DDI_ZWE_2012_PHC_v01_M_v7.5_A_IPUMS Population Census 2012 IPUMS May 21, 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. Population Census 2012 - IPUMS Subset PHC Zimbabwe 2012 (IPUMS Harmonized Subset) ZWE_2012_PHC_v01_M_v7.5_A_IPUMS National Statistical Agency IPUMS (c) Copyright 2012, National Statistical Agency and Minnesota Population Center MetadataEditor National Statistical Agency 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 Technical Household Variables -- HOUSEHOLD Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Utilities Variables -- HOUSEHOLD Work Variables -- PERSON Geography: O-Z Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Migration: O-Z Variables -- PERSON Household Economic Variables -- HOUSEHOLD Technical Person Variables -- PERSON Ethnicity and Language Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Disability Variables -- PERSON Technical Household Variables -- HOUSEHOLD Constructed Family Interrelationship Variables -- PERSON Education Variables -- PERSON Technical Person Variables -- PERSON Household Economic Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Dwelling Characteristics Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Demographic Variables -- PERSON Other Person Variables -- PERSON Nativity and Birthplace Variables -- PERSON Migration: Global Variables -- PERSON Ethnicity and Language Variables -- PERSON Fertility and Mortality Variables -- PERSON Work Variables -- PERSON Work: Occupation Variables -- PERSON Zimbabwe District Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: no - Households: A household is defined as person or a group of persons who stayed the census night in the dwelling unit, whether or not they were related by blood or marriage, including visitors. - Group quarters: Collective households are formed where institutionalized populations are found e.g. hospitals, hostels, hotels, prisons, military barracks, refugee camps, schools, colleges, old people's homes, orphanage, etc. All persons present in the country on census day Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Zimbabwe 2012 MICRODATA SOURCE: National Statistical Agency SAMPLE SIZE (person records): 654688. SAMPLE DESIGN: 5% sample drawn by national statistics office Face-to-face [f2f] A single census form for dwellings and persons de facto, CENSUS DAY: August 17, 2012 Self-weighting (expansion factor=20) 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. National Statistical Agency 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: Zimbabwe, National Statistical Agency. Population Census 2012 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. ZWE2012_PHC-H-H Household records 160 49 ZWE2012_PHC-P-H Person records 654688 123 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 Zimbabwe, Province 2012 [Level 1; consistent boundaries, GIS] 716000 Bulawayo 716001 Manicaland 716002 Mashonaland Central 716003 Mashonaland East 716004 Mashonaland West 716005 Matabeleland North 716006 Matabeleland South 716007 Midlands 716008 Masvingo 716009 Harare GEO1_ZW identifies the household's province within Zimbabwe in all sample years. Provinces are the first level administrative units of the country. GEO1_ZW is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization. A GIS map (in shapefile format), corresponding to GEO1_ZW can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Zimbabwe 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 Zimbabwe, Province 2012 [Level 1, GIS] 000 Bulawayo 001 Manicaland 002 Mashonaland Central 003 Mashonaland East 004 Mashonaland West 005 Matabeleland North 006 Matabeleland South 007 Midlands 008 Masvingo 009 Harare GEO1_ZW2012 identifies the household's province within Zimbabwe in 2012. Provinces are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_ZW2012 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Zimbabwe 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 Zimbabwe, District 2012 [Level 2; consistent boundaries, GIS] 716000021 Bulawayo Urban 716001001 Buhera 716001002 Chimanimani 716001003 Chipinge Rural 716001004 Makoni 716001005 Mutare Rural 716001006 Mutasa 716001007 Nyanga 716001021 Mutare Urban 716001022 Rusape Urban 716001023 Chipinge Urban 716002001 Bindura Rural 716002002 Muzarabani 716002003 Guruve 716002004 Mazowe, Mvurwi 716002005 Mt Darwin 716002006 Rushinga 716002007 Shamva 716002008 Mbire 716002021 Bindura Urban 716003001 Chikomba 716003002 Goromonzi 716003003 Hwedza 716003004 Marondera Rural 716003005 Mudzi 716003006 Murehwa 716003007 Mutoko 716003008 Seke 716003009 Uzumba Maramba Pfungwe 716003021 Marondera Urban 716003023 Ruwa 716004001 Chegutu 716004002 Hurungwe, Karoi 716004003 Mhondoro-Ngezi 716004004 Kariba Rural 716004005 Makonde 716004006 Zvimba 716004007 Sanyati 716004021 Chinhoyi 716004022 Kadoma 716004023 Chegutu Urban 716004024 Kariba Urban 716004025 Norton 716005001 Binga 716005002 Bubi 716005003 Hwange Rural 716005004 Lupane 716005005 Nkayi 716005006 Tsholotsho 716005007 Umguza 716005021 Hwange Urban 716005022 Victoria Falls 716006001 Beitbridge Rural 716006002 Bulilima 716006003 Mangwe Rural, Mangwe Urban (Plumtree) 716006004 Gwanda Rural 716006005 Insiza 716006006 Matobo 716006007 Umzingwane 716006021 Gwanda Urban 716006022 Beitbridge Urban 716007001 Chirumanzu 716007002 Gokwe North 716007003 Gokwe South 716007004 Gweru Rural 716007005 Kwekwe Rural 716007006 Mberengwa 716007007 Shurugwi Rural 716007008 Zvishavane Rural 716007021 Gweru Urban 716007022 Kwekwe Urban 716007023 Redcliff 716007024 Zvishavane Urban 716007025 Gokwe Centre 716007026 Shurugwi Urban 716008001 Bikita 716008002 Chiredzi Rural 716008003 Chivi 716008004 Gutu 716008005 Masvingo Rural 716008006 Mwenezi 716008007 Zaka 716008021 Masvingo Urban 716008022 Chiredzi Town 716009001 Harare Rural 716009021 Harare Urban 716009022 Chitungwiza 716009023 Epworth GEO2_ZW identifies the household's district within Zimbabwe in all sample years. Districts are the second level administrative units of the country, after provinces. GEO2_ZW is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization. A GIS map (in shapefile format), corresponding to GEO2_ZW can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Zimbabwe 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 Zimbabwe, District 2012 [Level 2, GIS] 000021 Bulawayo Urban 001001 Buhera 001002 Chimanimani 001003 Chipinge Rural 001004 Makoni 001005 Mutare Rural 001006 Mutasa 001007 Nyanga 001021 Mutare Urban 001022 Rusape Urban 001023 Chipinge Urban 002001 Bindura Rural 002002 Muzarabani 002003 Guruve 002004 Mazowe, Mvurwi 002005 Mt Darwin 002006 Rushinga 002007 Shamva 002008 Mbire 002021 Bindura Urban 003001 Chikomba 003002 Goromonzi 003003 Hwedza 003004 Marondera Rural 003005 Mudzi 003006 Murehwa 003007 Mutoko 003008 Seke 003009 Uzumba Maramba Pfungwe 003021 Marondera Urban 003023 Ruwa 004001 Chegutu 004002 Hurungwe, Karoi 004003 Mhondoro-Ngezi 004004 Kariba Rural 004005 Makonde 004006 Zvimba 004007 Sanyati 004021 Chinhoyi 004022 Kadoma 004023 Chegutu Urban 004024 Kariba Urban 004025 Norton 005001 Binga 005002 Bubi 005003 Hwange Rural 005004 Lupane 005005 Nkayi 005006 Tsholotsho 005007 Umguza 005021 Hwange Urban 005022 Victoria Falls 006001 Beitbridge Rural 006002 Bulilima 006003 Mangwe Rural, Mangwe Urban (Plumtree) 006004 Gwanda Rural 006005 Insiza 006006 Matobo 006007 Umzingwane 006021 Gwanda Urban 006022 Beitbridge Urban 007001 Chirumanzu 007002 Gokwe North 007003 Gokwe South 007004 Gweru Rural 007005 Kwekwe Rural 007006 Mberengwa 007007 Shurugwi Rural 007008 Zvishavane Rural 007021 Gweru Urban 007022 Kwekwe Urban 007023 Redcliff 007024 Zvishavane Urban 007025 Gokwe Centre 007026 Shurugwi Urban 008001 Bikita 008002 Chiredzi Rural 008003 Chivi 008004 Gutu 008005 Masvingo Rural 008006 Mwenezi 008007 Zaka 008021 Masvingo Urban 008022 Chiredzi Town 009001 Harare Rural 009021 Harare Urban 009022 Chitungwiza 009023 Epworth GEO2_ZW2012 identifies the household's district within Zimbabwe in 2012. Districts are the second level administrative units of the country, after provinces. A GIS map (in shapefile format), corresponding to GEO2_ZW can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Zimbabwe 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 Zimbabwe, Ward 2012 [Level 3, GIS] 000021001 Bulawayo Urban Wards 01, 07, 20 000021002 Bulawayo Urban Wards 10, 11 000021003 Bulawayo Urban Wards 17, 27 000021004 Bulawayo Urban Wards 21, 22 000021005 Bulawayo Urban Ward 12, 13 000021006 Bulawayo Urban Ward 28 000021007 Bulawayo Urban Wards 23, 24 000021008 Bulawayo Urban Wards 18, 29 000021009 Bulawayo Urban Wards 05, 06 000021010 Bulawayo Urban Ward 03 000021011 Bulawayo Urban Wards 15, 16 000021012 Bulawayo Urban Ward 09 000021013 Bulawayo Urban Ward 02 000021014 Bulawayo Urban Ward 04 000021015 Bulawayo Urban Ward 25 000021016 Bulawayo Urban Ward 08 000021017 Bulawayo Urban Ward 26 000021018 Bulawayo Urban Ward 19 000021019 Bulawayo Urban Ward 14 001001001 Buhera Wards 01, 02, 03, 04, 05, 08, 31 001001002 Buhera Wards 22, 23, 32 001001003 Buhera Wards 11, 12, 18, 20 001001004 Buhera Wards 06, 07, 14 001001005 Buhera Wards 09, 10, 13, 15 001001006 Buhera Wards 24, 26, 27 001001007 Buhera Wards 29, 30, 33 001001008 Buhera Wards 16, 17, 19, 21 001001009 Buhera Wards 25, 28 001002001 Chimanimani Wards 06, 09, 13, 15, 16, 17, 18, 19, 20 001002002 Chimanimani Wards 02, 03, 04, 05, 08 001002003 Chimanimani Wards 01, 07, 10, 11, 12, 14 001002004 Chimanimani Wards 21, 22, 23 001003001 Chipinge Rural Wards 22, 23, 25, 28 001003002 Chipinge Rural Wards 04, 05, 06, 10, 11, 12, 13 001003003 Chipinge Rural Wards 24, 26 001003004 Chipinge Rural Wards 14, 15, 18, 19 001003005 Chipinge Rural Wards 16, 20 001003006 Chipinge Rural Wards 07, 08, 09 001003007 Chipinge Rural Wards 01, 02, 03 001003008 Chipinge Rural Wards 27, 29, 30 001003009 Chipinge Rural Wards 17, 21 001004001 Makoni Wards 09, 10, 11, 17, 20, 21, 33 001004002 Makoni Wards 12, 15, 16, 26, 27, 29, 30 001004003 Makoni Wards 14, 24, 25, 28, 31, 39 001004004 Makoni Wards 05, 07, 08 001004005 Makoni Wards 01, 02, 03, 04, 35, 36 001004006 Makoni Wards 06, 13, 32, 34, 37, 38 001004007 Makoni Wards 18, 19, 22, 23 001005001 Mutare Rural Wards 04, 05, 10, 12, 13, 14, 17, 18, 20, 21, 35, 36 001005002 Mutare Rural Wards 24, 28, 29, 30 001005003 Mutare Rural Wards 02, 08, 11, 34 001005004 Mutare Rural Wards 06, 15, 32 001005005 Mutare Rural Wards 19, 23, 25, 26, 27 001005006 Mutare Rural Wards 01, 03, 31 001005007 Mutare Rural Wards 09, 16 001005008 Mutare Rural Wards 07, 22, 33 001006001 Mutasa Wards 01, 02, 03, 04, 05, 28, 29, 30 001006002 Mutasa Wards 17, 18, 20, 21, 24, 26, 27 001006003 Mutasa Wards 12, 13, 14, 15, 16, 22, 23, 25 001006004 Mutasa Wards 06, 07, 11, 31 001006005 Mutasa Wards 08, 09, 10, 19 001007001 Nyanga Wards 07, 08, 16, 20, 21, 23, 24, 25, 26, 27, 28 001007002 Nyanga Wards 17, 18, 19, 22, 29, 30, 31 001007003 Nyanga Wards 03, 05, 10, 11, 12 001007004 Nyanga Wards 01, 02, 04, 06 001007005 Nyanga Wards 09, 13, 14, 15 001021001 Mutare Urban Wards 03, 05, 17 001021002 Mutare Urban Wards 14, 16 001021003 Mutare Urban Wards 06, 08, 09, 18 001021004 Mutare Urban Wards 10, 11, 12 001021005 Mutare Urban Wards 07, 13, 15, 19 001021006 Mutare Urban Wards 01, 02, 04 001022001 Rusape Urban Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10 001023001 Chipinge Urban Wards 01, 02, 03, 04, 05, 06, 07, 08 002001001 Bindura Rural Wards 09, 10, 13, 14, 15, 16, 17, 18 002001002 Bindura Rural Wards 01, 02, 03, 04, 05 002001003 Bindura Rural Wards 07, 08, 19, 20 002001004 Bindura Rural Wards 06, 11, 12, 21 002002001 Muzarabani Wards 01, 04, 05, 06, 08, 23, 24 002002002 Muzarabani Wards 02, 03, 10, 17, 18, 19, 27 002002003 Muzarabani Wards 12, 14, 15, 16, 22, 28 002002004 Muzarabani Wards 07, 09, 11, 13, 20, 21, 25, 26, 29 002003001 Guruve Wards 05, 06, 07, 22 002003002 Guruve Wards 08, 09, 10, 11, 12 002003003 Guruve Wards 01, 03, 13, 14, 15 002003004 Guruve Wards 02, 17, 19, 20, 21 002003005 Guruve Wards 04, 16, 18, 23, 24 002004001 Mazowe, Mvurwi Wards 07, 08, 09, 10, 11, 12, 13 002004002 Mazowe, Mvurwi Wards 18, 19, 20, 22, 34, 35 002004003 Mazowe, Mvurwi Wards 01, 02, 03, 04, 05, 06, 25, 26, 27, 29, 30 002004004 Mazowe, Mvurwi Wards 14, 15, 16, 17, 32, 33 002004005 Mazowe, Mvurwi Wards 01, 02, 03, 04, 05, 06 002004006 Mazowe, Mvurwi Wards 21, 23, 24, 31 002005001 Mt Darwin Wards 01, 03, 05, 06, 10, 11, 13, 25, 27, 28, 29, 30, 31, 32, 33, 37, 38 002005002 Mt Darwin Wards 09, 12, 14, 15, 24, 36 002005003 Mt Darwin Wards 18, 19, 20, 21, 22, 39, 40 002005004 Mt Darwin Wards 07, 08, 17, 35 002005005 Mt Darwin Wards 02, 04, 34 002005006 Mt Darwin Wards 16, 23, 26 002006001 Rushinga Wards 12, 13, 14, 15, 16, 18, 24, 25 002006002 Rushinga Wards 04, 05, 06, 08, 09, 10, 11, 17, 19 002006003 Rushinga Wards 01, 02, 03, 07, 20, 21, 22, 23 002007001 Shamva Wards 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 27 002007002 Shamva Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 25, 26 002007003 Shamva Wards 22, 23, 24, 28, 29 002008001 Mbire Wards 01, 02, 03, 04, 07, 11, 12, 16 002008002 Mbire Wards 08, 09, 10, 17 002008003 Mbire Wards 05, 06, 13, 14, 15 002021001 Bindura Urban Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12 003001001 Chikomba Wards 08, 09, 10, 11, 12, 14, 15, 16, 17 003001002 Chikomba Wards 21, 22, 23, 24, 25, 28, 29, 30 003001003 Chikomba Wards 01, 02, 03, 04, 05, 06, 07, 13 003001004 Chikomba Wards 18, 19, 20, 26, 27 003002001 Goromonzi Wards 16, 25 003002002 Goromonzi Wards 03, 06, 07, 14, 15 003002003 Goromonzi Wards 13, 17, 19, 20, 21, 22, 23, 24 003002004 Goromonzi Wards 04, 05 003002005 Goromonzi Wards 08, 09, 10, 11 003002006 Goromonzi Wards 12,18 003002007 Goromonzi Ward 01, 02 003003001 Hwedza Wards 01, 02, 03, 04, 05, 06, 07, 08, 15 003003002 Hwedza Wards 09, 10, 11, 12, 13, 14 003004001 Marondera Rural Wards 10, 11, 12, 13, 14, 15, 16, 17, 18 003004002 Marondera Rural Wards 05, 07, 08, 09, 21, 22 003004003 Marondera Rural Wards 06, 19, 20, 23 003004004 Marondera Rural Wards 01, 02, 03, 04 003005001 Mudzi Wards 05, 06, 07, 08, 09 003005002 Mudzi Wards 02, 03, 04, 17 003005003 Mudzi Wards 12, 15, 16 003005004 Mudzi Wards 01, 10, 11 003005005 Mudzi Wards 13, 14, 18 003006001 Murehwa Wards 19, 22, 23, 24, 29 003006002 Murehwa Wards 14, 15, 25, 26, 27, 28 003006003 Murehwa Wards 01, 02, 03, 04, 05, 06, 07, 09, 10 003006004 Murehwa Wards 08, 17, 18, 20, 21 003006005 Murehwa Wards 11, 12, 13 003006006 Murehwa Wards 16, 30 003007001 Mutoko Wards 04, 08, 09, 12, 13, 14, 15, 16, 17 003007002 Mutoko Wards 18, 19, 21, 22, 23, 24, 27, 28 003007003 Mutoko Wards 01, 02, 03, 05, 06, 10 003007004 Mutoko Wards 25, 26, 29 003007005 Mutoko Wards 07, 11, 20 003008001 Seke Wards 01, 02, 08 003008002 Seke Wards 11, 12, 13, 14, 15, 18, 19, 20, 21 003008003 Seke Wards 03, 04, 05, 06, 07 003008004 Seke Wards 09, 10, 16, 17 003009001 Uzumba Maramba Pfungwe Wards 01, 02, 03, 04, 05, 06, 16, 17 003009002 Uzumba Maramba Pfungwe Wards 09, 12, 13, 14, 15 003009003 Uzumba Maramba Pfungwe Wards 07, 08, 10, 11 003021001 Marondera Urban Wards 03, 04, 08, 09, 10, 11, 12 003021002 Marondera Urban Wards 01, 02, 05, 06, 07 003023001 Ruwa Wards 05, 07, 08, 09 003023002 Ruwa Wards 01, 02, 03, 04, 06 004001001 Chegutu Wards 03, 04, 08, 09, 10, 27 004001002 Chegutu Wards 12, 13, 14, 15, 16, 17, 18, 19, 21, 26, 29 004001003 Chegutu Wards 11, 20, 22 004001004 Chegutu Wards 01, 02, 05, 06, 07 004001005 Chegutu Wards 23, 24, 25, 28 004002001 Hurungwe, Karoi Wards 10, 11, 23, 25 004002002 Hurungwe, Karoi Wards 09, 22 004002003 Hurungwe, Karoi Wards 01, 02, 03, 03, 04, 05, 05, 06, 06, 07, 08, 09, 10, 20 004002004 Hurungwe, Karoi Wards 12, 13 004002005 Hurungwe, Karoi Wards 01, 08 004002006 Hurungwe, Karoi Ward 14 004002007 Hurungwe, Karoi Wards 15, 17, 24 004002008 Hurungwe, Karoi Wards 16, 26 004002009 Hurungwe, Karoi Wards 18, 21 004002010 Hurungwe, Karoi Wards 04, 07 004002011 Hurungwe, Karoi Wards 02, 19 004003001 Mhondoro-Ngezi Wards 01, 02, 03, 04, 05, 06, 07, 08 004003002 Mhondoro-Ngezi Wards 13, 15, 16 004003003 Mhondoro-Ngezi Wards 10, 12, 14 004003004 Mhondoro-Ngezi Wards 09, 11 004004001 Kariba Rural Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12 004005001 Makonde Wards 03, 05, 06, 11, 13 004005002 Makonde Wards 07, 08, 09, 10 004005003 Makonde Wards 12, 14, 15, 16, 17, 18, 19 004005004 Makonde Wards 01, 02, 04 004006001 Zvimba Wards 19, 20, 21, 30, 32 004006002 Zvimba Wards 13, 14, 15, 16 004006003 Zvimba Wards 01, 02, 07, 08, 09, 10, 11, 12, 27, 28 004006004 Zvimba Wards 24, 35 004006005 Zvimba Wards 25, 26 004006006 Zvimba Wards 17, 18, 31 004006007 Zvimba Wards 22, 23, 33, 34 004006008 Zvimba Wards 03, 04, 05, 06, 29 004007001 Sanyati Wards 02, 03 004007002 Sanyati Wards 04, 06, 07, 08, 09, 13, 14, 15, 16, 17 004007003 Sanyati Wards 10, 11, 12, 18 004007004 Sanyati Wards 01, 05 004021001 Chinhoyi Wards 01, 03, 05, 09, 10, 11, 13, 14, 15 004021002 Chinhoyi Wards 02, 04, 06, 07, 08, 12 004022001 Kadoma Wards 01, 03, 07, 08, 13, 14 004022002 Kadoma Wards 09, 10, 11, 12, 15, 16, 17 004022003 Kadoma Wards 02, 04, 05, 06 004023001 Chegutu Urban Wards 01, 02, 03, 07, 10, 12 004023002 Chegutu Urban Wards 04, 05, 06, 08, 09, 11 004024001 Kariba Urban Wards 01, 02, 03, 04, 05, 06, 07, 08, 09 004025001 Norton Wards 01, 02, 03, 04, 06, 12, 13 004025002 Norton Wards 05, 07, 08, 09, 10, 11 005001001 Binga Wards 13, 14, 16, 17, 18, 19, 20, 21, 25 005001002 Binga Wards 01, 02, 03, 04, 05, 06, 22, 23 005001003 Binga Wards 07, 08, 09, 10, 11, 12, 15, 24 005002001 Bubi Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 14, 16, 17, 18, 20, 21, 22 005002002 Bubi Wards 11, 12, 13, 15, 19, 23 005003001 Hwange Rural Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 005004001 Lupane Wards 01, 02, 03, 04, 05, 06, 08, 09, 13, 24, 25, 26, 27 005004002 Lupane Wards 14, 15, 18, 19, 21, 22, 23, 28 005004003 Lupane Wards 07, 10, 11, 12, 16, 17, 20 005005001 Nkayi Wards 01, 02, 03, 04, 05, 16, 17, 28 005005002 Nkayi Wards 11, 13, 14, 23, 24, 25, 27, 30 005005003 Nkayi Wards 06, 07, 08, 09, 10, 12, 15, 26 005005004 Nkayi Wards 18, 19, 20, 21, 22, 29 005006001 Tsholotsho Wards 01, 02, 03, 04, 07, 08, 09, 21 005006002 Tsholotsho Wards 10, 11, 12, 13, 14, 15, 20 005006003 Tsholotsho Wards 16, 17, 18, 19 005006004 Tsholotsho Wards 05, 06, 22 005007001 Umguza Wards 01, 02, 03, 04, 05, 06, 07 005007002 Umguza Wards 08, 09, 15, 16 005007003 Umguza Wards 10, 11, 12, 13, 14, 17, 18, 19 005021001 Hwange Urban Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12, 14, 15 005021002 Hwange Urban Ward 13 005022001 Victoria Falls Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11 006001001 Beitbridge Rural Wards 07, 08, 09, 10, 11, 12, 13, 14 006001002 Beitbridge Rural Wards 04, 05, 06 006001003 Beitbridge Rural Wards 01, 02, 03, 15 006002001 Bulilima Wards 01, 02, 03, 04, 05, 17, 18, 19, 20, 21 006002002 Bulilima Wards 09, 10, 11, 12, 14, 15, 16 006002003 Bulilima Wards 06, 07, 08, 13, 22 006003001 Mangwe Rural, Mangwe Urban (Plumtree) Wards 01, 02, 03, 04, 05, 05, 06, 06, 07, 08, 09, 10, 11, 12, 15, 16, 17 006003002 Mangwe Rural, Mangwe Urban (Plumtree) Wards 01, 02, 03, 04, 13, 14 006004001 Gwanda Rural Wards 06, 07, 08, 09, 13, 14, 15, 18 006004002 Gwanda Rural Wards 01, 02, 03, 04, 05, 21, 22, 23 006004003 Gwanda Rural Wards 10, 11, 12, 16, 17, 19, 20, 24 006005001 Insiza Wards 04, 08, 13, 14, 15, 16, 17, 18, 22, 23 006005002 Insiza Wards 01, 02, 03, 05, 06, 07, 11, 12 006005003 Insiza Wards09, 10, 19, 20, 21 006006001 Matobo Wards 15, 16, 17, 18, 24, 25 006006002 Matobo Wards 10, 11, 12, 13, 14, 19 006006003 Matobo Wards 05, 06, 07, 08, 09, 20 006006004 Matobo Wards 01, 02, 03, 04, 21, 22, 23 006007001 Umzingwane Wards 03, 04, 05, 06, 07, 08, 09, 10, 11, 12, 13, 14, 20 006007002 Umzingwane Wards 01, 02, 15, 16, 17, 18, 19 006021001 Gwanda Urban Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10 006022001 Beitbridge Urban Wards 01, 02, 03, 04, 05, 06 007001001 Chirumanzu Wards 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 22, 24 007001002 Chirumanzu Wards 01, 02, 05, 06, 09, 21 007001003 Chirumanzu Wards 03, 04, 07, 08, 10, 23, 25 007002001 Gokwe North Wards 10, 11, 12, 13, 35, 36 007002002 Gokwe North Wards 01, 02, 03, 28, 29, 30, 31 007002003 Gokwe North Wards 17, 18, 19, 22, 24, 25, 26 007002004 Gokwe North Wards 08, 09, 14, 34 007002005 Gokwe North Wards 06, 07, 16, 27, 32 007002007 Gokwe North Wards 04, 05, 33 007002008 Gokwe North Wards 15, 20, 21, 23 007003001 Gokwe South Wards 14, 23, 24, 25, 33 007003002 Gokwe South Wards 02, 26, 27, 29 007003003 Gokwe South Wards 01, 19, 20 007003004 Gokwe South Wards 09, 10 007003005 Gokwe South Wards 13, 16, 17 007003006 Gokwe South Wards 03, 08, 21, 22 007003007 Gokwe South Wards 04, 05, 06 007003008 Gokwe South Wards 07, 18, 31, 32 007003009 Gokwe South Wards 11, 12 007003010 Gokwe South Wards 15, 28, 30 007004001 Gweru Rural Wards 01, 02, 04, 05, 09, 15, 16, 17, 19 007004002 Gweru Rural Wards 10, 11, 12, 13, 14, 18 007004003 Gweru Rural Wards03, 06, 07, 08 007005001 Kwekwe Rural Wards 09, 12, 13, 16, 17, 18, 19, 29 007005002 Kwekwe Rural Wards 20, 21, 22 007005003 Kwekwe Rural Wards 01, 02, 03, 04, 30 007005004 Kwekwe Rural Wards 23, 24, 25, 27, 28, 33 007005005 Kwekwe Rural Wards 06, 07, 08 007005006 Kwekwe Rural Wards 10, 11, 14, 32 007005007 Kwekwe Rural Wards 05, 15, 26, 31 007006001 Mberengwa Wards 15, 16, 22, 24, 25, 26, 27, 28, 33 007006002 Mberengwa Wards 01, 02, 03, 35, 36 007006003 Mberengwa Wards 04, 05, 06, 07, 08 007006004 Mberengwa Wards 09, 10, 11, 12, 13, 14, 17, 37 007006005 Mberengwa Wards 18, 19, 20, 21, 23 007006006 Mberengwa Wards 29, 30, 31, 32, 34 007007001 Shurugwi Rural Wards 01, 02, 03, 04, 05, 06, 16, 17, 18, 19, 20, 21, 22, 23 007007002 Shurugwi Rural Wards 07, 08 ,09, 10, 11, 12, 13, 14, 15, 24 007008001 Zvishavane Rural Wards 01, 02, 03, 04, 06, 07, 08, 10, 11, 12, 13 007008002 Zvishavane Rural Wards 05, 09, 14, 15, 16, 17, 18, 19 007021001 Gweru Urban Wards 09, 10, 11, 12, 13, 14 007021002 Gweru Urban Wards 15, 16, 17 007021003 Gweru Urban Wards 06, 07, 08 007021004 Gweru Urban Wards 01, 02, 18 007021005 Gweru Urban Wards 03, 04, 05 007022001 Kwekwe Urban Wards 01, 02, 03 007022002 Kwekwe Urban Wards 04, 05, 11, 12 007022003 Kwekwe Urban Wards 06, 07, 08, 09, 10, 13, 14 007023001 Redcliff Wards 01, 02, 03, 04, 05, 06, 07, 08, 09 007024001 Zvishavane Urban Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10 007025001 Gokwe Centre Wards 01, 02, 03, 04, 05, 06 007026001 Shurugwi Urban Wards 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12, 13 008001001 Bikita Wards 04, 05, 06, 07, 09, 13 008001002 Bikita Wards 01, 02, 03, 26, 28, 29 008001003 Bikita Wards 20, 21, 22, 24, 25, 27 008001004 Bikita Wards 10, 11, 12, 19, 23, 30, 32 008001005 Bikita Wards 15, 17, 18, 31 008001006 Bikita Wards 08, 14, 16 008002001 Chiredzi Rural Wards 20, 21, 23 008002002 Chiredzi Rural Wards 06, 07, 08, 31 008002003 Chiredzi Rural Wards 09, 12, 13, 14, 15, 22 008002004 Chiredzi Rural Wards 24, 32 008002005 Chiredzi Rural Wards 19, 27, 30 008002006 Chiredzi Rural Wards 17, 26, 29 008002007 Chiredzi Rural Wards 16, 18, 28 008002008 Chiredzi Rural Wards 01, 02, 03, 04, 05, 25 008002009 Chiredzi Rural Wards 10, 11 008003001 Chivi Wards 01, 02, 03, 04, 05, 06, 08, 09, 11 008003002 Chivi Wards 25, 26, 27, 28, 29, 31 008003003 Chivi Warda 07, 10, 13, 14, 15, 17, 18 008003004 Chivi Wards 12, 16, 20, 22, 30 008003005 Chivi Wards 19, 21, 23, 24, 32 008004001 Gutu Wards 01, 02, 03, 04, 32 008004002 Gutu Wards 18, 20, 21, 22, 23, 35, 38, 40 008004003 Gutu Wards 05, 06, 07, 28, 29, 31 008004004 Gutu Wards 24, 25, 26, 27, 30, 41 008004005 Gutu Wards 10, 12, 13, 14 008004006 Gutu Wards 08, 33, 34, 37 008004007 Gutu Wards 15, 16, 36 008004008 Gutu Wards 09, 11, 17, 19, 39 008005001 Masvingo Rural Wards 01, 02, 03, 04, 05, 06, 09, 33 008005002 Masvingo Rural Wards 13, 15, 16, 17, 18 008005003 Masvingo Rural Wards 23, 24, 25, 26, 27, 28, 35 008005004 Masvingo Rural Wards 10, 21, 22, 31, 34 008005005 Masvingo Rural Wards 07, 08, 14, 32 008005006 Masvingo Rural Wards 29, 30 008005007 Masvingo Rural Wards 11, 12, 19, 20 008006001 Mwenezi Wards 04, 06, 07, 08, 11, 12, 14, 18 008006002 Mwenezi Wards 09, 10, 17 008006003 Mwenezi Wards 01, 02, 03, 05 008006004 Mwenezi Ward 13 008006005 Mwenezi Wards 15, 16 008007001 Zaka Wards 01, 02, 03, 04, 05, 07, 08, 18, 19, 33, 34 008007002 Zaka Wards 06, 11, 12, 16, 17, 22 008007003 Zaka Wards 27, 28, 29, 30, 32 008007004 Zaka Wards 15, 21, 26, 31 008007005 Zaka Wards 20, 23, 24, 25 008007006 Zaka Wards 09, 10, 13, 14 008021001 Masvingo Urban Wards 02, 03, 04, 05 008021002 Masvingo Urban Wards 01, 07 008021003 Masvingo Urban Wards 06, 08, 09, 10 008022001 Chiredzi Town Wards 01, 02, 03, 04, 05, 06, 07, 08 009001001 Harare Rural Ward 01 009021001 Harare Urban Ward 37 009021002 Harare Urban Wards 29, 30 009021003 Harare Urban Ward 15 009021004 Harare Urban Ward 23 009021005 Harare Urban Ward 43 009021006 Harare Urban Ward 33 009021007 Harare Urban Ward 41 009021008 Harare Urban Ward 09 009021009 Harare Urban Ward 16 009021010 Harare Urban Ward 42 009021011 Harare Urban Ward 40 009021012 Harare Urban Ward 32 009021013 Harare Urban Ward 22 009021014 Harare Urban Wards 03, 04 009021015 Harare Urban Ward 26 009021016 Harare Urban Ward 02 009021017 Harare Urban Wards 20, 46 009021018 Harare Urban Ward 38 009021019 Harare Urban Ward 18 009021020 Harare Urban Ward 27 009021021 Harare Urban Wards 34, 36 009021022 Harare Urban Ward 14 009021023 Harare Urban Ward 25 009021024 Harare Urban Ward 24 009021025 Harare Urban Ward 07 009021026 Harare Urban Ward 45 009021027 Harare Urban Ward 28 009021028 Harare Urban Ward 44 009021029 Harare Urban Ward 17 009021030 Harare Urban Ward 39 009021031 Harare Urban Ward 35 009021032 Harare Urban Ward 13 009021033 Harare Urban Ward 21 009021034 Harare Urban Ward 31 009021035 Harare Urban Ward 12 009021036 Harare Urban Ward 10 009021037 Harare Urban Ward 05 009021038 Harare Urban Ward 06 009021039 Harare Urban Ward 19 009021040 Harare Urban Ward 11 009021041 Harare Urban Ward 08 009022001 Chitungwiza Wards 06, 12, 13, 18 009022002 Chitungwiza Wards 01, 02, 03, 07, 08 009022003 Chitungwiza Wards 17, 19, 20 009022004 Chitungwiza Wards 22, 23 009022005 Chitungwiza Wards 09, 10, 11, 14 009022006 Chitungwiza Wards 04, 05 009022007 Chitungwiza Wards 21, 25 009022008 Chitungwiza Wards 15, 16 009022009 Chitungwiza Ward 24 009023001 Epworth Ward 01, 02 009023002 Epworth Ward 07 009023003 Epworth Ward 03, 05 009023004 Epworth Ward 06 009023005 Epworth Ward 04 GEO3_ZW2012 identifies the household's ward within Zimbabwe in 2012. Wards are the third level administrative units of the country, after districts and provinces. A GIS map (in shapefile format), corresponding to GEO3_ZW2012 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Zimbabwe 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 DHS-IPUMS-I Zimbabwe regions, 1994-2015 [consistent boundaries, GIS] 01 Manicaland 02 Mashonaland Central 03 Mashonaland East 04 Mashonaland West 05 Matabeleland North 06 Matabeleland South 07 Midlands 08 Masvingo 09 Harare 10 Bulawayo DHS_IPUMSI_ZW provides geographic codes for Zimbabwe 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_ZW indicate the major administrative unit in which the household was enumerated or surveyed. GIS shapefiles for Zimbabwe 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 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 Zimbabwe 2012: All records This variable indicates the dwelling number for this observation. This is a 7-digit numeric variable with 0 implied decimal places IPUMS Number of persons in household Zimbabwe 2012: All records 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 22 22 27 27 29 29 30 30 37 37 39 39 40 40 41 41 43 43 44 44 46 46 48 48 49 49 50 50 55 55 60 60 61 61 65 65 67 67 68 68 71 71 72 72 73 73 77 77 81 81 82 82 86 86 89 89 90 90 91 91 96 96 98 98 99 99 This variable indicates how many people are in this observation's household. IPUMS Sector Enumerator number _ _ _ _ _ _ <br />A- Identification <br />Province _ <br />District _ _ <br />Ward _ _ <br />Sector _ _ <br />EA _ _ _ <br />Household _ _ _ <br />Agriculture _ Zimbabwe 2012: All households 1 Communal areas 2 Small scale commercial farms 3 Larg scale commercial farms 4 Resettlement area 5 Urban council area 6 Administrative centre 7 Growth point or other urban area 8 State land This variable indicates in which sector of residential zoning the household is located. IPUMS Type of household Zimbabwe 2012: All households 1 Private household 2 Prison 3 Police 4 Health institution 5 Education institution 6 Hotel, guest house, or lodge 7 Other collective groups This variable indicates the household type, whether it is a private household or some other type. IPUMS Agriculture Enumerator number _ _ _ _ _ _ <br />A- Identification <br />Province _ <br />District _ _ <br />Ward _ _ <br />Sector _ _ <br />EA _ _ _ <br />Household _ _ _ <br />Agriculture _ Zimbabwe 2012: Households in resettlement area sectors [discrepancies: type I 3.7%; type II 1.8%] 1 Small scale commercial farms 2 Large scale commercial farms 3 A1 resettlement scheme 4 A2 resettlement scheme 5 Old resettlement type 8 Unknown 9 NIU (Not in universe) No information is available for this variable IPUMS Tenure of the dwelling <span class="em">F - Living conditions </span></p> <p>28. What is the tenure status of the household? </p> <div class="i1">[] 1 Owner/ Purchaser <br />[] 2 Tenant <br />[] 3 Lodger <br />[] 4 Tied accommodation <br />[] 5 Other</div> Zimbabwe 2012: Private households [discrepancies: type I 0.1%; type II 3.7%] 1 Owner or purchaser 2 Tenant 3 Lodger 4 Tied accommodation 5 Other 8 Unknown 9 NIU (Not in universe) This variable indicates the tenure status or ownership of this household. IPUMS Dwelling unit type <span class="em">F - Living conditions </span></p> <p>29. Type of dwelling unit </p> <div class="i1">[] 1 Traditional <br />[] 2 Mixed <br />[] 3 Detached <br />[] 4 Semi- Detached <br />[] 5 Flat/ Townhouse <br />[] 6 Shack <br />[] 7 Other</div> Zimbabwe 2012: Private households [discrepancies: type I 0.1%; type II 3.8%] 1 Traditional 2 Mixed 3 Detached 4 Semi-detached 5 Flat or townhouse 6 Shack 7 Other 8 Unknown 9 NIU (Not in universe) This variable indicates the type of construction for this household. IPUMS Electricity <span class="em">F - Living conditions </span></p> <p>30. Does dwelling unit have electricity? </p> <div class="i1">[] 1 Yes<br />[] 2 No</div> Zimbabwe 2012: Private households [discrepancies: type I 0.1%; type II 3.9%] 1 Yes 2 No 8 Unknown 9 NIU (Not in universe) This variable indicates whether the household has electricity. IPUMS Source of water <span class="em">F - Living conditions </span></p> <p>Water for drinking and cooking</p> <p>31a. Main water source </p> <div class="i1">[] 1 Piped water inside house <br />[] 2 Piped water outside house <br />[] 3 Communal tap <br />[] 4 Well/ Borehole Protected <br />[] 5 Well- Unprotected <br />[] 6 River/ Stream/ Dam <br />[] 7 Other (specify below ____)</div> Zimbabwe 2012: Private households [discrepancies: type I 0.1%; type II 4.1%] 1 Piped water inside house 2 Piped water outside house 3 Communal tape 4 Well or borehole (protected) 5 Well (unprotected) 6 River, stream, or dam 7 Other specify 8 Unknown 9 NIU (Not in universe) This variable indicates what source this household uses for water. IPUMS Distance to water source <span class="em">F - Living conditions </span></p> <p>Water for drinking and cooking</p> <p>31b. Distance to water source </p> <div class="i1">[] 1 On premises <br />[] 2 Less than 500m <br />[] 3 500m to 1km <br />[] 4 more than 1km</div> Zimbabwe 2012: Private households [discrepancies: type I 0.1%; type II 4.3%] 1 On premises 2 Less than 500m 3 500m to 1km 4 More than 1km 8 Unknown 9 NIU (Not in universe) This variable indicates the distance from the household to the source of water. IPUMS Toilet facility <span class="em">F - Living conditions </span></p> <p>32. What type of toilet facility is used most by this household? </p> <div class="i1">[] 1 Flush <br />[] 2 Blair <br />[] 3 Pit<br />[] 4 Communal <br />[] 5 None</div> Zimbabwe 2012: Private households [discrepancies: type I 0.1%; type II 3.9%] 1 Flush 2 Blair 3 Pit 4 Communal 5 None 8 Unknown 9 NIU (Not in universe) This variable indicates the type of toilet facility this household uses. IPUMS Energy for cooking <span class="em">F - Living conditions </span></p> <p>33. What is the household's main source of energy for cooking?</p> <div class="i1">[] 1 Wood <br />[] 2 Paraffin <br />[] 3 Electricity <br />[] 4 Gas <br />[] 5 Coal <br />[] 6 Other (specify below____)</div> Zimbabwe 2012: Private households [discrepancies: type I 0.1%; type II 3.8%] 1 Wood 2 Paraffin 3 Electricity 4 Gas 5 Coal 6 Other 8 Unknown 9 NIU (Not in universe) This variable indicates the fuel source used for cooking by this household. IPUMS Number of deaths (last 12 months) <span class="em">G - Deaths in the household </span></p> <p>34. Did any deaths occur in the household in the last twelve months?</p> <div class="i1">[] 1 Yes (If yes, go to question 35)<br />[] 2 No</div> Zimbabwe 2012: All households 1 1 2 2 3 3 This variable indicates the number of deaths in the household in the last 12 months. IPUMS Strata Zimbabwe 2012: 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 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 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 Number of female 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+ 98 Unknown 99 NIU (not in universe) CHSURVF indicates the number of female children ever born to a woman still living at the time of the census. IPUMS Number of male 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+ 98 Unknown 99 NIU (not in universe) CHSURVM indicates the number of male children ever born to a woman still living at the time of the census. 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 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 Number of children surviving from last birth 1 1 2 2 3 3 4 4 8 Unknown 9 NIU (not in universe) LASTBSURV indicates the number of children from a woman's last birth occurrence who are still living. 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 Country of birth 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11005 British Indian Ocean Territory 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11051 Ethiopia (including Eritrea) 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, other or n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15021 Upper Volta 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15081 Guinea-Bissau and Cape Verde 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15180 Canary Islands 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21200 St. Croix 21210 St. John 21220 St. Lucia 21230 St Thomas 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21991 Caribbean commonwealth, n.s. 21999 Caribbean, other or n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, other or n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, other or n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32042 India/Pakistan/Bangladesh/Sri Lanka 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32101 Pakistan/Bangladesh 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32999 South-Central Asia, other or n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33999 South-Eastern Asia, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34071 Israel/Palestine 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34111 West Bank 34112 Gaza Strip 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41991 Albania, Bulgaria, Czech, Hungary, Romania, Yugoslavia 41992 Central-Eastern Europe 41999 Eastern Europe, other or n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43121 Spain/Portugal 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43991 Gibraltar/Malta 43992 Portugal/Greece 43993 Italy, Holy See, San Marino 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44021 Belgium/Luxemburg 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44042 West Germany 44043 Germany/Austria 44044 Mecklenburg-Schwerin 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44991 Belgium, Denmark, Luxembourg, Netherlands 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (original 15) 49994 Other European Union (not original 15) 49999 Europe, other or n.s. 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53060 Federated States of Micronesia 53999 Micronesia, other or n.s. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 80000 AT SEA 90000 Other countries n.s. 99999 Unknown BPLCOUNTRY indicates the person's country of birth. IPUMS Citizenship 1 Citizen, not specified 2 Citizen by birth 3 Naturalized citizen 4 Not a citizen 5 Without citizenship, stateless 8 Unknown 9 NIU (not in universe) CITIZEN indicates the person's citizenship status within the country in which they were enumerated. IPUMS Country of citizenship 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, other or n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt/United Arab Rep. 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21220 St. Lucia 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21999 Caribbean, other or n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, other or n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24021 Canada, First Nations 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, other or n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32990 Burma, India, Pakistan, Ceylon 32999 South-Central Asia, other or n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33991 Laos and Cambodia 33992 Malaysia and Singapore 33999 South-Eastern Asia, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41992 Central-Eastern Europe 41999 Eastern Europe, other or n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42121 Britain 42122 Scotland 42123 Wales 42990 Nordic countries 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44011 Austro-Hungarian 44020 Belgium 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44041 East Germany 44042 West Germany 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (Original 15) 49994 Other European Union 49999 Europe, other or n.s. 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53999 Micronesia, other or n.s. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 90000 Other countries n.s. 99998 No citizenship/nationality 99999 Unknown NATION indicates the person's country of citizenship. IPUMS Has birth certificate or birth is registered 1 Yes 2 No 3 Respodent does not know 8 Unknown 9 NIU (not in universe) BTHCERT indicates whether the person has a birth certificate or their own birth is registered. 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 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, Zimbabwe 00 NIU (not in universe) 10 None 21 Preschool, grade 1 22 Preschool, grade 2 23 Preschool, grade 3 29 Preschool, grade unknown 31 Primary, grade 1 32 Primary, grade 2 33 Primary, grade 3 34 Primary, grade 4 35 Primary, grade 5 36 Primary, grade 6 37 Primary, grade 7 38 Primary, grade unknown 41 Lower secondary, grade 1 42 Lower secondary, grade 2 43 Lower secondary, grade 3 44 Lower secondary, grade 4 45 Upper secondary, grade 5 46 Upper secondary, grade 6 49 Secondary, grade unknown 51 Tertiary, certificate or diploma after primary 52 Tertiary, certificate or diploma after secondary 53 Tertiary, undergraduate or graduate studies 59 Tertiary, unknown level 98 Unknown EDUCZW indicates the person's educational attainment in Zimbabwe in terms of the level of schooling completed. 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 Migration status, 10 years 00 NIU (not in universe) 10 Same major administrative unit 11 Same major, same minor administrative unit 12 Same minor administrative unit, same house 13 Same minor administrative unit, different house 14 Same major, different minor administrative unit 20 Different major administrative unit 30 Abroad 99 Unknown/missing MIGRATE0 indicates the person's place of residence 10 years ago. The first digit records movement across major administrative divisions and countries. The second digit reports movement across minor administrative divisions, for samples in which that detail is available. IPUMS 1st subnational geographic level of residence 10 years prior to survey, world [consistent boundaries over time] 368001 In residential place of birth [Governorate: Iraq] 368002 In current governate [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] 368099 NIU (not in universe) [Governorate: Iraq] 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] 426001 Butha Buthe [District: Lesotho] 426002 Leribe [District: Lesotho] 426003 Berea [District: Lesotho] 426004 Maseru [District: Lesotho] 426005 Mafeteng [District: Lesotho] 426006 Mohale's Hoek [District: Lesotho] 426007 Quthing [District: Lesotho] 426008 Qacha's Nek [District: Lesotho] 426009 Mokhotlong [District: Lesotho] 426010 Thaba-Tseka [District: Lesotho] 426097 Abroad [District: Lesotho] 426099 NIU [District: Lesotho] 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] 608009 Batanes [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] 686001 Dakar [Region: Senegal] 686002 Ziguinchor [Region: Senegal] 686003 Diourbel [Region: Senegal] 686004 Saint Louis, Louga, Matam [Region: Senegal] 686005 Tambacounda, Kedougou [Region: Senegal] 686006 Kaolack, Fatick, Kaffrine [Region: Senegal] 686007 Thiès [Region: Senegal] 686010 Kolda, Sedhiou [Region: Senegal] 686097 Abroad [Region: Senegal] 686099 NIU (not in universe) [Region: Senegal] 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] 724090 Other Spanish territories in 1970 [Communities & autonomous city: Spain] 724097 Foreign country [Communities & autonomous city: Spain] 724098 Unknown [Communities & autonomous city: Spain] 724999 NIU (not in universe) [Communities & autonomous city: Spain] 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] 780099 NIU (not in universe) [Region: Trinidad and Tobago] 834001 Dodoma [Region: Tanzania] 834002 Arusha, Manyara [Region: Tanzania] 834003 Kilimanjaro [Region: Tanzania] 834004 Tanga [Region: Tanzania] 834005 Morogoro [Region: Tanzania] 834006 Pwani [Region: Tanzania] 834007 Dar es Salaam [Region: Tanzania] 834008 Lindi [Region: Tanzania] 834009 Mtwara [Region: Tanzania] 834010 Ruvuma [Region: Tanzania] 834011 Iringa, Njombe [Region: Tanzania] 834012 Mbeya [Region: Tanzania] 834013 Singida [Region: Tanzania] 834014 Tabora [Region: Tanzania] 834015 Katavi, Rukwa [Region: Tanzania] 834016 Kigoma [Region: Tanzania] 834019 Geita, Kagera, Mwanza, Shinyanga, Simiyu [Region: Tanzania] 834020 Mara [Region: Tanzania] 834051 Zanzibar North [Region: Tanzania] 834052 Zanzibar South [Region: Tanzania] 834053 Zanzibar Town/West [Region: Tanzania] 834054 Pemba North [Region: Tanzania] 834055 Pemba South [Region: Tanzania] 834097 Abroad [Region: Tanzania] 716000 Bulawayo [Province: Zimbabwe] 716001 Manicaland [Province: Zimbabwe] 716002 Mashonaland Central [Province: Zimbabwe] 716003 Mashonaland East [Province: Zimbabwe] 716004 Mashonaland West [Province: Zimbabwe] 716005 Matabeleland North [Province: Zimbabwe] 716006 Matabeleland South [Province: Zimbabwe] 716007 Midlands [Province: Zimbabwe] 716008 Masvingo [Province: Zimbabwe] 716009 Harare [Province: Zimbabwe] 716097 Abroad [Province: Zimbabwe] 716098 Unknown [Province: Zimbabwe] 716099 NIU (Not in universe) [Province: Zimbabwe] GEOMIG1_10 indicates the major administrative unit in which the person resided ten years prior to the survey. Only intra-national migrations are recorded; however, the variable incorporates geographies for every country that lists place of residence ten year ago, to enable comparative analysis of subnational migration. Foreign migrants are coded 097 or 997. Codes for GEOMIG1_10 match the geographic codes in GEOLEV1 (current place of residence). For similar information for different time intervals since migration, see variables GEOMIG1_P, GEOMIG1_1, and GEOMIG1_5. More on migration and geography can be found here. IPUMS Province of residence 10 years ago, Zimbabwe; consistent boundaries, GIS 716000 Bulawayo 716001 Manicaland 716002 Mashonaland Central 716003 Mashonaland East 716004 Mashonaland West 716005 Matabeleland North 716006 Matabeleland South 716007 Midlands 716008 Masvingo 716009 Harare 716097 Abroad 716098 Unknown 716099 NIU (Not in universe) MIG1_10_ZW indicates the person's province of residence within Zimbabwe 10 years ago. 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 District of residence 10 years ago, Zimbabwe; consistent boundaries, GIS 716000021 Bulawayo Urban 716001001 Buhera 716001002 Chimanimani 716001003 Chipinge Rural 716001004 Makoni 716001005 Mutare Rural 716001006 Mutasa 716001007 Nyanga 716001021 Mutare Urban 716001022 Rusape Urban 716001023 Chipinge Urban 716002001 Bindura Rural 716002002 Muzarabani 716002003 Guruve 716002004 Mazowe, Mvurwi 716002005 Mt Darwin 716002006 Rushinga 716002007 Shamva 716002008 Mbire 716002021 Bindura Urban 716003001 Chikomba 716003002 Goromonzi 716003003 Hwedza 716003004 Marondera Rural 716003005 Mudzi 716003006 Murehwa 716003007 Mutoko 716003008 Seke 716003009 Uzumba Maramba Pfungwe 716003021 Marondera Urban 716003023 Ruwa 716004001 Chegutu 716004002 Hurungwe, Karoi 716004003 Mhondoro-Ngezi 716004004 Kariba Rural 716004005 Makonde 716004006 Zvimba 716004007 Sanyati 716004021 Chinhoyi 716004022 Kadoma 716004023 Chegutu Urban 716004024 Kariba Urban 716004025 Norton 716005001 Binga 716005002 Bubi 716005003 Hwange Rural 716005004 Lupane 716005005 Nkayi 716005006 Tsholotsho 716005007 Umguza 716005021 Hwange Urban 716005022 Victoria Falls 716006001 Beitbridge Rural 716006002 Bulilima 716006003 Mangwe Rural, Mangwe Urban (Plumtree) 716006004 Gwanda Rural 716006005 Insiza 716006006 Matobo 716006007 Umzingwane 716006021 Gwanda Urban 716006022 Beitbridge Urban 716007001 Chirumanzu 716007002 Gokwe North 716007003 Gokwe South 716007004 Gweru Rural 716007005 Kwekwe Rural 716007006 Mberengwa 716007007 Shurugwi Rural 716007008 Zvishavane Rural 716007021 Gweru Urban 716007022 Kwekwe Urban 716007023 Redcliff 716007024 Zvishavane Urban 716007025 Gokwe Centre 716007026 Shurugwi Urban 716008001 Bikita 716008002 Chiredzi Rural 716008003 Chivi 716008004 Gutu 716008005 Masvingo Rural 716008006 Mwenezi 716008007 Zaka 716008021 Masvingo Urban 716008022 Chiredzi Town 716009001 Harare Rural 716009021 Harare Urban 716009022 Chitungwiza 716009023 Epworth 716097097 Foreign Country 716098098 Unknown 716099099 NIU (not in universe) MIG2_10_ZW indicates the person's district of residence 10 years ago within Zimbabwe. Migration district codes for MIG2_10_ZW are compatible with codes for GEO2_ZW. 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 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 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 Difficulty hearing (Washington group) 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) WGHEAR indicates the person's level of difficulty in hearing, even if using a hearing aid. IPUMS Difficulty seeing (Washington group) 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) WGVISION indicates the person's level of difficulty in seeing, even while wearing glasses. IPUMS Person number (within household) Zimbabwe 2012: All records 00 Household record 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98 99 99 This variable indicates the person number for this observation. IPUMS Relationship to the head of household <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>2. What is [the respondent] relationship to the head of household? </p> <div class="i1">[] 1. Head <br />[] 2 Spouse <br />[] 3 Son/daughter <br />[] 4 Parent <br />[] 5 Grandson/daughter<br />[] 6 Brother/sister <br />[] 7 Other relative <br />[] 8 Non relative</div> Zimbabwe 2012: Persons in private households [discrepancies: type I none; type II 0.2%] 01 Head 02 Spouse 03 Son or daughter 04 Parent 05 Grandson or granddaughter 06 Brother or sister 07 Other relative 08 Not relative 98 Unknown 99 NIU (Not in universe) This variable indicates the relationship to the head of household for this person. IPUMS Sex <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>3. Is [the respondent] male or female?</p> <div class="i1">[] 1 Male<br />[] 2 Female</div> Zimbabwe 2012: All persons 1 Male 2 Female This variable indicates the person's sex. IPUMS Age <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>4. How old was [the respondent] at his or her last birthday? </p> <div class="i1">Enter age in completed years ("00" for children less than one year). Example: Name is 37. [First digit in the first box and the second digit in the second box]<br /><br />Age _ _</div> Zimbabwe 2012: All persons 000 Less than 1 001 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+ 998 Unknown This variable indicates the person's age. IPUMS Birth certificate <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>5. Does (the respondent) have a birth certificate? </p> <div class="i1">[] 1 Yes <br />[] 2 No <br />[] 9 Not known</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has their birth certificate. IPUMS Province or country of birth <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>6. Where was (the respondent) born? </p> <div class="i1">Enter district or country code.<br /><br />Code _ _ _</div> Zimbabwe 2012: All persons 02 Bulawayo 10 Manicaland (rural) 12 Manicaland (urban) 20 Mashonaland Central (rural) 22 Mashonaland Central (urban) 30 Mashonaland East (rural) 32 Mashonaland East (urban) 40 Mashonaland West (rural) 42 Mashonaland West (urban) 50 Matabeleland North (rural) 52 Matabeleland North (urban) 60 Matabeleland South (rural) 62 Matabeleland South (urban) 70 Midlands (rural) 72 Midlands (urban) 80 Masvingo (rural) 82 Masvingo (urban) 90 Harare (rural) 92 Harare (urban) 94 Other countries within Africa 95 Other countries outside Africa 98 Unknown This variable indicates the province or foreign region that the person was born in. IPUMS District or country of birth <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>6. Where was (the respondent) born? </p> <div class="i1">Enter district or country code.<br /><br />Code _ _ _</div> Zimbabwe 2012: All persons 021 Bulawayo 101 Buhera 102 Chimanimani 103 Chipinge 104 Makoni 105 Mutare Rural 106 Mutasa 107 Nyanga Rural 121 Mutare 122 Rusape 123 Chipinge 201 Bindura Rural 202 Centenary 203 Guruve 204 Mazowe Rural 205 Mount Darwin 206 Rushinga 207 Shamva 208 Mbire 221 Bindura 222 Trojan Mine 229 Mashonaland Central (urban), unknown district 301 Chikomba 302 Goromonzi 303 Hwedza 304 Marondera Rural 305 Mudzi 306 Murehwa 307 Mutoko 308 Seke 309 Uzumba Maramba Pfungwe 321 Marondera 322 Chivhu Local Board 323 Mutoko Growth Point 401 Chegutu Rural 402 Hurungwe 403 Kadoma Rural 404 Kariba Rural 405 Makonde 406 Zvimba 407 Sanyati 421 Chinhoyi 422 Kadoma 423 Chegutu 424 Kariba 425 Norton 426 Karoi 501 Binga 502 Bubi 503 Hwange Rural 504 Lupane 505 Nkayi 506 Tsholotsho 507 Umguza 521 Hwange 522 Victoria Falls 601 Beitbridge Rural 602 Bulilimamangwe North 603 Bulilimamangwe South 604 Gwanda Rural 605 Insiza 606 Matobo 607 Umzingwane 621 Gwanda 622 Beitbridge 623 Plumtree 701 Chirumhanzu 702 Gokwe North 703 Gokwe South 704 Gweru Rural 705 Kwekwe Rural 706 Mberengwa 707 Shurugwi 708 Zvishavane 721 Gweru 722 Kwekwe 723 Redcliff 724 Zvishavane Mine 725 Zvishavane Town 726 Shurugwi Mine 801 Bikita 802 Chiredzi 803 Chivi 804 Gutu 805 Masvingo Rural 806 Mwenezi 807 Zaka 821 Masvingo 822 Chiredzi Town 901 Harare Rural 921 Harare Urban 922 Chitungwiza 923 Epworth 941 Botswana 942 Malawi 943 Mozambique 944 South Africa 945 Zambia 949 Other African countries 951 United Kingdom 952 Other European countries 953 American countries 954 Asian countries 959 Other countries 998 Unknown This variable indicates the district or foreign region that the person was born in. IPUMS Province or country of usual residence <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>7. Where does (the respondent) usually live? </p> <div class="i1">Enter district or country code.<br /><br />Code _ _ _</div> Zimbabwe 2012: All persons 02 Bulawayo 10 Manicaland (rural) 12 Manicaland (urban) 20 Mashonaland Central (rural) 22 Mashonaland Central (urban) 30 Mashonaland East (rural) 32 Mashonaland East (urban) 40 Mashonaland West (rural) 42 Mashonaland West (urban) 50 Matabeleland North (rural) 52 Matabeleland North (urban) 60 Matabeleland South (rural) 62 Matabeleland South (urban) 70 Midlands (rural) 72 Midlands (urban) 80 Masvingo (rural) 82 Masvingo (urban) 90 Harare (rural) 92 Harare (urban) 94 Other countries within Africa 95 Other countries outside Africa 98 Unknown This variable indicates the person's usual province of residence. IPUMS District or country of usual residence <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>7. Where does (the respondent) usually live? </p> <div class="i1">Enter district or country code.<br /><br />Code _ _ _</div> Zimbabwe 2012: All persons 021 Bulawayo 101 Buhera 102 Chimanimani 103 Chipinge 104 Makoni 105 Mutare Rural 106 Mutasa 107 Nyanga Rural 121 Mutare 122 Rusape 123 Chipinge 201 Bindura Rural 202 Centenary 203 Guruve 204 Mazowe Rural 205 Mount Darwin 206 Rushinga 207 Shamva 208 Mbire 221 Bindura 222 Trojan Mine 229 Mashonaland Central (urban), unknown district 301 Chikomba 302 Goromonzi 303 Hwedza 304 Marondera Rural 305 Mudzi 306 Murehwa 307 Mutoko 308 Seke 309 Uzumba Maramba Pfungwe 321 Marondera 322 Chivhu Local Board 323 Mutoko Growth Point 401 Chegutu Rural 402 Hurungwe 403 Kadoma Rural 404 Kariba Rural 405 Makonde 406 Zvimba 407 Sanyati 421 Chinhoyi 422 Kadoma 423 Chegutu 424 Kariba 425 Norton 426 Karoi 501 Binga 502 Bubi 503 Hwange Rural 504 Lupane 505 Nkayi 506 Tsholotsho 507 Umguza 521 Hwange 522 Victoria Falls 601 Beitbridge Rural 602 Bulilimamangwe North 603 Bulilimamangwe South 604 Gwanda Rural 605 Insiza 606 Matobo 607 Umzingwane 621 Gwanda 622 Beitbridge 623 Plumtree 701 Chirumhanzu 702 Gokwe North 703 Gokwe South 704 Gweru Rural 705 Kwekwe Rural 706 Mberengwa 707 Shurugwi 708 Zvishavane 721 Gweru 722 Kwekwe 723 Redcliff 724 Zvishavane Mine 725 Zvishavane Town 726 Shurugwi Mine 801 Bikita 802 Chiredzi 803 Chivi 804 Gutu 805 Masvingo Rural 806 Mwenezi 807 Zaka 821 Masvingo 822 Chiredzi Town 901 Harare Rural 921 Harare Urban 922 Chitungwiza 923 Epworth 941 Botswana 942 Malawi 943 Mozambique 944 South Africa 945 Zambia 949 Other African countries 951 United Kingdom 952 Other European countries 953 American countries 954 Asian countries 959 Other countries 998 Unknown This variable indicates the person's usual district of residence. IPUMS Province or country of residence 10 years ago <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>8. Where was (the respondent) living (last census year) in August 2002? </p> <div class="i1">Enter district or country code.<br /><br />[Question asked only of persons 10 years and above] <br /><br />Code _ _ _</div> Zimbabwe 2012: Persons age 10+ [discrepancies: type I none; type II 1%] 00 Bulawayo 01 Manicaland 02 Mashonaland Central 03 Mashonaland East 04 Mashonaland West 05 Matabeleland North 06 Matabeleland South 07 Midlands 08 Masvingo 09 Harare 94 Other countries within Africa 95 Other countries outside Africa 98 Unknown 99 NIU (Not in universe) This variable indicates the person's province or country of residence 10 years ago. IPUMS District or country of residence 10 years ago <span class="em">B- For all persons </span> <br />[Question 1 to 7 were asked of all persons]</p> <p>8. Where was (the respondent) living (last census year) in August 2002? </p> <div class="i1">Enter district or country code.<br /><br />[Question asked only of persons 10 years and above] <br /><br />Code _ _ _</div> Zimbabwe 2012: Persons age 10+ [discrepancies: type I none; type II 1%] 021 Bulawayo 101 Buhera 102 Chimanimani 103 Chipinge 104 Makoni 105 Mutare Rural 106 Mutasa 107 Nyanga Rural 121 Mutare 122 Rusape 123 Chipinge 201 Bindura Rural 202 Centenary 203 Guruve 204 Mazowe Rural 205 Mount Darwin 206 Rushinga 207 Shamva 208 Mbire 221 Bindura 222 Trojan Mine 229 Mashonaland Central (urban), unknown district 301 Chikomba 302 Goromonzi 303 Hwedza 304 Marondera Rural 305 Mudzi 306 Murehwa 307 Mutoko 308 Seke 309 Uzumba Maramba Pfungwe 321 Marondera 322 Chivhu Local Board 323 Mutoko Growth Point 401 Chegutu Rural 402 Hurungwe 403 Kadoma Rural 404 Kariba Rural 405 Makonde 406 Zvimba 407 Sanyati 421 Chinhoyi 422 Kadoma 423 Chegutu 424 Kariba 425 Norton 426 Karoi 501 Binga 502 Bubi 503 Hwange Rural 504 Lupane 505 Nkayi 506 Tsholotsho 507 Umguza 521 Hwange 522 Victoria Falls 601 Beitbridge Rural 602 Bulilimamangwe North 603 Bulilimamangwe South 604 Gwanda Rural 605 Insiza 606 Matobo 607 Umzingwane 621 Gwanda 622 Beitbridge 623 Plumtree 701 Chirumhanzu 702 Gokwe North 703 Gokwe South 704 Gweru Rural 705 Kwekwe Rural 706 Mberengwa 707 Shurugwi 708 Zvishavane 721 Gweru 722 Kwekwe 723 Redcliff 724 Zvishavane Mine 725 Zvishavane Town 726 Shurugwi Mine 801 Bikita 802 Chiredzi 803 Chivi 804 Gutu 805 Masvingo Rural 806 Mwenezi 807 Zaka 821 Masvingo 822 Chiredzi Town 901 Harare Rural 921 Harare Urban 922 Chitungwiza 923 Epworth 941 Botswana 942 Malawi 943 Mozambique 944 South Africa 945 Zambia 949 Other African countries 951 United Kingdom 952 Other European countries 953 American countries 954 Asian countries 959 Other countries 998 Unknown 999 NIU (Not in universe) This variable indicates the district where this person lived 10 years ago. IPUMS Ethnic origin <span class="em">B- For all persons </span> <br />[Questions 9 and 10 were asked of all persons]</p> <p>9. What is (the respondent's) ethnic origin? </p> <div class="i1">[] 1 African <br />[] 2 European <br />[] 3 Asiatic <br />[] 4 Mixed race <br />[] 5 Other</div> Zimbabwe 2012: All persons 1 African 2 European 3 Asiatic 4 Mixed race 5 Other 8 Unknown This variable indicates the respondent's ethnic origin. IPUMS Citizenship <span class="em">B- For all persons </span> <br />[Questions 9 and 10 were asked of all persons]</p> <p>10. What is (the respondent's) citizenship? </p> <div class="i1">Enter country code ("000" for Zimbabwe)<br /><br />Country _ _ _</div> Zimbabwe 2012: All persons 000 Zimbabwe 941 Botswana 942 Malawi 943 Mozambique 944 South Africa 945 Zambia 949 Other African countries 951 United Kingdom 952 Other European countries 953 American countries 954 Asian countries 959 Other countries 998 Unknown This variable indicates the respondent's citizenship. IPUMS Marital status 11. What is (the respondent's) marital status? </p> <div class="i1">[Question was asked of persons age 15 years and above]<br /><br />[] 1 Never married <br />[] 2 Married <br />[] 3 Divorced/ separated <br />[] 4 Widowed</div> Zimbabwe 2012: Persons age 15+ [discrepancies: type I none; type II 0.5%] 1 Never married 2 Married 3 Divorced or separated 4 Widowed 8 Unknown 9 NIU (Not in universe) This variable indicates the respondent's marital status. IPUMS Father alive <span class="em">For persons age 17 years and below</span> <br />[Question 12 and 13 were asked of persons age 17 years and below]</p> <p>12. Is (the respondent's) father by birth alive? </p> <div class="i1">[] 1 Yes <br />[] 2 No <br />[] 9 Not known</div> Zimbabwe 2012: Persons age 17 or younger [discrepancies: type I trace; type II 1.4%] 1 Yes 2 No 8 Unknown 9 NIU (Not in universe) This variable indicates whether the respondent's father is alive. IPUMS Mother alive <span class="em">For persons age 17 years and below</span> <br />[Question 12 and 13 were asked of persons age 17 years and below]</p> <p>13. Is (the respondent's) mother by birth alive? </p> <div class="i1">[] 1 Yes <br />[] 2 No <br />[] 9 Not known</div> Zimbabwe 2012: Persons age 17 or younger [discrepancies: type I trace; type II 0.9%] 1 Yes 2 No 8 Unknown 9 NIU (Not in universe) This variable indicates whether the respondent's mother is alive. IPUMS Difficulty moving 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">a. Difficulty moving</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has difficulty moving. IPUMS Totally blind 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">b. Totally blind</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person is totally blind. IPUMS Difficulty seeing 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">c. Difficulty seeing</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has difficulty seeing. IPUMS Difficulty speaking 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">d. Difficulty speaking</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has difficulty speaking. IPUMS Deaf 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">e. Deaf</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person is deaf. IPUMS Difficulty hearing 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">f. Difficulty hearing</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has difficulty hearing. IPUMS Difficulty learning 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">g. Difficulty learning/ mental handicap</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has any difficulty learning. IPUMS Chronic fits 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">h. Chronic fits/ Epilepsy</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has chronic fits or epilepsy. IPUMS Mental illness 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">i. Strange behaviors/ mental illness</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has a mental illness. IPUMS Lack of feeling in hands and feet (leprosy) 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">j. Lack of feeling- hands or feet/ leprosy</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has a disability such as leprosy which causes a lack of feeling in the hands or feet. IPUMS Albinism 14. Does (the respondent) have any of the following disabilities? </p> <div class="i1">[Question was asked of all persons.]</div><div class="i1">k. Albinism</div><div class="i2">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: All persons 1 Yes 2 No 8 Unknown This variable indicates whether the person has albinism. IPUMS Ever been to school <span class="em">C. Education - for persons age 3 years and older </span> <br />[Questions 15 and 16 were asked of persons age 3 and older]</p> <p>15. Has (the respondent) ever been to school?</p> <div class="i1">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: Persons age 3+ [discrepancies: type I none; type II 0.3%] 1 Yes, attended school 2 No, never attended 8 Unknown 9 NIU (Not in universe) This variable indicates whether the person has ever been to school. IPUMS Highest education level completed <span class="em">C. Education - for persons age 3 years and older </span> <br />[Questions 15 and 16 were asked of persons age 3 and older]</p> <p>16. What is the highest level and grade of education completed by (the respondent)? </p> <div class="i1">[] Level 0</div><div class="i2">Grade <br />[] 1<br />[] 2<br />[] 3</div><div class="i1">[] Level 1</div><div class="i2">Grade <br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7</div><div class="i1">[] Level 2</div><div class="i2">Grade <br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6</div><div class="i1">[] Level 3</div><div class="i2">[] 1 Certificate / diploma after primary<br />[] 2 Certificate / diploma after secondary<br />[] 3 Graduate / postgraduate</div><div class="i1">[] 8 None<br />[] 9 Not known</div> Zimbabwe 2012: Persons age 3+ who have ever been to school [discrepancies: type I 1.3%; type II 0.1%] Pre-school 1 Primary 2 Secondary 3 Tertiary 4 None 8 Unknown 9 NIU (Not in universe) This variable indicates the highest level of school completed. IPUMS Educational attainment <span class="em">C. Education - for persons age 3 years and older </span> <br />[Questions 15 and 16 were asked of persons age 3 and older]</p> <p>15. Has (the respondent) ever been to school?</p> <div class="i1">[] 1 Yes <br />[] 2 No</div><p>16. What is the highest level and grade of education completed by (the respondent)? </p> <div class="i1">[] Level 0</div><div class="i2">Grade <br />[] 1<br />[] 2<br />[] 3</div><div class="i1">[] Level 1</div><div class="i2">Grade <br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7</div><div class="i1">[] Level 2</div><div class="i2">Grade <br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6</div><div class="i1">[] Level 3</div><div class="i2">[] 1 Certificate / diploma after primary<br />[] 2 Certificate / diploma after secondary<br />[] 3 Graduate / postgraduate</div><div class="i1">[] 8 None<br />[] 9 Not known</div> Zimbabwe 2012: Persons age 3+ who have ever been to school [discrepancies: type I 1.2%; type II 0.1%] 01 Pre-school, grade 1 02 Pre-school, grade 2 03 Pre-school, grade 3 08 Pre-school, unknown grade 11 Primary, grade 1 12 Primary, grade 2 13 Primary, grade 3 14 Primary, grade 4 15 Primary, grade 5 16 Primary, grade 6 17 Primary, grade 7 18 Primary, unknown grade 21 Secondary, grade 1 22 Secondary, grade 2 23 Secondary, grade 3 24 Secondary, grade 4 25 Secondary, grade 5 26 Secondary, grade 6 28 Secondary, unknown grade 31 Tertiary, certificate or diploma after primary 32 Tertiary, certificate or diploma after secondary 33 Tertiary, graduate or postgraduate 38 Tertiary, unknown level 80 None 98 Unknown 99 NIU (Not in universe) This variable indicates the highest grade completed. IPUMS School attendance <span class="em">C- Education for persons 3-24 </span> <br />[Questions 17 to 19 were asked of persons 3- 24 years]</p> <p>17. Is (the respondent) currently attending school? </p> <div class="i1">[] 1 Yes<br />[] 2 No</div> Zimbabwe 2012: Persons ages 3 to 24 who have ever attended school [discrepancies: type I 2.6%; type II 0.4%] 1 Yes, currently attending 2 No, left school 8 Unkown 9 NIU (Not in universe) This variable indicates whether the person is currently attending school. IPUMS Ever attended school during the current school year <span class="em">C- Education for persons 3-24 </span> <br />[Questions 17 to 19 were asked of persons 3- 24 years]</p> <p>18. Was (the respondent) ever in attendance in school at any point during this year?</p> <div class="i1">[] 1 Yes<br />[] 2 No</div> Zimbabwe 2012: Persons ages 3 to 24 who have ever attended school but are not currently attending [discrepancies: Type I 5.4%; Type II 0.2%] 1 Attended 2 Never attended 3 Left school 8 Unkown 9 NIU (Not in universe) This variable indicates whether the person has attended school at all during the current school year. IPUMS Current level in school <span class="em">C- Education for persons 3-24 </span> <br />[Questions 17 to 19 were asked of persons 3- 24 years]</p> <p>19. During this school year, what level and grade is (the respondent) attending/ was enrolled in? </p> <div class="i1">Level</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 9</div><div class="i1">Grade</div><div class="i2">[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 9</div> Zimbabwe 2012: Persons ages 3 to 24 who are currently attending school or have attended school during the current school year [discrepancies: type I 1.0%; type II 0.1%] Pre school 1 Primary 2 Secondary 3 Tertiary 8 Unknown 9 NIU (Not in universe) This variable indicates the person's current level in school. IPUMS Current grade in school <span class="em">C- Education for persons 3-24 </span> <br />[Questions 17 to 19 were asked of persons 3- 24 years]</p> <p>19. During this school year, what level and grade is (the respondent) attending/ was enrolled in? </p> <div class="i1">Level</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 9</div><div class="i1">Grade</div><div class="i2">[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 9</div> Zimbabwe 2012: Persons ages 3 to 24 who are currently attending school or have attended school during the current school year [discrepancies: type I 1.0%; type II 0.1%] 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 Unknown 9 NIU (Not in universe) This variable indicates the person's current grade in school. IPUMS Main economic activity (last 12 months) <span class="em">D- For persons age 10 years and above </span> <br />[Questions 20 to 22 were asked of persons age 10 years and above]</p> <p>20. What was (the respondent's) main activity during the last 12 months? </p> <div class="i1">[] 0 Paid employee<br />[] 1 Employer<br />[] 2 Own account worker <br />[] 3 Unpaid family worker<br />[] 4 Looking for work/ unemployed <br />[] 5 Student<br />[] 6 Homemaker <br />[] 7 Retired/ Sick/ Too old <br />[] 8 Other</div> Zimbabwe 2012: Persons ages 10+ [discrepancies: type I none; type II 0.6%] 00 Paid employee 01 Employer 02 Own account worker 03 Unpaid family worker 04 Looking for work or unemployed 05 Student 06 Homemaker 07 Retired, sick, or too old 08 Other 98 Unknown 99 NIU (Not in universe) This variable indicates the person's main economic activity. IPUMS Occupation (3-digits) <span class="em">D- For persons age 10 years and above </span> <br />[Questions 20 to 22 were asked of persons age 10 years and above]</p> <p>21. What was (the respondent's) main occupation during the last 12 months? </p> <div class="i1">For codes 0-3 in Question 20 <br /><br />Occupation _ _ _</div> Zimbabwe 2012: Persons age 10+ who are economically active but not unemployed or looking for work [discrepancies: type I 11.5%; type II 1.2%] 011 Armed forces 111 Legislators 112 Senior government officials 113 Traditional chiefs and heads of villages 114 Senior officials of special interest groups 115 Other government and senior 121 Directors and chief executives 122 Managers and company secretaries 211 Physicists and related professional 213 Computing professionals and associates 214 Architects and associated professionals 215 Engineers, all types 221 Life science professionals 222 Medical doctors, all types except dentists 223 Nursing and midwifery professionals 225 Veterinarians, all types 226 Pharmaceuticals chemists, pharmacists, pharmacologists 227 Other health professionals 231 College, university and higher education teaching 232 Secondary education teaching professionals 233 Primary education teaching professionals 234 Special education teaching professionals 235 Other teaching professionals 236 Pre-primary teachers including associates 241 Business professionals 242 Legal professionals 243 Archivists, librarians and related professionals 244 Social science and related professionals 245 Writers and creative or performance artists 246 Religious professionals 247 Artistic, entertainment and sports associate professionals 299 Professionals, not elsewhere classified 311 Physical and engineering science technicians 313 Optical and electronic machine operators 314 Ship and aircraft controllers and technicians 315 Safety quality inspectors 316 Technicians, uncertified 321 Life science technicians and related professionals 322 Modern health associated professionals (except nurses) 323 Medical assistants 324 Traditional medicine practitioners and faith healers 325 Temporary (untrained) secondary teachers 332 Temporary (untrained) primary teachers 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 (govt.) associate professional 345 Police inspectors and detectives 411 Secretaries and keyboard operator 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 423 Other clerks 511 Travel attendants and related workers 512 Housekeeping and restaurant services workers (based in institutions) 513 Personal care and related workers 514 Other personal services workers 516 Protective services workers 517 Domestic workers (private homes) 521 Fashion and other models 522 Shop salespersons and demonstrators 523 Stall and market salespersons 524 Businesspersons 611 Commercial farmers 614 Forestry and related workers 615 Fishery workers, hunters and trappers 621 Communal subsistence agricultural workers 711 Miners, short-firers, 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 715 Gold panners 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 725 Workshop attendants 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 shoe making trades workers 811 Plant and machine operators (all types) 828 Plant and machine assemblers (all types) 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 911 Street vendors and related workers (goods) 912 Shoe cleaning and other street services-elementary occupations (services) 913 Domestic and related helpers, cleaners and launderers (not home based) 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 997 Occupation not elsewhere classified 998 Unknown 999 NIU (Not in universe) This variable indicates the person's occupation. IPUMS Field of specialization <span class="em">D- For persons age 10 years and above </span> <br />[Questions 20 to 22 were asked of persons age 10 years and above]</p> <p>22. What was (the respondent's) field of specialization? </p> <div class="i1">For persons with level 3 in Question 16 and codes 0-4 in Question 20<br /><br />Field _ _</div> Zimbabwe 2012: Persons age 10+ who are paid employees and have completed tertiary education [discrepancies type I: 0.1% type II: 0.3%] 01 Basic programmes 14 Teacher training and education science 21 Arts 22 Humanities 31 Social and behavioral science 32 Journalism and information 34 Business and administration 38 Law 42 Life sciences 44 Physical sciences 46 Mathematics and statistics 48 Computing 52 Engineering and engineering trades 54 Manufacturing and processing 58 Architecture and building 62 Agriculture, forestry, and fishery 64 Veterinary 72 Health 76 Social services 81 Personal services 84 Transport services 85 Environmental protection 86 Security services 98 Unknown 99 NIU (Not in universe) This variable indicates the person's specialization in secondary school. IPUMS Ever gave live birth <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>23. Has (the respondent) given any live births?</p> <div class="i1">[] 1 Yes <br />[] 2 No</div> Zimbabwe 2012: Women age 15 to 49 [discrepancies type I: 0.3% type II: 0.3%] 1 Yes 2 No 8 Unknown 9 NIU (Not in universe) This variable indicates whether the person has ever had a live birth. IPUMS Male children in household <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>If yes, how many children born to (the respondent) were with her on the census night?</p> <div class="i1">Male</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">Female</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies: type I 25.8%; type II trace] 00 01 1 02 2 03 3 04 4 05 5 06 6+ 98 Unknown 99 NIU (Not in universe) This variable indicates how many male children belonging to this person are in the household. IPUMS Female children in household <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>If yes, how many children born to (the respondent) were with her on the census night?</p> <div class="i1">Male</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">Female</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies: type I 25.8%; type II trace] 00 01 1 02 2 03 3 04 4 05 5 06 6+ 98 Unknown 99 NIU (Not in universe) This variable indicates how many female children belonging to this person are in the household. IPUMS Male children elsewhere <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>If yes, how many children born to (the respondent) were elsewhere on the census night?</p> <div class="i1">Male</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">Female</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies: type I 0.4%; type II 0.1%] 00 01 1 02 2 03 3 04 4 05 5 06 6+ 98 Unknown 99 NIU (Not in universe) This variable indicates how many male children belonging to this person are outside of this household. IPUMS Female children elsewhere <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>If yes, how many children born to (the respondent) were elsewhere on the census night?</p> <div class="i1">Male</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">Female</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies: type I 0.4%; type II 0.1%] 00 01 1 02 2 03 3 04 4 05 5 06 6+ 98 Unknown 99 NIU (Not in universe) This variable indicates how many female children belonging to this person are outside of this household. IPUMS Male children dead <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>If yes, how many children born to (the respondent) have died?</p> <div class="i1">Male</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">Female</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies: type I 0.3%; type II 0.1%] 00 01 1 02 2 03 3 04 4 05 5+ 98 Unknown 99 NIU (Not in universe) This variable indicates how many of the person's male children have died. IPUMS Female children dead <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>If yes, how many children born to (the respondent) have died?</p> <div class="i1">Male</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">Female</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies: type I 0.3%; type II 0.1%] 00 01 1 02 2 03 3 04 4 05 5+ 98 Unknown 99 NIU (Not in universe) This variable indicates how many of the person's female children have died. IPUMS Age at first live birth <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>24. How old was (the respondent) when she had her first live birth?</p> <div class="i1">Age in complete years <br /><br />Age _ _</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies: type I 0.6%; type II 0.1%] 012 12 or younger 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+ 998 Unknown 999 NIU (Not in universe) This variable indicates the age this person was when they last gave birth. IPUMS Month of last live birth <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>25. When was (the respondent's) last live birth? </p> <div class="i1">Enter month (MM) and year (YY)<br /><br />_ _ Month <br />_ _ Years</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies type I: 0.2% type II: 0.4%] 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) This variable indicates the month when this person last gave birth. IPUMS Year of last live birth <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>25. When was (the respondent's) last live birth? </p> <div class="i1">Enter month (MM) and year (YY)<br /><br />_ _ Month <br />_ _ Years</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies type I: 0.2% type II: 0.3%] 1980 1980 or earlier 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 9998 Unknown 9999 NIU (Not in universe) This variable indicates the year when this person last gave birth. IPUMS Number of males in last live birth <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>26. Was it a boy or a girl? </p> <div class="i1">No. of Boys</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">No. of Girls</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies type I: 0.5% type II: 0.1%] 00 01 1 02 2 03 3 04 4+ 98 Unknown 99 NIU (Not in universe) This variable indicates the number of males that were in the last live birth. IPUMS Number of females in last live birth <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>26. Was it a boy or a girl? </p> <div class="i1">No. of Boys</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">No. of Girls</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies type I: 0.4% type II: 0.1%] 00 01 1 02 2 03 3 04 4+ 98 Unknown 99 NIU (Not in universe) This variable indicates the number of females that were in the last live birth. IPUMS Number of males from last live birth still living <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>27. Is the child still alive? </p> <div class="i1">No. of Boys</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">No. of Girls</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies type I: 0.4% type II: 0.1%] 00 01 1 02 2 03 3+ 98 Unknown 99 NIU (Not in universe) This variable indicates the number of male children still alive since the last live birth. IPUMS Number of females from last live birth still living <span class="em">E- For women age 15-49 years </span> <br />[Question 23 to 27 were asked of women age 15 to 49 years]</p> <p>27. Is the child still alive? </p> <div class="i1">No. of Boys</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div><div class="i1">No. of Girls</div><div class="i2">[] 0<br />[] 1<br />[] 2<br />[] 3<br />[] 4<br />[] 5<br />[] 6<br />[] 7<br />[] 8<br />[] 9</div> Zimbabwe 2012: Women age 15 to 49 who ever gave live birth [discrepancies type I: 0.4% type II: 0.1%] 00 01 1 02 2 03 3+ 98 Unknown 99 NIU (Not in universe) This variable indicates the number of famale children still alive since the last live birth.. IPUMS