98A433">For persons aged 12 years and above<br />[Questions 27-28]<br /></svar></p> <p><svar v="ML98A433" a="all">28. Literacy [see bottom of this document]<br /><div class="i1">[] 0 Not applicable<br />[] 1 Knows how to read and write in French (only)<br />[] 2 Knows how to read and write only in a national language<br />[] 3 Knows how to read and write only in another language<br />[] 4 Knows how to read and write in French and in one of the national languages<br />[] 5 Does not know to read or write</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A432 ML98A433"><span class="em">1.2.3. Population aged 12 years and more</span><br /></svar></p> <p><svar v="ML98A433" a="all">28. Column P28: Adult literacy<br /><br />The data to be gathered from this question will allow one to distinguish between the literate and the illiterate persons within the population.<br /><br />Definition: A literate person is a person able to read and write in any written language, and understand it, a short text related to daily life. An illiterate person will be a person who does not know how to read and write.<br /><br />As a consequence, a person who only knows to speak a language (for instance French), without being able to read it and to write it, shall not be considered as literate. Likewise, a person who only knows how to read and write his or her name, or numbers, and who does not know how to read and write a very elementary sentence, shall not be counted as literate.<br /><br />The question to be asked for gathering the ability to read and write, to household members aged 12 years of more is: "Does name know how to read and write in French, in Arabic, in any National language, or in any other written language?"<br /><br /><div class="i1">a. When the answer to the question asked is "yes", write down the number corresponding to the answer given, and according to the items listed at the bottom of the questionnaire.<br /><br />[] 1 Knows how to read and write in French only<br />[] 2 Knows how to read and write in one of the National languages<br />[] 3 Knows how to read and write in another language</div><br /><br /><span class="pg">[Page 33]</span><br /><br /><div class="i1">[] 4 Knows how to read and write in French and in a national language.<br /><br />b. When the answer to the question asked (--) in Column P28, this corresponds to a person who does not know how to read and write.</div><br /><br />N.B.: In Column P28, write (0) for all the persons aged less than 12 years, that is the persons who are not concerned by this question.<br /></svar> Mali 1998: Persons age 12+ [discrepancies: type I none; type II trace] This variable indicates whether the person is literate. 0 NIU (not in universe) 1 Knows how to read and write in French (only) 2 Knows how to read and write in a national language (only) 3 Knows how to read and write in another language (only) 4 Knows how to read and write in French and another language (only) 5 Does not know to read and write 8 Unknown Education Variables -- PERSON Number of children ever born <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A434 ML98A435">For women aged 12 years and above<br />[Questions 29-30]<br /></svar></p> <p><svar v="ML98A434" a="all">29. Total number of children ever born<br /><div class="i1">_ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A434 ML98A435"><span class="em">1.2.4. Women aged 12 years and above </span><br /></svar></p> <p><svar v="ML98A434" a="all">29. Column P29: Total number of children ever born<br /><br />This is the total number of live births born to women age 12 years or more. Ask the following question to the household head: "Overall, how many live births did name ever had?"<br /><br />A live birth is a delivery of a baby who cried or showed any sign of life after birth.<br /><br />In this total, shall be included all children born alive, whether legitimate or illegitimate, whether they are from the current marriage of the woman, or from a previous marriage, whether they are still alive or not at time of the census.<br /><br />Above all, make sure that all the following categories were captured:<br /><div class="i1">- Children who died in infancy<br />- Children who left their parental home<br />- Children born to the woman from a previous marriage</div><br /><br />On the contrary, the following categories shall not be included in the household questionnaire:<br /><div class="i1">- Stillbirths: that is, newborns who did not show any sign of life at time of birth.<br />- Adopted or fostered children and grand-sons or grand-daughters</div><br /></svar> Mali 1998: Females age 12+ [discrepancies: type I 15.1%; type II 1.4%] This variable indicates the number of children ever born to the person. 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+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of children surviving <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A424 ML98A425 ML98A426 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">Section B: Individual Characteristics</span><br /></svar></p> <p><svar v="ML98A434 ML98A435">For women aged 12 years and above<br />[Questions 29-30]<br /></svar></p> <p><svar v="ML98A435" a="all">30. Total number of children surviving<br /><div class="i1">_ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A434 ML98A435"><span class="em">1.2.4. Women aged 12 years and above </span><br /></svar></p> <p><svar v="ML98A435" a="all">30. Column P30: Children surviving<br /><br />Once the total number of children ever born is captured for each woman, ask the question on "number of children still alive".<br /><br />This question is also only for women aged 12 years or more. Ask the question as follows: "Among the children born alive declared in P29, how many are still alive?"<br /><br />Write down the corresponding number in Column P30.<br /><br />This total shall include all the children whether born from the current marriage or from a previous marriage. It must include the number of children living in the household as well as children living elsewhere.<br /></svar> Mali 1998: Females age 12+ [discrepancies: type I 15.1%; type II 1.4%] This variable indicates the number of children still surviving. 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+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Age in years <svar v="ML98A409 ML98A410 ML98A411 ML98A436" a="all">7. Age<br /><div class="i1">Day ____<br />Month ____<br />Year ____<br />Age _ _</div><br /></svar> <svar v="ML98A404 ML98A405 ML98A406 ML98A410 ML98A411 ML98A436 ML98A412 ML98A413 ML98A414 ML98A415 ML98A416 ML98A417 ML98A418 ML98A419 ML98A420 ML98A422 ML98A423 ML98A427 ML98A428 ML98A429 ML98A430 ML98A431 ML98A432 ML98A433 ML98A434 ML98A435"><span class="em">1.2.1. Questions for ALL Household Members</span><br /></svar></p> <p><svar v="ML98A407 ML98A408 ML98A409 ML98A410 ML98A411 ML98A436">6. and 7. Column P6 and P7: Date of birth and age<br /><br />The census enumerator should devote to this part a special care, since these questions are by themselves of utmost importance, since the age variable will play a major role in the analysis of the data collected.<br /></svar></p> <p><svar v="ML98A407 ML98A408 ML98A409 ML98A410 ML98A411 ML98A436">Principles for determining age from the correspondence tables:<br /><br />Determining the age shall be done, whenever possible, from a birth certificate. If this is true that in urban areas most children will have a birth certificate, this is however not the case in rural areas. Indeed, the high rate of illiteracy is a major handicap for the functioning of vital registration in rural areas. Therefore, in these areas, the age is expressed as the number of rainy seasons seen by the person.<br /><br />Furthermore, one should note that in rural areas, references are made to the lunar calendar, translated into vernacular languages.<br /><br />This is why a correspondence table was established, in order to allow the precise determination of the date of birth for children less than 10 years of age, according to the Gregorian calendar. This technique is based on the knowledge by the respondent of three elements:<br /><div class="i1">1. The number of rainy seasons lived by the child;<br />2. The name of the lunar month of the birth of the child;<br />3. The day of birth of the child in the lunar calendar.</div><br /><br />Example: A respondent tells you that his or her child has lived 6 rainy seasons, that he or she was born on Ramadan 27. What is the exact date of birth of the child?<br /><br /><span class="pg">[Page 23]</span><br /><br />Response: Refer to the correspondence table provided in Annex 2. Read the intersection of line "sounkalo" and Column "6 rainy seasons". You will find that the date of birth lies between February 23, 1993 and March 23, 1993. To obtain the precise date, add 26 (that is 27 - 1) to February 23, which gives 49. Then Subtract 28, corresponding to the number of days in February, and one obtains 21. The child is therefore born on March 21, 1993. Then, one can calculate the age of the child, as if he or she had a birth certificate. If the date of enumeration is March 16, 1998, the child's age is therefore: 4 years and 11 months, or 59 months.<br /><br />If the child is born on Ramadan 3, the precise date of birth will be obtained as 23+3-1 = 25, and the child's birth date would be February 25, 1993.<br /><br />In general, if the result of the computation for days is higher than the number of days in the months, one shall subtract this number from the result to obtain the corresponding date.<br /><br />If the first element of the calendar is known, and the two others are unknown, one could use, when needed, the approximate agricultural calendar (see Annex 3), for an estimation of the child's date of birth.<br /></svar></p> <p><svar v="ML98A410 ML98A411 ML98A436" a="all">7. Column P7: Age<br /><br />Age will be determined for the individuals who know their date of birth, as well as for those who do not have any official document, with their month and year of birth.<br /><br />Ask for the age of the person, and write it in the two boxes located in Column P7. Do not forget to circle the number of the unit in which the age is expressed: 1 = Days, 2= Months, 3= Years.<br /><br />Age will be determined in integer number of years for the persons aged 1 year of more, and in integer number of months for the infants (less than 1 year or less than 12 months). For example:<br /><div class="i1">- A person aged 30 years and 8 months will be written:<br />- A person born in 1950 will be written: 1998 - 1950 = 48 years<br />- A baby aged 4 months and 28 days will be written.<br />- A new born baby aged 15 days will be written = 15 days</div><br /><br />Please pay special attention to the writing of the age of infants (less than 1 year of age). The age of these children shall be determined in integer number of months. Use, when possible, the seasonal calendar in Annex, for which the principle of use has been described in the "Date of birth" section.<br /><span class="pg">[Page 24]</span><br /><br />N.B. The age in integer number of years is obtained the following way:<br /><div class="i1">a) By subtracting the year of birth from 1998, if the birthday date (day and month) is already passed at time of the interview.<br /><br />b) By subtracting the year of birth from 1997, if the birthday date (day and month) is not yet passed at time of the interview.</div><br /></svar></p> <p><svar v="ML98A410 ML98A411 ML98A436" a="all">Remark: Providing the date of birth does not exclude mentioning the age.<br /></svar></p> <p><svar v="ML98A410 ML98A411 ML98A436">Persons who do not know their age:<br /><br />It might happen that during the census operations, that you encounter persons who do not know their age. You shall then help these persons to estimate their age, using one of the following methods:<br /><br /><div class="i1">Method 1: Historical calendar<br /><br />The historical calendar is a list of noticeable events (national or local), with their dates, which have a special influence on national life in general, or on the life of local communities in particular.<br /><br />The determination of the age of a person using the historical calendar is done by estimating his or her age at time of one of these events, and as a consequence to estimate his or her date of birth. Then one subtracts it from the census date in order to obtain an approximate age.<br /><br />For using this historical calendar, one shall proceed as such:<br /><br />- One starts with a rough estimation of his or her age, by looking at the person.<br /><br />- Let us assume "30 years". To obtain the departing point on the calendar, one adds 5 years to the age, that is, 30 + 5 = 35 years. Then one subtracts this number from the census year, that is: 1998 - 35 = 1963.<br /><br />- One then looks in the historical calendar for events located around 1963, and one quotes the event to the person, asking: "Do you remember this event?"<br /><br />a) If the answer is "yes", then one asks: how old were you at that time?<br />Assume that the person answers with certainty "10 years". Then this person is born around 1963 -- 10 = 1953, and his or her age is then = 1998 - 1953 = 45 years.<br /><br />b) If the answer is "no", then go to another event.<br /><br />Method 2: Classifying persons among themselves<br /><br />Some household members do not know accurately their age, but may remember being somewhat older or younger than other household members, or in the neighborhood.<br /><br />If one can determine with precision the age of one or several of these persons, then one could deduce an estimation or the age of the person who does not know his or her age.</div><br /></svar> Mali 1998: All persons This variable indicates the person's age in completed years. 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 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98+ 99 Unknown Demographic Variables -- PERSON