DDI_POL_1978_PHC_v01_M_v7.5_A_IPUMS National Population and Housing Census 1978 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. National Population and Housing Census 1978 - IPUMS Subset PHC Poland 1978 (IPUMS Harmonized Subset) POL_1978_PHC_v01_M_v7.5_A_IPUMS Central Statistical Office IPUMS (c) Copyright 1978, Central Statistical Office and Minnesota Population Center MetadataEditor Central Statistical Office 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 Dwelling Characteristics Variables -- HOUSEHOLD Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Geography: O-Z Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Income Variables -- PERSON Technical Person Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Geography: O-Z Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Work Variables -- PERSON Work: Industry Variables -- PERSON Education Variables -- PERSON Demographic Variables -- PERSON Migration: Global Variables -- PERSON Disability Variables -- PERSON Income Variables -- PERSON Work: Occupation Variables -- PERSON Other Person Variables -- PERSON Fertility and Mortality Variables -- PERSON Poland Voivodeship Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: A dwelling in a housing unit incorporating one or more habitable space, as well as several auxiliary rooms (such as bathrooms, hall, toilets, etc) which has been built or modified to serve habitation-related purposes and constiutes an integral strucutral whole. Every dwelling should possess a separate entrance. - Households: A household is a number of related and nonrelated individuals who have been living or staying togther in one dwelling and support each other financially. - Group quarters: Collective housing units are hostels, dormitories, student's houses, child's houses, teenager support houses, small child care facilities, pensioner houses, facilities for severely and permanently ill individuals, facilities for blind people, care centers for diabled or mentally ill patients, professional car facilities, monasteries, convents, and other collective housing units as such in which the occupants live for a longer time or permanently. All individuals who were registered in a dwelling at the census moment regardsless of if they were inhabiting the dwelling at that moment. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Poland 1978 MICRODATA SOURCE: Central Statistical Office SAMPLE SIZE (person records): 3577272. SAMPLE DESIGN: Systematic; every tenth private household after a random start. Additionally every 10th individual in collective housing in the household. Face-to-face [f2f] A- population and housing. Az- collective housing. B- population sample survey of randomly selected individuals. C- vacants de jure, CENSUS DAY: December 6/7 1978 Self-weighting (expansion factor=10) IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS International are designed to extend this record. Central Statistical Office 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: Poland, Central Statistical Office. National Population and Housing Census 1978 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. POL1978_PHC-H-H Household records 1 56 POL1978_PHC-P-H Person records 3577272 60 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 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 Poland, Voivodship 1978 - 1988 [Level 1; consistent boundaries, GIS] 616001 Warszawskie 616003 Bialskopodlaskie 616005 Białostockie 616007 Bielskie 616009 Bydgoskie 616011 Chełmskie 616013 Ciechanowskie 616015 Częstochowskie 616017 Elbląskie 616019 Gdańskie 616021 Gorzowskie 616023 Jeleniogórskie 616025 Kaliskie 616027 Katowickie 616029 Kieleckie 616031 Konińskie 616033 Koszalińskie 616035 Krakowskie 616037 Krośnieńskie 616039 Legnickie 616041 Leszczyńskie 616043 Lubelskie 616045 Łomżyńskie 616047 Łódzkie 616049 Nowosądeckie 616051 Olsztyńskie 616053 Opolskie 616055 Ostrołęckie 616057 Pilskie 616059 Piotrkowskie 616061 Płockie 616063 Poznańskie 616065 Przemyskie 616067 Radomskie 616069 Rzeszowskie 616071 Siedleckie 616073 Sieradzkie 616075 Skierniewickie 616077 Słupskie 616079 Suwalskie 616081 Szczecińskie 616083 Tarnobrzeskie 616085 Tarnowskie 616087 Toruńskie 616089 Wałbrzyskie 616091 Włocławskie 616093 Wrocławskie 616095 Zamojskie 616097 Zielonogórskie GEO1ALT_PL identifies the household's voivodship within Poland in 1978 and 1988. Voivodships are the first level administrative units of the country. GEO1ALT_PL is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1ALT_PL can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Poland 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 Poland, Voivodship 1978 [Level 1, GIS] 001 Warszawskie 003 Bialskopodlaskie 005 Białostockie 007 Bielskie 009 Bydgoskie 011 Chełmskie 013 Ciechanowskie 015 Częstochowskie 017 Elbląskie 019 Gdańskie 021 Gorzowskie 023 Jeleniogórskie 025 Kaliskie 027 Katowickie 029 Kieleckie 031 Konińskie 033 Koszalińskie 035 Krakowskie 037 Krośnieńskie 039 Legnickie 041 Leszczyńskie 043 Lubelskie 045 Łomżyńskie 047 Łódzkie 049 Nowosądeckie 051 Olsztyńskie 053 Opolskie 055 Ostrołęckie 057 Pilskie 059 Piotrkowskie 061 Płockie 063 Poznańskie 065 Przemyskie 067 Radomskie 069 Rzeszowskie 071 Siedleckie 073 Sieradzkie 075 Skierniewickie 077 Słupskie 079 Suwalskie 081 Szczecińskie 083 Tarnobrzeskie 085 Tarnowskie 087 Toruńskie 089 Wałbrzyskie 091 Włocławskie 093 Wrocławskie 095 Zamojskie 097 Zielonogórskie GEO1_PL1978 identifies the household's voivodship within Poland in 1978. Voivodships are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_PL1978 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Poland 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 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 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 Hot water heater NIU (not in universe) 1 No 2 Yes 9 Unknown/missing HOTWATER indicates whether the housing unit had a water heater. IPUMS Number of rooms 00 Part of a room; no rooms 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) ROOMS indicates the number of rooms occupied by the housing unit. IPUMS Kitchen or cooking facilities 00 NIU (not in universe) 10 No kitchen 11 Food is prepared in a non-kitchen room 13 Does not prepare food in the dwelling 20 Yes, have a kitchen 21 Kitchen located inside the dwelling 22 Indoor kitchen, exclusive use 23 Indoor kitchen, shared use 24 Exclusive use of kitchen (indoor/outdoor status not specified) 25 Shared use of kitchen with another household (indoor/outdoor status not specified) 26 Kitchen located outside the dwelling 27 Outdoor kitchen, exclusive use 28 Outdoor kitchen, shared use 99 Unknown/missing KITCHEN indicates whether the household had a kitchen, cooking facilities, or room dedicated to food preparation. 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 Year structure was built 0000 NIU (not in universe) 1870 1870 or earlier 1871 1871 1872 1872 1873 1873 1874 1874 1875 1875 1876 1876 1877 1877 1878 1878 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 Under construction 9999 Unknown BUILTYR indicates the year in which construction was completed on the building in which the household resides. IPUMS Age of structure, coded from intervals 000 Less than 1 year old 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 99 100 100 101 101 102 102 103 103 104 104 105 105 106 106 107 107 108 108 109 109 110 110 111 111 112 112 113 113 114 114 115 115 116 116 117 117 118 118 119 119 120 120 121 121 122 122 123 123 124 124 125 125 126 126 127 127 128 128 129 129 130 130 131 131 132 132 133 133 134 134 135 135 136 136 137 137 138 138 139 139 140 140 141 141 142 142 143 143 144 144 145 145 146 146 147 147 148 148 149 149 150 150 151 151 152 152 153 153 154 154 155 155 156 156 157 157 158 158 159 159 160 160 161 161 162 162 163 163 164 164 165 165 166 166 167 167 168 168 169 169 170 170 171 171 172 172 173 173 174 174 175 175 176 176 177 177 178 178 179 179 180 180 181 181 182 182 183 183 184 184 185 185 186 186 187 187 188 188 189 189 190 190 191 191 192 192 193 193 194 194 195 195 196 196 197 197 198 198 199 199 200 200+ 997 Under construction 998 Unknown 999 NIU (not in universe) AGESTRUCT2 gives the estimated age of the structure. IPUMS Stories in structure 00 NIU (not in universe) 01 1 story 02 2 stories 03 3 stories 04 4 stories 05 5 stories 06 6 stories 07 7 stories 08 8 stories 09 9 stories 10 10 stories 11 11 stories 12 12 stories 13 13 stories 14 14 stories 15 15 stories 16 16 stories 17 17 stories 18 18 stories 19 19 stories 20 20 stories 21 21 stories 22 22 stories 23 23 stories 24 24 stories 25 25+ stories 99 Unknown STORIES indicates the number of floors or levels in the building containing the responding housing unit. IPUMS Living area in square meters LIVEAREA describes the total living area in the dwelling inhabited by the household. LIVEAREA is a 3-digit numeric variable. Codes000 = NIU (not in universe) 999 = Unknown Top codes:Unless otherwise specified: 998+ Austria 1991-2001: 150+ Belarus 1999: 201+ Belarus 2009: 250+ Germany 1987: 361+ Hungary 2001: 260+ Hungary 2011: 301+ Iran 2006: 501+ Italy 2001: 150+ Italy 2011: 145+ Laos 2005: 200+ Philippines 1990-2010: 200+ Poland 2002: 200+ Romania 2002: 221+ Romania 2011: 500+ Slovenia 2002: 101+ Spain 1991: 181+ Spain 2001-2011: 900+ Switzerland 1980-1990: 400+ Switzerland 2000: 500+ 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 For each occupied dwelling, mobile unit or provisional premises a separate form A should be completed.</p> <p>____ <span class="lang">Voidvoship </span> <br />____ Town <br />____ Community <br />____ Locality</p> <div class="i1">____ Name<br />____ Type</div><p>____ Street (square, circus, etc.) <br />____ No. of real estate <br />____ No. of dwelling</p> <p>____ Number of attached additional forms A <br />____ No. of census district <br />____ Successive no. of building in census district Poland 1978: All records The variable indicates the dwelling number. This is a 7-digit numeric variable with 0 implied decimal places IPUMS Household number (within dwelling) For each occupied dwelling, mobile unit or provisional premises a separate form A should be completed.</p> <p>____ <span class="lang">Voidvoship </span> <br />____ Town <br />____ Community <br />____ Locality</p> <div class="i1">____ Name<br />____ Type</div><p>____ Street (square, circus, etc.) <br />____ No. of real estate <br />____ No. of dwelling</p> <p>____ Number of attached additional forms A <br />____ No. of census district <br />____ Successive no. of building in census district Poland 1978: All records 1 1 2 2 3 3 4 4 The variable indicates the household number within the dwelling. IPUMS Number of households in dwelling Poland 1978: All records 1 1 2 2 3 3 4 4 This variable indicates the number of households that are in the dwelling. IPUMS Number of persons in dwelling Poland 1978: 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 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 This variable indicates the number of persons in the dwelling. IPUMS Number of persons in household Poland 1978: 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 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 35 35 37 37 This variable indicates the number of persons in the household. IPUMS Kind of locality Poland 1978: All households 1 Town (urban area) 2 Country (rural area) This variable indicates the type of locality, urban or rural, which the person enumerated lives. IPUMS Kind of locality in 1978 Poland 1978: All households With 100 thousand inhabitants or more 1 50 to 99.9 thousand inhabitants 2 20 to 49.9 thousand 3 10 to 19.9 thousand 4 5 to 9.9 thousand 5 2 to 4.9 thousand 6 Less than 2 thousand inhabitants 9 Rural area This variable indicates the kind of locality, defined in 1978 terms, which the person enumerated lives. The types of urban localities in 1978 were differentiated by the number of inhabitants. IPUMS Type of building 1. Type of building</p> <div class="i1">[] 1 Residential<br />[] 2 Mixed type: for residential and economic purposes<br />[] 3 Collective housing unit, i.e. at least a half of it is occupied by boarding school, hotel, hospital, etc.<br />[] 4 Non-residential</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.2%; type II trace] 1 Residential 2 Mixed type, for residential and economic purposes 3 Collective housing 4 Non-residential 8 Unknown 9 NIU (not in universe) This variable indicates the type of building. IPUMS Period (year) of construction of building 2. Period (year) of construction</p> <div class="i1">[] X before 1918<br />[] 9 1918 - 1944<br />[] 0 1945 - 1970<br />[] For buildings constructed after 1970 two last digits of construction year should be written in _ _</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.2%; type II trace] 00 Before 1918 01 1918 to 1944 02 1945 to 1970 03 1971 04 1972 05 1973 06 1974 07 1975 08 1976 09 1977 10 1978 98 Unknown 99 NIU (not in universe) This variable indicates the year that the building was constructed in. IPUMS Form of ownership of the building 3. Form of ownership</p> <div class="i1">[] Owned by institution</div><div class="i2">Write in full name of institution being owner ____</div><div class="i1">[] Owned by individual person</div><div class="i2">Write in name and first name of owner ____</div><div class="i1">Is the building at the disposal of local state administration body?</div><div class="i2">Please encircle the relevant.<br /><br />[] Yes<br />[] No</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.2%; type II trace] 1 Local state administration body 2 State-owned collective farm 3 Housing cooperative 4 Other socialized institution 5 Owned by individual person 6 Owned by individual person but at the disposal of local site administration body 7 Religious institution 8 Unknown 9 NIU (not in universe) This variable indicates who has ownership of the building. IPUMS Number of floors in building 4. Height of building (number of floors)</p> <div class="i1">[] 0 Ground-floor building<br />[] 1 One-floor building<br />[] 2 Two-floor building<br />[] 3 Three-floor building<br />[] 4 Four-floor building<br />[] 5 Five to nine-floor building<br />[] 6 Ten-floor building<br />[] 7 Eleven-floor building<br />[] 8 Twelve and over-floor building</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.2%; type II trace] 00 Ground floor building 01 1 floor 02 2 floors 03 3 04 4 05 5 to 9 06 10 07 11 08 12 or more 98 Unknown 99 NIU (not in universe) This variable indicates the height, represented in number of floors, that the building is. IPUMS Material of outer walls of the building 5. Outer wall's material</p> <div class="i1">[] 1 Not combustible (e.g. bricks, concrete, etc.)<br />[] 2 Combustible (wood, etc.)</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.2%; type II trace] 1 Not combustible (not flammable) 2 Combustible (flammable) 8 Unknown 9 NIU (not in universe) This variable indicates whether the outer walls of the building are made up of non- combustible or combustible materials. IPUMS Type of occupied housing unit <span class="h1">Type of occupied housing unit:</span><div class="i1">Please encircle symbol number of the relevant type of housing unit. In the case of symbols 2 or 3 the type of occupied unit should be more precisely specified (e.g. barge, trailer, barn, etc.)<br /><br />[] 1 Dwelling<br />[] 2 Mobile unit</div><div class="i2">Specify ________</div><div class="i1">[] 3 Provisional premises</div><div class="i2">Specify ________</div> Poland 1978: All households Collective housing 1 Dwelling 2 Mobile unit 3 Provisional premises This variable indicates the type of occupied housing unit. IPUMS Usable floor space (in square meters) 1. Useful floor space (total)</p> <div class="i1">Write in number of square meters (integer, without fraction) ____<br /><br />Useful dwelling space equals the sum of spaces within dwelling, i.e. spaces of rooms, kitchen with window or without it, rooms not occupied or seasonally used, antechamber, bathroom, toilet, pantry chamber, glazed veranda, etc.</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%, type II none] This variable indicates the amount of useable floor space, in meters squared, that the dwelling has. PL1978A0031 is a 3-digit numeric variable. Codes999 = NIU. IPUMS Number of rooms that are kitchens 2. Number of rooms</p> <div class="i1">(a) Living rooms ____<br />(b) Kitchens with window, with floor space of 4 square meters or more ____<br />(c) Other rooms (e.g. not occupied rooms, seasonally used rooms, rooms for storing household facilities, etc.) Do not include pantry chambers of rural type and dilapidated rooms. ____</div><div class="i1">Total number of rooms (a + b + c) ____</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%, type II none] No kitchen 1 1 kitchen 2 2 kitchens 3 3 4 4 5 5 or more 9 NIU (not in universe) This variable indicates the number of rooms in the dwelling that are kitchens. For this variable, a kitchen is defined as a room with a window that has an overall floor space of 4 square meters or more. IPUMS Number of rooms in the dwelling 2. Number of rooms</p> <div class="i1">(a) Living rooms ____<br />(b) Kitchens with window, with floor space of 4 square meters or more ____<br />(c) Other rooms (e.g. not occupied rooms, seasonally used rooms, rooms for storing household facilities, etc.) Do not include pantry chambers of rural type and dilapidated rooms. ____</div><div class="i1">Total number of rooms (a + b + c) ____</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%, type II none] 00 No rooms 01 1 room 02 2 rooms 03 3 04 4 05 5 06 6 07 7 08 8 09 9 99 NIU (not in universe) This variable indicates the number of rooms in the dwelling. IPUMS Space for kitchen, not in a room 3. Space for kitchen not being room</p> <div class="i1">Space without window or of space below 4 square meters.<br /><br />[] 1 There is such a place<br />[] 0 No such space</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%, type II none] No such space 1 There is such a place 9 NIU (not in universe) This variable indicates whether there is space for kitchen (that is not in a room) in the dwelling. A kitchen is defined as a room with a window that has an overall floor space of 4 square meters or more. Due to lack of lighting or the overall floor space being below 4 meters squares, there may not be a room for a kitchen; but there could be space in the dwelling that serves the same role as the typical kitchen. IPUMS Piped water supply 4. Piped water</p> <div class="i1">[] Inhabitants use piped water facilities</div><div class="i2">Within dwelling</div><div class="i3">Facilities linked:<br />[] 1 To the public water supply system<br />[] 2 To local system</div><div class="i2">Outside dwelling, but within the building</div><div class="i3">[] 3 As above in point 1<br />[] 4 As above in point 2</div><div class="i1">[] 0 There are not available such facilities in dwelling nor in building</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%, type II none] There are not available such facilities in dwelling nor in building 1 Public water system, within dwelling 2 Local system, within dwelling 3 Public water system, within the building 4 Local system, within the building 9 NIU (not in universe) This variable indicates the type of piped water system, and whether the system is within the dwelling. IPUMS Flush toilet in the dwelling 5. Flush toilet</p> <div class="i1">[] Inhabitants use piped water facilities for flush toilet</div><div class="i2">Within dwelling</div><div class="i3">Facilities connected:<br />[] 1 To the public water supply system<br />[] 2 To local system</div><div class="i2">Outside dwelling, but within the building</div><div class="i3">[] 3 As above in point 1<br />[] 4 As above in point 2</div><div class="i1">[] 0 There is no access to flush toilet in dwelling nor in building</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%, type II none] There is no access to flush toilet in dwelling nor in building 1 Connected to public system, within dwelling 2 Connected to the local system, within dwelling 3 Connected to public system, within the building 4 Connected to the local system, within the building 9 NIU (not in universe) This variable indicates whether there is a flush toilet in the dwelling, and the facilities that the flush toilet is connected to. IPUMS Sink or washbasin 6. Sink or washbasin</p> <div class="i1">[] Inhabitants use piped water facilities for sink or basin</div><div class="i2">Within dwelling</div><div class="i3">Facilities connected:<br />[] 1 To the public water supply system<br />[] 2 To local system</div><div class="i2">Outside dwelling, but within the building</div><div class="i3">[] 3 As above in point 1<br />[] 4 As above in point 2</div><div class="i1">[] 0 There is no access to sink or washbasin in dwelling nor in building</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%, type II trace] There is no access to sink or washbasin in dwelling nor in building 1 Connected to public system, within dwelling 2 Connected to the local system, within dwelling 3 Connected to public system, within the building 4 Connected to the local system, within the building 8 Unknown 9 NIU (not in universe) The variable indicates whether there is a sink or washbasin within the dwelling, and what type of facilities the sink or washbasin is connected to. IPUMS Bathroom in the dwelling 7. Bathroom in dwelling</p> <div class="i1">[] 1 With tub or shower<br />[] 2 Without tub or shower<br />[] 0 There is no bathroom</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%, type II none] There is no bathroom 1 There is a bathroom with a tub or shower in the dwelling 2 There is a bathroom without a tub or shower in the dwelling 9 NIU (not in universe) This variable indicates whether there is a bathroom in the dwelling, and if that bathroom has a tub or shower. IPUMS Hot running water in dwelling 8. Hot water supplies</p> <div class="i1">[] 1 Water heated outside dwelling in power stations or in boilers for flat blocks, etc.<br />[] 2 Water heated in dwelling (electric or gas stove), or in central heating boiler for one-family house<br />[] 0 There are not hot water supplies</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%; type II trace] There is no piped hot water in a dwelling 1 There is a hot piped water heated outside the dwelling (in power stations or boilers) 2 There is a hot piped water heated inside the dwelling (on electric or gas stove, or in a boiler) 8 Unknown 9 NIU (not in universe) This variable indicates whether there is hot water in the dwelling, and the method for heating the water. IPUMS Gas in the dwelling 9. Gas in dwelling</p> <div class="i1">[] Gas</div><div class="i2">[] 1 Supplied from public network<br />[] 2 From bottles</div><div class="i1">[] 0 There is not gas in dwelling</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%; type II trace] There is no gas in the dwelling 1 There is gas supplied from the public network 2 There is a gas from bottles 8 Unknown 9 NIU (not in universe) This variable indicates whether there is gas in the dwelling, and how the gas is supplied. IPUMS Method of heating the dwelling 10. Heating</p> <div class="i1">[] Central heating</div><div class="i2">[] 1 Collective, i.e. thermal energy is supplied from power stations, or from boiler for flat block<br />[] 2 Individual, i.e. thermal energy is supplied from boiler in on-family house, or boiler for storey</div><div class="i1">[] 3 Heating by electric accumulators<br />[] 4 Other types of heating (coal, or gas stoves, etc.)</div> Poland 1978: Private dwellings excluding provisional or mobile housing [discrepancies: type I 0.1%, type II trace] 1 Collective central heating 2 Individual central heating 3 Heating by electric accumulators 4 Other types of heating (coal, gas stoves) 8 Unknown 9 NIU (not in universe) This variable indicates the method of heating the dwelling. All private dwellings must have some type of heating. IPUMS Type of household Poland 1978: All households 1 Separate household 2 Collective household 3 Special household (one- person household, situated usually by typical households) This variable indicates the type of household. For this variable, a special household is a one-person-household, situated usually by typical households. IPUMS Number of persons in the household (excluding the permanently absent) Poland 1978: Separate households [discrepancies: type I trace, type II 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+ 99 NIU (not in universe) This variable indicates the number of persons in the household. Those that are permanently absent were not included. IPUMS Number of economically active persons in the household Poland 1978: Separate households [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9+ 98 Household without economically active persons but at least one person has a non-earned source of maintenance 99 NIU (not in universe) This variable indicates the number of economically active persons in the household. IPUMS Number of families in the household Poland 1978: Separate households [discrepancies: none] 1 1 2 2 3 3 4 4+ 9 NIU (not in universe) This variable indicates the number of families in the household. IPUMS Legal basis for occupancy of the dwelling 1. Right of household to occupying dwelling (or part of dwelling)</p> <p>Successive number of person being head of household ____</p> <p>Household occupies dwelling by the right of:</p> <div class="i1">(Encircle the relevant symbol number)<br /><br />[] 1 Single or shared ownership<br />[] Membership in housing cooperative</div><div class="i2">[] 2 Owner's right<br />[] 3 Tenant's right</div><div class="i1">[] 4 Allocation of dwelling (administrative allocation, or tenure contract with socialized economy unit)<br />[] 5 Tenure contract (with individual owner, or with member of housing cooperative)<br />[] 6 Sub-tenure of part or whole of allocated dwelling<br />[] Relationship with dwelling owner or main tenant</div><div class="i2">[] 7 Parents or children<br />[] 8 Other related person</div><div class="i1">[] Other right (specify) ________</div> Poland 1978: Separate households [discrepancies: type I 0.1%; type II none] 01 Single or shared ownership 02 Membership in housing cooperative, owner's right 03 Membership in housing cooperative, tenant's right 04 Allocation of dwelling 05 Tenure contract (with individual owner or with member of housing cooperative) 06 Sub- tenure of part or whole of allocated dwelling 07 Relationship with dwelling owner or main tenant- parents or children 08 Relationship with dwelling owner or main tenant- other related person 09 Other right (specify) 98 Unknown 99 NIU (not in universe) This variable indicates the legal basis that the household has in order to occupy the dwelling (or part of the dwelling). IPUMS Stata Poland 1978: All households This variable is the strata identifier for the sample. Strata is a constructed variable that captures implicit geographic stratification resulting from the sample design. It is created by assigning a unique identifier to groups of between 10 and 19 adjacent households. Additional documentation is available on the Variance Estimation page. This is a 6-digit numeric variable with 0 implied decimal places 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 Relationship to head, Europe 10 Reference person / Head 20 Spouse or partner 21 Husband or wife 22 Partner in consensual union 30 Child/child-in-law of head or of spouse/partner 31 Spouse or partner of child of head 40 Parent of head, of spouse, or of partner 50 Other relative of head, spouse, or partner 60 Non-relative of head 61 Foster child 62 Boarder 63 Domestic servant 64 Other 99 Not stated / unknown ERELATE describes for the European samples the relationship of the individual to the head of household -- sometimes called the householder or reference person. ERELATE has been classified according to the recommendations of the Conference of European Statisticians for the 2010 Population and Housing Censuses. 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 Marital status, Europe NIU (not in universe) 1 Never married 2 Married 3 Widowed and not remarried 4 Divorced/separated and not remarried 5 Widowed or divorced 9 Unknown / missing EMARST describes for the European samples the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. European census instructions generally limit marital status to legal unions, but there are exceptions. EMARST has been classified according to the recommendations given by the Conference of European Statisticians for the 2010 Population and Housing Censuses. IPUMS Relationship to head of subfamily 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 3000 Child 3100 Biological child 3200 Adopted or step child 4000 Other relative 4100 Grandchild 4200 Parent/parent-in-law 4210 Parent 4220 Parent-in-law 4300 Child-in-law 4400 Sibling/sibling-in-law 4410 Sibling 4430 Sibling-in-law 4500 Grandparent 4600 Parent/grandparent 4810 Nephew/niece 4900 Other relative, n.e.c. 5000 Non-relative 5120 Visitor 5210 Domestic employee 5220 Relative of employee, n.s. 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5400 Employee, boarder or guest 5510 Agregado 5600 Group quarters 6000 Other relative or non-relative 9998 Unknown 9999 NIU (not in universe) SUBFREL describes the relationship of the individual to the head of the subfamily (in most cases, conjugal unit). It is distinct from RELATE, which identifies a person's relationship to the head of the household. There can be multiple subfamilies within households. The particular subfamily to which a person belongs is recorded in SUBFNUM. Persons living alone without other family are identified as "heads" of family. IPUMS Subfamily membership number 0000 Non-family or sub-family not identified 0001 1st subfamily 0002 2nd subfamily 0003 3rd subfamily 0004 4th subfamily 0005 5th subfamily 0006 6th subfamily 0007 7th subfamily 0008 8th subfamily 0009 9th subfamily 0010 10th subfamily 0011 11th subfamily 0012 12th subfamily 0013 13th subfamily 0099 Unknown SUBFNUM gives the number of the subfamily to which the person belongs within the household (1 = first subfamily, 2 = second subfamily, etc.). SUBFNUM records the identification of subfamilies in the original dataset, which generally correspond to conjugal units and their offspring. IPUMS Year of birth 0000 NIU (not in universe) 1628 1628 1629 1629 1630 1630 1631 1631 1634 1634 1635 1635 1636 1636 1637 1637 1638 1638 1639 1639 1640 1640 1641 1641 1642 1642 1643 1643 1644 1644 1645 1645 1646 1646 1647 1647 1648 1648 1649 1649 1650 1650 1651 1651 1652 1652 1653 1653 1654 1654 1655 1655 1656 1656 1657 1657 1658 1658 1659 1659 1660 1660 1661 1661 1662 1662 1663 1663 1664 1664 1665 1665 1666 1666 1667 1667 1668 1668 1669 1669 1670 1670 1671 1671 1672 1672 1673 1673 1674 1674 1675 1675 1676 1676 1677 1677 1678 1678 1679 1679 1680 1680 1681 1681 1682 1682 1683 1683 1684 1684 1685 1685 1686 1686 1687 1687 1688 1688 1689 1689 1690 1690 1691 1691 1692 1692 1693 1693 1694 1694 1695 1695 1696 1696 1697 1697 1698 1698 1699 1699 1700 1700 1701 1701 1702 1702 1703 1703 1704 1704 1705 1705 1706 1706 1707 1707 1708 1708 1709 1709 1710 1710 1711 1711 1712 1712 1713 1713 1714 1714 1715 1715 1716 1716 1717 1717 1718 1718 1719 1719 1720 1720 1721 1721 1722 1722 1723 1723 1724 1724 1725 1725 1726 1726 1727 1727 1728 1728 1729 1729 1730 1730 1731 1731 1732 1732 1733 1733 1734 1734 1735 1735 1736 1736 1737 1737 1738 1738 1739 1739 1740 1740 1741 1741 1742 1742 1743 1743 1744 1744 1745 1745 1746 1746 1747 1747 1748 1748 1749 1749 1750 1750 1751 1751 1752 1752 1753 1753 1754 1754 1755 1755 1756 1756 1757 1757 1758 1758 1759 1759 1760 1760 1761 1761 1762 1762 1763 1763 1764 1764 1765 1765 1766 1766 1767 1767 1768 1768 1769 1769 1770 1770 1771 1771 1772 1772 1773 1773 1774 1774 1775 1775 1776 1776 1777 1777 1778 1778 1779 1779 1780 1780 1781 1781 1782 1782 1783 1783 1784 1784 1785 1785 1786 1786 1787 1787 1788 1788 1789 1789 1790 1790 1791 1791 1792 1792 1793 1793 1794 1794 1795 1795 1796 1796 1797 1797 1798 1798 1799 1799 1800 1800 1801 1801 1802 1802 1803 1803 1804 1804 1805 1805 1806 1806 1807 1807 1808 1808 1809 1809 1810 1810 1811 1811 1812 1812 1813 1813 1814 1814 1815 1815 1816 1816 1817 1817 1818 1818 1819 1819 1820 1820 1821 1821 1822 1822 1823 1823 1824 1824 1825 1825 1826 1826 1827 1827 1828 1828 1829 1829 1830 1830 1831 1831 1832 1832 1833 1833 1834 1834 1835 1835 1836 1836 1837 1837 1838 1838 1839 1839 1840 1840 1841 1841 1842 1842 1843 1843 1844 1844 1845 1845 1846 1846 1847 1847 1848 1848 1849 1849 1850 1850 1851 1851 1852 1852 1853 1853 1854 1854 1855 1855 1856 1856 1857 1857 1858 1858 1859 1859 1860 1860 1861 1861 1862 1862 1863 1863 1864 1864 1865 1865 1866 1866 1867 1867 1868 1868 1869 1869 1870 1870 1871 1871 1872 1872 1873 1873 1874 1874 1875 1875 1876 1876 1877 1877 1878 1878 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9999 Unknown BIRTHYR gives the person's year of birth. IPUMS 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 Educational attainment, Poland 00 NIU (not in universe) 10 None or incomplete primary 11 No education 12 Primary incomplete 20 Primary 30 Basic vocational 40 Secondary incomplete 41 Lower secondary 42 Vocational secondary, no certificate 43 General secondary, no certificate 50 Secondary completed 51 Vocational secondary completed 52 General secondary completed 60 Post-secondary 61 Post-secondary incomplete 62 Post-secondary completed 63 Training college 70 University 71 University, bachelor's 72 University, master's 73 University, doctorate 99 Unknown EDUCPL indicates the person's educational attainment in Poland in terms of the level of schooling completed. IPUMS Educational attainment, Europe 00 NIU (not in universe) 10 Less than primary 20 Primary (first stage of basic education) 30 Lower secondary (second stage of basic education) 40 Upper secondary 50 Post-secondary non-tertiary education 60 University completed 99 Unknown/missing EEDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone) for the European samples. 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. All education that was relevant to the completion of a level should be taken into account even if it was provided outside of schools and universities. EEDATTAIN 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. EEDATTAIN 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 EEDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country. Hungary 1980 and 1990 also give single years of schooling completed, recorded in YRSCHOOL. EEDATTAIN has been classified according to the recommendations of the Conference of European Statisticians for the 2010 Population and Housing Censuses. EEDATTAIN presents a less detailed version of EDATTAIN for the European Samples. 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 Industry, general recode 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. IPUMS Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. CodesArgentina 1970 - Spanish Argentina 1980 - Spanish Argentina 1991 - Spanish Argentina 2001 - Spanish Armenia 2001 Armenia 2011 Austria 1971-2001 - German Austria 2011 Bangladesh 1991 Bangladesh 2001 Bangladesh 2011 Belarus 2009 Benin 1979 Benin 1992 Benin 2002 Benin 2013 Bolivia 1976 Bolivia 1992 Bolivia 2001 Bolivia 2012 Botswana 1981 Botswana 1991 Botswana 2001 Botswana 2011 Brazil 1960 - Portuguese Brazil 1970 - Portuguese Brazil 1980 - Portuguese Brazil 1991 - Portuguese Brazil 2000 - Portuguese Brazil 2010 Burkina Faso 1996 Cambodia 1998 Cambodia 2004 Cambodia 2008 Cambodia 2013 Cambodia 2019 Cameroon 2005 Canada 1971 Canada 1981 Canada 1991-2001 Canada 2011 Chile 1960 Chile 1970 Chile 1982 Chile 1992 Chile 2002 Chile 2017 China 1982 China 1990 China 2000 Colombia 1964 - Spanish Colombia 1973 - Spanish Colombia 1993 - Spanish Colombia 2005 - Spanish Costa Rica 1963 Costa Rica 1973 Costa Rica 1984 Costa Rica 2000 Costa Rica 2011 Cote d’Ivoire 1988 Cote d’Ivoire 1998 Cuba 2002 Cuba 2012 Dominican Republic 1960 Dominican Republic 1970 Dominican Republic 1981 Dominican Republic 2002 Dominican Republic 2010 Ecuador 1962 Ecuador 1982 Ecuador 1990 Ecuador 2001 Ecuador 2010 Egypt 1986 Egypt 1996 Egypt 2006 El Salvador 1992 El Salvador 2007 Ethiopia 1984 Ethiopia 1994 Fiji 1966 Fiji 1976 Fiji 1986 Fiji 1996 Fiji 2007 Fiji 2014 Finland 2010 France 1962-1968 - French France 1975-1982 - French France 1990 - French France 1999 France 2006 France 2011 Germany 1970 Germany 1971 Germany 1981 Germany 1987 Ghana 1984 Ghana 2000 Ghana 2010 Greece 1971 Greece 1981 Greece 1991-2001 Greece 2011 Guatemala 1964 Guatemala 1973 Guatemala 1981 Guatemala 1994 Guatemala 2002 Guinea 1983 Guinea 2014 Haiti 1971 Haiti 1982 Haiti 2003 Honduras 1961 Honduras 1974 Honduras 2001 Hungary 2001 Hungary 2011 India 1983 India 1987 India 1993 India 1999 India 2004 India 2009 Indonesia 1971 Indonesia 1976 Indonesia 1980 Indonesia 1985 Indonesia 1990 Indonesia 1995 Indonesia 2000 Indonesia 2005 Indonesia 2010 Iran 2006 Iran 2011 Iraq 1997 Ireland 1971 Ireland 1981 Ireland 1986 Ireland 1991 Ireland 1996 Ireland 2002 Ireland 2006 Ireland 2011 Ireland 2016 Israel 1972 Israel 1983 Israel 1995 Israel 2008 Italy 2001 Italy 2011 Italy Surveys 2011-2013 Italy Surveys 2014-2020 Jamaica 1982 Jamaica 1991 Jamaica 2001 Jordan 2004 Kyrgyz Republic 1999 Kyrgyz Republic 2009 Laos 1995 Laos 2005 Laos 2015 Lesotho 2006 Liberia 1974 Liberia 2008 Malawi 1987 Malawi 1998 Malawi 2008 Malaysia 1970 Malaysia 1980-1991 Malaysia 2000 Mali 1987 Mali 1998 Mali 2009 Mauritius 1990 Mauritius 2000 Mauritius 2011 Mexico 1960 - Spanish Mexico 1970 - Spanish Mexico 1990 - Spanish Mexico 1995 - Spanish Mexico 2000 - Spanish Mexico 2010 Mexico 2015 Mexico 2020 Mexico surveys 2005-2019 Morocco 1982 Morocco 1994 Morocco 2004 Morocco 2014 Mozambique 1997 Mozambique 2007 Myanmar 2014 Nepal 2001 Nepal 2011 Netherlands 1960 Netherlands 1971 Netherlands 2001 Netherlands 2011 Nicaragua 1971 Nicaragua 1995 Nicaragua 2005 Nigeria 2006 Nigeria 2007 Nigeria 2008 Nigeria 2009 Nigeria 2010 Pakistan 1973 Palestine 1997 Palestine 2007 Palestine 2017 Panama 1960 - Spanish Panama 1970-1980 - Spanish Panama 1990-2000 - Spanish Panama 2010 Papua New Guinea 1980 Papua New Guinea 2000 Paraguay 1962 Paraguay 1972 Paraguay 1982 Paraguay 1992 Paraguay 2002 Peru 1993 Peru 2007 Peru 2017 Philippines 1990 Philippines 1995 Philippines 2000 Philippines 2010 Poland 1978 Poland 2002 Portugal 1981 - Portuguese Portugal 1991-2001 - Portuguese Portugal 2011 Puerto Rico 1970-2005 Puerto Rico 2010 Puerto Rico 2015 Puerto Rico 2020 Romania 1977 Romania 1992 Romania 2002 Romania 2011 Rwanda 2002 - French Rwanda 2012 Saint Lucia 1991 Senegal 1988 Senegal 2013 Sierra Leone 2004 South Africa 1996 South Africa 2001-2007 South Sudan 2008 Spain 1981 - Spanish Spain 1991 - Spanish Spain 2001 - Spanish Spain 2011 Spain Surveys 2005-2020 Sudan 2008 Suriname 2004 Suriname 2012 Switzerland 1970-2000 Switzerland 2011 Tanzania 2002 Tanzania 2012 Thailand 1970 Thailand 1980 Thailand 1990 Thailand 2000 Togo 1970 Togo 2010 Trinidad and Tobago 1980 Trinidad and Tobago 1990 Trinidad and Tobago 2000 Turkey 1985 Turkey 1990 Turkey 2000 Uganda 2002 United Kingdom 1961 United Kingdom 1971 United Kingdom 1991 United Kingdom 2001 United States 1960 United States 1970 United States 1980 United States 1990 United States 2000-2005 United States 2010 United States 2015 United States 2020 Uruguay 1963 Uruguay 1985 Uruguay 1996 Uruguay 2006 Venezuela 1981 Venezuela 1990 Venezuela 2001 - Spanish Vietnam 1989 Vietnam 1999 Vietnam 2009 Vietnam 2019 Zambia 1990 Zambia 2000 Zambia 2010 IPUMS Status in employment (class of worker) [general version] NIU (not in universe) 1 Self-employed 2 Wage/salary worker 3 Unpaid worker 4 Other 9 Unknown/missing CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. IPUMS Status in employment (class of worker) [detailed version] 000 NIU (not in universe) 100 Self-employed 101 Self-employed, unincorporated 102 Self-employed, incorporated 110 Employer 111 Sharecropper, employer 120 Working on own account 121 Own account, agriculture 122 Domestic worker, self-employed 123 Subsistence worker, own consumption 124 Own account, other 125 Own account, without temporary/unpaid help 126 Own account, with temporary/unpaid help 130 Member of cooperative 140 Sharecropper 141 Sharecropper, self-employed 142 Sharecropper, employee 150 Kibbutz member 199 Self-employed, not specified 200 Wage/salary worker 201 Management 202 Non-management 203 White collar (non-manual) 204 Blue collar (manual) 205 White or blue collar 206 Day laborer 207 Employee, with a permanent job 208 Employee, occasional, temporary, contract 209 Employee without legal contract 210 Wage/salary worker, private employer 211 Apprentice 212 Religious worker 213 Wage/salary worker, non-profit, NGO 214 White collar, private 215 Blue collar, private 216 Paid family worker 217 Cooperative employee 220 Wage/salary worker, government 221 Federal, government employee 222 State government employee 223 Local government employee 224 White collar, public 225 Blue collar, public 226 Public companies 227 Civil servants, local collectives 230 Domestic worker (work for private household) 240 Seasonal migrant 241 Seasonal migrant, no broker 242 Seasonal migrant, uses broker 250 Other wage and salary 251 Canal zone/commission employee 252 Government employment/training program 253 Mixed state/private enterprise/parastatal 254 Government public work program 255 State enterprise employee 256 Coordinated and continuous collaboration job 300 Unpaid worker 310 Unpaid family worker 320 Apprentice, unpaid or unspecified 330 Trainee 340 Apprentice or trainee 350 Works for others without wage 400 Other 999 Unknown/missing CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. IPUMS Status in employment (class of worker), Europe NIU (not in universe) 1 Employees 2 Employers 3 Own-account worker 4 Contributing family workers 5 Members of producers' co-operatives 6 Persons not classificable by status 9 Unknown ECLASSWK refers in European Samples to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. ECLASSWK is related to EEMPSTAT (employment status), which is used to define the universe for the variable in many samples. ECLASSWK has been classified according to the recommendations given by the Conference of European Statisticians for the 2010 Population and Housing Censuses. "Class of worker" is referred to as "Status in Employment" in the CES recommendations. The former term is used to maintain concordance with IPUMS practice. IPUMS Receives pension or similar benefit 10 Yes, receives a pension 11 Retirement 12 Retirement and other 13 Disability 14 Disability and other 15 Other or type not specified 20 No, does not receive a pension 98 Unknown 99 NIU (not in universe) PENSION indicates whether the respondent received a pension or similar benefits. IPUMS 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 Person number (within household) Poland 1978: 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 This variable indicates the person number within the household. IPUMS Economic position in the household Poland 1978: All persons 00 Married couple with their own source of income, not supporting anybody else 01 Other persons with their own source of income, not supporting anybody else 02 A wife or a husband with her or his own source of income and maintaining a spouse 03 Other persons with their own source of income and maintaining at least one other person from their household 04 Main breadwinner (supporter) 05 Secondary breadwinner (supporter) 06 Spouses being maintained by supporter 07 Other persons being supported by persons who are also supporting their spouses 08 Being supported by the other sole breadwinners 09 Being supported by co-supporters 10 Being supported by other persons (not registered within the household) This variable indicates the economic position in the household and whether the person is supporting other persons or being maintained by a supporter. IPUMS Industry (of person providing support) Poland 1978: Present persons who are economically active or who are being maintaned with earned sources of income [discrepancies: type I trace, type II none] 01 General industry 02 Agriculture 03 Construction 04 Forestry 05 Transportation and communication 06 Commerce 07 Other material production branches 08 Municipal economy 09 Housing economy and non-material municipal services 10 Science and technological development 11 Education and upbringing 12 Culture and arts 13 Health protection and social care 14 Physical education, tourism, and recreation 15 Other non-material service branches 16 Administration and judicature 17 Finance and insurance 18 Political organizations, trade unions, and others 98 Unknown 99 NIU (not in universe) This variable indicates the industry of the person who is providing economic support. IPUMS Education 11. Education attainment (for persons born in 1963 or earlier one of the education categories should be written in) ____</p> <div class="i1">Higher education completed<br />Higher education not completed - after general education<br />Higher education not completed - after vocational education<br />Post-secondary completed<br />Secondary education completed<br />Secondary education not completed<br />Basic vocational completed<br />Primary education completed<br />Primary education not completed<br />Self-education<br />Reading only<br />Neither writing nor reading</div> Poland 1978: Persons age 15+ [discrepancies: type I trace; type II 0.3%] 1 Higher education completed 2 Higher education not completed and secondary education completed 3 Post-secondary completed and higher education after vocational education not completed 4 Basic vocational completed 5 Primary education completed 6 No education or some primary 8 Unknown 9 NIU (not in universe) This variable indicates the person’s level of educational attainment. IPUMS Marital status 10. Marriage status (write in: single, or married, widower, widow, divorced) ____ Poland 1978: All persons 1 Single 2 Married 3 Widow or widower 4 Divorced 9 Unknown This variable indicates marital status. IPUMS Residence status 3. Permanently living (whether or not a given person is present in dwelling at the census time), or temporarily staying (please encircle the relevant category)</p> <div class="i1">[] A Permanently living and present<br />[] B Permanently living but not present<br />[] C Temporarily living</div> Poland 1978: All persons 1 Permanent 3 Permanently absent This variable indicates whether or not a given person is present in dwelling at the census time, or is staying in the dwelling temporarily. IPUMS Reason for absence 4. Please specify for person classified to the category B, or category C, cause of absence or of temporary staying ________ Poland 1978: Persons permanently absent [discrepancies: type I 4.7%; type II none] 1 NIU (not in universe) 2 Absent for up to 2 months 3 Studying 4 Working 5 Being in healthcare facility 6 Other reasons 7 Abroad This variable indicates the reason that the person enumerated is either absent or present in the household during the census period. IPUMS Sex 8. Sex (please encircle respectively)</p> <div class="i1">[] 1 Male<br />[] 2 Female</div> Poland 1978: All persons 1 Male 2 Female This variable indicates the person's sex. IPUMS Year of birth 9. Year of birth (four-digit number) _ _ _ _ Poland 1978: All persons 1878 Born in 1878 or earlier 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 9998 Unknown This variable indicates the person's year of birth. IPUMS Disability 14. Is he (she), for the reason of his (her) disability or disease, wholly or to a high degree limited in main activities relevant to his (her) age (professional activities, studies, household keeping, etc.; in the case of small children: playing games, etc.)?</p> <div class="i1">[] 0 Not<br />[] 1 Yes, wholly<br />[] 2 Yes, to a high degree</div> Poland 1978: All persons Not disabled 1 Disabled, entirely limited in main activities relevant to his (her) age 2 Disabled, partly limited in main activities relevant to his (her) age 9 Unknown This variable indicates whether the person is disabled, and the level of disability. IPUMS Main source of income 16. Main source of maintenance (Encircle the relevant source).</p> <div class="i1">For persons maintained write in the number of his (her) breadwinner (i.e. number successive in enumerating persons in dwelling)<br /><br />[] A Maintenance from work<br />[] B Maintenance not from work<br />[] C Number of breadwinner ____</div> Poland 1978: All persons 1 Economically active in the main source of maintenance 2 Economically active in the additional source of maintenance (with the non-earned main source of maintenance) 3 Having only non-earned source of maintenance 4 Being maintained by males who are economically active in the main source of maintenance 5 Being maintained by males who are economically active in the additional source of maintenance (with the non-earned main source of maintenance) 6 Being maintained by males who have only non-earned sources of maintences 7 Being maintained by females who are economically active in the main source of maintenance 8 Being maintained by females who are economically active in the additional source of maintenance (with the non-earned main source of maintenance) 9 Being maintained by females who have only non- earned sources of maintences This variable indicates the main source of income of the person enumerated. IPUMS First type of employment (of person providing support) <span class="em">17 to 20 - Main employment</span> <br />[Questions 17-20 were asked of the respondent's main employment.]</p> <p>19. Type of employment ____</p> <div class="i1">(Please write in one of the types given)<br /><br />Employee<br />Commissioner (commission-merchant)<br />Home-worker<br />Member of productive cooperative<br />User of farm<br />Worker on own account<br />Aiding in work of ____ (write in the relevant successive number of person enumerated)<br />Clergyman</div> Poland 1978: Present persons who are economically active or who are being maintaned with earned sources of income [discrepancies: type I trace, type II none] 01 Employed in socialized economy 02 Employed in non-socialized economy 03 Commission worker 04 Cottage worker 05 Member of a productive cooperative 06 User of a farm 07 Self- employed 08 Aiding in the work of a family member 09 Clergyman 99 NIU (not in universe) This variable indicates the first type of employment of the person who is providing economic support. IPUMS Occupation <span class="em">17 to 20 - Main employment</span> <br />[Questions 17-20 were asked of the respondent's main employment.]</p> <p>20. Write in the name of working post describing precisely type of performed activities or duties ____ Poland 1978: Present persons who are economically active or who are being maintaned with earned sources of income [discrepancies: type I trace, type II none] 001 Leaders of political parties and groups, central and regional administration, key cooperative organizations 002 Leaders of internal organizational units in central and regional administration, as well as in key cooperative organizations 003 Directors of associations and units alike, both national and cooperative 004 Leaders of internal organizational units in primary associations and units alike, both national and cooperative 005 Directors (chairmen) of combinats, companies, factories, construction firms, and urban economy units 006 Directors (managers) of offices and workshops having equal status to construction-oriented and technological enterprises 007 Managers of factories, manufactories, and branches being parts of combinats (companies and cooperatives) 008 Managers of internal organizational units in primary companies, factories, construction firms, and urban economy units 009 Directors (managers) of combinats, companies, agricultural establishments, production cooperatives, and group farms 010 Directors (managers) of companies and agriculture servicing establishments, machinery centers, and agricultural stations 011 Managers of veterinary establishments and managers alike 012 Managers of internal organizational units in primary agricultural companies and factories, as well as in horticulture and breeding-oriented establishments 013 Directors of local state forest, national park, and nature reserve boards, chief foresters 014 Managers of internal organizational units in primary forestry-related companies, establishments, and offices 015 Directors of local and regional Polish State Railways units, as well as automobile, airway, waterway, inland, and maritime transportation firms 016 Directors and heads of branches, boards, non-directional offices and transportation-oriented units alike 017 Managers (heads, leaders, captains) of executive and auxiliary units in transportation 018 Directors (managers) of radio and TV stations, as well as units alike 019 Directors (heads) of postal and telecommunication-oriented offices, telecommunication-related supervisory managers 020 Managers of internal organizational units in primary transportation and communication-oriented establishments 021 Directors (managers) of companies and industry-related offices in international commerce, exchange, and units alike 022 Directors (presidents) of national and cooperative internal commerce companies and department stores 023 Managers of wholesale stores, storage areas, agencies, sub-wholesale stores, warehouses, and establishments alike 024 Managers of shops and other retail commerce-oriented establishments 025 Managers of restaurants, bars, buffets, cantinas, and establishments alike 026 Managers of internal organizational units in primary international and national commerce, as well as in gastronomy 027 Rectors, deans, directors of educational units, academic secretaries 028 Supervisors of professional chairs, offices, workshops, and laboratories in tertiary education units and research facilities 029 Principals (except of those of tertiary education units), managers of vocational education units 030 Principals (managers) of special educational units, dormitories, hostels, and clubrooms 031 Managers of internal organizational units in primary and secondary education 032 Directors (managers) of theaters, operas, philharmonics, ballet centers, operettas, revues, circuses 033 Directors (managers) of libraries, archives, reading rooms, as well as technical and educational information centers 034 Directors of museums, artistic exhibitions, monument protection institutions, art protection institutions 035 Directors (managers) of film studios, movie distribution institutions, and units alike 036 Directors (managers) of culture centers, clubs for adults, cinemas, and units alike 037 Directors (managers) of radio and TV editing units 038 Directors (chairs) of publishing houses, editors-in-chief, and directors alike 039 Managers of internal organizational units in primary culture and arts institutions 040 Directors of healthcare units, clinics, general and specialized hospitals, as well as health resorts 041 Directors (managers) of outpatient clinics, blood donation centers, emergency ambulance services, health centers, heads of hospitals 042 Divisional nurses, matrons, ward nurses 043 Managers of drug stores and units alike 044 Directors of central sanitary and epidemiological units, sanitary centers, and units alike 045 Directors of social welfare units and establishment, managers of preventive treatment centers, small children houses, and nurseries 046 Managers of internal organizational units in primary sanitary and epidemiological units, blood donation centers, and dissecting rooms 047 Heads and directors (managers) of physical education, sports, and recreation promotion units 048 Directors (managers) of hotels, holiday resorts, artists retreats 049 Managers of internal organizational units in primary physical education, tourism, and recreation units 050 Chairs and vice-chairs of courts, labor and social security courts, local arbitration commissions, local and regional prosecutors 051 Managers of notarial offices, lawyer associations, and units alike 052 Managers of internal organizational units in judiciary establishments 053 Directors (chairs, managers) of banks and their branches, as well as insurance offices and inspectorates 054 Managers of internal organizational units in primary financial and insurance-related establishments 055 Directors (managers) of IT companies and centers 056 Managers of internal organizational units in primary mechanical and automatic data processing establishments 057 Managers of units not classified in other groups 058 Economic, supply and sales deputy heads (deputy managers) 059 Human resources deputy heads (deputy managers) 060 Administrative deputy heads (deputy managers) 061 Main accountants 062 Managers of internal organizational units: technical, investment, energetics, renovation, conservation, and work safety 063 Managers of internal organizational units: economic, organizational and legal, supply and sales, financial and accounting, as well as work organization 064 Managers of internal organizational units in employment servicing 065 Managers of internal organizational units in administration and economy, storage management, transportation, and office management 066 Masters 067 Managers of public servicing companies (departments) 068 Commanding officers, inspectors, commissioners, and sub-commissioners of industrial, forestry, and railroad firefighting units 069 Firefighting establishments commanding officers and individuals alike 070 Commanders, chiefs of Staff, and commissioners of self-defense units and units alike 071 Political and social activities professionals 072 Consular technical, economic, commercial attaches and individuals alike 073 Experts, consular agents, and individuals alike 074 Advisors and councilors of secretaries, chairs, leaders in ministries, and central offices 075 Experts, councilors, inspectors, and individuals alike in ministries, central offices, and chief cooperative associations 076 Provincial, municipal, local, and regional inspectors 077 Builders, technologists, urban planners, architects, designers, and individuals alike 078 Technical experts (mechanics, electricians, electronic engineers, metal processing experts, power engineers) 079 Supervisors (technical, constructional, production, etc.), investment advisers, coordinators of rescue operations 080 Technicians and lab assistants 081 Quality control inspectors, technical control experts, and individuals alike 082 Company, shift, mining dispatchers and individuals alike (except transportation dispatchers) 083 Work safety instructors, inspectors, and appraisers 084 Work control experts and individuals alike 085 Inspectors, rationalization inspectors, technical development advisors, patent experts, and individuals alike 086 Draftsmen, drawers, and individuals alike 087 Agronomists, mechanization advisers, specialists in agricultural reclamation, plantation instructors, plant protection advisors, zoo technicians 088 Veterinarians 089 Veterinary technicians, inspectors, controllers, and individuals alike 090 Chief foresters, foresters, forestry adjuncts, and individuals alike 091 Inspectors and other forestry experts 092 Traffic orderly in railroad transportation 093 Dispatchers in railroad, automobile, airway and waterway transportation 094 Inspectors, controllers, auditors, and individuals alike in railroad, automobile, airway and waterway transportation 095 Railroad assessors, national railroads adjuncts, train drivers, and individuals alike 096 Pilots, on-board mechanics, airway navigators, and individuals alike 097 Merchant navy and maritime fishing officers, harbor, maritime, and dockyard pilots 098 Postal offices, telecommunication units, as well as radio communication data forwarding dispatchers, auditors, inspectors, and individuals alike 099 Supply and sales, exchange, as well as market analysis inspectors and instructors 100 Technologists, general nutrition instructors, and individuals alike 101 Professors, associate professors, docents (not serving any managerial roles) 102 Adjuncts, assistants, lecturers, lectors, and individuals alike 103 Auditors, general and vocational schooling inspectors, pedagogics and education inspectors, as well as individuals alike 104 Teachers (except academic tutors), training course lecturers 105 Teachers in kindergartens, educators in educational care facilities, correctional units, and hostels 106 Vocational, training, practical education and driving instructors, as well as individuals alike 107 Directors, set adjusters, choreographers, musical directors, literary advisors, conductors 108 Actors, singers, dancers, musicians, whisperers, announcers, their assistants, and individuals alike 109 Circus performers, magicians, and individuals alike 110 Organizers and realizers of events and audience, stagehands, disc jockeys, and individuals alike 111 Visual artists, graphics, painters, decorators, prop managers, sketcher, and individuals alike 112 Custodians library, archives and museum adjuncts, librarians, documentation experts 113 Artistic exhibition, as well as culture and education inspectors and instructors, individuals alike 114 Emission inspectors, production workers, RTV program editor, movie, sound, camera, and image production workers 115 Journalists, redactors, speakers, commentators, lectors, press correspondents, photojournalists 116 Writers and individual alike 117 Consecutive, text, and sworn translators 118 Practitioners (senior assistants, assistants, junior assistants) and trainees 119 Dentists (senior assistants, assistants, junior assistants) 120 Pharmacists (senior assistants, assistants, junior assistants) 121 Medical certification, pharmaceutical, sanitary and epidemiology inspectors, hygiene instructors, and individuals alike 122 Military surgeons, nurses, midwives, caretakers, hygienists, masseurs, and individuals alike 123 Medical, dentistry, pharmaceutical, apothecary, and orthopedic technicians, lab assistants, nutritionists 124 Tourism instructors, tour guides, coaches, movement-based rehabilitation instructors 125 Receptionists, dispatchers, booking supervisors, floor managers in hotels 126 Judges, assessors, legal apprentices, court auditors 127 Prosecutors, vice-prosecutors, sub-prosecutors, prosecution assessors, prosecution apprentices 128 Notaries, notary assessors and apprentices, notary auditors, and individuals alike 129 Lawyers, law firm apprentices, legal advisors, arbitration experts, arbitration auditors 130 Bailiffs and professional probation officers 131 Accountants, controllers, inspectors, instructors, auditors 132 Bank branch treasurers and individuals alike, financing and accounting experts, material insurance professionals 133 Analysts, data processing system engineers, compilation controllers 134 Protectants, programmers and individuals alike in mechanical and automatic data processing 135 Organization and management experts, as well as individuals alike 136 Economy, planning, and statistics experts, as well as individuals alike 137 Administration and materials management experts, as well as individuals alike 138 Employment, salaries, human resources, training, social, and personal development experts 139 Sociologists and psychologists 140 General inspectors, railroad protection, industry, forestry, and defense officers and inspectors 141 Inspectors, evaluators, fire protection officers, and individuals alike 142 Customs officials 143 Not specified experts 144 Technical, production, organization, work control, work safety, investment, and transportation reporters 145 Administration, archiving, culture and education, printing, and publishing reporters, as well as individuals alike 146 Finance, accounting, material insurances, social, commercial, commerce and sales reporters 147 Planning, economy, management, statistics, employment, salary, human resources, and social management reporters 148 Operators of electronic data processing and calculating or analyzing devices, input and output controllers 149 Secretaries, stenographers, registrants, scribes, cart index managers, office correspondents, and individuals alike 150 Invoicing managers, actuaries, accounting and invoicing machines operators, as well as individuals alike 151 Cashiers, post office assistants, calculators, liquidators, collectors, treasurers, paymasters 152 Building administrators, intendants, chief stewards, and individuals alike 153 Shipping agents, warehousemen, goods dispatchers, and individuals alike 154 Unspecified technical position 155 Miners, mining drillers, quarrymen, and individuals alike 156 Engine drivers, mining machinery operators, and individuals alike 157 Oil and gas extraction machinery operators and individuals alike 158 Mining experts not classified in other groups 159 Pipe formers and individuals alike 160 Formers, core makers, casters, founders, and individuals alike 161 Metal hardeners, blacksmiths, and individuals alike 162 Fritting experts, ore smelters, and individuals alike 163 Metal production experts not classified in other groups 164 Panel beaters, tracers, benders, coppersmiths, and individuals alike 165 Slotting machine operators, milling machine operators, grinders, metal polishers, drillers, and individuals alike 166 Welders, brazing experts, riveters 167 Galvanizers, metal coaters, metal processors, varnish appliers, and individuals alike 168 Turners and individuals alike 169 Metal processing experts not classified in other groups 170 Fixed machinery operators and individuals alike 171 Machinery and device mechanics (except precision machinery), repairmen, and machine adjusters 172 Machinery and device assemblers (except precision machinery) 173 Machine and device operators in metal production and individuals alike 174 Stokers, greasers, and individuals alike 175 Precision mechanics and assemblers, opticians, and individuals alike 176 Jewelers, goldsmiths, gemstone and semi-gem polishers, metal formers 177 Electro power engineers (except fixed machinery) 178 Electro mechanics and electro assemblers of apparatuses, installations, and electric or electronic devices 179 Electro assemblers and assemblers of power and telecommunication lines 180 Machinery installations, apparatuses, and devices assemblers, machine and device operators in electric and technical production 181 Tele-transmission, telecommunication, and tele-commutation devices assemblers 182 Chemical processes operators, chemical fibers production operators, and individuals alike 183 Paper, rubber, and plastics production experts 184 Machine and device operators in cellulose and paper production 185 Stokers and coppersmiths in chemical production and individuals alike 186 Chemical production and alike experts not classified in other groups 187 Construction materials, ceramics, and glass production operators (operators, hardeners, dryers, stokers) 188 Ceramic, gypsum, silicate, and glass product formers, modelers, ceramic product casters 189 Glass and ceramics decorators, painters, and individuals alike 190 Machine and device operators in production of construction materials and fireproof products 191 Workers in production of construction materials, glass, and ceramics not specified in other groups 192 Coopers, carpenters, cartwrights, shipwrights 193 Machine and device operators in wood, cork, and match products processing, as well as individuals alike 194 Jointers and individuals alike 195 Turners, frasiers, tracers, wood polishers, modelers, and individuals alike 196 Basket and rim makers, as well as individuals alike 197 Workers in wood processing and production not specified in other groups 198 Fabric preparation experts, yarn makers, yarn ordering workers, and individuals alike 199 Weaving machinery operators, weavers, warping experts, knitters, and individuals alike 200 Bleachers, dyers, fabric finishers, and individuals alike 201 Workers in fabric production not specified in other groups 202 Tailors, cutters, and individuals alike 203 Furriers 204 Hatters and milliners 205 Underwear makers and individuals alike 206 Embroiderers, basket workers, tassel makers, and individuals alike 207 Upholsterers and individuals alike 208 Workers in clothing production not specified in other groups 209 Tanners, tanning machinery operators and individuals alike 210 Shoemakers and individuals alike (shank makers, shoemakers, shoemaking machinery operators) 211 Purse makers and saddlers 212 Workers in haberdashery, leather, and materials alike production not specified in other groups 213 Sugar production operators and individuals alike 214 Machine and device operators in production of potato, dextrose, and starch production, as well as individuals alike 215 Alcoholic beverages, beer, and wine production operators, brewers, and individuals alike 216 Machine and device operators in production of canned, smoked, and salted products, as well as individuals alike 217 Machine and device operators in production of processed meat, butchers, as well as individuals alike 218 Machine and device operators in production of egg and meat-based products, quality controllers, as well as individuals alike 219 Milk, butter, and whey production operators, as well as individuals alike 220 Fruit and vegetable production operators, pressure controllers, separators, as well as individuals alike 221 Machine and device operators in production of processed dairy products, millers, granary supervisors, as well as individuals alike 222 Machine and device operators in production of baked products, bakers, as well as individuals alike 223 Machine and device operators in production of sweets, chocolate and caramel makers, as well as individuals alike 224 Machine and device operators in production of tobacco-based products, as well as individuals alike 225 Machine and device operators in product utilization, fodder production, aggregate supervisors, as well as individuals alike 226 Workers in food processing not specified in other groups 227 Printing machinery operators, aligners, printing works devices operators, printing casters, and individuals alike 228 Bunglers, reproduction printing forms assemblers, retouching experts, engravers, and individuals alike 229 Bookbinders, paper and plastics products preparation experts, as well as individuals alike 230 Luthiers, assemblers, and musical instrument tuners 231 Device operators in liquid products distribution, loaders, labelers, and sorters 232 Operators of cranes and guides 233 Operators of lifts and individuals alike 234 Operators of transshipment devices in docks, dockers, and individuals alike 235 Operators of loading, unloading, and sorting machines (forklift operators) 236 Concrete workers, bricklayers, assemblers, roofers, plasterers, sorters, tile-stove setters, and individuals alike 237 Glazers and individuals alike 238 Painters and individuals alike 239 Tillers and individuals alike 240 Masons and individuals alike 241 Pavers and individuals alike 242 Track layers and individuals alike 243 Dam makers, sod removers, pipeline assemblers, caisson workers, pile drivers, and individuals alike 244 Construction workers not specified in other groups 245 Machine and device operators in road works, ground works, track laying, and individuals alike 246 Steel and reinforced concrete constructions assemblers, as well as individuals alike 247 Pipeline assemblers and individuals alike 248 Farmers (individual ones) 249 Farm supporters 250 Gardeners and individuals alike 251 Animal breeders and individuals alike 252 Agricultural and horticultural machinery and device operators 253 Anglers (inland and maritime ones) 254 Agricultural workers not specified in other groups 255 Machine and device operators in peat removal and processing, as well as individuals alike 256 Operators of machinery and mechanic forestry devices, lumberjacks, raftsmen, log rollers, and individuals alike 257 Workers in forest cultivation, protection, and exploitation 258 Train drivers, traction vehicles drivers, train stokers, and individuals alike 259 Train conductors 260 Shunters, train adjusters, compartment auditors, and individuals alike 261 Motor vehicle drivers (tramways, trolleys) 262 Automobile drivers (cars, tractors) 263 Conductors in road transport, ticket inspectors 264 Electric and machinery experts 265 On-board sailors 266 Typists, tele-typists, and office devices operators 267 Telephonists, telegraphers, radio-telephonists, and radio-telegraphers 268 Postmen, post forwarders 269 Salesmen 270 Clerks in servicing points and individuals alike 271 Nurse assistants, paramedics, fango preparation experts, general preparation experts, disinfection experts 272 Orthopedists 273 Waiters, barmaids 274 Cook 275 Hairdressers, beauticians, make-up artists, and individuals alike 276 Photographers, bunglers, photo bunglers, photography lab assistants, and individuals alike 277 Lauders, ironers, dyers, paint makers, and individuals alike 278 Lab assistants, sample collectors 279 Firefighters 280 Non-commissioned guard officers, guardians 281 Plastic, horn, bone, metal haberdashery manufacturers, toy makers, umbrella makers 282 Wardrobe supervisors, models, theater repellents, set assemblers, gunsmiths, armorers 283 Janitors, runners, porters, lift operators, clockers, house supervisors, and individuals alike 284 Transportation, loading, and unloading workers, red-caps, escorts, warehouse workers 285 Ash removers, grates, track markers, chimneysweepers, and individuals alike 286 Cleaners, sweepers, waste removers, household workers, dish washers, fruit and vegetable peelers 287 Unspecified physical work-related positions 288 Clergymen 999 NIU (not in universe) This variable indicates the occupation of the person who is providing economic support. IPUMS Second type of employment (of person or secondary person providing support) <span class="em">21 and 22 - Second employment</span> <br />[Questions 21 and 22 were asked of the respondent's secondary employment.]</p> <p>22. Type of employment</p> <div class="i1">(Please write in one of the types given in footnote)<br /><br />Employee<br />Commissioner (commission-merchant)<br />Home-worker<br />Member of productive cooperative<br />User of farm<br />Worker on own account<br />Aiding in work of ____ (write in the relevant successive number of person enumerated)<br />Clergyman</div> Poland 1978: Present persons with second employment who are economically active or who are being maintaned with an earned source of income [discrepancies: unverifiable] 01 Employed in socialized economy 02 Employed in non-socialized economy 03 Commissioner 04 Homeworker 05 Member of a productive cooperative 06 User of a farm 07 Self-employed 08 Helping a farm user 09 Helping a self-employed person 99 NIU (not in universe) This variable indicates the second type of employment of the person who is providing economic support. IPUMS Type of non-commercial sources of income (of person providing support) <span class="em">23 and 24 - Maintenance not from work</span> <br />[Questions 23 and 24 were asked of any financial support not from work the respondent has.]</p> <p>23. Type of such maintenance (e.g. old age or disability pension, scholarship, etc.) ____ Poland 1978: Present persons who are economically active or who are being maintained with an additional or non-earned income source [discrepancies: type I 0.2%; type II none] 01 Pension 02 Allowance for transferred agricultural holding 03 Disability allowance 04 Sickness allowance 05 Family allowance 06 Healthcare facility 07 Welfare allowance 08 Scholarship 09 Alimony 10 Order 11 Other sources of maintenance not from work 99 NIU (not in universe) This variable indicates the type of non- commercial sources of income, if any, that the person providing support receives. IPUMS Position in the family 7. Relation to the head of household (please write in respectively: head of household, wife or husband, son, daughter, grandson, father, etc.) ____</p> <div class="i1">For head of household is considered household member contributing mainly to defraying the cost of household keeping.</div> Poland 1978: All persons 01 Husband 02 Wife 03 Single mother or single father 04 Child 05 Related to someone of the older generation in the household 06 Other household members 07 People in non-family households and special households 08 Persons who are not family members of collective households 09 Permanently absent spouse 10 Permanently absent child 11 Permanently absent other person This variable indicates the person's position in the family. IPUMS Family type, head of household specified Poland 1978: Present persons with family position husband, wife, parent alone, or child [discrepancies: type I none; type II 0.2%] 01 Married couple without children, a husband 02 Married couple without children, a wife 03 Married couple with children, a husband 04 Married couple with children, a wife 05 Married couple with children, a child 06 Mother with children, a mother 07 Mother with children, a child 08 Father with children, a father 09 Father with children, a child 10 Oldest sibling 11 Other sibling 98 Unknown 99 NIU (not in universe) This variable indicates the family type, with the head of the household specified. IPUMS Number of children in the family (regardless of age) Poland 1978: Present persons in family position husband, wife, parent alone, or oldest sibling [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 99 NIU (not in universe) This variable indicates the number of children in the family, regardless of the age of the child. IPUMS Subfamily number Poland 1978: Present persons with family position husband, wife, parent alone, or child [discrepancies: type I none; type II 0.2%] 1 1 2 2 3 3 4 4 5 5 8 Unknown 9 NIU (not in universe) This variable indicates the person's subfamily number. IPUMS