DDI_ZAF_2007_PHC_v01_M_v7.5_A_IPUMS Community Survey 2007 IPUMS May 20, 2024 MetadataEditor Version 7.5 October 2024. NEW FEATURES. --Historical data from NAPP project now available from IPUMS-International. --Historical census data from Canada, Denmark, the United Kingdom, Germany, Iceland, Norway, Sweden, and the United States for the period 1703 to 1911 are now available from IPUMS-International. The complete count and sample datasets were previously disseminated by the North Atlantic Population Project (NAPP). Where possible, the data have been integrated into existing IPUMS-International variable coding schema. Some new variables have been created that are available only for these pre-1960 datasets. NAPP data users should note that many NAPP variables are available from IPUMS-International by different names. For a complete list of NAPP variables that have been renamed in IPUMS-Interational, refer to the crosswalk. --Individual country shapefiles for the third-level administrative level of geography are now available for a few IPUMS samples. --New spatially harmonized previous-residence variables at the second administrative level of geography are available for several samples in this data release. More information is available here. Users should note that many older migration variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. --IPUMS now hosts the Census Mosaic data collection. Census Mosaic identifies, gathers, harmonizes, and distributes surviving historical census microdata from regions of Continental Europe where complete centralized records are not available. The Mosaic project was founded by a consortium of historical social scientists in Europe. Data can be downloaded as static files from the Census Mosaic website. Although the data are not yet integrated fully into IPUMS International, variables have been standardized and harmonized to be roughly compatible with IPUMS coding structures. NEW SAMPLES. --Full-count datasets for Great Britain 1851, 1861, 1871 (Scotland only), 1891, and 1901. --Full-count dataset for Sweden 1910. Denmark (1845, 1880, and 1885) --Labor force surveys from Spain and eight new labor force surveys from Italy added to the series. Newly added countries: Benin, Cote d'Ivoire, Finland, Guatemala, Honduras, Laos, Lesotho, Mauritius, Myanmar, Papua New Guinea, Russia, Slovak Republic, Suriname, Togo, and Zimbabwe New samples for: Bolivia, Cambodia, Cambodia, Chile, Cuba, Cote d'Ivoire, Egypt (1848 and 1868, historical samples), Fiji, Guinea, Ireland, Israel, Italy, Lao PDR, Mexico, Morocco, Nepal, Netherlands, Palestine, Peru, Philippines, Puerto Rico, Rwanda, Senegal, Sierra Leone, South Africa, Switzerland, Uganda, United States, United Kingdom, United States, Vietnam, and Zimbabwe SUPPLEMENTAL DATA. Data from censuses from Benin and Lesotho that record individual fertility and/or mortality events were made available in IPUMS-International. These files can be downloaded and linked to data produced by the extract system. NEW VARIABLES. --IPUMS-International now provides harmonized and year-specific geography variables for all countries including 13 new samples from Dominican Republic, Germany, Indonesia, Israel, Malaysia, Mongolia, Nicaragua, Nigeria, Palestine, Paraguay, Thailand, United Kingdom, and Uruguay. First-level and second-level year specific geography variables are also available for all countries. IPUMS provides corresponding, downloadable GIS boundary files for all harmonized and year specific geography variables. More information about IPUMS geography variables is available here. --IPUMS International now provides spatially harmonized previous-residence variables at the first administrative level of geography. The codes for the spatially harmonized previous-residence variables match the spatially harmonized place of current residence. More information is available here. --IPUMS International provides spatially harmonized previous-residence variables at the first administrative level of geography for all samples; previously available country-specific migration variables at the first administrative level that were not fully harmonized spatially have been phased out. Spatially harmonized previous-residence variables at the second administrative level of geography are available for selected samples. More information is available here. Users should note that many older migration variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. --IPUMS International now provides spatially harmonized previous-residence variables at the first administrative level of geography for all samples. Spatially harmonized previous-residence variables at the second administrative level of geography are available for several samples in this data release. More information is available here. Users should note that many older migration variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. --Lower (third) level geography codes and GIS files have been added for Bangladesh, China, Ethiopia, Mali, Rwanda, and Zimbabwe. Some geography codes and labels might have changed for these countries to accommodate the newer lower level geography. --Added more detailed 3-digit industry and occupation variables for China 2000. EDITED SAMPLES. --Revised full-count data for Great Britain 1881 --Revised full-count datasets for Sweden 1890 and 1900. The revision includes the following changes that improve comparability across Sweden datasets: --Revisions to certain ethnicity and work variables (and the underlying source data): ORIGIN, LABFORCE, OCCHISCO, OCRELATE, OCSTATUS. --Revisions to unharmonized source variables: SE1890A_HISCOSE, SE1890A_HISCRELSE, SE1890A_HISCSTATSE, SE1890A_OCCMULTISE, SE1900A_HISCOSE, SE1900A_HISCRELSE, SE1900A_HISCSTATSE, SE1900A_OCCMULTISE. --A new United States 1850 full-count dataset now matches the corresponding dataset distributed by the USA IPUMS data project. The source variable US1850A_0502 (HISTID) provides a linking key to match person records to the USA version of the data. The IPUMS International version of the data contains names, which the USA version cannot distribute. EDITED VARIABLES. An error affecting HHWT for South Africa 2007 was corrected. The existing values were adjusted by a factor of 0.01. AGEMARR was edited to add data for Hungary 1980 and 1990. Harmonized and year-specific geography variables for Brazil and Colombia have been edited to accommodate for the availability of refined municipal boundaries. Users should be aware that codes and labels have changed in all harmonized and year specific geography varaibles for these two countries. Errors affecting BPLSE2 (formerly BPLPARSE) for Sweden 1890 and the underlying source variable were corrected. Several thousand cases were incorrectly coded as 258101000. These cases have been updated with the correct code: 258171000. Harmonized geography variables for Italy, Philippines, Rwanda, and United States have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year specific geography varaibles for these countries. More information about IPUMS geography variables is available here. The codes for the source variable RW2002A_0419 were corrected to include 0 and 8 as possible responses, which were previously identified as 'unknown years' within primary education. Errors affecting EDUCFJ for Fiji 2006 were corrected. A problem with PERWT for Tanzania 2012 was corrected. The previous weights were adjusted to properly reflect population totals. MOMLOC, POPLOC, and PARRULE were updated for the United States 2010 and 2015 samples to include additional information on subfamilies. Prior to this correction, persons above age 17 were not receiving links to their co-resident mothers and fathers. An error affecting codes for the URBAN variable in Egypt 1986 for Cairo, Alexandria, Port-Said, and Suez was corrected. An error in INCEARN affecting Venezuela 2001 was corrected. Earned income in the source variable VE2001A_0440 is interpreted as a monthly amount, thus adjustments previously applied to convert data from daily or weekly income were supressed. All the six Brazil samples in IPUMS International were replaced with higher density samples. An edited version of the Chile 2017 sample was introduced to correct an error in household breaks. Errors affecting codes for GEO1_ZA in South Africa 2011 and ENUTS1 in United Kingdom 1991 were corrected. Harmonized geography variables for Cambodia, Fiji, and Nepal have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography varaibles for these countries. More information about IPUMS geography variables is available here. An error in PERWT affecting Nepal 2001 was corrected. Errors affecting a code in GQ for Brazil 2010 and Indonesia 2010 were corrected. Both census samples now identify 1-person units created by splitting a large household. An error in MARRNUM affecting Indonesia 1976 was corrected. Some codes for GEO1_EG2006 and GEO2_EG2006 were edited. Harmonized geography variables for Bolivia, Cuba, Guinea, Ireland, Morocco, Palestine, Senegal, South Africa, and Uganda have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography variables for these countries. More information about IPUMS geography variables is available here. An error in INCEARN affecting Brazil 1980 was corrected. An error in EDATTAIN affecting Ireland 1971 and 1981 was corrected. A small proportion of person records in Mexico 1960 were re-classified in MIGRATEP based on information about their current and previous residence. These were previously coded to 'different major administrative unit', even though their place of residence suggests that their last move was within the same major administrative unit. The second-level technician (higher) degrees for Spain 1991, 2001, and 2011 were re-classified into post-secondary technical education in EDATTAIN. An error affecting codes for SEX for Egypt 1848 and 1868 was corrected. The values for male and female had been reversed. A problem with HHWT and PERWT for Canada 2011 was corrected. The previous weights were adjusted to properly reflect population totals. Harmonized geography variables for Cambodia, Lao PDR, Mexico, Peru, Switzerland, Vietnam, Puerto Rico, United Kingdom, and United States have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography variables for these countries. More information about IPUMS geography variables is available here. Harmonized geography variables for Chile and Sierra Leone have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography variables for these countries. More information about IPUMS geography variables is available here. An error affecting codes for COMPUTER for Senegal 2013 was corrected. An error affecting labels available in IND for Peru 1993 was corrected. An error affecting codes for persons previously residing abroad for MIG1_5_BO in Bolivia 2001 and 2012 was corrected. EDUCAR, EDATTAIN, and YRSCHOOL were adjusted in the Argentina samples to incorporate information on completion of education levels in the data harmonization. HHWT and PERWT were calibrated in Kenya 1979 to properly reflect the population distribution by province. In GQ (group quarters status), persons residing in hospitals of all types were reclassified to 'institutional group quarters' from 'other group quarters,' making their treatment consistent with GQTYPE. Errors affecting codes for BPLBJ2 in Benin 1979, 1992, and 2002 were corrected. Errors affecting codes for GEO2_BR1970 in Brazil 1970 were corrected. Community Survey 2007 - IPUMS Subset PHC South Africa 2007 (IPUMS Harmonized Subset) ZAF_2007_PHC_v01_M_v7.5_A_IPUMS Statistics South Africa IPUMS (c) Copyright 2007, Statistics South Africa and Minnesota Population Center MetadataEditor Statistics South Africa Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.5 Version 7.5. The datasets contain selected variables from the original census microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Other Household Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Fertility and Mortality Variables -- PERSON Nativity and Birthplace Variables -- PERSON Utilities Variables -- HOUSEHOLD Work Variables -- PERSON Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Technical Household Variables -- HOUSEHOLD Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Geography: O-Z Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Income Variables -- PERSON Migration: O-Z Variables -- PERSON Household Economic Variables -- HOUSEHOLD Technical Person Variables -- PERSON Ethnicity and Language Variables -- PERSON Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Demographic Variables -- PERSON Technical Person Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Technical Household Variables -- HOUSEHOLD Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Utilities Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Work Variables -- PERSON Geography: O-Z Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Household Imputation Flags Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Other Person Variables -- PERSON Demographic Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Ethnicity and Language Variables -- PERSON Nativity and Birthplace Variables -- PERSON Migration: Global Variables -- PERSON Disability Variables -- PERSON Income Variables -- PERSON Education Variables -- PERSON Work Variables -- PERSON Fertility and Mortality Variables -- PERSON Person Imputation Flags Variables -- PERSON Person Imputation Flags Variables -- PERSON Technical Person Variables -- PERSON Work Variables -- PERSON Disability Variables -- PERSON Income Variables -- PERSON Other Person Variables -- PERSON Work: Occupation Variables -- PERSON Work: Industry Variables -- PERSON South Africa Municipalities with 20,000+ population Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: A structure or part of a structure or group of strucutres occupied or meant to be occupied by one or more households - Households: A household is a group of persons who live together and provide themselves jointly with food or other essentials for living, or a single person who lives alone. - Group quarters: Collective living quarters or communal living quarters are (1) structually separate and independent places of abode intended for habitation by large groups of individuals or several households. Such quarters usually have certain common facilities, such as cooking and ablution facilities, lounges or dormitories which are shared by the occupants. (2) Lving quarters where certain facilities are shared by groups of individulas or households. Institution: A particular type of collective living quarters, for people with a common characteristic who are living under a common regime. Examples are: hospital/clinic, frail care center, childcare institution/orphanage, etc. All usual members of the household who stay in the dwelling at least four nights a week and have done so over the last four weeks prior to census date, plus visitors who spent the night before the interview with the household. Sample survey data [ssd] Additional notes on a sample that is part of this study: South Africa 2007 MICRODATA SOURCE: Statistics South Africa SAMPLE SIZE (person records): 1047657. SAMPLE DESIGN: Two-stage, stratified systematic random sampling drawn by the country. Stage I: The sampling frame contains 79,466 enumeration areas (EAs) (the primary sampling units) which are stratified by municipality. Systematic random sampling is used to select EAs within municipalities. In municipalities with fewer than 30 EAs, all EAs are automatically selected. In municipalities with 30+ EAs, a fix proportion of 19% of EAs are selected. If the selected EAs in a municipality are less than 30, the sample in the municipality is increased to 30 EAs. Stage 2: A fixed proportion of 10% of the dwellings in a selected EA are selected. If there are less than 10 dwellings in an EA, the selection is increased to 10 dwelling units. All households within the selected dwelling units are covered. No replacement of refusals, vacant dwellings or non-contacts. Response rate 93.9%. Face-to-face [f2f] A single &quot;Household Questionnaire&quot; for information on dwelling, household, and individuals. both, CENSUS DAY: 2007-02-07 00:00:00 Computed by census agency and should be used for most types of analysis. IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS International are designed to extend this record. Statistics South Africa Steven Ruggles, Lara Cleveland, Rodrigo Lovaton, Sula Sarkar, Matthew Sobek, Derek Burk, Dan Ehrlich, Quinn Heimann, Jane Lee. Integrated Public Use Microdata Series, International: Version 7.5 [dataset]. Minneapolis, MN: IPUMS, 2024. https://doi.org/10.1 [dataset]. Minneapolis, MN: IPUMS, 2024. https://doi.org/10.18128/D020.V7.5 Researchers should also acknowledge the statistical agency that originally produced the data: South Africa, Statistics South Africa. Community Survey 2007 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. ZAF2007_PHC-H-H Household records 345 109 ZAF2007_PHC-P-H Person records 1047657 251 Record type H Household P Person 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. IPUMS Country 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 Ivory Coast 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 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). IPUMS Year 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 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. IPUMS IPUMS sample identifier 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 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 Ivory Coast 1988 384199801 Ivory Coast 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 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 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 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 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 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 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). IPUMS 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. IPUMS 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. IPUMS 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. IPUMS Subsample number 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 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. IPUMS Strata identifier This variable is the strata identifier for the sample. The STRATA variable provides information about the sample design that can be used to improve estimation. STRATA is a 12-digit numeric variable. IPUMS Group quarters (collective dwelling) status 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 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. IPUMS Group quarters type 100 Institutional 110 Prisons, reformatories, or correctional institutions 120 Hospital, nursing home, hospice, or instutions for persons with disabilities 121 Institutions for persons with disabilities 122 Sanatorium or mental institutions 130 Homes for the elderly or orphanage 131 Retirement home 132 Orphanage, children's home 140 Shelter for homeless, youth, or others 150 Military or police institution 160 Boarding school or student housing 170 Religious institution, monastery, seminary, or convent 199 Other institutional n.e.c. 200 Non-institutional 210 Camps (refugees, workers, or others) 220 Hotel, pension, lodging, or boarding house 230 Floating population 299 Other non-institutional n.e.c. 300 Other group quarters 399 1-person unit created by splitting large household 998 Unknown 999 NIU (not in universe) GQTYPE identifies the type of group quarters -- collective dwellings -- which are broadly classified into institutional and non-institutional types. Institutions are a place of residence where people are subject to a common authority or bound by a common objective or personal interest. The definition encompasses correctional facilities, health institutions, retirement homes, orphanages, shelters (social welfare institutions), military or police establishments, boarding schools, and religious group dwellings. Non-institutional group quarters comprise refugee and workers' camps (temporary accommodation), hotels, pensions, and all types of boarding or lodging houses. The "floating population" is included as a category within the non-institutional group quarters, when identified by the corresponding sample. This group refers to outdoor sleepers, homeless persons, travelers, and persons in ships, boats, or other mobile dwellings. A more general classification of households between private and group quarters is available in GQ. IPUMS Number of unrelated persons 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ UNREL indicates the number of persons in the household who are unrelated to the head as defined in the variable RELATE. IPUMS Urban-rural status 1 Rural 2 Urban 9 Unknown URBAN indicates whether the household was located in a place designated as urban or as rural. IPUMS Continent and region of 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 REGIONW identifies the continent and region of each country. IPUMS 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. IPUMS 2nd subnational geographic level, world [consistent boundaries over time] GEOLEV2 indicates the second major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. Second administrative units in GEOLEV2 have been spatio-temporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV2 is a 9-digit numeric variable. GEOLEV2 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO2_BR. IPUMS 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 string variable listing the population density in persons per square kilometer. IPUMS Population density of GEOLEV2 unit, in persons per square kilometer POPDENSGEO2 indicates the population density in persons per square kilometer of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO2 is a 12-digit string variable listing the population density in persons per square kilometer. IPUMS 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 string variable listing the area in square kilometers. IPUMS Area of GEOLEV2 unit in square kilometers AREAMOLLWGEO2 indicates the area in square kilometers of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO2 is a 10-digit string variable listing the area in square kilometers. IPUMS South Africa, Province 2001 - 2016 [Level 1; consistent boundaries, GIS] 710001 Western Cape 710004 Free State 710005 Eastern Cape, KwaZulu-Natal 710007 Gauteng, Limpopo, Mpumalanga, North West, Northern Cape 710999 Unknown GEO1_ZA identifies the household's province (provinsie) within South Africa from 2001 to present. Provinces are the first level administrative units of the country. GEO1_ZA is spatially harmonized accounting for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_ZA can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for South Africa 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. IPUMS South Africa, Province 2007 [Level 1, GIS] 001 Western Cape 002 Eastern Cape 003 Northern Cape 004 Free State 005 KwaZulu-Natal 006 North West 007 Gauteng 008 Mpumalanga 009 Limpopo GEO1_ZA2007 identifies the household's province (provinsie) within South Africa in 2007. Provinces are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_ZA2007 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for South Africa 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. IPUMS South Africa, District council 2001 - 2016 [Level 2; consistent boundaries, GIS] 710001001 West Coast 710001002 Cape Winelands, Overberg 710001003 Eden 710001004 Central Karoo 710001005 City of Cape Town 710004001 Thabo Mofutsanyane, Mangaung, Lejweleputswa, Fezile Dabi, Xhariep 710005001 Cacadu 710005002 Nelson Mandela Bay 710005003 Uthukela, Amajuba 710005004 Umkhanyakude 710005005 Uthungulu 710005006 iLembe 710005007 eThekwini, O.R.Tambo, Umgungundlovu, Amathole, Zululand, Alfred Nzo, Chris Hani, Buffalo City, Ugu, Umzinyathi, Sisonke, Joe Gqabi 710007001 Namakwa 710007002 Sedibeng, Ngaka Modiri Molema, West Rand, Dr Kenneth Kaunda, Dr Ruth Segomotsi Mompati, Frances Baard, Siyanda, John Taolo Gaetsewe, Pixley ka Seme 710007003 Ekurhuleni, City of Tshwane, Ehlanzeni, Bojanala, Nkangala, Vhembe, Capricorn, Greater Sekhukhune, Mopani, Waterberg 710007004 City of Johannesburg 710007005 Gert Sibande 710098098 Unknown GEO2_ ZA identifies the household's district council (also known as district municipality) within South Africa from 2001 to present. District councils are the second level administrative units of the country, after province. GEO2_ZA is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO2_ZA can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for South Africa can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS South Africa, District council 2007 [Level 2, GIS] 001001 DC1: West Coast 001002 DC2: Cape Winelands 001003 DC3: Overberg 001004 DC4: Eden 001005 DC5: Central Karoo 001171 CPT: City of Cape Town 002010 DC10: Cacadu 002012 DC12: Amatole 002013 DC13: Chris Hani 002014 DC14: Ukhahlamba 002015 DC15: O.R.Tambo 002044 DC44: Alfred Nzo 002275 NMA: Nelson Mandela Bay Metro 003006 DC6: Namakwa 003007 DC7: Pixley ka Seme 003008 DC8: Siyanda 003009 DC9: Frances Baard 003045 DC45: Kgalagadi 004016 DC16: Xhariep 004017 DC17: Motheo 004018 DC18: Lejweleputswa 004019 DC19: Thabo Mofutsanyane 004020 DC20: Fezile Dabi 005021 DC21: Ugu 005022 DC22: UMgungundlovu 005023 DC23: Uthukela 005024 DC24: Umzinyathi 005025 DC25: Amajuba 005026 DC26: Zululand 005027 DC27: Umkhanyakude 005028 DC28: Uthungulu 005029 DC29: iLembe 005043 DC43: Sisonke 005572 ETH: eThekwini 006037 DC37: Bojanala 006038 DC38: Central 006039 DC39: Bophirima 006040 DC40: Southern 007046 DC46: Metsweding 007048 DC48: West Rand 007042 DC42: Sedibeng 007773 EKU: Ekurhuleni 007774 JHB: City of Johannesburg 007776 TSH: City of Tshwane 008030 DC30: Gert Sibande 008031 DC31: Nkangala 008032 DC32: Ehlanzeni 009033 DC33: Mopani 009034 DC34: Vhembe 009035 DC35: Capricorn 009036 DC36: Waterberg 009047 DC47: Greater Sekhukhune GEO2_ZA2007 identifies the household’s district council (also known as district municipality) within South Africa in 2007. District councils are the second level administrative units of the country, after provinces. A GIS map (in shapefile format), corresponding to GEO2_ZA2007 can be downloaded from the GIS Boundary files page in the IPUMS International web site The full set of geography variables for South Africa can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS South Africa, Local municipality 2007 [Level 3, GIS] 001001001 Matzikama, West Coast 001001002 Cederberg 001001003 Bergrivier 001001004 Saldanha Bay 001001005 Swartland 001002006 Witzenberg, Cape Winelands 001002007 Drakenstein 001002008 Stellenbosch 001002009 Breede Valley 001002010 Breede River/Winelands 001003011 Theewaterskloof 001003012 Overstrand 001003013 Cape Agulhas, Overberg 001003014 Swellendam 001004015 Kannaland 001004016 Hessequa 001004017 Mossel Bay 001004018 George, Eden 001004019 Oudtshoorn 001004020 Bitou 001004021 Knysna 001005024 Beaufort West, Prince Albert, Central Karoo, Laingsburg 001171071 City of Cape Town 002010002 Blue Crane Route 002010004 Makana 002010005 Ndlambe 002010006 Sundays River Valley, Camdeboo, Baviaans, Ikwezi, Cacadu 002010008 Kouga 002010009 Kou-Kamma 002012010 Mbhashe 002012011 Mnquma 002012012 Great Kei 002012013 Amahlathi 002012014 Buffalo City 002012015 Ngqushwa 002012016 Nkonkobe 002012017 Nxuba 002013019 Tsolwana, Inkwanca, Inxuba Yethemba, Chris Hani 002013021 Lukanji 002013022 Intsika Yethu 002013023 Emalahleni-EC 002013024 Engcobo 002013025 Sakhisizwe 002014026 Elundini 002014027 Senqu 002014028 Maletswai 002014029 Gariep 002015030 Mbizana 002015031 Ntabankulu 002015032 Qaukeni 002015033 Port St Johns 002015034 Nyandeni 002015035 Mhlontlo 002015036 King Sabata Dalindyebo 002044038 Umzimvubu 002044049 Matatiele 002275075 Nelson Mandela Bay 003006002 Nama Khoi, Richtersveld 003006006 Khai-Ma, Kamiesberg, Namakwa, Hantam, Karoo Hoogland 003007007 Ubuntu, Kareeberg 003007008 Umsobomvu 003007009 Emthanjeni 003007012 Thembelihle, Renosterberg 003007013 Siyathemba, Pixley ka Seme 003007014 Siyancuma 003008016 Kai Garib, Mier, Siyanda 003008017 Khara Hais 003008018 Kheis 003008019 Tsantsabane 003008020 Kgatelopele 003009021 Sol Plaatjie 003009022 Dikgatlong, Frances Baard 003009023 Magareng 003009026 Phokwane 003045024 Gamagara 003045025 Moshaweng, Kgalagadi 003045052 Ga-Segonyane 004016001 Letsemeng 004016002 Kopanong 004016003 Mohokare 004017004 Naledi-FS 004017005 Mangaung 004017006 Mantsopa 004018007 Masilonyana 004018008 Tokologo 004018009 Tswelopele 004018010 Matjhabeng 004018011 Nala 004019012 Setsoto 004019013 Dihlabeng 004019014 Nketoana 004019015 Maluti a Phofung, Thabo Mofutsanyane 004019016 Phumelela 004020017 Moqhaka 004020018 Ngwathe 004020019 Metsimaholo 004020020 Mafube 005021001 Vulamehlo 005021002 Umdoni 005021003 Umzumbe 005021004 UMuziwabantu 005021005 Ezingoleni 005021006 Hibiscus Coast 005022007 uMshwathi 005022008 uMngeni 005022009 Mpofana, Umgungundlovu 005022010 Impendle 005022011 The Msunduzi 005022012 Mkhambathini 005022013 Richmond 005023014 Emnambithi-Ladysmith 005023015 Indaka 005023016 Umtshezi 005023017 Okhahlamba, Uthukela 005023018 Imbabazane 005024019 Endumeni 005024020 Nqutu 005024022 Msinga 005024023 Umvoti 005025024 Newcastle 005025025 Emadlangeni 005025026 Dannhauser 005026027 eDumbe 005026028 UPhongolo 005026029 Abaqulusi 005026030 Nongoma 005026031 Ulundi 005027032 Umhlabuyalingana, Umkhanyakude 005027033 Jozini 005027034 The Big 5 False Bay 005027035 Hlabisa 005027036 Mtubatuba 005028037 Mbonambi 005028038 uMhlathuze 005028039 Ntambanana 005028040 uMlalazi 005028041 Mthonjaneni 005028042 Nkandla 005029043 Mandeni 005029044 KwaDukuza 005029045 Ndwedwe 005029046 Maphumulo 005043047 Ingwe, Kwa Sani, Sisonke 005043050 Greater Kokstad 005043051 Ubuhlebezwe 005043052 Umzimkhulu 005572072 eThekwini 006037001 Moretele 006037002 Madibeng 006037003 Rustenburg 006037004 Kgetlengrivier 006037005 Moses Kotane 006038006 Ratlou 006038007 Tswaing 006038008 Mafikeng 006038009 Ditsobotla 006038010 Ramotshere Moiloa 006039011 Kagisano, Molopo 006039012 Naledi-NW 006039013 Mamusa 006039014 Greater Taung 006039016 Lekwa-Teemane 006040017 Ventersdorp 006040018 Potchefstroom 006040019 City of Matlosana 006040020 Maquassi Hills 006040022 Merafong City 007042004 Emfuleni 007042005 Midvaal 007042006 Lesedi 007046007 Nokeng tsa Taemane 007046062 Kungwini 007048001 Mogale City, West Rand 007048002 Randfontein 007048003 Westonaria 007773073 Ekurhuleni 007774074 City of Johannesburg 007776076 City of Tshwane 008030001 Albert Luthuli 008030002 Msukaligwa 008030003 Mkhondo 008030004 Seme 008030005 Lekwa 008030006 Dipaleseng 008030007 Govan Mbeki 008031008 Delmas 008031009 Emalahleni 008031010 Steve Tshwete 008031011 Emakhazeni 008031012 Thembisile 008031013 Dr JS Moroka 008032014 Thaba Chweu 008032015 Mbombela 008032016 Umjindi 008032017 Nkomazi, Ehlanzeni 008032025 Bushbuckridge 009033001 Greater Giyani 009033002 Greater Letaba 009033003 Greater Tzaneen 009033004 Ba-Phalaborwa, Mopani 009033022 Maruleng 009034005 Musina 009034006 Mutale 009034007 Thulamela 009034008 Makhado 009035009 Blouberg 009035010 Aganang 009035011 Molemole 009035012 Polokwane 009035013 Lepele-Nkumpi 009036014 Thabazimbi 009036015 Lephalale 009036017 Modimolle, Mookgopong 009036018 Bela-Bela 009036019 Mogalakwena 009047020 Makhuduthamaga 009047021 Fetakgomo 009047071 Greater Marble Hall 009047072 Elias Motsoaledi 009047075 Greater Tubatse GEO3_ZA2007 identifies the household's local municipality within South Africa in 2007. Local municipalities are the third level administrative units of the country, after province and district council (or district/metropolitan municipalities). A GIS map (in shapefile format), corresponding to GEO3_ZA2011 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for South Africa can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS South Africa, Municipality 011 Sol Plaatje 012 Dikgatlong, Magareng 014 Phokwane 015 City of Tshwane Metro 016 Gamagara 017 Ga-Segonyana 018 Moshaweng 019 Nokeng tsa Taemane 020 Kungwini 021 Makhuduthamaga 022 Fetakgomo 023 Greater Marble Hall 024 Greater Groblersdal 025 Greater Tubatse 026 Maruleng 027 Bushbuckridge 028 Mogale City 029 Randfontein 030 Westonaria 031 Merafong City 099 District Management Areas 160 Matzikama 161 Cederberg 162 Bergrivier 163 Saldanha Bay 164 Swartland 165 Witzenberg 166 Drakenstein 167 Stellenbosch 168 Breede Valley 169 Langeberg 150 Breede River/Winelands 170 Swellendam 171 Theewaterskloof 172 Overstrand 173 Cape Agulhas 175 Hessequa, Kannaland 176 Mossel Bay 177 George 178 Oudtshoorn 179 Bitou 180 Knysna 151 Plettenberg Bay 182 Prince Albert, Laingsburg 183 Beaufort West 199 City of Cape Town 261 Camdeboo 262 Blue Crane Route, Ikwezi 264 Makana 265 Ndlambe 266 Sunday's River Valley, Baviaans 268 Kouga 269 Kou-Kamma 270 Mbhashe 271 Mnquma 272 Great Kei 273 Amahlathi 274 Ngqushwa 276 Nkonkobe 277 Nxuba 278 Inxuba Yethemba 279 Tsolwana, Inkwanca 282 Intsika Yethu 283 Emalahleni 284 Engcobo 285 Sakhisizwe 286 Elundini 287 Senqu 288 Maletswai 289 Gariep 250 Qaukeni 290 Nguza Hill 291 Port St Johns 292 Nyandeni 293 Mhlontlo 294 King Sabata Dalindyebo 295 Matatiele 296 Umzimvubu 297 Mbizana 298 Ntabankulu 260 Buffalo City 299 Nelson Mandela 364 Nama Khoi, Richtersveld 366 Hantam, Kamiesberg 367 Karoo Hoogland, Khâi-Ma 370 Umsombomvu, Ubuntu 371 Emthanjeni 375 Siyathemba, Thembelihle, Renosterberg, Kareeberg 376 Siyancuma 378 Kai Garib, Mier 379 Khara Hais 381 Tsantsabane, Kgatelopele, Kheis 360 Joe Morolong 460 Letsemeng 461 Kopanong 462 Mohokare 463 Naledi 464 Masilonyana 465 Tokologo 466 Tswelopele 467 Matjhabeng 468 Nala 469 Setsoto 470 Dihlabeng 471 Nketoana 472 Maluti a Phofung 473 Phumelela 474 Mantsopa 475 Moqhaka 477 Ngwathe 478 Metsimaholo 479 Mafube 499 Mangaung 503 Umzumbe 504 uMuziwabantu 505 Ezingoleni 506 Hibiscus Coast 560 Vulamehlo 561 Umdoni 562 uMshwathi 563 uMngeni 564 Mooi Mpofana 565 Impendle 566 Msunduzi 567 Mkhambathini 568 Richmond 514 Emnambithi/Ladysmith 569 Indaka 570 Umtshezi 571 Okhahlamba 573 Imbabazane 574 Endumeni 575 Nqutu 576 Msinga 577 Umvoti 524 Newcastle 525 Emadlangeni 526 Dannhauser 550 Utrecht 529 Abaqulusi 578 eDumbe 579 uPhongolo 580 Nongoma 581 Ulundi 582 Umhlabuyalingana 583 Jozini 584 The Big 5 False Bay 585 Hlabisa 586 Mtubatuba 538 uMhlathuze 542 Nkandla 587 Mfolozi 588 Ntambanana 589 uMlalazi 590 Mthonjaneni 551 Mbonambi 546 Maphumulo 591 Mandeni 592 KwaDukuza 593 Ndwedwe 552 eNdondakusuka 595 Kwa Sani, Ingwe 596 Greater Kokstad 597 Ubuhlebezwe 598 Umzimkhulu 599 Ethekwini 660 Moretele 661 Madibeng 662 Rustenburg 663 Kgetlengrivier 664 Moses Kotane 665 Ratlou 666 Tswaing 667 Mafikeng 668 Ditsobotla 669 Ramotshere Moiloa 650 Setla-Kgobi 651 Zeerust 674 Kagisano/Molopo 670 Naledi 671 Mamusa 672 Greater Taung 673 Lekwa-Teemane 675 Ventersdorp 676 Tlokwe City Council 677 City of Matlosana 678 Maquassi Hills 652 Potchefstroom 653 City Council of Klerksdorp 760 Emfuleni 761 Midvaal 762 Lesedi 797 Ekurhuleni Metro 798 City of Johannesburg Metro 860 Albert Luthuli 861 Msukaligwa 862 Mkhondo 863 Seme 864 Lekwa 865 Dipaleseng 866 Govan Mbeki Municipality 867 Victor Khanye 868 Emalahleni 869 Steve Tshwete 870 Emakhazeni 871 Thembisile 872 Dr JS Moroka 850 Delmas 851 Middelburg 852 Highlands 873 Thaba Chweu 874 Mbombela 875 Umjindi 876 Nkomazi 960 Greater Giyani 961 Greater Letaba 962 Greater Tzaneen 963 Ba-Phalaborwa 967 Musina 965 Mutale 966 Thulamela 968 Makhado 969 Blouberg 970 Aganang 973 Molemole 974 Polokwane 976 Lepele-Nkumpi 977 Thabazimbi 978 Lephalale 979 Modimolle 980 Mookgopong 981 Bela-Bela 982 Mogalakwena 983 Ephraim Mogale 984 Elias Motsoaledi MUNIZA identifies the household's municipality within South Africa from 2001 to present. Municipalities are the third level administrative units of the country, after district council. MUNIZA is harmonized by name and does not account for boundary changes over time. The full set of geography variables for South Africa 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. IPUMS DHS-IPUMS-I South Africa regions, 1998-2016 [consistent boundaries, GIS] 1 Western Cape 4 Free State 5 Eastern Cape, Kwazulu-Natal 7 Gauteng, Limpopo, Mpumalanga, North West, Northern Cape 9 Unknown DHS_IPUMSI_ZA provides geographic codes for South Africa that match those in the DHS and IPUMS-International databases. This variable can be used to link contextual area data from IPUMS-DHS to IPUMS-International or vice versa. The codes in DHS_IPUMSI_ZA indicate the major administrative unit in which the household was enumerated or surveyed. GIS shapefiles for South Africa can be downloaded here. IPUMS Ownership of dwelling [general version] NIU (not in universe) 1 Owned 2 Not owned 9 Unknown 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. IPUMS Ownership of dwelling [detailed version] 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 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. IPUMS Electricity NIU (not in universe) 1 Yes 2 No 9 Unknown ELECTRIC indicates whether the household had access to electricity. IPUMS Water supply 00 NIU (not in universe) 10 Yes, piped water 11 Piped inside dwelling 12 Piped, exclusively to this household 13 Piped, shared with other households 14 Piped outside the dwelling 15 Piped outside dwelling, in building 16 Piped within the building or plot of land 17 Piped outside the building or lot 18 Have access to public piped water 20 No piped water 99 Unknown WATSUP describes the physical means by which the housing unit receives its water. The primary distinction is whether or not the household had piped (running) water. IPUMS Cooking fuel 00 NIU (not in universe) 10 None 20 Electricity 30 Petroleum gas, unspecified 31 Gas -- piped/utility 32 Gas -- tanked or bottled 33 Propane 34 Liquefied petroleum gas 35 Gas -- piped and bottled 40 Petroleum liquid 41 Oil, kerosene, and other liquid fuels 42 Kerosene/paraffin 43 Kerosene or oil 44 Kerosene or gasoline 45 Gasoline 46 Cocinol 47 Diesel 50 Wood, coal, and other solid fuels 51 Wood and other plant fuels 52 Non-wood plant materials 53 Coal or charcoal 54 Charcoal 55 Coal 56 Wood or charcoal 60 Multiple fuels 61 Bottled gas and wood 62 Propane and electricity 63 Propane, kerosene, and electricity 64 Propane and kerosene 65 Kerosene and electrictiy 66 Other combinations 70 Other 71 Alcohol 72 Biogas 73 Discarded or waste material 74 Dung/manure 75 Other combined organic waste materials 76 Solar energy 77 Candle 99 Unknown/missing FUELCOOK indicates the predominant type of fuel or energy used for cooking. IPUMS Fuel for heating 00 NIU (not in universe) 01 None 02 Electricity 03 Fuel oil, kerosene, other liquid fuels 04 Kerosene/paraffin 05 Diesel 06 Gas 07 Bottled gas, in tank, liquified 08 Solid fuel 09 Coal 10 Wood 11 Wood or coal 12 Solar 13 Animal dung 14 Charcoal 15 Biofuel 16 Other 17 Multiple sources 99 Unknown FUELHEAT indicates the main fuel source for heating the household. IPUMS Telephone availability NIU (not in universe) 1 No 2 Yes 9 Unknown/missing PHONE indicates the availability of a telephone in the dwelling. IPUMS Cellular phone availability NIU (not in universe) 1 Yes 2 No 9 Unknown CELL indicates the availability of a cellular phone in the household. IPUMS Internet access NIU (not in universe) 1 No 2 Yes 9 Unknown INTERNET indicates whether or not the household had an internet connection. IPUMS Trash disposal 00 NIU (not in universe) 10 Collected by a sanitation service 11 Collected directly from the household or dwelling 12 Collected indirectly from a garbage container or deposit 13 Collected by a sanitation service only 14 Collected by a sanitation service and disposed of in some other manner 20 Disposed of in some other manner 21 Burned or buried 22 Burned 23 Buried 24 Thrown into street, vacant land, or common area 25 Thrown into river, lake, ocean, lagoon, etc. 26 Thrown into canyon or gulley 27 Dumped in pit 28 Communal refuse dump 29 Own refuse dump 30 Authorized refuse dump 31 Illegal refuse dump 32 Other dumping 33 Outside 34 In the fields 35 Fed to animals 36 Composted 37 Heap 38 Garden 39 Other, none 99 Unknown/missing This variable indicates whether the household's waste or garbage is collected by a sanitation service or disposed of in some other manner. IPUMS Computer NIU (not in universe) 1 No 2 Yes 9 Unknown/missing COMPUTER indicates whether the household had a personal computer. IPUMS Refrigerator NIU (not in universe) 1 No 2 Yes 9 Unknown/missing REFRIG indicates whether the household had a refrigerator. IPUMS Television set 00 NIU (not in universe) 10 No 20 Yes, color or black-and-white not specified 21 1 television 22 2 televisions 23 3 televisions 24 4 televisions 25 5 televisions 26 6 televisions 27 7 televisions 28 8 televisions 29 9+ televisions 30 Yes, at least one color tv 31 1 color tv 32 2 color tvs 33 3+ televisions 40 Yes, black-and-white only 41 1 black-white tv 42 2 black-white tvs 43 3+ black-white tvs 99 Unknown/missing TV indicates whether the household had a television. IPUMS Radio in household NIU (not in universe) 1 No 2 Yes 9 Unknown/missing RADIO indicates whether the household had a radio. IPUMS Number of rooms 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) ROOMS indicates the number of rooms occupied by the housing unit. IPUMS Toilet 00 NIU (not in universe) 10 No toilet 11 No flush toilet 20 Have toilet, type not specified 21 Flush toilet 22 Non-flush, latrine 23 Non-flush, other and unspecified 99 Unknown TOILET indicates whether the household had access to a toilet and, in most cases, whether it was a flush toilet or other type of installation. IPUMS Number of deaths in household last year None 1 1 death 2 2 deaths 3 3 deaths 4 4 deaths 5 5 deaths 6 6 deaths 7 7 or more deaths 8 Unknown 9 NIU (not in universe) MORTNUM indicates the number of deaths in the household in the past year. IPUMS Any deaths in household last year 1 Yes 2 No 8 Unknown/missing 9 NIU (not in universe) ANYMORT indicates whether there were any deaths in the household in the past year. IPUMS Household classification 00 Vacant household 01 One-person household 02 Married/cohab couple, no children 03 Married/cohab couple with children 04 Single-parent family 05 Polygamous family 06 Extended family, relatives only 07 Composite household, family and non-relatives 08 Non-family household 09 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable HHTYPE is a constructed variable that describes the composition of households. HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ. IPUMS Number of families in household Vacant household 1 1 family 2 2 families 3 3 families 4 4 families 5 5 families 6 6 families 7 7 families 8 8 families 9 9 or more families NFAMS is a constructed variable that indicates the number of families within each household. Family membership is defined by FAMUNIT. A "family" is any group of persons related by blood, adoption, or marriage. An unrelated individual within the household is considered a separate family. Thus, a household consisting of a widow and a domestic employee contains two families; a household consisting of a large, multi-generation extended family with no persons unrelated to the head counts as a single family. NFAMS is constructed from information in RELATE (relationship to head) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). See those variable descriptions for more detail. IPUMS Number of married couples in household No married couples in household 1 1 couple 2 2 couples 3 3 couples 4 4 couples 5 5 couples 6 6 couples 7 7 couples 8 8 couples 9 9 or more couples NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household. NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household). IPUMS Number of mothers in household No mothers in household 1 1 mother 2 2 mothers 3 3 mothers 4 4 mothers 5 5 mothers 6 6 mothers 7 7 mothers 8 8 mothers 9 9 or more mothers in household NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household. NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household). IPUMS Number of fathers in household No fathers in household 1 1 father 2 2 fathers 3 3 fathers 4 4 fathers 5 5 fathers 6 6 fathers 7 7 fathers 8 8 fathers 9 9 or more fathers in household NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household. NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household). IPUMS Head's location in household HEADLOC gives the person number (PERNUM) of the head of household in samples in which persons are organized into households. HEADLOC is a 3-digit numeric variable. IPUMS Dwelling number South Africa 2007: All households This variable indicates the dwelling number. This is a 6-digit numeric variable with 0 implied decimal places IPUMS Urban <span class="h2">Particulars of the household</span> <br /><svar a="all" v="ZA07A016 ZA07A017 ZA07A018 ZA07A019 ZA07A020 ZA07A021 ZA07A022 ZA07A023">Enumeration area number _ _ _ _ _ _ _ _<br />Dwelling unit number _ _ _ _<br />Physical identification of the dwelling unit ________<br /></svar> <br />Landline telephone number of enumerated household (if any) _ _ _ - _ _ _ _ _ _ _ _ <br />Cellphone number (if any) _ _ _ - _ _ _ _ _ _ _ _ <br /><svar a="all" v="ZA07A071 ZA07A102 ZA07A103">Total number of persons in the household _ _<br /><div class="i1">Number of males _ _ <br />Number of females _ _</div><br /></svar> <br /><svar a="all" v="ZA07A104">Number of questionnaires for this household _<br /></svar> South Africa 2007: All households 1 Urban formal 2 Urban informal 4 Tribal area 5 Rural formal This variable indicates the type of geographic area in which the household is located. IPUMS Enumeration area type South Africa 2007: All households Vacant 1 Tribal settlement 2 Farm 3 Small holding 4 Urban settlement 5 Informal settlement 6 Recreational 7 Industrial area 8 Institution 9 Hostel This variable indicates the enumeration area type. IPUMS Household number South Africa 2007: Non-institutional households [discrepancies: none] 000 NIU (not in universe) 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 021 21 022 22 025 25 030 30 031 31 032 32 034 34 041 41 051 51 058 58 060 60 061 61 062 62 067 67 071 71 072 72 081 81 085 85 091 91 099 99 999 Unknown This variable indicates the household number (within the dwelling). IPUMS Type of dwelling <svar a="all" v="ZA07A028">H-01 Type of main dwelling<br />Which of the following types best describes the main dwelling unit that this household occupies?<br /><div class="i1">If this household lives in More than one dwelling, write the code of the <span class="em">main</span> dwelling that the household occupies in the box.<br /><span class="ital">Read out</span>:<br />[] 01 House or brick structure on a separate stand or yard<br />[] 02 Traditional dwelling/ hut /structure made of traditional material<br />[] 03 Flat in block of flats<br />[] 04 Town/ cluster/ semi-detached house (simplex, duplex, triplex)<br />[] 05 House/flat/room in backyard<br />[] 06 Informal dwelling/ shack in backyard<br />[] 07 Informal dwelling/ shack <span class="em">not</span> in backyard e.g. in informal/ squatter settlement<br />[] 08 Room/ flatlet <span class="em">not</span> in backyard but on a shared property<br />[] 09 Caravan or tent<br />[] 10 Private ship/boat<br />[] 11 Workers' hostel (bed/room)<br />[] 12 Other (specify) ______<br />_ _</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] 00 NIU (not in universe) 01 House or brick structure on a separate stand or yard 02 Traditional dwelling/hut/structure made of traditional materials 03 Flat in block of flats 04 Town/cluster/semi-detached house (simplex, duplex, triplex) 05 House/flat/room in back yard 06 Informal dwelling/shack in back yard 07 Informal dwelling/shack not in backyard, e.g. in an informal/squatter settlement 08 Room/flatlet not in backyard but on a shared property 09 Caravan or tent 10 Private ship/boat 11 Workers' hostel (bed/room) 12 Other (specify) This variable indicates the type of dwelling in which the household lives. IPUMS Number of rooms <svar a="all" v="ZA07A029">H-02 Rooms<br />How many rooms, including kitchens, are there for this household?<br /><div class="i1">Count all rooms in all dwellings.<br />Exclude bathrooms, sheds, garages, stables, etc. unless persons are living in them.<br />_ _</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] 00 NIU (not in universe) 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 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 This variable indicates the number of rooms (including kitchens) for the household (excluding bathrooms, stables, garages, etc. unless there are people living in them). IPUMS Access to water <svar a="all" v="ZA07A030">H-03 Access to water<br />In which way does this household obtain <span class="em">water</span> for domestic use?<br /><div class="i1">[] 1 Piped water inside the dwelling<br />[] 2 Piped water inside the yard<br />[] 3 Piped water from access point outside the yard<br />[] 4 Borehole<br />[] 5 Spring<br />[] 6 Dam/pool<br />[] 7 River/stream<br />[] 8 Water vendor<br />[] 9 Rain water tank<br />[] 0 Other<br />Write only one code in the box.<br />_</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] 00 NIU (not in universe) 01 Piped water inside the dwelling 02 Piped water inside the yard 03 Piped water from access point outside the yard 04 Borehole 05 Spring 06 Dam/pool 07 River/stream 08 Water vendor 09 Rain water tank 99 Other This variable indicates the type of access to water for the household. IPUMS Municipal water service provider <svar a="all" v="ZA07A031">H-04 Service provider<br />Does the household get water from the Municipality (Regional/ Local water scheme)?<br /><div class="i1">Mark appropriate box with an X.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the household gets water from a municipal service provider. IPUMS Distance from water access point <svar a="all" v="ZA07A032">H-05 Distance from water access point<br />What is the distance from water access point?<br /><div class="i1">[] 1 Less than 200m<br />[] 2 Between 200m and 500m<br />[] 3 Between 500m and 1km<br />[] 4 More than 1km<br />Write only one code in the box.<br />_</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Less than 200 meters 2 Between 200 meters and 500 meters 3 Between 500 meters and 1 kilometer 4 More than 1 kilometer This variable indicates the distance from the household to the water access point. IPUMS Toilet facility <svar a="all" v="ZA07A033">H-06 Toilet facilities<br />What is the <span class="em">main</span> type of <span class="em">toilet</span> facility available for use by this household?<br /><div class="i1"><span class="ital">Read out</span>:<br />[] 1 Flush toilet (connected to sewerage system)<br />[] 2 Flush toilet (with septic tank)<br />[] 3 Dry toilet facility<br />[] 4 Pit toilet with ventilation (VIP)<br />[] 5 Pit toilet without ventilation<br />[] 6 Chemical toilet<br />[] 7 Bucket toilet system<br />[] 8 None<br />Write only one code in the box.<br />_</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Flush toilet (connected to sewerage system) 2 Flush toilet (with septic tank) 3 Dry toilet facility 4 Pit toilet with ventilation (VIP) 5 Pit latrine without ventilation 6 Chemical toilet 7 Bucket toilet system 8 None This variable indicates the type of toilet facility used by the household. IPUMS Energy or fuel for cooking <svar a="all" v="ZA07A034">H-07 Energy/fuel for cooking<br />What type of energy/fuel does this household <span class="em">mainly</span> use for cooking?<br /><div class="i1">[] 1 Electricity<br />[] 2 Gas<br />[] 3 Paraffin<br />[] 4 Wood<br />[] 5 Coal<br />[] 7 Animal dung<br />[] 8 Solar<br />[] 9 Other (specify) ______<br />Write only one code in the box.<br />_</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Electricity 2 Gas 3 Paraffin 4 Wood 5 Coal 7 Animal dung 8 Solar 9 Other This variable indicates the type of energy or fuel for cooking used by the household. IPUMS Energy or fuel for heating <svar a="all" v="ZA07A035">H-08 Energy / fuel for heating<br />What type of energy/fuel does this household <span class="em">mainly</span> use for heating?<br /><div class="i1">[] 1 Electricity<br />[] 2 Gas<br />[] 3 Paraffin<br />[] 4 Wood<br />[] 5 Coal<br />[] 7 Animal dung<br />[] 8 Solar<br />[] 9 Other (specify) ______<br />Write only one code in the box.<br />_</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Electricity 2 Gas 3 Paraffin 4 Wood 5 Coal 7 Animal dung 8 Solar 9 Other This variable indicates the type of energy or fuel for heating used by the household. IPUMS Energy or fuel for lighting <svar a="all" v="ZA07A036">H-09 Energy / fuel for lighting<br />What type of energy/fuel does this household <span class="em">mainly</span> use for lighting?<br /><div class="i1">[] 1 Electricity<br />[] 2 Gas<br />[] 3 Paraffin<br />[] 6 Candles<br />[] 8 Solar<br />[] 9 Other (specify) ______<br />Write only one code in the box.<br />_</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Electricity 2 Gas 3 Paraffin 6 Candles 8 Solar 9 Other This variable indicates the type of energy or fuel for lighting used by the household. IPUMS Refrigerator <svar v="ZA07A037 ZA07A038 ZA07A039 ZA07A040 ZA07A041 ZA07A042 ZA07A043 ZA07A044">H-10 Household goods<br />Does the household have any of the following?<br /><div class="i1">Mark appropriate box with an X</div><br /></svar></p> <p><svar a="all" v="ZA07A037"><div class="i1">Refrigerator</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the household has a refrigerator. IPUMS Radio <svar v="ZA07A037 ZA07A038 ZA07A039 ZA07A040 ZA07A041 ZA07A042 ZA07A043 ZA07A044">H-10 Household goods<br />Does the household have any of the following?<br /><div class="i1">Mark appropriate box with an X</div><br /></svar></p> <p><svar a="all" v="ZA07A038"><div class="i1">Radio</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the household has a radio. IPUMS Television <svar v="ZA07A037 ZA07A038 ZA07A039 ZA07A040 ZA07A041 ZA07A042 ZA07A043 ZA07A044">H-10 Household goods<br />Does the household have any of the following?<br /><div class="i1">Mark appropriate box with an X</div><br /></svar></p> <p><svar a="all" v="ZA07A039"><div class="i1">Television</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the household has a television. IPUMS Computer <svar v="ZA07A037 ZA07A038 ZA07A039 ZA07A040 ZA07A041 ZA07A042 ZA07A043 ZA07A044">H-10 Household goods<br />Does the household have any of the following?<br /><div class="i1">Mark appropriate box with an X</div><br /></svar></p> <p><svar a="all" v="ZA07A040"><div class="i1">Computer</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the household has a computer. IPUMS Landline telephone facilities <svar v="ZA07A037 ZA07A038 ZA07A039 ZA07A040 ZA07A041 ZA07A042 ZA07A043 ZA07A044">H-10 Household goods<br />Does the household have any of the following?<br /><div class="i1">Mark appropriate box with an X</div><br /></svar></p> <p><svar a="all" v="ZA07A041"><div class="i1">Landline telephone</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the household has a landline telephone. IPUMS Internet facilities <svar v="ZA07A037 ZA07A038 ZA07A039 ZA07A040 ZA07A041 ZA07A042 ZA07A043 ZA07A044">H-10 Household goods<br />Does the household have any of the following?<br /><div class="i1">Mark appropriate box with an X</div><br /></svar></p> <p><svar a="all" v="ZA07A042"><div class="i1">Internet facilities at home</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the household has internet facilities. IPUMS Post facilities (mail postbox) <svar v="ZA07A037 ZA07A038 ZA07A039 ZA07A040 ZA07A041 ZA07A042 ZA07A043 ZA07A044">H-10 Household goods<br />Does the household have any of the following?<br /><div class="i1">Mark appropriate box with an X</div><br /></svar></p> <p><svar a="all" v="ZA07A043"><div class="i1">Post facilities (Mail postbox)</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the household has post facilities (mail postbox). IPUMS Cell phone <svar v="ZA07A037 ZA07A038 ZA07A039 ZA07A040 ZA07A041 ZA07A042 ZA07A043 ZA07A044">H-10 Household goods<br />Does the household have any of the following?<br /><div class="i1">Mark appropriate box with an X</div><br /></svar></p> <p><svar a="all" v="ZA07A044"><div class="i1">Cellphone</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the household has a cell phone. IPUMS Tenure status <svar a="all" v="ZA07A045">H-11 Tenure status<br />What is the tenure status of this household?<br /><div class="i1">If the household uses several dwellings, write the code for the main dwelling in the box.<br /><span class="ital">Read out</span>:<br />[] 1 Owned and fully paid off<br />[] 2 Owned but not yet paid off<br />[] 3 Rented<br />[] 4 Occupied rent-free<br />[] 5 Other (specify) ____<br />Write only one code in the box.<br />_</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Owned and fully paid off 2 Owned but not yet paid off 3 Rented 4 Occupied rent-free 5 Other This variable indicates the arrangements under which the household occupies the dwelling. IPUMS Refuse or rubbish <svar a="all" v="ZA07A046">H-12 Refuse disposal<br />How is the refuse or rubbish from this household <span class="em">mainly</span> disposed of?<br /><div class="i1"><span class="ital">Read out</span>:<br />1 Removed by local authority/ private company at least once a week<br />2 Removed by local authority/ private company less often<br />3 Communal refuse dump<br />4 Own refuse dump<br />5 No rubbish disposal<br />6 Other (specify) ____<br />Write only one code in the box.<br />_</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Removed by local authority at least once a week 2 Removed by local authority less often 3 Communal refuse dump 4 Own refuse dump 5 No rubbish disposal 6 Other This variable indicates the type of refuse or rubbish removal used by the household. IPUMS Flag for DWTYPE South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the type of dwelling. IPUMS Flag for ROOMS South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the number of rooms used by the household. IPUMS Flag for WATSRC South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the type of access the household has to water. IPUMS Flag for WATSERV South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the household gets water from the municipal service provider. IPUMS Flag for WATDIST South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the distance from the household to the water access point. IPUMS Flag for TOILET South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the type of toilet facility used by the household. IPUMS Flag for COOKENER South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the type of energy or fuel used by the household for cooking. IPUMS Flag for HEATENER South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the type of energy or fuel used by the household for heating. IPUMS Flag for LIGHTENR South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the type of energy or fuel used by the household for lighting. IPUMS Flag for REFRIG South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether or not the household has a refrigerator. IPUMS Flag for RADIO South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether or not the household has a radio. IPUMS Flag for TV South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether or not the household has a television. IPUMS Flag for COMPUTER South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether or not the household has a computer. IPUMS Flag for PHONE South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether or not the household has landline telephone facilities. IPUMS Flag for INTERNET South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether or not the household has internet facilities. IPUMS Flag for POSTAL South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether or not the household has post facilities (mail postbox). IPUMS Flag for CELLPHON South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether or not the household has a cell phone. IPUMS Flag for TENURE South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the tenure status of the household. IPUMS Flag for REFUSE South Africa 2007: Non-institutional households [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the type of refuse or rubbish disposal used by the household. IPUMS Design weights South Africa 2007: All households This variable is the design weight for the household. ZA07A066 is a 9-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Average adjusted weights South Africa 2007: All households This variable is the average adjusted weight for the household. ZA07A067 is a 9-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Derived race/ethnicity of head of household South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Black 2 Coloured 3 Indian or Asian 4 White This variable indicates the derived population group of the head of household. IPUMS Derived sex of head of household South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Male 2 Female This variable indicates the derived sex of the head of household. IPUMS Derived majority race/ethnicity South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 Black 2 Coloured 3 Indian or Asian 4 White This variable indicates the derived majority population group for the household. IPUMS Household size South Africa 2007: Non-institutional households [discrepancies: none] 00 NIU (not in universe) 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 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 28 28 29 29 30 30 32 32 This variable indicates the size of the household. IPUMS Annual household income South Africa 2007: Non-institutional households [discrepancies: none] This variable indicates the annual household income in rands. ZA07A072 is a 7-digit numeric variable. Codes9999998 = Unknown. 9999999 = NIU. IPUMS Community survey less unoccupied weights South Africa 2007: All households This variable indicates the community survey less unoccupied weights. ZA07A073 is a 9-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Community survey adjusted all non-response weights South Africa 2007: All households This variable indicates the community survey adjusted all non-response weights. ZA07A074 is a 9-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Community survey final provincial weights South Africa 2007: All households This variable indicates the Community Survey final provincial weights. ZA07A075 is a 10-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Community survey scope status South Africa 2007: All households 1 In community survey sample 2 Out of scope of community survey sample This variable indicates the community survey scope status. IPUMS Community Survey final municipal weights South Africa 2007: All households This variable indicates the community survey final municipal weights. ZA07A077 is a 10-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Number of mortality records South Africa 2007: All households 1 1 2 2 3 3 4 4 5 5 6 6 8 8 This variable indicates the number of mortality records associated with the household. IPUMS Number of males <span class="h2">Particulars of the household</span> <br /><svar a="all" v="ZA07A016 ZA07A017 ZA07A018 ZA07A019 ZA07A020 ZA07A021 ZA07A022 ZA07A023">Enumeration area number _ _ _ _ _ _ _ _<br />Dwelling unit number _ _ _ _<br />Physical identification of the dwelling unit ________<br /></svar> <br />Landline telephone number of enumerated household (if any) _ _ _ - _ _ _ _ _ _ _ _ <br />Cellphone number (if any) _ _ _ - _ _ _ _ _ _ _ _ <br /><svar a="all" v="ZA07A071 ZA07A102 ZA07A103">Total number of persons in the household _ _<br /><div class="i1">Number of males _ _ <br />Number of females _ _</div><br /></svar> <br /><svar a="all" v="ZA07A104">Number of questionnaires for this household _<br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] 00 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 99 NIU (not in universe) This variable indicates the number of males in the household. IPUMS Number of females <span class="h2">Particulars of the household</span> <br /><svar a="all" v="ZA07A016 ZA07A017 ZA07A018 ZA07A019 ZA07A020 ZA07A021 ZA07A022 ZA07A023">Enumeration area number _ _ _ _ _ _ _ _<br />Dwelling unit number _ _ _ _<br />Physical identification of the dwelling unit ________<br /></svar> <br />Landline telephone number of enumerated household (if any) _ _ _ - _ _ _ _ _ _ _ _ <br />Cellphone number (if any) _ _ _ - _ _ _ _ _ _ _ _ <br /><svar a="all" v="ZA07A071 ZA07A102 ZA07A103">Total number of persons in the household _ _<br /><div class="i1">Number of males _ _ <br />Number of females _ _</div><br /></svar> <br /><svar a="all" v="ZA07A104">Number of questionnaires for this household _<br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] 00 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 99 NIU (not in universe) This variable indicates the number of females in the household. IPUMS Number of questionnaires for this household <span class="h2">Particulars of the household</span> <br /><svar a="all" v="ZA07A016 ZA07A017 ZA07A018 ZA07A019 ZA07A020 ZA07A021 ZA07A022 ZA07A023">Enumeration area number _ _ _ _ _ _ _ _<br />Dwelling unit number _ _ _ _<br />Physical identification of the dwelling unit ________<br /></svar> <br />Landline telephone number of enumerated household (if any) _ _ _ - _ _ _ _ _ _ _ _ <br />Cellphone number (if any) _ _ _ - _ _ _ _ _ _ _ _ <br /><svar a="all" v="ZA07A071 ZA07A102 ZA07A103">Total number of persons in the household _ _<br /><div class="i1">Number of males _ _ <br />Number of females _ _</div><br /></svar> <br /><svar a="all" v="ZA07A104">Number of questionnaires for this household _<br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] NIU (not in universe) 1 1 2 2 This variable indicates the number of questionnaires for this household. IPUMS Total number of households at the selected dwelling <span class="h2">Households at the selected dwelling</span> <br /><svar a="all" v="ZA07A105">Household number of this household _ _<br />Total number of households at the selected dwelling _ _<br /></svar> <br /><svar a="all" v="ZA07A106">Was this questionnaire subjected to quality control (or checks) by any Community Survey personnel other than the supervisor? Mark the appropriate box with an X.<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] 000 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 028 28 031 31 032 32 034 34 041 41 042 42 049 49 050 50 051 51 052 52 054 54 061 61 062 62 071 71 072 72 073 73 080 80 081 81 091 91 092 92 099 99 998 Unknown 999 NIU (not in universe) This variable indicates the total number of households in the selected dwelling. IPUMS Questionnaire quality control (by CS personnel) <span class="h2">Households at the selected dwelling</span> <br /><svar a="all" v="ZA07A105">Household number of this household _ _<br />Total number of households at the selected dwelling _ _<br /></svar> <br /><svar a="all" v="ZA07A106">Was this questionnaire subjected to quality control (or checks) by any Community Survey personnel other than the supervisor? Mark the appropriate box with an X.<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: All households 1 Yes 2 No 9 Unknown This variable indicates whether the questionnaire was subjected to a quality control by any Community Survey personnel other than the enumerator. IPUMS Any deaths <svar v="ZA07A113 ZA07A114"><span class="h2">Section I: Mortality in the last 12 months - (between February 2006 and March 2007)</span><br /></svar></p> <p><span class="ital">Read out</span>: I am now going to ask for information on any member of the household who has passed away in the last 12 months between February 2006 and March 2007.</p> <p><svar a="ZA07A113" v="ZA07A113 ZA07A114">M-00 Has any member of this household passed away in the last 12 months between February 2006 and March 2007?<br /><div class="i1">Mark appropriate box with an X<br />If <span class="em">no</span>, the questionnaire is completed. Thank the respondent(s).<br />[] Yes<br />[] No</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether anyone in the household died in the past year. IPUMS Number of deaths <svar v="ZA07A113 ZA07A114"><span class="h2">Section I: Mortality in the last 12 months - (between February 2006 and March 2007)</span><br /></svar></p> <p><svar a="ZA07A113" v="ZA07A113 ZA07A114">M-00 Has any member of this household passed away in the last 12 months between February 2006 and March 2007?<br /><div class="i1">Mark appropriate box with an X<br />If <span class="em">no</span>, the questionnaire is completed. Thank the respondent(s).<br />[] Yes<br />[] No</div><br /></svar></p> <p><svar a="all" v="ZA07A114">M-01 How many members passed away?<br /><div class="i1">_ _</div><br /></svar> South Africa 2007: Non-institutional households [discrepancies: none] 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 NIU (not in universe) This variable indicates the number of deaths that occurred in the household in the past year. IPUMS Strata South Africa 2007: All households This variable is the strata identifier for the sample. Strata is a constructed variable that captures implicit geographic stratification resulting from the sample design. It is created by assigning a unique identifier to groups of between 10 and 19 adjacent households. Additional documentation is available on the Variance Estimation page. This is a 5-digit numeric variable with 0 implied decimal places IPUMS 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. IPUMS 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. IPUMS Residence status: de facto, de jure 1 Present resident 2 Absent resident 3 Visitor/non-resident 4 De facto population (present persons) 9 Unknown/missing RESIDENT identifies whether an enumerated person is a household resident or a visitor and whether she or he was present at the time of enumeration. This variable is available only in samples that enumerated both de facto and de jure residents. It can be used to eliminate the double-counting of persons who were enumerated both at their permanent residence and at the residence they were visiting on census night. De jure population: present residents and absent residents. De facto population: present residents and visitors/non-residents. IPUMS Mother's location in household MOMLOC is a constructed variable that indicates whether or not the person's mother lived in the same household and, if so, gives the person number of the mother (see PERNUM). MOMLOC makes it easy for researchers to link the characteristics of children and their (probable) mothers. The method by which probable child-mother links are identified is described in PARRULE. The general design of MOMLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of MOMLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: MOMLOC identifies social relationships (such as stepmother and adopted mother) as well as biological relationships. The variable STEPMOM is designed to identify some of these social relationships. To restrict MOMLOC to biological mothers, such as for own children fertility estimation, MOMLOC should be reset to zero when STEPMOM is greater than zero. MOMLOC is a 3-digit numeric variable. Codes0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother IPUMS Father's location in household POPLOC is a constructed variable that indicates whether or not the person's father lived in the same household and, if so, gives the person number of the father (see PERNUM). POPLOC makes it easy for researchers to link the characteristics of children and their (probable) fathers. The method by which probable child-father links are identified is described in PARRULE. The general design of POPLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of POPLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: POPLOC identifies social relationships (such as stepfather and adopted father) as well as biological relationships. The variable STEPPOP is designed to identify some of these social relationships. To restrict POPLOC to biological mothers, such as for own children fertility estimation, POPLOC should be reset to zero when STEPPOP is greater than zero. POPLOC is a 3-digit numeric variable. Codes0 = No father of this person present in the household. 1 or higher = The person number of this person's father IPUMS Spouse's location in household SPLOC is a constructed variable that indicates whether or not the person's spouse lived in the same household and, if so, gives the person number (PERNUM) of the spouse. SPLOC makes it easy for researchers to link the characteristics of (probable) spouses. The method by which probable spouse-spouse links are identified is described in SPRULE. The general design of SPLOC and other constructed variables is modeled on the methods developed for IPUMS-USA "Family Interrelationships", but the details vary significantly. For more details on the construction of SPLOC, see the Comparability section of SPRULE and this paper on IPUMSI family linking methodology. SPLOC is a 3-digit numeric variable. Codes0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse IPUMS Rule for linking parent 00 No parent of person in household 11 Link to head or spouse, unambiguous 12 Link to head or spouse, ambiguous 21 Child-Grandchild, within empirical child cap 22 Child-Grandchild, within constructed child cap 23 Child-Grandchild, exceeds child cap 31 Specified Other Relatives, within empirical child cap 32 Specified Other Relatives, within constructed child cap 33 Specified Other Relatives, exceeds child cap 41 Other Relatives, within empirical child cap 42 Other Relatives, within constructed child cap 51 Non-Relatives, within empirical child cap 52 Non-Relatives, within constructed child cap PARRULE describes the criteria by which the IPUMS International variables MOMLOC and POPLOC linked the person to a probable mother and/or father. IPUMS International establishes child-parent links according to five basic rules, and PARRULE gives the number of the rule that applied to the link in question. A link to any parent automatically generates a second link to that parent's spouse or partner, so only one rule is needed to describe both MOMLOC and POPLOC. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. IPUMS Rule for linking spouse 00 No spouse present 01 Rule 1: strong relationship pairing, couple adjacent 02 Rule 2: strong relationship pairing, couple not adjacent 03 Rule 3: weak relationship pairing, couple adjacent 04 Rule 4: weak relationship pairing, couple not adjacent 05 Rule 5: weak consensual union pairings 06 Rule 6: sample-specific rules (usually child-to-child) SPRULE explains the criteria by which the IPUMS-International variable SPLOC linked the person to his/her probable spouse. IPUMS International establishes spouse-spouse links according to five basic rules, and SPRULE gives the number of the rule that applied to the link in question. A sixth rule identifies sample-specific linking procedures only imposed in selected instances. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. IPUMS Probable stepmother Biological mother or no mother present 1 Mother has no children born or surviving 2 Child reports mother is deceased 3 Explicitly identified step relationship 4 Mother reports no children in the home 5 Age difference implausible 6 Child exceeds known fertility of mother STEPMOM indicates whether a person's mother, as identified by MOMLOC, was most probably not the person's biological mother. Non-zero values of STEPMOM explain why it is probable that the person's mother was a step- or adopted mother. A value of 0 indicates no likely stepmother because (1) the mother identified in MOMLOC was probably the biological mother or (2) there is no mother of this person present in the household. The codes for STEPMOM are as follows: 0 = Biological mother or no mother of this person present in household. 1 = Mother has no children born or surviving. 2 = Child reports mother is deceased. 3 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner, stepchild/child-in-law). 4 = Mother reports no children in the home. 5 = Age difference between mother and child was less than 12 or greater than 54 years. 6 = Child exceeds known fertility of mother. In cases where more than one criterion for a likely stepmother is met, STEPMOM will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepmothers and adopted mothers in the population that cannot be identified with information available in the censuses. Therefore, STEPMOM will always under-represent their actual number in the population. IPUMS Probable stepfather Biological father or no father present 1 Child reports father is deceased 2 Explicitly identified step relationship 3 Age difference implausible 4 Spouse of mother 5 Identified as adopted 6 Surname difference -- male child or never-married female STEPPOP indicates whether a person's father, as identified by POPLOC, was most probably not the person's biological father. Non-zero values of STEPPOP explain why it is probable that the person's father was a step- or adopted father. A value of 0 indicates no likely stepfather because (1) the father identified in POPLOC was probably the biological father or (2) there is no father of this person present in the household. The codes for STEPPOP are as follows: 0 = Biological father or no father of this person present in household. 1 = Child reports father is deceased. 2 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner; stepchild/child-in-law). 3 = Age difference between father and child was less than 12 or greater than 54 years. In cases where more than one criterion for a likely stepfather is met, STEPPOP will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepfathers and adopted fathers in the population that cannot be identified with information available in the censuses. Therefore, STEPPOP will always under-represent their actual number in the population. IPUMS Man with more than one wife linked No more than one wife linked via SPLOC 1 More than one wife linked via SPLOC POLYMAL indicates if a man had more than one wife linked to him in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The point of POLYMAL is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. IPUMS Woman is second or higher order wife Person is not the 2nd or higher order wife linked via SPLOC 1 Person is the 2nd or higher order wife linked via SPLOC POLY2ND indicates if a woman was the second or higher order wife linked to a husband in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The variable does not suggest the actual marital order of wives, only their relative positions in the person order of the household as it was enumerated. The point of POLY2ND is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. IPUMS Family unit membership FAMUNIT is a constructed variable indicating to which family within the household a person belongs. All persons related to the household head receive a 1 (see RELATE). Each secondary family or secondary individual receives a higher code. For purposes of FAMUNIT, secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). FAMUNIT is a 4-digit numeric variable. CodesIf there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on. IPUMS Number of own family members in household 0001 1 family member present 0002 2 family members present 0003 3 family members present 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 or more persons FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them. FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membership). The primary family is defined as all persons related to the head in the RELATE variable. Secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). IPUMS Number of own children in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children in household NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Number of own children under age 5 in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more own children under age 5 in household 98 One or more children have unknown age NCHLT5 provides a count of the person's own children under age five living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Age of eldest own child in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. ELDCH is top-coded at age 50 or older. IPUMS Age of youngest own child in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. YNGCH is top-coded at age 50 or older. IPUMS Relationship to household head [general version] 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Relationship to household head [detailed version] 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling's sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder, or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Age 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 AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. IPUMS 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 AGE2 gives computed years of age grouped into intervals. IPUMS Sex 1 Male 2 Female 9 Unknown SEX reports the sex (gender) of the respondent. IPUMS Marital status [general version] NIU (not in universe) 1 Single/never married 2 Married/in union 3 Separated/divorced/spouse absent 4 Widowed 9 Unknown/missing 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. IPUMS Marital status [detailed version] 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 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. IPUMS Consensual union 1 Yes, in consensual union 2 No, married 8 Unknown 9 NIU (not in universe) CONSENS indicates whether the respondent was in a consensual union -- a de facto marriage. IPUMS Polygamous union 00 NIU (not in universe) 01 No, in monogamous union 02 Yes, in polygamous union 03 Man in polygamous union 04 Polygamous man, 2 wives 05 Polygamous man, 3 or more wives 06 Woman in polygamous union 07 Polygamous marriage, 2 wives 08 Polygamous marriage, 3 or more wives 09 First wife 10 Second wife 11 Third or higher order wife 99 Unknown/missing POLYGAM indicates whether the respondent was in a polygamous union and, in some samples, the number of wives or the rank order of the wife. IPUMS Year of birth 0000 NIU (not in universe) 1628 1628 1629 1629 1630 1630 1631 1631 1634 1634 1635 1635 1636 1636 1637 1637 1638 1638 1639 1639 1640 1640 1641 1641 1642 1642 1643 1643 1644 1644 1645 1645 1646 1646 1647 1647 1648 1648 1649 1649 1650 1650 1651 1651 1652 1652 1653 1653 1654 1654 1655 1655 1656 1656 1657 1657 1658 1658 1659 1659 1660 1660 1661 1661 1662 1662 1663 1663 1664 1664 1665 1665 1666 1666 1667 1667 1668 1668 1669 1669 1670 1670 1671 1671 1672 1672 1673 1673 1674 1674 1675 1675 1676 1676 1677 1677 1678 1678 1679 1679 1680 1680 1681 1681 1682 1682 1683 1683 1684 1684 1685 1685 1686 1686 1687 1687 1688 1688 1689 1689 1690 1690 1691 1691 1692 1692 1693 1693 1694 1694 1695 1695 1696 1696 1697 1697 1698 1698 1699 1699 1700 1700 1701 1701 1702 1702 1703 1703 1704 1704 1705 1705 1706 1706 1707 1707 1708 1708 1709 1709 1710 1710 1711 1711 1712 1712 1713 1713 1714 1714 1715 1715 1716 1716 1717 1717 1718 1718 1719 1719 1720 1720 1721 1721 1722 1722 1723 1723 1724 1724 1725 1725 1726 1726 1727 1727 1728 1728 1729 1729 1730 1730 1731 1731 1732 1732 1733 1733 1734 1734 1735 1735 1736 1736 1737 1737 1738 1738 1739 1739 1740 1740 1741 1741 1742 1742 1743 1743 1744 1744 1745 1745 1746 1746 1747 1747 1748 1748 1749 1749 1750 1750 1751 1751 1752 1752 1753 1753 1754 1754 1755 1755 1756 1756 1757 1757 1758 1758 1759 1759 1760 1760 1761 1761 1762 1762 1763 1763 1764 1764 1765 1765 1766 1766 1767 1767 1768 1768 1769 1769 1770 1770 1771 1771 1772 1772 1773 1773 1774 1774 1775 1775 1776 1776 1777 1777 1778 1778 1779 1779 1780 1780 1781 1781 1782 1782 1783 1783 1784 1784 1785 1785 1786 1786 1787 1787 1788 1788 1789 1789 1790 1790 1791 1791 1792 1792 1793 1793 1794 1794 1795 1795 1796 1796 1797 1797 1798 1798 1799 1799 1800 1800 1801 1801 1802 1802 1803 1803 1804 1804 1805 1805 1806 1806 1807 1807 1808 1808 1809 1809 1810 1810 1811 1811 1812 1812 1813 1813 1814 1814 1815 1815 1816 1816 1817 1817 1818 1818 1819 1819 1820 1820 1821 1821 1822 1822 1823 1823 1824 1824 1825 1825 1826 1826 1827 1827 1828 1828 1829 1829 1830 1830 1831 1831 1832 1832 1833 1833 1834 1834 1835 1835 1836 1836 1837 1837 1838 1838 1839 1839 1840 1840 1841 1841 1842 1842 1843 1843 1844 1844 1845 1845 1846 1846 1847 1847 1848 1848 1849 1849 1850 1850 1851 1851 1852 1852 1853 1853 1854 1854 1855 1855 1856 1856 1857 1857 1858 1858 1859 1859 1860 1860 1861 1861 1862 1862 1863 1863 1864 1864 1865 1865 1866 1866 1867 1867 1868 1868 1869 1869 1870 1870 1871 1871 1872 1872 1873 1873 1874 1874 1875 1875 1876 1876 1877 1877 1878 1878 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9999 Unknown BIRTHYR gives the person's year of birth. IPUMS Children ever born 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living. IPUMS Children surviving 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHSURV reports the number of children born to a woman who were still living at the time of the census. IPUMS Number of female children ever born 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORNF indicates the number of female children ever born to a woman. Only live births are counted. IPUMS Number of male children ever born 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORNM indicates the number of male children ever born to a woman. Only live births are counted. IPUMS Month of last birth 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) LASTBMO indicates the month of birth of the last child born by the respondent. The data refer to live births. IPUMS Year of last birth 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 Unknown 9999 NIU (not in universe) LASTBYR indicates the year of birth of the last child born by the respondent. The data refer to live births. IPUMS Sex of last birth NIU (not in universe) 1 Male 2 Female 3 Both sexes (multiple births) 9 Unknown LASTBSEX indicates the sex of a woman's most recent birth. IPUMS Number of children dead 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown/missing 99 NIU (not in universe) CHDEAD reports how many of the children ever born to a woman were no longer living at the time of the census. Women were to consider all live births by all fathers; they were to exclude still births. IPUMS Number of female children dead 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) CHDEADFEM indicates the number of female children ever born to a woman who are no longer living. Stillbirths are not counted. It is possible to calculate total child deaths for samples that have both the "Female children ever born" and "Female children surviving" variables. That is not done in CHDEADFEM, which includes only the samples that directly reported the information in the appropriate form. IPUMS Number of male children dead 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) CHDEADMALE indicates the number of male children ever born to a woman who are no longer living. Stillbirths are not counted. It is possible to calculate total child deaths for samples that have both the "Male children ever born" and "Male children surviving" variables. That is not done in CHDEADMALE, which includes only the samples that directly reported the information in the appropriate form. IPUMS Mortality status of mother 1 Alive 2 Dead 7 Does not know 8 Missing 9 NIU (not in universe) MORTMOT indicates whether the person's biological mother was still living at the time of the census. IPUMS Mortality status of father 1 Alive 2 Dead 7 Does not know 8 Missing 9 NIU (not in universe) MORTFAT indicates whether the person's biological father was still living. IPUMS Number of own children in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) HOMECHILD indicates the number of surviving biological children living in the household with their mother (the respondent) at the time of the census. IPUMS Number of own female children in household 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 17 17 20 20+ 98 Unknown 99 NIU (not in universe) HOMEFEM indicates the number of female children born living in the household with their mother (the respondent). IPUMS Number of own male children in household 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) HOMEMALE indicates the number of male children born living in the household with their mother (the respondent). IPUMS Number of own children living elsewhere 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 98 Unknown 99 NIU (not in universe) AWAYCHILD indicates the number of surviving biological children not living in the household with their mother (the respondent) at the time of the census. IPUMS Number of own female children living elsewhere 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) AWAYFEM indicates the number of surviving biological female children not living in the household with their mother (the respondent). IPUMS Number of own male children living elsewhere 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 98 Unknown 99 NIU (not in universe) AWAYMALE indicates the number of surviving biological male children not living in the household with their mother (the respondent). IPUMS Nativity status NIU (not in universe) 1 Native-born 2 Foreign-born 9 Unknown/missing NATIVITY indicates whether the person was native-born or foreign-born. IPUMS Province of birth, South Africa 01 Western Cape 02 Eastern Cape 03 Northern Cape 04 Free State 05 KwaZulu-Natal 06 North West 07 Gauteng 08 Mpumalanga 09 Limpopo 97 Foreign country 98 Unknown 99 NIU (not in universe) BPLZA indicates the province in South Africa in which the person was born. IPUMS Race or color 10 White 20 Black 21 Black African 22 Black Caribbean 23 Afro-Ecuadorian 24 Other Black 30 Indigenous 31 American Indian 32 Latin American Indian 40 Asian 41 Chinese 42 Japanese 43 Korean 44 Vietnamese 45 Filipino 46 Indian 47 Pakistani 48 Bangladeshi 49 Other Asian 50 Mixed race 51 Brown (Brazil) 52 Mestizo (Indigenous and White) 53 Mulatto (Black and White) 54 Coloured (South Africa) 55 Two or more races 60 Other 61 Montubio (Ecuador) 99 Unknown Race identifies the racial group with which a person identified himself or herself, or to which an enumerator assigned them. Determinations of race are based largely on appearance or ancestral place of origin. IPUMS School attendance NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing 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. IPUMS Educational attainment, international recode [general version] NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS Educational attainment, international recode [detailed version] 000 NIU (not in universe) 100 Less than primary completed (n.s.) 110 No schooling 120 Some primary completed 130 Primary (4 yrs) completed 211 Primary (5 yrs) completed 212 Primary (6 yrs) completed 221 Lower secondary general completed 222 Lower secondary technical completed 311 Secondary, general track completed 312 Some college completed 320 Secondary or post-secondary technical completed 321 Secondary, technical track completed 322 Post-secondary technical education 400 University completed 999 Unknown/missing EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS Years of schooling 00 None or pre-school 01 1 year 02 2 years 03 3 years 04 4 years 05 5 years 06 6 years 07 7 years 08 8 years 09 9 years 10 10 years 11 11 years 12 12 years 13 13 years 14 14 years 15 15 years 16 16 years 17 17 years 18 18 years or more 90 Not specified 91 Some primary 92 Some technical after primary 93 Some secondary 94 Some tertiary 95 Adult literacy 96 Special education 98 Unknown/missing 99 NIU (not in universe) YRSCHOOL indicates the highest grade/level of schooling the person had completed, in years. Only formal schooling is counted. YRSCHOOL accounts for the number of years of study, regardless of the track or kind of study. Information on degree and/or technical track is available in EDATTAIN. Years of schooling for Israel, categorized into intervals, are given in YRSCHOOL2. Users should pay close attention to the top-codes in each sample, as discussed in the comparability section. IPUMS Educational attainment, South Africa 000 None 100 Formal Schooling 101 Year 0 (preschool) 102 Year 1 103 Year 2 104 Year 3 105 Year 4 106 Year 5 107 Year 6 108 Year 7 109 Year 8 110 Year 9 111 Year 10 112 Year 11 113 Year 12 114 Year 12, without university exemption 115 Year 12, with university exemption 120 Less than year 12 with certificate or diploma 121 Less than year 12 with certificate 122 Less than year 12 with diploma 130 Year 12 with certificate 140 Year 12 with diploma 150 Certificate or diploma 151 Certificate or diploma I 152 Certificate or diploma II 153 Certificate or diploma III 154 Certificate or diploma 4 155 Certificate or diploma 5 156 Certificate or diploma 6 210 Bachelor's degree and diploma 220 Bachelor's degree 310 Honours degree or post-graduate diploma 311 Honours degree 312 Post-graduate diploma 320 Post higher diploma (Masters, Doctoral diploma) 330 Higher degree 331 Master's degree 332 Doctorate degree 300 Other 998 Unknown 999 NIU (not in universe) EDUCZA indicates the person's educational attainment in South Africa in terms of the level of schooling completed and the number of years completed at that level. IPUMS Activity status (employment status) [general version] NIU (not in universe) 1 Employed 2 Unemployed 3 Inactive 9 Unknown/missing EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". IPUMS Activity status (employment status) [detailed version] 000 NIU (not in universe) 100 Employed, not specified 110 At work 111 At work, and 'student' 112 At work, and 'housework' 113 At work, and 'seeking work' 114 At work, and 'retired' 115 At work, and 'no work' 116 At work, and other situation 117 At work, family holding, not specified 118 At work, family holding, not agricultural 119 At work, family holding, agricultural 120 Have job, not at work in reference period 130 Armed forces 131 Armed forces, at work 132 Armed forces, not at work in reference period 133 Military trainee 140 Marginally employed 200 Unemployed, not specified 201 Unemployed 6 or more months 202 Worked fewer than 6 months, permanent job 203 Worked fewer than 6 months, temporary job 210 Unemployed, experienced worker 220 Unemployed, new worker 230 No work available 240 Inactive unemployed 300 Inactive (not in labor force) 310 Housework 320 Unable to work, disabled or health reasons 321 Permanent disability 322 Temporary illness 323 Disabled or imprisoned 330 In school 340 Retirees and living on rent 341 Living on rents 342 Living on rents or pension 343 Retirees/pensioners 344 Retired 345 Pensioner 346 Non-retirement pension 347 Disability pension 348 Retired without benefits 350 Elderly 351 Elderly or disabled 360 Institutionalized 361 Prisoner 370 Intermittent worker 371 Not working, seasonal worker 372 Not working, occasional worker 380 Other income recipient 390 Inactive, other reasons 391 Too young to work 392 Dependent 999 Unknown/missing EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". IPUMS Labor force participation 1 No, not in the labor force 2 Yes, in the labor force 8 Unknown 9 NIU (not in universe) LABFORCE is a dichotomous variable identifying whether a person participated in the labor force. Labor force participation generally means working or seeking work within a specified reference period. For most samples LABFORCE is a recode of EMPSTAT (employment status). A consistent lower age universe of 15 or older has been applied to increase comparability across samples. Full detail is retained in EMPSTAT, which should be used for any study of child labor. IPUMS Occupation, ISCO general 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) 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. IPUMS 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. CodesArgentina 1970 - Spanish Argentina 1980 - Spanish Argentina 1991 - Spanish Argentina 2001 - Spanish Armenia 2011 Austria 1971-2001 - German Belarus 1999 - Russian Belarus 2009 Benin 1979 Benin 1992 Benin 2002 Benin 2013 Bolivia 1976 Bolivia 1992 Bolivia 2001 Bolivia 2012 Botswana 1981 Botswana 1991 Botswana 2001 Botswana 2011 Brazil 1960 - Portuguese Brazil 1970 - Portuguese Brazil 1980 - Portuguese Brazil 1991 - Portuguese Brazil 2000 - Portuguese Brazil 2010 Burkina Faso 1985 Burkina Faso 1996 Cambodia 1998 Cambodia 2004 Cambodia 2008 Cambodia 2013 Cambodia 2019 Cameroon 1976 Cameroon 2005 Canada 1971 Canada 1981-1991 Canada 2001 Canada 2011 Chile 1960 Chile 1970 Chile 1982 Chile 1992 Chile 2002 China 1982 China 1990 China 2000 Colombia 1964 Colombia 1973 - Spanish Costa Rica 1973 Costa Rica 1984 Costa Rica 2000 Costa Rica 2011 Cote d'Ivoire 1988 Cote d'Ivoire 1998 Cuba 2002 Cuba 2012 Denmark 1845 Denmark 1880 Denmark 1885 Dominican Republic 1960 Dominican Republic 1970 Dominican Republic 1981 Dominican Republic 2002 Dominican Republic 2010 Ecuador 1962 Ecuador 1974 Ecuador 1982 Ecuador 1990 Ecuador 2001 Ecuador 2010 Egypt 1986 Egypt 2006 El Salvador 1992 El Salvador 2007 Ethiopia 1984 Ethiopia 1994 Fiji 1976 Fiji 1986 Fiji 1996 Fiji 2007 Fiji 2014 Finland 2010 France 1962-1990 - French France 1999 France 2006 France 2011 Germany 1970 Germany 1981 Germany 1987 Ghana 1984 Ghana 2000 Ghana 2010 Greece 1971-1991 - Greek Greece 2001 - Greek Greece 2011 Guatemala 1964 Guatemala 1973 Guatemala 1981 Guatemala 1994 Guatemala 2002 Guinea 1983 Guinea 1996 Guinea 2014 Haiti 1982 Haiti 2003 Honduras 1961 Honduras 1974 Honduras 1988 Honduras 2001 Hungary 1970-1990 Hungary 2001 Hungary 2011 India 1983-2004 India 2009 Indonesia 1971 Indonesia 1976 Indonesia 1980 Indonesia 1985 Indonesia 1990 Indonesia 1995 Indonesia 2005 Iran 2006 Iran 2011 Iraq 1997 Ireland 1901 Ireland 1911 Ireland 1971 Ireland 1981 Ireland 1986 Ireland 1991 Ireland 1996 Ireland 2002 Ireland 2006 Ireland 2011 Ireland 2016 Israel 1972 Israel 1983 Israel 1995 Israel 2008 Italy 2001 Italy 2011 Italy Surveys 2011-2020 Jamaica 1982 Jamaica 1991 Jamaica 2001 Jordan 2004 Kenya 1989 Kyrgyz Republic 1999 Laos 1995 Lesotho 1996 Lesotho 2006 Liberia 1974 Liberia 2008 Malawi 1987 Malawi 1998 Malawi 2008 Malaysia 1970 Malaysia 1980-1991 Malaysia 2000 Mali 1987 Mali 1998 Mali 2009 Mauritius 1990 Mauritius 2000 Mauritius 2011 Mexico 1960 - Spanish Mexico 1970 - Spanish Mexico 1990 - Spanish Mexico 1995 - Spanish Mexico 2000 - Spanish Mexico 2010 Mexico 2015 Mexico 2020 Mexico Surveys 2005-2020 Mongolia 2000 Morocco 1982 Morocco 1994 Morocco 2004 Morocco 2014 Mozambique 1997 Mozambique 2007 Myanmar 2014 Nepal 2001 Nepal 2011 Netherlands 1960 Netherlands 1971 Netherlands 2001 Netherlands 2011 Nicaragua 1971 Nicaragua 1995 Nicaragua 2005 Nigeria 2008 Nigeria 2009 Nigeria 2010 Pakistan 1973 Palestine 1997 Palestine 2007 Palestine 2017 Panama 1960 - Spanish Panama 1970 - Spanish Panama 1980 - Spanish Panama 1990 - Spanish Panama 2000 - Spanish Panama 2010 Papua New Guinea 1980 Papua New Guinea 1990 Papua New Guinea 2000 Paraguay 1962 Paraguay 1972 Paraguay 1982 Paraguay 1992 Paraguay 2002 Peru 1993 Peru 2007 Peru 2017 Philippines 1990 Philippines 2000 Philippines 2010 Poland 1978 Poland 1988 Poland 2002 Portugal 1981 - Portuguese Portugal 1991 - Portuguese Portugal 2001 - Portuguese Portugal 2011 Puerto Rico 1970 Puerto Rico 1980 Puerto Rico 1990 Puerto Rico 2000-2005 Puerto Rico 2010 Puerto Rico 2015 Puerto Rico 2020 Romania 1977 Romania 1992 Romania 2002 Romania 2011 Rwanda 2002 - French Rwanda 2012 Saint Lucia 1991 Senegal 1988 Senegal 2002 Senegal 2013 Slovak Republic 1991 Slovak Republic 2001 Slovak Republic 2011 Sierra Leone 2004 Sierra Leone 2015 Slovenia 2002 South Africa 1996 South Africa 2001 South Africa 2007 South Sudan 2008 Spain 1981 - Spanish Spain 1991 - Spanish Spain 2001 - Spanish Spain 2011 Spain Surveys 2005-2020 Sudan 2008 Suriname 2004 Suriname 2012 Switzerland 1970 Switzerland 1980 Switzerland 1990 Switzerland 2000 Switzerland 2011 Tanzania 1988 Tanzania 2002 Tanzania 2012 Thailand 1970 Thailand 1980 Thailand 1990 Thailand 2000 Togo 1960 Togo 1970 Togo 2010 Trinidad and Tobago 1990 Trinidad and Tobago 2000 Trinidad and Tobago 2011 Turkey 1985 Turkey 1990 Turkey 2000 Uganda 1991 Uganda 2002 Uganda 2014 United Kingdom 1961 United Kingdom 1971 United Kingdom 1991 United Kingdom 2001 United States 1960 United States 1970 United States 1980 United States 1990 United States 2000-2005 United States 2010 United States 2015 United States 2020 Uruguay 1963 Uruguay 1975 Uruguay 1996 Uruguay 2006 Venezuela 1981 Venezuela 1990 Venezuela 2001 - Spanish Vietnam 1989 Vietnam 1999 Vietnam 2009 Vietnam 2019 Zambia 1990 Zambia 2000 Zambia 2010 Zimbabwe 2012 IPUMS Occupation, ISCO-1988, 3-digit 010 Armed forces 111 Legislators 112 Senior government officials 113 Traditional chiefs and heads of villages 114 Senior officials of special-interest organizations 121 Directors and chief executives 122 Production and operations department managers 123 Other department managers 131 General managers 199 Legislators, senior officials and managers not elsewhere classified 211 Physicists, chemists and related professionals 212 Mathematicians, statisticians and related professionals 213 Computing professionals 214 Architects, engineers and related professionals 221 Life science professionals 222 Health professionals (except nursing) 223 Nursing and midwifery professionals 231 College, university and higher education teaching professionals 232 Secondary education teaching professionals 233 Primary and pre-primary education teaching professionals 234 Special education teaching professionals 235 Other teaching professionals 241 Business professionals 242 Legal professionals 243 Archivists, librarians and related information professionals 244 Social science and related professionals 245 Writers and creative or performing artists 246 Religious professionals 299 Professionals no elsewhere classified 311 Physical and engineering science technicians 312 Computer associate professionals 313 Optical and electronic equipment operators 314 Ship and aircraft controllers and technicians 315 Safety and quality inspectors 321 Life science technicians and related associate professionals 322 Modern health associate professionals (except nursing) 323 Nursing and midwifery associate professionals 324 Traditional medicine practitioners and faith healers 331 Primary education teaching associate professionals 332 Pre-primary education teaching associate professionals 333 Special education teaching associate professionals 334 Other teaching associate professionals 341 Finance and sales associate professionals 342 Business services agents and trade brokers 343 Administrative associate professionals 344 Customs, tax and related government associate professionals 345 Police inspectors and detectives 346 Social work associate professionals 347 Artistic, entertainment and sports associate professionals 348 Religious associate professionals 399 Technicians and associate professionals not elsewhere classified 411 Secretaries and keyboard-operating clerks 412 Numerical clerks 413 Material-recording and transport clerks 414 Library, mail and related clerks 419 Other office clerks 421 Cashiers, tellers and related clerks 422 Client information clerks 499 Clerks not elsewhere classified 511 Travel attendants and related workers 512 Housekeeping and restaurant services workers 513 Personal care and related workers 514 Other personal services workers 515 Astrologers, fortune-tellers and related workers 516 Protective services workers 521 Fashion and other models 522 Shop salespersons and demonstrators 523 Stall and market salespersons 599 Service workers and shop and market sales workers not elsewhere classified 611 Market gardeners and crop growers 612 Market-oriented animal producers and related workers 613 Market-oriented crop and animal producers 614 Forestry and related workers 615 Fishery workers, hunters and trappers 621 Subsistence agricultural and fishery workers 699 Skilled agricultural and fishery workers not elsewhere classified 711 Miners, shotfirers, stone cutters and carvers 712 Building frame and related trades workers 713 Building finishers and related trades workers 714 Painters, building structure cleaners and related trades workers 721 Metal moulders, welders, sheet-metal workers, structural- metal preparers, and related trades workers 722 Blacksmiths, tool-makers and related trades workers 723 Machinery mechanics and fitters 724 Electrical and electronic equipment mechanics and fitters 731 Precision workers in metal and related materials 732 Potters, glass-makers and related trades workers 733 Handicraft workers in wood, textile, leather and related materials 734 Printing and related trades workers 741 Food processing and related trades workers 742 Wood treaters, cabinet-makers and related trades workers 743 Textile, garment and related trades workers 744 Pelt, leather and shoemaking trades workers 799 Craft and related trade workers not elsewhere classified 811 Mining- and mineral-processing-plant operators 812 Metal-processing-plant operators 813 Glass, ceramics and related plant operators 814 Wood-processing- and papermaking-plant operators 815 Chemical-processing-plant operators 816 Power-production and related plant operators 817 Automated-assembly-line and industrial-robot operators 821 Metal- and mineral-products machine operators 822 Chemical-products machine operators 823 Rubber- and plastic-products machine operators 824 Wood-products machine operators 825 Printing-, binding- and paper-products machine operators 826 Textile-, fur- and leather-products machine operators 827 Food and related products machine operators 828 Assemblers 829 Other machine operators and assemblers 831 Locomotive-engine drivers and related workers 832 Motor-vehicle drivers 833 Agricultural and other mobile-plant operators 834 Ships' deck crews and related workers 899 Other plant and machine operaters and assemblers not elsewhere classified 911 Street vendors and related workers 912 Shoe cleaning and other street services elementary occupations 913 Domestic and related helpers, cleaners and launderers 914 Building caretakers, window and related cleaners 915 Messengers, porters, doorkeepers and related workers 916 Garbage collectors and related labourers 921 Agricultural, fishery and related labourers 931 Mining and construction labourers 932 Manufacturing labourers 933 Transport labourers and freight handlers 989 Elementary occupations not elsewhere classified 990 Other workers, not elsewhere classified 998 Unknown 999 NIU (not in universe) ISCO88A provides the 3-digit occupation code for the respondent using the ISCO-1988 occupation classification. IPUMS Industry, general recode 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 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. IPUMS 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. CodesArgentina 1970 - Spanish Argentina 1980 - Spanish Argentina 1991 - Spanish Argentina 2001 - Spanish Armenia 2001 Armenia 2011 Austria 1971-2001 - German Austria 2011 Bangladesh 1991 Bangladesh 2001 Bangladesh 2011 Belarus 2009 Benin 1979 Benin 1992 Benin 2002 Benin 2013 Bolivia 1976 Bolivia 1992 Bolivia 2001 Bolivia 2012 Botswana 1981 Botswana 1991 Botswana 2001 Botswana 2011 Brazil 1960 - Portuguese Brazil 1970 - Portuguese Brazil 1980 - Portuguese Brazil 1991 - Portuguese Brazil 2000 - Portuguese Brazil 2010 Burkina Faso 1996 Cambodia 1998 Cambodia 2004 Cambodia 2008 Cambodia 2013 Cambodia 2019 Cameroon 2005 Canada 1971 Canada 1981 Canada 1991-2001 Canada 2011 Chile 1960 Chile 1970 Chile 1982 Chile 1992 Chile 2002 Chile 2017 China 1982 China 1990 China 2000 Colombia 1964 - Spanish Colombia 1973 - Spanish Colombia 1993 - Spanish Colombia 2005 - Spanish Costa Rica 1963 Costa Rica 1973 Costa Rica 1984 Costa Rica 2000 Costa Rica 2011 Cote d’Ivoire 1988 Cote d’Ivoire 1998 Cuba 2002 Cuba 2012 Dominican Republic 1960 Dominican Republic 1970 Dominican Republic 1981 Dominican Republic 2002 Dominican Republic 2010 Ecuador 1962 Ecuador 1982 Ecuador 1990 Ecuador 2001 Ecuador 2010 Egypt 1986 Egypt 1996 Egypt 2006 El Salvador 1992 El Salvador 2007 Ethiopia 1984 Ethiopia 1994 Fiji 1966 Fiji 1976 Fiji 1986 Fiji 1996 Fiji 2007 Fiji 2014 Finland 2010 France 1962-1968 - French France 1975-1982 - French France 1990 - French France 1999 France 2006 France 2011 Germany 1970 Germany 1971 Germany 1981 Germany 1987 Ghana 1984 Ghana 2000 Ghana 2010 Greece 1971 Greece 1981 Greece 1991-2001 Greece 2011 Guatemala 1964 Guatemala 1973 Guatemala 1981 Guatemala 1994 Guatemala 2002 Guinea 1983 Guinea 2014 Haiti 1971 Haiti 1982 Haiti 2003 Honduras 1961 Honduras 1974 Honduras 2001 Hungary 2001 Hungary 2011 India 1983 India 1987 India 1993 India 1999 India 2004 India 2009 Indonesia 1971 Indonesia 1976 Indonesia 1980 Indonesia 1985 Indonesia 1990 Indonesia 1995 Indonesia 2000 Indonesia 2005 Indonesia 2010 Iran 2006 Iran 2011 Iraq 1997 Ireland 1971 Ireland 1981 Ireland 1986 Ireland 1991 Ireland 1996 Ireland 2002 Ireland 2006 Ireland 2011 Ireland 2016 Israel 1972 Israel 1983 Israel 1995 Israel 2008 Italy 2001 Italy 2011 Italy Surveys 2011-2013 Italy Surveys 2014-2020 Jamaica 1982 Jamaica 1991 Jamaica 2001 Jordan 2004 Kyrgyz Republic 1999 Kyrgyz Republic 2009 Laos 1995 Laos 2005 Laos 2015 Lesotho 2006 Liberia 1974 Liberia 2008 Malawi 1987 Malawi 1998 Malawi 2008 Malaysia 1970 Malaysia 1980-1991 Malaysia 2000 Mali 1987 Mali 1998 Mali 2009 Mauritius 1990 Mauritius 2000 Mauritius 2011 Mexico 1960 - Spanish Mexico 1970 - Spanish Mexico 1990 - Spanish Mexico 1995 - Spanish Mexico 2000 - Spanish Mexico 2010 Mexico 2015 Mexico 2020 Mexico surveys 2005-2019 Morocco 1982 Morocco 1994 Morocco 2004 Morocco 2014 Mozambique 1997 Mozambique 2007 Myanmar 2014 Nepal 2001 Nepal 2011 Netherlands 1960 Netherlands 1971 Netherlands 2001 Netherlands 2011 Nicaragua 1971 Nicaragua 1995 Nicaragua 2005 Nigeria 2006 Nigeria 2007 Nigeria 2008 Nigeria 2009 Nigeria 2010 Pakistan 1973 Palestine 1997 Palestine 2007 Palestine 2017 Panama 1960 - Spanish Panama 1970-1980 - Spanish Panama 1990-2000 - Spanish Panama 2010 Papua New Guinea 1980 Papua New Guinea 2000 Paraguay 1962 Paraguay 1972 Paraguay 1982 Paraguay 1992 Paraguay 2002 Peru 1993 Peru 2007 Peru 2017 Philippines 1990 Philippines 1995 Philippines 2000 Philippines 2010 Poland 1978 Poland 2002 Portugal 1981 - Portuguese Portugal 1991-2001 - Portuguese Portugal 2011 Puerto Rico 1970-2005 Puerto Rico 2010 Puerto Rico 2015 Puerto Rico 2020 Romania 1977 Romania 1992 Romania 2002 Romania 2011 Rwanda 2002 - French Rwanda 2012 Saint Lucia 1991 Senegal 1988 Senegal 2013 Sierra Leone 2004 South Africa 1996 South Africa 2001-2007 South Sudan 2008 Spain 1981 - Spanish Spain 1991 - Spanish Spain 2001 - Spanish Spain 2011 Spain Surveys 2005-2020 Sudan 2008 Suriname 2004 Suriname 2012 Switzerland 1970-2000 Switzerland 2011 Tanzania 2002 Tanzania 2012 Thailand 1970 Thailand 1980 Thailand 1990 Thailand 2000 Togo 1970 Togo 2010 Trinidad and Tobago 1980 Trinidad and Tobago 1990 Trinidad and Tobago 2000 Turkey 1985 Turkey 1990 Turkey 2000 Uganda 2002 United Kingdom 1961 United Kingdom 1971 United Kingdom 1991 United Kingdom 2001 United States 1960 United States 1970 United States 1980 United States 1990 United States 2000-2005 United States 2010 United States 2015 United States 2020 Uruguay 1963 Uruguay 1985 Uruguay 1996 Uruguay 2006 Venezuela 1981 Venezuela 1990 Venezuela 2001 - Spanish Vietnam 1989 Vietnam 1999 Vietnam 2009 Vietnam 2019 Zambia 1990 Zambia 2000 Zambia 2010 IPUMS Status in employment (class of worker) [general version] NIU (not in universe) 1 Self-employed 2 Wage/salary worker 3 Unpaid worker 4 Other 9 Unknown/missing CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. IPUMS Status in employment (class of worker) [detailed version] 000 NIU (not in universe) 100 Self-employed 101 Self-employed, unincorporated 102 Self-employed, incorporated 110 Employer 111 Sharecropper, employer 120 Working on own account 121 Own account, agriculture 122 Domestic worker, self-employed 123 Subsistence worker, own consumption 124 Own account, other 125 Own account, without temporary/unpaid help 126 Own account, with temporary/unpaid help 130 Member of cooperative 140 Sharecropper 141 Sharecropper, self-employed 142 Sharecropper, employee 150 Kibbutz member 199 Self-employed, not specified 200 Wage/salary worker 201 Management 202 Non-management 203 White collar (non-manual) 204 Blue collar (manual) 205 White or blue collar 206 Day laborer 207 Employee, with a permanent job 208 Employee, occasional, temporary, contract 209 Employee without legal contract 210 Wage/salary worker, private employer 211 Apprentice 212 Religious worker 213 Wage/salary worker, non-profit, NGO 214 White collar, private 215 Blue collar, private 216 Paid family worker 217 Cooperative employee 220 Wage/salary worker, government 221 Federal, government employee 222 State government employee 223 Local government employee 224 White collar, public 225 Blue collar, public 226 Public companies 227 Civil servants, local collectives 230 Domestic worker (work for private household) 240 Seasonal migrant 241 Seasonal migrant, no broker 242 Seasonal migrant, uses broker 250 Other wage and salary 251 Canal zone/commission employee 252 Government employment/training program 253 Mixed state/private enterprise/parastatal 254 Government public work program 255 State enterprise employee 256 Coordinated and continuous collaboration job 300 Unpaid worker 310 Unpaid family worker 320 Apprentice, unpaid or unspecified 330 Trainee 340 Apprentice or trainee 350 Works for others without wage 400 Other 999 Unknown/missing CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. IPUMS Available to work 1 Yes 2 No 8 Unknown 9 NIU (Not in universe) WRKAVAIL indicates whether a person is available to work (readiness) within a short period of time. IPUMS Total income INCTOT reports the person's total personal income from all sources in the previous month or year. INCTOT is a 7-digit numeric variable. Codes9999998 = Unknown/missing. 9999999 = NIU (not in universe). Top codes:Brazil 1991: 9,999,997+ Canada 1971: 50,000+ females in Atlantic region; 75,000+ for others Canada 1981: 75,000+ all females, males in Atlantic region; 100,000+ males other regions Canada 1991-2001: 200,000+ Dominican Republic 1981: 3,000+ Dominican Republic 2002: 500,000+ Indonesia 1976: 600,000+ Mexico 1970: 5,500,000+ Panama 2010: 10,000+ Puerto Rico 1980: 50,000+ South Africa 1996: 360,001+ South Africa 2001-2011: 2,457,601+ Trinidad and Tobago 1970: 1,200+ Trinidad and Tobago 2000: 13,000+ U.S.A. 1960: 25,000+ U.S.A. 1970: 50,000+ U.S.A. 1980: 75,000+ U.S.A. 1990: State median of values over 400,000 U.S.A. 2000: 999,998+ Bottom codes:Canada 1981-2001: -50,000 Puerto Rico 2005-2020: -19,998 U.S.A. 1960: -9,900 U.S.A. 1970: -9,900 U.S.A. 1980: -9,995 U.S.A. 1990, 2005-2020: -19,998 U.S.A. 2000: -20,000 IPUMS Receives pension or similar benefit 10 Yes, receives a pension 11 Retirement 12 Retirement and other 13 Disability 14 Disability and other 15 Other or type not specified 20 No, does not receive a pension 98 Unknown 99 NIU (not in universe) PENSION indicates whether the respondent received a pension or similar benefits. IPUMS Migration status, previous residence 00 NIU (not in universe) 10 Same major administrative unit 11 Same major, same minor administrative unit 12 Same major, different minor administrative unit 20 Different major administrative unit 30 Abroad 98 Response suppressed 99 Not reported/missing/unknown MIGRATEP indicates whether the person's most recent move (if any) was between minor administrative units, major units, or countries. IPUMS 1st subnational geographic level of previous residence, world [consistent boundaries over time] 051901 Yerevan [Province: Armenia] 051902 Aragatsotn [Province: Armenia] 051903 Ararat [Province: Armenia] 051904 Armavir [Province: Armenia] 051905 Gegharkunik [Province: Armenia] 051906 Lori [Province: Armenia] 051907 Kotayk [Province: Armenia] 051908 Shirak [Province: Armenia] 051909 Syunik [Province: Armenia] 051910 Vayots Dzor [Province: Armenia] 051911 Tavush [Province: Armenia] 051912 Nagorno-Karabagh [Province: Armenia] 051997 Foreign country [Province: Armenia] 051998 Unknown [Province: Armenia] 051999 NIU (not in universe) [Province: Armenia] 112001 Brest [Region: Belarus] 112002 Vitebsk [Region: Belarus] 112003 Gomel [Region: Belarus] 112004 Grodno [Region: Belarus] 112006 Minsk, Minsk City [Region: Belarus] 112007 Mogilev [Region: Belarus] 112097 Foreign country [Region: Belarus] 112098 Unknown [Region: Belarus] 112099 NIU (not in universe) [Region: Belarus] 204001 Alibori [Department: Benin] 204002 Atacora [Department: Benin] 204003 Atlantique [Department: Benin] 204004 Borgou [Department: Benin] 204005 Collines [Department: Benin] 204006 Couffo [Department: Benin] 204007 Donga [Department: Benin] 204008 Littoral [Department: Benin] 204009 Mono [Department: Benin] 204010 Oueme [Department: Benin] 204011 Plateau [Department: Benin] 204012 Zou [Department: Benin] 204097 Abroad [Department: Benin] 204098 Unknown [Department: Benin] 204099 NIU (not in universe) [Department: Benin] 076011 Rondônia [State: Brazil] 076012 Acre [State: Brazil] 076013 Amazonas [State: Brazil] 076014 Roraima [State: Brazil] 076015 Pará [State: Brazil] 076016 Amapá [State: Brazil] 076021 Maranhão [State: Brazil] 076022 Piauí [State: Brazil] 076023 Ceará [State: Brazil] 076024 Rio Grande do Norte [State: Brazil] 076025 Paraíba [State: Brazil] 076026 Pernambuco, Arquipelago de Fernando de Noronha [State: Brazil] 076027 Alagoas [State: Brazil] 076028 Sergipe [State: Brazil] 076029 Bahia [State: Brazil] 076031 Minas Gerais [State: Brazil] 076032 Espírito Santo [State: Brazil] 076033 Rio de Janeiro, Guanabara [State: Brazil] 076035 São Paulo [State: Brazil] 076036 Serra dos Aimorés [State: Brazil] 076041 Paraná [State: Brazil] 076042 Santa Catarina [State: Brazil] 076043 Rio Grande do Sul [State: Brazil] 076051 Mato Grosso do Sul, Mato Grosso [State: Brazil] 076052 Goiás, Tocantins [State: Brazil] 076053 Distrito Federal [State: Brazil] 076054 Brazil, unspecified [State: Brazil] 076097 Abroad [State: Brazil] 076098 Unknown [State: Brazil] 076099 NIU (not in universe) [State: Brazil] 116001 Banteay Meanchey [Province: Cambodia] 116002 Battambang [Province: Cambodia] 116003 Kampong Cham, Tbong Khmum [Province: Cambodia] 116004 Kampong Chhnang [Province: Cambodia] 116005 Kampong Speu [Province: Cambodia] 116006 Kampong Thom [Province: Cambodia] 116007 Kampot [Province: Cambodia] 116008 Phnom Penh, Kandal [Province: Cambodia] 116009 Koh Kong, Preah Sihanouk [Province: Cambodia] 116010 Kratie [Province: Cambodia] 116011 Mondul Kiri [Province: Cambodia] 116013 Preah Vihear [Province: Cambodia] 116014 Prey Veng [Province: Cambodia] 116015 Pursat [Province: Cambodia] 116016 Ratanak Kiri [Province: Cambodia] 116017 Siem Reap, Otdar Meanchey [Province: Cambodia] 116019 Stung Treng [Province: Cambodia] 116020 Svay Rieng [Province: Cambodia] 116021 Takeo [Province: Cambodia] 116023 Kep [Province: Cambodia] 116024 Pailin [Province: Cambodia] 116097 Foreign country [Province: Cambodia] 116098 Unknown [Province: Cambodia] 116099 NIU (not in universe) [Province: Cambodia] 120002 Centre, Sud [Province: Cameroon] 120003 Est [Province: Cameroon] 120004 Nord, Adamoua, Extrème Nord [Province: Cameroon] 120005 Littoral [Province: Cameroon] 120007 Nord Ouest [Province: Cameroon] 120008 Ouest [Province: Cameroon] 120010 Sud Ouest [Province: Cameroon] 120096 Cameroon - unknown arrondissement [Province: Cameroon] 120097 Foreign country [Province: Cameroon] 120098 Unknown [Province: Cameroon] 120099 NIU (not in universe) [Province: Cameroon] 152001 Tarapaca [Province: Chile] 152002 Antofagasta [Province: Chile] 152003 Atacama [Province: Chile] 152004 Coquimbo [Province: Chile] 152005 Aconcagua [Province: Chile] 152006 Valparaíso [Province: Chile] 152007 Santiago [Province: Chile] 152008 O'Higgins [Province: Chile] 152009 Colchagua [Province: Chile] 152010 Curicó [Province: Chile] 152011 Talca [Province: Chile] 152012 Maule [Province: Chile] 152013 Linares [Province: Chile] 152014 Ñuble [Province: Chile] 152015 Concepción [Province: Chile] 152016 Arauco [Province: Chile] 152017 Bío Bío [Province: Chile] 152018 Malleco [Province: Chile] 152019 Cautín [Province: Chile] 152020 Valdivia [Province: Chile] 152021 Osorno [Province: Chile] 152022 Llanquihue [Province: Chile] 152023 Chiloé [Province: Chile] 152024 Aysén [Province: Chile] 152025 Magallanes [Province: Chile] 152097 Foreign country [Province: Chile] 152098 Unknown [Province: Chile] 152099 NIU (not in universe) [Province: Chile] 170005 Antioquia [Department: Colombia] 170008 Atlántico [Department: Colombia] 170011 Bogotá D.C., Cundinamarca [Department: Colombia] 170013 Bolívar, Sucre [Department: Colombia] 170015 Boyacá, Casanare [Department: Colombia] 170018 Caquetá [Department: Colombia] 170019 Cauca [Department: Colombia] 170023 Córdoba [Department: Colombia] 170027 Chocó [Department: Colombia] 170041 Huila [Department: Colombia] 170044 La Guajira [Department: Colombia] 170050 Meta [Department: Colombia] 170052 Nariño [Department: Colombia] 170054 Cesar, Norte De Santander, Magdalena [Department: Colombia] 170066 Caldas, Quindío, Risaralda [Department: Colombia] 170068 Santander [Department: Colombia] 170073 Tolima [Department: Colombia] 170076 Valle Del Cauca [Department: Colombia] 170081 Arauca [Department: Colombia] 170086 Putumayo [Department: Colombia] 170088 Archipiélago De San Andrés Y Providencia [Department: Colombia] 170095 Amazonas, Guaviare, Vaupés, Vichada, Guainía [Department: Colombia] 170097 Abroad [Department: Colombia] 170098 Unknown [Department: Colombia] 188001 San José [Province: Costa Rica] 188002 Alajuela [Province: Costa Rica] 188003 Cartago [Province: Costa Rica] 188004 Heredia [Province: Costa Rica] 188005 Guanacaste [Province: Costa Rica] 188006 Puntarenas [Province: Costa Rica] 188007 Limón [Province: Costa Rica] 188097 Foreign country [Province: Costa Rica] 188098 Unknown [Province: Costa Rica] 192021 Pinar del Río, Artemisa, Mayabeque [Province: Cuba] 192023 La Habana [Province: Cuba] 192025 Matanzas [Province: Cuba] 192026 Villa Clara [Province: Cuba] 192027 Cienfuegos [Province: Cuba] 192028 Sancti Spíritus [Province: Cuba] 192029 Ciego de Ávila [Province: Cuba] 192030 Camagüey [Province: Cuba] 192031 Las Tunas [Province: Cuba] 192032 Holguín [Province: Cuba] 192033 Granma [Province: Cuba] 192034 Santiago de Cuba [Province: Cuba] 192035 Guantánamo [Province: Cuba] 192040 Isla de la Juventud [Province: Cuba] 192997 Abroad [Province: Cuba] 192998 Unknown [Province: Cuba] 192999 NIU (not in universe) [Province: Cuba] 218001 Azuay [Province: Ecuador] 218002 Bolívar [Province: Ecuador] 218004 Carchi [Province: Ecuador] 218005 Cotopaxi [Province: Ecuador] 218006 Chimborazo [Province: Ecuador] 218007 El Oro [Province: Ecuador] 218009 Cañar, Esmeraldas, Guayas, Manabí, Manga del Cura [Disputed canton], Pichincha, El Piedrero [Disputed canton], Los Ríos, Santa Elena, Santo Domingo de las Tsáchilas, Galápagos [Province: Ecuador] 218010 Imbabura, Las Golondrinas [Disputed canton] [Province: Ecuador] 218011 Loja [Province: Ecuador] 218014 Morona Santiago [Province: Ecuador] 218016 Pastaza [Province: Ecuador] 218018 Tungurahua [Province: Ecuador] 218019 Zamora Chinchipe [Province: Ecuador] 218021 Napo, Orellana, Sucumbíos [Province: Ecuador] 218097 Foreign country [Province: Ecuador] 218098 Unknown and Disputed Zones [Province: Ecuador] 218999 NIU (not in universe) [Province: Ecuador] 818000 Reported same governorate as household location [Governorate: Egypt] 818001 Giza, 6th October City, Cairo, Helwan [Governorate: Egypt] 818002 Alexandria [Governorate: Egypt] 818003 Port Said [Governorate: Egypt] 818004 Suez [Governorate: Egypt] 818011 Demietta [Governorate: Egypt] 818012 Dakahlia [Governorate: Egypt] 818013 Sharkia [Governorate: Egypt] 818014 Kaliobia [Governorate: Egypt] 818015 Kafr Sheikh [Governorate: Egypt] 818016 Gharbia [Governorate: Egypt] 818018 Menoufia, Behera [Governorate: Egypt] 818019 Ismailia [Governorate: Egypt] 818022 Bani Swif [Governorate: Egypt] 818023 Fayoum [Governorate: Egypt] 818024 Menia [Governorate: Egypt] 818025 Asiut [Governorate: Egypt] 818026 Sohag [Governorate: Egypt] 818027 Qena, Luxor [Governorate: Egypt] 818028 Aswan [Governorate: Egypt] 818031 Red Sea [Governorate: Egypt] 818032 New Valley [Governorate: Egypt] 818033 Marsa Matroh [Governorate: Egypt] 818034 North Sinai [Governorate: Egypt] 818035 South Sinai [Governorate: Egypt] 818097 Abroad [Governorate: Egypt] 818098 Unknown [Governorate: Egypt] 818099 NIU (not in universe) [Governorate: Egypt] 222001 Ahuachapán [Department: El Salvador] 222002 Santa Ana [Department: El Salvador] 222003 Sonsonate [Department: El Salvador] 222004 Chalatenango [Department: El Salvador] 222005 La Libertad [Department: El Salvador] 222006 San Salvador [Department: El Salvador] 222007 Cuscatlán [Department: El Salvador] 222008 La Paz [Department: El Salvador] 222009 Cabañas [Department: El Salvador] 222010 San Vicente [Department: El Salvador] 222011 Usulután [Department: El Salvador] 222012 San Miguel [Department: El Salvador] 222013 Morazán [Department: El Salvador] 222014 La Unión [Department: El Salvador] 222098 Abroad [Department: El Salvador] 222099 NIU (not in universe) [Department: El Salvador] 231001 Tigray [Region: Ethiopia] 231002 Affar [Region: Ethiopia] 231003 Amhara [Region: Ethiopia] 231004 Oromia, Somali [Region: Ethiopia] 231006 Benishangul-Gumuz [Region: Ethiopia] 231007 Southern Nations, Nationalities, and Peoples (SNNP) [Region: Ethiopia] 231012 Gambela [Region: Ethiopia] 231013 Harari [Region: Ethiopia] 231014 Addis Ababa [Region: Ethiopia] 231015 Dire Dawa [Region: Ethiopia] 231097 Abroad [Region: Ethiopia] 231099 NIU [Region: Ethiopia] 250001 Guadeloupe [Region: France] 250002 Martinique [Region: France] 250003 French Guyana [Region: France] 250004 Réunion Island [Region: France] 250011 Île-de-France [Region: France] 250021 Champagne-Ardenne [Region: France] 250022 Picardy [Region: France] 250023 Upper Normandy [Region: France] 250024 Centre [Region: France] 250025 Lower Normandy [Region: France] 250026 Burgundy [Region: France] 250031 North Pas-de-Calais [Region: France] 250041 Lorraine [Region: France] 250042 Alsace [Region: France] 250043 Franche-Comté [Region: France] 250052 Loire Valley [Region: France] 250053 Brittany [Region: France] 250054 Poitou-Charentes [Region: France] 250072 Aquitaine [Region: France] 250073 Midi-Pyrénées [Region: France] 250074 Limousin [Region: France] 250082 Rhône-Alpes [Region: France] 250083 Auvergne [Region: France] 250091 Languedoc-Roussillon [Region: France] 250093 Provence-Alpes-Riviera [Region: France] 250094 Corsica [Region: France] 250097 Abroad [Region: France] 320001 Guatemala [Department: Guatemala] 320002 El Progreso [Department: Guatemala] 320003 Sacatepéquez [Department: Guatemala] 320004 Chimaltenango [Department: Guatemala] 320005 Escuintla [Department: Guatemala] 320006 Santa Rosa [Department: Guatemala] 320007 Sololá [Department: Guatemala] 320008 Totonicapán [Department: Guatemala] 320009 Quetzaltenango [Department: Guatemala] 320010 Suchitepéquez [Department: Guatemala] 320011 Retalhuleu [Department: Guatemala] 320012 San Marcos [Department: Guatemala] 320013 Huehuetenango [Department: Guatemala] 320014 Quiché [Department: Guatemala] 320015 Baja Verapaz [Department: Guatemala] 320016 Alta Verapaz [Department: Guatemala] 320017 Petén [Department: Guatemala] 320018 Izabal [Department: Guatemala] 320019 Zacapa [Department: Guatemala] 320020 Chiquimula [Department: Guatemala] 320021 Jalapa [Department: Guatemala] 320022 Jutiapa [Department: Guatemala] 320097 Foreign Country [Department: Guatemala] 320098 Unknown [Department: Guatemala] 320099 NIU [Department: Guatemala] 324011 Boffa [Region: Guinea] 324012 Boké [Region: Guinea] 324013 Fria [Region: Guinea] 324014 Gaoual [Region: Guinea] 324015 Koundara [Region: Guinea] 324021 Conakry [Region: Guinea] 324031 Dabola [Region: Guinea] 324032 Dinguiraye [Region: Guinea] 324033 Faranah [Region: Guinea] 324034 Kissidougou [Region: Guinea] 324041 Kankan [Region: Guinea] 324042 Kérouané [Region: Guinea] 324043 Kouroussa [Region: Guinea] 324044 Mandiana [Region: Guinea] 324045 Siguiri [Region: Guinea] 324051 Coyah, Dubréka [Region: Guinea] 324053 Forécariah [Region: Guinea] 324054 Kindia [Region: Guinea] 324055 Télimélé [Region: Guinea] 324061 Koubia [Region: Guinea] 324062 Labé [Region: Guinea] 324063 Lélouma [Region: Guinea] 324064 Mali [Region: Guinea] 324065 Tougué [Region: Guinea] 324071 Dalaba [Region: Guinea] 324072 Mamou [Region: Guinea] 324073 Pita [Region: Guinea] 324081 Beyla [Region: Guinea] 324082 Guéckédou [Region: Guinea] 324083 Lola [Region: Guinea] 324084 Macenta [Region: Guinea] 324085 Nzerekore [Region: Guinea] 324086 Yomou [Region: Guinea] 324096 Guinea, place unknown [Region: Guinea] 324097 Foreign country [Region: Guinea] 324098 Unknown [Region: Guinea] 324099 NIU (not in universe) [Region: Guinea] 332003 Nord (North) and Nord'est (North East) [Department: Haiti] 332006 Centre (Central), L'Artibonite, Ouest (West), Sud'Est (South East) [Department: Haiti] 332007 Grand'Anse, Nippes, Sud (South) [Department: Haiti] 332009 Nord'Ouest (North West) [Department: Haiti] 332097 Foreign Country [Department: Haiti] 332098 Unknown [Department: Haiti] 356001 Jammu and Kashmir [State: India] 356002 Himachal Pradesh [State: India] 356003 Punjab [State: India] 356004 Chandigarh [State: India] 356006 Haryana [State: India] 356007 Delhi [State: India] 356008 Rajasthan [State: India] 356009 Uttar Pradesh, Uttaranchal [State: India] 356010 Bihar, Jharkhand [State: India] 356011 Sikkim [State: India] 356012 Arunachal Pradesh [State: India] 356013 Nagaland [State: India] 356014 Manipur [State: India] 356015 Mizoram [State: India] 356016 Tripura [State: India] 356017 Meghalaya [State: India] 356018 Assam [State: India] 356019 West Bengal [State: India] 356021 Orissa [State: India] 356023 Madhya Pradesh, Chhattisgarh [State: India] 356024 Gujarat [State: India] 356026 Dadra and Nagar Haveli [State: India] 356027 Maharashtra [State: India] 356028 Andhra Pradesh [State: India] 356029 Karnataka [State: India] 356030 Goa, Daman and Diu [State: India] 356031 Lakshadweep [State: India] 356032 Kerala [State: India] 356033 Tamil Nadu [State: India] 356034 Pondicherry [State: India] 356035 Andaman and Nicobar Islands [State: India] 356097 Abroad [State: India] 356098 Unknown [State: India] 356099 NIU (not in universe) [State: India] 360011 Nanggroe Aceh Darussalam [Province: Indonesia] 360012 Sumatera Utara [Province: Indonesia] 360013 Sumatera Barat [Province: Indonesia] 360014 Kepulauan Riau, Riau [Province: Indonesia] 360015 Jambi [Province: Indonesia] 360016 Bangka Belitung, Sumatera Selatan [Province: Indonesia] 360017 Bengkulu [Province: Indonesia] 360018 Lampung [Province: Indonesia] 360031 DKI Jakarta [Province: Indonesia] 360032 Banten, Jawa Barat [Province: Indonesia] 360033 Jawa Tengah [Province: Indonesia] 360034 DKI Yogyakarta [Province: Indonesia] 360035 Jawa Timur [Province: Indonesia] 360051 Bali [Province: Indonesia] 360052 Nusa Tenggara Barat [Province: Indonesia] 360053 Nusa Tenggara Timur [Province: Indonesia] 360061 Kalimantan Barat [Province: Indonesia] 360062 Kalimantan Tengah [Province: Indonesia] 360063 Kalimantan Selatan [Province: Indonesia] 360064 Kalimantan Timur [Province: Indonesia] 360071 Gorontalo, Sulawesi Utara [Province: Indonesia] 360072 Sulawesi Tengah [Province: Indonesia] 360073 Sulawesi Barat, Sulawesi Selatan [Province: Indonesia] 360074 Sulawesi Tenggara [Province: Indonesia] 360081 Maluku, Maluku Utara [Province: Indonesia] 360094 Papua, Papua Barat [Province: Indonesia] 360097 Abroad [Province: Indonesia] 360098 Unknown [Province: Indonesia] 360099 NIU (not in universe) [Province: Indonesia] 360626 East Timor [Province: Indonesia] 364000 Markazi [Province: Iran] 364001 Gilan [Province: Iran] 364002 Mazandaran [Province: Iran] 364003 East Azarbayejan [Province: Iran] 364004 West Azarbayejan [Province: Iran] 364005 Kermanshah [Province: Iran] 364006 Khuzestan [Province: Iran] 364007 Fars [Province: Iran] 364008 Kerman [Province: Iran] 364009 Razavi Khorasan [Province: Iran] 364010 Esfahan [Province: Iran] 364011 Sistan and Baluchestan [Province: Iran] 364012 Kordestan [Province: Iran] 364013 Hamedan [Province: Iran] 364014 Chaharmahal and Bakhtiyari [Province: Iran] 364015 Lorestan [Province: Iran] 364016 Ilam [Province: Iran] 364017 Kohgiluyeh and Boyerahmad [Province: Iran] 364018 Bushehr [Province: Iran] 364019 Zanjan [Province: Iran] 364020 Semnan [Province: Iran] 364021 Yazd [Province: Iran] 364022 Hormozgan [Province: Iran] 364023 Tehran, Alborz [Province: Iran] 364024 Ardebil [Province: Iran] 364025 Qom [Province: Iran] 364026 Qazvin [Province: Iran] 364027 Golestan [Province: Iran] 364028 North Khorasan [Province: Iran] 364029 South Khorasan [Province: Iran] 364098 Unknown [Province: Iran] 364099 NIU (not in universe) [Province: Iran] 368000 Always lived in residential place of birth [Governorate: Iraq] 368001 In this governorate [Governorate: Iraq] 368011 Dahuk [Governorate: Iraq] 368012 Nineveh [Governorate: Iraq] 368013 Sulaymaniyah [Governorate: Iraq] 368014 Al-Tameem [Governorate: Iraq] 368015 Erbil [Governorate: Iraq] 368021 Diala [Governorate: Iraq] 368022 Al-Anbar [Governorate: Iraq] 368023 Baghdad [Governorate: Iraq] 368024 Babylon [Governorate: Iraq] 368025 Kerbela [Governorate: Iraq] 368026 Wasit [Governorate: Iraq] 368027 Salah Al-Deen [Governorate: Iraq] 368028 Al-Najaf [Governorate: Iraq] 368031 Al-Qadisiya [Governorate: Iraq] 368032 Al-Muthanna [Governorate: Iraq] 368033 Thi-Qar [Governorate: Iraq] 368034 Maysan [Governorate: Iraq] 368035 Al-Basrah [Governorate: Iraq] 368097 Other countries [Governorate: Iraq] 368098 Unknown [Governorate: Iraq] 388001 Kingston [Parish: Jamaica] 388002 Saint Andrew [Parish: Jamaica] 388003 Saint Thomas [Parish: Jamaica] 388004 Portland [Parish: Jamaica] 388005 Saint Mary [Parish: Jamaica] 388006 Saint Ann [Parish: Jamaica] 388007 Trelawny [Parish: Jamaica] 388008 Saint James [Parish: Jamaica] 388009 Hanover [Parish: Jamaica] 388010 Westmoreland [Parish: Jamaica] 388011 Saint Elizabeth [Parish: Jamaica] 388012 Manchester [Parish: Jamaica] 388013 Clarendon [Parish: Jamaica] 388014 Saint Catherine [Parish: Jamaica] 388098 Unknown [Parish: Jamaica] 388099 NIU (Not in universe) [Parish: Jamaica] 400011 Amman [Governorate: Jordan] 400012 Balqa [Governorate: Jordan] 400013 Zarqa [Governorate: Jordan] 400014 Madaba [Governorate: Jordan] 400021 Irbid [Governorate: Jordan] 400022 Mafraq [Governorate: Jordan] 400023 Jarash [Governorate: Jordan] 400024 Ajlun [Governorate: Jordan] 400031 Karak [Governorate: Jordan] 400032 Tafilah [Governorate: Jordan] 400033 Ma'an [Governorate: Jordan] 400034 Aqaba [Governorate: Jordan] 400997 Foreign Country [Governorate: Jordan] 400998 Unknown [Governorate: Jordan] 404001 Nairobi [Province: Kenya] 404002 Central [Province: Kenya] 404003 Coast [Province: Kenya] 404004 Eastern [Province: Kenya] 404005 Northeastern [Province: Kenya] 404006 Nyanza [Province: Kenya] 404007 Rift Valley [Province: Kenya] 404008 Western [Province: Kenya] 404097 Abroad [Province: Kenya] 404098 Unknown [Province: Kenya] 404099 NIU (not in universe) [Province: Kenya] 417001 Bishkek [Region: Kyrgyz Republic] 417002 Issyk-Kul region [Region: Kyrgyz Republic] 417003 Dzhalal-Abad region [Region: Kyrgyz Republic] 417004 Naryn region [Region: Kyrgyz Republic] 417005 Batken region [Region: Kyrgyz Republic] 417006 Oshskaya region, City of Osh [Region: Kyrgyz Republic] 417007 Talasskaya region [Region: Kyrgyz Republic] 417008 Chuya region [Region: Kyrgyz Republic] 417096 Other Kyrgyz Republic, not specified [Region: Kyrgyz Republic] 417097 Foreign country [Region: Kyrgyz Republic] 417098 Unknown [Region: Kyrgyz Republic] 417099 NIU (not in universe) [Region: Kyrgyz Republic] 418001 Vientiane Capital [Province: Laos] 418002 Phongsaly [Province: Laos] 418003 Luangnamtha [Province: Laos] 418004 Oudomxay [Province: Laos] 418005 Bokeo [Province: Laos] 418006 Luangprabang [Province: Laos] 418007 Huaphanh [Province: Laos] 418008 Xayaboury [Province: Laos] 418009 Xienkhuang [Province: Laos] 418010 Vientiane Province [Province: Laos] 418011 Borikhamxay [Province: Laos] 418012 Khammuane [Province: Laos] 418013 Savanakhet [Province: Laos] 418014 Saravane [Province: Laos] 418015 Sekong [Province: Laos] 418016 Champasack [Province: Laos] 418017 Attapeu [Province: Laos] 418018 Xaysomboune [Province: Laos] 418097 Foreign Country [Province: Laos] 418098 Unknown [Province: Laos] 418099 NIU [Province: Laos] 662003 Castries city, Castries rural, Castries suburban [District: Saint Lucia] 662009 Choiseul, Laborie, Vieux-Fort [District: Saint Lucia] 662010 Anse-la-Raye, Canaries, Micoud, Soufriere [District: Saint Lucia] 662012 Dennery, Gros-Islet [District: Saint Lucia] 662098 Unknown [District: Saint Lucia] 662099 NIU [District: Saint Lucia] 454101 Chitipa [District: Malawi] 454102 Karonga [District: Malawi] 454103 Nkhata Bay, Likoma [District: Malawi] 454104 Rumphi [District: Malawi] 454105 Mzimba, Mzuzu city [District: Malawi] 454201 Kasungu [District: Malawi] 454202 Nkhotakota [District: Malawi] 454203 Ntchisi [District: Malawi] 454204 Dowa [District: Malawi] 454205 Salima [District: Malawi] 454206 Lilongwe, Lilongwe city [District: Malawi] 454207 Mchinji [District: Malawi] 454208 Dedza [District: Malawi] 454209 Ntcheu [District: Malawi] 454301 Mangochi [District: Malawi] 454302 Machinga [District: Malawi] 454303 Zomba, Zomba city [District: Malawi] 454304 Chiradzulu [District: Malawi] 454305 Blantyre, Blantyre city [District: Malawi] 454307 Thyolo [District: Malawi] 454308 Mulanje [District: Malawi] 454309 Phalombe [District: Malawi] 454310 Chikwawa [District: Malawi] 454311 Nsanje [District: Malawi] 454312 Balaka [District: Malawi] 454313 Mwanza, Neno [District: Malawi] 454997 Abroad [District: Malawi] 454999 NIU (not in universe) [District: Malawi] 466001 Kayes [Region: Mali] 466002 Koulikoro [Region: Mali] 466003 Sikasso [Region: Mali] 466004 Ségou [Region: Mali] 466005 Mopti [Region: Mali] 466006 Tombouctou [Region: Mali] 466007 Gao, Kidal [Region: Mali] 466009 Bamako [Region: Mali] 466096 Mali, province unspecified [Region: Mali] 466097 Foreign country [Region: Mali] 466098 Unknown [Region: Mali] 466999 NIU (not in universe) [Region: Mali] 484001 Aguascalientes [State: Mexico] 484002 Baja California [State: Mexico] 484003 Baja California Sur [State: Mexico] 484004 Campeche [State: Mexico] 484005 Coahuila de Zaragoza [State: Mexico] 484006 Colima [State: Mexico] 484007 Chiapas [State: Mexico] 484008 Chihuahua [State: Mexico] 484009 Distrito Federal [State: Mexico] 484010 Durango [State: Mexico] 484011 Guanajuato [State: Mexico] 484012 Guerrero [State: Mexico] 484013 Hidalgo [State: Mexico] 484014 Jalisco [State: Mexico] 484015 México [State: Mexico] 484016 Michoacán de Ocampo [State: Mexico] 484017 Morelos [State: Mexico] 484018 Nayarit [State: Mexico] 484019 Nuevo León [State: Mexico] 484020 Oaxaca [State: Mexico] 484021 Puebla [State: Mexico] 484022 Querétaro [State: Mexico] 484023 Quintana Roo [State: Mexico] 484024 San Luis Potosí [State: Mexico] 484025 Sinaloa [State: Mexico] 484026 Sonora [State: Mexico] 484027 Tabasco [State: Mexico] 484028 Tamaulipas [State: Mexico] 484029 Tlaxcala [State: Mexico] 484030 Veracruz de Ignacio de la Llave [State: Mexico] 484031 Yucatán [State: Mexico] 484032 Zacatecas [State: Mexico] 484097 Abroad [State: Mexico] 484098 Unknown [State: Mexico] 484099 NIU (not in universe) [State: Mexico] 496001 Arkhangai [Province: Mongolia] 496002 Bayan-Olgii [Province: Mongolia] 496003 Bayankhongor [Province: Mongolia] 496004 Bulgan [Province: Mongolia] 496005 Govi-Altai [Province: Mongolia] 496006 Dornogovi, Govisumber [Province: Mongolia] 496007 Dornod [Province: Mongolia] 496008 Dundgovi [Province: Mongolia] 496009 Zavkhan [Province: Mongolia] 496010 Ovorkhangai [Province: Mongolia] 496011 Omnogovi [Province: Mongolia] 496012 Sukhbaatar [Province: Mongolia] 496013 Selenge [Province: Mongolia] 496014 Tov [Province: Mongolia] 496015 Uvs [Province: Mongolia] 496016 Khovd [Province: Mongolia] 496017 Khovsgol [Province: Mongolia] 496018 Khentii [Province: Mongolia] 496019 Darkhan-Uul [Province: Mongolia] 496020 Ulaanbaatar [Province: Mongolia] 496021 Orkhon [Province: Mongolia] 496097 Abroad [Province: Mongolia] 496099 NIU (not in universe) [Province: Mongolia] 104001 Kachin [State: Myanmar] 104002 Kayah [State: Myanmar] 104003 Kayin [State: Myanmar] 104004 Chin [State: Myanmar] 104005 Sagaing [State: Myanmar] 104006 Tanintharyi [State: Myanmar] 104007 Bago [State: Myanmar] 104008 Magway [State: Myanmar] 104009 Mandalay [State: Myanmar] 104010 Mon [State: Myanmar] 104011 Rakhine [State: Myanmar] 104012 Yangon [State: Myanmar] 104013 Shan [State: Myanmar] 104014 Ayeyawady [State: Myanmar] 104015 Nay Pyi Taw [State: Myanmar] 104097 Abroad [State: Myanmar] 104099 NIU [State: Myanmar] 591002 Coclé [Province: Panama] 591003 Colón, Comarca Kuna Yala (San Blas) [Province: Panama] 591004 Bocas de Toro, Chiriquí, Comarca Ngäbe Buglé, Veraguas [Province: Panama] 591005 Comarca Emberá, Darién [Province: Panama] 591006 Herrera [Province: Panama] 591007 Los Santos [Province: Panama] 591008 Panamá [Province: Panama] 591009 Unknown district in Panamá province [Province: Panama] 591097 Foreign country [Province: Panama] 591098 Unknown [Province: Panama] 591099 NIU (not in universe) [Province: Panama] 608001 Abra [Province: Philippines] 608002 Agusan del norte [Province: Philippines] 608003 Agusan del sur [Province: Philippines] 608004 Aklan [Province: Philippines] 608005 Albay [Province: Philippines] 608006 Antique [Province: Philippines] 608007 Basilan, City Of Isabela [Province: Philippines] 608008 Bataan [Province: Philippines] 608010 Batangas [Province: Philippines] 608011 Benguet [Province: Philippines] 608012 Bohol [Province: Philippines] 608013 Bukidnon [Province: Philippines] 608014 Bulacan [Province: Philippines] 608015 Cagayan, Batanes [Province: Philippines] 608016 Camarines norte [Province: Philippines] 608017 Camarines Sur [Province: Philippines] 608018 Camiguin [Province: Philippines] 608019 Capiz [Province: Philippines] 608020 Catanduanes [Province: Philippines] 608021 Cavite [Province: Philippines] 608022 Cebu [Province: Philippines] 608023 Davao (Davao del Norte) [Province: Philippines] 608024 Davao del Sur, Davao Occidental [Province: Philippines] 608025 Davao Oriental [Province: Philippines] 608026 Eastern Samar [Province: Philippines] 608027 Ifugao [Province: Philippines] 608028 Ilocos Norte [Province: Philippines] 608029 Ilocos Sur [Province: Philippines] 608030 Iloilo, Guimaras [Province: Philippines] 608031 Isabela [Province: Philippines] 608032 Kalinga-Apayao, Apayo, Kalinga [Province: Philippines] 608033 La Union [Province: Philippines] 608034 Laguna [Province: Philippines] 608035 Lanao del Norte [Province: Philippines] 608036 Lanao del Sur, Maguindanao, Marawi City and Cotabato city [Province: Philippines] 608037 Leyte, Biliran [Province: Philippines] 608039 Manila [Province: Philippines] 608040 Marinduque [Province: Philippines] 608041 Masbate [Province: Philippines] 608042 Misamis Occidental [Province: Philippines] 608043 Misamis Oriental [Province: Philippines] 608044 Mountain Province [Province: Philippines] 608045 Negros Occidental [Province: Philippines] 608046 Negros Oriental [Province: Philippines] 608047 Cotabato (North Cotabato) [Province: Philippines] 608048 Northern Samar [Province: Philippines] 608049 Nueva Ecija [Province: Philippines] 608050 Nueva Vizcaya [Province: Philippines] 608051 Occidental Mindoro [Province: Philippines] 608052 Oriental Mindoro [Province: Philippines] 608053 Palawan [Province: Philippines] 608054 Pampanga [Province: Philippines] 608055 Pangasinan [Province: Philippines] 608056 Quezon [Province: Philippines] 608057 Quirino [Province: Philippines] 608058 Rizal [Province: Philippines] 608059 Romblon [Province: Philippines] 608060 Samar (Western Samar) [Province: Philippines] 608061 Siquijor [Province: Philippines] 608062 Sorsogon [Province: Philippines] 608063 South Cotabato, Sarangani [Province: Philippines] 608064 Southern Leyte [Province: Philippines] 608065 Sultan Kudarat [Province: Philippines] 608066 Sulu [Province: Philippines] 608067 Surigao Del Norte, Dinagat islands [Province: Philippines] 608068 Surigao del Sur [Province: Philippines] 608069 Tarlac [Province: Philippines] 608070 Tawi-Tawi [Province: Philippines] 608071 Zambales [Province: Philippines] 608072 Zamboanga Norte [Province: Philippines] 608073 Zamboanga del Sur, Zamboanga Sibugay [Province: Philippines] 608074 Manila Metro, 2nd District [Province: Philippines] 608075 Manila Metro, 3rd District [Province: Philippines] 608076 Manila Metro, 4th District [Province: Philippines] 608077 Aurora [Province: Philippines] 608097 Foreign country [Province: Philippines] 608098 Unknown [Province: Philippines] 608099 NIU (not in universe) [Province: Philippines] 642001 Alba [County: Romania] 642002 Arad [County: Romania] 642003 Arges [County: Romania] 642004 Bacau [County: Romania] 642005 Bihor [County: Romania] 642006 Bistrita Nasaud [County: Romania] 642007 Botosani [County: Romania] 642008 Brasov [County: Romania] 642009 Braila [County: Romania] 642010 Buzau [County: Romania] 642011 Caras Severin [County: Romania] 642012 Cluj [County: Romania] 642013 Constanta [County: Romania] 642014 Covasna [County: Romania] 642015 Dambovita [County: Romania] 642016 Dolj [County: Romania] 642017 Galati [County: Romania] 642018 Gorj [County: Romania] 642019 Harghita [County: Romania] 642020 Hunedoara [County: Romania] 642022 Iasi [County: Romania] 642024 Maramures [County: Romania] 642025 Mehedinti [County: Romania] 642026 Mures [County: Romania] 642027 Neamt [County: Romania] 642028 Olt [County: Romania] 642029 Prahova [County: Romania] 642030 Satu Mare [County: Romania] 642031 Salaj [County: Romania] 642032 Sibiu [County: Romania] 642033 Suceava [County: Romania] 642034 Teleorman [County: Romania] 642035 Timis [County: Romania] 642036 Tulcea [County: Romania] 642037 Vaslui [County: Romania] 642038 Valcea [County: Romania] 642039 Vrancea [County: Romania] 642043 Bucharest Sector 1 to 6 [County: Romania] 642051 Calarasi, Giurgiu, Ialomita, Ilfov [County: Romania] 642097 Foreign country [County: Romania] 642098 Unknown [County: Romania] 642099 NIU (not in universe) [County: Romania] 646002 Byumba, Kigali Ngali, Kigali Ville, Kibungo, Umutara [Province: Rwanda] 646003 Gitarama [Province: Rwanda] 646004 Butare [Province: Rwanda] 646005 Gikongoro [Province: Rwanda] 646006 Cyangugu [Province: Rwanda] 646007 Kibuye [Province: Rwanda] 646008 Gisenyi [Province: Rwanda] 646009 Ruhengeri [Province: Rwanda] 646097 Foreign Countries [Province: Rwanda] 646098 Unknown [Province: Rwanda] 646099 NIU [Province: Rwanda] 705001 Pomurska [Region: Slovenia] 705002 Podravska [Region: Slovenia] 705003 Koroška [Region: Slovenia] 705004 Savinjska [Region: Slovenia] 705005 Zasavska [Region: Slovenia] 705006 Spodnjeposavska [Region: Slovenia] 705007 Jugovzhodna Slovenija [Region: Slovenia] 705008 Osrednjeslovenska [Region: Slovenia] 705009 Gorenjska [Region: Slovenia] 705010 Notranjsko-kraška [Region: Slovenia] 705011 Goriška [Region: Slovenia] 705012 Obalno-kraška [Region: Slovenia] 705097 Abroad [Region: Slovenia] 705999 NIU (not in universe) [Region: Slovenia] 710001 Western Cape [Province: South Africa] 710004 Free State [Province: South Africa] 710005 Eastern Cape, KwaZulu-Natal [Province: South Africa] 710007 Gauteng, Limpopo, Mpumalanga, North West, Northern Cape [Province: South Africa] 710097 Foreign country [Province: South Africa] 710098 Unknown [Province: South Africa] 710099 NIU (not in universe) [Province: South Africa] 724011 Galicia [Communities & autonomous city: Spain] 724012 Principado de Asturias [Communities & autonomous city: Spain] 724013 Cantabria [Communities & autonomous city: Spain] 724021 País Vasco [Communities & autonomous city: Spain] 724022 Comunidad Foral de Navarra [Communities & autonomous city: Spain] 724023 La Rioja [Communities & autonomous city: Spain] 724024 Aragón [Communities & autonomous city: Spain] 724030 Comunidad de Madrid [Communities & autonomous city: Spain] 724041 Castilla y León [Communities & autonomous city: Spain] 724042 Castilla-La Mancha [Communities & autonomous city: Spain] 724043 Extremadura [Communities & autonomous city: Spain] 724051 Cataluña [Communities & autonomous city: Spain] 724052 Comunidad Valenciana [Communities & autonomous city: Spain] 724053 Islas Baleares [Communities & autonomous city: Spain] 724061 Andalucía [Communities & autonomous city: Spain] 724062 Región de Murcia [Communities & autonomous city: Spain] 724063 Ciudad Autónoma de Ceuta [Communities & autonomous city: Spain] 724064 Ciudad Autónoma de Melilla [Communities & autonomous city: Spain] 724070 Canarias [Communities & autonomous city: Spain] 724097 Abroad [Communities & autonomous city: Spain] 724999 NIU (not in universe) [Communities & autonomous city: Spain] 740001 Paramaribo [District: Suriname] 740002 Wanica [District: Suriname] 740003 Nickerie [District: Suriname] 740005 Saramacca, Coronie [District: Suriname] 740006 Marowijne, Commewijne [District: Suriname] 740008 Brokopondo, Para [District: Suriname] 740010 Sipaliwini [District: Suriname] 740096 Suriname, district unknown [District: Suriname] 740097 Foreign [District: Suriname] 740098 Unknown [District: Suriname] 764010 Bangkok [Province: Thailand] 764011 Samut Prakan [Province: Thailand] 764012 Nonthaburi [Province: Thailand] 764013 Pathum Thani [Province: Thailand] 764014 Phra Nakhon Si Ayutthaya [Province: Thailand] 764015 Ang Thong [Province: Thailand] 764016 Lop Buri [Province: Thailand] 764017 Sing Buri [Province: Thailand] 764018 Chai Nat [Province: Thailand] 764019 Sa Kaeo, Prachin Buri [Province: Thailand] 764020 Chon Buri [Province: Thailand] 764021 Rayong [Province: Thailand] 764022 Chanthaburi [Province: Thailand] 764023 Trat [Province: Thailand] 764024 Chachoengsao [Province: Thailand] 764026 Nakhon Nayok [Province: Thailand] 764027 Saraburi [Province: Thailand] 764030 Nakhon Ratchasima [Province: Thailand] 764031 Buri Ram [Province: Thailand] 764032 Surin [Province: Thailand] 764033 Si Sa Ket [Province: Thailand] 764034 Ubon Ratchathani, Yasothon, Amnat Charoen [Province: Thailand] 764036 Chaiyaphum [Province: Thailand] 764039 Nong Bua Lam Phu, Udon Thani [Province: Thailand] 764040 Khon Kaen [Province: Thailand] 764042 Loei [Province: Thailand] 764043 Nong Khai [Province: Thailand] 764044 Maha Sarakham [Province: Thailand] 764045 Roi Et [Province: Thailand] 764046 Kalasin [Province: Thailand] 764047 Sakon Nakhon [Province: Thailand] 764048 Nakhon Phanom, Mukdahan [Province: Thailand] 764050 Chiang Mai [Province: Thailand] 764051 Lamphun [Province: Thailand] 764052 Lampang [Province: Thailand] 764053 Uttaradit [Province: Thailand] 764054 Phrae [Province: Thailand] 764055 Nan [Province: Thailand] 764057 Phayao, Chiang Rai [Province: Thailand] 764058 Mae Hong Son [Province: Thailand] 764060 Nakhon Sawan [Province: Thailand] 764061 Uthai Thani [Province: Thailand] 764062 Kamphaeng Phet [Province: Thailand] 764063 Tak [Province: Thailand] 764064 Sukhothai [Province: Thailand] 764065 Phitsanulok [Province: Thailand] 764066 Phichit [Province: Thailand] 764067 Phetchabun [Province: Thailand] 764070 Ratchaburi [Province: Thailand] 764071 Kanchanaburi [Province: Thailand] 764072 Suphanburi [Province: Thailand] 764073 Nakhon Pathom [Province: Thailand] 764074 Samut Sakhon [Province: Thailand] 764075 Samut Songkhram [Province: Thailand] 764076 Phetchaburi [Province: Thailand] 764077 Prachuap Khiri Khan [Province: Thailand] 764080 Nakhon Si Thammarat [Province: Thailand] 764082 Phangnga [Province: Thailand] 764083 Phuket [Province: Thailand] 764084 Krabi, Surat Thani [Province: Thailand] 764086 Ranong, Chumphon [Province: Thailand] 764090 Songkhla [Province: Thailand] 764091 Satun [Province: Thailand] 764092 Trang [Province: Thailand] 764093 Phatthalung [Province: Thailand] 764094 Pattani [Province: Thailand] 764095 Yala [Province: Thailand] 764096 Narathiwat [Province: Thailand] 764097 Same province [Province: Thailand] 764098 Unknown province, but within Thaliand [Province: Thailand] 764997 Abroad [Province: Thailand] 764998 Unknown [Province: Thailand] 764999 NIU (not in universe) [Province: Thailand] 768001 Maritime, Lomé [Region: Togo] 768002 Plateaux, Centrale, Kara [Region: Togo] 768003 Savanes [Region: Togo] 768097 Foreign Country [Region: Togo] 768098 Unknown [Region: Togo] 768099 NIU [Region: Togo] 780010 Port of Spain [Region: Trinidad and Tobago] 780020 San Fernando [Region: Trinidad and Tobago] 780080 Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] 780094 St. Paul, St. Mary, St. David, St. George, St. Patrick, St. Andrew, St. John, Tobago [Region: Trinidad and Tobago] 780098 Unknown [Region: Trinidad and Tobago] 800101 Kalangala [District: Uganda] 800102 Kampala [District: Uganda] 800103 Kiboga, Kyankwanzi [District: Uganda] 800104 Luwero, Nakasongola, Nakaseke [District: Uganda] 800105 Masaka, Ssembabule, Bukomansimbi, Kalungu, Lwengo [District: Uganda] 800106 Mpigi, Wakiso, Butambala, Gomba [District: Uganda] 800107 Mubende, Mityana [District: Uganda] 800108 Mukono, Kayunga, Buikwe, Buvuma [District: Uganda] 800110 Rakai, Lyantonde [District: Uganda] 800201 Bugiri, Iganga, Mayuge, Namutumba, Luuka, Namayingo [District: Uganda] 800202 Busia, Tororo, Butaleja [District: Uganda] 800204 Jinja [District: Uganda] 800205 Kamuli, Kaliro, Buyende [District: Uganda] 800206 Kapchorwa, Bukwo, Kween [District: Uganda] 800207 Katakwi, Soroti, Kaberamaido, Amuria, Serere [District: Uganda] 800208 Kumi, Bukedea, Ngora [District: Uganda] 800209 Mbale, Sironko, Bududa, Manafwa, Bulambuli [District: Uganda] 800210 Pallisa, Budaka, Kibuku [District: Uganda] 800301 Adjumani, Moyo [District: Uganda] 800302 Apac, Oyam, Kole [District: Uganda] 800303 Arua, Yumbe, Koboko, Maracha [District: Uganda] 800304 Gulu, Amuru, Nwoya, Omoro [District: Uganda] 800305 Kitgum, Pader, Agago, Lamwo [District: Uganda] 800306 Kotido, Moroto, Nakapiripirit, Abim, Kaabong, Amudat, Napak [District: Uganda] 800307 Lira, Amolatar, Dokolo, Alebtong, Otuke [District: Uganda] 800310 Nebbi, Zombo [District: Uganda] 800401 Bundibugyo, Ntoroko [District: Uganda] 800402 Bushenyi, Mbarara, Ntungamo, Ibanda, Isingiro, Kiruhura, Buhweju, Mitooma, Rubirizi, Sheema [District: Uganda] 800403 Hoima [District: Uganda] 800404 Kabale, Rubanda [District: Uganda] 800405 Kabarole, Kamwenge, Kyenjojo, Kyegegwa [District: Uganda] 800406 Kasese [District: Uganda] 800407 Kibaale, Kagadi, Kakumiro [District: Uganda] 800408 Kisoro [District: Uganda] 800409 Masindi, Buliisa, Kiryandongo [District: Uganda] 800412 Rukungiri, Kanungu [District: Uganda] 800096 Visitor [District: Uganda] 800097 Foreign country [District: Uganda] 800098 Unknown [District: Uganda] 804001 The Autonomous Republic of Crimea [Region: Ukraine] 804005 Vinnytska oblast [Region: Ukraine] 804007 Volynska oblast [Region: Ukraine] 804012 Dnipropetrovska oblast [Region: Ukraine] 804014 Donetska oblast [Region: Ukraine] 804018 Zhytomyrska oblast [Region: Ukraine] 804021 Zakarpatska oblast [Region: Ukraine] 804023 Zaporizka oblast [Region: Ukraine] 804026 Ivano-Frankivska oblast [Region: Ukraine] 804032 Kyivska oblast [Region: Ukraine] 804035 Kirovohradska oblast [Region: Ukraine] 804044 Luhanska oblast [Region: Ukraine] 804046 Lvivska oblast [Region: Ukraine] 804048 Mykolaivska oblast [Region: Ukraine] 804051 Odeska oblast [Region: Ukraine] 804053 Poltavska oblast [Region: Ukraine] 804056 Rivnenska oblast [Region: Ukraine] 804059 Sumska oblast [Region: Ukraine] 804061 Ternopilska oblast [Region: Ukraine] 804063 Kharkivska oblast [Region: Ukraine] 804065 Khersonska oblast [Region: Ukraine] 804068 Khmelnytska oblast [Region: Ukraine] 804071 Cherkaska oblast [Region: Ukraine] 804073 Chernivetska oblast [Region: Ukraine] 804074 Chernihivska oblast [Region: Ukraine] 804080 Kyiv (independent city) [Region: Ukraine] 804085 Sevastopol (independent city) [Region: Ukraine] 804097 Foreign country [Region: Ukraine] 804098 Unknown [Region: Ukraine] 804099 NIU (not in universe) [Region: Ukraine] 858001 Montevideo [Department: Uruguay] 858002 Artigas [Department: Uruguay] 858003 Canelones [Department: Uruguay] 858004 Cerro Largo [Department: Uruguay] 858005 Colonia [Department: Uruguay] 858006 Durazno [Department: Uruguay] 858007 Flores [Department: Uruguay] 858008 Florida [Department: Uruguay] 858009 Lavalleja [Department: Uruguay] 858010 Maldonado [Department: Uruguay] 858011 Paysandú [Department: Uruguay] 858012 Río Negro [Department: Uruguay] 858013 Rivera [Department: Uruguay] 858014 Rocha [Department: Uruguay] 858015 Salto [Department: Uruguay] 858016 San Jose [Department: Uruguay] 858017 Soriano [Department: Uruguay] 858018 Tacuarembó [Department: Uruguay] 858019 Treinta Y Tres [Department: Uruguay] 858097 Abroad [Department: Uruguay] 858098 Unknown [Department: Uruguay] 858999 NIU (not in universe) [Department: Uruguay] 862001 Federal District, Vargas [State: Venezuela] 862002 Amazonas Federal Territory [State: Venezuela] 862003 Anzoátegui [State: Venezuela] 862004 Apure [State: Venezuela] 862005 Aragua [State: Venezuela] 862007 Bolívar [State: Venezuela] 862008 Carabobo [State: Venezuela] 862009 Cojedes [State: Venezuela] 862010 Amacuros Delta Federal Territory [State: Venezuela] 862011 Falcón [State: Venezuela] 862012 Guárico [State: Venezuela] 862013 Lara [State: Venezuela] 862014 Barinas, Mérida [State: Venezuela] 862015 Miranda [State: Venezuela] 862016 Monagas [State: Venezuela] 862017 Nueva Esparta, Federal Dependencies [State: Venezuela] 862018 Portuguesa [State: Venezuela] 862019 Sucre [State: Venezuela] 862020 Táchira [State: Venezuela] 862021 Trujillo [State: Venezuela] 862022 Yaracuy [State: Venezuela] 862023 Zulia [State: Venezuela] 862097 Foreign country [State: Venezuela] 862098 Unknown [State: Venezuela] 862099 NIU (not in universe) [State: Venezuela] GEOMIG1_P indicates the major administrative unit in which the person previously resided prior to the survey. Only intra-national migrations are recorded; however, the variable incorporates geographies for every country that lists place of previous residence, to enable comparative analysis of subnational migration. Foreign migrants are coded 097 or 997. Codes for GEOMIG1_1 match the geographic codes in GEOLEV1 (current place of residence). For similar information for different time intervals since migration, see variables GEOMIG1_1, GEOMIG1_5, and GEOMIG1_10. More on migration and geography can be found here. IPUMS Years residing in current dwelling 00 Less than 1 year 01 1 year 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 or more 98 Unknown 99 NIU (not in universe) MIGYRS2 indicates the number of years that the respondent has lived in his/her current dwelling. IPUMS Same house 5 years ago NIU (not in universe) 1 Same house 2 Different house 9 Unknown MIGHOUSE indicates whether the person lived in the same house 5 years ago. IPUMS Province of previous residence, South Africa; consistent boundaries, GIS 710001 Western Cape 710004 Free State 710005 Eastern Cape, KwaZulu-Natal 710007 Gauteng, Limpopo, Mpumalanga, North West, Northern Cape 710097 Foreign country 710098 Unknown 710099 NIU (not in universe) MIG1_P_ZA indicates the person's province of previous residence. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. IPUMS Same place 5 years ago, South Africa NIU (not in universe) 1 Yes 2 No 8 Unknown MIGPLCZA indicates whether the person lived in the same location five years prior to the census. IPUMS Disability status NIU (not in universe) 1 Yes, disabled 2 No, not disabled 9 Unknown DISABLED indicates whether the person reported a disability of any kind. IPUMS Employment disability 1 Disabled 2 Not disabled 8 Unknown 9 NIU (not in universe) DISEMP indicates if the respondent was economically inactive because of disabilities or, in some instances, other health-related reasons. IPUMS Blind or vision-impaired NIU (not in universe) 1 Yes 2 No 9 Unknown DISBLND indicates whether the person was blind or had limited vision. IPUMS Deaf or hearing-impaired NIU (not in universe) 1 Yes 2 No 9 Unknown DISDEAF indicates whether the person was deaf or had limited hearing. IPUMS Mute or speech impaired NIU (not in universe) 1 Yes 2 No 9 Unknown DISMUTE indicates if the person could not speak or had a significant speech impediment. IPUMS Mental disability NIU (not in universe) 1 Yes 2 No 9 Unknown DISMNTL indicates whether the person suffered a mental disability in the form of diminished capacity. IPUMS Psychological disability NIU (not in universe) 1 Yes 2 No 9 Unknown DISPSYC indicates whether the person was disabled due to mental illness. IPUMS Person number (within household) South Africa 2007: All persons 00 Household record 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 This variable indicates the person number (within household). IPUMS Number of persons in household South Africa 2007: All households 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 28 28 29 29 30 30 32 32 This variable indicates the number of persons in the household. IPUMS Person number <svar a="all" v="ZA07A400"><br />P-01 Person number<br /><div class="i1">_ _</div><br /></svar> <br />F-01 First name and surname</p> <div class="i1">Write down the name and surname of each member in the appropriate column.<br />Start with the usual members (starting with the head) who were present last night, followed by those members who were absent last night, and lastly by those who stayed in the household last night as visitors.<br />Always start with the head or acting head of household i.e. person no. 01. The head or acting head is the person who is the main decision-maker in the household. If two or more people are equal decision-makers, take the oldest person first. Write sideways.<br />______</div><p>F-02 Age</p> <div class="i1">Do not ask the question. Write the age in block provided based on answer from P-03<br />_ _ _</div><p>F-03 Sex</p> <div class="i1">Do not ask the question. Mark the appropriate box with an X based on answer from P-04<br />[] 1 Male<br />[] 2 Female</div><p>F-04 Respondent</p> <div class="i1">For each person in the household, indicate the number of the person who provided or responded to most questions applicable to that person. Enter person no. in the box.<br />_ _</div> South Africa 2007: Persons not residing in institutions [discrepancies: none] 00 NIU (not in universe) 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 This variable indicates the person number (within the household). IPUMS Month of birth <svar a="all" v="ZA07A402 ZA07A403 ZA07A404">P-02 Date of birth<br />What is (the person)'s date of birth?<br /><div class="i1">Date of birth is recorded as DD/MM/YYYY<br />DD is for day; MM is for month and YYYY is for year.<br />For any information that is not known, leave the box blank.<br />[Example omitted]<br />Day of birth: _ _<br />Month of birth: _ _<br />Year of birth: _ _ _ _</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 99 NIU (not in universe) This variable indicates the person's month of birth. IPUMS Year of birth <svar a="all" v="ZA07A402 ZA07A403 ZA07A404">P-02 Date of birth<br />What is (the person)'s date of birth?<br /><div class="i1">Date of birth is recorded as DD/MM/YYYY<br />DD is for day; MM is for month and YYYY is for year.<br />For any information that is not known, leave the box blank.<br />[Example omitted]<br />Day of birth: _ _<br />Month of birth: _ _<br />Year of birth: _ _ _ _</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] 0000 NIU (not in universe) 1887 1887 1889 1889 1893 1893 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 This variable indicates the person's year of birth. IPUMS Age <svar a="all" v="ZA07A405">P-03 Age<br />What is (the person)'s age in completed years?<br /><div class="i1">If age not known ask for an estimate of age. If no one is able to estimate, write 998.<br />For babies less than 1 year write 000 for age. For a person 7 years and 10 months write 007 for age.<br />Age (in years): _ _ _ _<br />Transcribe the answer to F-02 on the flap</div><br /></svar> South Africa 2007: All persons 000 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100 101 101 102 102 103 103 104 104 105 105 106 106 107 107 108 108 109 109 110 110 111 111 112 112 113 113 114 114 115 115 116 116 117 117 118 118 119 119 120 120 This variable indicates the person's age. IPUMS Sex <svar a="all" v="ZA07A406">P-04 Sex<br />Is (the person) male or female?<br /><div class="i1">Mark the appropriate box with an X.<br />[] 1 Male<br />[] 2 Female<br />Transcribe the answer to F-03 on the flap.</div><br /></svar> South Africa 2007: All persons 1 Male 2 Female This variable indicates the person's sex. IPUMS Usually stay in this house four nights a week <svar a="all" v="ZA07A407">P-05 Usually stay<br />Does (the person) usually live in this household for at least four nights a week and has done so over the last four weeks?<br /><div class="i1">Mark the appropriate box with an X.<br />[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: All persons 1 Yes 2 No This variable indicates whether the person usually stays in the place of enumeration four nights a week. IPUMS Stayed in this house last night <svar a="all" v="ZA07A408">P-06 Last night stay<br />Did (the person) stay in this household last night?<br /><div class="i1">Mark the appropriate box with an X.<br />[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: All persons 1 Yes 2 No This variable indicates whether the person stayed in this house the night previous to the enumeration. IPUMS Relationship <svar a="all" v="ZA07A409">P-07 Relationship<br />What is (the person)'s relationship to the head or acting head of the household?<br /><div class="i1">The head or acting head is the person listed in column 1 of the first questionnaire, if more than one questionnaire has been completed for this household.<br />[] 01 Head/acting head<br />[] 02 Husband/wife/partner<br />[] 03 Son/daughter<br />[] 04 Adopted son/daughter<br />[] 05 Stepchild<br />[] 06 Brother/sister<br />[] 07 Parent (mother/father)<br />[] 08 Parent-in-law<br />[] 09 Grand/great grandchild<br />[] 10 Son/daughter-in-law<br />[] 11 Brother/sister-in-law<br />[] 12 Grandmother/father<br />[] 13 Other relative<br />[] 14 Non-related person<br />_ _</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] 00 NIU (not in universe) 01 Head/acting head 02 Husband/wife/partner 03 Son/daughter 04 Adopted son/daughter 05 Stepchild 06 Brother/sister 07 Parent (mother/father) 08 Parent-in-law 09 Grand/great-grand child 10 Son/daughter-in-law 11 Brother/sister-in-law 12 Grandmother/father 13 Other relative 14 Non related person This variable indicates the person's relationship to the household head. IPUMS Marital status <svar a="all" v="ZA07A410">P-08 Marital status<br />What is (the person)'s present marital status?<br /><div class="i1">Write only one code per person.<br />If both civil/religious and traditional indicate civil/religious.<br />[] 1 Married civil/religious<br />[] 2 Married traditional/customary<br />[] 3 Polygamous marriage<br />[] 4 Living together as married partners<br />[] 5 Never married<br />[] 6 Widower/widow<br />[] 7 Separated<br />[] 8 Divorced<br />If 5 to 8, Go to P-10<br />_</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Married civil/religious 2 Married traditional/customary 3 Polygamous marriage 4 Living together as married partners 5 Never married 6 Widower/widow 7 Separated 8 Divorced This variable indicates the person's marital status. IPUMS Spouse person number <svar a="all" v="ZA07A411">P-09 Spouse<br />Who, in this household, is (the person)'s spouse or partner?<br /><div class="i1">[Question P-09 was asked of persons who are currently married, per question P-08.]<br />Write the person no. of the spouse or partner in the appropriate box. If the spouse does not reside in the household, write 98.<br />_ _</div><br /></svar> South Africa 2007: Married persons who are not residing in institutions [discrepancies: Type I trace; Type II none] 00 NIU (not in universe) 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 98 Spouse not in household This variable indicates the person number of the person's spouse. IPUMS Race/ethnicity <svar a="all" v="ZA07A412">P-10 Population group<br />How would (the person) describe himself/herself in terms of population group?<br /><div class="i1">Write code in the box.<br />[] 1 Black<br />[] 2 Coloured<br />[] 3 Indian or Asian<br />[] 4 White<br />_</div><br /></svar> South Africa 2007: All persons 1 Black African 2 Coloured 3 Indian or Asian 4 White This variable indicates the person's race/ethnicity. IPUMS Province of birth <svar a="all" v="ZA07A413">P-11 Province of birth<br />In which province in South Africa was (the person) born?<br /><div class="i1">Write code in the box. If the person was not born in South Africa, the code is 10.<br />[] 01 Western Cape<br />[] 02 Eastern Cape<br />[] 03 Northern Cape<br />[] 04 Free State<br />[] 05 KwaZulu-Natal<br />[] 06 North West<br />[] 07 Gauteng<br />[] 08 Mpumalanga<br />[] 09 Limpopo<br />[] 10 Outside RSA<br />[] 11 Do not know<br />_ _</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] 00 NIU (not in universe) 01 Western Cape 02 Eastern Cape 03 Northern Cape 04 Free State 05 Kwazulu-Natal 06 North West 07 Gauteng 08 Mpumalanga 09 Limpopo 10 Outside RSA 11 Respondent did not know 99 Unspecified This variable indicates the person's province of birth. IPUMS Person lived in this dwelling in October 2001 <svar a="all" v="ZA07A418">P-16 Five years ago<br />Was (the person) living in this dwelling in October 2001?<br /><div class="i1">Mark appropriate box with an X.<br />If 1 "Yes" or 3 "Born after October 2001", Go to P-21.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Born after October 2001</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No 3 Born after October 2001 This variable indicates whether the person lived in this dwelling in October 2001. IPUMS Month the person moved to this place <svar a="all" v="ZA07A419 ZA07A420">P-17 Period of movement<br />In which year and month did (the person) move to this dwelling?<br /><div class="i1">[Question P-17 was asked of persons who were born before October 2001and not living in the current dwelling in October 2001, per question P-16].<br />[Example omitted]<br />Month _ _<br />Year _ _ _ _</div><br /></svar> South Africa 2007: Persons who were not residing in institutions and did not live in the same dwelling 5 years ago [discrepancies: Type I 9.0%; Type II none] 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 99 NIU (not in universe) This variable indicates the month in which the person moved to the current residence. IPUMS Year the person moved to this place <svar a="all" v="ZA07A419 ZA07A420">P-17 Period of movement<br />In which year and month did (the person) move to this dwelling?<br /><div class="i1">[Question P-17 was asked of persons who were born before October 2001and not living in the current dwelling in October 2001, per question P-16].<br />[Example omitted]<br />Month _ _<br />Year _ _ _ _</div><br /></svar> South Africa 2007: Persons who were not residing in institutions and did not live in the same dwelling 5 years ago [discrepancies: Type I 9.0%; Type II none] 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 9999 NIU (not in universe) This variable indicates the year the person moved to the current residence. IPUMS Province of previous residence <svar a="all" v="ZA07A421">P-18 Province of previous residence<br />In which province did (the person) live before moving to this dwelling?<br /><div class="i1">[Question P-18 was asked of persons who were born before October 2001and not living in the current dwelling in October 2001, per question P-16].<br />Write code in the box. If the person moved from outside South Africa, write code 10.<br />[] 01 Western Cape<br />[] 02 Eastern Cape<br />[] 03 Northern Cape<br />[] 04 Free State<br />[] 05 KwaZulu-Natal<br />[] 06 North West<br />[] 07 Gauteng<br />[] 08 Mpumalanga<br />[] 09 Limpopo<br />[] 10 Outside RSA<br />[] 11 Do not know<br />_ _</div><br /></svar> South Africa 2007: Persons who did not live in the same dwelling 5 years ago and were not residing in institutions [discrepancies: none] 00 NIU (not in universe) 01 Western Cape 02 Eastern Cape 03 Northern Cape 04 Free State 05 Kwazulu-Natal 06 North West 07 Gauteng 08 Mpumalanga 09 Limpopo 10 Outside RSA 11 Respondent did not know 99 Unspecified This variable indicates the province of previous residence. IPUMS Any disability <svar a=" ZA07A424 " v="ZA07A424 ZA07A570">P-21 Disability<br />Does (the person) have any kind of disability?<br /><div class="i1">Mark appropriate box with an X<br />If 2 "No" or 3 "Do not know" Go to P-24.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons not residing in institutions NIU (not in universe) 1 Yes 2 No This variable indicates whether the person suffers from any disability. IPUMS Disability: sight <svar a=" ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A570" v="ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A431 ZA07A570">P-22 Disability type<br />What type(s) of disability does (the person) have?<br /><div class="i1">[Question P-22 was asked of persons who had some kind of disability, per question P-21.]<br />Mark any that apply with an X.<br />Multiple disabilities are indicated by marking more than one selection.<br /><span class="ital">Read out</span>:<br />[] 1 Sight (blind/severe visual limitation<br />[] 2 Hearing (deaf, profoundly hard of hearing)<br />[] 3 Communication (speech impairment)<br />[] 4 Physical (needs wheelchair, crutches, etc.)<br />[] 5 Intellectual (serious difficulties in learning)<br />[] 6 Emotional (behavioural, psychological)</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the person has a sight related disability. IPUMS Disability: hearing <svar a=" ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A570" v="ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A431 ZA07A570">P-22 Disability type<br />What type(s) of disability does (the person) have?<br /><div class="i1">[Question P-22 was asked of persons who had some kind of disability, per question P-21.]<br />Mark any that apply with an X.<br />Multiple disabilities are indicated by marking more than one selection.<br /><span class="ital">Read out</span>:<br />[] 1 Sight (blind/severe visual limitation<br />[] 2 Hearing (deaf, profoundly hard of hearing)<br />[] 3 Communication (speech impairment)<br />[] 4 Physical (needs wheelchair, crutches, etc.)<br />[] 5 Intellectual (serious difficulties in learning)<br />[] 6 Emotional (behavioural, psychological)</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the person has a hearing related disability. IPUMS Disability: communication <svar a=" ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A570" v="ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A431 ZA07A570">P-22 Disability type<br />What type(s) of disability does (the person) have?<br /><div class="i1">[Question P-22 was asked of persons who had some kind of disability, per question P-21.]<br />Mark any that apply with an X.<br />Multiple disabilities are indicated by marking more than one selection.<br /><span class="ital">Read out</span>:<br />[] 1 Sight (blind/severe visual limitation<br />[] 2 Hearing (deaf, profoundly hard of hearing)<br />[] 3 Communication (speech impairment)<br />[] 4 Physical (needs wheelchair, crutches, etc.)<br />[] 5 Intellectual (serious difficulties in learning)<br />[] 6 Emotional (behavioural, psychological)</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person has a communication disability. IPUMS Disability: physical <svar a=" ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A570" v="ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A431 ZA07A570">P-22 Disability type<br />What type(s) of disability does (the person) have?<br /><div class="i1">[Question P-22 was asked of persons who had some kind of disability, per question P-21.]<br />Mark any that apply with an X.<br />Multiple disabilities are indicated by marking more than one selection.<br /><span class="ital">Read out</span>:<br />[] 1 Sight (blind/severe visual limitation<br />[] 2 Hearing (deaf, profoundly hard of hearing)<br />[] 3 Communication (speech impairment)<br />[] 4 Physical (needs wheelchair, crutches, etc.)<br />[] 5 Intellectual (serious difficulties in learning)<br />[] 6 Emotional (behavioural, psychological)</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the person has a physical disability. IPUMS Disability: intellectual <svar a=" ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A570" v="ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A431 ZA07A570">P-22 Disability type<br />What type(s) of disability does (the person) have?<br /><div class="i1">[Question P-22 was asked of persons who had some kind of disability, per question P-21.]<br />Mark any that apply with an X.<br />Multiple disabilities are indicated by marking more than one selection.<br /><span class="ital">Read out</span>:<br />[] 1 Sight (blind/severe visual limitation<br />[] 2 Hearing (deaf, profoundly hard of hearing)<br />[] 3 Communication (speech impairment)<br />[] 4 Physical (needs wheelchair, crutches, etc.)<br />[] 5 Intellectual (serious difficulties in learning)<br />[] 6 Emotional (behavioural, psychological)</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person has an intellectual disability. IPUMS Disability: emotional <svar a=" ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A570" v="ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A431 ZA07A570">P-22 Disability type<br />What type(s) of disability does (the person) have?<br /><div class="i1">[Question P-22 was asked of persons who had some kind of disability, per question P-21.]<br />Mark any that apply with an X.<br />Multiple disabilities are indicated by marking more than one selection.<br /><span class="ital">Read out</span>:<br />[] 1 Sight (blind/severe visual limitation<br />[] 2 Hearing (deaf, profoundly hard of hearing)<br />[] 3 Communication (speech impairment)<br />[] 4 Physical (needs wheelchair, crutches, etc.)<br />[] 5 Intellectual (serious difficulties in learning)<br />[] 6 Emotional (behavioural, psychological)</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person has an emotional disability. IPUMS Disability prevents from life activities <svar a=" ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A570" v="ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A431 ZA07A570">P-22 Disability type<br />What type(s) of disability does (the person) have?<br /><div class="i1">[Question P-22 was asked of persons who had some kind of disability, per question P-21.]<br />Mark any that apply with an X.<br />Multiple disabilities are indicated by marking more than one selection.<br /><span class="ital">Read out</span>:<br />[] 1 Sight (blind/severe visual limitation<br />[] 2 Hearing (deaf, profoundly hard of hearing)<br />[] 3 Communication (speech impairment)<br />[] 4 Physical (needs wheelchair, crutches, etc.)<br />[] 5 Intellectual (serious difficulties in learning)<br />[] 6 Emotional (behavioural, psychological)</div><br /></svar></p> <p><svar a="all" v="ZA07A431">P-23 Disability intensity<br />Does the disability seriously prevent (the person) from full participation in life activities (such as education, work, social life, etc.)?<br /><div class="i1">[Question P-23 was asked of persons who had some kind of disability, per question P-21.]<br />Mark appropriate box with an X.<br />[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Persons who have a disability [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the person's disability prevents them from engaging in life activities. IPUMS Receive government/welfare grant <svar a=" ZA07A432" v="ZA07A432 ZA07A571">P-24 Social grant<br />Does (the person) receive any social / government grant?<br /><div class="i1">Mark appropriate box with an X<br />If 2 "No" or 3 "Do not know" Go to P-26.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons not residing in institutions NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the person receives a governmental/welfare grant. IPUMS Social grant - old age pension <svar a="all" v="ZA07A433 ZA07A434 ZA07A435 ZA07A436 ZA07A437 ZA07A438 ZA07A439 ZA07A571">P-25 Type of social grant<br />What type(s) of social /government grant does (the person) receive?<br /><div class="i1">[Question P-25 was asked of persons who received social/government grant, per question P-24.]<br />Mark any that apply with an X.<br />[] 1 Old age pension<br />[] 2 Disability grant<br />[] 3 Child support grant (linked to a child)<br />[] 4 Care dependency grant<br />[] 5 Foster care grant<br />[] 6 Grant in aid<br />[] 7 Social relief</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person receives a social grant in the form of an old age pension. IPUMS Social grant - disability grant <svar a="all" v="ZA07A433 ZA07A434 ZA07A435 ZA07A436 ZA07A437 ZA07A438 ZA07A439 ZA07A571">P-25 Type of social grant<br />What type(s) of social /government grant does (the person) receive?<br /><div class="i1">[Question P-25 was asked of persons who received social/government grant, per question P-24.]<br />Mark any that apply with an X.<br />[] 1 Old age pension<br />[] 2 Disability grant<br />[] 3 Child support grant (linked to a child)<br />[] 4 Care dependency grant<br />[] 5 Foster care grant<br />[] 6 Grant in aid<br />[] 7 Social relief</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person receives a social grant for disability (disability grant). IPUMS Social grant - child support grant <svar a="all" v="ZA07A433 ZA07A434 ZA07A435 ZA07A436 ZA07A437 ZA07A438 ZA07A439 ZA07A571">P-25 Type of social grant<br />What type(s) of social /government grant does (the person) receive?<br /><div class="i1">[Question P-25 was asked of persons who received social/government grant, per question P-24.]<br />Mark any that apply with an X.<br />[] 1 Old age pension<br />[] 2 Disability grant<br />[] 3 Child support grant (linked to a child)<br />[] 4 Care dependency grant<br />[] 5 Foster care grant<br />[] 6 Grant in aid<br />[] 7 Social relief</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person receives a social grant for child support (child support grant). IPUMS Social grant - care dependency grant <svar a="all" v="ZA07A433 ZA07A434 ZA07A435 ZA07A436 ZA07A437 ZA07A438 ZA07A439 ZA07A571">P-25 Type of social grant<br />What type(s) of social /government grant does (the person) receive?<br /><div class="i1">[Question P-25 was asked of persons who received social/government grant, per question P-24.]<br />Mark any that apply with an X.<br />[] 1 Old age pension<br />[] 2 Disability grant<br />[] 3 Child support grant (linked to a child)<br />[] 4 Care dependency grant<br />[] 5 Foster care grant<br />[] 6 Grant in aid<br />[] 7 Social relief</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person receives a social grant for care of disabled children (care dependency grant). IPUMS Social grant - foster care grant <svar a="all" v="ZA07A433 ZA07A434 ZA07A435 ZA07A436 ZA07A437 ZA07A438 ZA07A439 ZA07A571">P-25 Type of social grant<br />What type(s) of social /government grant does (the person) receive?<br /><div class="i1">[Question P-25 was asked of persons who received social/government grant, per question P-24.]<br />Mark any that apply with an X.<br />[] 1 Old age pension<br />[] 2 Disability grant<br />[] 3 Child support grant (linked to a child)<br />[] 4 Care dependency grant<br />[] 5 Foster care grant<br />[] 6 Grant in aid<br />[] 7 Social relief</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person receives a social grant for providing foster care to children from orphanages (foster care grant). IPUMS Social grant - grant in aid <svar a="all" v="ZA07A433 ZA07A434 ZA07A435 ZA07A436 ZA07A437 ZA07A438 ZA07A439 ZA07A571">P-25 Type of social grant<br />What type(s) of social /government grant does (the person) receive?<br /><div class="i1">[Question P-25 was asked of persons who received social/government grant, per question P-24.]<br />Mark any that apply with an X.<br />[] 1 Old age pension<br />[] 2 Disability grant<br />[] 3 Child support grant (linked to a child)<br />[] 4 Care dependency grant<br />[] 5 Foster care grant<br />[] 6 Grant in aid<br />[] 7 Social relief</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person receives a grant for people who receive other grants and are unable to care for themselves or have someone looking after them on a full time basis (grant in aid). IPUMS Social grant - social relief <svar a="all" v="ZA07A433 ZA07A434 ZA07A435 ZA07A436 ZA07A437 ZA07A438 ZA07A439 ZA07A571">P-25 Type of social grant<br />What type(s) of social /government grant does (the person) receive?<br /><div class="i1">[Question P-25 was asked of persons who received social/government grant, per question P-24.]<br />Mark any that apply with an X.<br />[] 1 Old age pension<br />[] 2 Disability grant<br />[] 3 Child support grant (linked to a child)<br />[] 4 Care dependency grant<br />[] 5 Foster care grant<br />[] 6 Grant in aid<br />[] 7 Social relief</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person receives a social grant for people who cannot meet basic needs (social relief). IPUMS School Attendance <svar a="all" v="ZA07A440">P-26 School attendance<br />Does (the person) presently attend an educational institution?<br /><div class="i1"><span class="ital">Read out</span>: Attendance includes all part-time and full-time studies, whether in person or as a distance learner, as well as home schooling.<br />Mark appropriate box with an X.<br />If 2 "No" Go to P-29.<br />[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether or not the person attends an educational institution. IPUMS Educational institution <svar a="all" v="ZA07A441">P-27 Educational institution<br />Which of the following educational institutions does (the person) attend?<br /><div class="i1">[Question P-27 was asked of persons who presently attend an educational institution, per question P-26.]<br />Write code in the box.<br /><span class="ital">Read out</span>:<br />[] 1 Pre-school<br />[] 2 Primary school<br />[] 3 Secondary school<br />[] 4 College<br />[] 5 University/university of technology/Technikon<br />[] 6 Adult Basic Education and Training<br />[] 7 Other<br />_</div><br /></svar> South Africa 2007: Persons attending school who are not residing in institutions [discrepancies: none] 1 Pre-school 2 Primary school 3 Secondary school 4 College 5 University/university of technology/technikon 6 Adult education 7 Other 9 NIU (not in universe) This variable indicates the type of educational institution the person attends. IPUMS Private/public school <svar a="all" v="ZA07A442">P-28 Public or independent institution<br />Is the institution (the person) attends public (government) or independent (private)?<br /><div class="i1">[Question P-28 was asked of persons who presently attend an educational institution, per question P-26.]<br />Write code in the box.<br />[] 1 Public<br />[] 2 Independent<br />[] 3 Do not know<br />_</div><br /></svar> South Africa 2007: Persons attending school who are not residing in institutions [discrepancies: none] 1 Public (government) 2 Private 9 NIU (not in universe) This variable indicates whether the person attends a private or public school. IPUMS Highest level of education <svar a="all" v="ZA07A443">P-29 Level of education<br />What is the highest level of education that (the person) has completed?<br /><div class="i1">For a person with grade 12, probe whether he/she has a university exemption or not.<br />For a person with a certificate or a diploma, probe whether he/she has grade 12 (std 10) or not.<br />Write code in the box.<br />[] 00 Grade 0<br />[] 01 Grade 1<br />[] 02 Grade 2<br />[] 03 Grade 3/ Std 1/ ABET 1<br />[] 04 Grade 4/ Std 2<br />[] 05 Grade 5/ Std 3/ ABET 2<br />[] 06 Grade 6/ Std 4<br />[] 07 Grade 7/ Std 5/ ABET 3<br />[] 08 Grade 8/ Std 6<br />[] 09 Grade 9/ Std 7/ ABET 4<br />[] 10 Grade 10/Std 8/ NTCI<br />[] 11 Grade 11/ Std 9/ NTCII<br />[] 12 Attended Grade 12, but not completed Grade 12<br />[] 13 Grade 12 / Std 10/ NTCIII (without university exemption)<br />[] 14 Grade 12/ Std 10 (with university exemption)<br />[] 15 Certificate with [less than] Std 10/Gr.12<br />[] 16 Diploma with [less than] Std 10/Gr.12<br />[] 17 Certificate with Std 10/Gr.12<br />[] 18 Diploma with Std 10 /Gr.12<br />[] 19 Bachelors degree<br />[] 20 BTech<br />[] 21 Post graduate diploma<br />[] 22 Honours degree<br />[] 23 Higher degree (Masters/PhD)<br />[] 24 No schooling<br />[] 98 Out of scope (children under five<br />years of age)<br />_ _</div><br /></svar> South Africa 2007: Persons aged 5+ who are not residing in institutions [discrepancies: none] 00 Grade 0 01 Grade 1 02 Grade 2 03 Grade 3/std1/ABET 1 04 Grade 4/std 2 05 Grade 5/std 3/ ABET 2 06 Grade 6/std 4 07 Grade 7/std 5 / ABET 3 08 Grade 8/std 6 09 Grade 9/std 7/ABET 4 10 Grade 10/std 8/NTC I 11 Grade 11/std 9/NTC II 12 Attended grade 12, but not completed grade 12 13 Grade 12/std 10/NTC III (without university exemption) 14 Grade 12/std 10 (with university exemption) 15 Certificate with less than std 10/grade12 16 Diploma with less than std 10/grade 12 17 Certificate with std 10/grade 12 18 Diploma with std 10/grade 12 19 Bachelors degree 20 BTech 21 Post graduate diploma 22 Honours degree 23 Higher degree (Master/Phd) 24 No schooling 98 Unspecified 99 NIU (not in universe) This variable indicates the highest level of education the person has completed. IPUMS Run or do any kind of business, big or small <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p>P-30 <span class="em">Employment status</span></p> <p><svar a="all" v="ZA07A444"><div class="i1">P-30a In the last 7 days, did (the person) run or do any kind of business, big or small, for himself/herself or with one or more partners even for only one hour?</div><br /><div class="i2">Examples: Selling things, making things for sale, repairing things, guarding cars, brewing beer, hairdressing, creche business, taxi or other transport business, having a legal or medical practice, etc.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person has run or done any kind of business, big or small, in the seven days prior to enumeration. IPUMS Worked for a wage, salary, commission or payment in-kind <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p>P-30 <span class="em">Employment status</span></p> <p><svar a="all" v="ZA07A445"><div class="i1">P-30b In the last 7 days, did (the person) do any work for a wage, salary, commission or payment in kind (excluding domestic worker) even for only one hour?</div><br /><div class="i2">Examples: a regular job, contract, casual or piece work for pay, work in exchange for food or housing.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person worked for a wage, salary, commission or payment in-kind during the seven days prior to enumeration. IPUMS Worked as domestic worker for a wage, salary, or payment in-kind <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p>P-30 <span class="em">Employment status</span></p> <p><svar a="all" v="ZA07A446"><div class="i1">P-30c In the last 7 days, did (the person) do any work as a domestic worker for a wage, salary or payment in kind even for only one hour?</div><br /><div class="i2">[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person worked as domestic worker for a wage, salary, or payment in-kind during the seven days prior to enumeration. IPUMS Helped without pay in a household business <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p>P-30 <span class="em">Employment status</span></p> <p><svar a="all" v="ZA07A447"><div class="i1">P-30d In the last 7 days, did (the person) help unpaid in a household business of any kind even for only one hour?<br />Examples: Help to sell things, make things for sale or exchange, doing the accounts, cleaning up for the business, etc. Do not count normal housework</div><br /><div class="i2">[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person helped without pay in a household business of any kind during the 7 days prior to enumeration. IPUMS Worked on household's plot, farm, food garden, cattle post or kraal <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p>P-30 <span class="em">Employment status</span></p> <p><svar a="all" v="ZA07A448"><div class="i1">P-30e In the last 7 days, did (the person) do any work on his/her own or the household's plot, farm, food garden, cattle post or kraal, or help in growing farm produce or in looking after animals for the household even for only one hour?</div><br /><div class="i2">Examples: Ploughing, harvesting, looking after livestock.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person worked on his/her own or the household's plot, farm, food garden, cattle post or kraal, or helped in growing farm produce or in looking after animals during the 7 days prior to enumeration. IPUMS Helped with construction/repair of own home, plot, cattle post or business <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p>P-30 <span class="em">Employment status</span></p> <p><svar a="all" v="ZA07A449"><div class="i1">P-30f In the last 7 days, did (the person) do any construction or major repair work on his/her own home, plot, cattle post or business even for only one hour?</div><br /><div class="i2">[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person helped with construction or major repair work on his/her own home, plot, cattle post or business during the seven days prior to enumeration. IPUMS Caught fish, wild animals or other food for sale or household consumption <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p>P-30 <span class="em">Employment status</span></p> <p><svar a="all" v="ZA07A450"><div class="i1">P-30g In the last 7 days, did (the person) catch any fish, prawns, shell fish, wild animals either as food for sale or for household use, even for only one hour?</div><br /><div class="i2">If 1 "Yes" to any of P-30a to P-30g, Go to P-36.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person caught fish, prawns, shells, wild animals or other food for sale or household consumption during the 7 days prior to enumeration. IPUMS Have a job, business, or other economic or farming activity to return to <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p><svar a="ZA07A451" v="ZA07A451 ZA07A568 ZA07A569">P-31 Temporary absence from work<br />Even though (the person) did not do any of these activities in the last seven days, does he/she have a job, business, or other economic or farming activity that he/she will definitely return to?<br /><div class="i1">[Question P-31 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />For agricultural activities, the off season in agriculture is not a temporary absence.<br />If 1 "Yes" Go to P-36.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ who have not worked at least one hour in the last 7 days [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the person had a job, business, or other economic or farming activity to return to if they had not worked during the 7 days prior to enumeration. IPUMS Reason not working <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p><svar a="ZA07A452" v="ZA07A452 ZA07A568 ZA07A569">P-32 Reasons for not working<br />Why did (the person) not work during the past seven days?<br /><div class="i1">[Question P-32 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />[] 01 Has found a job, but is only starting at a definite date in the future<br />[] 02 Scholar/student and prefers not to work<br />[] 03 Housewife/homemaker and prefers not to work<br />[] 04 Retired and prefers not to seek formal work<br />[] 05 Invalid, ill, disabled or unable to work (handicapped)<br />[] 06 Too young or too old to work<br />[] 07 Seasonal worker, e.g. fruit picker, wool-shearer<br />[] 08 Lack of skills or qualifications for available jobs<br />[] 09 Cannot find work<br />[] 10 Cannot find suitable work (salary, location of work or conditions not satisfactory)<br />[] 11 Contract worker, e.g. mine worker resting according to contract<br />[] 12 Retrenched<br />[] 13 Other reason<br />Write code in the box.<br />_ _</div><br /></svar> South Africa 2007: Persons age 15 to 74 who have not worked in the last 7 days and who do not have a job they will return to [discrepancies: none] 00 NIU (not in universe) 01 Has found a job, but is only starting at a definite date in the future 02 Scholar/student and prefers not to work 03 Housewife/homemaker and prefers not to work 04 Retired and prefers not to seek formal work 05 Illness, invalid, disabled or unable to work (handicapped) 06 Too young or too old to work 07 Seasonal worker, e.g. fruit picker, wool-shearer 08 Lack of skills or qualifications for available jobs 09 Cannot find work 10 Cannot find suitable work (salary, location of work or conditions not satisfactory) 11 Contract worker, e.g. mine worker resting according to contract 12 Retrenched 13 Other reason 99 Unknown This variable indicates the person's reason for not working. IPUMS Availability for work <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p><svar a="ZA07A453" v="ZA07A453 ZA07A568 ZA07A569">P-33 Availability for work<br />If a suitable job is offered, how soon can (the person) start work?<br /><div class="i1">[Question P-33 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />[] 1 Within a week<br />[] 2 Within two weeks<br />[] 3 Within four weeks<br />[] 4 More than four weeks from now<br />[] 5 Not interested<br />[] 6 Not able (health or disability)<br />[] 7 Do not know<br />Write code in the box.<br />_</div><br /></svar> South Africa 2007: Persons age 15 to 74 who have not worked in the last 7 days and who do not have a job they will return to [discrepancies: none] NIU (not in universe) 1 Within a week 2 Within two weeks 3 Within four weeks 4 More than four weeks from now 5 Not interested 6 Not able (health disability) 7 Respondent did not know 9 Unknown This variable indicates how soon the person could start working if a suitable job were offered. IPUMS Looked for work <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p><svar a="ZA07A454" v="ZA07A454 ZA07A568">P-34 Active steps seeking work<br />During the past four weeks, has (the person) taken any action to look for any kind of work?<br /><div class="i1">[Question P-34 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />Mark appropriate box with an X.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ who are available for work [discrepancies: none] NIU (not in universe) 1 Yes 2 No 3 Respondent did not know 9 Unknown This variable indicates whether persons who were not working had looked for work during the four weeks prior to the enumeration. IPUMS Start any kind of business <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p><svar a="ZA07A455" v="ZA07A455 ZA07A568">P-35 Active steps seeking work<br />During the past four weeks, has (the person) taken any action to start any kind of business?<br /><div class="i1">[Question P-35 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />If P-34 and P-35 completed Go to P-40<br />Mark appropriate box with an X.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15+ who are available for work [discrepancies: none] NIU (not in universe) 1 Yes 2 No 3 Respondent did not know 9 Unknown This variable indicates whether the person who was not working had taken action to start any kind of business during the four weeks prior to enumeration. IPUMS Work status <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p><svar a="all" v="ZA07A456">P-36 Work status<br />How can one describe (the person)'s main activity or work status best?<br /><div class="i1">If yes to any of P-30a to P-30g or P-31 [who were either working during the last seven days or had work that the persons could definitely return to.] <br />Write code in the box.<br /><span class="ital">Read out</span> :<br />[] 1 Paid employee<br />[] 2 Paid family worker<br />[] 3 Self-employed<br />[] 4 Employer<br />[] 5 Unpaid family worker<br />_</div><br /></svar> South Africa 2007: Persons age 15 to 74 who have worked in the last 7 days or who have regular work to which they will return and who do not live in institutions [discrepancies: none] NIU (not in universe) 1 Paid employee 2 Paid family worker 3 Self-employed 4 Employer 5 Unpaid family worker 9 Unknown This variable indicates the person's main activity or work status. IPUMS Work sector <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p><svar a="all" v="ZA07A457">P-37 Business type<br />Is the organisation/ company / business /enterprise/branch where (the person) works in the formal or informal sector?<br /><div class="i1">[Question P-37 was asked of persons who were either working during the last seven days or had work that the persons could definitely return to, person questions P-30a to P-30g and P-31.]<br />Formal sector employment is where the employer (institution, business) is registered (i.e. has a tax number) and informal is when it is not registered.<br />Mark appropriate box with an X.<br />[] 1 In the formal sector<br />[] 2 In the informal sector (including domestic work)<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15 to 74 who have worked in the last 7 days or who have regular work to which they will return and who do not live in institutions [discrepancies: none] NIU (not in universe) 1 In the formal sector 2 In the informal sector (including domestic work) 3 Respondent did not know 9 Unknown This variable indicates whether the person works in the formal or informal sector. IPUMS Occupation, 3 digits <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p><svar a="all" v="ZA07A458 ZA07A588">P-38 Occupation<br />What is the main occupation of (the person) in this workplace?<br /><div class="i1">[Question P-38 was asked of persons who were either working during the last seven days or had work that the persons could definitely return to, person questions P-30a to P-30g and P-31.]<br />For example: street vendor, primary school teacher, domestic worker etc.<br />Write in capital letters.<br />______</div><br /></svar> South Africa 2007: Persons age 15 to 74 who have worked in the last 7 days or who have regular work to which they will return and who do not live in institutions [discrepancies: none] 011 Armed forces 111 Legislators 112 Senior government officials 113 Traditional chiefs and heads of villages 114 Senior officials of special-interest organisations 121 Directors and chief executives 122 Production and operations department managers 123 Other department managers 129 Other department managers 131 General managers 139 General managers, n.e.c. 211 Physicists, chemists and related professionals 212 Mathematicians, statisticians and related professionals 213 Computing professionals 214 Architects, engineers and related professionals 219 Science and engineering professionals, not elsewhere classified 221 Life science professionals 222 Health professionals (except nursing) 223 Nursing and midwifery professionals 231 College, university and higher education teaching professionals 232 Secondary education teaching professionals 233 Primary and pre-primary education teaching professionals 234 Special education teaching professionals 235 Other teaching professionals 241 Business professionals 242 Legal professionals 243 Archivists, librarians and related information professionals 244 Social science and related professionals 245 Writers and creative or performing artists 246 Religious professionals 249 Other professionals, not elsewhere classified 311 Physical and engineering science technicians 312 Computer associate professionals 313 Optical and electronic equipment operators 314 Ship and aircraft controllers and technicians 315 Safety and quality inspectors 321 Life science technicians and related associate professionals 322 Modern health associate professionals (except nursing) 323 Nursing and midwifery associate professionals 324 Traditional medicine practitioners and faith healers 331 Primary education teaching associate professionals 332 Pre-primary education teaching associate professionals 333 Special education teaching associate professionals 334 Other teaching associate professionals 339 Other teaching associate professionals 341 Finance and sales associate professionals 342 Business services agents and trade brokers 343 Administrative associate professionals 344 Customs, tax and related government associate professionals 345 Police inspectors and detectives 346 Social work associate professionals 347 Artistic, entertainment and sports associate professionals 348 Religious associate professionals 411 Secretaries and keyboard-operating clerks 412 Numerical clerks 413 Material-recording and transport clerks 414 Library, mail and related clerks 419 Other office clerks 421 Cashiers, tellers and related clerks 422 Client information clerks 429 Customer service clerks, not elsewhere classified 511 Travel attendants and related workers 512 Housekeeping and restaurant services workers 513 Personal care and related workers 514 Other personal services workers 515 Astrologers, fortune-tellers and related workers 516 Protective services workers 521 Fashion and other models 522 Shop salespersons and demonstrators 523 Stall and market salespersons 611 Market gardeners and crop growers 612 Market-oriented animal producers and related workers 613 Market-oriented crop and animal producers 614 Forestry and related workers 615 Fishery workers, hunters and trappers 621 Subsistence agricultural and fishery workers 711 Miners, shotfirers, stone cutters and carvers 712 Building frame and related trades workers 713 Building finishers and related trades workers 714 Painters, building structure cleaners and related trades workers 719 Extraction and building trades workers, not elsewhere classified 721 Metal moulders, welders, sheet-metal workers, structural-metal preparers, and related trades workers 722 Blacksmiths, tool-makers and related trades workers 723 Machinery mechanics and fitters 724 Electrical and electronic equipment mechanics and fitters 729 Electrical and electronic equipment mechanics and fitters 731 Precision workers in metal and related materials 732 Potters, glass-makers and related trades workers 733 Handicraft workers in wood, textile, leather and related materials 734 Printing and related trades workers 741 Food processing and related trades workers 742 Wood treaters, cabinet-makers and related trades workers 743 Textile, garment and related trades workers 744 Pelt, leather and shoemaking trades workers 749 Other craft and related workers, not elsewhere classified 811 Mining- and mineral-processing-plant operators 812 Metal-processing-plant operators 813 Glass, ceramics and related plant operators 814 Wood-processing- and papermaking-plant operators 815 Chemical-processing-plant operators 816 Power-production and related plant operators 817 Automated-assembly-line and industrial-robot operators 821 Metal- and mineral-products machine operators 822 Chemical-products machine operators 823 Rubber- and plastic-products machine operators 824 Wood-products machine operators 825 Printing-, binding- and paper-products machine operators 826 Textile-, fur- and leather-products machine operators 827 Food and related products machine operators 828 Assemblers 829 Other machine operators and assemblers 831 Locomotive-engine drivers and related workers 832 Motor-vehicle drivers 833 Agricultural and other mobile-plant operators 834 Ships' deck crews and related workers 839 Drivers and mobile plant operators, not elsewhere classified 911 Street vendors and related workers 912 Shoe cleaning and other street services elementary occupations 913 Domestic and related helpers, cleaners and launderers 914 Building caretakers, window and related cleaners 915 Messengers, porters, doorkeepers and related workers 916 Garbage collectors and related labourers 919 Sales and service elementary workers, not elsewhere classified 921 Agricultural, fishery and related labourers 931 Mining and construction labourers 932 Manufacturing labourers 933 Transport labourers and freight handlers 939 Laborers, not elsewhere classified 998 Unknown 999 NIU (not in universe) This variable indicates the person's 3 digit occupation. IPUMS Industry, 3 digit <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p><svar v="ZA07A459 ZA07A460">P-39 Industry<br /></svar> <br /><svar a="all" v="ZA07A459"><div class="i1">P-39a What is the name of (the person)'s place of work or company.</div><br /><div class="i2">[Question P-39a was asked of persons who were either working during the last seven days or had work that the persons could definitely return to, person questions P-30a to P-30g and P-31.]<br />______</div><br /></svar></p> <p><svar a="all" v="ZA07A460 ZA07A589"><div class="i1">P-39b What is the main business/function of the company that (the person) works (main economic activity) for?</div><br /><div class="i2">[Question P-39b was asked of persons who were either working during the last seven days or had work that the persons could definitely return to, person questions P-30a to P-30g and P-31.]<br />For example: gold mining, road construction, supermarket, police service, healthcare, hairdressing, banking, or subsistence farming if self-employed.<br />Write the main industry, main economic activity, product, goods or service in capital letters.<br />______</div><br /></svar> South Africa 2007: Persons age 15 to 74 who have worked in the last 7 days or who have regular work to which they will return and who do not live in institutions [discrepancies: none] 000 NIU (not in universe) 010 Private households with employees 020 Extraterritorial organizations 030 Representatives of foreign governments 111 Grain and staple farming 112 Vegetable farming 113 Nursery farming 114 Fruit farming 115 Vineyards 116 Sugar cane farming 117 Cotton farming 118 Other crop farming 121 Cattle farming 122 Chicken farming 123 Horse farming 124 Dairy farming 125 Sheep farming 126 Ostrich farming 127 Goat farming 128 Unspecified animal farming 129 Other animal farming 130 Fertilizer manufacturing 141 Forestry 142 Logging 151 Ocean fishing 152 Inland fishing 153 Fish farms 160 Mixed farming 171 Animal boarding without health care 172 Pest control 173 Clearing land for agriculture 174 Providing agricultural machinery and crew 175 Harvesting crops 176 Landscaping and gardening 177 Herd testing and insemination 178 Other agricultural services 181 Game farming 182 Hunting 183 Game breeding 190 Unspecified farming 210 Mining of coal and lignite 221 Extraction of crude petroleum and natural gas and services incidental to, excluding surveying 230 Mining of gold and uranium ore 240 Mining of gold and uranium ore 241 Mining of iron ore 242 Mining of non-ferrous metal ores, except gold and uranium (not in m 251 Stone quarrying, clay and sand-pits 252 Mining of diamonds (including alluvial diamonds) 253 Mining and quarrying n.e.c. 290 Services activities incidental to mining of minerals 301 Production, processing and preserving of meat, fish, fruit, vegetables, oils and fats 302 Manufacture of dairy products 303 Manufacture of grain mill products, starches and starch products and prepared animal feeds 304 Manufacture of other food products 305 Manufacture of beverages 306 Manufacture of tobacco products 311 Spinning, weaving and finishing of textiles 312 Manufacture of other textiles 313 Manufacture of knitted and crocheted fabrics and articles 314 Manufacture of wearing apparel, except fur apparel 315 Dressing and dyeing of fur; manufacture of articles of fur 316 Tanning and dressing of leather; manufacture of luggage, handbags, saddlery and harness 317 Manufacture of footwear 321 Sawmilling and planing of wood 322 Manufacture of products of wood, cork, straw and plaiting materials 323 Manufacture of paper and paper products 324 Publishing 325 Printing and service activities related to printing 326 Reproduction of recorded media 331 Manufacture of coke oven products 332 Petroleum refineries/synthesizers 333 Processing of nuclear fuel 334 Manufacture of basic chemicals 335 Manufacture of other chemical products 337 Manufacture of rubber products 338 Manufacture of plastic products 341 Manufacture of glass and glass products 342 Manufacture of non-metallic mineral products n.e.c. 351 Manufacture of basic iron and steel 352 Manufacture of basic precious and non-ferrous metals 353 Casting of metals 354 Manufacture of structural metal products, tanks, reservoirs and steam generators 355 Manufacture of other fabricated metal products; metalwork service activities 356 Manufacture of general purpose machinery 357 Manufacture of special purpose machinery 358 Manufacture of household appliances 359 Manufacture of office, accounting and computing machinery 361 Manufacture of electric motors, generators and transformers 362 Manufacture of electricity distribution and control apparatus 363 Manufacture of insulated wire and cable 364 Manufacture of accumulators, primary cells and primary batteries 365 Manufacture of electric lamps and lighting equipment 366 Manufacture of other electrical equipment n.e.c. 371 Manufacture of electronic valves and tubes and other electric components 372 Manufacture of television and radio transmitters and apparatus for line telephony and line telegraphy 373 Manufacture of television and radio receivers, sound or video recording or reproducing apparatus and associated goods 374 Manufacture of medical appliances and instruments and appliances for measuring, checking, testing, navigating and other purposes, except optical instruments 375 Manufacture of optical instruments and photographic equipment 376 Manufacture of watches and clocks 381 Manufacture of motor vehicles 382 Manufacture of bodies (coachwork) for motor vehicles, manufacture of trailers and semi-trailers 383 Manufacture of parts and accessories for motor vehicles and their engines 384 Building and repairing of ships and boats 385 Manufacture of railway and tramway locomotives and rolling stock 386 Manufacture of aircraft and space craft 387 Manufacture of transport equipment n.e.c. 391 Manufacture of furniture; manufacturing n.e.c.; recycling 392 Manufacture of furniture 395 Recycling n.e.c. 411 Production, collection and distribution of electricity 412 Manufacture of gas, distribution of gaseous fuels through mains 413 Steam and hot water supply 420 Collection, purification and distribution of water 501 Site preparation 502 Building of complete constructions or parts thereof; civil engineering 503 Building installation 504 Building completion 505 Renting of construction or demolition equipment with operators 611 Wholesales trade on a fee or contract basis 612 Wholesale trade in agricultural raw materials, livestock, food, beverages and tobacco 613 Wholesale trade in household goods 614 Wholesale trade in non-agricultural intermediate products, waste and scrap 615 Wholesale trade in machinery, equipment and supplies 619 Other wholesale trade 621 Non-specialized retail trade in stores 622 Retail trade in food, beverages and tobacco in specialized stores 623 Other retail trade in new goods in specialized stores 624 Retail trade in second-hand goods in stores 625 Retail trade not in stores 626 Repair of personal and household goods 631 Sale of motor vehicles 632 Maintenance and repair of motor vehicles 633 Sale of motor vehicle parts and accessories 634 Sale, maintenance and repair of motor cycles and related parts and accessories 635 Retail sale of automotive fuel 641 Hotels, camping sites and other provision of short-stay accommodation 642 Restaurants, bars and canteens 643 Shebeen bars 711 Railway transport 712 Other land transport 713 Transport via pipelines 721 Sea and coastal water transport 722 Inland water transport 730 Air transport 741 Supporting and auxiliary transport activities; activities of travel agencies 751 Postal and related courier activities 752 Telecommunications 811 Monetary intermediation 818 Cash loans 819 Other financial intermediation n.e.c. 821 Insurance and pension funding, except compulsory social security 831 Activities auxiliary to financial intermediation, except insurance and pension funding 832 Activities auxiliary to insurance and pension funding 841 Real estate activities with own or leased property 842 Real estate activities on a fee or contract basis 851 Renting of transport equipment 852 Renting of other machinery and equipment 853 Renting of personal and household goods n.e.c. 861 Hardware consultancy 862 Software consultancy and supply 863 Data processing 864 Data base activities 869 Other computer related activities 871 Research and experimental development of natural sciences and engineering 881 Legal, accounting, bookkeeping and auditing activities; tax consultancy; market research and public opinion research; business and management consultancy 882 Architectural, engineering and other technical activities 883 Advertising 889 Business activities n.e.c. 911 Central government activities 912 Regional services council activities 913 Local authority activities 914 Provincial administrations 915 Armed forces 916 Police 917 Correctional services 920 Educational services 931 Human health activities 932 Veterinary activities 933 Social work activities 940 Sewage and refuse disposal, sanitation and similar activities 951 Activities of business, employers' and professional organizations 952 Activities of trade unions 959 Activities of other membership organizations 961 Motion picture, radio, television and other entertainment activities 962 News agency activities 963 Library, archives, museums and other cultural activities 964 Sporting and other recreational activities 990 Other service activities 995 Other activities not adequately specified 999 Unknown This variable indicates the 3 digit version of the main business/function of the company where the person works (the person's industry). IPUMS Ever given birth to a live child <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A461">P-40 Has (the person) ever given birth to a live child even if the child died soon after birth?<br /><div class="i1">Mark appropriate box with an X.<br />If 2 "No" Go to P-48.<br />[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Females age 12 to 50 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person has ever given birth to a live child. IPUMS Total children ever born <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A462 ZA07A463 ZA07A464">P-41 Total children ever born<br /><div class="i1">a. How many children has (the person) ever had that were born alive, even if they died soon after birth?<br />_ _<br />b. How many are boys?<br />_ _<br />c. How many are girls?<br />_ _<br />Include ALL her children, i.e. those who are still living, whether or not they live in this household, and those who are dead. <span class="em">Do not count stillbirths</span>.</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 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 99 NIU (not in universe) This variable indicates the total number of children ever born. IPUMS Male children ever born <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A462 ZA07A463 ZA07A464">P-41 Total children ever born<br /><div class="i1">a. How many children has (the person) ever had that were born alive, even if they died soon after birth?<br />_ _<br />b. How many are boys?<br />_ _<br />c. How many are girls?<br />_ _<br />Include ALL her children, i.e. those who are still living, whether or not they live in this household, and those who are dead. <span class="em">Do not count stillbirths</span>.</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 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 99 NIU (not in universe) This variable indicates the total number of male children ever born. IPUMS Female children ever born <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A462 ZA07A463 ZA07A464">P-41 Total children ever born<br /><div class="i1">a. How many children has (the person) ever had that were born alive, even if they died soon after birth?<br />_ _<br />b. How many are boys?<br />_ _<br />c. How many are girls?<br />_ _<br />Include ALL her children, i.e. those who are still living, whether or not they live in this household, and those who are dead. <span class="em">Do not count stillbirths</span>.</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 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 99 NIU (not in universe) This variable indicates the total number of female children ever born. IPUMS Total children surviving and living in the household <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A465 ZA07A466 ZA07A467">P-42 Total children surviving and living in this household<br /><div class="i1">a. How many of (the person's) children are still alive and living with her in this household, including grown-ups?<br />_ _<br />b. How many are boys?<br />_ _<br />c. How many are girls?<br />_ _</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 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 20 20 21 21 22 22 99 NIU (not in universe) This variable indicates the total number of children surviving and living in the household. IPUMS Male children surviving and living in the household <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A465 ZA07A466 ZA07A467">P-42 Total children surviving and living in this household<br /><div class="i1">a. How many of (the person's) children are still alive and living with her in this household, including grown-ups?<br />_ _<br />b. How many are boys?<br />_ _<br />c. How many are girls?<br />_ _</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 16 16 99 NIU (not in universe) This variable indicates the number of male children of the person who are surviving and living in the household. IPUMS Female children surviving and living in the household <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A465 ZA07A466 ZA07A467">P-42 Total children surviving and living in this household<br /><div class="i1">a. How many of (the person's) children are still alive and living with her in this household, including grown-ups?<br />_ _<br />b. How many are boys?<br />_ _<br />c. How many are girls?<br />_ _</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 14 14 17 17 99 NIU (not in universe) This variable indicates the number of female children surviving and living in the household. IPUMS Total children surviving and living elsewhere <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A468 ZA07A469 ZA07A470">P-43 Total children surviving and living elsewhere<br /><div class="i1">a. How many of (the person's) children are still alive and living elsewhere, including grown-ups?<br />_ _<br />b. How many are boys?<br />_ _<br />c. How many are girls?<br />_ _</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 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 16 16 18 18 19 19 20 20 99 NIU (not in universe) This variable indicates the total children surviving and living elsewhere. IPUMS Male children surviving living elsewhere <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A468 ZA07A469 ZA07A470">P-43 Total children surviving and living elsewhere<br /><div class="i1">a. How many of (the person's) children are still alive and living elsewhere, including grown-ups?<br />_ _<br />b. How many are boys?<br />_ _<br />c. How many are girls?<br />_ _</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 14 14 16 16 99 NIU (not in universe) This variable indicates the number of male children of the person who are surviving and living elsewhere. IPUMS Female children surviving living elsewhere <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A468 ZA07A469 ZA07A470">P-43 Total children surviving and living elsewhere<br /><div class="i1">a. How many of (the person's) children are still alive and living elsewhere, including grown-ups?<br />_ _<br />b. How many are boys?<br />_ _<br />c. How many are girls?<br />_ _</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 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 99 NIU (not in universe) This variable indicates the number of female children surviving and living elsewhere. IPUMS Total children dead <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A471 ZA07A472 ZA07A473">P-44 Total children no longer alive<br /><div class="i1">a. How many of (the person's) children are no longer alive?<br />_ _<br />b. How many were boys?<br />_ _<br />c. How many were girls?<br />_ _</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 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 15 15 17 17 99 NIU (not in universe) This variable indicates the total number of the person's children who are dead. IPUMS Male children dead <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A471 ZA07A472 ZA07A473">P-44 Total children no longer alive<br /><div class="i1">a. How many of (the person's) children are no longer alive?<br />_ _<br />b. How many were boys?<br />_ _<br />c. How many were girls?<br />_ _</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 99 NIU (not in universe) This variable indicates the number of the person's male children who are dead. IPUMS Female children dead <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A471 ZA07A472 ZA07A473">P-44 Total children no longer alive<br /><div class="i1">a. How many of (the person's) children are no longer alive?<br />_ _<br />b. How many were boys?<br />_ _<br />c. How many were girls?<br />_ _</div><br /></svar> South Africa 2007: Females age 12 to 50 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 15 15 17 17 99 NIU (not in universe) This variable indicates the number of the person's female children who are dead. IPUMS Day of birth of last child <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A474 ZA07A475 ZA07A476">P-45 Last child born<br />If the person has ever given live birth: When was (the person's) last child born, even if the child died soon after birth?<br /><div class="i1">Write the day (2 digits), month (2 digits) and year (4 digits) of the last live birth. For example, if the child was born on 5 January 1970, write 05 for the day, 01 for the month and 1970 for the year. If multiple births, indicate only last child.<br />Do not count still births (children born dead.)<br />Day _ _<br />Month _ _<br />Year _ _ _ _</div><br /></svar> South Africa 2007: Females age 12 to 49 who have given birth to a child [discrepancies: none] 00 NIU (not in universe) 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 This variable indicates the day of birth of the person's last child. IPUMS Month of birth of last child <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A474 ZA07A475 ZA07A476">P-45 Last child born<br />If the person has ever given live birth: When was (the person's) last child born, even if the child died soon after birth?<br /><div class="i1">Write the day (2 digits), month (2 digits) and year (4 digits) of the last live birth. For example, if the child was born on 5 January 1970, write 05 for the day, 01 for the month and 1970 for the year. If multiple births, indicate only last child.<br />Do not count still births (children born dead.)<br />Day _ _<br />Month _ _<br />Year _ _ _ _</div><br /></svar> South Africa 2007: Females age 12 to 49 who have given birth to a child [discrepancies: none] 00 NIU (not in universe) 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December This variable indicates the month of birth of the person's last child. IPUMS Year of birth of last child <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A474 ZA07A475 ZA07A476">P-45 Last child born<br />If the person has ever given live birth: When was (the person's) last child born, even if the child died soon after birth?<br /><div class="i1">Write the day (2 digits), month (2 digits) and year (4 digits) of the last live birth. For example, if the child was born on 5 January 1970, write 05 for the day, 01 for the month and 1970 for the year. If multiple births, indicate only last child.<br />Do not count still births (children born dead.)<br />Day _ _<br />Month _ _<br />Year _ _ _ _</div><br /></svar> South Africa 2007: Females age 12 to 49 who have given birth to a child [discrepancies: none] 0000 NIU (not in universe) 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 This variable indicates the year of birth of the person's last child. IPUMS Sex of last child born <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A477">P-46<br />Is (the person)'s last born child male or female?<br /><div class="i1">Mark appropriate box with an X.<br />If multiple births, indicate only last child.<br />[] 1 Male<br />[] 2 Female</div><br /></svar> South Africa 2007: Females age 12 to 49 who have given birth to a child [discrepancies: none] NIU (not in universe) 1 Male 2 Female This variable indicates the sex of the last child born. IPUMS Last child born still alive <svar v="ZA07A461 ZA07A462 ZA07A463 ZA07A464 ZA07A465 ZA07A466 ZA07A467 ZA07A468 ZA07A469 ZA07A470 ZA07A471 ZA07A472 ZA07A473 ZA07A474 ZA07A475 ZA07A476 ZA07A477 ZA07A478"><span class="h2">Section F: Fertility - ask of women aged 12 to 50 years (born between and including 1957 and 1995) listed on the flap</span><br />[Questions P-40 to P-47.]<br /></svar></p> <p><svar a="all" v="ZA07A478">P-47 Last born child alive<br />Is (the person)'s last born child still alive?<br /><div class="i1">Mark appropriate box with an X.<br />If multiple births, indicate only last child.<br />[] 1 Yes<br />[] 2 No</div><br /></svar> South Africa 2007: Females age 12 to 49 who have given birth to a child [discrepancies: none] NIU (not in universe) 1 Yes 2 No This variable indicates whether the last child born is still alive. IPUMS Mother still alive <svar v="ZA07A479 ZA07A480 ZA07A481 ZA07A482 ZA07A483 ZA07A072"><span class="h2">Section G: Parental survival and income - ask everyone listed on the flap</span><br /></svar></p> <p><svar a="all" v="ZA07A479">P-48 Mother alive<br />Is (the person's) own biological mother still alive?<br /><div class="i1">Mark appropriate box with an X. If 2 "No" or 3 "Do not know" Go to P-50.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] 1 Yes 2 No 3 Respondent did not know 9 NIU (not in universe) This variable indicates whether or not the person's biological mother was still alive. IPUMS Mother's person number <svar v="ZA07A479 ZA07A480 ZA07A481 ZA07A482 ZA07A483 ZA07A072"><span class="h2">Section G: Parental survival and income - ask everyone listed on the flap</span><br /></svar></p> <p><svar a="all" v="ZA07A480">P-49 Mother's person number<br />Who in this household is (the person's) biological mother?<br />(column no. of biological mother).<br /><div class="i1">[Question P-49 was asked of persons whose own biological mother is still alive, per question P-48.]<br />If the mother does not live in this household, write 98.<br />_ _</div><br /></svar> South Africa 2007: Persons not residing in institutions whose mothers are still living [discrepancies: none] 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 98 Mother not in household 99 NIU (not in universe) This variable indicates the person number of the person's mother. IPUMS Father still alive <svar v="ZA07A479 ZA07A480 ZA07A481 ZA07A482 ZA07A483 ZA07A072"><span class="h2">Section G: Parental survival and income - ask everyone listed on the flap</span><br /></svar></p> <p><svar a="all" v="ZA07A481">P-50 Father alive<br />Is (the person)'s own biological father still alive?<br /><div class="i1">Mark appropriate box with an X.<br />If 2 "No" or 3 "Do not know", go to P-52.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] 1 Yes 2 No 3 Respondent did not know 8 Unknown 9 NIU (not in universe) This variable indicates whether the person's father was still alive. IPUMS Father's person number <svar v="ZA07A479 ZA07A480 ZA07A481 ZA07A482 ZA07A483 ZA07A072"><span class="h2">Section G: Parental survival and income - ask everyone listed on the flap</span><br /></svar></p> <p><svar a="all" v="ZA07A482">P-51 Father's person number<br />Who in this household is (the person)'s biological father?<br />(column no. of biological father).<br /><div class="i1">[Question P-51 was asked of persons whose own biological father is still alive, per question P-50.]<br />If the father does not live in this household, write 98.<br />_ _</div><br /></svar> South Africa 2007: Persons not residing in institutions whose fathers are still living [discrepancies: none] 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 98 Father not in household 99 NIU (not in universe) This variable indicates the person number of the person's father. IPUMS Income (monthly/annual) <svar v="ZA07A479 ZA07A480 ZA07A481 ZA07A482 ZA07A483 ZA07A072"><span class="h2">Section G: Parental survival and income - ask everyone listed on the flap</span><br /></svar></p> <p><svar a="all" v="ZA07A072 ZA07A483">P-52 Income category<br />What is the income category that best describes the gross monthly or annual income of (the person) before deductions and including all sources of income?<br /><div class="i1"><span class="ital">Read out</span>:<br />Monthly / Annual<br />[] 01 No income / No income<br />[] 02 R 1 - R 400 / R 1 - R 4 800<br />[] 03 R 401 - R 800 / R 4 801 - R 9 600<br />[] 04 R 801 - R 1 600 / R 9 601 - R 19 200<br />[] 05 R 1 601 - R 3 200 / R 19 201 - R 38 400<br />[] 06 R 3 201 - R 6 400 / R 38 401 - R 76 800<br />[] 07 R 6 401 - R 12 800 / R 76 801 - R 153 600<br />[] 08 R 12 801 - R 25 600 / R 153 601 - R 307 200<br />[] 09 R 25 601 - R 51 200 / R 307 201 - R 614 400<br />[] 10 R 51 201 - R 102 400 / R 614 401 - R 1 228 800<br />[] 11 R 102 401- R 204 800 / R 1 228 801- R 2 457 600<br />[] 12 R 204 801 or more / R 2 457 601 or more<br />[] 13 Response not given<br />Write code in the box.<br />_ _</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] 01 No income 02 R 1-400 monthly / 1-4800 annual 03 R 401-800 monthly/ 4801-9600 annual 04 R 801-1600 monthly / 9601-19200 annual 05 R 1601-3200 monthly / 19201-38400 annual 06 R 3201-6400 monthly / 38401-76800 annual 07 R 6401-12800 monthly / 76801-153600 annual 08 R 12801-25560 monthly / 153601-307200 annual 09 R 25601-51200 monthly / 307201-614400 annual 10 R 51201-102400 monthly / 614401-1228800 annual 11 R 102401-204800 monthly / 1228801-2457600 annual 12 R 204801+ monthly / 2457601+ annual 13 Response not given 99 NIU (not in universe) This variable indicates the person's income category. IPUMS Flag for PERNUMO South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person number. IPUMS Flag for BIRDAY South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's day of birth. IPUMS Flag for BIRMON South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's month of birth. IPUMS Flag for BIRYR South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's year of birth. IPUMS Flag for AGE South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's age. IPUMS Flag for SEX South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's sex. IPUMS Flag for STAY4NIT South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates an imputation flag for whether the person usually stays four nights a week at the residence of enumeration. IPUMS Flag for LASTNIT South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates an imputation flag for whether the person stayed at the enumeration household the previous night. IPUMS Flag for RELATE South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's relationship to the head of household. IPUMS Flag for MARST South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's marital status. IPUMS Flag for SPLOCO South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person number of the spouse of the enumerated person. IPUMS Flag for RACE South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's race. IPUMS Flag for BPLPR South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's province of birth. IPUMS Flag for BPLPL South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for person's main place of birth. IPUMS Flag for BPLSUB South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's sub-place of birth. IPUMS Flag for RESPL South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's main place of usual residence. IPUMS Flag for RESSUB South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's sub-place of usual residence. IPUMS Flag for HERE5YR South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person lived in the dwelling five years prior to the date of enumeration (October 2001). IPUMS Flag for HEREMON South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the month in which the person moved to the dwelling. IPUMS Flag for HEREYR South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the year in which the person moved to the dwelling. IPUMS Flag for RESPRPR South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the province of previous residence. IPUMS Flag for RESPRPL South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's main place of previous residence. IPUMS Flag for RESPRSUB South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's sub-place of previous residence. IPUMS Flag for DISAB South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's disability. IPUMS Flag for DISABS South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the sight-related disability. IPUMS Flag for DISABH South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for hearing-related disability. IPUMS Flag for DISABC South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for communication disability. IPUMS Flag for DISABP South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for physical disability. IPUMS Flag for DISABI South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for intellectual disability. IPUMS Flag for DISABE South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for emotional disability. IPUMS Flag for DISABLA South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for a disability that prevents the person from life activities. IPUMS Flag for GRANT South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person receives any government/welfare grants. IPUMS Flag for GRANTOA South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for receipt of a social grant in the form of old age pension. IPUMS Flag for GRANTD South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for receipt of a social grant for disability. IPUMS Flag for GRANTCS South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for receipt of social grant for child support. IPUMS Flag for GRANTDC South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for receipt of social grant for dependent child care. IPUMS Flag for GRANTFC South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for receipt of a social grant for foster care. IPUMS Flag for GRANTIA South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the receipt of a social grant in aid. IPUMS Flag for GRANTSR South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the receipt of a social relief grant. IPUMS Flag for SCHOOL South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for school attendance. IPUMS Flag for SCHLLEV South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for educational institution. IPUMS Flag for SCHLPUB South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for private/public school. IPUMS Flag for EDATTAN South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the highest level of education. IPUMS Flag for WKBUS South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person ran or conducted any kind of business, big or small, in the 7 days prior to enumeration. IPUMS Flag for WKPAY South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person worked for a wage, salary, commission or any payment in kind during the 7 days prior to enumeration. IPUMS Flag for WKDOM South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person worked as domestic worker for a wage, salary, or any payment in kind during the 7 days prior to enumeration. IPUMS Flag for WKHHBUS South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person helped unpaid in a household business of any kind during the 7 days prior to enumeration. IPUMS Flag for WKPLOT South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person worked on the household's plot, farm, food garden, cattle post or kraal or helped in growing farm produce or in looking after animals for the household during the 7 days prior to enumeration. IPUMS Flag for WKREPAIR South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person did any construction or major repair work on his/her own home, plot, cattle post or business during the 7 days prior to enumeration. IPUMS Flag for WKHUNT South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person caught any fish, prawns, shells, wild animals or other food for sale or for the household during the 7 days prior to enumeration. IPUMS Flag for WKNOTNOW South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person had a job, business, or other economic or farming activity to return to if they had not worked during the 7 days prior to enumeration. IPUMS Flag for WKWHYNOT South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the reason for not working. IPUMS Flag for WKAVAIL South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for availability for work. IPUMS Flag for WKLOOK South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person took action to look for any kind of work during the 4 weeks prior to enumeration. IPUMS Flag for WKBUSNEW South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person taken any action to start any kind of business during the 4 weeks prior to enumeration. IPUMS Flag for CLASSWK South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for work status. IPUMS Flag for WKFORMAL South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's sector of employment. IPUMS Flag for OCC South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for occupation. IPUMS Flag for WKNAME South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates an imputation flag for the name of the person's place of work/company. IPUMS Flag for IND South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates an imputation flag for industry. IPUMS Flag for ANYKIDS South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates an imputation flag for whether the person ever given birth to a live child. IPUMS Flag for CHBORN South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for total children ever born. IPUMS Flag for CHBORNM South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for male children ever born. IPUMS Flag for CHBORNF South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for female children ever born. IPUMS Flag for CHSURVH South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for total children surviving living in the household. IPUMS Flag for CHSURVHM South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for male children surviving living in the household. IPUMS Flag for CHSURVHF South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for female children surviving and living in the household. IPUMS Flag for CHSURVE South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 9 NIU (not in universe) This variable indicates whether there is an imputation flag for total children surviving and living elsewhere. IPUMS Flag for CHSURVEM South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 9 NIU (not in universe) This variable indicates an imputation flag for male children surviving and living elsewhere. IPUMS Flag for CHSURVEF South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 9 NIU (not in universe) This variable indicates an imputation flag for female children surviving and living elsewhere. IPUMS Flag for CHDEAD South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 9 NIU (not in universe) This variable indicates whether there is an imputation flag for total children dead. IPUMS Flag for CHDEADM South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 9 NIU (not in universe) This variable indicates whether there is an imputation flag for male children dead. IPUMS Flag for CHDEADF South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 9 NIU (not in universe) This variable indicates whether there is an imputation flag for female children dead. IPUMS Flag for LSTCHDAY South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for day of birth for the last child born. IPUMS Flag for LSTCHSEX South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the sex of the last child born. IPUMS Flag for LSTCHLIV South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the last child born is still alive. IPUMS Flag for MOMLIV South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for whether the person's mother is living. IPUMS Flag for MOMLOCO South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person number of the mother (of the enumerated person). IPUMS Flag for POPLIV South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates an imputation flag for whether the person's father is living. IPUMS Flag for POPLOCO South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person number of the father (of the enumerated person). IPUMS Flag for INCOMEGR South Africa 2007: Persons not residing in institutions [discrepancies: none] No imputation 1 Logical imputation (from blank) 2 Logical imputation (non-blank) 3 Hot deck imputation (from blank) 4 Hot deck imputation (non-blank) 9 NIU (not in universe) This variable indicates whether there is an imputation flag for the person's income category. IPUMS Weight: design weights South Africa 2007: All persons This variable indicates the design weights. ZA07A567 is a 9-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Employment status (official definition) <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p>P-30 <span class="em">Employment status</span></p> <p><svar a="ZA07A451" v="ZA07A451 ZA07A568 ZA07A569">P-31 Temporary absence from work<br />Even though (the person) did not do any of these activities in the last seven days, does he/she have a job, business, or other economic or farming activity that he/she will definitely return to?<br /><div class="i1">[Question P-31 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />For agricultural activities, the off season in agriculture is not a temporary absence.<br />If 1 "Yes" Go to P-36.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar></p> <p><svar a="ZA07A452" v="ZA07A452 ZA07A568 ZA07A569">P-32 Reasons for not working<br />Why did (the person) not work during the past seven days?<br /><div class="i1">[Question P-32 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />[] 01 Has found a job, but is only starting at a definite date in the future<br />[] 02 Scholar/student and prefers not to work<br />[] 03 Housewife/homemaker and prefers not to work<br />[] 04 Retired and prefers not to seek formal work<br />[] 05 Invalid, ill, disabled or unable to work (handicapped)<br />[] 06 Too young or too old to work<br />[] 07 Seasonal worker, e.g. fruit picker, wool-shearer<br />[] 08 Lack of skills or qualifications for available jobs<br />[] 09 Cannot find work<br />[] 10 Cannot find suitable work (salary, location of work or conditions not satisfactory)<br />[] 11 Contract worker, e.g. mine worker resting according to contract<br />[] 12 Retrenched<br />[] 13 Other reason<br />Write code in the box.<br />_ _</div><br /></svar></p> <p><svar a="ZA07A453" v="ZA07A453 ZA07A568 ZA07A569">P-33 Availability for work<br />If a suitable job is offered, how soon can (the person) start work?<br /><div class="i1">[Question P-33 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />[] 1 Within a week<br />[] 2 Within two weeks<br />[] 3 Within four weeks<br />[] 4 More than four weeks from now<br />[] 5 Not interested<br />[] 6 Not able (health or disability)<br />[] 7 Do not know<br />Write code in the box.<br />_</div><br /></svar></p> <p><svar a="ZA07A454" v="ZA07A454 ZA07A568">P-34 Active steps seeking work<br />During the past four weeks, has (the person) taken any action to look for any kind of work?<br /><div class="i1">[Question P-34 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />Mark appropriate box with an X.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar></p> <p><svar a="ZA07A455" v="ZA07A455 ZA07A568">P-35 Active steps seeking work<br />During the past four weeks, has (the person) taken any action to start any kind of business?<br /><div class="i1">[Question P-35 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />If P-34 and P-35 completed Go to P-40<br />Mark appropriate box with an X.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar> South Africa 2007: Persons age 15 to 65 who do not live in institutions [discrepancies: none] 1 Employed 2 Unemployed 3 Not economically active 8 Unknown (not working, reason unknown) 9 NIU (not in universe) This variable indicates the person's employment status according to the official definition. Employed persons are those who reported having engaged in any of the work activities listed on the census (questions P30a-g) for at least one hour during the 7 days prior to the census interview or who reported being temporarily out of work but having a job to which they would return. The variable listing reason for not working (WKWHYNOT) distinguishes, in part, among unemployed people and those who were not economically active. People who reported their status as student, housewife/homemaker, retired, ill/invalid/disabled, or too young/too old to work in their reason for not working (categories 2 through 6 of WKWHYNOT) are "not economically active." People who had found a job which would start at a definite date in the future (category 1 of WKWHYNOT) are "unemployed." People who listed other reasons for not working (categories 7 through 13 of WKWHYNOT) were divided into unemployed or not economically active based on a combination of additional criteria from WKAVAIL, WKLOOK and WKBUSNEW. If this group was available for work within 1-2 weeks and also either looking for work or taking action to start a business, they considered unemployed. Otherwise, they were classified as not economically active. (In contrast, the variable for the expanded definition of employment status, EMPSTATEXP, relies only on the WKAVAIL criteria of being available for work within two weeks to classify as unemployed.) People who did not report a reason for not working are in the Unknown category (=8). IPUMS Employment status (expanded definition) <svar v="ZA07A444 ZA07A445 ZA07A446 ZA07A447 ZA07A448 ZA07A449 ZA07A450 ZA07A451 ZA07A452 ZA07A453 ZA07A454 ZA07A455 ZA07A456 ZA07A457 ZA07A458 ZA07A459 ZA07A460 ZA07A568 ZA07A569"><span class="h2">Section E: Employment and economic activities - ask of all persons 15 years and older listed on the flap</span><br />[Questions P-30 to P-39 were asked of persons age 15 and older.]<br /></svar></p> <p>P-30 <span class="em">Employment status</span></p> <p><svar a="ZA07A451" v="ZA07A451 ZA07A568 ZA07A569">P-31 Temporary absence from work<br />Even though (the person) did not do any of these activities in the last seven days, does he/she have a job, business, or other economic or farming activity that he/she will definitely return to?<br /><div class="i1">[Question P-31 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />For agricultural activities, the off season in agriculture is not a temporary absence.<br />If 1 "Yes" Go to P-36.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar></p> <p><svar a="ZA07A452" v="ZA07A452 ZA07A568 ZA07A569">P-32 Reasons for not working<br />Why did (the person) not work during the past seven days?<br /><div class="i1">[Question P-32 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />[] 01 Has found a job, but is only starting at a definite date in the future<br />[] 02 Scholar/student and prefers not to work<br />[] 03 Housewife/homemaker and prefers not to work<br />[] 04 Retired and prefers not to seek formal work<br />[] 05 Invalid, ill, disabled or unable to work (handicapped)<br />[] 06 Too young or too old to work<br />[] 07 Seasonal worker, e.g. fruit picker, wool-shearer<br />[] 08 Lack of skills or qualifications for available jobs<br />[] 09 Cannot find work<br />[] 10 Cannot find suitable work (salary, location of work or conditions not satisfactory)<br />[] 11 Contract worker, e.g. mine worker resting according to contract<br />[] 12 Retrenched<br />[] 13 Other reason<br />Write code in the box.<br />_ _</div><br /></svar></p> <p><svar a="ZA07A453" v="ZA07A453 ZA07A568 ZA07A569">P-33 Availability for work<br />If a suitable job is offered, how soon can (the person) start work?<br /><div class="i1">[Question P-33 was asked of persons who were not working in the last seven days, per questions P-30a to P-30g.]<br />[] 1 Within a week<br />[] 2 Within two weeks<br />[] 3 Within four weeks<br />[] 4 More than four weeks from now<br />[] 5 Not interested<br />[] 6 Not able (health or disability)<br />[] 7 Do not know<br />Write code in the box.<br />_</div><br /></svar> South Africa 2007: Persons age 15 to 65 who do not live in institutions [discrepancies: none] 1 Employed 2 Unemployed 3 Not economically active 8 Unknown (not working, reason unknown) 9 NIU (not in universe) This variable indicates the person's employment status according to an expanded definition of employment. The number of employed persons is the same in both the official and expanded definitions of employment status and includes people who reported having engaged in any of the work activities listed on the census (questions P30a-g) for at least one hour during the 7 days prior to the census interview or who reported being temporarily out of work from a job to which they would return. Both the official and expanded definitions of employment status classify people who reported their status as student, housewife/homemaker, retired, ill/invalid/disabled, or too young/too old to work in reason for not working (categories 2 through 6 of WKWHYNOT) as "not economically active," and those who had found a new job beginning at a definite date in the future (category 1 of WKWHYNOT) as "unemployed." The difference between the official and expanded classification systems applies to people who reported other reasons for not working (categories 7 through 13 of WKWHYNOT). Under the expanded definition, people with other reasons for not working, who reported being available for work (WKAVAIL) within two weeks, are unemployed. (In contrast, the official definition of employment status imposes additional limitations based upon whether a person was looking for work or starting a business to qualify as unemployed). People who did not report a reason for not working are in the Unknown category (=8). IPUMS Derived disability <svar a=" ZA07A424 " v="ZA07A424 ZA07A570">P-21 Disability<br />Does (the person) have any kind of disability?<br /><div class="i1">Mark appropriate box with an X<br />If 2 "No" or 3 "Do not know" Go to P-24.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar></p> <p><svar a=" ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A570" v="ZA07A425 ZA07A426 ZA07A427 ZA07A428 ZA07A429 ZA07A430 ZA07A431 ZA07A570">P-22 Disability type<br />What type(s) of disability does (the person) have?<br /><div class="i1">[Question P-22 was asked of persons who had some kind of disability, per question P-21.]<br />Mark any that apply with an X.<br />Multiple disabilities are indicated by marking more than one selection.<br /><span class="ital">Read out</span>:<br />[] 1 Sight (blind/severe visual limitation<br />[] 2 Hearing (deaf, profoundly hard of hearing)<br />[] 3 Communication (speech impairment)<br />[] 4 Physical (needs wheelchair, crutches, etc.)<br />[] 5 Intellectual (serious difficulties in learning)<br />[] 6 Emotional (behavioural, psychological)</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] No disabilities 1 Sight (blind/severe visual limitation) 2 Hearing (deaf, profoundly hard of hearing) 3 Communication (speech impairment) 4 Physical (e.g. needs wheelchair, crutches or prosthesis; limb, hand usage limitations) 5 Intellectual (serious difficulties in learning) 6 Emotional (behavioral, psychological) 7 Multiple disabilities (combination of more than one of the above) 9 NIU (not in universe) This variable indicates the derived disability. IPUMS Derived social grant <svar a=" ZA07A432" v="ZA07A432 ZA07A571">P-24 Social grant<br />Does (the person) receive any social / government grant?<br /><div class="i1">Mark appropriate box with an X<br />If 2 "No" or 3 "Do not know" Go to P-26.<br />[] 1 Yes<br />[] 2 No<br />[] 3 Do not know</div><br /></svar></p> <p><svar a="all" v="ZA07A433 ZA07A434 ZA07A435 ZA07A436 ZA07A437 ZA07A438 ZA07A439 ZA07A571">P-25 Type of social grant<br />What type(s) of social /government grant does (the person) receive?<br /><div class="i1">[Question P-25 was asked of persons who received social/government grant, per question P-24.]<br />Mark any that apply with an X.<br />[] 1 Old age pension<br />[] 2 Disability grant<br />[] 3 Child support grant (linked to a child)<br />[] 4 Care dependency grant<br />[] 5 Foster care grant<br />[] 6 Grant in aid<br />[] 7 Social relief</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies: none] No grants 1 Old age pension 2 Disability grant 3 Child support grant (linked to a child) 4 Care dependency grant 5 Foster care grant 6 Grant in aid 7 Social relief 8 Multiple social grants (combination of more than one of the above) 9 NIU (not in universe) This variable indicates the derived social grant. IPUMS Province of usual residence (2001 classification) <svar a="all" v="ZA07A416 ZA07A572">P-14 Main place of usual residence<br />In which city, town, township, or tribal area does (the person) usually live?<br /><div class="i1">Write the name of the place in capital letters.<br />____</div><br /></svar> South Africa 2007: Persons not residing in institutions [discrepancies:none] 01 Western cape 02 Eastern cape 03 Northern cape 04 Free state 05 Kwazulu-natal 06 North west 07 Gauteng 08 Mpumalanga 09 Limpopo 98 Unknown 99 NIU (not in universe) This variable indicates the province of the person's usual residence in 2001. IPUMS Weight: average adjusted South Africa 2007: All persons This variable indicates the average adjusted weights. ZA07A573 is a 9-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Weight: survey less unoccupied South Africa 2007: All persons This variable indicates the Community Survey less unoccupied weights. ZA07A575 is a 9-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Weight: survey adjusted all non-response South Africa 2007: All persons This variable indicates the Community Survey adjusted all non-response weights. ZA07A576 is a 9-digit numeric variable. Codes0 = Institutional resident weighted zero. IPUMS Weight: survey final provincial weights South Africa 2007: All persons This variable indicates the Community Survey final provincial weights. This is a 10-digit numeric variable with 6 implied decimal places IPUMS Type of dwelling, CS scope South Africa 2007: All persons 1 Sampled CS dwelling 2 Prisons 3 Boarding schools 4 Other households out of CS scope 5 Other institutions This variable indicates the type of dwelling/Community Survey scope status. IPUMS Weight: final municipal de-facto weights South Africa 2007: All persons This variable indicates the Community Survey final municipal de-facto weights. This is a 10-digit numeric variable with 6 implied decimal places IPUMS Weight: final municipal de-jure weights South Africa 2007: All persons This variable indicates the Community Survey final municipal de-jure weights. This is a 10-digit numeric variable with 6 implied decimal places IPUMS