1961 Census DDI_GBR_1961_PHC_v01_M_v7.6_A_IPUMS IPUMS

Integrated Public Use Microdata Series (IPUMS) International

IPUMS April 2, 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. 1961 Census - IPUMS Subset PHC uk1961a (IPUMS Harmonized Subset) GBR_1961_PHC_v01_M_v7.6_A_IPUMS Office of Population and Surveys for England and Wales IPUMS (c) Copyright 1961, Office of Population and Surveys for England and Wales and Minnesota Population Center Office of Population and Surveys for England and Wales 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: O-Z Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Work Variables -- PERSON Household Economic Variables -- HOUSEHOLD Technical Person Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Education Variables -- PERSON Work: Industry Variables -- PERSON Other Person Variables -- PERSON April 23, 1961 United Kingdom of Great Britain and Northern Ireland Region Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: No - Households: A household comprises either one person living alone or a group of people not necessarily related, living at the same address with common housekeeping - that is, sharing at least one meal a day or sharing a living room or sitting room. People staying temporarily with the household are included. - Group quarters: Yes All persons (members of the household, including visitors, employees and boarders) who are present at midnight on the night of Sunday, 23rd April, 1961, in the dwelling, and alI persons who arrive at the dwelling and join the household on Monday, 24th April, 1961, before the collection of the schedule, and who have not been enumerated elsewhere. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: United Kingdom 1961 Note: Excludes Northern Ireland; age is grouped into categories MICRODATA SOURCE: Office of Population and Surveys for England and Wales SAMPLE SIZE (person records): 495581. SAMPLE DESIGN: Original data from which the sample was extracted is itself a systematic sample of every 10th household, selected during the data collection process, and that received the long form. The original data was then stratified by household type and sorted geographically. One in ten households was subsequently systematically excluded. Persons living in communal establishments or in households with more than nine residents were excluded. Finally, a 0.95% sample of households was extracted by selecting randomly 1-in-9 households from the remaining long form respondents. Individuals within communal establishments and those in households with more than nine residents were selected separately from data ordered by geography. No weighting was applied. NOTE: The sample excludes Northern Ireland. It includes England, Scotland and Wales. Face-to-face [f2f] Two questionnaires: a long form applied to ten percent of the poulation and a short form to the other ninety percent. Each of them collected information from all persons, private households, and persons absent from the household. Both, CENSUS DAY: April 23, 1961 Self-weighting (expansion factor = 100) IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS International are designed to extend this record. Office of Population and Surveys for England and Wales 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: United Kingdom of Great Britain and Northern Ireland, Office of Population and Surveys for England and Wales. 1961 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 uk1961a, 2025 GBR1961_PHC-H-H.dat Household records 173,048 ascii Minnesota Population Center Version 7.5, IPUMS sample GBR1961_PHC-P-H.dat Person records 495581 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 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 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 Nomenclature of Territorial Units for Statistics 1, Europe ENUTS1 identifies the Nomenclature of Territorial Units for Statistics (NUTS) within Europe in which the household was enumerated. NUTS1 is the first level territorial units within countries. NUTS is a standard administrative division of the European Union, and was developed by the EU. The European Free Trade Association extends the NUTS system to several additional countries outside of the EU, and they are also incorporated into this variable. ENUTS1 corresponds to the 2010 version of NUTS1 released by Eurostat. IPUMS has added ENUTS1_2013 for the more recent samples. ENUTS1_2013 is an amendment to the annexes to the ENUTS1 classification. The last 2-digits of the ENUTS1 variable provide the NUTS1 code. The labels include the standard code for the NUTS1 system and the name of the NUTS1 region, separated by a slash. Smaller sub-national units are available for most countries in ENUTS2 and ENUTS3. The full set of geography variables for the countries can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 0101 AT1 / Ostösterreich 0102 AT2 / Südösterreich 0103 AT3 / Westösterreich 0601 DE1 / Baden-Württemberg 0602 DE2 / Bayern 0603 DE3 / Berlin 0604 DE4 / Brandenburg 0605 DE5 / Bremen 0606 DE6 / Hamburg 0607 DE7 / Hessen 0608 DE8 / Mecklenburg-Vorpommern 0609 DE9 / Niedersachsen 0610 DEA / Nordrhein-Westfalen 0611 DEB / Rheinland-Pfalz 0612 DEC / Saarland 0613 DED / Sachsen 0614 DEE / Sachsen-Anhalt 0615 DEF / Schleswig-Holstein 0616 DEG / Thüringen 0901 ES1 / Noroeste 0902 ES2 / Noreste 0903 ES3 / Comunidad de Madrid 0904 ES4 / Centro (E) 0905 ES5 / Este 0906 ES6 / Sur 0907 ES7 / Canarias 0909 ES / Unknown 1101 FR1 / Île de France 1102 FR2 / Bassin Parisien 1103 FR3 / Nord - Pas-de-Calais 1104 FR4 / Est 1105 FR5 / Ouest 1106 FR6 / Sud-Ouest 1107 FR7 / Centre-Est 1108 FR8 / Méditerranée 1109 FR9 / Département d’Outre-Mer 1199 FR99 / Unknown 1201 EL1 / Voreia Ellada 1202 EL2 / Kentriki Ellada 1203 EL3 / Attiki 1204 EL4 / Nisia Aigaiou, Kriti 1400 IE0 / Republic of Ireland 1503 ITC / Nord-Ovest 1506 ITF / Sud 1507 ITG / Isole 1508 ITH / Nord-Est 1509 ITI / Centro 2101 PL1 / Centralny 2102 PL2 / Południowy 2103 PL3 / Wschodni 2104 PL4 / Północno-zachodni 2105 PL5 / Południowo-zachodni 2106 PL6 / Północny 2201 PT1 / Continente 2202 PT2 / Região Autónoma dos Açores 2203 PT3 / Região Autónoma da Madeira 2301 RO1 / Macroregiunea Unu 2302 RO2 / Macroregiunea Doi 2303 RO3 / Macroregiunea Trei 2304 RO4 / Macroregiunea Patru 2501 SI0 / Slovenia 2600 SK0 / Slovensko 2701 UKC / North East (England) 2702 UKD / North West (England) 2703 UKE / Yorkshire and the Humber (England) 2704 UKF / East Midlands (England) 2705 UKG / West Midlands (England) 2706 UKH / East of England (England) 2707 UKI / LONDON (England) 2708 UKJ / South East (England) 2709 UKK / South West (England) 2710 UKL / WALES 2711 UKM / SCOTLAND 2712 UKN / NORTHERN IRELAND 3400 CH0/Switzerland 3901 TR1 / Istanbul 3902 TR2 / Bati Marmara 3903 TR3 / Ege 3904 TR4 / Dogu Marmara 3905 TR5 / Bati Anadolu 3906 TR6 / Akdeniz 3907 TR7 / Orta Anadolu 3908 TR8 / Bati Karadeniz 3909 TR9 / Dogu Karadeniz 3911 TRA / Kuzeydogu Anadolu 3912 TRB / Ortadogu Anadolu 3913 TRC / Güneydogu Anadolu 9999 UNKNOWN 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 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 United Kingdom, Region 1961 - 2001 [Level 1; consistent boundaries, GIS] GEO1_UK identifies the household's region within United Kingdom in all sample years. Regions are the first level administrative units of the country. GEO1_UK 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_UK can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for the United Kingdom 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. 826101 North East 826102 North West 826103 Yorkshire and the Humber 826104 East Midlands 826105 West Midlands 826106 East of England 826107 South East 826108 South West 826110 Outer London, Inner London 826111 Scotland 826112 Wales 826113 Northern Ireland Geography: O-Z Variables -- HOUSEHOLD United Kingdom, Region 1961 GEO1_ UK1961 identifies the household's region within United Kingdom in 1961. Regions are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_ UK1961 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for United Kingdoms 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. 001 East 002 East Midlands 003 London 004 North East 005 North West 006 South East 007 South West 008 Wales 009 West Midlands 010 Yorks and Humberside 011 Scotland 013 Northern Ireland Geography: O-Z 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 Number of rooms ROOMS indicates the number of rooms occupied by the housing unit. 00 Part of a room; no rooms 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Dwelling number United Kingdom 1961: All records This variable indicates the dwelling number. This is a 6-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Number of persons in household United Kingdom 1961: All records This variable indicates the number of persons in household. 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 Technical Household Variables -- HOUSEHOLD Dwelling created by splitting apart a large dwelling or household United Kingdom 1961: All records This variable indicates whether the dwelling was created by splitting apart a large dwelling or household. 0 No problem Technical Household Variables -- HOUSEHOLD Region (from 2001) <span class="h3">For enumerators' use</span> <br />Census District No. ____ <br />Enumeration District No. ____ <br />Name and postal address of householder or other person responsible for making the return. ________ 2. Usual address (Column C)</p> <div class="i1">(a) School children, students, etc., who live away from home during term should give their home address, not their term-time address.<br />(b) Members of H.M. Forces should give the address of their married quarters or other home address.<br />(c) Resident staff should regard the private house, boarding house, or other premises where they live as their usual address.<br />(d) For persons with no settled address, write "None".<br />(e) For boarders who have a settled residence with this household, write "Here".</div> United Kingdom 1961: All households This variable indicates the region (2001). 01 East 02 East midlands 03 London 04 North east 05 North west 06 South east 07 South west 08 Wales 09 West midlands 10 Yorks and Humberside 11 Scotland Geography: O-Z Variables -- HOUSEHOLD Rooms in private household <span class="h3">Information to be given to the enumerator</span></p> <p>____ Whether sharing stove and sink in shared dwelling <br />____ Number of rooms</p> <div class="i1">____Number of persons<br />____ Males<br />____ Females</div><p>Schedule No. ____ United Kingdom 1961: Private households [discrepancies: none] This variable indicates the number of rooms in the private 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+ 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Number of residents in household <span class="h3">Information to be given to the enumerator</span></p> <p>____ Whether sharing stove and sink in shared dwelling <br />____ Number of rooms</p> <div class="i1">____Number of persons<br />____ Males<br />____ Females</div><p>Schedule No. ____ United Kingdom 1961: Private non-communal non-institutional households [disrepancies: none] This variable indicates the number of residents in household. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 99 NIU (not in universe) Technical Household Variables -- HOUSEHOLD Private or non-private household United Kingdom 1961: All households This variable indicates whether the dwelling is considered private or non-private. 1 Non-private household 2 Private household Group Quarters Variables -- HOUSEHOLD Dwelling ownership L. State how this household occupies its accommodation (house, flat, rooms, etc.) by writing "yes" at (a), (b), (c), (d), or (e), or by giving details at (f). (See note 9).</p> <div class="i1">____ (a) As owner-occupiers (including purchase by mortgage)<br />____ (b) By renting it with a farm, shop or other business premises<br />____ (c) By virtue of employment<br />____ (d) By renting it from the Council or New Town Corporation<br />____ (e) By renting it from another landlord - furnished or unfurnished<br />____ (f) In some other way - please give details</div> 9. Ownership and renting (Panel L)</p> <div class="i1">Leaseholds. If the household occupy their house, flat, etc, on a lease which was originally granted for more than 21 years, or has since been extended for more than 21 years, write "yes" at (a). For shorter leases, answer one of the other parts of the question in Panel L.<br />By virtue of employment. If the accommodation is provided in connection with the employment of a member of the household and ceases to be provided after the employment comes to an end (e.g. a tied cottage, caretaker's flat), write "yes" at (c) whether rent is paid or not.</div> United Kingdom 1961: Private households [discrepancies: none] This variable indicates the dwelling tenure. 1 Owner occupied 2 Rented with business 3 Held by virtue of employment 4 Rented from council 5 Other rented (furnished) 6 Other rented (unfurnished) 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Visitors in the household United Kingdom 1961: Private non-communal non-institutional households [disrepancies: none] This variable indicates the number of visitors in the household. 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 9 NIU (not in universe) Technical Household 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 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 Marital status, Europe EMARST describes for the European samples the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. European census instructions generally limit marital status to legal unions, but there are exceptions. EMARST has been classified according to the recommendations given by the Conference of European Statisticians for the 2010 Population and Housing Censuses. 0 NIU (not in universe) 1 Never married 2 Married 3 Widowed and not remarried 4 Divorced/separated and not remarried 5 Widowed or divorced 9 Unknown / missing Demographic 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 Occupation, ISCO general OCCISCO records the person's primary occupation, coded according to the major categories in the International Standard Classification of Occupations (ISCO) scheme for 1988. For someone with more than one job, the primary occupation is typically the one in which the person had spent the most time or earned the most money. 01 Legislators, senior officials and managers 02 Professionals 03 Technicians and associate professionals 04 Clerks 05 Service workers and shop and market sales 06 Skilled agricultural and fishery workers 07 Crafts and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 10 Armed forces 11 Other occupations, unspecified or n.e.c. 97 Response suppressed 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Occupation, unrecoded OCC records the person's primary occupation, classified according to the system used by the respective national census office at the time. For someone with more than one job, the primary occupation is usually the one in which the person spent the most time or earned the most money, although this may not have been explicit in the instructions for a specific census. To ensure confidentiality, very small occupations are recoded to a residual category indicating the persons had an occupation, but the job title is not identified. The number of cases recoded should be too small to affect analyses. OCC is a 4-digit numeric variable. Some samples use fewer than 4 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_OCC3 - Occupation [3 digit] Argentina 1980 - see Variable: AR1980A_OCC - Occupation Argentina 1991 - see Variable: AR1991A_OCC - Occupation Argentina 2001 - see Variable: AR2001A_OCC4 - Occupation (4-digits) Armenia 2011 - see Variable: AM2011A_OCC - Occupation Austria 1971 - see Variable: AT1971A_OCCSM - Occupation of supporter: sub-major groups Austria 1981 - see Variable: AT1981A_OCCSM - Occupation of supporter: sub-major groups Austria 1991 - see Variable: AT1991A_OCCSM - Occupation of supporter: sub-major groups Austria 2001 - see Variable: AT2001A_OCCSM - Occupation of supporter: sub-major groups Belarus 1999 - see Variable: BY1999A_OCC2 - Occupation, 2 digits Belarus 2009 - see Variable: BY2009A_OCC - Occupation Benin 1979 - see Variable: BJ1979A_OCC - Occupation (2-digits) Benin 1992 - see Variable: BJ1992A_OCC3 - Occupation (3-digits) Benin 2002 - see Variable: BJ2002A_OCC - Occupation (3-digits) Benin 2013 - see Variable: BJ2013A_OCC - Occupation (3-digit) Bolivia 1976 - see Variable: BO1976A_OCC2 - Occupation, 2 digits Bolivia 1992 - see Variable: BO1992A_OCC - Occupation Bolivia 2001 - see Variable: BO2001A_OCC - Occupation, 3 digits Bolivia 2012 - see Variable: BO2012A_OCC2 - Occupation (3 digit) Botswana 1981 - see Variable: BW1981A_OCC - Occupation Botswana 1991 - see Variable: BW1991A_OCC - Occupation (last 30 days) Botswana 2001 - see Variable: BW2001A_OCC - Occupation in the past 7 days, 3 digit Botswana 2011 - see Variable: BW2011A_OCC - Occupation, 3-digits Brazil 1960 - see Variable: BR1960A_USUALOCC - Usual occupation Brazil 1970 - see Variable: BR1970A_MAINOCC - Principal occupation Brazil 1980 - see Variable: BR1980A_OCC - Occupation Brazil 1991 - see Variable: BR1991A_OCC - Occupation Brazil 2000 - see Variable: BR2000A_OCC - Occupation, 4 digits Brazil 2010 - see Variable: BR2010A_OCC - Occupation held from July 25 to July 31, 2010 Burkina Faso 1985 - see Variable: BF1985A_OCC - Principal occupation Burkina Faso 1996 - see Variable: BF1996A_OCC - Principal occupation Cambodia 1998 - see Variable: KH1998A_OCC - Occupation Cambodia 2004 - see Variable: KH2004A_OCC3 - Occupation (3-digits) Cambodia 2008 - see Variable: KH2008A_OCC - Occupation Cambodia 2013 - see Variable: KH2013A_OCC - Occupation (3-digits) Cambodia 2019 - see Variable: KH2019A_OCC1 - Occupation, 1-digit Cameroon 1976 - see Variable: CM1976A_OCC2 - Occupation (2 digits) Cameroon 2005 - see Variable: CM2005A_OCC - Occupation Canada 1971 - see Variable: CA1971A_OCC - Occupation Canada 1981 - see Variable: CA1981A_OCC - Occupation (1981 classification basis) Canada 1991 - see Variable: CA1991A_OCC80 - Occupation (1980 classification basis) Canada 2001 - see Variable: CA2001A_NOCS01P - Occupation (2001 national occupational classification for statistics) Canada 2011 - see Variable: CA2011A_OCC - Occupation Chile 1960 - see Variable: CL1960A_OCC - Occupation Chile 1970 - see Variable: CL1970A_OCC3 - Occupation (3-digit) Chile 1982 - see Variable: CL1982A_OCC3 - Occupation (3-digit) Chile 1992 - see Variable: CL1992A_OCC3 - Occupation (3-digit) Chile 2002 - see Variable: CL2002A_OCC - Occupation China 1982 - see Variable: CN1982A_OCC - Occupation China 1990 - see Variable: CN1990A_OCC - Occupation China 2000 - see Variable: CN2000A_OCC - Occupation (2-digit) Colombia 1964 - see Variable: CO1964A_OCC2 - Occupation (COTA, 4 digits) Colombia 1973 - see Variable: CO1973A_OCC - Occupation last week Costa Rica 1973 - see Variable: CR1973A_OCC3 - Occupation, 3 digits Costa Rica 1984 - see Variable: CR1984A_OCC - Occupation, 3 digits Costa Rica 2000 - see Variable: CR2000A_OCC3 - Occupation, 3 digits Costa Rica 2011 - see Variable: CR2011A_OCC - Occupation, 2-digit Cuba 2002 - see Variable: CU2002A_OCC - Occupation Cuba 2012 - see Variable: CU2012A_OCC3 - Main occupation (3-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_OCC2 - Current occupation (2-digit) Dominican Republic 1960 - see Variable: DO1960A_OCC - Occupation Dominican Republic 1970 - see Variable: DO1970A_OCC1 - Current occupation, 3 digits Dominican Republic 1981 - see Variable: DO1981A_OCC - Occupation Dominican Republic 2002 - see Variable: DO2002A_OCC - Occupation Dominican Republic 2010 - see Variable: DO2010A_OCC - Occupation Ecuador 1962 - see Variable: EC1962A_OCC - Occupation Ecuador 1974 - see Variable: EC1974A_OCC3 - Occupation, three digits Ecuador 1982 - see Variable: EC1982A_OCC3 - Occupation, 3 digits Ecuador 1990 - see Variable: EC1990A_OCC3 - Occupation, 3 digits Ecuador 2001 - see Variable: EC2001A_OCC - Occupation, 3 digits Ecuador 2010 - see Variable: EC2010A_OCC3 - Occupation (3 digits, ISCO 08) Egypt 1986 - see Variable: EG1986A_OCC3 - Occupation (3-digit) Egypt 2006 - see Variable: EG2006A_OCC - Primary occupation, 3-digit El Salvador 1992 - see Variable: SV1992A_OCC - Occupation (3-digit) El Salvador 2007 - see Variable: SV2007A_OCC3DIG - Occupation (3-digit) Ethiopia 1984 - see Variable: ET1984A_OCC2 - Occupation (2-digit) Ethiopia 1994 - see Variable: ET1994A_OCC - Occupation Fiji 1976 - see Variable: FJ1976A_OCC - Occupation Fiji 1986 - see Variable: FJ1986A_OCC - Occupation Fiji 1996 - see Variable: FJ1996A_OCC3 - Occupation (3 digits) Fiji 2007 - see Variable: FJ2007A_OCC3 - Occupation, 3 digits Fiji 2014 - see Variable: FJ2014A_OCC3 - Occupation (3 digits) Finland 2010 - see Variable: FI2010A_OCC - Occupation France 1962 - see Variable: FR1962A_SOCCUP - SAPHIR occupation France 1968 - see Variable: FR1968A_SOCC - SAPHIR occupation France 1975 - see Variable: FR1975A_SOCC - SAPHIR occupation France 1982 - see Variable: FR1982A_SOCC - SAPHIR occupation France 1990 - see Variable: FR1990A_SOCC - Saphir occupation France 1999 - see Variable: FR1999A_OCC - Occupation, ISCO France 2006 - see Variable: FR2006A_PROF486 - Detailed profession (4-digit) France 2011 - see Variable: FR2011A_PROF - Profession, 486 categories Germany 1970 - see Variable: DE1970A_OCC - Occupation Germany 1981 - see Variable: DE1981A_OCC - Occupation Germany 1987 - see Variable: DE1987A_OCC - Occupation Ghana 1984 - see Variable: GH1984A_OCC2 - Occupation, 2 digits Ghana 2000 - see Variable: GH2000A_OCC - Occupation Ghana 2010 - see Variable: GH2010A_OCC - Occupation (major groups) Greece 1971 - see Variable: GR1971A_OCC - Occupation Greece 1981 - see Variable: GR1981A_OCC - Occupation Greece 1991 - see Variable: GR1991A_OCC - Occupation Greece 2001 - see Variable: GR2001A_OCC - Occupation Greece 2011 - see Variable: GR2011A_OCC - Occupation Guatemala 1964 - see Variable: GT1964A_OCC3 - Occupation (3-digits) Guatemala 1973 - see Variable: GT1973A_OCC3 - Principal occupation (3-digits) Guatemala 1981 - see Variable: GT1981A_OCC3 - Principal occupation (3-digits) Guatemala 1994 - see Variable: GT1994A_OCC - Principal occupation (1-digit) Guatemala 2002 - see Variable: GT2002A_OCC3 - Principal occupation (3-digits) Guinea 1983 - see Variable: GN1983A_OCC2 - Occupation, 2 digits Guinea 1996 - see Variable: GN1996A_OCC - Occupation Guinea 2014 - see Variable: GN2014A_OCC - Occupation (3-digit) Haiti 1982 - see Variable: HT1982A_OCC - Main occupation or profession Haiti 2003 - see Variable: HT2003A_OCC2 - Occupation, 3 digits Honduras 1961 - see Variable: HN1961A_OCC - Occupation (2-digits) Honduras 1974 - see Variable: HN1974A_OCC2 - Occupation (3-digits) Honduras 1988 - see Variable: HN1988A_OCC4 - Occupation (4-digits) Honduras 2001 - see Variable: HN2001A_OCC - Occupation (4-digit) Honduras 2013 - see Variable: HN2013A_OCC3 - Occupation (3-digit) Hungary 1970 - see Variable: HU1970A_OCC - Occupation Hungary 1980 - see Variable: HU1980A_OCC - Occupation, scope of activity Hungary 1990 - see Variable: HU1990A_OCC - Occupation Hungary 2001 - see Variable: HU2001A_OCC - Occupation Hungary 2011 - see Variable: HU2011A_OCC - Occupation Indonesia 1971 - see Variable: ID1971A_OCC - Occupation Indonesia 1976 - see Variable: ID1976A_OCC - Primary occupation during past week Indonesia 1980 - see Variable: ID1980A_OCC - Primary occupation during the previous week (3 digit version) Indonesia 1985 - see Variable: ID1985A_OCC - Primary occupation Indonesia 1990 - see Variable: ID1990A_OCC - Main occupation last week Indonesia 1995 - see Variable: ID1995A_OCC - Occupation Indonesia 2005 - see Variable: ID2005A_OCC - Occupation Iran 2006 - see Variable: IR2006A_OCC4 - Occupation Iran 2011 - see Variable: IR2011A_OCC - Occupation (3-digit) Iraq 1997 - see Variable: IQ1997A_OCC - Occupation Ireland 1971 - see Variable: IE1971A_OCC - Occupation Ireland 1981 - see Variable: IE1981A_OCC - Occupation Ireland 1986 - see Variable: IE1986A_OCC - Occupation group Ireland 1991 - see Variable: IE1991A_OCC - Occupation group Ireland 1996 - see Variable: IE1996A_OCC - Occupation Ireland 2002 - see Variable: IE2002A_OCC - Occupation Ireland 2006 - see Variable: IE2006A_OCC - Occupation group Ireland 2011 - see Variable: IE2011A_OCC - Occupation (shuffled) Ireland 2016 - see Variable: IE2016A_OCC - Occupation (groups) Israel 1972 - see Variable: IL1972A_OCC - Occupation Israel 1983 - see Variable: IL1983A_OCC - Occupation Israel 1995 - see Variable: IL1995A_OCC - Occupation Israel 2008 - see Variable: IL2008A_OCC - Occupation Italy 2001 - see Variable: IT2001A_OCC - Occupation Italy 2011 - see Variable: IT2011A_WKTYPE - Type of work Jamaica 1982 - see Variable: JM1982A_OCC - Occupation during past week / in last job Jamaica 1991 - see Variable: JM1991A_OCC - Occupation during past week/in last job Jamaica 2001 - see Variable: JM2001A_OCC3 - Occupation 3-digit Jordan 2004 - see Variable: JO2004A_OCC3 - Major current occupation (3-digit) Kenya 1989 - see Variable: KE1989A_OCC4 - Occupation, 4 digits Kenya 2019 - see Variable: KE2019A_OCC3 - Occupation (3-digit) Kyrgyzstan 1999 - see Variable: KG1999A_OCC - Main activity Laos 1995 - see Variable: LA1995A_OCC1 - Main occupation in the last 12 months (1-digit) Lesotho 1996 - see Variable: LS1996A_OCC - Occupation (2-digits) Lesotho 2006 - see Variable: LS2006A_OCC - Occupation (2-digits) Liberia 1974 - see Variable: LR1974A_OCC2 - Occupation (2-digit) Liberia 2008 - see Variable: LR2008A_OCC - Occupation Malawi 1987 - see Variable: MW1987A_OCC2 - Occupation, 2 digit Malawi 1998 - see Variable: MW1998A_OCC2 - Occupation, 2-digit Malawi 2008 - see Variable: MW2008A_OCC2 - Occupation (2 digits) Malawi 2018 - see Variable: MW2018A_OCC1 - Main occupation (1-digit) Malaysia 1970 - see Variable: MY1970A_OCC - Occupation last week Malaysia 1980 - see Variable: MY1980A_OCC3 - Principal occupation last week (3 digits) Malaysia 1991 - see Variable: MY1991A_OCC3 - Principal occupation (3 digits) Malaysia 2000 - see Variable: MY2000A_OCC3 - Occupation -- 3 digits Mali 1987 - see Variable: ML1987A_OCC - Occupation last month Mali 1998 - see Variable: ML1998A_OCC - Main occupation Mali 2009 - see Variable: ML2009A_OCC - Principal occupation Mauritius 1990 - see Variable: MU1990A_OCC3 - Occupation (3-digit) Mauritius 2000 - see Variable: MU2000A_OCC4 - Occupation (4 digit) Mauritius 2011 - see Variable: MU2011A_OCC4 - Occupation (4-digit) Mexico 1960 - see Variable: MX1960A_OCC2 - Principal occupation, 2 digits Mexico 1970 - see Variable: MX1970A_OCC3 - Occupation 3 digit Mexico 1990 - see Variable: MX1990A_OCC - Occupation, 4 digits Mexico 1995 - see Variable: MX1995A_OCC - Occupation Mexico 2000 - see Variable: MX2000A_OCC4 - Occupation, 4 digits Mexico 2010 - see Variable: MX2010A_OCC - Occupation or trade Mexico 2015 - see Variable: MX2015A_OCC - Occupation Mexico 2020 - see Variable: MX2020A_OCC3 - Occupation (3-digits) Mongolia 2000 - see Variable: MN2000A_OCC - Occupation Mongolia 2010 - see Variable: MN2010A_OCC3 - Occupation 3 digits (ISCO-2008) Mongolia 2020 - see Variable: MN2020A_OCC3 - Occupation (3-digit) Morocco 1982 - see Variable: MA1982A_OCC3 - Occupation (3-digit) Morocco 1994 - see Variable: MA1994A_OCC3 - Occupation, 3-digit Morocco 2004 - see Variable: MA2004A_OCC3 - Occupation (3-digit) Morocco 2014 - see Variable: MA2014A_OCC2 - Occupation (2-digit) Mozambique 1997 - see Variable: MZ1997A_OCC2 - Occupation 3-digit Mozambique 2007 - see Variable: MZ2007A_OCC - Occupation Mozambique 2017 - see Variable: MZ2017A_OCC3 - Main occupation (3-digits ISCO 2008) Myanmar 2014 - see Variable: MM2014A_OCC - Occupation Nepal 2001 - see Variable: NP2001A_OCC - Usual occupation Nepal 2011 - see Variable: NP2011A_OCC1 - Occupation (1-digit) Netherlands 1960 - see Variable: NL1960A_OCC - Occupation Netherlands 1971 - see Variable: NL1971A_OCC - Occupation Netherlands 2001 - see Variable: NL2001A_OCC - Occupation Netherlands 2011 - see Variable: NL2011A_OCC - Occupation (1-digit) Nicaragua 1971 - see Variable: NI1971A_OCC - Occupation Nicaragua 1995 - see Variable: NI1995A_OCC - Occupation (ISCO 88, 3 digits) Nicaragua 2005 - see Variable: NI2005A_OCC3 - Occupation (ISCO 88, 3 digits) Pakistan 1973 - see Variable: PK1973A_OCC3 - Occupation Palestine 1997 - see Variable: PS1997A_OCC - Main occupation Palestine 2007 - see Variable: PS2007A_OCC - Main occupation Palestine 2017 - see Variable: PS2017A_OCC - Occupation Panama 1960 - see Variable: PA1960A_OCC4 - Occupation (4-digit) Panama 1970 - see Variable: PA1970A_OCC2 - Occupation, 2-digit Panama 1980 - see Variable: PA1980A_OCC2 - Occupation (3-digit) Panama 1990 - see Variable: PA1990A_OCC - Occupation Panama 2000 - see Variable: PA2000A_OCC - Occupation Panama 2010 - see Variable: PA2010A_OCC - Occupation, 3 digits Papua New Guinea 1980 - see Variable: PG1980A_OCC - Occupation, 3 digits Papua New Guinea 1990 - see Variable: PG1990A_OCC - Occupation Papua New Guinea 2000 - see Variable: PG2000A_OCC - Occupation (4-digit) Paraguay 1962 - see Variable: PY1962A_OCC1 - Occupation (1-digit) Paraguay 1972 - see Variable: PY1972A_OCC3 - Occupation (3 digits) Paraguay 1982 - see Variable: PY1982A_OCC3 - Occupation, 3-digits Paraguay 1992 - see Variable: PY1992A_OCC2 - Main occupation, 3 digits Paraguay 2002 - see Variable: PY2002A_OCC - Occupation (4 digits) Peru 1993 - see Variable: PE1993A_OCC - Occupation (3 digits) Peru 2007 - see Variable: PE2007A_OCC - Main occupation last week (3 digits) Peru 2017 - see Variable: PE2017A_OCC1 - Occupation (1-digit, in primary job last week) Philippines 1990 - see Variable: PH1990A_OCC - Occupation Philippines 2000 - see Variable: PH2000A_OCC - Occupation Philippines 2010 - see Variable: PH2010A_OCC3 - Usual occupation (3-digit) Poland 1978 - see Variable: PL1978A_OCC - Occupation Poland 1988 - see Variable: PL1988A_OCC - Main occupation Poland 2002 - see Variable: PL2002A_OCC - Occupation Portugal 1981 - see Variable: PT1981A_OCC - Main occupation Portugal 1991 - see Variable: PT1991A_OCC - Main occupation Portugal 2001 - see Variable: PT2001A_OCC - Main occupation Portugal 2011 - see Variable: PT2011A_OCC - Main occupation Puerto Rico 1970 - see Variable: PR1970A_OCC - Occupation Puerto Rico 1980 - see Variable: PR1980A_OCC - Occupation Puerto Rico 1990 - see Variable: PR1990A_OCC - Occupation Puerto Rico 2000 - see Variable: PR2000A_OCC - Occupation Puerto Rico 2005 - see Variable: PR2005A_OCC - Occupation Puerto Rico 2010 - see Variable: PR2010A_OCC - Occupation Puerto Rico 2015 - see Variable: PR2015A_OCC - Occupation last week Puerto Rico 2020 - see Variable: PR2020A_OCC2010 - Occupation last week, 2010 basis Romania 1992 - see Variable: RO1992A_OCC - Occupation Romania 2002 - see Variable: RO2002A_OCC4 - Occupation, 4 digits Romania 2011 - see Variable: RO2011A_OCC - Occupation (unrecoded) Rwanda 2002 - see Variable: RW2002A_OCC - Occupation Rwanda 2012 - see Variable: RW2012A_OCC2 - Occupation (3-digit) Saint Lucia 1991 - see Variable: LC1991A_OCC - Occupation Senegal 1988 - see Variable: SN1988A_OCC - Occupation Senegal 2002 - see Variable: SN2002A_OCC3 - Occupation, 3 digits Senegal 2013 - see Variable: SN2013A_OCC3 - Profession or occupation (3-digit) Sierra Leone 2004 - see Variable: SL2004A_OCC - Occupation Sierra Leone 2015 - see Variable: SL2015A_OCC - Main occupation in the past 12 months Slovakia 1991 - see Variable: SK1991A_OCC - Occupation (2-digit) Slovakia 2001 - see Variable: SK2001A_OCC2 - Occupation (2-digit) Slovakia 2011 - see Variable: SK2011A_OCC2 - Occupation (2-digit) Slovenia 2002 - see Variable: SI2002A_OCC - Occupation South Africa 1996 - see Variable: ZA1996A_OCC3 - Occupation, 3 digits South Africa 2001 - see Variable: ZA2001A_OCC - Occupation, 3 digit South Africa 2007 - see Variable: ZA2007A_OCC3 - Occupation, 3 digits South Sudan 2008 - see Variable: SS2008A_OCC - Occupation Spain 1981 - see Variable: ES1981A_OCC - Occupation Spain 1991 - see Variable: ES1991A_OCC - Occupation Spain 2001 - see Variable: ES2001A_OCC - Occupation Spain 2011 - see Variable: ES2011A_OCC - Occupation, 2-digits Sudan 2008 - see Variable: SD2008A_OCC - Occupation Suriname 2004 - see Variable: SR2004A_OCC - Occupation Suriname 2012 - see Variable: SR2012A_OCC - Occupation (groups) Switzerland 1970 - see Variable: CH1970A_ISCO - Present occupation (ISCO) Switzerland 1980 - see Variable: CH1980A_ISCO - Present occupation (ISCO-COM) Switzerland 1990 - see Variable: CH1990A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2000 - see Variable: CH2000A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2011 - see Variable: CH2011A_OCC - Current occupation (1-digit, ISCO-08) Tanzania 1988 - see Variable: TZ1988A_OCC - Occupation Tanzania 2002 - see Variable: TZ2002A_OCC - Occupation last week Tanzania 2012 - see Variable: TZ2012A_OCC - Occupation Thailand 1970 - see Variable: TH1970A_OCC - Principal occupation last year Thailand 1980 - see Variable: TH1980A_OCC - Occupation last year Thailand 1990 - see Variable: TH1990A_OCC3 - Occupation last year Thailand 2000 - see Variable: TH2000A_OCC3 - Occupation last year, 3 digits Togo 1960 - see Variable: TG1960A_OCC - Occupation (3-digits) Togo 1970 - see Variable: TG1970A_OCC3 - Occupation (3-digits) Togo 2010 - see Variable: TG2010A_OCC2 - Occupation (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_OCC - Main occupation (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_OCC - Main occupation during previous week (three digits) Trinidad and Tobago 2000 - see Variable: TT2000A_OCC - Main occupation (3 digits) Turkey 1985 - see Variable: TR1985A_OCC2 - Occupation (2-digit) Turkey 1990 - see Variable: TR1990A_OCC2 - Current occupation (2 digits) Turkey 2000 - see Variable: TR2000A_OCC2 - Current occupation, 2 digit Uganda 1991 - see Variable: UG1991A_OCC - Occupation, 3 digits Uganda 2002 - see Variable: UG2002A_OCC - Occupation, 3 digits Uganda 2014 - see Variable: UG2014A_OCC - Occupation (2-digits) United Kingdom 1961 - see Variable: UK1961A_OCC - Occupation United Kingdom 1971 - see Variable: UK1971A_OCC - Occupation United Kingdom 1991 - see Variable: UK1991A_OCC - Occupational classification United Kingdom 2001 - see Variable: UK2001A_OCC3 - Standard occupational classification 2000-minor United States 1960 - see Variable: US1960A_OCC - Occupation United States 1970 - see Variable: US1970A_OCC - Occupation United States 1980 - see Variable: US1980A_OCC - Occupation United States 1990 - see Variable: US1990A_OCC - Occupation United States 2000 - see Variable: US2000A_OCC - Occupation United States 2005 - see Variable: US2005A_OCC2000M - Occupation, 2000 basis, modal category assignment United States 2010 - see Variable: US2010A_OCC - Occupation United States 2015 - see Variable: US2015A_OCC - Occupation last week United States 2020 - see Variable: US2020A_OCC - Occupation last week Uruguay 1963 - see Variable: UY1963A_OCC2 - Primary occupation [2-digit] Uruguay 1975 - see Variable: UY1975A_OCC - Occupation (COTA, 3 digits) Uruguay 1985 - see Variable: UY1985A_OCC - Occupation during the past week Uruguay 1996 - see Variable: UY1996A_OCC - Occupation (ISCO 88, 3 digits) Uruguay 2006 - see Variable: UY2006A_OCC3 - Occupation (ISCO-88, 3 digits) Venezuela 1981 - see Variable: VE1981A_OCC3 - Occupation, 3 digits Venezuela 1990 - see Variable: VE1990A_OCC - Occupation, 3 digits Venezuela 2001 - see Variable: VE2001A_OCC - Occupation Vietnam 1989 - see Variable: VN1989A_OCC2 - Occupation, 2 digits Vietnam 1999 - see Variable: VN1999A_OCC3 - Occupation, 3 digit Vietnam 2009 - see Variable: VN2009A_OCC - Occupation Vietnam 2019 - see Variable: VN2019A_OCC1 - Occupation, 1 digit Zambia 1990 - see Variable: ZM1990A_OCC - Occupation Zambia 2000 - see Variable: ZM2000A_OCC - Main occupation last 12 months, 3 digits Zambia 2010 - see Variable: ZM2010A_OCC2 - Main occupation last 12 months, 3 digits Zimbabwe 2012 - see Variable: ZW2012A_OCC - Occupation (3-digits) Work Variables -- PERSON Industry, general recode INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown Work Variables -- PERSON Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_IND4 - Industry [4 digit] Argentina 1980 - see Variable: AR1980A_IND - Industry Argentina 1991 - see Variable: AR1991A_IND - Industry Argentina 2001 - see Variable: AR2001A_IND - Industry Armenia 2001 - see Variable: AM2001A_IND - Principal activity at place of work Armenia 2011 - see Variable: AM2011A_IND - Industry Austria 1971 - see Variable: AT1971A_INDBR - Economic activity of supporter: branch Austria 1981 - see Variable: AT1981A_INDBR - Economic activity of supporter: branch Austria 1991 - see Variable: AT1991A_INDBR - Economic activity of supporter: branch Austria 2001 - see Variable: AT2001A_INDBR - Economic activity of supporter: branch Austria 2011 - see Variable: AT2011A_IND - Industry Bangladesh 1991 - see Variable: BD1991A_IND - Industry Bangladesh 2001 - see Variable: BD2001A_IND - Main work field Bangladesh 2011 - see Variable: BD2011A_IND - Industry Belarus 2009 - see Variable: BY2009A_ECONACT - Industry Benin 1979 - see Variable: BJ1979A_IND - Industry (1-digit) Benin 1992 - see Variable: BJ1992A_IND3 - Industry (2-digits) Benin 2002 - see Variable: BJ2002A_IND2 - Industry (2-digits) Benin 2013 - see Variable: BJ2013A_IND3 - Industry (3-digit) Bolivia 1976 - see Variable: BO1976A_IND - Industry Bolivia 1992 - see Variable: BO1992A_IND3 - Activity, 3 digits Bolivia 2001 - see Variable: BO2001A_IND3 - Industry, 3 digits Bolivia 2012 - see Variable: BO2012A_IND2 - Industry (2 digit) Botswana 1981 - see Variable: BW1981A_IND - Industry Botswana 1991 - see Variable: BW1991A_IND - Industry Botswana 2001 - see Variable: BW2001A_IND - Industry Botswana 2011 - see Variable: BW2011A_IND - Industry, 3-digits Brazil 1960 - see Variable: BR1960A_INDUSTRY - Industry Brazil 1970 - see Variable: BR1970A_INDUSTRY - Industry Brazil 1980 - see Variable: BR1980A_INDUSTRY - Industry Brazil 1991 - see Variable: BR1991A_IND - Industry Brazil 2000 - see Variable: BR2000A_IND - Industry, 5 digits Brazil 2010 - see Variable: BR2010A_IND - Industry of work from July 25 to July 31, 2010 Burkina Faso 1996 - see Variable: BF1996A_IND - Branch of activity Cambodia 1998 - see Variable: KH1998A_IND - Industry Cambodia 2004 - see Variable: KH2004A_IND3 - Industry (3-digits) Cambodia 2008 - see Variable: KH2008A_IND - Industry Cambodia 2013 - see Variable: KH2013A_IND - Industry (3-digits) Cambodia 2019 - see Variable: KH2019A_IND3 - Industy (ISIC rev 4, 3-digit) Cameroon 2005 - see Variable: CM2005A_IND - Industry Canada 1971 - see Variable: CA1971A_IND - Industry Canada 1981 - see Variable: CA1981A_IND - Industry (1981 standard industrial classification) Canada 1991 - see Variable: CA1991A_IND80 - Industry (1980 standard industrial classification) Canada 2001 - see Variable: CA2001A_IND80P - Industry (1980 Standard Industrial Classification) Canada 2011 - see Variable: CA2011A_IND - Industry Chile 1960 - see Variable: CL1960A_IND - Industry Chile 1970 - see Variable: CL1970A_IND4 - Industry (4-digit) Chile 1982 - see Variable: CL1982A_IND4 - Industry (4-digit) Chile 1992 - see Variable: CL1992A_IND - Industry Chile 2002 - see Variable: CL2002A_IND - Industry Chile 2017 - see Variable: CL2017A_IND - Industry (1-digit) China 1982 - see Variable: CN1982A_INDUSTRY - Industry China 1990 - see Variable: CN1990A_IND - Industry China 2000 - see Variable: CN2000A_IND - Industry (2-digit) Colombia 1964 - see Variable: CO1964A_IND4 - Industry, 4 digits Colombia 1973 - see Variable: CO1973A_IND - Industry Colombia 1993 - see Variable: CO1993A_IND - Industry Colombia 2005 - see Variable: CO2005A_IND - Industry (2-digit) Costa Rica 1963 - see Variable: CR1963A_IND3 - Industry, 3 digits Costa Rica 1973 - see Variable: CR1973A_IND4 - Industry, 4 digits Costa Rica 1984 - see Variable: CR1984A_IND4 - Industry, 4 digits Costa Rica 2000 - see Variable: CR2000A_IND3 - Industry, 3 digits Costa Rica 2011 - see Variable: CR2011A_IND - Industry 2-digit Cuba 2002 - see Variable: CU2002A_IND - Industry Cuba 2012 - see Variable: CU2012A_IND - Industry Côte d'Ivoire 1988 - see Variable: CI1988A_IND - Industry (1-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_IND2 - Industry sector (detailed) Dominican Republic 1960 - see Variable: DO1960A_IND - Industry Dominican Republic 1970 - see Variable: DO1970A_IND1 - Industry, 3 digits Dominican Republic 1981 - see Variable: DO1981A_IND - Industry (3-digit) Dominican Republic 2002 - see Variable: DO2002A_IND - Industry Dominican Republic 2010 - see Variable: DO2010A_IND - Main activity of business Ecuador 1962 - see Variable: EC1962A_IND3 - Industry, 3 digits Ecuador 1982 - see Variable: EC1982A_IND3 - Industry Ecuador 1990 - see Variable: EC1990A_IND3 - Industry, 3 digits Ecuador 2001 - see Variable: EC2001A_IND - Industry, 3 digits Ecuador 2010 - see Variable: EC2010A_IND3 - Industry (3 digits, ISIC rev 4) Egypt 1986 - see Variable: EG1986A_IND3 - Industry (3-digit) Egypt 1996 - see Variable: EG1996A_IND3 - Industry (ISIC) Egypt 2006 - see Variable: EG2006A_IND - Industry, 3-digit El Salvador 1992 - see Variable: SV1992A_IND - Industry (3-digit) El Salvador 2007 - see Variable: SV2007A_IND3DIG - Industry (3-digit) Ethiopia 1984 - see Variable: ET1984A_IND2 - Industry Ethiopia 1994 - see Variable: ET1994A_IND - Industry Fiji 1966 - see Variable: FJ1966A_IND - Industry Fiji 1976 - see Variable: FJ1976A_IND - Industry Fiji 1986 - see Variable: FJ1986A_IND - Industry 3 digits Fiji 1996 - see Variable: FJ1996A_IND2DIG - Industry (2 digits) Fiji 2007 - see Variable: FJ2007A_IND2 - Industry, 2 digits Fiji 2014 - see Variable: FJ2014A_IND - Industry Finland 2010 - see Variable: FI2010A_IND - Industry France 1962 - see Variable: FR1962A_IND - Industry France 1968 - see Variable: FR1968A_IND41 - Industry, 41 categories France 1975 - see Variable: FR1975A_INDUN - Industry, UNO France 1982 - see Variable: FR1982A_INDUN - Industry, United Nations nomenclature France 1990 - see Variable: FR1990A_IND15 - Industry, 15 categories France 1999 - see Variable: FR1999A_INDCITI - Industry, ISIC France 2006 - see Variable: FR2006A_IND700N - Economic activity in 700 categories (2003 classification) numeric recode France 2011 - see Variable: FR2011A_IND - Industry, 732 categories Germany 1970 - see Variable: DE1970A_IND - Industry Germany 1971 - see Variable: DE1971A_IND - Industry Germany 1981 - see Variable: DE1981A_IND - Industry Germany 1987 - see Variable: DE1987A_IND - Industry Ghana 2000 - see Variable: GH2000A_IND - Industry Ghana 2010 - see Variable: GH2010A_IND - Industry (major groups) Greece 1971 - see Variable: GR1971A_IND - Industry Greece 1981 - see Variable: GR1981A_IND - Industry Greece 1991 - see Variable: GR1991A_IND - Industry Greece 2001 - see Variable: GR2001A_IND - Industry Greece 2011 - see Variable: GR2011A_IND - Industry Guatemala 1964 - see Variable: GT1964A_IND3 - Field of economic activity (3-digits) Guatemala 1973 - see Variable: GT1973A_IND3 - Industry (3-digits) Guatemala 1981 - see Variable: GT1981A_IND3 - Industry (3-digits) Guatemala 1994 - see Variable: GT1994A_IND2 - Field of economic activity (2-digits) Guatemala 2002 - see Variable: GT2002A_IND1 - Field of economic activity (1-digit) Guinea 1983 - see Variable: GN1983A_IND2 - Branch of economic activity, 2 digits Guinea 2014 - see Variable: GN2014A_IND - Industry (3-digit) Haiti 1982 - see Variable: HT1982A_IND - Branch of work Haiti 2003 - see Variable: HT2003A_IND2 - Industry, 3 digits Honduras 1961 - see Variable: HN1961A_IND - Industry (2-digits) Honduras 1974 - see Variable: HN1974A_IND - Industry (3-digits) Honduras 2001 - see Variable: HN2001A_IND - Industry (4-digit) Honduras 2013 - see Variable: HN2013A_IND3 - Economic activity (3-digit) Hungary 2001 - see Variable: HU2001A_IND - Industry, branch of economy Hungary 2011 - see Variable: HU2011A_IND - Industry Indonesia 1971 - see Variable: ID1971A_IND - Industry Indonesia 1976 - see Variable: ID1976A_IND - Industry Indonesia 1980 - see Variable: ID1980A_IND - Industry Indonesia 1985 - see Variable: ID1985A_IND - Industry of primary occupation Indonesia 1990 - see Variable: ID1990A_IND - Industry of main occupation last week Indonesia 1995 - see Variable: ID1995A_IND - Industry Indonesia 2000 - see Variable: ID2000A_IND - Industry of primary occupation Indonesia 2005 - see Variable: ID2005A_IND - Industry Indonesia 2010 - see Variable: ID2010A_IND - Industry Iran 2006 - see Variable: IR2006A_IND4 - Industry Iran 2011 - see Variable: IR2011A_IND - Industry (3-digit) Iraq 1997 - see Variable: IQ1997A_IND - Industry Ireland 1971 - see Variable: IE1971A_IND - Industry Ireland 1981 - see Variable: IE1981A_IND - Industry class Ireland 1986 - see Variable: IE1986A_IND - Industry class Ireland 1991 - see Variable: IE1991A_IND - Industry class Ireland 1996 - see Variable: IE1996A_IND - Industry class Ireland 2002 - see Variable: IE2002A_IND - Industry class Ireland 2006 - see Variable: IE2006A_IND - Industry class Ireland 2011 - see Variable: IE2011A_IND - Industry Ireland 2016 - see Variable: IE2016A_IND - Industry Israel 1972 - see Variable: IL1972A_IND - Industry Israel 1983 - see Variable: IL1983A_IND - Industry Israel 1995 - see Variable: IL1995A_IND - Industry Israel 2008 - see Variable: IL2008A_IND - Branch of economy Italy 2001 - see Variable: IT2001A_IND - Industry Italy 2011 - see Variable: IT2011A_IND - Sector of economic activity Jamaica 1982 - see Variable: JM1982A_IND - Industry or type of business during past week / in last job Jamaica 1991 - see Variable: JM1991A_IND3 - Industry during past week or in last job, 3 digits Jamaica 2001 - see Variable: JM2001A_IND3 - Industry 3-digit Jordan 2004 - see Variable: JO2004A_IND - Major current economic activity of the establishment Kenya 2019 - see Variable: KE2019A_IND1 - Industry, ISIC section Kyrgyzstan 1999 - see Variable: KG1999A_IND - Activity type of an enterprise you are working in Kyrgyzstan 2009 - see Variable: KG2009A_IND - Type of industry, enterprise or organization Laos 1995 - see Variable: LA1995A_IND2 - Main industry in the last 12 months (2-digit) Laos 2005 - see Variable: LA2005A_IND3 - Industry (ISIC 3-digit) Laos 2015 - see Variable: LA2015A_IND2 - Industry (2-digit ISIC Rev. 4) Lesotho 2006 - see Variable: LS2006A_IND - Industry (2-digits) Liberia 1974 - see Variable: LR1974A_IND - Industry (3-digit) Liberia 2008 - see Variable: LR2008A_IND - Industry Malawi 1987 - see Variable: MW1987A_IND2 - Industry, 2 digit Malawi 1998 - see Variable: MW1998A_IND4 - Industry, 4-digit Malawi 2008 - see Variable: MW2008A_IND2 - Main industry Malawi 2018 - see Variable: MW2018A_IND3 - Main industry (ISIC 2008 3-digit) Malaysia 1970 - see Variable: MY1970A_IND3 - Industry last week Malaysia 1980 - see Variable: MY1980A_IND3 - Industry last week (3 digits) Malaysia 1991 - see Variable: MY1991A_IND3 - Main industry (3 digits) Malaysia 2000 - see Variable: MY2000A_IND3 - Main industry - 3 digits Mali 1987 - see Variable: ML1987A_IND - Principal branch of employment last month Mali 1998 - see Variable: ML1998A_IND - Branch of economic activity Mali 2009 - see Variable: ML2009A_IND - Industry Mauritius 1990 - see Variable: MU1990A_IND - Industry (1-digit) Mauritius 2000 - see Variable: MU2000A_IND1 - Industry (1 digit) Mauritius 2011 - see Variable: MU2011A_IND2 - Industry (2-digit) Mexico 1960 - see Variable: MX1960A_IND - Industry Mexico 1970 - see Variable: MX1970A_IND - Industry Mexico 1990 - see Variable: MX1990A_IND5 - Industry, 5 digits Mexico 1995 - see Variable: MX1995A_IND - Industry Mexico 2000 - see Variable: MX2000A_IND3 - Industry, 3 digits Mexico 2010 - see Variable: MX2010A_IND - Industry Mexico 2015 - see Variable: MX2015A_IND - Industry Mexico 2020 - see Variable: MX2020A_IND - Industry (4-digits) Mongolia 2000 - see Variable: MN2000A_IND - Industry Mongolia 2010 - see Variable: MN2010A_IND2 - Industry, division (ISIC Revision 4) Mongolia 2020 - see Variable: MN2020A_IND3 - Main industry (3-digit) Morocco 1982 - see Variable: MA1982A_IND3 - Industry (3-digit) Morocco 1994 - see Variable: MA1994A_IND2 - Industry (2 digits) Morocco 2004 - see Variable: MA2004A_IND2 - Sector of economic activity (2-digit) Morocco 2014 - see Variable: MA2014A_IND2 - Industry (2-digit) Mozambique 1997 - see Variable: MZ1997A_IND1 - Industry Mozambique 2007 - see Variable: MZ2007A_IND - Industry Mozambique 2017 - see Variable: MZ2017A_IND2 - Main economic activity (2-digits CAE Rev.2) Myanmar 2014 - see Variable: MM2014A_IND - Industry Nepal 2001 - see Variable: NP2001A_IND - Usual industry Nepal 2011 - see Variable: NP2011A_IND - Industry (2-digit) Netherlands 1960 - see Variable: NL1960A_IND - Industry Netherlands 1971 - see Variable: NL1971A_IND - Industry Netherlands 2001 - see Variable: NL2001A_IND - Industry Netherlands 2011 - see Variable: NL2011A_IND - Industry (1-digit) Nicaragua 1971 - see Variable: NI1971A_IND3 - Industry (ISIC2), 3 digits Nicaragua 1995 - see Variable: NI1995A_IND - Industry (ISIC 3.1, 3 digits) Nicaragua 2005 - see Variable: NI2005A_IND3 - Industry (ISIC 3.1, 3 digits)) Pakistan 1973 - see Variable: PK1973A_IND2 - Industry, 2 digit Palestine 1997 - see Variable: PS1997A_IND - Industry Palestine 2007 - see Variable: PS2007A_IND - Industry Palestine 2017 - see Variable: PS2017A_IND - Industry Panama 1960 - see Variable: PA1960A_IND3 - Industry (3 digit) Panama 1970 - see Variable: PA1970A_IND3 - Industry [3 digit] Panama 1980 - see Variable: PA1980A_IND - Industry, 3-digit Panama 1990 - see Variable: PA1990A_IND3 - Industry - 3 Digits Panama 2000 - see Variable: PA2000A_IND - Economic activity, 3 digits Panama 2010 - see Variable: PA2010A_IND - Economic activity, 4 digits Papua New Guinea 1980 - see Variable: PG1980A_IND - Industry, 3 digits Papua New Guinea 2000 - see Variable: PG2000A_IND3 - Industry (3-digit) Paraguay 1962 - see Variable: PY1962A_IND3 - Industry (3 digits) Paraguay 1972 - see Variable: PY1972A_IND3 - Industry (3 digits) Paraguay 1982 - see Variable: PY1982A_IND3 - Industry, 3-digits Paraguay 1992 - see Variable: PY1992A_IND3 - Industry, 3 digits Paraguay 2002 - see Variable: PY2002A_IND - Industry (4 digits) Peru 1993 - see Variable: PE1993A_IND - Economic activity (4 digits) Peru 2007 - see Variable: PE2007A_IND - Economic activity (4-digits) Peru 2017 - see Variable: PE2017A_IND4 - Economic activity (4-digits, in primary job last week) Philippines 1990 - see Variable: PH1990A_IND - Industry Philippines 1995 - see Variable: PH1995A_IND - Industry Philippines 2000 - see Variable: PH2000A_IND - Industry Philippines 2010 - see Variable: PH2010A_IND3 - Kind of business or industry (3-digit) Poland 1978 - see Variable: PL1978A_IND - Industry (of person providing support) Poland 2002 - see Variable: PL2002A_IND - Industry (main employer) Portugal 1981 - see Variable: PT1981A_IND - Industry Portugal 1991 - see Variable: PT1991A_IND - Industry Portugal 2001 - see Variable: PT2001A_IND - Industry Portugal 2011 - see Variable: PT2011A_IND - Industry Puerto Rico 1970 - see Variable: PR1970A_IND1990 - Industry, 1990 basis Puerto Rico 1980 - see Variable: PR1980A_IND1990 - Industry, 1990 basis Puerto Rico 1990 - see Variable: PR1990A_IND - Industry Puerto Rico 2000 - see Variable: PR2000A_IND1990 - Industry, 1990 basis Puerto Rico 2005 - see Variable: PR2005A_IND1990 - Industry, 1990 basis Puerto Rico 2010 - see Variable: PR2010A_IND - Industry Puerto Rico 2015 - see Variable: PR2015A_IND - Industry Puerto Rico 2020 - see Variable: PR2020A_IND - Industry Romania 1977 - see Variable: RO1977A_IND - Industry of supporter Romania 1977 - see Variable: RO1977A_WKACT - Activity category Romania 1992 - see Variable: RO1992A_IND - Industry Romania 2002 - see Variable: RO2002A_IND - Industry Romania 2011 - see Variable: RO2011A_INDGEN - Industry (general categories) Rwanda 2002 - see Variable: RW2002A_IND - Industry Rwanda 2012 - see Variable: RW2012A_IND2 - Industry (3-digit) Saint Lucia 1991 - see Variable: LC1991A_IND3 - Industry, 2 digit Senegal 1988 - see Variable: SN1988A_IND - Industry Senegal 2013 - see Variable: SN2013A_IND3 - Industry (3-digit) Sierra Leone 2004 - see Variable: SL2004A_IND - Industry Slovenia 2002 - see Variable: SI2002A_IND - Industry South Africa 1996 - see Variable: ZA1996A_IND2 - Industry, 2 digits South Africa 2001 - see Variable: ZA2001A_IND3 - Industry, 3 digit South Africa 2007 - see Variable: ZA2007A_IND3 - Industry, 3 digit South Sudan 2008 - see Variable: SS2008A_IND - Industry Spain 1981 - see Variable: ES1981A_IND - Industry Spain 1991 - see Variable: ES1991A_IND - Activity of the establishment Spain 2001 - see Variable: ES2001A_IND - Industry Spain 2011 - see Variable: ES2011A_IND - Industry, 2-digits Sudan 2008 - see Variable: SD2008A_IND - Industry Suriname 2004 - see Variable: SR2004A_IND - Industry Suriname 2012 - see Variable: SR2012A_IND - Industry (groups) Switzerland 1970 - see Variable: CH1970A_IND - Branch of economic activity (industry) Switzerland 1980 - see Variable: CH1980A_IND - Branch of economic activity (industry) Switzerland 1990 - see Variable: CH1990A_IND - Branch of economic activity (industry) Switzerland 2000 - see Variable: CH2000A_IND - Branch of economic activity (industry) Switzerland 2011 - see Variable: CH2011A_IND2 - Industry of local unit, workplace (NOGA 2-digit) Tanzania 2002 - see Variable: TZ2002A_IND - Industry last week Tanzania 2012 - see Variable: TZ2012A_IND - Industry Thailand 1970 - see Variable: TH1970A_IND - Principal industry last year Thailand 1980 - see Variable: TH1980A_IND - Principal industry last year Thailand 1990 - see Variable: TH1990A_IND3 - Principal industry last year, 3 digits Thailand 2000 - see Variable: TH2000A_IND3 - Industry last year, 3 digits Togo 1970 - see Variable: TG1970A_IND - Industry (1-digit) Togo 2010 - see Variable: TG2010A_IND3 - Industry (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_IND - Industry (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_IND - Industry Trinidad and Tobago 2000 - see Variable: TT2000A_IND - Industry (2 digits) Turkey 1985 - see Variable: TR1985A_INDALT - Industry (2-digit) Turkey 1990 - see Variable: TR1990A_IND2 - Industry (2 digits) Turkey 2000 - see Variable: TR2000A_IND2 - Industry, 2 digit Uganda 2002 - see Variable: UG2002A_IND - Industry United Kingdom 1961 - see Variable: UK1961A_IND - Industry United Kingdom 1971 - see Variable: UK1971A_IND - Industry United Kingdom 1991 - see Variable: UK1991A_IND - Industrial classification United Kingdom 2001 - see Variable: UK2001A_IND - Industry classification United States 1960 - see Variable: US1960A_IND - Industry United States 1970 - see Variable: US1970A_IND - Industry United States 1980 - see Variable: US1980A_IND - Industry United States 1990 - see Variable: US1990A_IND - Industry United States 2000 - see Variable: US2000A_IND - Industry United States 2005 - see Variable: US2005A_IND - Industry United States 2010 - see Variable: US2010A_IND - Industry United States 2015 - see Variable: US2015A_IND - Industry United States 2020 - see Variable: US2020A_IND - Industry Uruguay 1963 - see Variable: UY1963A_IND2 - Primary industry [2-digit] Uruguay 1985 - see Variable: UY1985A_IND - Industry during the past week Uruguay 1996 - see Variable: UY1996A_IND2 - Industry (ISIC 3, 2 digits) Uruguay 2006 - see Variable: UY2006A_IND3 - Industry (ISIC rev 3, 3 digits) Venezuela 1981 - see Variable: VE1981A_IND - Industry Venezuela 1990 - see Variable: VE1990A_IND - Industry Venezuela 2001 - see Variable: VE2001A_IND - Industry Vietnam 1989 - see Variable: VN1989A_IND2 - Industry, 2 digits Vietnam 1999 - see Variable: VN1999A_IND3 - Industry, 3 digit Vietnam 2009 - see Variable: VN2009A_IND - Industry Vietnam 2019 - see Variable: VN2019A_IND3 - Industry, 3 digit Zambia 1990 - see Variable: ZM1990A_IND - Industry Zambia 2000 - see Variable: ZM2000A_IND - Type of industry, 3 digits Zambia 2010 - see Variable: ZM2010A_IND2 - Industry, 3 digits Work Variables -- PERSON Person number (within household) United Kingdom 1961: All records This variable indicates the person number (within household). 0 Household record 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 Technical Person Variables -- PERSON Occupation 21. Occupation.</p> <div class="i1">Full and precise details of the occupation should be given in columns (b) or (h). Terms such as scientist, technician, engineer, machinist, foreman, inspector, checker, civil servant, are too vague and should not be used by themselves. Managers or foremen should give the department where applicable; civil servants and other public officials should give their rank and the department or branch in which they are serving.<br /><br />If a job is known in the trade or industry by a special name, use that name.</div> United Kingdom 1961: Persons age 15+ who are employed [discrepancies: not verifiable] This variable indicates the person's occupation. 1 Professional and related occupations 2 Managerial and technical occupations 3 Skilled non-manual occupations 4 Manual occupations 5 Partly skilled occupations 6 Unskilled occupations 7 Armed forces 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Marital status E. <span class="em">Persons 16 years or over.</span><div class="i1">Write "single", "married", "widowed", or "divorced" (See note 4). ____</div><p>G. <span class="em">All married women.</span><div class="i1">Write at (i) the date of her present marriage.</div><div class="i2">(i) ____</div><div class="i1">Has she been married more than once? Write "yes" or "no" at (ii).</div><div class="i2">If "yes" fill in column H<br />(ii) ____</div><p>H. <span class="em">Widowed or divorced women or women married more than once.</span><div class="i1">Write at (i) the date of first or only marriage.</div><div class="i2">It is only answered if part (ii) or question G was "yes".<br />(i) ____</div><div class="i1">Write at (ii) the date when that marriage ended (See note 6).<br /><div class="i2">(ii) ____</div></div> 4. Marriage, etc. (Column E)</p> <div class="i1">If a person is legally separated, not divorced, write "Married".</div><p>6. End of first marriage (Column H)</p> <div class="i1">Write at (ii) the date of her first or only husband's death or date of divorce.</div> United Kingdom 1961: All persons This variable indicates the person's marital status. 1 Single 2 Married 3 Widowed 4 Divorced Demographic Variables -- PERSON Industry Ra. [Name and business of employer]</p> <div class="i1">State the name and business of the employer, but if self-employed write either "self-employed, employes others" or "self-employed without employees", and also the nature of the business: if a trading name is used give that name as well. See Notes 16, 19, 20, and 23.<br /><br />[Name and business] ____</div><p>Rb. [Occupation]</p> <div class="i1">(i) For the employment given in column (a) given at (i) the precise occupation, showing where appropriate the material worked or dealt in, and for workers at mines whether employed mainly above or below ground. See note 21. ____<br /><br />(ii) If applicable write at (ii) "Apprentice", "Learner" (only if in skilled craft), "Articled pupil", "Student Apprentice", "Graduate Apprentice", or "Management Trainee". See note 22. ____</div> 19. Employer and employer's business.</p> <div class="i1">These details are required only to help in classifying the industry or service. Describe the business fully and try to avoid using abbreviations or initials.<br /><br />The following are examples of terms insufficient by themselves: Manufacturer, merchant, agent, broker, factor, dealer, engineering, iron works, etc.</div> United Kingdom 1961: Persons age 15+ who are employed [discrepancies: none] This variable indicates the person's industry. 01 Agriculture, forestry, and fishing 02 Mining and quarrying 03 Food, drink, and tobacco 04 Chemicals and allied industries 05 Metal manufacture 06 Engineering and medical goods 07 Shipbuilding and marine engineering 08 Vehicles 09 Metal goods not elsewhere specified 10 Textiles 11 Leather, leather goods, and fur 12 Clothing and footwear 13 Bricks, pottery, glass, cement, or similar 14 Timber, furniture, or similar 15 Paper, printing, and publishing 16 Other manufacturing industries 17 Construction 18 Gas, electricity, and water 19 Transport and communication 20 Distributive trades 21 Insurance, banking, and finance 22 Professional and scientific services 23 Miscellaneous services 24 Public administration and defence 25 Professional, technical workers, artists 26 Armed forces (British and foreign) 98 Unknown 99 NIU (not in universe) Work: Industry Variables -- PERSON Age (grouped) D. Sex "M" or "F" and age in years at last birthday and completed months since then (See Note 3).</p> <div class="i1">Sex: _<br />Years ____<br />Months ____</div> 3. Age (Column D)</p> <div class="i1">(a) If the age is not known exactly, give it as accurately as possible.<br />(b) Even where the birthday is only a few days after Census day, the required age is the number of years at the last birthday and 11 months.<br />(c) For babies under one month old, write "Under I month".</div> United Kingdom 1961: All persons This variable indicates the person's age grouped into intervals. 01 0 to 4 years 02 5 to 9 03 10 to 14 04 15 to 19 05 20 to 24 06 25 to 29 07 30 to 34 08 35 to 39 09 40 to 44 10 45 to 49 11 50 to 54 12 55 to 59 13 60 to 64 14 65 to 69 15 70 to 74 16 75 to 79 17 80 to 84 18 85 to 89 19 90 to 94 20 95+ years 98 Unknown Demographic Variables -- PERSON Socio-economic group Ra. [Name and business of employer]</p> <div class="i1">State the name and business of the employer, but if self-employed write either "self-employed, employes others" or "self-employed without employees", and also the nature of the business: if a trading name is used give that name as well. See Notes 16, 19, 20, and 23.<br /><br />[Name and business] ____</div><p>Rb. [Occupation]</p> <div class="i1">(i) For the employment given in column (a) given at (i) the precise occupation, showing where appropriate the material worked or dealt in, and for workers at mines whether employed mainly above or below ground. See note 21. ____<br /><br />(ii) If applicable write at (ii) "Apprentice", "Learner" (only if in skilled craft), "Articled pupil", "Student Apprentice", "Graduate Apprentice", or "Management Trainee". See note 22. ____</div> 19. Employer and employer's business.</p> <div class="i1">These details are required only to help in classifying the industry or service. Describe the business fully and try to avoid using abbreviations or initials.<br /><br />The following are examples of terms insufficient by themselves: Manufacturer, merchant, agent, broker, factor, dealer, engineering, iron works, etc.</div><p>20. Employs others means having one or more employees other than his (her) relatives living in the same household.</p> <p>21. Occupation.</p> <div class="i1">Full and precise details of the occupation should be given in columns (b) or (h). Terms such as scientist, technician, engineer, machinist, foreman, inspector, checker, civil servant, are too vague and should not be used by themselves. Managers or foremen should give the department where applicable; civil servants and other public officials should give their rank and the department or branch in which they are serving.<br /><br />If a job is known in the trade or industry by a special name, use that name.</div> United Kingdom 1961: Persons age 15+ who are employed [discrepancies: none] This variable indicates the person's socio-economic group. 01 Employers and managers in large companies 02 Employers and managers small companies 03 Self-employed workers (professional) 04 Employees (professional) 05 Non-manual workers (ancillary workers, artists, foremen, and supervisors) 06 Junior non-manual workers 07 Personal service workers 08 Manual workers (foremen and supervisors) 09 Skilled manual workers 10 Semi-skilled manual workers 11 Unskilled manual workers 12 Self-employed workers (non-professional) 13 Farmers (employers and managers) 14 Farmers (self-employed) 15 Agricultural workers 16 Members of armed forces 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Sex D. Sex "M" or "F" and age in years at last birthday and completed months since then (See Note 3).</p> <div class="i1">Sex: _<br />Years ____<br />Months ____</div> United Kingdom 1961: All persons This variable indicates the sex of the person. 1 Male 2 Female Demographic Variables -- PERSON Student <span class="em">Section T</span><div class="i1">For other persons. Write "housewife", "home duties", "at school", "student", etc. as applicable.<br /><br />[Status] ____</div> 14. In employment means that the person had a job during the week ending Saturday, 22nd April, 1961, even if he was away from work because of holidays, sickness, strikes, etc. That is, a sick person is in employment if his job is waiting for him when he gets well.</p> <p>For persons temporarily laid off by their employer throughout the week, answer the questions in section R and not in section S.</p> <p>For persons who retired or became out of work during the week, complete section S and not section R.</p> <p>"Employment" includes any service in the armed forces, and also jobs at which a person worked for only a few hours; e.g. for a housewife who helped in her husband's shop or did some office cleaning answer the questions in section R and not section T.</p> <p>For persons who are at school or university full-time during term answer section T and not section R, even if they did paid work during the holidays. United Kingdom 1961: All persons This variable indicates whether the person is a student or not. 1 Yes, student 2 No, not a student Education Variables -- PERSON Private or non-private household (person-level variable) United Kingdom 1961: All persons This variable indicates whether the person belongs to private or non-private household. 1 Non-private household 2 Private household Other Person Variables -- PERSON