DDI_POL_2011_PHC_v01_M_v7.5_A_IPUMS National Population and Housing Census 2011 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 2011 - IPUMS Subset PHC Poland 2011 (IPUMS Harmonized Subset) POL_2011_PHC_v01_M_v7.5_A_IPUMS Central Statistical Office of Poland IPUMS (c) Copyright 2011, Central Statistical Office of Poland and Minnesota Population Center MetadataEditor Central Statistical Office of Poland 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 Geography: Global Variables -- HOUSEHOLD Nativity and Birthplace Variables -- PERSON Technical Household Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Geography: O-Z Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Income Variables -- PERSON Technical Person Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Constructed Family Interrelationship 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 is premises comprising one or several rooms, including auxiliary rooms, built or remodelled for residential purposes, strucutrally separated (by fixed walls) within a building into which a separate entrance leads from a staircases, a passage, a common hall or directly from the street, courtyard, or garden. - Households: A composition of related and unrelated persons living together and having registered sources of maintenance. - Group quarters: Collective living quarters are a complex of rooms and other auxiliary facilities located in one or more buildings, and occupied by one separate establishment rendering the following syteps of serviceL care and education, residential healthcare, hotel service or other, and which the services is usually inhabited by a larger number of persons. The data will be collected from various administrative sources in addtion to confirming data by respondents online, via telephone, or through direct interviews. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Poland 2011 MICRODATA SOURCE: Central Statistical Office of Poland SAMPLE SIZE (person records): 4051255. SAMPLE DESIGN: The sample frame required a special preparation due to the fact that is was applied the one-step stratified sampling scheme, the corresponding sampling frame and the sample allocation in various poviats (in all previous censuses in the accompanying census sample survey used two-step strafitied sampling schemes). Face-to-face [f2f] Electronic froms: long and short. Offline forms: short. Direct enumeration using CATI and CAPI methods. de jure, CENSUS DAY: March 31, 2011 Self-weighting (expansion factor=10) IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS International are designed to extend this record. Central Statistical Office of Poland 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 of Poland. National Population and Housing Census 2011 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. POL2011_PHC-H-H Household records 1 34 POL2011_PHC-P-H Person records 4051255 51 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 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 Continent and region of country 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia REGIONW identifies the continent and region of each country. IPUMS 1st subnational geographic level, world [consistent boundaries over time] GEOLEV1 indicates the major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. First administrative units in GEOLEV1 have been spatiotemporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV1 is a 6-digit numeric variable. GEOLEV1 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO1_BR. IPUMS Nomenclature of Territorial Units for Statistics 1, Europe 0101 AT1 / Ostösterreich 0102 AT2 / Südösterreich 0103 AT3 / Westösterreich 0601 DE1 / Baden-Württemberg 0602 DE2 / Bayern 0603 DE3 / Berlin 0604 DE4 / Brandenburg 0605 DE5 / Bremen 0606 DE6 / Hamburg 0607 DE7 / Hessen 0608 DE8 / Mecklenburg-Vorpommern 0609 DE9 / Niedersachsen 0610 DEA / Nordrhein-Westfalen 0611 DEB / Rheinland-Pfalz 0612 DEC / Saarland 0613 DED / Sachsen 0614 DEE / Sachsen-Anhalt 0615 DEF / Schleswig-Holstein 0616 DEG / Thüringen 0901 ES1 / Noroeste 0902 ES2 / Noreste 0903 ES3 / Comunidad de Madrid 0904 ES4 / Centro (E) 0905 ES5 / Este 0906 ES6 / Sur 0907 ES7 / Canarias 0909 ES / Unknown 1101 FR1 / Île de France 1102 FR2 / Bassin Parisien 1103 FR3 / Nord - Pas-de-Calais 1104 FR4 / Est 1105 FR5 / Ouest 1106 FR6 / Sud-Ouest 1107 FR7 / Centre-Est 1108 FR8 / Méditerranée 1109 FR9 / Département d’Outre-Mer 1199 FR99 / Unknown 1201 EL1 / Voreia Ellada 1202 EL2 / Kentriki Ellada 1203 EL3 / Attiki 1204 EL4 / Nisia Aigaiou, Kriti 1400 IE0 / Republic of Ireland 1503 ITC / Nord-Ovest 1506 ITF / Sud 1507 ITG / Isole 1508 ITH / Nord-Est 1509 ITI / Centro 2101 PL1 / Centralny 2102 PL2 / Południowy 2103 PL3 / Wschodni 2104 PL4 / Północno-zachodni 2105 PL5 / Południowo-zachodni 2106 PL6 / Północny 2201 PT1 / Continente 2202 PT2 / Região Autónoma dos Açores 2203 PT3 / Região Autónoma da Madeira 2301 RO1 / Macroregiunea Unu 2302 RO2 / Macroregiunea Doi 2303 RO3 / Macroregiunea Trei 2304 RO4 / Macroregiunea Patru 2501 SI0 / Slovenia 2600 SK0 / Slovensko 2701 UKC / North East (England) 2702 UKD / North West (England) 2703 UKE / Yorkshire and the Humber (England) 2704 UKF / East Midlands (England) 2705 UKG / West Midlands (England) 2706 UKH / East of England (England) 2707 UKI / LONDON (England) 2708 UKJ / South East (England) 2709 UKK / South West (England) 2710 UKL / WALES 2711 UKM / SCOTLAND 2712 UKN / NORTHERN IRELAND 3400 CH0/Switzerland 3901 TR1 / Istanbul 3902 TR2 / Bati Marmara 3903 TR3 / Ege 3904 TR4 / Dogu Marmara 3905 TR5 / Bati Anadolu 3906 TR6 / Akdeniz 3907 TR7 / Orta Anadolu 3908 TR8 / Bati Karadeniz 3909 TR9 / Dogu Karadeniz 3911 TRA / Kuzeydogu Anadolu 3912 TRB / Ortadogu Anadolu 3913 TRC / Güneydogu Anadolu 9999 UNKNOWN ENUTS1 identifies the Nomenclature of Territorial Units for Statistics (NUTS) within Europe in which the household was enumerated. NUTS1 is the first level territorial units within countries. NUTS is a standard administrative division of the European Union, and was developed by the EU. The European Free Trade Association extends the NUTS system to several additional countries outside of the EU, and they are also incorporated into this variable. ENUTS1 corresponds to the 2010 version of NUTS1 released by Eurostat. IPUMS has added ENUTS1_2013 for the more recent samples. ENUTS1_2013 is an amendment to the annexes to the ENUTS1 classification. The last 2-digits of the ENUTS1 variable provide the NUTS1 code. The labels include the standard code for the NUTS1 system and the name of the NUTS1 region, separated by a slash. Smaller sub-national units are available for most countries in ENUTS2 and ENUTS3. The full set of geography variables for the countries can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS Nomenclature of Territorial Units for Statistics 2, Europe 0111 AT11 / Burgenland 0112 AT12 / Niederösterreich 0113 AT13 / Wien 0121 AT21 / Kärnten 0122 AT22 / Steiermark 0131 AT31 / Oberösterreich 0132 AT32 / Salzburg 0133 AT33 / Tirol 0134 AT34 / Vorarlberg 0911 ES11 / Galicia 0912 ES12 / Principado de Asturias 0913 ES13 / Cantabria 0921 ES21 / País Vasco 0922 ES22 / Comunidad Foral de Navarra 0923 ES23 / La Rioja 0924 ES24 / Aragón 0930 ES30 / Comunidad de Madrid 0941 ES41 / Castilla y León 0942 ES42 / Castilla-La Mancha 0943 ES43 / Extremadura 0951 ES51 / Cataluña 0952 ES52 / Comunidad Valenciana 0953 ES53 / Illes Balears 0961 ES61 / Andalucía 0962 ES62 / Región de Murcia 0963 ES63 / Ciudad Autónoma de Ceuta 0964 ES64 / Ciudad Autónoma de Melilla 0970 ES70 / Canarias 0999 ES / Unknown 1110 FR10 / Île de France 1121 FR21 / Champagne-Ardenne 1122 FR22 / Picardie 1123 FR23 / Haute-Normandie 1124 FR24 / Centre 1125 FR25 / Basse-Normandie 1126 FR26 / Bourgogne 1130 FR30 / Nord-Pas-de-Calais 1141 FR41 / Lorraine 1142 FR42 / Alsace 1143 FR43 / Franche-Comté 1151 FR51 / Pays de la Loire 1152 FR52 / Bretagne 1153 FR53 / Poitou-Charentes 1161 FR61 / Aquitaine 1162 FR62 / Midi-Pyrénées 1163 FR63 / Limousin 1171 FR71 / Rhône-Alpes 1172 FR72 / Auvergne 1181 FR81 / Lanquedoc-Roussillon 1182 FR82 / Provence-Alpes-Côte d'Azur 1183 FR83 / Corse 1191 FR91 / Guadeloupe 1192 FR92 / Martinique 1193 FR93 / Guyane 1194 FR94 / Réunion 1199 FR99 / Unknown 1211 EL11 / Anatoliki Makedonia, Thraki 1212 EL12 / Kentriki Makedonia 1213 EL13 / Dytiki Makedonia 1214 EL14 / Thessalia 1221 EL21 / Ipeiros 1222 EL22 / Ionia Nisia 1223 EL23 / Dytiki Ellada 1224 EL24 / Sterea Ellada 1225 EL25 / Peloponnisos 1230 EL30 / Attiki 1241 EL41 / Voreio Aigaio 1242 EL42 / Notio Aigaio 1243 EL43 / Kriti 1401 IE01 / Border, Midland and Western 1402 IE02 / Southern and Eastern 1531 ITC1 / Piemonte + ITC2 / Valle d'Aosta 1533 ITC3 / Liguria 1534 ITC4 /Lombardia 1561 ITF1 / Abruzzo 1562 ITF2 / Molise 1563 ITF3 / Campania 1564 ITF4 / Puglia 1565 ITF5 / Basilicata 1566 ITF6 / Calabria 1571 ITG1 / Sicilia 1572 ITG2 / Sardegna 1581 ITH1 / Bolzano-Bozen + ITH2 / Trento 1583 ITH3 / Veneto 1584 ITH4 / Friuli-Venezia Giulia 1585 ITH5 / Emilia-Romagna 1591 ITI1 / Toscana 1592 ITI2 / Umbria 1593 ITI3 / Marche 1594 ITI4 / Lazio 2111 PL11 / Łódzkie 2112 PL12 / Mazowieckie 2121 PL21 / Małopolskie 2122 PL22 / Śląskie 2131 PL31 / Lubelskie 2132 PL32 / Podkarpackie 2133 PL33 / Świętokrzyskie 2134 PL34 / Podlaskie 2141 PL41 / Wielkopolskie 2142 PL42 / Zachodniopomorskie 2143 PL43 / Lubuskie 2151 PL51 / Dolnośląskie 2152 PL52 / Opolskie 2161 PL61 / Kujawsko-Pomorskie 2162 PL62 / Warmińsko-Mazurskie 2163 PL63 / Pomorskie 2211 PT11 / Norte 2215 PT15 / Algarve 2216 PT16 / Centro (P) 2217 PT17 / Lisboa 2218 PT18 / Alentejo 2220 PT20 / Região Autónoma dos Açores 2230 PT30 / Região Autónoma da Madeira 2311 RO11 / Nord-Vest 2312 RO12 / Centru 2321 RO21 / Nord-Est 2322 RO22 / Sud-Est 2331 RO31 / Sud - Muntenia 2332 RO32 / Bucuresti - Ilfov 2341 RO41 / Sud-Vest Oltenia 2342 RO42 / Vest 2501 SI01 / Vzhodna Slovenija 2502 SI02 / Zahodna Slovenija 2599 SI / Unknown 2601 SK01 / Bratislavský kraj 2602 SK02 / Západné Slovensko 2603 SK03 / Stredné Slovensko 2604 SK04 / Východné Slovensko 3401 CH01 / Région Lémanique 3402 CH02 / Espace Mittelland 3403 CH03 / Nordwestschweiz 3404 CH04 / Zurich 3405 CH05 / Ostschweiz 3406 CH06 / Zentralschweiz 3407 CH07 / Ticino 3910 TR10 / Istanbul 3921 TR21 / Tekirdag, Edirne, Kirklareli 3922 TR22 / Balikesir, Çanakkale 3931 TR31 / Izmir 3932 TR32 / Aydin, Denizli, Mugla 3933 TR33 / Manisa, Afyonkarahisar, Kütahya, Usak 3941 TR41 / Bursa, Eskisehir, Bilecik 3942 TR42 / Kocaeli, Sakarya, Düzce, Bolu, Yalova 3951 TR51 / Ankara 3952 TR52 / Konya, Karaman 3961 TR61 / Antalya, Isparta, Burdur 3962 TR62 / Adana, Mersin 3963 TR63 / Hatay, Kahramanmaras, Osmaniye 3971 TR71 / Kirikkale, Aksaray, Nigde, Nevsehir, Kirsehir 3972 TR72 / Kayseri, Sivas, Yozgat 3981 TR81 / Zonguldak, Karabük, Bartin 3982 TR82 / Kastamonu, Çankiri, Sinop 3983 TR83 / Samsun, Tokat, Çorum, Amasya 3990 TR90 / Trabzon 3991 TRA1 / Erzurum, Erzincan, Bayburt 3992 TRA2 / Agri, Kars, Igdir, Ardahan 3993 TRB1 / Malatya, Elazig, Bingöl, Tunceli 3994 TRB2 / Van, Mus, Bitlis, Hakkari 3995 TRC1 / Gaziantep, Adiyaman, Kilis 3996 TRC2 / Sanliurfa, Diyarbakir 3997 TRC3 / Mardin, Batman, Sirnak, Siirt ENUTS2 identifies the Nomenclature of Territorial Units for Statistics (NUTS) within Europe in which the household was enumerated. NUTS2 is the second level territorial units within countries. NUTS is a standard administrative division of the European Union, and was developed by the EU. The European Free Trade Association extends the NUTS system to several additional countries outside of the EU, and they are also incorporated into this variable. ENUTS2 corresponds to the 2010 version of NUTS2 released by Eurostat. The code labels include the standard code for the NUTS2 system and the name of the NUTS2 region, separated by a slash. The full set of geography variables for the countries can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS Nomenclature of Territorial Units for Statistics 1, 2013 codes, Europe 04001 AT1 / Ostösterreich 04002 AT2 / Sudösterreich 04003 AT3 / Westösterreich 72401 ES1 / Noroeste 72402 ES2 / Noreste 72403 ES3 / Comunidad de Madrid 72404 ES4 / Centro 72405 ES5 / Este 72406 ES6 / Sur 72407 ES7 / Canarias 72409 ES / Unknown 25001 FR1 / Île-de-France 25002 FRB / Centre - Val de Loire 25003 FRC / Bourgogne-Franche-Comté 25004 FRD / Normandie 25005 FRE / Nord-Pas de Calais-Picardie 25006 FRF / Alsace-Champagne-Ardenne-Lorraine 25007 FRG / Pays de la Loire 25008 FRH / Bretagne 25009 FRI / Aquitaine-Limousin-Poitou-Charentes 25010 FRJ / Languedoc-Roussillon-Midi-Pyrénées 25011 FRK / Auvergne-Rhône-Alpes 25012 FRL / Provence-Alpes-Côte d'Azur 25013 FRM / Corse 25025 FRY / RUP FR-Régions Ultrapèriphèrique Françaises 25099 FR9 / Unknown 30003 EL3 / Attica 30004 EL4 / Aegean Islands Crete 30005 EL5 / Northern Greece 30006 EL6 / Central Greece 37200 IE0 / Ireland 38003 ITC / Nord-Ovest 38006 ITF / Sud 38007 ITG / Isole 38008 ITH / Nord-Est 38009 ITI / Centro 61602 PL2 / Makroregion Południowy 61604 PL4 / Makroregion Północno-Zachodni 61605 PL5 / Makroregion Południowo-Zachodni 61606 PL6 / Makroregion Północny 61607 PL7 / Makroregion Centralny 61608 PL8 / Makroregion Wschodni 61609 PL9 / Makroregion Województwo Mazowieckie 62001 PT1 / Continente 62002 PT2 / Região Autónoma dos Açores 62003 PT3 / Região Autónoma da Madeira 64201 RO1 / Macroreguinea Unu 64202 RO2 / Macroreguinea Doi 64203 RO3 / Macroreguinea Trei 64204 RO4 / Macroreguinea Patru 70300 SK0 / Slovensko 75600 CH0 / Switzerland ENUTS1_2013 is the third regular amendment to the annexes to the ENUTS1 classification. ENUTS1_2013 was enforced on 31 December 2013 and was applied from 1 January 2015. ENUTS1_2013 identifies the Nomenclature of Territorial Units for Statistics (NUTS) within Europe in which the household was enumerated. NUTS1 is the first level territorial units within countries. NUTS is a standard administrative division of the European Union, and was developed by the EU. The European Free Trade Association extends the NUTS system to several additional countries outside of the EU (e.g. Turkey), and they are also incorporated into this variable. The first 3-digits of ENUTS1_2013 variable provide the COUNTRY code followed by the 2-digit NUTS1 code. The labels include the standard code for the NUTS1 (2013) system and the name of the NUTS1 region, separated by a slash. Smaller sub-national units are available for most countries in ENUTS2_2013 and ENUTS3_2013. The full set of geography variables for the countries can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS Nomenclature of Territorial Units for Statistics 2, 2013 codes, Europe 040011 AT11 / Burgenland 040012 AT12 / Niederösterreich 040013 AT13 / Wien 040021 AT21 / Kärnten 040022 AT22 / Steiermark 040031 AT31 / Oberösterreich 040032 AT32 / Salzburg 040033 AT33 / Tirol 040034 AT34 / Vorarlberg 724011 ES11 / Galicia 724012 ES12 / Principado de Asturias 724013 ES13 / Cantabria 724021 ES21 / País Vasco 724022 ES22 / Comunidad Foral de Navarra 724023 ES23 / La Rioja 724024 ES24 / Aragón 724030 ES30 / Comunidad de Madrid 724041 ES41 / Castilla y León 724042 ES42 / Castilla-La Mancha 724043 ES43 / Extremadura 724051 ES51 / Cataluña 724052 ES52 / Comunidad Valenciana 724053 ES53 / Illes Balears 724061 ES61 / Andalucía 724062 ES62 / Región de Murcia 724063 ES63 / Ciudad Autónoma de Ceuta 724064 ES64 / Ciudad Autónoma de Melilla 724070 ES70 / Canarias 724099 ES / Unknown 250010 FR10 / Île-de-France 250020 FRB0 / Centre - Val de Loire 250031 FRC1 / Bourgogne 250032 FRC2 / Franche-Comté 250041 FRD1 / Basse-Normandie 250042 FRD2 / Haute-Normandie 250051 FRE1 / Nord-Pas de Calais 250052 FRE2 / Picardie 250061 FRF1 / Alsace 250062 FRF2 / Champagne-Ardenne 250063 FRF3 / Lorraine 250070 FRG0 / Pays de la Loire 250080 FRH0 / Bretagne 250091 FRI1 / Aquitaine 250092 FRI2 / Limousin 250093 FRI3 / Poitou-Charentes 250101 FRJ1 / Languedoc-Roussillon 250102 FRJ2 / Midi-Pyrénées 250111 FRK1 / Auvergne 250112 FRK2 / Rhône-Alpes 250131 FRL1 / Provence-Alpes-Côte d'Azur 250140 FRM0 / Corse 250251 FRY1 / Guadeloupe 250252 FRY2 / Martinique 250253 FRY3 / Guyane 250254 FRY4 / La Réunion 250255 FRY5 / Mayotte 250999 FR99 / Unknown 300030 EL30 / Attica 300041 EL41 / Northern Aegean 300042 EL42 / Southern Aegean 300043 EL43 / Crete 300051 EL51 / East Macedonia, Thrace 300052 EL52 / Central Macedonia 300053 EL53 / West Macedonia 300054 EL54 / Epirus 300061 EL61 / Thessalia 300062 EL62 / Ionian Islands 300063 EL63 / Western Greece 300064 EL64 / Central Greece 300065 EL65 / Pelopponese 372004 IE04 / Northern and Western 372005 IE05 / Southern 372006 IE06 / Eastern and Midland 380031 ITC1 / Piemonte + ITC2 / Valle d'Aosta/Vallée d'Aoste 380033 ITC3 / Liguria 380034 ITC4 / Lombardia 380061 ITF1 / Abruzzo 380062 ITF2 / Molise 380063 ITF3 / Campania 380064 ITF4 / Puglia 380065 ITF5 / Basilicata 380066 ITF6 / Calabria 380071 ITG1 / Sicilia 380072 ITG2 / Sardegna 380081 ITH1 / Provincia Autonoma di Bolzano/Bozen + ITH2 / Provincia Autonoma di Trento 380083 ITH3 / Veneto 380084 ITH4 / Friuli-Venezia Giulia 380085 ITH5 / Emilia-Romagna 380091 ITI1 / Toscana 380092 ITI2 / Umbria 380093 ITI3 / Marche 380094 ITI4 / Lazio 616021 PL21 / Małopolskie 616022 PL22 / Śląskie 616041 PL41 / Wielkopolskie 616042 PL42 / Zachodniopomorskie 616043 PL43 / Lubuskie 616051 PL51 / Dolnośląskie 616052 PL52 / Opolskie 616061 PL61 / Kujawsko-pomorskie 616062 PL62 / Warmińsko-mazurskie 616063 PL63 / Pomorskie 616071 PL71 / Łódzkie 616072 PL72 / Świętokrzyskie 616081 PL81 / Lubelskie 616082 PL82 / Podkarpackie 616084 PL84 / Podlaskie 616091 PL91 / Warszawski stołeczny + PL92 / Mazowieckie regionalny 620011 PT11 / Norte 620015 PT15 / Algarve 620017 PT17 / Área Metropolitana de Lisboa + PT16 / Centro 620018 PT18 / Alentejo 620020 PT20 / Região Autónoma dos Açores 620030 PT30 / Região Autónoma da Madeira 642011 RO11 / Nord-Vest 642012 RO12 / Centru 642021 RO21 / Nord-Est 642022 RO22 / Sud-Est 642031 RO31 / Sud-Muntenia 642032 RO32 / Bucharești-Ilfov 642041 RO41 / Sud-Vest Oltenia 642042 RO42 / Vest 703001 SK01 / Bratislavský kraj 703002 SK02 / Západné Slovensko 703003 SK03 / Stredné Slovensko 703004 SK04 / Východné Slovensko 756001 CH01 / Région Lémanique 756002 CH02 / Espace Mittelland 756003 CH03 / Nordwestschweiz 756004 CH04 / Zurich 756005 CH05 / Ostschweiz 756006 CH06 / Zentralschweiz 756007 CH07 / Ticino ENUTS2_2013 is the third regular amendment to the annexes to the ENUTS2 classification. ENUTS2_2013 was enforced on 31 December 2013 and was applied from 1 January 2015. ENUTS2_2013 identifies the Nomenclature of Territorial Units for Statistics (NUTS) within Europe in which the household was enumerated. NUTS2 is the second level territorial units within countries. NUTS is a standard administrative division of the European Union, and was developed by the EU. The European Free Trade Association extends the NUTS system to several additional countries outside of the EU (e.g. Turkey), and they are also incorporated into this variable. The first 3-digits of ENUTS2_2013 variable provide the COUNTRY code followed by the 3-digit NUTS2 code. The labels include the standard code for the NUTS1 (2013) system and the name of the NUTS2 region, separated by a slash. Smaller sub-national units are available for most countries in ENUTS3_2013. Larger sub-national units are available for most countries in ENUTS1_2013. The full set of geography variables for the countries can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS Population density of GEOLEV1 unit, in persons per square kilometer POPDENSGEO1 indicates the population density in persons per square kilometer of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO1 is an 8-digit string variable listing the population density in persons per square kilometer. IPUMS Area of GEOLEV1 unit in square kilometers AREAMOLLWGEO1 indicates the area in square kilometers of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO1 is a 10-digit string variable listing the area in square kilometers. IPUMS Poland, Voivodship 2002 - 2011 [Level 1; consistent boundaries, GIS] 616002 Dolnośląskie 616004 Kujawsko pomorskie 616006 Lubelskie 616008 Lubuskie 616010 Łódzkie 616012 Małopolskie 616014 Mazowieckie 616016 Opolskie 616018 Podkarpackie 616020 Podlaskie 616022 Pomorskie 616024 Śląskie 616026 Świętokrzyskie 616028 Warmińsko mazurskie 616030 Wielkopolskie 616032 Zachodniopomorskie GEO1_PL identifies the household's voivodship within Poland in 2002 and 2011. Voivodships are the first level administrative units of the country. GEO1_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 GEO1_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 2011 [Level 1, GIS] 002 Dolnośląskie 004 Kujawsko pomorskie 006 Lubelskie 008 Lubuskie 010 Łódzkie 012 Małopolskie 014 Mazowieckie 016 Opolskie 018 Podkarpackie 020 Podlaskie 022 Pomorskie 024 Śląskie 026 Świętokrzyskie 028 Warmińsko mazurskie 030 Wielkopolskie 032 Zachodniopomorskie GEO1_PL2011 identifies the household's voivodship within Poland in 2011. Voivodships are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_PL2011 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 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 Dwelling number Poland 2011: All records This variable indicates dwelling number. This is a 7-digit numeric variable with 0 implied decimal places IPUMS Number of persons in household Poland 2011: 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 24 24 This variable indicates the number of persons in household. IPUMS City or village Poland 2011: All households 1 City 2 Village This variable indicates the city or village where the household is located. IPUMS Household weight Poland 2011: All households This variable indicates the household weight. PL2011A0026 is a 12-digit numeric variable. Codes999999999999 = Unknown. IPUMS Main source of household maintenance <span class="h1">Additional information about households</span> </p> <div class="i1">(Please give information for each household in your dwelling)</div><p>1. What is the main source of maintenance of the household?</p> <div class="i1">Please mark the source of income which for the last 12 months has been the principal source of maintenance of the household established in your dwelling</div><div class="i1">[] 1. Income from hired work in the public sector<br />[] 2. Income from hired work in the private sector<br />[] 3. Income from self-employment outside agriculture<br />[] 4. Income from self-employment in agriculture<br />[] 5. Income from renting<br />[] 6. Income from property<br />[] 7. Retirement pay (for employees, combatants, farmers)<br />[] 8. Structural pension<br />[] 9. Pension resulting from an inability to work, pension for invalids<br />[] 10. Family pension<br />[] 11. Social pension<br />[] 12. Unemployment benefit<br />[] 13. Pre-retirement benefit or allowance<br />[] 14. Social assistance benefits<br />[] 15. Other sources of income not elsewhere specified</div> Poland 2011: All households 01 Earned income from work in public sector 02 Earned income from work in private sector 03 Earned income from self-employment (excluding agriculture) 04 Earned income from self-employment in agriculture 05 Rental income 06 Income from property 07 Pension (employees, military, farmers) 08 Structural pension 09 Disability pension 10 Survivor's pension 11 Social pension 12 Unemployment benefits 13 Pre-retirement benefit or allowance 14 Social assistance benefits 15 Other 99 Unknown This variable indicates the main source of household maintenance. IPUMS Additional source of household income <span class="h1">Additional information about households</span> </p> <div class="i1">(Please give information for each household in your dwelling)</div><p>1. What is the additional source of maintenance of the household? </p> <div class="i1">In case the household has an additional source of income, please indicate the relevant symbol using the response to question 1.<br />Any such additional source may not be identical as the main source.</div><div class="i1">[] 1. Income from hired work in the public sector<br />[] 2. Income from hired work in the private sector<br />[] 3. Income from self-employment outside agriculture<br />[] 4. Income from self-employment in agriculture<br />[] 5. Income from renting<br />[] 6. Income from property<br />[] 7. Retirement pay (for employees, combatants, farmers)<br />[] 8. Structural pension<br />[] 9. Pension resulting from an inability to work, pension for invalids<br />[] 10. Family pension<br />[] 11. Social pension<br />[] 12. Unemployment benefit<br />[] 13. Pre-retirement benefit or allowance<br />[] 14. Social assistance benefits<br />[] 15. Other sources of income not elsewhere specified<br />[] 16. No additional source</div> Poland 2011: All households 01 Earned income from work in public sector 02 Earned income from work in private sector 03 Earned income from self-employment (excluding agriculture) 04 Earned income from self-employment in agriculture 05 Rental income 06 Income from property 07 Pension (employees, military, farmers) 08 Structural pension 09 Disability pension 10 Survivor's pension 11 Social pension 12 Unemployment benefits 13 Pre-retirement benefit or allowance 14 Social assistance benefits 15 Other 16 No additional source of income 99 Unknown This variable indicates the additional source of household income. IPUMS Number of employed persons in the household Poland 2011: All households 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9+ 99 Unknown This variable indicates the number of employed persons in household. IPUMS Number of unemployed persons in the household Poland 2011: All households 1 1 2 2 3 3 4 4 5 5 6 6+ 9 Unknown This variable indicates the number of unemployed persons in household. IPUMS Disabled person in household Poland 2011: All households 1 All persons in the household are disabled 2 At least one person in the household is disabled 3 No disabled persons in the household 9 Unknown This variable indicates whether there is a disabled person in household. IPUMS Number of disabled persons in the household Poland 2011: All households 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7+ 99 Unknown This variable indicates the number of disabled persons in the household. IPUMS Generational composition of household Poland 2011: All households 1 Exclusively young 2 Exclusively middle-aged 3 Exclusively elderly 4 Young and middle-aged 5 Young and elderly 6 Middle-aged and elderly 7 Young, middle-aged, and elderly 9 Unknown This variable indicates the generational composition of household. IPUMS Socio-economic group of household Poland 2011: All households 1 Workers 2 Farmers 3 Self-employed 4 Pensioners 5 Disabled pensioners 6 Having non-earned source of maintenance 7 Having other source of maintenance 9 Unknown This variable indicates the socio-economic group of household. IPUMS Household composition Poland 2011: All households 1 Single family 2 Two families 3 Three or more families 4 Single non-family 5 Shared non-family 9 Unknown This variable indicates the household composition. IPUMS Sex of household head 7. Sex</p> <div class="i1">[] 1) Male<br />[] 2) Female</div> Poland 2011: All households 1 Male 2 Female 9 Unknown This variable indicates the sex of household head. IPUMS Age group of household head 8. Date of birth _ _-_ _-_ _ _ _</p> <div class="i1">Day-Month-Year</div> Poland 2011: All households 01 0 to 4 years 02 5 to 9 03 10 to 14 04 15 to 19 05 20 to 24 06 25 to 29 07 30 to 34 08 35 to 39 09 40 to 44 10 45 to 49 11 50 to 54 12 55 to 59 13 60 to 64 14 65 to 69 15 70 to 74 16 75 to 79 17 80 to 84 18 85 to 89 19 90 to 94 20 95 to 99 21 100 years or older 99 Unknown This variable indicates the age group of household head. IPUMS Main source of income of household head Poland 2011: All households 01 Earned income from work in public sector 02 Earned income from work in private sector 03 Earned income from self-employment (excluding agriculture) 04 Earned income from self-employment in agriculture 05 Rental income 06 Income from property 07 Pension 08 Structural pension 09 Disability pension 10 Survivor's pension 11 Social pension 12 Unemployment benefits 13 Pre-retirement benefit or allowance 14 Social assistance benefits 15 Other 16 Dependent 99 Unknown This variable indicates the main source of income of household head. IPUMS Educational attainment of household head <span class="h2">2. Module -- Education</span><div class="i1">(Questions concern persons aged 13 years or more i.e. born on 31.03.1998 or earlier)<br />[Questions 1-6 were asked of persons aged 13 years or more i.e. born on 31.03.1998 or earlier.]</div><p>1. What is your highest educational level achieved in the education system?</p> <div class="i1">[] 1. Tertiary, at least with a degree of Doctor's (Ph.D.)<br />[] 2. Tertiary, with a degree of Master (MA, MSc), Medical Doctor or equivalent<br />[] 3. Tertiary with a degree of Engineer, Bachelor, or certified economist<br />[] 4. College diploma<br />[] 5. Post-secondary with secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 6. Post-secondary without secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 7. Secondary vocational with secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 8. Secondary vocational without secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 9. General secondary with secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 10. General secondary without secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 11. Basic vocational<br />[] 12. Lower-secondary<br />[] 13. Primary<br />[] 14. Incomplete primary or no education</div> Poland 2011: All households 01 Tertiary, PhD 02 Tertiary, master's degree, medical doctor, or equivalent 03 Tertiary, engineer, bachelor, or certified economist 04 College diploma 05 Post-secondary with completion certificate, baccalaureate 06 Post-secondary without completion certificate 07 Secondary vocation with completion certificate 08 Secondary vocational without completion certificate 09 General secondary with completion certificate 10 General secondary without completion certificate 11 Basic vocational 12 Lower secondary 13 Primary 14 Incomplete primary or no education 98 Unknown This variable indicates the educational attainment of household head. IPUMS De facto marital status of household head <span class="h2">1. Module -- Socio-demographic characteristics</span></p> <p>21. What is your marital status? </p> <div class="i1">(Concerns people aged 15 years or more)<br />[] 1. Single<br />[] 2. Married (in actual status of marriage)<br />[] 3. Married (in separation adjudicated by court)<br />[] 4. Married (not in the actual status of marriage but without separation adjudicated by court)<br />[] 5. Widower/widow<br />[] 6. Divorced</div> Poland 2011: Households where the head is 15+ [discrepancies: none] 1 Single 2 Married 3 Partnership 4 Widowed 5 Divorced 6 Separated 8 Unknown 9 NIU (not in universe) This variable indicates the de facto marital status of household head. IPUMS Legal marital status of household head <span class="h2">1. Module -- Socio-demographic characteristics</span></p> <p>21. What is your marital status? </p> <div class="i1">(Concerns people aged 15 years or more)<br />[] 1. Single<br />[] 2. Married (in actual status of marriage)<br />[] 3. Married (in separation adjudicated by court)<br />[] 4. Married (not in the actual status of marriage but without separation adjudicated by court)<br />[] 5. Widower/widow<br />[] 6. Divorced</div> Poland 2011: Households where the head is 15+ [discrepancies: none] 1 Single 2 Married 3 Widowed 4 Divorced 8 Unknown 9 NIU (not in universe) This variable indicates the legal marital status of household head. 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 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 Consensual union 1 Yes, in consensual union 2 No, married 8 Unknown 9 NIU (not in universe) CONSENS indicates whether the respondent was in a consensual union -- a de facto marriage. IPUMS 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 Nativity status NIU (not in universe) 1 Native-born 2 Foreign-born 9 Unknown/missing NATIVITY indicates whether the person was native-born or foreign-born. IPUMS Citizenship 1 Citizen, not specified 2 Citizen by birth 3 Naturalized citizen 4 Not a citizen 5 Without citizenship, stateless 8 Unknown 9 NIU (not in universe) CITIZEN indicates the person's citizenship status within the country in which they were enumerated. IPUMS Country of citizenship 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, other or n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt/United Arab Rep. 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21220 St. Lucia 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21999 Caribbean, other or n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, other or n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24021 Canada, First Nations 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, other or n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32990 Burma, India, Pakistan, Ceylon 32999 South-Central Asia, other or n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33991 Laos and Cambodia 33992 Malaysia and Singapore 33999 South-Eastern Asia, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41992 Central-Eastern Europe 41999 Eastern Europe, other or n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42121 Britain 42122 Scotland 42123 Wales 42990 Nordic countries 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44011 Austro-Hungarian 44020 Belgium 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44041 East Germany 44042 West Germany 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (Original 15) 49994 Other European Union 49999 Europe, other or n.s. 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53999 Micronesia, other or n.s. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 90000 Other countries n.s. 99998 No citizenship/nationality 99999 Unknown NATION indicates the person's country of citizenship. IPUMS School attendance NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census. IPUMS Educational attainment, international recode [general version] NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS Educational attainment, international recode [detailed version] 000 NIU (not in universe) 100 Less than primary completed (n.s.) 110 No schooling 120 Some primary completed 130 Primary (4 yrs) completed 211 Primary (5 yrs) completed 212 Primary (6 yrs) completed 221 Lower secondary general completed 222 Lower secondary technical completed 311 Secondary, general track completed 312 Some college completed 320 Secondary or post-secondary technical completed 321 Secondary, technical track completed 322 Post-secondary technical education 400 University completed 999 Unknown/missing EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS 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 Source of livelihood 01 Work 02 Property or entrepreneurial income 03 Pension 04 Unemployment benefits 05 Illness or disability benefits 06 Other social support 07 Under state security or care 08 Scholarship 09 Apprenticeship 10 Credits, savings, or capital sale 11 Household support (dependent) 12 Assistance from relatives in country 13 Assistance from relatives, acquintances abroad 14 Multiple sources 15 Other 98 Unknown INCSRC indicates the respondent's primary source of livelihood, whether from work, benefits, or various other categories. 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 2011: 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 This variable indicates the person number (within household). IPUMS Person's weight Poland 2011: All persons This variable indicates the person's weight. This is a 12-digit numeric variable with 0 implied decimal places IPUMS Sex 7. Sex</p> <div class="i1">[] 1) Male<br />[] 2) Female</div> Poland 2011: All persons 1 Male 2 Female This variable indicates the sex of a person. IPUMS Age 8. Date of birth _ _-_ _-_ _ _ _</p> <div class="i1">Day-Month-Year</div> Poland 2011: All persons 00 Less than 1 year 01 1 year 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 years or older This variable indicates the age of a person. IPUMS Economic age group Poland 2011: All persons 1 Pre-production (men and women age 0-17 years) 2 Mobile production (men and women age 18-44 years) 3 Immobile production (men age 45-64 years, women age 45-49 years) 4 Transition (men age 65 years or older, women age 60 years or older) This variable indicates the economic age group. IPUMS Age group Poland 2011: All persons 01 0 to 4 years 02 5 to 9 03 10 to 14 04 15 to 19 05 20 to 24 06 25 to 29 07 30 to 34 08 35 to 39 09 40 to 44 10 45 to 49 11 50 to 54 12 55 to 59 13 60 to 64 14 65 to 69 15 70 to 74 16 75 to 79 17 80 to 84 18 85 years or older This variable indicates the age group of a person. IPUMS De facto marital status <span class="h2">1. Module -- Socio-demographic characteristics</span></p> <p>21. What is your marital status? </p> <div class="i1">(Concerns people aged 15 years or more)<br />[] 1. Single<br />[] 2. Married (in actual status of marriage)<br />[] 3. Married (in separation adjudicated by court)<br />[] 4. Married (not in the actual status of marriage but without separation adjudicated by court)<br />[] 5. Widower/widow<br />[] 6. Divorced</div> Poland 2011: Persons age 15+ [discrepancies: none] 1 Single 2 Married 3 Partnership 4 Widowed 5 Divorced 6 Separated 8 Unknown 9 NIU (not in universe) This variable indicates the de facto marital status of a person. IPUMS Legal marital status <span class="h2">1. Module -- Socio-demographic characteristics</span></p> <p>21. What is your marital status? </p> <div class="i1">(Concerns people aged 15 years or more)<br />[] 1. Single<br />[] 2. Married (in actual status of marriage)<br />[] 3. Married (in separation adjudicated by court)<br />[] 4. Married (not in the actual status of marriage but without separation adjudicated by court)<br />[] 5. Widower/widow<br />[] 6. Divorced</div> Poland 2011: Persons age 15+ [discrepancies: none] 1 Single 2 Married 3 Widowed 4 Divorced 8 Unknown 9 NIU (not in universe) This variable indicates the legal marital status. IPUMS Citizenship <span class="h2">8. Module -- Country of birth and citizenship</span></p> <p>4. What is your citizenship?</p> <div class="i1">[] 1) Polish (only Polish or Polish and other)<br />[] 2) Only other</div><div class="i2">Please specify the country of your citizenship ____</div><div class="i1">[] 3) Stateless person (person with no citizenship)</div> Poland 2011: All persons 1 Polish (exlusively Polish or Polish with others) 2 Exclusively foreign 3 Stateless 9 Unknown This variable indicates the citizenship of a person. IPUMS Country of citizenship <span class="h2">8. Module -- Country of birth and citizenship</span></p> <p>4. What is your citizenship?</p> <div class="i1">[] 1) Polish (only Polish or Polish and other)<br />[] 2) Only other</div><div class="i2">Please specify the country of your citizenship ____</div><div class="i1">[] 3) Stateless person (person with no citizenship)</div> Poland 2011: All persons 040 Austria 051 Armenia 100 Bulgaria 112 Belarus 156 China 203 Czech Republic 208 Denmark 250 France 276 Germany 300 Greece 348 Hungary 356 India 372 Ireland 380 Italy 398 Kazakhstan 440 Lithuania 528 The Netherlands 616 Poland 642 Romania 643 Russia 703 Slovakia 704 Vietnam 752 Sweden 792 Turkey 804 Ukraine 826 United Kingdom 840 United States 990 Africa 991 America, other 992 Asia and Oceania, other 993 Europe, other 997 Stateless 999 Unknown This variable indicates the person country of citizenship. IPUMS Other country of citizenship <span class="h2">8. Module -- Country of birth and citizenship</span></p> <p>5. Are you a citizen of any other country apart from the aforementioned?</p> <div class="i1">[] 1. Yes</div><div class="i2">Please specify the country/countries (2 names of countries of citizenship may be inserted) ____</div><div class="i1">[] 2. No</div> Poland 2011: Persons with more than one country of citizenship [universe unverifiable] 012 Algeria 036 Australia 040 Austria 056 Belgium 100 Bulgaria 112 Belarus 124 Canada 203 Czech Republic 250 France 276 Germany 300 Greece 352 Iceland 372 Ireland 380 Italy 440 Lithuania 528 The Netherlands 578 Norway 643 Russia 703 Slovakia 704 Vietnam 710 South Africa 724 Spain 752 Sweden 756 Switzerland 760 Syria 788 Tunisia 792 Turkey 804 Ukraine 826 United Kingdom 840 United States 990 Africa, other 991 America, other 992 Asia and Oceania, other 993 Europe, other 998 Unknown 999 NIU (not in universe) This variable indicates the other country of citizenship of a person. IPUMS Nativity <span class="h2">8. Module -- Country of birth and citizenship</span></p> <p>1. What is your country of birth (according to current state borders)?</p> <div class="i1">[] 1. Poland<br />[] 2. Other</div><div class="i2">Please specify the country ____</div> Poland 2011: All persons 1 Native-born 2 Foreign-born 9 Unknown This variable indicates person's nativity. IPUMS Region of birth Poland 2011: All persons 01 Poland 02 European Union 03 Other Europe 04 Asia 05 North America 06 Central America 07 South America 08 Africa 09 Oceania 99 Unknown This variable indicates a person's region of birth. IPUMS Educational attainment <span class="h2">2. Module -- Education</span><div class="i1">(Questions concern persons aged 13 years or more i.e. born on 31.03.1998 or earlier)<br />[Questions 1-6 were asked of persons aged 13 years or more i.e. born on 31.03.1998 or earlier.]</div><p>1. What is your highest educational level achieved in the education system?</p> <div class="i1">[] 1. Tertiary, at least with a degree of Doctor's (Ph.D.)<br />[] 2. Tertiary, with a degree of Master (MA, MSc), Medical Doctor or equivalent<br />[] 3. Tertiary with a degree of Engineer, Bachelor, or certified economist<br />[] 4. College diploma<br />[] 5. Post-secondary with secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 6. Post-secondary without secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 7. Secondary vocational with secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 8. Secondary vocational without secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 9. General secondary with secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 10. General secondary without secondary education completion certificate ("Matura" - Baccalaureate)<br />[] 11. Basic vocational<br />[] 12. Lower-secondary<br />[] 13. Primary<br />[] 14. Incomplete primary or no education</div> Poland 2011: Persons age 13+ [discrepancies: none] 01 Tertiary, PhD 02 Tertiary, master's degree, medical doctor, or equivalent 03 Tertiary, engineer, bachelor, or certified economist 04 College diploma 05 Post-secondary with completion certificate, baccalaureate 06 Post-secondary without completion certificate 07 Secondary vocational with completion certificate 08 Secondary vocational without completion certificate 09 General secondary with completion certificate 10 General secondary without completion certificate 11 Basic vocational 12 Lower secondary 13 Primary 14 Incomplete primary or no education 98 Unknown 99 NIU (not in universe) This variable indicates the educational attainment of a person. IPUMS Field of study <span class="h2">2. Module -- Education</span><div class="i1">(Questions concern persons aged 13 years or more i.e. born on 31.03.1998 or earlier)<br />[Questions 1-6 were asked of persons aged 13 years or more i.e. born on 31.03.1998 or earlier.]</div><p>2. What is your field of education? ____ Poland 2011: Persons who attained a college diploma, post-secondary, secondary, or basic vocational training [discrepancies: none] 100 Teacher training, pedagogy 200 Humanities, languages, art 300 Social science, economics, law 440 Physical science 481 Informatics 500 Engineering, manufacturing, and construction 600 Agriculture and veterinary 700 Health and social services 800 Services 998 Unknown 999 NIU (not in universe) This variable indicates a person's field of study. IPUMS Continuing education <span class="h2">2. Module -- Education</span><div class="i1">(Questions concern persons aged 13 years or more i.e. born on 31.03.1998 or earlier)<br />[Questions 1-6 were asked of persons aged 13 years or more i.e. born on 31.03.1998 or earlier.]</div><p>5. Are you continuing your education?</p> <div class="i1">[] 1. Yes, on a daily/full-time basis<br />[] 2. Yes, on an evening/weekend (part-time) basis, distance learning<br />[] 3. No</div> Poland 2011: Persons age 13+ [discrepancies: none] 1 Yes, full-time 2 Yes, evening classes, part-time classes, or distance learning 3 No 8 Unknown 9 NIU (not in universe) This variable indicates whether a person is continuing with education. IPUMS Type of continuing education <span class="h2">2. Module -- Education</span><div class="i1">(Questions concern persons aged 13 years or more i.e. born on 31.03.1998 or earlier)<br />[Questions 1-6 were asked of persons aged 13 years or more i.e. born on 31.03.1998 or earlier.]</div><p>6. What type of school/studies are you attending?</p> <div class="i1">[] 1. Doctor (Ph.D.) studies<br />[] 2. Post-graduate studies<br />[] 3. Higher education institution -- Master studies<br />[] 4. Higher education institution -- Bachelor or engineering studies<br />[] 5. College<br />[] 6. Post-secondary school<br />[] 7. Technical secondary school<br />[] 8. Specialized secondary school<br />[] 9. General secondary school<br />[] 10. Basic vocational school<br />[] 11. Lower secondary school<br />[] 12. Primary school</div> Poland 2011: Persons who are continuing their education [discrepancies: none] 01 Doctoral (PhD) studies 02 Post-graduate studies 03 Higher education, master's degree 04 Higher education, bachelor or engineering degree 05 College 06 Post-secondary 07 Technical secondary 08 Specialized secondary 09 General secondary 10 Basic vocational 11 Lower secondary 12 Primary 98 Unknown 99 NIU (not in universe) This variable indicates the type of continuing education being pursued by the person. IPUMS Main source of income <span class="h2">5. Module -- Source of maintenance</span><div class="i1">(Concerns persons aged 15 years or more)<br />[Questions 1-2 were asked of persons aged 15 years or more.]</div><p>1. What is your main source of maintenance?</p> <div class="i1">[] 1. Income from hired work in the public sector<br />[] 2. Income from hired work in the private sector<br />[] 3. Income from self-employment outside agriculture<br />[] 4. Income from self-employment in agriculture<br />[] 5. Income from renting<br />[] 6. Income from property<br />[] 7. Retirement pay (for employees, combatants, farmers)<br />[] 8. Structural pension<br />[] 9. Pension resulting from an inability to work, pension for invalids<br />[] 10. Family pension<br />[] 11. Social pension<br />[] 12. Unemployment benefit<br />[] 13. Pre-retirement benefit or allowance<br />[] 14. Social assistance benefits<br />[] 15. Other sources of income not elsewhere specified<br />[] 16. Dependent</div> Poland 2011: Persons age 15+ [discrepancies: type I 0.1%; type II 15.4% ] 01 Earned income from work in public sector 02 Earned income from work in private sector 03 Earned income from self-employment (excluding agriculture) 04 Earned income from self-employment in agriculture 05 Rental income 06 Income from property 07 Pension 08 Structural pension 09 Disability pension 10 Survivor's pension 11 Social pension 12 Unemployment benefits 13 Pre-retirement benefit or allowance 14 Social assistance benefits 15 Other 16 Dependent 98 Unknown 99 NIU (not in universe) This variable indicates the main source of income of a person. IPUMS Additional source of income <span class="h2">5. Module -- Source of maintenance</span><div class="i1">(Concerns persons aged 15 years or more)<br />[Questions 1-2 were asked of persons aged 15 years or more.]</div><p>2. What is your additional source of maintenance?</p> <div class="i1">[] 1. Income from hired work in the public sector<br />[] 2. Income from hired work in the private sector<br />[] 3. Income from self-employment outside agriculture<br />[] 4. Income from self-employment in agriculture<br />[] 5. Income from renting<br />[] 6. Income from property<br />[] 7. Retirement pay (for employees, combatants, farmers)<br />[] 8. Structural pension<br />[] 9. Pension resulting from an inability to work, pension for invalids<br />[] 10. Family pension<br />[] 11. Social pension<br />[] 12. Unemployment benefit<br />[] 13. Pre-retirement benefit or allowance<br />[] 14. Social assistance benefits<br />[] 15. Other sources of income not elsewhere specified<br />[] 16. No additional source</div> Poland 2011: Persons age 15+ [discrepancies: type I none; type II 6.4% ] 01 Earned income from work in public sector 02 Earned income from work in private sector 03 Earned income from self-employment (excluding agriculture) 04 Earned income from self-employment in agriculture 05 Rental income 06 Income from property 07 Pension 08 Structural pension 09 Disability pension 10 Survivor's pension 11 Social pension 12 Unemployment benefits 13 Pre-retirement benefit or allowance 14 Social assistance benefits 15 Other 16 No additional source of income 98 Unknown 99 NIU (not in universe) This variable indicates the additional source of income. IPUMS Disability <span class="h2">6. Module -- Disability</span></p> <p>1. Has your ability to perform usual activities (learning at school, professional activity, running a household, self-service) been limited due to health problems (disability or chronic disease) for 6 months or longer?</p> <div class="i1">[] 1. Yes, entirely limited<br />[] 2. Yes, considerably limited<br />[] 3. Yes, moderately limited<br />[] 4. No, it is not limited<br />[] 5. I don't want to answer this question</div><p>5. How was your disability/inability to work/impairment classified?</p> <div class="i1">[] 1. Considerable disability or complete inability to work and to live self-sufficiently, or the 1st group of disability, or long-term inability to work on a farm with entitlements to nursing benefits;<br />[] 2. Moderate disability or complete inability to work, or the 2nd group of disability;<br />[] 3. Slight disability or partial inability to work, or advisability to re-qualify professionally, or the 3rd group of disability, or long-term inability to work on a farm without entitlements to nursing benefits;<br />[] 4. Disability for persons up to 16 years of age<br />[] 5. I don't want to answer this question</div> Poland 2011: All persons 00 Non-disabled person 01 Disabled person with complete inability to perform everyday tasks, having a high disability degree certificate 02 Disabled person with complete inability to perform everyday tasks, having a moderate disability degree certificate 03 Disabled person with complete inability to perform everyday tasks, having a low disability degree certificate 04 Disabled person (aged 0-15) with complete inability to perform everyday tasks, having a disability degree certificate 05 Disabled person with complete inability to perform everyday tasks and having a disability degree certificate, for whom the exact disability degree has not been specified 06 Physically disabled person with complete inability to perform everyday tasks 07 Disabled person with complete inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a high degree of disability 08 Disabled person with complete inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a moderate or low degree of disability 10 Disabled person (aged 0-15) with complete or severe inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a degree of disability 11 Disabled person with complete inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate and to what degree he or she is disabled 12 Disabled person with severe inability to perform everyday tasks, having a high disability degree certificate 13 Disabled person with a severe inability to perform everyday tasks, having a moderate disability degree certificate 14 Disabled person with a severe inability to perform everyday tasks, having a low disability degree certificate 15 Disabled person (aged 0-15) with a severe inability to perform everyday tasks, having a disability degree certificate 16 Disabled person with a severe inability to perform everyday tasks and having a disability degree certificate, for whom the exact disability degree has not been specified 17 Physically disabled person with a severe inability to perform everyday tasks 18 Disabled person with a severe inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a high degree of disability 19 Disabled person with a severe inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a moderate degree of disability 20 Disabled person with a severe inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a low degree of disability 22 Physically disabled person with a severe inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate and to what degree he or she is disabled 23 Disabled person with a slight inability to perform everyday tasks, having a high disability degree certificate 24 Disabled person with a slight inability to perform everyday tasks, having a moderate disability degree certificate 25 Disabled person with a slight inability to perform everyday tasks, having a low disability degree certificate 26 Disabled person (aged 0-15) with a slight inability to perform everyday tasks, having a disability degree certificate 27 Disabled person with a slight inability to perform everyday tasks and having a disability degree certificate, for whom the exact disability degree has not been specified 28 Physically disabled person with a slight inability to perform everyday tasks 29 Disabled person with a slight inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a high degree of disability 30 Disabled person with a slight inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a moderate degree of disability 31 Disabled person with a slight inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a low degree of disability 32 Disabled person (aged 0-15) with a slight inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a degree of disability 33 Physically disabled person with a slight inability to perform everyday tasks; he or she has refused to answer if he or she has a disability degree certificate and to what degree he or she is disabled 34 Legally disabled person, having a high disability degree certificate 35 Legally disabled person, having a moderate disability degree certificate 36 Legally disabled person, having a low disability degree certificate 37 Legally disabled person (aged 0-15), having a disability degree certificate 38 Person with no impaired ability to perform everyday tasks; he or she has a valid disability degree certificate, while in the same time refusing to answer to what degree he or she is disabled 40 Legally disabled person; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a high degree of disability 41 Legally disabled person; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a moderate degree of disability 42 Legally disabled person; he or she has refused to answer if he or she has a disability degree certificate, while in the same time declaring a low degree of disability 44 Person with no impaired ability to perform everyday tasks; no disability degree certificate provided or disability degree specified 45 Person who has refused to answer to what degree he or she is disabled, but has a high degree of disability certificate 46 Person who has refused to answer to what degree he or she is disabled, but has a moderate degree of disability certificate 47 Person who has refused to answer to what degree he or she is disabled, but has a low degree of disability certificate 48 Person (aged 0-15) who has refused to answer to what degree he or she is disabled, but has a degree of disability certificate 49 Person who has refused to answer to what degree he or she is disabled, but has a valid degree of disability certificate 50 Person who has refused to answer to what degree he or she is disabled and does not have a valid degree of disability certificate 51 Person who has refused to answer if he or she has a disability degree certificate and to what degree he or she is disabled, while in the same time declaring a high degree of disability 52 Person who has refused to answer if he or she has a disability degree certificate and to what degree he or she is disabled, while in the same time declaring a moderate degree of disability 53 Person who has refused to answer if he or she has a disability degree certificate and to what degree he or she is disabled, while in the same time declaring a low degree of disability 54 Person (aged 0-15) who has refused to answer if he or she has a disability degree certificate and to what degree he or she is disabled, while in the same time declaring a degree of disability 55 Person who has refused to answer if he or she has a disability degree certificate and to what degree he or she is disabled, while in the same time not informing the census officer about the degree of disability 99 Unknown This variable indicates the type of disability a person have. IPUMS Family weight Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] This variable indicates the family weight. PL2011A0421 is a 12-digit numeric variable. Codes9999999998 = Unknown. 9999999999 = NIU. IPUMS Type of family Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 1 Married couple without children 2 Married couple with children 3 Partnership without children 4 Partnership with children 5 Single mother 6 Single father 8 Unknown 9 NIU (not in universe) This variable indicates the type of family a person is belonging. IPUMS Number of persons in the family Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 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 98 Unknown 99 NIU (not in universe) This variable indicates the number of persons in the family. IPUMS Number of rooms in the dwelling <span class="h1">Dwelling Module</span></p> <p>6. Number of rooms in this dwelling</p> <div class="i1">____ 1) Total <br />____ 2) Of which rooms used solely for the purpose of conducting economic activity</div> Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 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+ 98 Unknown 99 NIU (not in universe) This variable indicates the number of rooms in dwelling. IPUMS Total number of children in the family Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 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 98 Unknown 99 NIU (not in universe) This variable indicates the total number of children in family. IPUMS Number of children age 0 to 14 Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 98 Unknown 99 NIU (not in universe) This variable indicates the number of children aged 0 to 14 in a family. IPUMS Total number of dependent children Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 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+ 98 Unknown 99 NIU (not in universe) This variable indicates the total number of dependent children in a family. IPUMS Number of persons age 0 to 29 in family Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 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 98 Unknown 99 NIU (not in universe) This variable indicates the number of person's aged 0 to 29 in the family. IPUMS Number of persons age 30 to 59 in family Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8+ 98 Unknown 99 NIU (not in universe) This variable indicates the number of persons aged 30 to 59 in the family. IPUMS Number of persons age 60 or older in family Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 1 1 2 2 3 3+ 8 Unknown 9 NIU (not in universe) This variable indicates the number of persons aged 60 or older in the family. IPUMS Subfamily number Poland 2011: Persons in a family [discrepancies: type I none; type II 3.7%] 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 98 Unknown 99 NIU (not in universe) This variable indicates the person's subfamily number. IPUMS