Population and Housing Census 2011 DDI_BGD_2011_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. Population and Housing Census - IPUMS Subset 2011 PHC bd2011a (IPUMS Harmonized Subset) BGD_2011_PHC_v01_M_v7.6_A_IPUMS Bangladesh Bureau of Statistics IPUMS (c) Copyright 2011, Bangladesh Bureau of Statistics and Minnesota Population Center Bangladesh Bureau of Statistics Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.6 Version 7.6. The datasets contain selected variables from the original microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Geography: Global Variables -- HOUSEHOLD 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 Work Variables -- PERSON Geography: A-E Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Technical Person Variables -- PERSON Ethnicity and Language Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Work Variables -- PERSON Work: Industry Variables -- PERSON 12 a.m. to 6 a.m., March 15, 2011 March 15-19, 2011 (enumeration period) Bangladesh Upazila/Thana Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: Yes - Households: Person or persons related or unrelated, living together and taking food from the same kitchen. - Group quarters: The hostels, hospitals, clinics, jails, barracks or orphanages where a person or a group of persons spent the census night. Everyone who spent the night of March 14-15 in Bangladesh. The homeless or transient population found on the census night e.g. at railway stations, launch ghats, boats, majars, Mosques etc. Enumeration of this population was completed between 12 a.m. to 6 a.m. on March 15, 2011. Offices, residential hotels, religious institutions, educational institutions, and businesses where persons stay overnight. Overnight security guards are included here. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Bangladesh 2011 MICRODATA SOURCE: Bangladesh Bureau of Statistics SAMPLE SIZE (person records): 7205720. SAMPLE DESIGN: Systematic Sample of every 10th dwelling with a random start, drawn by Bureau of Statistics. The homeless or transient population found on the census night e.g. at railway stations, launch ghats, boats, majars, Mosques etc. Enumeration of this population was completed between 12 a.m. to 6 a.m. on March 15, 2011. Offices, residential hotels, religious institutions, educational institutions, and businesses where persons stay overnight. Overnight security guards are included here. Face-to-face [f2f] Long and short enumeration forms. de facto, CENSUS DAY: 12 a.m. to 6 a.m., March 15, 2011 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. Bangladesh Bureau of Statistics Steven Ruggles, Lara Cleveland, Rodrigo Lovaton, Sula Sarkar, Matthew Sobek, Derek Burk, Dan Ehrlich, Quinn Heimann, Jane Lee, and Nate Merrill. Integrated Public Use Microdata Series, International: Version 7.6 [dataset]. Minneapolis, MN: IPUMS, 2025. https://doi.org/10.18128/D020.V7.6 Researchers should also acknowledge the statistical agency that originally produced the data: Bangladesh, Bangladesh Bureau of Statistics. Population and Housing Census 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 bd2011a, 2025 BGD2011_PHC-H-H.dat Household records 1,654,631 ascii Minnesota Population Center Version 7.5, IPUMS sample BGD2011_PHC-P-H.dat Person records 7205720 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 Bangladesh, Division 1991 - 2011 [Level 1; consistent boundaries, GIS] GEO1_BD identifies the household's division (bibhag) within Bangladesh in all sample years. Divisions are the first level administrative units of the country. GEO1_BD is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_BD can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Bangladesh 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. 050010 Barisal 050020 Chittagong 050030 Dhaka 050040 Khulna 050050 Rajshahi, Rangpur 050060 Sylhet Geography: A-E Variables -- HOUSEHOLD Bangladesh, Division 2011 [Level 1, GIS] GEO1_BD2011 identifies the household's division (bibhag) within Bangladesh in 2011. Divisions are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_BD2011 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Bangladesh 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. 010 Barisal 020 Chittagong 030 Dhaka 040 Khulna 050 Rajshahi 055 Rangpur 060 Sylhet Geography: A-E Variables -- HOUSEHOLD Bangladesh, Zilla 1991 - 2011 [Level 2; consistent boundaries, GIS] GEO2_BD identifies the household's zila within Bangladesh in all sample years. Zilas are the second level administrative units of the country. GEO2_BD 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_BD can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Bangladesh 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. 050010001 Barguna, Patuakhali 050010002 Barisal 050010003 Bhola 050010004 Jhalokati 050010005 Pirojpur 050020001 Bandarban 050020002 Brahmanbaria 050020003 Chandpur 050020004 Chittagong 050020005 Comilla 050020006 Cox's Bazar 050020007 Feni 050020008 Khagrachhari 050020009 Lakshmipur 050020010 Noakhali 050020011 Rangamati 050030001 Dhaka, Gazipur, Narayanganj 050030002 Faridpur 050030003 Gopalganj 050030004 Jamalpur 050030005 Kishoreganj 050030006 Madaripur 050030007 Manikganj 050030008 Munshiganj 050030009 Mymensingh, Netrokona 050030010 Narsingdi 050030011 Rajbari 050030012 Shariatpur 050030013 Sherpur 050030014 Tangail 050040001 Bagerhat 050040002 Chuadanga 050040003 Jessore 050040004 Jhenaidaha 050040005 Khulna 050040006 Kushtia 050040007 Magura 050040008 Meherpur 050040009 Narail 050040010 Satkhira 050050001 Bogra 050050002 Joypurhat 050050003 Naogaon 050050004 Natore 050050005 Chapai Nababganj 050050006 Pabna 050050007 Rajshahi 050050008 Sirajganj 050050009 Dinajpur 050050010 Gaibandha 050050011 Kurigram 050050012 Lalmonirhat 050050013 Nilphamari 050050014 Panchagarh 050050015 Rangpur 050050016 Thakurgaon 050060001 Habiganj 050060002 Maulvi Bazar 050060003 Sunamganj 050060004 Sylhet Geography: A-E Variables -- HOUSEHOLD Bangladesh, Zilla 2011 [Level 2, GIS] GEO2_BD2011 identifies the household's zila (district) within Bangladesh in 2011. Zilas (districts) are the second level administrative units of the country, after divisions. A GIS map (in shapefile format), corresponding to GEO2_BD2011can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Bangladesh 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. 010004 Barguna 010006 Barisal 010009 Bhola 010042 Jhalokati 010078 Patuakhali 010079 Pirojpur 020003 Bandarban 020012 Brahmanbaria 020013 Chandpur 020015 Chittagong 020019 Comilla 020022 Cox's Bazar 020030 Feni 020046 Khagrachhari 020051 Lakshmipur 020075 Noakhali 020084 Rangamati 030026 Dhaka 030029 Faridpur 030033 Gazipur 030035 Gopalganj 030039 Jamalpur 030048 Kishoreganj 030054 Madaripur 030056 Manikganj 030059 Munshiganj 030061 Mymensingh 030067 Narayanganj 030068 Narsingdi 030072 Netrokona 030082 Rajbari 030086 Shariatpur 030089 Sherpur 030093 Tangail 040001 Bagerhat 040018 Chuadanga 040041 Jessore 040044 Jhenaidaha 040047 Khulna 040050 Kushtia 040055 Magura 040057 Meherpur 040065 Narail 040087 Satkhira 050010 Bogra 050038 Joypurhat 050064 Naogaon 050069 Natore 050070 Chapai Nababganj 050076 Pabna 050081 Rajshahi 050088 Sirajganj 055027 Dinajpur 055032 Gaibandha 055049 Kurigram 055052 Lalmonirhat 055073 Nilphamari 055077 Panchagarh 055085 Rangpur 055094 Thakurgaon 060036 Habiganj 060058 Maulvi Bazar 060090 Sunamganj 060091 Sylhet Geography: A-E Variables -- HOUSEHOLD Bangladesh, Upazilla 2011 [Level 3, GIS] GEO3_BD2011 identifies the household's upazila within Bangladesh in 2011. Upazilas are the third level administrative units of the country, after divisions and zilas. A GIS map (in shapefile format), corresponding to GEO3_BD2011 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Bangladesh 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. 010004009 Amtali 010004019 Bamna 010004028 Barguna Sadar 010004047 Betagi 010004085 Patharghata 010006002 Agailjhara 010006003 Babuganj 010006007 Bakerganj 010006010 Banaripara 010006032 Gaurnadi 010006036 Hizla 010006051 Barisal Sadar 010006062 Mehendiganj 010006069 Muladi 010006094 Wazirpur 010009018 Bhola Sadar 010009021 Burhanuddin 010009025 Char Fasson 010009029 Daulat Khan 010009054 Lalmohan 010009065 Manpura 010009091 Tazumuddin 010042040 Jhalokati Sadar 010042043 Kanthalia 010042073 Nalchity 010042084 Rajapur 010078038 Bauphal 010078052 Dashmina 010078055 Dumki 010078057 Galachipa 010078066 Kala Para 010078076 Mirzaganj 010078095 Patuakhali Sadar 010079014 Bhandaria 010079047 Kawkhali 010079058 Mathbaria 010079076 Nazirpur 010079080 Pirojpur Sadar 010079087 Nesarabad (Swarupkati) 010079090 Zianagar 020003004 Alikadam 020003014 Bandarban Sadar 020003051 Lama 020003073 Naikhongchhari 020003089 Rowangchhari 020003091 Ruma 020003095 Thanchi 020012002 Akhaura 020012004 Banchharampur 020012007 Bijoynagar 020012013 Brahmanbaria Sadar 020012033 Ashuganj 020012063 Kasba 020012085 Nabinagar 020012090 Nasirnagar 020012094 Sarail 020013022 Chandpur Sadar 020013045 Faridganj 020013047 Haim Char 020013049 Hajiganj 020013058 Kachua 020013076 Matlab Dakshin 020013079 Matlab Uttar 020013095 Shahrasti 020015004 Anowara 020015006 Bayejid Bostami 020015008 Banshkhali 020015010 Bakalia 020015012 Boalkhali 020015018 Chandanaish 020015019 Chandgaon 020015020 Chittagong Port 020015028 Double Mooring 020015033 Fatikchhari 020015035 Halishahar 020015037 Hathazari 020015041 Kotwali 020015043 Khulshi 020015047 Lohagara 020015053 Mirsharai 020015055 Pahartali 020015057 Panchlaish 020015061 Patiya 020015065 Patenga 020015070 Rangunia 020015074 Raozan 020015078 Sandwip 020015082 Satkania 020015086 Sitakunda 020019009 Barura 020019015 Brahman Para 020019018 Burichang 020019027 Chandina 020019031 Chauddagram 020019033 Comilla Sadar Dakhin 020019036 Daudkandi 020019040 Debidwar 020019054 Homna 020019067 Comilla Adarsha Sadar 020019072 Laksam 020019074 Manoharganj 020019075 Meghna 020019081 Muradnagar 020019087 Nangalkot 020019094 Titas 020022016 Chakaria 020022024 Cox's Bazar Sadar 020022045 Kutubdia 020022049 Maheshkhali 020022056 Pekua 020022066 Ramu 020022090 Teknaf 020022094 Ukhia 020030014 Chhagalnaiya 020030025 Daganbhuiyan 020030029 Feni Sadar 020030041 Fulgazi 020030051 Parshuram 020030094 Sonagazi 020046043 Dighinala 020046049 Khagrachhari Sadar 020046061 Lakshmichhari 020046065 Mahalchhari 020046067 Manikchhari 020046070 Matiranga 020046077 Panchhari 020046080 Ramgarh 020051033 Kamalnagar 020051043 Lakshmipur Sadar 020051058 Roypur 020051065 Ramganj 020051073 Ramgati 020075007 Begumganj 020075010 Chatkhil 020075021 Companiganj 020075036 Hatiya 020075047 Kabirhat 020075080 Senbagh 020075083 Sonaimuri 020075085 Subarna Char 020075087 Noakhali Sadar (Sudharam) 020084007 Baghai Chhari 020084021 Barkal 020084025 Kawkhali (Betbunia) 020084029 Belai Chhari 020084036 Kaptai 020084047 Jurai Chhari 020084058 Langadu 020084075 Maniarchar 020084078 Rajasthali 020084087 Rangamati Sadar 030026002 Adabor 030026004 Badda 030026005 Bangshal 030026008 Cantonment 030026009 Chak Bazar 030026010 Dakshinkhan 030026011 Darus Salam 030026012 Demra 030026014 Dhamrai 030026016 Dhanmondi 030026018 Dohar 030026024 Gendaria 030026026 Gulshan 030026028 Hazaribagh 030026029 Jatrabari 030026030 Kafrul 030026032 Kadam Tali 030026033 Kalabagan 030026034 Kamrangir Char 030026036 Khilgaon 030026037 Khilkhet 030026038 Keraniganj 030026040 Kotwali 030026042 Lalbagh 030026048 Mirpur 030026050 Mohammadpur 030026054 Motijheel 030026062 Nawabganj 030026063 New Market 030026064 Pallabi 030026065 Paltan 030026066 Ramna 030026067 Rampura 030026068 Sabujbagh 030026072 Savar 030026074 Shah Ali 030026075 Shahbag 030026076 Shyampur 030026080 Sher-E-Bangla Nagar 030026088 Sutrapur 030026090 Tejgaon 030026092 Tejgaon Industrial Area 030026093 Turag 030026095 Uttara, Bimanbandar 030026096 Uttar Khan 030029003 Alfadanga 030029010 Bhanga 030029018 Boalmari 030029021 Char Bhadrasan 030029047 Faridpur Sadar 030029056 Madhukhali 030029062 Nagarkanda 030029084 Sadarpur 030029090 Saltha 030033030 Gazipur Sadar 030033032 Kaliakair 030033034 Kaliganj 030033036 Kapasia 030033086 Sreepur 030035032 Gopalganj Sadar 030035043 Kashiani 030035051 Kotalipara 030035058 Muksudpur 030035091 Tungipara 030039007 Bakshiganj 030039015 Dewanganj 030039029 Islampur 030039036 Jamalpur Sadar 030039058 Madarganj 030039061 Melandaha 030039085 Sarishabari 030048002 Austagram 030048006 Bajitpur 030048011 Bhairab 030048027 Hossainpur 030048033 Itna 030048042 Karimganj 030048045 Katiadi 030048049 Kishoreganj Sadar 030048054 Kuliar Char 030048059 Mithamain 030048076 Nikli 030048079 Pakundia 030048092 Tarail 030054040 Kalkini 030054054 Madaripur Sadar 030054080 Rajoir 030054087 Shib Char 030056010 Daulatpur 030056022 Ghior 030056028 Harirampur 030056046 Manikganj Sadar 030056070 Saturia 030056078 Shibalaya 030056082 Singair 030059024 Gazaria 030059044 Lohajang 030059056 Munshiganj Sadar 030059074 Serajdikhan 030059084 Sreenagar 030059094 Tongibari 030061013 Bhaluka 030061016 Dhobaura 030061020 Fulbaria 030061022 Gaffargaon 030061023 Gauripur 030061024 Haluaghat 030061031 Ishwarganj 030061052 Mymensingh Sadar 030061065 Muktagachha 030061072 Nandail 030061081 Phulpur 030061094 Trishal 030067002 Araihazar 030067004 Sonargaon 030067006 Bandar 030067058 Narayanganj Sadar 030067068 Rupganj 030068007 Belabo 030068052 Manohardi 030068060 Narsingdi Sadar 030068063 Palash 030068064 Roypura 030068076 Shibpur 030072004 Atpara 030072009 Barhatta 030072018 Durgapur 030072038 Khaliajuri 030072040 Kalmakanda 030072047 Kendua 030072056 Madan 030072063 Mohanganj 030072074 Netrokona Sadar 030072083 Purbadhala 030082007 Baliakandi 030082029 Goalandaghat 030082047 Kalukhali 030082073 Pangsha 030082076 Rajbari Sadar 030086014 Bhedarganj 030086025 Damudya 030086036 Gosairhat 030086065 Naria 030086069 Shariatpur Sadar 030086094 Zanjira 030089037 Jhenaigati 030089067 Nakla 030089070 Nalitabari 030089088 Sherpur Sadar 030089090 Sreebardi 030093009 Basail 030093019 Bhuapur 030093023 Delduar 030093025 Dhanbari 030093028 Ghatail 030093038 Gopalpur 030093047 Kalihati 030093057 Madhupur 030093066 Mirzapur 030093076 Nagarpur 030093085 Sakhipur 030093095 Tangail Sadar 040001008 Bagerhat Sadar 040001014 Chitalmari 040001034 Fakirhat 040001038 Kachua 040001056 Mollahat 040001058 Mongla 040001060 Morrelganj 040001073 Rampal 040001077 Sarankhola 040018007 Alamdanga 040018023 Chuadanga Sadar 040018031 Damurhuda 040018055 Jiban Nagar 040041004 Abhaynagar 040041009 Bagher Para 040041011 Chaugachha 040041023 Jhikargachha 040041038 Keshabpur 040041047 Jessore Sadar 040041061 Manirampur 040041090 Sharsha 040044014 Harinakunda 040044019 Jhenaidaha Sadar 040044033 Kaliganj 040044042 Kotchandpur 040044071 Maheshpur 040044080 Shailkupa 040047012 Batiaghata 040047017 Dacope 040047021 Daulatpur 040047030 Dumuria 040047040 Dighalia 040047045 Khalishpur 040047048 Khan Jahan Ali 040047051 Khulna Sadar 040047053 Koyra 040047064 Paikgachha 040047069 Phultala 040047075 Rupsa 040047085 Sonadanga 040047094 Terokhada 040050015 Bheramara 040050039 Daulatpur 040050063 Khoksa 040050071 Kumarkhali 040050079 Kushtia Sadar 040050094 Mirpur 040055057 Magura Sadar 040055066 Mohammadpur 040055085 Shalikha 040055095 Sreepur 040057047 Gangni 040057060 Mujib Nagar 040057087 Meherpur Sadar 040065028 Kalia 040065052 Lohagara 040065076 Narail Sadar 040087004 Assasuni 040087025 Debhata 040087043 Kalaroa 040087047 Kaliganj 040087082 Satkhira Sadar 040087086 Shyamnagar 040087090 Tala 050010006 Adamdighi 050010020 Bogra Sadar 050010027 Dhunat 050010033 Dhupchanchia 050010040 Gabtali 050010054 Kahaloo 050010067 Nandigram 050010081 Sariakandi 050010085 Shajahanpur 050010088 Sherpur 050010094 Shibganj 050010095 Sonatola 050038013 Akkelpur 050038047 Joypurhat Sadar 050038058 Kalai 050038061 Khetlal 050038074 Panchbibi 050064003 Atrai 050064006 Badalgachhi 050064028 Dhamoirhat 050064047 Manda 050064050 Mahadebpur 050064060 Naogaon Sadar 050064069 Niamatpur 050064075 Patnitala 050064079 Porsha 050064085 Raninagar 050064086 Sapahar 050069009 Bagati Para 050069015 Baraigram 050069041 Gurudaspur 050069044 Lalpur 050069063 Natore Sadar 050069091 Singra 050070018 Bholahat 050070037 Gomastapur 050070056 Nachole 050070066 Chapai Nawabganj Sadar 050070088 Shibganj 050076005 Atgharia 050076016 Bera 050076019 Bhangura 050076022 Chatmohar 050076033 Faridpur 050076039 Ishwardi 050076055 Pabna Sadar 050076072 Santhia 050076083 Sujanagar 050081010 Bagha 050081012 Baghmara 050081022 Boalia 050081025 Charghat 050081031 Durgapur 050081034 Godagari 050081040 Matihar 050081053 Mohanpur 050081072 Paba 050081082 Puthia 050081085 Rajpara 050081090 Shah Makhdum 050081094 Tanore 050088011 Belkuchi 050088027 Chauhali 050088044 Kamarkhanda 050088050 Kazipur 050088061 Royganj 050088067 Shahjadpur 050088078 Sirajganj Sadar 050088089 Tarash 050088094 Ullah Para 055027010 Birampur 055027012 Birganj 055027017 Biral 055027021 Bochaganj 055027030 Chirirbandar 055027038 Fulbari 055027043 Ghoraghat 055027047 Hakimpur 055027056 Kaharole 055027060 Khansama 055027064 Dinajpur Sadar 055027069 Nawabganj 055027077 Parbatipur 055032021 Fulchhari 055032024 Gaibandha Sadar 055032030 Gobindaganj 055032067 Palashbari 055032082 Sadullapur 055032088 Saghatta 055032091 Sundarganj 055049006 Bhurungamari 055049008 Char Rajibpur 055049009 Chilmari 055049018 Phulbari 055049052 Kurigram Sadar 055049061 Nageshwari 055049077 Rajarhat 055049079 Raumari 055049094 Ulipur 055052002 Aditmari 055052033 Hatibandha 055052039 Kaliganj 055052055 Lalmonirhat Sadar 055052070 Patgram 055073012 Dimla 055073015 Domar 055073036 Jaldhaka 055073045 Kishoreganj 055073064 Nilphamari Sadar 055073085 Saidpur 055077004 Atwari 055077025 Boda 055077034 Debiganj 055077073 Panchagarh Sadar 055077090 Tentulia 055085003 Badarganj 055085027 Gangachara 055085042 Kaunia 055085049 Rangpur Sadar 055085058 Mitha Pukur 055085073 Pirgachha 055085076 Pirganj 055085092 Taraganj 055094008 Baliadangi 055094051 Haripur 055094082 Pirganj 055094086 Ranisankail 055094094 Thakurgaon Sadar 060036002 Ajmiriganj 060036005 Bahubal 060036011 Baniachong 060036026 Chunarughat 060036044 Habiganj Sadar 060036068 Lakhai 060036071 Madhabpur 060036077 Nabiganj 060058014 Barlekha 060058035 Juri 060058056 Kamalganj 060058065 Kulaura 060058074 Maulvi Bazar Sadar 060058080 Rajnagar 060058083 Sreemangal 060090018 Bishwambarpur 060090023 Chhatak 060090027 Dakhin Sunamganj 060090029 Derai 060090032 Dharampasha 060090033 Dowarabazar 060090047 Jagannathpur 060090050 Jamalganj 060090086 Sulla 060090089 Sunamganj Sadar 060090092 Tahirpur 060091008 Balaganj 060091017 Beani Bazar 060091020 Bishwanath 060091027 Companiganj 060091031 Dakhin Surma 060091035 Fenchuganj 060091038 Golabganj 060091041 Gowainghat 060091053 Jaintiapur 060091059 Kanaighat 060091062 Sylhet Sadar 060091094 Zakiganj Geography: A-E Variables -- HOUSEHOLD DHS-IPUMS-I Bangladesh regions, 1991-2018 [consistent boundaries, GIS] DHS_IPUMSI_BD provides geographic codes for Bangladesh 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_BD indicate the major administrative unit in which the household was enumerated or surveyed. GIS shapefiles for Bangladesh can be downloaded here. 1 Barisal 2 Chittagong and Sylhet 3 Dhaka and Mymensingh 4 Khulna 5 Rajshahi and Rangpur 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 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 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 Bangladesh 2011: All records 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 Bangladesh 2011: All records This variable indicates the number of persons in 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 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 Technical Household Variables -- HOUSEHOLD Dwelling created by splitting apart a large dwelling or household Bangladesh 2011: All records This variable indicates if the dwelling was created by splitting apart a large dwelling or household. 0 No problem 1 Yes: households within a large dwelling were split apart into separate dwellings 2 Yes: persons within a large household were split apart into separate dwellings Technical Household Variables -- HOUSEHOLD Urban-rural (RMO code) <span class="h1">[Bangladesh 2011 enumeration form - short version.]</span></p> <p><svar v="BD11A028" a="all">RMO code<br /><div class="i1">[] 1 Rural<br />[] 2 <span class="lang">Pourashava</span><br />[] 3 <span class="lang">Upazila</span> headquarter<br />[] 5 Cantonment board<br />[] 9 City corporation</div><br /></svar> In this census digital maps maintaining 1.5000 scale for urban area and 1.10000 scale for rural area have been prepared after having image from the air. In those maps identification boundary for <span class="lang">mauza</span> and within <span class="lang">mauza</span> villages and dividing villages enumeration areas have been clearly done for rural area. In urban area identification boundary for <span class="lang">mahallah</span> and dividing <span class="lang">mahallah</span> enumeration areas have been shown. Bangladesh 2011: All households This variable indicates whether the household is in an urban or rural area (RMO code). 1 Rural 2 Pourashava 3 Upazila headquarter 5 Cantonment board 9 City corporation Geography: A-E Variables -- HOUSEHOLD Floating population <svar v="BD11A032" a="all">3. Floating? <br /><div class="i1">[] Yes<br />[] No</div><br /></svar></p> <p><svar v="BD11A032">Q3. Floating?: to enumerate the floating population put x inside the 'yes' box and fill-in information of one individual in each line of the individual module. If it is not a floating population mark the 'no' box.<br /></svar> <span class="em">Question -3. Floating</span> <br />Floating population will be counted using the same questionnaire. Enter cross symbol in the 'yes' [X] box to count floating population and for enumeration of people living in the household enter cross symbol in the 'no' [X] box. <br />Enter address where the floating population is found in the blank space of Quest-1a.</p> <div class="i1">Example: Kamlapur Rail station<br />Kamlapur, Dhaka</div><p>To count floating population no need to fill out any Questions in the household module. Enter information of every individual floating population in each line of individual module. If the floating population is more than 10, fill out each page for every 10 persons. At the same time fill out Ques- 1b. Don't fill out Ques- 2a and Ques- 4 to 11b for floating population. Count the boarders living in the residential hotels as floating population with the help of hotel administration. Bangladesh 2011: All households This variable indicates that a household is part of the floating population. 1 Yes 2 No Other Household Variables -- HOUSEHOLD Type of household <svar v="BD11A033" a="all">4. Type of household<br /><div class="i1">[] General<br />[] Institutional<br />[] Others</div><br /></svar></p> <p><svar v="BD11A033">Q4. Type of household: if the housing unit is used for residential purposes only then put x inside the general box. If it is used for jailkhana, orphanage, hostel, hospital, clinic, or barrack, then put x inside institutional box and else put x inside others box.<br /></svar> <svar v="BD11A033" a="all"><span class="em">Question -4. Type of Household:</span><br />Households are three types: Dwelling household, Institutional household and Other household.<br /><div class="i1">Dwelling Household: Household live mainly for dwelling purpose will be considered as Dwelling Household.<br />Institutional Household: Orphange, Hospital, Clinic, Hotel, Jail, Barack will be considered as Institutional Household. For patients in the hospital and clinics a list will be prepared with the help Hospital Authorities and necessary questionnaires will be filled out. But doctors, nurses and other employee those who reside out side will be enumerated in their respective households.<br />Other Household: Peolple living in the mess, shops and trading centres, offices combinedly form household will be considered as other household. Considering the above enter cross symbol in the appropriate box</div><br /></svar> Bangladesh 2011: Permanent households [discrepancies: none] This variable indicates the type of household. 1 General 2 Institutional 3 Others 9 NIU (not in universe) Group Quarters Variables -- HOUSEHOLD Type of house <svar v="BD11A035" a="all">6. Type of house<br /><div class="i1">[] Pucka<br />[] Semi-pucka<br />[] Kutcha<br />[] Jhupri</div><br /></svar></p> <p><svar v="BD11A040 BD11A041">Q11. In case of a tribal household: find the code for the community mentioned by the respondent on the back page of the tally sheet and write it clearly using English digits inside the blank box.<br /></svar> <svar v="BD11A035" a="all"><span class="em">Question-6. Type of the Main House of the Household:</span><br />The main house of the household has been categorized in to four categories on the bassis of its type. Such as <span class="lang">pucca, semi pucca, kutcha </span>and <span class="lang">jupri</span>. The structure which is recognized as main house by the members of the household, enter appropriate symbol for its type looking at the structure. <br /></svar> Bangladesh 2011: Permanent households [discrepancies: none] This variable indicates the type of house. 1 Pucka 2 Semi-pucka 3 Kutcha 4 Jhupri 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Ownership <svar v="BD11A028" a="all">RMO code<br /><div class="i1">[] 1 Rural<br />[] 2 <span class="lang">Pourashava</span><br />[] 3 <span class="lang">Upazila</span> headquarter<br />[] 5 Cantonment board<br />[] 9 City corporation</div><br /></svar></p> <p><span class="em">For questions 6, 7, 8, 9, 10 and 11a put x in the relevant box.</span> <svar v="BD11A036" a="all"><span class="em">Question -7. Tenancy of the House:</span><br />Tenancy of house has divided in to three categories. Such as owned, rented and rent free. Enter cross symbol in the appropriate box for its tenancy.<br /></svar> Bangladesh 2011: Permanent households [discrepancies: none] This variable indicates the ownership of the dwelling. 1 Own 2 Rented 3 Rent-free 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Source of drinking water <svar v="BD11A037" a="all">8. Source of drinking water<br /><div class="i1">[] Tap<br />[] Tube-well<br />[] Other</div><br /></svar></p> <p><span class="em">For questions 6, 7, 8, 9, 10 and 11a put x in the relevant box.</span> <svar v="BD11A037" a="all"><span class="em">Question-8. Source of Drinking Water:</span><br />Source of drinking water is divided in to three categories for example- tap, tubewell and others. The source from which the household callect necessary drinking water indentifying the source enter cross in the appropriate box.<br /></svar> Bangladesh 2011: Permanent households [discrepancies: none] This variable indicates the source of drinking water for the household. 1 Tap 2 Tube-well 3 Other 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Toilet facilities <svar v="BD11A038" a="all">9. Toilet facilities<br /><div class="i1">[] Sanitary (with water seal)<br />[] Sanitary (no water seal)<br />[] Non-sanitary <br />[] None</div><br /></svar></p> <p><span class="em">For questions 6, 7, 8, 9, 10 and 11a put x in the relevant box.</span> <svar v="BD11A038" a="all"><span class="em">Question -9. Toilet Facility:</span><br />Considering the use toilet facility has been divided in to four categories such as sanitary (water sealed), sanitary (Non-water sealed). Non-sanitary and none. The toilet which is pit latrine with water sealed facility is called sanitary (water sealed). The latrine wich is pit latrine but having no water sealed facility is called sanitary (Non water sealed). The toilet which may be pucca, semi-pucca or kutch but having no facility to cover the discharge waste is called Non-sanitary. Such type of toilet is not free from water and environment polution. None means there is no toilet for the household usually uses to go bush, jungle or open space as and when necessary.<br />Ask the respondent that what type of toilet the household use. Enter cross in the appropriate box for the answer. <br /></svar> Bangladesh 2011: Permanent households [discrepancies: none] This variable indicates the type of toilet facilities for the household. 1 Sanitary (with water seal) 2 Sanitary (no water seal) 3 Non-sanitary 4 None 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Electricity connection <svar v="BD11A039" a="all">10. Electricity connection <br /><div class="i1">[] Yes<br />[] No</div><br /></svar></p> <p><span class="em">For questions 6, 7, 8, 9, 10 and 11a put x in the relevant box.</span> <svar v="BD11A039" a="all"><span class="em">Question -10. Electricity Connection:</span><br />Ask the respondent and confirm whether the household is connected with electricity or not. Electricity generated from Bio-Gas and solar energy will be considered as electricity connected. If the electricity is available enter cross in the yes box and if none enter cross in the no box.<br /></svar> Bangladesh 2011: Permanent households [discrepancies: none] This variable indicates the type of electricity connection. 1 Yes 2 No 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Ethnic population <svar v="BD11A040 BD11A041" a="all">11a. Is it a Tribal household<br /><div class="i1">[] Yes</div><br /><div class="i2">11b. If yes, write the code of tribal community _ _</div><br /><div class="i1">[] No</div><br /></svar></p> <p><svar v="BD11A040 BD11A041">Q11. In case of a tribal household: find the code for the community mentioned by the respondent on the back page of the tally sheet and write it clearly using English digits inside the blank box.<br /></svar> <svar v="BD11A040 BD11A041" a="all"><span class="em">Question -11. Is it a Tribal Household?</span><br />If any head of household acknowledge themself as a tribal commune consider the household as Tribal. The people of Chakma, Marma, Tripura, Santhal, Garo, Khasia, Monipuri, Rakhain etc. community is considered as tribal. This is a very sensitive question. So be sure about the household before entering cross box. If the household is a tribal one enter cross in the yes box and enter cross in the no box for non-tribal.<br />If the household is tribal go to the back page of tally sheet and identify the community code for the household and enter cross in the appropriate box.<br />According to Cultural Institution of Tribal law 2010 the tribe has been categorised in to 27 categories. If there is more than this category code 28 has been fixed for them which have been presented at the opposite page of second Tally sheet as follows:<br /><div class="i1">01 - Chakma<br />02 - Marma <br />03 - Tripura<br />04 - Mro<br />05 - Tonchonga<br />06 - Bom<br />07 - Pankhoa<br />08 - Chak<br />09 - Khying<br />10 - Khumi<br />11 - Lushai<br />12 - Kotch<br />13 - Shanthal<br />14 - Dalu<br />15 - Ushai(Usui)<br />16 - Rakhain<br />17 - Monipuri<br />18 - Garo<br />19 - Hazong<br />20 - Khashia<br />21 - Mong<br />22 - Orao<br />23 - Barman<br />24 - Pahari<br />25 - Malpahari<br />26 - Munda<br />27 - Kole<br />28 - Others</div><br />Example: Enter [0][1] if the community is chakma. <br /></svar> Bangladesh 2011: Permanent households [discrepancies: none] This variable indicates whether the household is part of a tribal community. 1 Yes 2 No 9 NIU (not in universe) Other Household Variables -- HOUSEHOLD Ethnicity <svar v="BD11A040 BD11A041" a="all">11a. Is it a Tribal household<br /><div class="i1">[] Yes</div><br /><div class="i2">11b. If yes, write the code of tribal community _ _</div><br /><div class="i1">[] No</div><br /></svar></p> <p><svar v="BD11A040 BD11A041">Q11. In case of a tribal household: find the code for the community mentioned by the respondent on the back page of the tally sheet and write it clearly using English digits inside the blank box.<br /></svar> <svar v="BD11A040 BD11A041" a="all"><span class="em">Question -11. Is it a Tribal Household?</span><br />If any head of household acknowledge themself as a tribal commune consider the household as Tribal. The people of Chakma, Marma, Tripura, Santhal, Garo, Khasia, Monipuri, Rakhain etc. community is considered as tribal. This is a very sensitive question. So be sure about the household before entering cross box. If the household is a tribal one enter cross in the yes box and enter cross in the no box for non-tribal.<br />If the household is tribal go to the back page of tally sheet and identify the community code for the household and enter cross in the appropriate box.<br />According to Cultural Institution of Tribal law 2010 the tribe has been categorised in to 27 categories. If there is more than this category code 28 has been fixed for them which have been presented at the opposite page of second Tally sheet as follows:<br /><div class="i1">01 - Chakma<br />02 - Marma <br />03 - Tripura<br />04 - Mro<br />05 - Tonchonga<br />06 - Bom<br />07 - Pankhoa<br />08 - Chak<br />09 - Khying<br />10 - Khumi<br />11 - Lushai<br />12 - Kotch<br />13 - Shanthal<br />14 - Dalu<br />15 - Ushai(Usui)<br />16 - Rakhain<br />17 - Monipuri<br />18 - Garo<br />19 - Hazong<br />20 - Khashia<br />21 - Mong<br />22 - Orao<br />23 - Barman<br />24 - Pahari<br />25 - Malpahari<br />26 - Munda<br />27 - Kole<br />28 - Others</div><br />Example: Enter [0][1] if the community is chakma. <br /></svar> Bangladesh 2011: Ethnic households [discrepancies: none] This variable indicates the household ethnicity. 01 Chakma 02 Marma 03 Tripura 04 Mro 05 Tanchaynga 06 Bawm 08 Chak 09 Khiyang 10 Khumi 12 Coach 13 Sawntal 16 Rakhain 17 Monipuri 18 Garo 19 Hajong 20 Khasia 22 Orao 23 Barmon 24 Pahari 25 Malpahari 26 Monda 27 Cool 28 Other 99 NIU (not in universe) Other Household Variables -- HOUSEHOLD Strata Bangladesh 2011: All households This variable is the strata identifier for the sample. Strata is a constructed variable that captures implicit geographic stratification resulting from the sample design. It is created by assigning a unique identifier to groups of between 10 and 19 adjacent households. Additional documentation is available on the Variance Estimation page. This is a 6-digit numeric variable with 0 implied decimal places Geography: A-E Variables -- HOUSEHOLD Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. Technical Person Variables -- PERSON Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Person Variables -- PERSON 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 Religion [general version] RELIGION indicates the person's religion, including "none." 0 NIU (not in universe) 1 No religion 2 Buddhist 3 Hindu 4 Jewish 5 Muslim 6 Christian 7 Other 9 Unknown Ethnicity and Language Variables -- PERSON Religion [detailed version] RELIGION indicates the person's religion, including "none." 0000 NIU (not in universe) 1000 No religion 1001 Atheist 1002 Agnostic 1003 Without religion 2000 Buddhist 3000 Hindu 4000 Jewish 5000 Muslim 5005 Ahmadis 5006 Sunni 6000 Christian 6001 Catholic (Roman or unspecified) 6002 Orthodox 6003 Protestant 6004 Evangelical protestant 6005 Pentecostal 6006 Adventist / Seventh-day adventist 6007 Anglican 6008 Assembly of God 6009 Baptist 6010 Church of the Nazarene 6011 Congregational 6012 Dutch Reformed 6013 Episcopalian 6014 Jehovah's Witnesses 6015 Latter Day Saints (Mormon) 6016 Lutheran 6017 Mennonite 6018 Methodist 6019 New Apostolic 6020 Presbyterian 6021 Zion Christian 6022 Moravian 6090 Other Christian, historical 6100 Other Christian, Armenia 6101 Armenia apostolic 6102 Nestorian 6103 Molokai 6104 Other Christian, Austria 6105 Old Catholic 6106 Protestant, Augsburg confession 6107 Protestant, Westminster confession 6108 Protestant, Helvetic confession 6109 Greek Oriental 6110 Armenian Apostolic 6111 Other Protestant 6112 Christian Community for renewal 6113 Christian Community, not specified 6114 Other Christian, Benin 6115 Other Christian 6116 Celestial 6117 Other Christian, Brazil 6118 Christian Congregation of Brazil 6119 Brazilian Catholic Apostolic 6120 Brazil for Christ 6121 Foursquare Gospel 6122 Universal of the Kingdom of God 6123 House of the Blessing 6124 House of Prayer 6125 God is Love 6126 Maranata 6127 Other Christian, Brazil 1991 6128 Undetermined Protestant 6129 Other traditional Protestant 6130 Neo-Christian 6131 Other Neo-Christian 6132 Undetermined Christian 6133 Other Christian, Brazil 2000 6134 Other Catholic 6135 Renewed Evangelical Protestant without institutional ties 6136 Pentecostal Evangelical without institutional ties 6137 New Life Evangelical Protestant Pentecostal 6138 Evangelical Protestant Biblical Revival Pentecostal 6139 Chain Of Prayer Pentecostal 6140 Undetermined Evangelical Protestant 6141 Religion Of God 6142 Christian without institutional ties 6143 Other Christian, Brazil 2010 6144 Salvation Army 6145 Other Christian, Canada 6146 Other Catholic 6147 United Church 6148 Protestant, not specified 6149 Other Protestant 6150 Other Christian, Cameroon 6151 Other Christian, Fiji 6152 Christian undefined 6153 Church of England 6154 Gospel Hall and Brethern 6155 Christian Mission Fellowship (CMF) or Every Home 6156 Salvation Army 6157 All Nations Christian Fellowship 6158 Apostles Gospel Outreach Fellowship 6159 Christian Outreach Centre 6160 Other Christian 6161 Other Christian, Germany 6162 Oriental Christian 6163 Other Christian, Ghana 6164 Other Christian, Iran 6165 Assyrian or Chaldean 6166 Armenian 6167 Other Christians 6168 Other Christian, Indonesia 6169 Other Christian 6170 Protestant/Other Christian 6171 Other Christian, Ireland 6172 Church of Ireland 6173 Church of Scotland 6174 Independent 6175 Unitarian 6176 Salvation Army 6177 Free Church 6178 Brethren 6179 Christian Brethren 6180 Plymouth Brethren 6181 Quaker 6182 Other Christians 6183 Other Christian, Ivory Coast 6184 Other Christian, Jamaica 6185 Brethren 6186 Church of God 6187 Church of God of Prophecy 6188 Other Church of God 6189 United Church 6190 Salvation Army 6191 New Testament 6192 Disciples of Christ 6193 Other Christian, Mauritius 6194 Christian Tamil 6195 Salvation and Healing Mission 6196 Voice of Deliverance 6197 Other Christian 6198 Other Christian, Mexico 6199 Anabaptist 6200 Calvinist 6201 Cuaquera 6202 Disciples of Christ 6203 Christian Friendship Church 6204 Prayer House Church 6205 Faith Center 6206 Agape Force Church 6207 Alpha and Omega Church 6208 Living Water Church 6209 Apostolic Church 6210 Church of God 6211 Church of God of Prophecy 6212 Complete Gospel Church 6213 Evangelical Siblings Church 6214 Upper Room Church 6215 Pentecostal Indigenous Church 6216 Angular Stone Voice Church 6217 Pentecostal Missionary 6218 Christian 6219 Christian Societies 6220 Evangelical 6221 Evangelical Societies 6222 New Testament Evangelical 6223 Pentecostal 6224 Pentecostal Societies 6225 Independent Pentecostal 6226 Evangelical Christian Societies 6227 Pentecostal Christian Societies 6228 Evangelical Pentecostal Societies 6229 Evangelical Pentecostal Christian Societies 6230 Soldiers of Christ's Cross Church 6231 Tabernacle 6232 Traditionalists 6233 Other Evangelical Pentecostal Societies 6234 Pentecostal not clearly specified 6235 Living God, Light of the World 6236 Christian and Missionary Alliance 6237 Non-Pentecostal Apostolic 6238 Evangelical Associations 6239 Biblical 6240 Confraternities 6241 Christ Church 6242 Peace Grace and Misericordia Church 6243 Open Bible Church 6244 Holiness Church 6245 Evangelical Salem Church 6246 Beautiful Woman Dressed in the Sun 6247 Messianic Church 6248 Evangelical Ministers 6249 Evangelical Missionaries 6250 Evangelical Movements 6251 New Jerusalem 6252 World Vision Church 6253 Evangelical not clearly specified 6254 Biblical - non-evangelicals 6255 Other Christians not clearly specified 6256 Assumptionist 6257 Carmelite 6258 Claretian 6259 Conception Franciscan 6260 Maronite Diocese of Mexico 6261 Dominican 6262 Servants of Mary Immaculate 6263 Franciscan 6264 Guadalupan 6265 Daughters of the Immaculate Conception 6266 Jesuit 6267 Legionaries of Christ 6268 Divine Word Missionary 6269 Pauline 6270 Sacred Heart 6271 Saint Joseph of Tarbes 6272 Servant of the Lord and the Virgin 6273 Servant of Jesus 6274 Greek Catholic Church 6275 Reformed Roman Catholic Church 6276 Mexican National Catholic Church 6277 Tridentine Latin Rite Catholic Church 6278 Priestly Society Trento 6279 Mexican Catholic Union of Trento 6280 Anabaptist / Memnonite 6281 Anglican / Episcopal 6282 House of Prayer 6283 Center of Faith, Hope and Love of the Missionary Revival Crusade 6284 Center of Faith, Hope and Love Agape Force 6285 Salvation Army 6286 Independent Pentecostal Fellowship 6287 Upper Chamber Church 6288 Faith Apostolic Church of Jesus Christ 6289 Spiritual Christian Church 6290 Pentecostal Evangelical Christian Church 6291 Interdenominational Christian Church 6292 Church of God Full Gospel in Mexico 6293 Church of Jesus Christ on the Rock 6294 Christ Evangelical Pentecostal Church Rock of my Salvation 6295 Mexican Church of Christ's Gospel Pentecost 6296 United Pentecostal Church of Mexico 6297 Universal Church of the Kingdom of God 6298 Only Christ Savior Christian Church 6299 Independent Evangelical Pentecostal Movement 6300 Prince of Peace 6301 National Union of Evangelical Christian Churches (UNICE) 6302 Union of Independent Evangelical Churches 6303 Other associations Pentecostal 6304 Church of the Living God, Pillar and Support of Truth, the Light of the World 6305 Bible Church 6306 Interdenominational Christian Church in Mexico 6307 Church of Christ 6308 Honey Church of Christ 6309 Independent Evangelical Church in Mexico 6310 Renewed Church of Jesus Christ and the Apostles of Divine Love 6311 Other Christian and Evangelical associations without Pentecostal support 6312 Faith Christian Church 6313 Traditional Apostolic Catholic Holy Church Mexico-USA 6314 Mexican Apostolic Catholic Church 6315 Elias 6316 Spiritualistic 6317 Spiritualist 6318 Marian Trinitarian Spirituality 6319 Spirituality of the Third Age 6320 Christian Spiritual 6321 Judiciary Society Reign of Leonardo Alcalá Leos 6322 Spirituality for the Divine Master and the purity of Mary 6323 Light and Hope 6324 Holy Spirit, Purity, Love and Light 6325 Christian Science 6326 Neo-Israelite Jewish Syncretic Movements 6327 Other Christian, Netherlands 6328 Reformed Churches in The Netherlands 6329 Other Reformed 6330 Other Christian, Papua New Guinea 6331 Asian Pacific Christian Mission 6332 Asutalian Church 6333 Bamu River Mission 6334 Christian Brethren Church of PNG 6335 Christian Mission of Many Lands 6336 Christian Revival Crusade 6337 Christain Union Mission 6338 Church of Christ of PNG 6339 Faith mission 6340 Four Square Gospel Mission 6341 Kwato Church 6342 Life Center 6343 Lighthouse church 6344 New Guinea Gospel Mission 6345 New Life Mission 6346 New tribes Mission 6347 Paliau Christian Native Church 6348 Rhema Fellowship 6349 Salvation Army 6350 Sovereign Grace 6351 United Church 6352 Wewak Fellowship 6353 Western Highland 6354 Independent 6355 Plymouth Brethern 6356 Tiliba Mission 6357 Tokarara Christian Fellowship 6358 Village Mission 6359 Other Christian 6360 Other Christian, Paraguay 6361 Christian Community 6362 Free Brothers 6363 Church of God 6364 Church of God of Prophecy 6365 New testament 6366 God is love 6367 Universal Church of the Kingdom of God 6368 People of God 6369 Family worship center 6370 Pseudo-Christian groups 6371 Other Christian, Philippines 6372 Aglipay 6373 Bible Christian Committees 6374 Born-again Christian 6375 Bread of Life Ministries 6376 Cathedral of Praise, Incorporated 6377 Charismatic Full Gospel Ministries 6378 Christ the Living Stone Fellowship 6379 Christian and Missionary Alliance 6380 Christians Missions 6381 Christian Reformed Church in the Philippines, Incorporated 6382 Church of Christ 6383 Crusaders of the Divine Church of Christ, Incorporated 6384 Evangelical Christian Outreach Foundation 6385 Evangelical Free Church 6386 Filipino Assemblies of the First Born Inc. 6387 Foursquare Gospel 6388 Free Believers in Christ Fellowship 6389 Free Mission in the Philippines Inc. 6390 God World Mission 6391 Good News Christian Churches 6392 IEMELIF Reform Movement 6393 Iglesia Evangelista Methodista en Las 6394 Iglesia Evangelica Unida de Cristo 6395 Iglesia ni Cristo 6396 Iglesia sa Dios Espiritu Santo, Incorporated 6397 Jesus Christ Saves Global Outreach 6398 Jesus is Alive Community, Incorporated 6399 Jesus is Lord Church 6400 Jesus Reigns Ministries 6401 Love of Christ International Ministries 6402 Other Evangelical 6403 Other Evangelical Church 6404 Other Protestants 6405 Philippine Ecumenical Christian Church 6406 Philippine Evangelical Mission 6407 Philippine Grace Gospel Fellowship 6408 Philippines Benevolent Missionaries 6409 Philippines General Council of the Assemblies of God 6410 Potter's House Christian Center 6411 Salvation Army Philippines 6412 Take the Nation for Jesus Global Ministries (Corpus Christi) 6413 UNIDA Evangelical Church 6414 Union Espiritista Cristiana de Filipinas, Incorporated 6415 United Church of Christ in the Philippines 6416 United Evangelical Church of the Philippines (Chinese) 6417 Victory Chapel Christian Fellowship 6418 Wesleyan Church 6419 World Missionary Evangelism 6420 Worldwide Church of God 6421 Zion Christian Community Church 6422 Other Christian, Portugal 6423 Other Christian, Romania 6424 Greek Catholic 6425 Reformed Church 6426 Evangelic of Augustan Confession 6427 Evangelic Synodo-Presbyterian 6428 Christian of Old Rite 6429 Christian by Gospel 6430 Evangelic 6431 Other Christian, Rwanda 2002 6432 Other Christian, Sierra Leone 6433 Other Christian, Slovak Republic 6434 Old Catholic 6435 Greek Catholic 6436 Christian Reformed 6437 Other Christian, South Africa 6438 Reformed 6439 International Fellowship of Christian Churches 6440 Apostolic Faith Mission of SA 6441 Other Apostolic Churches 6442 Pinkster Protestant Church 6443 Afrikaanse Protestant Church 6444 Full Gospel Church of God in Southern Africa 6445 Pentecostal Churches 6446 Salvation Army 6447 Bandla Lama Nazaretha 6448 African Methodist Episcopal Church 6449 St John's Apostolic Church 6450 International Pentecost Church 6451 Ethiopian type churches 6452 Ethnic churches 6453 Other African Independent Churches 6454 Other Christian Churches 6455 Other Catholic Churches 6456 Other Pentecostal Churches 6457 Other Orthodox Churches 6458 Other African Apostolic churches 6459 Other Assemblies 6460 Christian Scientist 6461 Christian Centres 6462 Other Evangelical Churches 6463 Other Charismatic Churches 6464 Just a Christian or non-denominational 6465 Other 6466 Other Christian, Suriname 6467 Other Christian 6468 Other Christian, Saint Lucia 6469 Church of God 6470 Other Christian, Senegal 6471 Other Christian 6472 Other Christian, Switzerland 6473 Other protestant churches and communities 6474 Christ-Catholic church 6475 Other Christian communities 6476 Other Christian, Trinidad and Tobago 6477 Church of God 6478 African Methodist Espiscopalians 6479 Brethren, Christian or Plymouth 6480 Church of Christ 6481 Gospel Hall or Gospel Missionary 6482 Nazarenes 6483 Pilgrim Holiness 6484 Ethiopian Orthodox 6485 Open Bible Church 6486 Assemblies of Yahweh 6487 Evangelical Church of West Indies 6488 Christadelphian 6489 Full Gospel Fellowship 6490 Dutch Reform 6491 Christian Brotherhood Assembly 6492 Other Christian, Uganda 6493 Other Christian 6494 Salvation Army 6495 Other Christian non-Catholic, Uruguay 6496 Other Christian non-Catholic, Guatemala 6497 Other Christian, Togo 7000 Other 7001 Bahai 7002 Sikh 7003 Rastafarian 7100 Other, Armenia 7101 Pagan 7102 Shar-fadinian 7103 Other, Austria 7104 Unification Church, Austria 7105 Other, Benin 7106 Traditional 7107 Vodoun 7108 Other, Botswana 7109 Badimo 7110 Other, Brazil 7111 Spiritist 7112 Kardecist Spiritist 7113 Afro Spiritist 7114 Mediumistic Spiritist 7115 Umbandist Mediumistic 7116 Candomblecist Mediumistic 7117 Other Afro-Brazilian 7118 Oriental, Brazil 7119 New Oriental 7120 Oriental Seicho No-le 7121 Other Oriental, Brazil 7122 Esoteric, Brazil 7123 Indigenous, Brazil 7124 Other minority groups, Brazil 7125 Other, Burkina Faso 7126 Animist 7127 Other, Cameroon 7128 Animist 7129 Other, Canada 7130 Eastern religions, Canada 7131 Other, Chile 7132 Theosophism 7133 Shintoism 7134 Other, Ethiopia 7135 Traditional 7136 Other, Ethiopia 7137 Other, Fiji 7138 Confucian 7139 Kabir Panthi 7140 Satya Sai Baba 7141 Bahai 7142 Other non-Christian, Fiji 7143 Other, Germany 7144 Other, Germany 7145 Other, Ghana 7146 Traditional, Ghana 7147 Other, Guinea 7148 Animist 7149 Other, Guinea 7150 Other, Haiti 7151 Voodoo 7152 Other, India 7153 Jainism 7154 Zoroastrianism 7155 Other, India 7156 Other, Indonesia 7157 Confucianism 7158 Other, Indonesia 7159 Other, Iran 7160 Zoroastrian 7161 Other, Iran 7162 Other, Ivory Coast 7163 Animist 7164 Harrist 7165 Other, Jamaica 7166 Muslim/Hindu 7167 Other, Israel 7168 Druse 7169 Other, Israel 7170 Other, Laos 7171 Animist 7172 Other, Liberia 7173 Traditional 7174 Other, Malaysia 7175 Confucianism/Taoism 7176 Tribal/Folk religion, Malaysia 7177 Other, Mali 7178 Animist 7179 Other, Mexico 7180 Brahmanism 7181 Hare Krishna 7182 Shintoism 7183 Taoism 7184 Mexican Movements 7185 Ananda Marga 7186 Church of Scientology 7187 Masons 7188 Raelian Movement 7189 New Age Movement 7190 Neoisraelites 7191 Occultists 7192 Palmar of Troya 7193 Rose Cross 7194 Theosophism 7195 Spiritualist Special Keys 7196 Onkaranada Center 7197 Confucianism 7198 Shia 7199 Universal Great Brotherhood 7200 Esoteric Science 7201 Gnosticism 7202 Metaphysics 7203 Wicca 7204 Shamanism 7205 The Custom 7206 Mexicayotl 7207 Restorative Confederate Movement of Anahuac Culture 7208 African Origin 7209 Indigenous Religions 7210 Growing in Grace 7211 Eckankar 7212 Transcendental Meditation 7213 Mission Branch 7214 Children of God 7215 Sri Sathya Sai Baba 7216 Other religions from Asia 7217 Ethnic roots 7218 Afro roots 7219 Popular cults 7220 Other new religious movements 7221 Other, Nepal 7222 Kirat 7223 Jain 7224 Garaute 7225 Tap jura 7226 Bon 7227 Prakriti 7228 Other, Nigeria 7229 Traditional 7230 Other, Pakistan 7231 Ahmadi 7232 Parsi 7233 Scheduled caste 7234 Other, Paraguay 7235 Philosophical revelations 7236 Indigenous religion 7237 Reyukai 7238 Other, Paraguay 7239 Other, Philippines 7240 Door of Faith 7241 Faith Tabernacle Church (Living Rock Ministries) 7242 Iglesia Filipina Independiente 7243 International One Way Outreach 7244 Miracle Life Fellowship International 7245 Miracle Revival Church of the Philippines 7246 Philippine Good News Ministries 7247 Philippine Missionary fellowship 7248 Things to Come 7249 Way of Salvation 7250 Word of the World 7251 Word International Ministries 7252 Tribal Religions, Philippines 7253 Other, Romania 7254 Unitarian 7255 Armenian 7256 Mosaic 7257 Other, Romania 7258 Other, Rwanda 7259 Traditional religion, Rwanda 7260 Other, Rwanda 7261 Other, Sierra Leone 7262 Traditional religion, Sierra Leone 7263 Other, South Africa 7264 African traditional belief 7265 Taoist 7266 Confucian 7267 New Age 7268 Winti 7269 Javanism 7270 Other non-Christian, S. Africa 7271 Other, Suriname 7272 Javanism 7273 Traditional 7274 Winti 7275 Other, Thailand 7276 Confucian 7277 Other, Trinidad and Tobago 7278 Pocamania or Shango 7279 Orisha 7280 Other, Uganda 7281 Traditional religion 7282 Mammon 7283 Other non-Christian, Uganda 7284 Other, United Kindom 7285 Other, Uruguay 7286 Umbanda/other Afro-American 7287 Other, Uruguay 7288 Other, Vietnam 7289 Cao Dai 7290 Cham Brahmin 7296 Other, Togo 7297 Animist 7900 Other, not elsewhere classified 9999 Unknown Ethnicity and Language Variables -- PERSON 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, Bangladesh EDUCBD indicates the person's educational attainment in Bangladesh in terms of the level of schooling completed. 00 NIU (not in universe) 10 No education 21 Class I 22 Class II 23 Class III 24 Class IV 25 Class V 26 Class VI 27 Class VII 28 Class VIII 29 Class IX 30 Secondary school certificate (SSC) or Dakhil 31 Training (technical education) 32 Higher secondary certificate (HSC) or Alim 40 Diploma (technical education) 41 Bachelor or Fazil 42 Bachelor honors 43 Master / Kamil 44 Master or doctorate 98 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 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 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 Mental disability DISMNTL indicates whether the person suffered a mental disability in the form of diminished capacity. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Person number (within household) Bangladesh 2011: All records This variable indicates the person number (within household). 00 Household record 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 Technical Person Variables -- PERSON Age <svar v="BD11A401" a="all">14. Age (completed years) _ _<br /></svar></p> <p><svar v="BD11A401">Q14. Age (completed years): write the age of each member in English digits in the blank boxes. If the age of some member is less than 12 months then write 0 0. If the age of any member is 100 years or more then write 9 9. Age is a very important indicator. Many people do not have accurate perception about their age. Therefore, age stated by the respondent is to be probed with historical events, such as, war of liberation, flood of 1988, age at marriage, age of youngest child and corrections should be made where necessary.<br /></svar> <svar v="BD11A401" a="all"><span class="em">Question-14. Age (in completed years)</span><br />Collect the age information of the head of household first from 14 to 25 following the horizontal rule and next information of age for the spouse and other members of the household. The probing question is required to justify the accurate age data. In this case age of the youngest child, age at marrige, liberation war, cyclone of 1970, flood of 1988, and justify with historical events to project the acurate age and enter in the specifie box. Verify with national Identity Card (ID card)or any other valid document if possible. Enter [0][0] for age less than one year and for 100 years of age or more enter [9][9] in the specific box.<br /></svar> Bangladesh 2011: All persons This variable indicates a person's age. 00 Less than 1 years old 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+ Demographic Variables -- PERSON Relationship to household head <svar v="BD11A402" a="all">15. Relationship with head of household<br /><div class="i1">[] Head <br />[] Wife/husband<br />[] Child<br />[] Other relative<br />[] Non-relative</div><br /></svar></p> <p><span class="em">For questions 15, 16, 17, 18, 20, 22, 23, 24 and 25, put x in the relevant box.</span> <svar v="BD11A402" a="all"><span class="em">Question-15. Relationship with Head of Household:</span><br />Relationship with head of household has been categorized in to 5 categories and one column for every category in the questionnaire has been kept reserve.<br /><div class="i1">For example:<br />1st Head of Household;<br />2nd Spouse of Head of Household;<br />3rd Children;<br />4th Other relatives; and<br />5th Non relative</div><br />Enter cross in the appropriate box for relationship of the members of the household.<br /></svar> Bangladesh 2011: All persons This variable indicates a person's relationship to household head. 1 Head 2 Spouse 3 Child 4 Other relative 5 Non-relative 8 Unknown Demographic Variables -- PERSON Sex <svar v="BD11A403" a="all">16. Sex <br /><div class="i1">[] Male<br />[] Female</div><br /></svar></p> <p><span class="em">For questions 15, 16, 17, 18, 20, 22, 23, 24 and 25, put x in the relevant box.</span> <svar v="BD11A403" a="all"><span class="em">Question-16. Sex:</span><br />Enter cross in the male box for males.<br />Enter cross in the female box for females.<br />If the person is nutral (Hizra) ovserving the nature and behaviour enter cross in the male or female box as applicable.<br /></svar> Bangladesh 2011: All persons This variable indicates a person's sex. 1 Male 2 Female Demographic Variables -- PERSON Marital status <svar v="BD11A404" a="all">17. Marital status<br /><div class="i1">[] Unmarried<br />[] Married<br />[] Widowed<br />[] Divorced/separated</div><br /></svar></p> <p><span class="em">For questions 15, 16, 17, 18, 20, 22, 23, 24 and 25, put x in the relevant box.</span> <svar v="BD11A404" a="all"><span class="em">Question-17. Marital Status: </span><br />Marital status has been categorized into four categories. <br /><div class="i1">For unmarried enter cross in the 1st check box;<br />For married enter cross in the 2nd check box;<br />For widowed enter cross in the 3rd check box;<br />For divorced/separated/left cross in the 4th check box.</div><br /></svar> Bangladesh 2011: All persons This variable indicates a person's marital status. 1 Unmarried 2 Married 3 Widowed 4 Divorced or separated Demographic Variables -- PERSON Religion <svar v="BD11A405" a="all">18. Religion<br /><div class="i1">[] Muslim<br />[] Hindu<br />[] Christian<br />[] Buddhist<br />[] Other</div><br /></svar></p> <p><span class="em">For questions 15, 16, 17, 18, 20, 22, 23, 24 and 25, put x in the relevant box.</span> <svar v="BD11A405" a="all"><span class="em">Question-18. Religion:</span><br />Religion has been categorized into 5 categories.<br /><div class="i1">For Islam religion enter cross in the 1st check box;<br />For Hindu religion enter cross in the 2nd check box;<br />For Christian religion enter cross in the 3rd check box;<br />For Bhuddist religion enter cross in the 4th check box;<br />For other religion enter cross in the 5th check box.</div><br /></svar> Bangladesh 2011: All persons This variable indicates a person's religion. 1 Muslim 2 Hindu 3 Christian 4 Buddhist 5 Other Ethnicity and Language Variables -- PERSON Type of disability <svar v="BD11A406" a="all">19. Type of disability<br /><div class="i1">[] 0 None<br />[] 1 Speech<br />[] 2 Vision<br />[] 3 Hearing<br />[] 4 Physical<br />[] 5 Mental<br />[] 6 Autistic</div><br /></svar></p> <p><svar v="BD11A406">Q19. Disability: if no disability then write 0 in the blank box, if speaking problem write 1 in blank box, if vision problem then write 2 in blank box, if listening problem then write 3 in the blank box, if physical problem then write 4 in the blank box, if mental problem then write 5 in the blank box, if autistic write 6 in the blank box.<br /></svar> <svar v="BD11A406" a="all"><span class="em">Question-19. Is Disabled? </span><br />According to Disabled Welfare Act 2010 person who is by born or cause of others physically unable or completely/partly handicapped or mentally retarded is considered as Disabled. In this census as per recommendation of the Washington Group disabled has been categorized into six categories. <br />Ask the respondent is there any body in this household who is having trouble in speaking, seeing, listening, physical or mental. Ask in this regards.<br />For person having none of the above problem enter zero in the check box;<br />For person having problem in speaking enter [1] in the check box;<br />For person having problem in eye side even using spectacle enter [2] in the check box;<br />For person having listening problem even using Hearing Aid unable to listen enter [3] <br />For handicapped person unable to move freely enter [4] in the check box;<br />For person mentally retarded enter [5] in the check box;<br />For autistic person lack of intelligence enter [6] in the check box.<br /></svar> Bangladesh 2011: All persons This variable indicates the type of disability that a person may have. 0 No disability 1 Speech 2 Vision 3 Hearing 4 Physical 5 Mental 6 Autistic Disability Variables -- PERSON Student <svar v="BD11A407" a="all">20. Student (currently)<br /><div class="i1">[] Yes<br />[] No</div><br /></svar> <svar v="BD11A407" a="all"><span class="em">Question-20. Is currently student? </span><br />If the answer is yes enter cross in the yes check box.<br />For no enter cross in the no check box. <br /></svar> Bangladesh 2011: All persons This variable indicates the school attendance. 1 Yes 2 No Education Variables -- PERSON Educational attainment <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412"><span class="em">For members age 7 years and above</span><br />[Questions 21-25 were asked for persons 7 years of age and older.]<br /></svar></p> <p><svar v="BD11A408" a="all">21. Highest class passed (write class passed code) _ _<br /></svar></p> <p><svar v="BD11A408">Q21. Highest class passed (year): a code list has been prepared on the basis of years required for a member for passing the highest class, by the board and university for awarding a degree or certificate and is printed on the back page of the tally sheet. Using this code list write appropriate code to the blank boxes for the highest class passed by each member of the household. If someone did not go to school, then the highest class passed code will be 0 0. If someone is ssc passed then highest class passed code will be 1 0. If someone has higher degree than masters then code will be 1 8.<br /></svar> <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412">Fill out Questions- 21 to 25 only for persons aged 7 years and over.<br /></svar></p> <p><svar v="BD11A408" a="all"><span class="em">Question-21. Highest class passed: </span><br />Ask everybody beginning with the head of household that which highest class they passed. Enter the answer checking with the codes for class printed at opposite page of tally sheet in two digits in the check box. Codes for highest class passed are given below for the convenience of training:<br /><div class="i1">00. No schooling/Not passed class I<br />01. Class I<br />02. Class II<br />03. Class III<br />04. Class IV<br />05. Class V<br />06. Class VI<br />07. Class VII<br />08. Class VIII<br />09. Class IX<br />10. SSC or Equivalent<br />12. HSC or Equivalent<br />15. Degree or Equivalent<br />16. Degree (Hons) or Equivalent<br />18. Masters or Equivalent</div><br /><div class="i1">Example:<br />Enter class code [0][0] if reported no schooling or did not pass class one. <br />Enter [0][5] for person passed class five. <br />Enter [1][5] for person passed highest class Graduation and [1][8] for person passed Masters.</div><br /></svar> Bangladesh 2011: Persons age 7+ [discrepancies: none] This variable indicates the educational attainment. 00 No class passed 01 Class 1 02 Class 2 03 Class 3 04 Class 4 05 Class 5 06 Class 6 07 Class 7 08 Class 8 09 Class 9 10 Class SSC (secondary school certificate) 12 Class HSC (higher secondary certificate) 15 Graduation (general) 16 Graduation (honors) 18 Masters and higher 99 NIU (not in universe) Education Variables -- PERSON Field of education <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412"><span class="em">For members age 7 years and above</span><br />[Questions 21-25 were asked for persons 7 years of age and older.]<br /></svar></p> <p><svar v="BD11A409" a="all">22. Field of education<br /><div class="i1">[] General<br />[] Vocational/technical<br />[] Religious<br />[] Not applicable</div><br /></svar> <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412">Fill out Questions- 21 to 25 only for persons aged 7 years and over.<br /></svar></p> <p><svar v="BD11A409" a="all"><span class="em">Question-22. Field of Education: </span><br />The field of education is divided into four categories. These are General, Vocational/Technical, Religious and not applicable.<br />General means persons who are qualified in science, arts, and commerce. Vocational/Technical means doctor, engineer agriculturist and technical training holders. Persons who got degree from Madrasa or other religious institutions will be considered in the category of religious. Enter cross in the appropriate check box.<br /></svar> Bangladesh 2011: Persons age 7+ [discrepancies: none] This variable indicates the field of education. 1 General 2 Vocational/technical 3 Religious 4 Not applicable 8 Unknown 9 NIU (not in universe) Education Variables -- PERSON Literacy <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412"><span class="em">For members age 7 years and above</span><br />[Questions 21-25 were asked for persons 7 years of age and older.]<br /></svar></p> <p><svar v="BD11A410" a="all">23. Can write a letter?<br /><div class="i1">[] Yes<br />[] No</div><br /></svar> <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412">Fill out Questions- 21 to 25 only for persons aged 7 years and over.<br /></svar></p> <p><svar v="BD11A410" a="all"><span class="em">Question-23. Able to Write Letter? </span><br />Ask all who are aged 7 years and over whether they are able to write letter or express their views in writing. Enter cross in the yes box for answer 'yes' and enter cross in the no box for answer 'no'.<br /></svar> Bangladesh 2011: Persons age 7+ [discrepancies: none] This variable indicates literacy based on whether or not a person can write a letter. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Education Variables -- PERSON Activity status <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412"><span class="em">For members age 7 years and above</span><br />[Questions 21-25 were asked for persons 7 years of age and older.]<br /></svar></p> <p><svar v="BD11A411" a="all">24. Activity status<br /><div class="i1">[] Employed<br />[] Looking for job<br />[] Household work<br />[] Do not work</div><br /></svar> <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412">Fill out Questions- 21 to 25 only for persons aged 7 years and over.<br /></svar></p> <p><svar v="BD11A411" a="all"><span class="em">Question-24. Working Status: </span><br />Working status has been categorized into four categories such as working, looking for work, household work and do not work. Enter a cross in the box for 'engaged in work' for working, enter a cross in the box for 'looking for work' for persons who are not currently working but willing for work, enter a cross in the box for 'household work' for persons who are engaged in household work, and enter a cross in the box for 'do not work' for persons who do not work or are unable to work. <br /></svar> Bangladesh 2011: Persons age 7+ [discrepancies: none] This variable indicates the activity status. 1 Employed 2 Looking for job 3 Household work 4 Do not work 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Industry <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412"><span class="em">For members age 7 years and above</span><br />[Questions 21-25 were asked for persons 7 years of age and older.]<br /></svar></p> <p><svar v="BD11A412" a="all">25. If employed, field of employment<br /><div class="i1">[Question 25 was asked for persons 7 years of age and older who reported being employed.]<br />[] Agriculture<br />[] Industry<br />[] Service</div><br /></svar> <svar v="BD11A408 BD11A409 BD11A410 BD11A411 BD11A412">Fill out Questions- 21 to 25 only for persons aged 7 years and over.<br /></svar></p> <p><svar v="BD11A412" a="all"><span class="em">Question-25. Field of Work if Employed:</span><br />If found employed or working in the earlier question- 24 category them in the three main categories such as agriculture, industry and service.<br /> <br />Person who are engaged most of the time in agricultural work, raising of livestock, fish culture/hatchery and work in the forest department as labour or employer enter cross in the box for agriculture, enter cross in the box for industry if most of time engaged in the [p. 21] industry/factory as labour or employer and enter cross in the box for service if most of the time engaged as a professional, service holder, or engaged in providing services (such as doctor, advocate, barber).<br />If you have any confusion to understand any question in the individual module from Quest-12 to 25 ask me. (If any question asked explain it initials) Now I shall ask 14 questions to 14 trainees of you (Ask addressing some one) Tell me which name you will enter in the first line of Ques-12? (In this way ask all the questions and evaluate)<br /></svar> Bangladesh 2011: Employed persons [discrepancies: none] This variable indicates the employment field. 1 Agriculture 2 Industry 3 Services 8 Unknown 9 NIU (not in universe) Work: Industry Variables -- PERSON