Population census 2011 DDI_HUN_2011_PHC_v01_M_v7.6_A_IPUMS IPUMS

Integrated Public Use Microdata Series (IPUMS) International

 IPUMS April 1, 2025 IPUMS, 50 Willey Hall, 225 - 19th Avenue South, Minneapolis, MN 55455 Organization for Economic Co-operation and Development, Development Co-operation Directorate JADE#:60525;MEHLB(2010)12 IPUMS Version 7.6 October 2025 : NEW FEATURES. --NO "new features" listed in Revision History NEW SAMPLES. --Six new census samples for Honduras (2013), Kenya (2019), Malawi (2018), Mongolia (2010, 2020), and Mozambique (2017) were added to the data series. All census samples extend pre-existing series for those countries. --91 quarterly labor force surveys from the Philippines (1997 - 2019) were added to IPUMS. SUPPLEMENTAL DATA. --No "supplemental data" listed in revision history NEW VARIABLES. --New spatially harmonized birthplace and previous-residence variables are available for samples in this data release. More information is available here (https://international.ipums.org/international/geo_mig.shtml). --Users should note that many older migration and birthplace variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. For birthplace variables refer to this table (https://international.ipums.org/international/resources/misc_docs/migCrosswalk_names.pdf). EDITED SAMPLES. --For the Zambia 2000 sample, an error in the household breaks was corrected, resulting in the creation of 1,988 new households (1% increase) that were previously combined with other households. The person records included in the sample did not change. Due to an inconsistency in the original file, no household-level information other than geographic location is available for these newly identified households, necessitating the addition of "unknown" values for this sample to the following variables: BEDROOMS, ELECTRIC, FLOOR, FUELCOOK, FUELHEAT, OWNERSHIP, PHONE, RADIO, REFRIG, ROOMS, SEWAGE, TRASH, WATSRC, TV, TOILET, GQ, ROOF, WATSUP, BIKE, MOTORCYCLE, KITCHEN, GQTYPE, AUTOS, and WALL. EDITED VARIABLES. --For the 1998 and 2008 Malawi samples, the family interrelationship pointer variables MOMLOC and POPLOC were modified to allow a "Spouse/partner" of the household head to be linked as a parent to an "Other relative", because the enumeration instructions specify that adopted and stepchildren were categorized as "Other relative". These samples are now consistent with the links made in the newly released 2018 Malawi sample, which had the same enumeration instructions for adopted and stepchildren. --In the samples for Côte d'Ivoire 1988 and 1998, Rwanda 1991 and 2002, Togo 1960 and 2010, and South Africa 2001, for the harmonized variable POLYGAM, persons in consensual unions were previously coded as "No, in monogamous union". Because there was no response option in these samples for polygamous consensual unions, it is more appropriate to treat these cases as not-in-universe, so they have been recoded to "NIU (not in universe)". --MARST has been edited for Honduras 1974 to reclassify the source variable responses "married, wife lives separately" and "consensual union, companion lives separately" as separations. The documentation suggests that "separately" actually indicates a relationship separation and not an absent spouse or companion. Other minor edits were implemented for MARST for Mozambique 1997 and 2007. --In the Mozambique 1997 sample, an error was corrected that recoded persons with a relationship of "Unknown" in the source data to "Other relative or non-relative" (6000) in the harmonized variable RELATE. These persons are now coded as "Not Stated/Unknown" (9999). --In the Malawi 1987, 1998, and 2008 samples, for variable WATSUP, a programming error was corrected such that any households who reported having piped water in either the wet or the dry season are classified as having access to piped water. This programming was also applied to the newly released 2018 sample. --The NATIVITY variable has been edited in the Chile 2017 sample to correct a programming error that mistakenly classified as foreign-born about 20 thousand person records that were actually native-born. --The MIGRATE5 variable has been edited in the Chile 2017 sample, given a programming error that classified most migrants as having changed their major geographic unit. The MIGRATE5 variable for the Chile 1982 and 1992 samples has been edited to use spatially harmonized geographic units to calculate migration status. --In the 1989, 1999, and 2009 Kenya samples, households who indicated that their lighting type or fuel was "Solar" were recoded from "No" to "Yes" in ELECTRIC, based on secondary sources documenting the spread of home solar energy systems in Kenya beginning in the mid-1980s. In the 1989 and 1999 Kenya samples, programming was removed that previously recoded households that reported using electricity as their main cooking fuel to "Yes" in the access to electricity variable ELECTRIC, making it more consistent across samples. Other minor edits were implemented for ELECTRIC in Botswana 2011, Ethiopia 1984 and 1994, Mongolia 1989, Mozambique 2007. --Some samples in DISCARE classified responses indicating "some" difficulty into "yes". These cases were revised to consistently include in "yes" only responses indicating "a lot of difficulty" or "cannot do at all". --Some codes were improperly labeled for municipalities in Honduras 1961 and 1974, which affect variables on place of residence, birthplace, and previous residence. Population census 2011 - IPUMS Subset PHC hu2011a (IPUMS Harmonized Subset) HUN_2011_PHC_v01_M_v7.6_A_IPUMS Hungarian Central Statistical Office IPUMS (c) Copyright 2011, Hungarian Central Statistical Office and Minnesota Population Center Hungarian Central Statistical Office Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.6 Version 7.6. The datasets contain selected variables from the original microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Nativity and Birthplace Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Fertility and Mortality Variables -- PERSON Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Technical Person Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Technical Person Variables -- PERSON Demographic Variables -- PERSON Other Person Variables -- PERSON Nativity and Birthplace Variables -- PERSON Fertility and Mortality Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Education Variables -- PERSON Work Variables -- PERSON Work: Occupation Variables -- PERSON Work: Industry Variables -- PERSON Migration: Global Variables -- PERSON October 1, 2011 October 1-31, 2012 Hungary None Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: Yes - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: Structure intended for human accommodation, stay (home) or converted into dwelling and also suitable for living at present. A group of technically (architecturally) adjoining places that is suitable for accommodation for the whole year. It has which has a separate entrance from a public place, courtyard or from a collectively used place inside the building (staircase, corridor etc.) - Households: An economic unit including family members studying or working away from home as well, together forming and economic community of productive and dependent persons. - Group quarters: Premises or premise groups providing collective accommodation and certain boarding for five or more persons, irrespective of whether there were persons living and boarding there at the reference date of the census. Among others, student hostels, infants' and children's home, workers' homes, hospitals, residential social institutions, hotels, boarding houses and campsites, holdiay houses owned by corporations and institutions, as well as prisons, etc. belong to this category. All Hungarian citizens and foreign citizens staying in Hungary for more than three months (excluding members of foreign dimplomatic corps and their family members) living om private and group quarters. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Hungary 2011 MICRODATA SOURCE: Hungarian Central Statistical Office SAMPLE SIZE (person records): 496762. SAMPLE DESIGN: 5% simple random sample drawn by the Hungarian Central Statistical Office. Face-to-face [f2f] Possible to do fill in a census form via the internet. Self respone, or direct enumeration. There is a household questionnaire, a person questionnaire, and institutional building's and household questionnaire. de jure, CENSUS DAY: October 1, 2011 Self-weighting (expansion factor = 20). IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS International are designed to extend this record. Hungarian Central Statistical Office Steven Ruggles, Lara Cleveland, Rodrigo Lovaton, Sula Sarkar, Matthew Sobek, Derek Burk, Dan Ehrlich, Quinn Heimann, Jane Lee, and Nate Merrill. Integrated Public Use Microdata Series, International: Version 7.6 [dataset]. Minneapolis, MN: IPUMS, 2025. https://doi.org/10.18128/D020.V7.6 Researchers should also acknowledge the statistical agency that originally produced the data: Hungary, Hungarian Central Statistical Office. Population 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. User-provided description: DOI:10.18128/D020.V7.6 Extract for hu2011a, 2025 HUN2011_PHC-H-H.dat Household records 208,974 ascii Minnesota Population Center Version 7.5, IPUMS sample HUN2011_PHC-P-H.dat Person records 496762 ascii Minnesota Population Center Version 7.5, IPUMS sample Record type RECTYPE identifies the type of record for the case: household or person. NOTE: RECTYPE is an alphabetic (character string) variable with a value of 'H' for household records and 'P' for person records. RECTYPE will not appear as a variable in the default rectangular extracts produced by the data extract system. It is only available in hierarchical extracts, to distinguish between the two record types. H Household P Person Technical Household Variables -- HOUSEHOLD Country COUNTRY gives the country from which the sample was drawn. The codes assigned to each country are those used by the UN Statistics Division and the ISO (International Organization for Standardization). 032 Argentina 051 Armenia 040 Austria 050 Bangladesh 112 Belarus 204 Benin 068 Bolivia 072 Botswana 076 Brazil 854 Burkina Faso 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 208 Denmark 214 Dominican Republic 218 Ecuador 818 Egypt 222 El Salvador 231 Ethiopia 242 Fiji 246 Finland 250 France 276 Germany 288 Ghana 300 Greece 320 Guatemala 324 Guinea 332 Haiti 340 Honduras 348 Hungary 352 Iceland 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 384 Côte d'Ivoire 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 418 Laos 426 Lesotho 430 Liberia 454 Malawi 458 Malaysia 466 Mali 480 Mauritius 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 104 Myanmar 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 578 Norway 586 Pakistan 275 Palestine 591 Panama 598 Papua New Guinea 600 Paraguay 604 Peru 608 Philippines 616 Poland 620 Portugal 630 Puerto Rico 642 Romania 643 Russia 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 703 Slovak Republic 705 Slovenia 710 South Africa 728 South Sudan 724 Spain 729 Sudan 740 Suriname 752 Sweden 756 Switzerland 834 Tanzania 764 Thailand 768 Togo 780 Trinidad and Tobago 792 Turkey 800 Uganda 804 Ukraine 826 United Kingdom 840 United States 858 Uruguay 862 Venezuela 704 Vietnam 894 Zambia 716 Zimbabwe Technical Household Variables -- HOUSEHOLD Year YEAR gives the year in which the census or survey was taken. For samples that span years, the midpoint or first year of the interval is reported. 1703 1703 1729 1729 1787 1787 1801 1801 1819 1819 1845 1845 1848 1848 1850 1850 1851 1851 1852 1852 1860 1860 1861 1861 1865 1865 1868 1868 1870 1870 1871 1871 1875 1875 1880 1880 1881 1881 1885 1885 1890 1890 1891 1891 1900 1900 1901 1901 1910 1910 1911 1911 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1966 1966 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 Technical Household Variables -- HOUSEHOLD IPUMS sample identifier SAMPLE identifies the IPUMS sample from which the case is drawn. Each sample receives a unique 9-digit code. The code is structured as follows: The first 3 digits are the ISO/UN codes used in COUNTRY The next 4 digits are the year of the census/survey The final 2 digits identify the sample within the year. For the last two digits, censuses or large census-like surveys have a value "0" (e.g, 01) in the second-to-last digit, household surveys have a value of "2" (e.g., 21), and employment surveys have a value of "4" (e.g., 41). 032197001 Argentina 1970 032198001 Argentina 1980 032199101 Argentina 1991 032200101 Argentina 2001 032201001 Argentina 2010 051200101 Armenia 2001 051201101 Armenia 2011 040197101 Austria 1971 040198101 Austria 1981 040199101 Austria 1991 040200101 Austria 2001 040201101 Austria 2011 050199101 Bangladesh 1991 050200101 Bangladesh 2001 050201101 Bangladesh 2011 112199901 Belarus 1999 112200901 Belarus 2009 204197901 Benin 1979 204199201 Benin 1992 204200201 Benin 2002 204201301 Benin 2013 068197601 Bolivia 1976 068199201 Bolivia 1992 068200101 Bolivia 2001 068201201 Bolivia 2012 072198101 Botswana 1981 072199101 Botswana 1991 072200101 Botswana 2001 072201101 Botswana 2011 076196001 Brazil 1960 076197001 Brazil 1970 076198001 Brazil 1980 076199101 Brazil 1991 076200001 Brazil 2000 076201001 Brazil 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 116199801 Cambodia 1998 116200401 Cambodia 2004 116200801 Cambodia 2008 116201301 Cambodia 2013 116201901 Cambodia 2019 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124185201 Canada 1852 124187101 Canada 1871 124188101 Canada 1881 124189101 Canada 1891 124190101 Canada 1901 124191101 Canada 1911 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 124201101 Canada 2011 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 152201701 Chile 2017 156198201 China 1982 156199001 China 1990 156200001 China 2000 170196401 Colombia 1964 170197301 Colombia 1973 170198501 Colombia 1985 170199301 Colombia 1993 170200501 Colombia 2005 188196301 Costa Rica 1963 188197301 Costa Rica 1973 188198401 Costa Rica 1984 188200001 Costa Rica 2000 188201101 Costa Rica 2011 192200201 Cuba 2002 192201201 Cuba 2012 208178701 Denmark 1787 208180101 Denmark 1801 208184501 Denmark 1845 208188001 Denmark 1880 208188501 Denmark 1885 214196001 Dominican Republic 1960 214197001 Dominican Republic 1970 214198101 Dominican Republic 1981 214200201 Dominican Republic 2002 214201001 Dominican Republic 2010 218196201 Ecuador 1962 218197401 Ecuador 1974 218198201 Ecuador 1982 218199001 Ecuador 1990 218200101 Ecuador 2001 218201001 Ecuador 2010 818184801 Egypt 1848 818186801 Egypt 1868 818198601 Egypt 1986 818199601 Egypt 1996 818200601 Egypt 2006 222199201 El Salvador 1992 222200701 El Salvador 2007 231198401 Ethiopia 1984 231199401 Ethiopia 1994 231200701 Ethiopia 2007 242196601 Fiji 1966 242197601 Fiji 1976 242198601 Fiji 1986 242199601 Fiji 1996 242200701 Fiji 2007 242201401 Fiji 2014 246201001 Finland 2010 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 276181901 Germany 1819 (Mecklenburg) 276197001 Germany 1970 (West) 276197101 Germany 1971 (East) 276198101 Germany 1981 (East) 276198701 Germany 1987 (West) 288198401 Ghana 1984 288200001 Ghana 2000 288201001 Ghana 2010 300197101 Greece 1971 300198101 Greece 1981 300199101 Greece 1991 300200101 Greece 2001 300201101 Greece 2011 320196401 Guatemala 1964 320197301 Guatemala 1973 320198101 Guatemala 1981 320199401 Guatemala 1994 320200201 Guatemala 2002 324198301 Guinea 1983 324199601 Guinea 1996 324201401 Guinea 2014 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 340196101 Honduras 1961 340197401 Honduras 1974 340198801 Honduras 1988 340200101 Honduras 2001 340201301 Honduras 2013 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 348201101 Hungary 2011 352170301 Iceland 1703 352172901 Iceland 1729 352180101 Iceland 1801 352190101 Iceland 1901 352191001 Iceland 1910 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 356200941 India 2009 360197101 Indonesia 1971 360197601 Indonesia 1976 360198001 Indonesia 1980 360198501 Indonesia 1985 360199001 Indonesia 1990 360199501 Indonesia 1995 360200001 Indonesia 2000 360200501 Indonesia 2005 360201001 Indonesia 2010 364200601 Iran 2006 364201101 Iran 2011 368199701 Iraq 1997 372190101 Ireland 1901 372191101 Ireland 1911 372197101 Ireland 1971 372197901 Ireland 1979 372198101 Ireland 1981 372198601 Ireland 1986 372199101 Ireland 1991 372199601 Ireland 1996 372200201 Ireland 2002 372200601 Ireland 2006 372201101 Ireland 2011 372201601 Ireland 2016 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 376200801 Israel 2008 380200101 Italy 2001 380201101 Italy 2011 380201121 Italy 2011 Q1 LFS 380201221 Italy 2012 Q1 LFS 380201321 Italy 2013 Q1 LFS 380201421 Italy 2014 Q1 LFS 380201521 Italy 2015 Q1 LFS 380201621 Italy 2016 Q1 LFS 380201721 Italy 2017 Q1 LFS 380201821 Italy 2018 Q1 LFS 380201921 Italy 2019 Q1 LFS 380202021 Italy 2020 Q1 LFS 384198801 Côte d'Ivoire 1988 384199801 Côte d'Ivoire 1998 388198201 Jamaica 1982 388199101 Jamaica 1991 388200101 Jamaica 2001 400200401 Jordan 2004 404196901 Kenya 1969 404197901 Kenya 1979 404198901 Kenya 1989 404199901 Kenya 1999 404200901 Kenya 2009 404201901 Kenya 2019 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 418199501 Laos 1995 418200501 Laos 2005 418201501 Laos 2015 426199601 Lesotho 1996 426200601 Lesotho 2006 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 454201801 Malawi 2018 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 480199001 Mauritius 1990 480200001 Mauritius 2000 480201101 Mauritius 2011 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 484201501 Mexico 2015 484202001 Mexico 2020 484200521 Mexico 2005 Q1 LFS 484200522 Mexico 2005 Q2 LFS 484200523 Mexico 2005 Q3 LFS 484200524 Mexico 2005 Q4 LFS 484200621 Mexico 2006 Q1 LFS 484200622 Mexico 2006 Q2 LFS 484200623 Mexico 2006 Q3 LFS 484200624 Mexico 2006 Q4 LFS 484200721 Mexico 2007 Q1 LFS 484200722 Mexico 2007 Q2 LFS 484200723 Mexico 2007 Q3 LFS 484200724 Mexico 2007 Q4 LFS 484200821 Mexico 2008 Q1 LFS 484200822 Mexico 2008 Q2 LFS 484200823 Mexico 2008 Q3 LFS 484200824 Mexico 2008 Q4 LFS 484200921 Mexico 2009 Q1 LFS 484200922 Mexico 2009 Q2 LFS 484200923 Mexico 2009 Q3 LFS 484200924 Mexico 2009 Q4 LFS 484201021 Mexico 2010 Q1 LFS 484201022 Mexico 2010 Q2 LFS 484201023 Mexico 2010 Q3 LFS 484201024 Mexico 2010 Q4 LFS 484201121 Mexico 2011 Q1 LFS 484201122 Mexico 2011 Q2 LFS 484201123 Mexico 2011 Q3 LFS 484201124 Mexico 2011 Q4 LFS 484201221 Mexico 2012 Q1 LFS 484201222 Mexico 2012 Q2 LFS 484201223 Mexico 2012 Q3 LFS 484201224 Mexico 2012 Q4 LFS 484201321 Mexico 2013 Q1 LFS 484201322 Mexico 2013 Q2 LFS 484201323 Mexico 2013 Q3 LFS 484201324 Mexico 2013 Q4 LFS 484201421 Mexico 2014 Q1 LFS 484201422 Mexico 2014 Q2 LFS 484201423 Mexico 2014 Q3 LFS 484201424 Mexico 2014 Q4 LFS 484201521 Mexico 2015 Q1 LFS 484201522 Mexico 2015 Q2 LFS 484201523 Mexico 2015 Q3 LFS 484201524 Mexico 2015 Q4 LFS 484201621 Mexico 2016 Q1 LFS 484201622 Mexico 2016 Q2 LFS 484201623 Mexico 2016 Q3 LFS 484201624 Mexico 2016 Q4 LFS 484201721 Mexico 2017 Q1 LFS 484201722 Mexico 2017 Q2 LFS 484201723 Mexico 2017 Q3 LFS 484201724 Mexico 2017 Q4 LFS 484201821 Mexico 2018 Q1 LFS 484201822 Mexico 2018 Q2 LFS 484201823 Mexico 2018 Q3 LFS 484201824 Mexico 2018 Q4 LFS 484201921 Mexico 2019 Q1 LFS 484201922 Mexico 2019 Q2 LFS 484201923 Mexico 2019 Q3 LFS 484201924 Mexico 2019 Q4 LFS 484202021 Mexico 2020 Q1 LFS 484202023 Mexico 2020 Q3 LFS 496198901 Mongolia 1989 496200001 Mongolia 2000 496201001 Mongolia 2010 496202001 Mongolia 2020 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 508201701 Mozambique 2017 104201401 Myanmar 2014 524200101 Nepal 2001 524201101 Nepal 2011 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 528201101 Netherlands 2011 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 578180101 Norway 1801 578186501 Norway 1865 578187501 Norway 1875 578190001 Norway 1900 578191001 Norway 1910 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 275199701 Palestine 1997 275200701 Palestine 2007 275201701 Palestine 2017 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 598198001 Papua New Guinea 1980 598199001 Papua New Guinea 1990 598200001 Papua New Guinea 2000 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 604201701 Peru 2017 608199721 Philippines 1997 Q1 LFS 608199722 Philippines 1997 Q2 LFS 608199723 Philippines 1997 Q3 LFS 608199724 Philippines 1997 Q4 LFS 608199821 Philippines 1998 Q1 LFS 608199822 Philippines 1998 Q2 LFS 608199823 Philippines 1998 Q3 LFS 608199824 Philippines 1998 Q4 LFS 608199921 Philippines 1999 Q1 LFS 608199922 Philippines 1999 Q2 LFS 608199923 Philippines 1999 Q3 LFS 608199924 Philippines 1999 Q4 LFS 608200021 Philippines 2000 Q1 LFS 608200022 Philippines 2000 Q2 LFS 608200023 Philippines 2000 Q3 LFS 608200024 Philippines 2000 Q4 LFS 608200121 Philippines 2001 Q1 LFS 608200122 Philippines 2001 Q2 LFS 608200123 Philippines 2001 Q3 LFS 608200124 Philippines 2001 Q4 LFS 608200221 Philippines 2002 Q1 LFS 608200222 Philippines 2002 Q2 LFS 608200223 Philippines 2002 Q3 LFS 608200224 Philippines 2002 Q4 LFS 608200321 Philippines 2003 Q1 LFS 608200322 Philippines 2003 Q2 LFS 608200323 Philippines 2003 Q3 LFS 608200324 Philippines 2003 Q4 LFS 608200421 Philippines 2004 Q1 LFS 608200422 Philippines 2004 Q2 LFS 608200423 Philippines 2004 Q3 LFS 608200424 Philippines 2004 Q4 LFS 608200521 Philippines 2005 Q1 LFS 608200522 Philippines 2005 Q2 LFS 608200523 Philippines 2005 Q3 LFS 608200524 Philippines 2005 Q4 LFS 608200621 Philippines 2006 Q1 LFS 608200622 Philippines 2006 Q2 LFS 608200623 Philippines 2006 Q3 LFS 608200624 Philippines 2006 Q4 LFS 608200721 Philippines 2007 Q1 LFS 608200722 Philippines 2007 Q2 LFS 608200723 Philippines 2007 Q3 LFS 608200724 Philippines 2007 Q4 LFS 608200821 Philippines 2008 Q1 LFS 608200822 Philippines 2008 Q2 LFS 608200823 Philippines 2008 Q3 LFS 608200824 Philippines 2008 Q4 LFS 608200921 Philippines 2009 Q1 LFS 608200922 Philippines 2009 Q2 LFS 608200923 Philippines 2009 Q3 LFS 608200924 Philippines 2009 Q4 LFS 608201021 Philippines 2010 Q1 LFS 608201022 Philippines 2010 Q2 LFS 608201023 Philippines 2010 Q3 LFS 608201024 Philippines 2010 Q4 LFS 608201121 Philippines 2011 Q1 LFS 608201122 Philippines 2011 Q2 LFS 608201123 Philippines 2011 Q3 LFS 608201124 Philippines 2011 Q4 LFS 608201221 Philippines 2012 Q1 LFS 608201222 Philippines 2012 Q2 LFS 608201223 Philippines 2012 Q3 LFS 608201224 Philippines 2012 Q4 LFS 608201321 Philippines 2013 Q1 LFS 608201322 Philippines 2013 Q2 LFS 608201323 Philippines 2013 Q3 LFS 608201324 Philippines 2013 Q4 LFS 608201421 Philippines 2014 Q1 LFS 608201422 Philippines 2014 Q2 LFS 608201423 Philippines 2014 Q3 LFS 608201424 Philippines 2014 Q4 LFS 608201521 Philippines 2015 Q1 LFS 608201522 Philippines 2015 Q2 LFS 608201523 Philippines 2015 Q3 LFS 608201524 Philippines 2015 Q4 LFS 608201621 Philippines 2016 Q1 LFS 608201622 Philippines 2016 Q2 LFS 608201623 Philippines 2016 Q3 LFS 608201624 Philippines 2016 Q4 LFS 608201721 Philippines 2017 Q1 LFS 608201722 Philippines 2017 Q2 LFS 608201723 Philippines 2017 Q3 LFS 608201724 Philippines 2017 Q4 LFS 608201821 Philippines 2018 Q1 LFS 608201822 Philippines 2018 Q2 LFS 608201823 Philippines 2018 Q3 LFS 608201824 Philippines 2018 Q4 LFS 608201921 Philippines 2019 Q1 LFS 608201922 Philippines 2019 Q2 LFS 608201923 Philippines 2019 Q3 LFS 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 608201001 Philippines 2010 616197801 Poland 1978 616198801 Poland 1988 616200201 Poland 2002 616201101 Poland 2011 620198101 Portugal 1981 620199101 Portugal 1991 620200101 Portugal 2001 620201101 Portugal 2011 630197001 Puerto Rico 1970 630198001 Puerto Rico 1980 630199001 Puerto Rico 1990 630200001 Puerto Rico 2000 630200501 Puerto Rico 2005 630201001 Puerto Rico 2010 630201501 Puerto Rico 2015 630202001 Puerto Rico 2020 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 642201101 Romania 2011 643200201 Russia 2002 643201001 Russia 2010 646199101 Rwanda 1991 646200201 Rwanda 2002 646201201 Rwanda 2012 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 686201301 Senegal 2013 694200401 Sierra Leone 2004 694201501 Sierra Leone 2015 703199101 Slovak Republic 1991 703200101 Slovak Republic 2001 703201101 Slovak Republic 2011 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 710201601 South Africa 2016 728200801 South Sudan 2008 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 724200521 Spain 2005 Q1 LFS 724200522 Spain 2005 Q2 LFS 724200523 Spain 2005 Q3 LFS 724200524 Spain 2005 Q4 LFS 724200621 Spain 2006 Q1 LFS 724200622 Spain 2006 Q2 LFS 724200623 Spain 2006 Q3 LFS 724200624 Spain 2006 Q4 LFS 724200721 Spain 2007 Q1 LFS 724200722 Spain 2007 Q2 LFS 724200723 Spain 2007 Q3 LFS 724200724 Spain 2007 Q4 LFS 724200821 Spain 2008 Q1 LFS 724200822 Spain 2008 Q2 LFS 724200823 Spain 2008 Q3 LFS 724200824 Spain 2008 Q4 LFS 724200921 Spain 2009 Q1 LFS 724200922 Spain 2009 Q2 LFS 724200923 Spain 2009 Q3 LFS 724200924 Spain 2009 Q4 LFS 724201021 Spain 2010 Q1 LFS 724201022 Spain 2010 Q2 LFS 724201023 Spain 2010 Q3 LFS 724201024 Spain 2010 Q4 LFS 724201121 Spain 2011 Q1 LFS 724201122 Spain 2011 Q2 LFS 724201123 Spain 2011 Q3 LFS 724201124 Spain 2011 Q4 LFS 724201221 Spain 2012 Q1 LFS 724201222 Spain 2012 Q2 LFS 724201223 Spain 2012 Q3 LFS 724201224 Spain 2012 Q4 LFS 724201321 Spain 2013 Q1 LFS 724201322 Spain 2013 Q2 LFS 724201323 Spain 2013 Q3 LFS 724201324 Spain 2013 Q4 LFS 724201421 Spain 2014 Q1 LFS 724201422 Spain 2014 Q2 LFS 724201423 Spain 2014 Q3 LFS 724201424 Spain 2014 Q4 LFS 724201521 Spain 2015 Q1 LFS 724201522 Spain 2015 Q2 LFS 724201523 Spain 2015 Q3 LFS 724201524 Spain 2015 Q4 LFS 724201621 Spain 2016 Q1 LFS 724201622 Spain 2016 Q2 LFS 724201623 Spain 2016 Q3 LFS 724201624 Spain 2016 Q4 LFS 724201721 Spain 2017 Q1 LFS 724201722 Spain 2017 Q2 LFS 724201723 Spain 2017 Q3 LFS 724201724 Spain 2017 Q4 LFS 724201821 Spain 2018 Q1 LFS 724201822 Spain 2018 Q2 LFS 724201823 Spain 2018 Q3 LFS 724201824 Spain 2018 Q4 LFS 724201921 Spain 2019 Q1 LFS 724201922 Spain 2019 Q2 LFS 724201923 Spain 2019 Q3 LFS 724201924 Spain 2019 Q4 LFS 724202021 Spain 2020 Q1 LFS 724202022 Spain 2020 Q2 LFS 724202023 Spain 2020 Q3 LFS 724202024 Spain 2020 Q4 LFS 729200801 Sudan 2008 740200401 Suriname 2004 740201201 Suriname 2012 752188001 Sweden 1880 752189001 Sweden 1890 752190001 Sweden 1900 752191001 Sweden 1910 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 756201101 Switzerland 2011 834198801 Tanzania 1988 834200201 Tanzania 2002 834201201 Tanzania 2012 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 768196001 Togo 1960 768197001 Togo 1970 768201001 Togo 2010 780197001 Trinidad and Tobago 1970 780198001 Trinidad and Tobago 1980 780199001 Trinidad and Tobago 1990 780200001 Trinidad and Tobago 2000 780201101 Trinidad and Tobago 2011 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 800201401 Uganda 2014 804200101 Ukraine 2001 826185101 United Kingdom 1851 (England and Wales) 826185102 United Kingdom 1851 (Scotland) 826185103 United Kingdom 1851 (2% sample) 826186101 United Kingdom 1861 (England and Wales) 826186102 United Kingdom 1861 (Scotland) 826187101 United Kingdom 1871 (Scotland) 826188101 United Kingdom 1881 (England and Wales) 826188102 United Kingdom 1881 (Scotland) 826189101 United Kingdom 1891 (England and Wales) 826189102 United Kingdom 1891 (Scotland) 826190101 United Kingdom 1901 (England and Wales) 826190102 United Kingdom 1901 (Scotland) 826191101 United Kingdom 1911 (England and Wales) 826196101 United Kingdom 1961 826197101 United Kingdom 1971 826199101 United Kingdom 1991 826200101 United Kingdom 2001 840185001 United States 1850 (100%) 840185002 United States 1850 (1%) 840186001 United States 1860 (1%) 840187001 United States 1870 (1%) 840188001 United States 1880 (100%) 840188002 United States 1880 (10%) 840190001 United States 1900 (5%) 840191001 United States 1910 (1%) 840196001 United States 1960 840197001 United States 1970 840198001 United States 1980 840199001 United States 1990 840200001 United States 2000 840200501 United States 2005 840201001 United States 2010 840201501 United States 2015 840202001 United States 2020 858196301 Uruguay 1963 858196302 Uruguay 1963 (full count) 858197501 Uruguay 1975 858197502 Uruguay 1975 (full count) 858198501 Uruguay 1985 858198502 Uruguay 1985 (full count) 858199601 Uruguay 1996 858199602 Uruguay 1996 (full count) 858200621 Uruguay 2006 858201101 Uruguay 2011 858201102 Uruguay 2011 (full count) 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 704201901 Vietnam 2019 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 716201201 Zimbabwe 2012 Technical Household Variables -- HOUSEHOLD Household serial number SERIAL is an identifying number unique to each household in a given sample. All person records are assigned the same serial number as the household record that they follow. (Person records also have their own unique identifiers -- see PERNUM.) The combination of SAMPLE and SERIAL provides a unique identifier for every household in the IPUMS-International database; SAMPLE, SERIAL and PERNUM uniquely identify every person in the database. SERIAL can be used to identify dwellings in some samples. In these samples, the first 7 digits of SERIAL provide the dwelling number common to all households that were sampled from the same structure. The last three digits give the sequence of the household within the dwelling. The following is a list of samples in which dwellings can be inferred: Chile 1970, 1992, 2002Colombia 1993, 2005Costa Rica 1984, 2000Cuba 2002Dominican Republic 1981, 2002, 2010Ecuador 1990, 2001Germany 1971Hungary 1980, 1990, 2001Jamaica 1982, 1991, 2001Malaysia 1970, 1991, 2000Mexico 1995, 1990, 2000, 2005Nigeria 2006Panama 2000Peru 1993, 2007Portugal 1981, 1991, 2001Spain 1991Uruguay 2011Venezuela 1990, 2001Vietnam 1989In all other samples, the last 3 digits are always zeroes. SERIAL was constructed for IPUMS-International, and has no relation to the serial number in the original datasets. The U.S. 1900 sample and 1880 10% sample have multi-household dwellings that can be identified using the last 3 digits of SERIAL. SERIAL is a 10-digit numeric variable. The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes. Technical Household Variables -- HOUSEHOLD Number of person records in the household PERSONS indicates how many person records are included in the household (i.e., the number of person records associated with the household record in the sample). These person records will all have the same serial number (SERIAL) as the household record. The information contained in the household record will normally apply to all of these persons. PERSONS is a 4-digit numeric variable. Technical Household Variables -- HOUSEHOLD Household weight HHWT indicates the number of households in the population represented by the household in the sample. For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics. NOTE: HHWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Household Variables -- HOUSEHOLD Subsample number SUBSAMP allocates each case to one of 100 subsample replicates, randomly numbered from 0 to 99. Each subsample is nationally representative and preserves any stratification of the sample from which it is drawn. Users who need a representative subset of a sample can use SUBSAMP to select their cases. For example, to randomly extract 10% of the cases from a sample, select any 10 of the 100 subsamples. 00 1st 1% subsample 01 2nd 1% subsample 02 3rd 1% subsample 03 4th 1% subsample 04 5th 1% subsample 05 6th 1% subsample 06 7th 1% subsample 07 8th 1% subsample 08 9th 1% subsample 09 10th 1% subsample 10 11th 1% subsample 11 12th 1% subsample 12 13th 1% subsample 13 14th 1% subsample 14 15th 1% subsample 15 16th 1% subsample 16 17th 1% subsample 17 18th 1% subsample 18 19th 1% subsample 19 20th 1% subsample 20 21st 1% subsample 21 22nd 1% subsample 22 23rd 1% subsample 23 24th 1% subsample 24 25th 1% subsample 25 26th 1% subsample 26 27th 1% subsample 27 28th 1% subsample 28 29th 1% subsample 29 30th 1% subsample 30 31st 1% subsample 31 32nd 1% subsample 32 33rd 1% subsample 33 34th 1% subsample 34 35th 1% subsample 35 36th 1% subsample 36 37th 1% subsample 37 38th 1% subsample 38 39th 1% subsample 39 40th 1% subsample 40 41st 1% subsample 41 42nd 1% subsample 42 43rd 1% subsample 43 44th 1% subsample 44 45th 1% subsample 45 46th 1% subsample 46 47th 1% subsample 47 48th 1% subsample 48 49th 1% subsample 49 50th 1% subsample 50 51st 1% subsample 51 52nd 1% subsample 52 53rd 1% subsample 53 54th 1% subsample 54 55th 1% subsample 55 56th 1% subsample 56 57th 1% subsample 57 58th 1% subsample 58 59th 1% subsample 59 60th 1% subsample 60 61st 1% subsample 61 62nd 1% subsample 62 63rd 1% subsample 63 64th 1% subsample 64 65th 1% subsample 65 66th 1% subsample 66 67th 1% subsample 67 68th 1% subsample 68 69th 1% subsample 69 70th 1% subsample 70 71st 1% subsample 71 72nd 1% subsample 72 73rd 1% subsample 73 74th 1% subsample 74 75th 1% subsample 75 76th 1% subsample 76 77th 1% subsample 77 78th 1% subsample 78 79th 1% subsample 79 80th 1% subsample 80 81st 1% subsample 81 82nd 1% subsample 82 83rd 1% subsample 83 84th 1% subsample 84 85th 1% subsample 85 86th 1% subsample 86 87th 1% subsample 87 88th 1% subsample 88 89th 1% subsample 89 90th 1% subsample 90 91st 1% subsample 91 92nd 1% subsample 92 93rd 1% subsample 93 94th 1% subsample 94 95th 1% subsample 95 96th 1% subsample 96 97th 1% subsample 97 98th 1% subsample 98 99th 1% subsample 99 100th 1% subsample Technical Household Variables -- HOUSEHOLD Group quarters (collective dwelling) status GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools. Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification. Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions. 00 Vacant 10 Households 20 Group quarters (collective), n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified Group Quarters Variables -- HOUSEHOLD Continent and region of country REGIONW identifies the continent and region of each country. 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia Geography: Global Variables -- HOUSEHOLD Ownership of dwelling [general version] OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. 0 NIU (not in universe) 1 Owned 2 Not owned 9 Unknown Household Economic Variables -- HOUSEHOLD Ownership of dwelling [detailed version] OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. 000 NIU (not in universe) 100 Owned 110 Owned, already paid 120 Owned, still paying 130 Owned, constructed 140 Owned, inherited 190 Owned, other 191 Owned, house 192 Owned, condominium 193 Apartment proprietor 194 Shared ownership 200 Not owned 210 Renting, not specified 211 Renting, government 212 Renting, local authority 213 Renting, parastatal 214 Renting, private 215 Renting, private company 216 Renting, individual 217 Renting, collective 218 Renting, joint state and individual 219 Renting, public subsidized 220 Renting, private subsidized 221 Renting, co-tenant 222 Renting, relative of tenant 223 Renting, cooperative 224 Renting, with a job or business 225 Renting, loan-backed habitation 226 Renting, mixed contract 227 Furnished dwelling 228 Sharecropping 230 Subletting 231 Rent to own 239 Renting, other 240 Occupied de facto/squatting 250 Free/usufruct (no cash rent) 251 Free, provided by employer 252 Free, without work or services 253 Free, provided by family or friend 254 Free, private 255 Free, public 256 Free, condemned 257 Free, other 260 Endowment, Waqf (Egypt historical) 290 Not owned, other 999 Unknown Household Economic Variables -- HOUSEHOLD Water supply WATSUP describes the physical means by which the housing unit receives its water. The primary distinction is whether or not the household had piped (running) water. 00 NIU (not in universe) 10 Yes, piped water 11 Piped inside dwelling 12 Piped, exclusively to this household 13 Piped, shared with other households 14 Piped outside the dwelling 15 Piped outside dwelling, in building 16 Piped within the building or plot of land 17 Piped outside the building or lot 18 Have access to public piped water 20 No piped water 99 Unknown Utilities Variables -- HOUSEHOLD Sewage SEWAGE indicates whether the household has access to a sewage system or septic tank. 00 NIU (not in universe) 10 Connected to sewage system or septic tank 11 Sewage system (public sewage disposal) 12 Septic tank (private sewage disposal) 20 Not connected to sewage disposal system 99 Unknown Utilities Variables -- HOUSEHOLD Hot water heater HOTWATER indicates whether the housing unit had a water heater. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Central heating HEAT indicates the type of heating in the dwelling: individual or collective central heating, non-central heating, or none. 0 NIU (not in universe) 1 No heating 2 Central heating, not specified 3 Collective central heating 4 Individual central heating 5 Other heating, not central 6 Heating, unspecified 7 No central heating/heating unknown 9 Unknown Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Number of rooms ROOMS indicates the number of rooms occupied by the housing unit. 00 Part of a room; no rooms 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Kitchen or cooking facilities KITCHEN indicates whether the household had a kitchen, cooking facilities, or room dedicated to food preparation. 00 NIU (not in universe) 10 No kitchen 11 Food is prepared in a non-kitchen room 13 Does not prepare food in the dwelling 20 Yes, have a kitchen 21 Kitchen located inside the dwelling 22 Indoor kitchen, exclusive use 23 Indoor kitchen, shared use 24 Exclusive use of kitchen (indoor/outdoor status not specified) 25 Shared use of kitchen with another household (indoor/outdoor status not specified) 26 Kitchen located outside the dwelling 27 Outdoor kitchen, exclusive use 28 Outdoor kitchen, shared use 99 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Toilet TOILET indicates whether the household had access to a toilet and, in most cases, whether it was a flush toilet or other type of installation. 00 NIU (not in universe) 10 No toilet 11 No flush toilet 20 Have toilet, type not specified 21 Flush toilet 22 Non-flush, latrine 23 Non-flush, other and unspecified 99 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Year structure was built BUILTYR indicates the year in which construction was completed on the building in which the household resides. 0000 NIU (not in universe) 1870 1870 or earlier 1871 1871 1872 1872 1873 1873 1874 1874 1875 1875 1876 1876 1877 1877 1878 1878 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 Under construction 9999 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Living area in square meters LIVEAREA describes the total living area in the dwelling inhabited by the household. LIVEAREA is a 3-digit numeric variable. Codes000 = NIU (not in universe) 999 = Unknown Top codes:Unless otherwise specified: 998+ Austria 1991-2001: 150+ Belarus 1999: 201+ Belarus 2009: 250+ Germany 1987: 361+ Hungary 2001: 260+ Hungary 2011: 301+ Iran 2006: 501+ Italy 2001: 150+ Italy 2011: 145+ Laos 2005: 200+ Philippines 1990-2010: 200+ Poland 2002: 200+ Romania 2002: 221+ Romania 2011: 500+ Slovenia 2002: 101+ Spain 1991: 181+ Spain 2001-2011: 900+ Switzerland 1980-1990: 400+ Switzerland 2000: 500+ Dwelling Characteristics Variables -- HOUSEHOLD Household classification HHTYPE is a constructed variable that describes the composition of households. HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ. 00 Vacant household 01 One-person household 02 Married/cohab couple, no children 03 Married/cohab couple with children 04 Single-parent family 05 Polygamous family 06 Extended family, relatives only 07 Composite household, family and non-relatives 08 Non-family household 09 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable Constructed Household Variables -- HOUSEHOLD Number of families in household NFAMS is a constructed variable that indicates the number of families within each household. Family membership is defined by FAMUNIT. A "family" is any group of persons related by blood, adoption, or marriage. An unrelated individual within the household is considered a separate family. Thus, a household consisting of a widow and a domestic employee contains two families; a household consisting of a large, multi-generation extended family with no persons unrelated to the head counts as a single family. NFAMS is constructed from information in RELATE (relationship to head) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). See those variable descriptions for more detail. 0 Vacant household 1 1 family 2 2 families 3 3 families 4 4 families 5 5 families 6 6 families 7 7 families 8 8 families 9 9 or more families Constructed Household Variables -- HOUSEHOLD Number of married couples in household NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household. NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household). 0 No married couples in household 1 1 couple 2 2 couples 3 3 couples 4 4 couples 5 5 couples 6 6 couples 7 7 couples 8 8 couples 9 9 or more couples Constructed Household Variables -- HOUSEHOLD Number of mothers in household NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household. NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household). 0 No mothers in household 1 1 mother 2 2 mothers 3 3 mothers 4 4 mothers 5 5 mothers 6 6 mothers 7 7 mothers 8 8 mothers 9 9 or more mothers in household Constructed Household Variables -- HOUSEHOLD Number of fathers in household NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household. NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household). 0 No fathers in household 1 1 father 2 2 fathers 3 3 fathers 4 4 fathers 5 5 fathers 6 6 fathers 7 7 fathers 8 8 fathers 9 9 or more fathers in household Constructed Household Variables -- HOUSEHOLD Head's location in household HEADLOC gives the person number (PERNUM) of the head of household in samples in which persons are organized into households. HEADLOC is a 3-digit numeric variable. Constructed Household Variables -- HOUSEHOLD Dwelling number Hungary 2011: All records This variable indicates the dwelling number. This is a 7-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Household number (within dwelling) Hungary 2011: All records This variable indicates the household number (within the dwelling). 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 Technical Household Variables -- HOUSEHOLD Number of households in dwelling Hungary 2011: All records This variable indicates the number of households in the dwelling. 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 18 18 19 19 Technical Household Variables -- HOUSEHOLD Number of persons in dwelling Hungary 2011: All records This variable indicates the number of persons in the dwelling. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 39 39 49 49 52 52 Technical Household Variables -- HOUSEHOLD Number of persons in household Hungary 2011: All records This variable indicates the number of persons in the household. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 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 39 39 49 49 52 52 Technical Household Variables -- HOUSEHOLD Type of building <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>1. What is the type of building?</p> <div class="i1">[] 1 Family house, 1-3 dwelling residential building<br />[] 2 Residential building of 4 or more flats<br />[] 3 Holiday resort<br />[] 4 Not residential building (e.g. public institute, office building, factory building)</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">1. What is the type of building?</span></p> <p><span class="em">Residential building</span>: a building which contains mostly dwellings. Residential buildings are broken down in two groups by the number of dwellings: family house, 1-3 unit dwelling residential building and residential building of 4 or more flats.</p> <p><span class="em">Holiday resort</span>: a building with one or more units used temporary for recreation, holiday and rest.</p> <p><span class="em">Not residential building</span>: any kind of building where the majority of rooms are nonresidential or rooms used for other than habitation purposes, there is at least one dwelling or occupied other housing unit. This building might be a school, office-house, shopping-house, industrial plant. This category contains also other buildings, such as economic (e.g. storage rooms, workshops, shops, garages, wine press-houses, stables), temporary, mobile or other facilities (e.g. huts, hovels, caravans, caves, railway carriages, ships).</p> <p>The answer "<span class="em">Not residential building" </span>should be marked also in the case of dwellings found in institutional buildings, such as buildings of dormitories, workers' accommodation houses, social homes, children's homes, daily nurseries, hotels, pensions, hospitals. Hungary 2011: All households This variable indicates the type of building. 1 Family house, residential building 2 Seasonal or holiday housing unit 3 Not residential building (public institute, office building, factory building) 4 Person living in institution, homeless with no home address Group Quarters Variables -- HOUSEHOLD Period of construction of the dwelling <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <p>3. When was the dwelling built?</p> <div class="i1">[] 1 Before 1919<br />[] 2 1919-1945<br />[] 3 1946-1960<br />[] 4 1961-1970<br />[] 5 1971-1980<br />[] 6 1981-1990<br />[] 7 1991-2000<br />[] 8 2001-2005<br />[] 9 2006 or later<br />[] 10 Unknown</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">3. When was the dwelling built?</span> <br />That period must be marked when the official permit for occupation had been issued. In case the dwelling does not have a permit yet but is already occupied then the year of move must be considered as the year of construction.</p> <p>In case the main structural parts of the building consisting the dwelling had been significantly transformed since their original built (e.g. joist between floors had been wrecked then rebuilt) the year of rebuilding must be marked as the year of construction irrespectively of the time when the permit had been issued.</p> <p>Refurbishing dwellings with the main walls unaltered or creating a new dwelling out of more dwellings do not change the year of construction. Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the period of construction of the dwelling. 01 Before 1919 02 1919 to 1945 03 1946 to 1960 04 1961 to 1970 05 1971 to 1980 06 1981 to 1990 07 1991 to 2000 08 2001 to 2005 09 2006 and after 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Type of housing unit <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <p>2. What is the type of the housing unit?</p> <div class="i1">[] Dwelling (family house as well)<br />[] Holiday home<br />[] Others (e.g. shop, caravan)</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">2. What is the type of the housing unit?</span></p> <p><span class="em">Apartment or family house </span>can be marked only if the dwelling is intended for human accommodation, built for or converted into dwelling and also suitable for living at present. A group of technically (architecturally) adjoining places that is suitable for accommodation for the whole year. It has which has a separate entrance from a public place, courtyard or from a collectively used place inside the building (staircase, corridor etc.).</p> <p>If a summer kitchen is not used by the household living in the main building but is lent to another household e.g. a subtenant than it is considered as a separate housing unit. In this case the type of the housing unit is other. If the address of the summer kitchen is missing from the Address list it must be entered in a new row.</p> <p>Holiday home and other can be marked only if it is inhabited i.e.at least one person lives there at the reference date (in this case only it is included in the group of housing units to be enumerated).</p> <p>Indicate <span class="em">Other</span> in case of</p> <div class="i1">- Occupied parts of business premises (warehouse, wine press-house, stable, workshop, wash-house, shop, garage etc.),<br />- Occupied parts of temporary, mobile or other facilities (hut, caravan, ship cave etc.)</div> Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the type of housing unit. 1 Dwelling (family house as well) 2 Holiday home 3 Other (eg. shop, caravan) 9 NIU (not in universe) Group Quarters Variables -- HOUSEHOLD Occupancy status of housing unit <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>5. How is the dwelling used?</p> <div class="i1">[] Habitually, for everyday life as a home<br />[] Only seasonally or as a second home<br />[] For other purpose (e.g. office, doctor's office)<br />[] Vacant dwelling, no dwellers</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">5. How is the dwelling used?</span> <br />The dwelling is used habitually, for everyday life as a home when its inhabitants are living there permanently in the whole year or in most of the year.</p> <p>The dwelling is used only seasonally or as a second home when its inhabitants are living there only temporarily, in a certain period or occasionally. They can be:</p> <div class="i1">- Seasonal dwellings (for example farm-houses) that are occupied only temporarily e.g. in the time of agricultural works,<br />- Dwellings in suburban or rural areas that are only used for recreational purposes mostly in nice weather. (Not occupied holiday houses must not be enumerated).</div><p>The dwelling is used <span class="em">for other purpose </span>when it is considered a dwelling however in the time of the enumeration it was used as e.g. an office, a doctor's office, a workshop, though at any time it could have been suitable -- without any alteration -- for use as dwelling.</p> <p><span class="em">Vacant dwelling </span>must be marked in case the dwelling has no inhabitants and is not used for other purpose either. This answer can be marked also when the persons who have their permanent home in the dwelling are staying abroad for more than 12 months and the dwelling has no other inhabitants and is not used for other purpose either. This is the right answer also in the case of dwellings that are not yet occupied but have an official permit for occupation.</p> <p>In case you find a dwelling occupied by <span class="em">foreign diplomats </span>or their relatives, please leave the Dwelling Questionnaire empty (if did not get a pre-printed one) and do not complete any Personal Questionnaires. Hungary 2011: Private households, seasonal and non-residential housing units [discrepancies: none] This variable indicates the occupancy status of the housing unit. 1 Occupied habitually, for everyday life as home 9 NIU (not in universe) Technical Household Variables -- HOUSEHOLD Type of ownership <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <p>6. Who is the owner of the dwelling?</p> <div class="i1">[] Natural person<br />[] Local government<br />[] Other institution, organization (e.g. company, enterprise, church)</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">6. Who is owner of the dwelling?</span> <br />The answer must be related to the whole dwelling, irrespectively that the dwelling has one or more owners, the owner lives in the dwelling or not, and the title of use (see Personal Questionnaire question 4.2.).</p> <p>If instead of a person, the owner of the dwelling is an institution, organization or company as well, the answer should be marked according to the majority shareholding. In case of equal owning the natural person is the right answer. Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the type of ownership of the dwelling. 1 Natural person(s) 2 Local government 3 Other institution, organization (e.g. company, enterprise, church) 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Size of housing unit according to the number of rooms 7. Is there any... <br />A room is considered as a bedroom, a dining room, a living room. <br />Multi-purpose rooms must be divided by usage (e.g. American kitchen divides to kitchen and room). <br />Please mark a "no" answer!</p> <div class="i1">7.1 Room (over 12 square meters)</div><p> </p> <div class="i2">[] Yes _ _ (number)<br />[] No</div><div class="i1">7.2 Room (12 square meters or smaller)</div><p> </p> <div class="i2">[] Yes _ _ (number)<br />[] No</div><div class="i1">7.3 Kitchen (4 square meters or larger)</div><p> </p> <div class="i2">[] Yes<br />[] No</div><div class="i1">7.4 Kitchen (under 4 square meters)</div><p> </p> <div class="i2">[] Yes<br />[] No</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">7. Is there a room, a kitchen etc. in the dwelling?</span> <br />Rooms and kitchens must be enumerated with their size also taken into account. Premises of common airspace with more functions (e.g. living room and cooking room together) must be divided by function. Attics (mansards) must be enumerated only if the headroom is 1.9 m2 or higher. Gallery is not considered an individual room.</p> <p>In questions 7.1.- 7.7 do not forget to mark "no" in case the given premise is not available in the dwelling.</p> <div class="i1">7.1., 7.2. <span class="em">Rooms</span> are premises provided with direct natural light used as living rooms, bedrooms, dining rooms etc. They must be taken into account by their size.<br /><br />7.3., 7.4.<span class="em"> Kitchens </span>are premises established and used for cooking (or eating). Kitchenettes and kitchen cabinets are included. In case the dwelling does not have a kitchen but has a summer kitchen that is used for cooking by the household living in the main building then it must be counted according to the size.<br /><br />Premises of common airspace with more functions had been enumerated based on the purpose of use, and classified in the appropriate category of premises.<br /><br />7.5. <span class="em">Bathroom</span> (shower-stall, wash-basin alcove) is a premise used for washing in the dwelling. Bathrooms generally are equipped with water supply system, sewage disposal system and bathing (washing) facilities.<br /><br />7.6. The total number of flush toilets must be marked irrespective of whether they are in a separate room or e.g. in the bathroom. Flush toilets belonging to the dwelling and used exclusively by the occupants must not be counted if they are not in the dwelling.<br /><br />7.7. <span class="em">Other room </span>e.g. lobby, corridor, pantry. In case you answered other to question 2 and the housing unit contains more premises, then each premise must be counted according to its function. However if it consists of one function, only then the premise must be counted as a room of the given size.</div> Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the size of the dwelling according to the number of rooms. 01 1 room with no kitchen 02 1 room with kitchen(s) 03 2 rooms with no kitchen 04 2 rooms with kitchen(s) 05 3 rooms 06 4 rooms 07 5 rooms 08 6 or more rooms 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Kitchen (4 square meters or larger) <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <div class="i1">7.3 Kitchen (4 square meters or larger)</div><p> </p> <div class="i2">[] Yes<br />[] No</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">7. Is there a room, a kitchen etc. in the dwelling?</span> <br />Rooms and kitchens must be enumerated with their size also taken into account. Premises of common airspace with more functions (e.g. living room and cooking room together) must be divided by function. Attics (mansards) must be enumerated only if the headroom is 1.9 m2 or higher. Gallery is not considered an individual room.</p> <p>In questions 7.1.- 7.7 do not forget to mark "no" in case the given premise is not available in the dwelling.</p> <div class="i1">7.1., 7.2. <span class="em">Rooms</span> are premises provided with direct natural light used as living rooms, bedrooms, dining rooms etc. They must be taken into account by their size.<br /><br />7.3., 7.4.<span class="em"> Kitchens </span>are premises established and used for cooking (or eating). Kitchenettes and kitchen cabinets are included. In case the dwelling does not have a kitchen but has a summer kitchen that is used for cooking by the household living in the main building then it must be counted according to the size.<br /><br />Premises of common airspace with more functions had been enumerated based on the purpose of use, and classified in the appropriate category of premises.<br /><br />7.5. <span class="em">Bathroom</span> (shower-stall, wash-basin alcove) is a premise used for washing in the dwelling. Bathrooms generally are equipped with water supply system, sewage disposal system and bathing (washing) facilities.<br /><br />7.6. The total number of flush toilets must be marked irrespective of whether they are in a separate room or e.g. in the bathroom. Flush toilets belonging to the dwelling and used exclusively by the occupants must not be counted if they are not in the dwelling.<br /><br />7.7. <span class="em">Other room </span>e.g. lobby, corridor, pantry. In case you answered other to question 2 and the housing unit contains more premises, then each premise must be counted according to its function. However if it consists of one function, only then the premise must be counted as a room of the given size.</div> Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates whether the dwelling has a kitchen (4 square meters or larger). 0 No 1 Yes 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Kitchen (under 4 square meters) <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <div class="i1">7.4 Kitchen (under 4 square meters)</div><p> </p> <div class="i2">[] Yes<br />[] No</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">7. Is there a room, a kitchen etc. in the dwelling?</span> <br />Rooms and kitchens must be enumerated with their size also taken into account. Premises of common airspace with more functions (e.g. living room and cooking room together) must be divided by function. Attics (mansards) must be enumerated only if the headroom is 1.9 m2 or higher. Gallery is not considered an individual room.</p> <p>In questions 7.1.- 7.7 do not forget to mark "no" in case the given premise is not available in the dwelling.</p> <div class="i1">7.1., 7.2. <span class="em">Rooms</span> are premises provided with direct natural light used as living rooms, bedrooms, dining rooms etc. They must be taken into account by their size.<br /><br />7.3., 7.4.<span class="em"> Kitchens </span>are premises established and used for cooking (or eating). Kitchenettes and kitchen cabinets are included. In case the dwelling does not have a kitchen but has a summer kitchen that is used for cooking by the household living in the main building then it must be counted according to the size.<br /><br />Premises of common airspace with more functions had been enumerated based on the purpose of use, and classified in the appropriate category of premises.<br /><br />7.5. <span class="em">Bathroom</span> (shower-stall, wash-basin alcove) is a premise used for washing in the dwelling. Bathrooms generally are equipped with water supply system, sewage disposal system and bathing (washing) facilities.<br /><br />7.6. The total number of flush toilets must be marked irrespective of whether they are in a separate room or e.g. in the bathroom. Flush toilets belonging to the dwelling and used exclusively by the occupants must not be counted if they are not in the dwelling.<br /><br />7.7. <span class="em">Other room </span>e.g. lobby, corridor, pantry. In case you answered other to question 2 and the housing unit contains more premises, then each premise must be counted according to its function. However if it consists of one function, only then the premise must be counted as a room of the given size.</div> Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates whether the dwelling has a kitchen (under 4 square meters). 0 No 1 Yes 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Number of bathrooms <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <div class="i1">7.5 Bathroom</div><p> </p> <div class="i2">[] Yes _ (number)<br />[] No</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">7. Is there a room, a kitchen etc. in the dwelling?</span> <br />Rooms and kitchens must be enumerated with their size also taken into account. Premises of common airspace with more functions (e.g. living room and cooking room together) must be divided by function. Attics (mansards) must be enumerated only if the headroom is 1.9 m2 or higher. Gallery is not considered an individual room.</p> <p>In questions 7.1.- 7.7 do not forget to mark "no" in case the given premise is not available in the dwelling.</p> <div class="i1">7.1., 7.2. <span class="em">Rooms</span> are premises provided with direct natural light used as living rooms, bedrooms, dining rooms etc. They must be taken into account by their size.<br /><br />7.3., 7.4.<span class="em"> Kitchens </span>are premises established and used for cooking (or eating). Kitchenettes and kitchen cabinets are included. In case the dwelling does not have a kitchen but has a summer kitchen that is used for cooking by the household living in the main building then it must be counted according to the size.<br /><br />Premises of common airspace with more functions had been enumerated based on the purpose of use, and classified in the appropriate category of premises.<br /><br />7.5. <span class="em">Bathroom</span> (shower-stall, wash-basin alcove) is a premise used for washing in the dwelling. Bathrooms generally are equipped with water supply system, sewage disposal system and bathing (washing) facilities.<br /><br />7.6. The total number of flush toilets must be marked irrespective of whether they are in a separate room or e.g. in the bathroom. Flush toilets belonging to the dwelling and used exclusively by the occupants must not be counted if they are not in the dwelling.<br /><br />7.7. <span class="em">Other room </span>e.g. lobby, corridor, pantry. In case you answered other to question 2 and the housing unit contains more premises, then each premise must be counted according to its function. However if it consists of one function, only then the premise must be counted as a room of the given size.</div> Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the number of bathrooms. 0 None 1 1 bathroom 2 2 bathrooms 3 3 bathrooms 4 4 or more bathrooms 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Useful floor space of the housing unit (in square meters) <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <p>8. How much is the total floor space of the dwelling? _ _ _ square meters.</p> <div class="i1">Do not count size of the cellar, attic, garage, balcony, terrace</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">8. How much is the total floor-space of the dwelling?</span> <br />The sum of the floor spaces of all the premises belonging to the dwelling, expressed in meters squared (m2). <br />The floor space of entrance-halls (wind-gags, wraps), built-in cupboards, changing rooms (wardrobes), store-rooms, furniture of kitchens and bathrooms must all be calculated in the useful floor space of the dwelling.</p> <p>If the summer kitchen is taken into account as a kitchen then its floor space must be calculated in the total useful floor space of the dwelling.</p> <p>In case of loggias, roofed (closed) terraces and roofed (closed) balconies, half of the floor space must be included, while the floor space of attics (mansards) must be only included where the headroom is 1,9 m2 or higher.</p> <p>Balconies, basements, attics, and storage rooms, garages outside the dwelling are considered as parts of the dwelling thus their floor-space must not be calculated in the total useful floor-space. Inside galleries do not extend the total floor space of the dwelling either.</p> <p>Premises, e.g. summer kitchens that are built to be part of the dwelling and are used by the household living in the main building must be considered a part of the dwelling.</p> <p>The premises of shops, workshops, restaurants etc. that are built or converted for the purpose of inhabitation even if they are accessible through a door of the dwelling or on an inside staircase must not be considered a part of the dwelling.</p> <p>In case the exact size of the floor-space is not known it must be estimated. Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the useful floor-space of the housing unit (in square meters). HU2011A0031 is a 3-digit numeric variable. Codes11 = 11 or less. 301 = 301 or more. 999 = NIU. Dwelling Characteristics Variables -- HOUSEHOLD Water supply of the housing unit <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <div class="i1">10.1 Water supply</div><div class="i2">[] 1 From pipeline<br />[] 2 From private pipeline (e.g.: from well by pump)<br />[] 3 No piped water in the dwelling</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">10. Type of water supply in the dwelling </span></p> <p>10.1.<span class="em"> From pipeline or from private pipeline (e.g. from well by pump</span>) must be marked in case water supply is obtained through a tap installed inside the dwelling thus the dwelling is connected to a community water conduit or a well.</p> <p>10.2. Any form of <span class="em">hot water supply </span>can be marked only if dwelling is supplied with water thus from pipeline or from private pipeline (e.g. from well by pump) is marked at question 10.1. If the dwelling is supplied with hot water from more sources (e.g. from hot water pipeline and also from individual hot water reservoir) then the answer must reflect the hot water used for wash-up, bathing. Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the type of water supply of the housing unit. 0 No piped water in the housing unit 1 Piped water in the housing unit from a community scheme 2 Piped water in the housing unit from private pipeline (eg. from well by pump) 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Hot water supply <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <div class="i1">10.2 Hot water supply</div><div class="i2">[] From pipeline<br />[] In another way (from a central or own electric or gas boiler, kitchen water heater)<br />[] No hot running water</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">10. Type of water supply in the dwelling </span></p> <p>10.1.<span class="em"> From pipeline or from private pipeline (e.g. from well by pump</span>) must be marked in case water supply is obtained through a tap installed inside the dwelling thus the dwelling is connected to a community water conduit or a well.</p> <p>10.2. Any form of <span class="em">hot water supply </span>can be marked only if dwelling is supplied with water thus from pipeline or from private pipeline (e.g. from well by pump) is marked at question 10.1. If the dwelling is supplied with hot water from more sources (e.g. from hot water pipeline and also from individual hot water reservoir) then the answer must reflect the hot water used for wash-up, bathing. Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the type of hot water supply of the housing unit. 0 No hot water 1 From a community scheme 2 In another way (from a central, own electric, gas boiler, kitchen water heater) 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Heating <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <p>12. Heating</p> <div class="i1">[] Separately for each place with convector, stove<br />[] One or more dwellings heated by boiler (central, circle)<br />[] District (block) heating [Go to question 14]<br />[] No heating [Go to question 14]</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">12. Heating</span> <br /><span class="em">Separately for each place with convector, stove </span>is the answer when the heating of the premises of the dwelling is provided individually.</p> <p><span class="em">One or more dwellings heated by boiler (central, circle) </span>is the right answer if:</p> <div class="i1">-The premises of the dwelling or a one-dwelling building is heated by one heating place or<br />-The dwellings in a building are heated by a boiler located in the building or in close connection with the building.</div><span class="em">District (block) heating </span>must be marked if more buildings receive heating from thermal power station, heating works or natural thermal spring. In case you marked this answer continue with question 14.</p> <p>In case the dwelling is heated more ways, then the <span class="em">heating of the rooms </span>must be considered. If the exact answer cannot be defined even in this way then the most characteristic heating must be marked.</p> <p>If there is <span class="em">no heating</span> in the dwelling you must continue with question 14. Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the type of heating of the housing unit. 0 No heating 1 Separately for each place with convector, stove 2 Central heating, one or more dwellings heated by boiler (central, circle) 3 Central heating, from community heating centre 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Number of flush toilets (in bathroom or separately) <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <div class="i1">7.6 Flush toilet</div><div class="i2">[] 1 Yes _ (number)<br />[] 2 No</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">7. Is there a room, a kitchen etc. in the dwelling?</span> <br />Rooms and kitchens must be enumerated with their size also taken into account. Premises of common airspace with more functions (e.g. living room and cooking room together) must be divided by function. Attics (mansards) must be enumerated only if the headroom is 1.9 m2 or higher. Gallery is not considered an individual room.</p> <p>In questions 7.1.- 7.7 do not forget to mark "no" in case the given premise is not available in the dwelling.</p> <div class="i1">7.1., 7.2. <span class="em">Rooms</span> are premises provided with direct natural light used as living rooms, bedrooms, dining rooms etc. They must be taken into account by their size.<br /><br />7.3., 7.4.<span class="em"> Kitchens </span>are premises established and used for cooking (or eating). Kitchenettes and kitchen cabinets are included. In case the dwelling does not have a kitchen but has a summer kitchen that is used for cooking by the household living in the main building then it must be counted according to the size.<br /><br />Premises of common airspace with more functions had been enumerated based on the purpose of use, and classified in the appropriate category of premises.<br /><br />7.5. <span class="em">Bathroom</span> (shower-stall, wash-basin alcove) is a premise used for washing in the dwelling. Bathrooms generally are equipped with water supply system, sewage disposal system and bathing (washing) facilities.<br /><br />7.6. The total number of flush toilets must be marked irrespective of whether they are in a separate room or e.g. in the bathroom. Flush toilets belonging to the dwelling and used exclusively by the occupants must not be counted if they are not in the dwelling.<br /><br />7.7. <span class="em">Other room </span>e.g. lobby, corridor, pantry. In case you answered other to question 2 and the housing unit contains more premises, then each premise must be counted according to its function. However if it consists of one function, only then the premise must be counted as a room of the given size.</div> Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the number of flush toilets (in bathroom or separately). 0 None 1 1 flush toilet 2 2 flush toilets 3 3 flush toilets 4 4 or more flush toilets 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Sewage disposal <span class="h1">Dwelling questionnaire</span></p> <p><span class="h1">I. Dwelling data</span></p> <p>[Questions 2 through 23 were asked of all occupied private households, seasonal and non-residential housing unit]</p> <p>11. Sewage disposal from dwelling</p> <div class="i1">[] Into a public sewer<br />[] Into private sewer (closed reservoir, cesspit)<br />[] Into another place or there is no sewage disposal</div> <span class="h2">I. Dwelling data</span></p> <p><span class="em">11. Sewage disposal from dwelling</span> <br /><span class="em">Into public sewer </span>is the right answer when the dwelling is connected to the sewage system of public utility.</p> <p><span class="em">Into private sewer (closed reservoir, cesspit)</span> must be marked if wastewater is led through an underground drainpipe to a closed sewage storage tank or to a desiccator (drain tank) on the ground plot of the building. Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the type of sewage system. 0 Into another place or no sewage disposal 1 Into public sewer 2 Into private sewer (closed reservoir, cesspit) 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Level of comfort Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the level of comfort of the dwelling. 1 With all amenities 2 With principal amenities 3 With part of amenities 4 Without comfort 5 Emergency or other dwelling 8 Other occupied housing unit 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Tenure status of the housing unit Hungary 2011: Occupied private dwellings, seasonal, and non-residential housing units [discrepancies: none] This variable indicates the tenure status of the dwelling. 1 Occupied by owner or relative, beneficial owner 2 Occupied by tenant of the whole dwelling or relative of tenant 3 Occupied by tenant of a part of the dwelling, other 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. Technical Person Variables -- PERSON Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Person Variables -- PERSON Mother's location in household MOMLOC is a constructed variable that indicates whether or not the person's mother lived in the same household and, if so, gives the person number of the mother (see PERNUM). MOMLOC makes it easy for researchers to link the characteristics of children and their (probable) mothers. The method by which probable child-mother links are identified is described in PARRULE. The general design of MOMLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of MOMLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: MOMLOC identifies social relationships (such as stepmother and adopted mother) as well as biological relationships. The variable STEPMOM is designed to identify some of these social relationships. To restrict MOMLOC to biological mothers, such as for own children fertility estimation, MOMLOC should be reset to zero when STEPMOM is greater than zero. MOMLOC is a 3-digit numeric variable. Codes0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother Constructed Family Interrelationship Variables -- PERSON Father's location in household POPLOC is a constructed variable that indicates whether or not the person's father lived in the same household and, if so, gives the person number of the father (see PERNUM). POPLOC makes it easy for researchers to link the characteristics of children and their (probable) fathers. The method by which probable child-father links are identified is described in PARRULE. The general design of POPLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of POPLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: POPLOC identifies social relationships (such as stepfather and adopted father) as well as biological relationships. The variable STEPPOP is designed to identify some of these social relationships. To restrict POPLOC to biological mothers, such as for own children fertility estimation, POPLOC should be reset to zero when STEPPOP is greater than zero. POPLOC is a 3-digit numeric variable. Codes0 = No father of this person present in the household. 1 or higher = The person number of this person's father Constructed Family Interrelationship Variables -- PERSON Spouse's location in household SPLOC is a constructed variable that indicates whether or not the person's spouse lived in the same household and, if so, gives the person number (PERNUM) of the spouse. SPLOC makes it easy for researchers to link the characteristics of (probable) spouses. The method by which probable spouse-spouse links are identified is described in SPRULE. The general design of SPLOC and other constructed variables is modeled on the methods developed for IPUMS-USA "Family Interrelationships", but the details vary significantly. For more details on the construction of SPLOC, see the Comparability section of SPRULE and this paper on IPUMSI family linking methodology. SPLOC is a 3-digit numeric variable. Codes0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse Constructed Family Interrelationship Variables -- PERSON Rule for linking parent PARRULE describes the criteria by which the IPUMS International variables MOMLOC and POPLOC linked the person to a probable mother and/or father. IPUMS International establishes child-parent links according to five basic rules, and PARRULE gives the number of the rule that applied to the link in question. A link to any parent automatically generates a second link to that parent's spouse or partner, so only one rule is needed to describe both MOMLOC and POPLOC. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. 00 No parent of person in household 11 Link to head or spouse, unambiguous 12 Link to head or spouse, ambiguous 21 Child-Grandchild, within empirical child cap 22 Child-Grandchild, within constructed child cap 23 Child-Grandchild, exceeds child cap 31 Specified Other Relatives, within empirical child cap 32 Specified Other Relatives, within constructed child cap 33 Specified Other Relatives, exceeds child cap 41 Other Relatives, within empirical child cap 42 Other Relatives, within constructed child cap 51 Non-Relatives, within empirical child cap 52 Non-Relatives, within constructed child cap Constructed Family Interrelationship Variables -- PERSON Rule for linking spouse SPRULE explains the criteria by which the IPUMS-International variable SPLOC linked the person to his/her probable spouse. IPUMS International establishes spouse-spouse links according to five basic rules, and SPRULE gives the number of the rule that applied to the link in question. A sixth rule identifies sample-specific linking procedures only imposed in selected instances. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. 00 No spouse present 01 Rule 1: strong relationship pairing, couple adjacent 02 Rule 2: strong relationship pairing, couple not adjacent 03 Rule 3: weak relationship pairing, couple adjacent 04 Rule 4: weak relationship pairing, couple not adjacent 05 Rule 5: weak consensual union pairings 06 Rule 6: sample-specific rules (usually child-to-child) Constructed Family Interrelationship Variables -- PERSON Probable stepmother STEPMOM indicates whether a person's mother, as identified by MOMLOC, was most probably not the person's biological mother. Non-zero values of STEPMOM explain why it is probable that the person's mother was a step- or adopted mother. A value of 0 indicates no likely stepmother because (1) the mother identified in MOMLOC was probably the biological mother or (2) there is no mother of this person present in the household. The codes for STEPMOM are as follows: 0 = Biological mother or no mother of this person present in household. 1 = Mother has no children born or surviving. 2 = Child reports mother is deceased. 3 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner, stepchild/child-in-law). 4 = Mother reports no children in the home. 5 = Age difference between mother and child was less than 12 or greater than 54 years. 6 = Child exceeds known fertility of mother. In cases where more than one criterion for a likely stepmother is met, STEPMOM will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. In cases where a mother is linked to more children than she reports in CHBORN or CHSURV, the determination of which children to flag as probable stepchildren is based first on the strength of the child-mother pairing (see PARRULE), and then on the order of children in the household roster. Since most links to a given mother will be made at the same strength level, order will often be the decisive factor in flagging probable stepmother relationships. Users should note that there are many stepmothers and adopted mothers in the population that cannot be identified with information available in the censuses. Therefore, STEPMOM will always under-represent their actual number in the population. 0 Biological mother or no mother present 1 Mother has no children born or surviving 2 Child reports mother is deceased 3 Explicitly identified step relationship 4 Mother reports no children in the home 5 Age difference implausible 6 Child exceeds known fertility of mother Constructed Family Interrelationship Variables -- PERSON Probable stepfather STEPPOP indicates whether a person's father, as identified by POPLOC, was most probably not the person's biological father. Non-zero values of STEPPOP explain why it is probable that the person's father was a step- or adopted father. A value of 0 indicates no likely stepfather because (1) the father identified in POPLOC was probably the biological father or (2) there is no father of this person present in the household. The codes for STEPPOP are as follows: 0 = Biological father or no father of this person present in household. 1 = Child reports father is deceased. 2 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner; stepchild/child-in-law). 3 = Age difference between father and child was less than 12 or greater than 54 years. In cases where more than one criterion for a likely stepfather is met, STEPPOP will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepfathers and adopted fathers in the population that cannot be identified with information available in the censuses. Therefore, STEPPOP will always under-represent their actual number in the population. 0 Biological father or no father present 1 Child reports father is deceased 2 Explicitly identified step relationship 3 Age difference implausible 4 Spouse of mother 5 Identified as adopted 6 Surname difference -- male child or never-married female Constructed Family Interrelationship Variables -- PERSON Man with more than one wife linked POLYMAL indicates if a man had more than one wife linked to him in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The point of POLYMAL is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. 0 No more than one wife linked via SPLOC 1 More than one wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON Woman is second or higher order wife POLY2ND indicates if a woman was the second or higher order wife linked to a husband in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The variable does not suggest the actual marital order of wives, only their relative positions in the person order of the household as it was enumerated. The point of POLY2ND is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. 0 Person is not the 2nd or higher order wife linked via SPLOC 1 Person is the 2nd or higher order wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON Family unit membership FAMUNIT is a constructed variable indicating to which family within the household a person belongs. All persons related to the household head receive a 1 (see RELATE). Each secondary family or secondary individual receives a higher code. For purposes of FAMUNIT, secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). FAMUNIT is a 4-digit numeric variable. CodesIf there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on. Constructed Family Interrelationship Variables -- PERSON Number of own family members in household FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them. FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membership). The primary family is defined as all persons related to the head in the RELATE variable. Secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). 0001 1 family member present 0002 2 family members present 0003 3 family members present 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 or more persons Constructed Family Interrelationship Variables -- PERSON Number of own children in household NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children in household Constructed Family Interrelationship Variables -- PERSON Number of own children under age 5 in household NCHLT5 provides a count of the person's own children under age five living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more own children under age 5 in household 98 One or more children have unknown age Constructed Family Interrelationship Variables -- PERSON Age of eldest own child in household ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. ELDCH is top-coded at age 50 or older. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Age of youngest own child in household YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. YNGCH is top-coded at age 50 or older. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Relationship to household head [general version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown Demographic Variables -- PERSON Relationship to household head [detailed version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling's sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder, or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown Demographic Variables -- PERSON Relationship to head, Europe ERELATE describes for the European samples the relationship of the individual to the head of household -- sometimes called the householder or reference person. ERELATE has been classified according to the recommendations of the Conference of European Statisticians for the 2010 Population and Housing Censuses. 10 Reference person / Head 20 Spouse or partner 21 Husband or wife 22 Partner in consensual union 30 Child/child-in-law of head or of spouse/partner 31 Spouse or partner of child of head 40 Parent of head, of spouse, or of partner 50 Other relative of head, spouse, or partner 60 Non-relative of head 61 Foster child 62 Boarder 63 Domestic servant 64 Other 99 Not stated / unknown Demographic Variables -- PERSON Age AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. 000 Less than 1 year 001 1 year 002 2 years 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100+ 999 Not reported/missing Demographic Variables -- PERSON Age, grouped into intervals AGE2 gives computed years of age grouped into intervals. 01 0 to 4 02 5 to 9 03 10 to 14 04 15 to 19 05 0 to 5 06 6 to 10 07 10 to 15 08 11 to 14 09 15 to 17 10 16 to 19 11 18 to 24 12 20 to 24 13 25 to 29 14 30 to 34 15 35 to 39 16 40 to 44 17 45 to 49 18 50 to 54 19 55 to 59 20 60 to 64 21 65 to 69 22 70 to 74 23 75 to 79 24 80 to 84 25 85+ 98 Unknown Demographic Variables -- PERSON Sex SEX reports the sex (gender) of the respondent. 1 Male 2 Female 9 Unknown Demographic Variables -- PERSON Marital status [general version] MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. 0 NIU (not in universe) 1 Single/never married 2 Married/in union 3 Separated/divorced/spouse absent 4 Widowed 9 Unknown/missing Demographic Variables -- PERSON Marital status [detailed version] MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. 000 NIU (not in universe) 100 Single/never married 110 Engaged 111 Never married and never cohabited 200 Married or consensual union 210 Married, formally 211 Married, civil 212 Married, religious 213 Married, civil and religious 214 Married, civil or religious 215 Married, traditional/customary 216 Married, monogamous 217 Married, polygamous 219 Married, spouse absent (historical samples) 220 Consensual union 300 Separated/divorced/spouse absent 310 Separated or divorced 320 Separated or annulled 330 Separated 331 Separated legally 332 Separated de facto 333 Separated from marriage 334 Separated from consensual union 335 Separated from consensual union or marriage 340 Annulled 350 Divorced 400 Widowed 410 Widowed or divorced 411 Widowed from consensual union or marriage 412 Widowed from marriage 413 Widowed from consensual union 420 Widowed, divorced, or separated 999 Unknown/missing Demographic Variables -- PERSON Marital status, Europe EMARST describes for the European samples the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. European census instructions generally limit marital status to legal unions, but there are exceptions. EMARST has been classified according to the recommendations given by the Conference of European Statisticians for the 2010 Population and Housing Censuses. 0 NIU (not in universe) 1 Never married 2 Married 3 Widowed and not remarried 4 Divorced/separated and not remarried 5 Widowed or divorced 9 Unknown / missing Demographic Variables -- PERSON Consensual union CONSENS indicates whether the respondent was in a consensual union -- a de facto marriage. 1 Yes, in consensual union 2 No, married 8 Unknown 9 NIU (not in universe) Demographic Variables -- PERSON Duration of current marriage or union DURMARR reports the duration of the respondent's current marriage or union, or, in some cases, the total years spent within marriage. 00 Less than 1 year 01 1 year 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95+ 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Relationship to head of subfamily SUBFREL describes the relationship of the individual to the head of the subfamily (in most cases, conjugal unit). It is distinct from RELATE, which identifies a person's relationship to the head of the household. There can be multiple subfamilies within households. The particular subfamily to which a person belongs is recorded in SUBFNUM. Persons living alone without other family are identified as "heads" of family. 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 3000 Child 3100 Biological child 3200 Adopted or step child 4000 Other relative 4100 Grandchild 4200 Parent/parent-in-law 4210 Parent 4220 Parent-in-law 4300 Child-in-law 4400 Sibling/sibling-in-law 4410 Sibling 4430 Sibling-in-law 4500 Grandparent 4600 Parent/grandparent 4810 Nephew/niece 4900 Other relative, n.e.c. 5000 Non-relative 5120 Visitor 5210 Domestic employee 5220 Relative of employee, n.s. 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5400 Employee, boarder or guest 5510 Agregado 5600 Group quarters 6000 Other relative or non-relative 9998 Unknown 9999 NIU (not in universe) Demographic Variables -- PERSON Subfamily membership number 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. 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 Demographic Variables -- PERSON Children ever born CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Citizenship CITIZEN indicates the person's citizenship status within the country in which they were enumerated. 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) Nativity and Birthplace Variables -- PERSON Region of birth, Hungary BPLHU indicates the person's place of birth at the region level for Hungary. 1 Central Hungary 2 Transdanubia 3 Great Plains and Northern Hungary 8 Foreign country 9 Unknown Nativity and Birthplace Variables -- PERSON Region of birth, Europe, NUTS1 EBPLNT1 indicates the NUTS1 region in which the person was born. The Nomenclature of Territorial Units for Statistics (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. NUTS1 identifies the largest territorial units within countries. EBPLNT1 only identifies regions within the person's country of residence; it does not identify birthplaces of international migrants. The code labels include the standard code for the NUTS1 system and the name of the NUTS1 region, separated by a slash. 0000 NIU (not in universe) 0901 ES1 / Noroeste 0902 ES2 / Noreste 0903 ES3 / Comunidad de Madrid 0904 ES4 / Centro (E) 0905 ES5 / Este 0906 ES6 / Sur 0907 ES7 / Canarias 0908 ES6 / Sur + Other Spanish territories 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 1201 EL1 / Voreia Ellada 1202 EL2 / Kentriki Ellada 1203 EL3 / Attiki 1204 EL4 / Nisia Aigaiou, Kriti 1301 HU1 / Közép-Magyarország 1302 HU2 / Dunántúl 1303 HU3 / Alföld és Észak 1400 IE0 / Republic of Ireland 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 / Slovenija 3401 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 9998 Response suppressed 9999 Unknown Nativity and Birthplace Variables -- PERSON School attendance SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census. 0 NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing Education Variables -- PERSON Educational attainment, international recode [general version] 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. 0 NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown Education Variables -- PERSON Educational attainment, international recode [detailed version] 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. 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 Education Variables -- PERSON Educational attainment, Hungary EDUCHU indicates the person's educational attainment in Hungary in terms of the level of schooling completed. 000 NIU (not in universe) 110 No schooling 211 Some primary (less than 4 yrs) 212 Primary (4 yrs completed) 213 Primary (6 yrs completed) 214 Primary completed (8 yrs) 310 Secondary general 311 Some secondary 312 Secondary completed 320 Apprentice school or vocational high school certificate 321 Apprentice or vocational, with some primary 322 Apprentice or vocational, primary completed 323 Apprentice or vocational, with some secondary 400 Post-secondary education (non-tertiary) 500 Higher education 510 Some university 520 Non-university completed 530 University completed 540 Doctorate or equivalent 999 Unknown Education Variables -- PERSON Educational attainment, Europe 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. 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 Education Variables -- PERSON Activity status (employment status) [general version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 0 NIU (not in universe) 1 Employed 2 Unemployed 3 Inactive 9 Unknown/missing Work Variables -- PERSON Activity status (employment status) [detailed version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 000 NIU (not in universe) 100 Employed, not specified 110 At work 111 At work, and 'student' 112 At work, and 'housework' 113 At work, and 'seeking work' 114 At work, and 'retired' 115 At work, and 'no work' 116 At work, and other situation 117 At work, family holding, not specified 118 At work, family holding, not agricultural 119 At work, family holding, agricultural 120 Have job, not at work in reference period 130 Armed forces 131 Armed forces, at work 132 Armed forces, not at work in reference period 133 Military trainee 140 Marginally employed 200 Unemployed, not specified 201 Unemployed 6 or more months 202 Worked fewer than 6 months, permanent job 203 Worked fewer than 6 months, temporary job 210 Unemployed, experienced worker 220 Unemployed, new worker 230 No work available 240 Inactive unemployed 300 Inactive (not in labor force) 301 Unavailable jobseekers 302 Available potential jobseekers 310 Housework 320 Health reasons, unable to work, or disabled 321 Permanent disability 322 Temporary illness 323 Disabled or imprisoned 330 In school 340 Retirees and living on rent 341 Living on rents 342 Living on rents or pension 343 Retirees/pensioners 344 Retired 345 Pensioner 346 Non-retirement pension 347 Disability pension 348 Retired without benefits 350 Elderly 351 Elderly or disabled 360 Institutionalized 361 Prisoner 370 Intermittent worker 371 Not working, seasonal worker 372 Not working, occasional worker 380 Other income recipient 390 Inactive, other reasons 391 Too young to work 392 Dependent 999 Unknown/missing Work Variables -- PERSON Activity status (employment status), Europe EEMPSTAT indicates for the European samples whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EEMPSTAT can also convey further information. EEMPSTAT has been classified according to the recommendations given by the Conference of European Statisticians for the 2010 Population and Housing Censuses. "Employment Status" is referred to as "Activity Status" in the CES recommendations, but the former term is used to maintain consistency with IPUMS practices. The economically active population constitutes the total labor force: employed and unemployed persons. 000 NIU (not in universe) 110 Employed 120 Unemployed 121 Unemployed, never worked before 200 Not economically active, unspecified 210 Students 220 Pension or capital income recipients 230 Homemakers 240 Others 999 Unknown / missing Work Variables -- PERSON Labor force participation LABFORCE is a dichotomous variable identifying whether a person participated in the labor force. Labor force participation generally means working or seeking work within a specified reference period. For most samples LABFORCE is a recode of EMPSTAT (employment status). A consistent lower age universe of 15 or older has been applied to increase comparability across samples. Full detail is retained in EMPSTAT, which should be used for any study of child labor. 1 No, not in the labor force 2 Yes, in the labor force 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Occupation, ISCO general OCCISCO records the person's primary occupation, coded according to the major categories in the International Standard Classification of Occupations (ISCO) scheme for 1988. For someone with more than one job, the primary occupation is typically the one in which the person had spent the most time or earned the most money. 01 Legislators, senior officials and managers 02 Professionals 03 Technicians and associate professionals 04 Clerks 05 Service workers and shop and market sales 06 Skilled agricultural and fishery workers 07 Crafts and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 10 Armed forces 11 Other occupations, unspecified or n.e.c. 97 Response suppressed 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Occupation, unrecoded OCC records the person's primary occupation, classified according to the system used by the respective national census office at the time. For someone with more than one job, the primary occupation is usually the one in which the person spent the most time or earned the most money, although this may not have been explicit in the instructions for a specific census. To ensure confidentiality, very small occupations are recoded to a residual category indicating the persons had an occupation, but the job title is not identified. The number of cases recoded should be too small to affect analyses. OCC is a 4-digit numeric variable. Some samples use fewer than 4 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_OCC3 - Occupation [3 digit] Argentina 1980 - see Variable: AR1980A_OCC - Occupation Argentina 1991 - see Variable: AR1991A_OCC - Occupation Argentina 2001 - see Variable: AR2001A_OCC4 - Occupation (4-digits) Armenia 2011 - see Variable: AM2011A_OCC - Occupation Austria 1971 - see Variable: AT1971A_OCCSM - Occupation of supporter: sub-major groups Austria 1981 - see Variable: AT1981A_OCCSM - Occupation of supporter: sub-major groups Austria 1991 - see Variable: AT1991A_OCCSM - Occupation of supporter: sub-major groups Austria 2001 - see Variable: AT2001A_OCCSM - Occupation of supporter: sub-major groups Belarus 1999 - see Variable: BY1999A_OCC2 - Occupation, 2 digits Belarus 2009 - see Variable: BY2009A_OCC - Occupation Benin 1979 - see Variable: BJ1979A_OCC - Occupation (2-digits) Benin 1992 - see Variable: BJ1992A_OCC3 - Occupation (3-digits) Benin 2002 - see Variable: BJ2002A_OCC - Occupation (3-digits) Benin 2013 - see Variable: BJ2013A_OCC - Occupation (3-digit) Bolivia 1976 - see Variable: BO1976A_OCC2 - Occupation, 2 digits Bolivia 1992 - see Variable: BO1992A_OCC - Occupation Bolivia 2001 - see Variable: BO2001A_OCC - Occupation, 3 digits Bolivia 2012 - see Variable: BO2012A_OCC2 - Occupation (3 digit) Botswana 1981 - see Variable: BW1981A_OCC - Occupation Botswana 1991 - see Variable: BW1991A_OCC - Occupation (last 30 days) Botswana 2001 - see Variable: BW2001A_OCC - Occupation in the past 7 days, 3 digit Botswana 2011 - see Variable: BW2011A_OCC - Occupation, 3-digits Brazil 1960 - see Variable: BR1960A_USUALOCC - Usual occupation Brazil 1970 - see Variable: BR1970A_MAINOCC - Principal occupation Brazil 1980 - see Variable: BR1980A_OCC - Occupation Brazil 1991 - see Variable: BR1991A_OCC - Occupation Brazil 2000 - see Variable: BR2000A_OCC - Occupation, 4 digits Brazil 2010 - see Variable: BR2010A_OCC - Occupation held from July 25 to July 31, 2010 Burkina Faso 1985 - see Variable: BF1985A_OCC - Principal occupation Burkina Faso 1996 - see Variable: BF1996A_OCC - Principal occupation Cambodia 1998 - see Variable: KH1998A_OCC - Occupation Cambodia 2004 - see Variable: KH2004A_OCC3 - Occupation (3-digits) Cambodia 2008 - see Variable: KH2008A_OCC - Occupation Cambodia 2013 - see Variable: KH2013A_OCC - Occupation (3-digits) Cambodia 2019 - see Variable: KH2019A_OCC1 - Occupation, 1-digit Cameroon 1976 - see Variable: CM1976A_OCC2 - Occupation (2 digits) Cameroon 2005 - see Variable: CM2005A_OCC - Occupation Canada 1971 - see Variable: CA1971A_OCC - Occupation Canada 1981 - see Variable: CA1981A_OCC - Occupation (1981 classification basis) Canada 1991 - see Variable: CA1991A_OCC80 - Occupation (1980 classification basis) Canada 2001 - see Variable: CA2001A_NOCS01P - Occupation (2001 national occupational classification for statistics) Canada 2011 - see Variable: CA2011A_OCC - Occupation Chile 1960 - see Variable: CL1960A_OCC - Occupation Chile 1970 - see Variable: CL1970A_OCC3 - Occupation (3-digit) Chile 1982 - see Variable: CL1982A_OCC3 - Occupation (3-digit) Chile 1992 - see Variable: CL1992A_OCC3 - Occupation (3-digit) Chile 2002 - see Variable: CL2002A_OCC - Occupation China 1982 - see Variable: CN1982A_OCC - Occupation China 1990 - see Variable: CN1990A_OCC - Occupation China 2000 - see Variable: CN2000A_OCC - Occupation (2-digit) Colombia 1964 - see Variable: CO1964A_OCC2 - Occupation (COTA, 4 digits) Colombia 1973 - see Variable: CO1973A_OCC - Occupation last week Costa Rica 1973 - see Variable: CR1973A_OCC3 - Occupation, 3 digits Costa Rica 1984 - see Variable: CR1984A_OCC - Occupation, 3 digits Costa Rica 2000 - see Variable: CR2000A_OCC3 - Occupation, 3 digits Costa Rica 2011 - see Variable: CR2011A_OCC - Occupation, 2-digit Cuba 2002 - see Variable: CU2002A_OCC - Occupation Cuba 2012 - see Variable: CU2012A_OCC3 - Main occupation (3-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_OCC2 - Current occupation (2-digit) Dominican Republic 1960 - see Variable: DO1960A_OCC - Occupation Dominican Republic 1970 - see Variable: DO1970A_OCC1 - Current occupation, 3 digits Dominican Republic 1981 - see Variable: DO1981A_OCC - Occupation Dominican Republic 2002 - see Variable: DO2002A_OCC - Occupation Dominican Republic 2010 - see Variable: DO2010A_OCC - Occupation Ecuador 1962 - see Variable: EC1962A_OCC - Occupation Ecuador 1974 - see Variable: EC1974A_OCC3 - Occupation, three digits Ecuador 1982 - see Variable: EC1982A_OCC3 - Occupation, 3 digits Ecuador 1990 - see Variable: EC1990A_OCC3 - Occupation, 3 digits Ecuador 2001 - see Variable: EC2001A_OCC - Occupation, 3 digits Ecuador 2010 - see Variable: EC2010A_OCC3 - Occupation (3 digits, ISCO 08) Egypt 1986 - see Variable: EG1986A_OCC3 - Occupation (3-digit) Egypt 2006 - see Variable: EG2006A_OCC - Primary occupation, 3-digit El Salvador 1992 - see Variable: SV1992A_OCC - Occupation (3-digit) El Salvador 2007 - see Variable: SV2007A_OCC3DIG - Occupation (3-digit) Ethiopia 1984 - see Variable: ET1984A_OCC2 - Occupation (2-digit) Ethiopia 1994 - see Variable: ET1994A_OCC - Occupation Fiji 1976 - see Variable: FJ1976A_OCC - Occupation Fiji 1986 - see Variable: FJ1986A_OCC - Occupation Fiji 1996 - see Variable: FJ1996A_OCC3 - Occupation (3 digits) Fiji 2007 - see Variable: FJ2007A_OCC3 - Occupation, 3 digits Fiji 2014 - see Variable: FJ2014A_OCC3 - Occupation (3 digits) Finland 2010 - see Variable: FI2010A_OCC - Occupation France 1962 - see Variable: FR1962A_SOCCUP - SAPHIR occupation France 1968 - see Variable: FR1968A_SOCC - SAPHIR occupation France 1975 - see Variable: FR1975A_SOCC - SAPHIR occupation France 1982 - see Variable: FR1982A_SOCC - SAPHIR occupation France 1990 - see Variable: FR1990A_SOCC - Saphir occupation France 1999 - see Variable: FR1999A_OCC - Occupation, ISCO France 2006 - see Variable: FR2006A_PROF486 - Detailed profession (4-digit) France 2011 - see Variable: FR2011A_PROF - Profession, 486 categories Germany 1970 - see Variable: DE1970A_OCC - Occupation Germany 1981 - see Variable: DE1981A_OCC - Occupation Germany 1987 - see Variable: DE1987A_OCC - Occupation Ghana 1984 - see Variable: GH1984A_OCC2 - Occupation, 2 digits Ghana 2000 - see Variable: GH2000A_OCC - Occupation Ghana 2010 - see Variable: GH2010A_OCC - Occupation (major groups) Greece 1971 - see Variable: GR1971A_OCC - Occupation Greece 1981 - see Variable: GR1981A_OCC - Occupation Greece 1991 - see Variable: GR1991A_OCC - Occupation Greece 2001 - see Variable: GR2001A_OCC - Occupation Greece 2011 - see Variable: GR2011A_OCC - Occupation Guatemala 1964 - see Variable: GT1964A_OCC3 - Occupation (3-digits) Guatemala 1973 - see Variable: GT1973A_OCC3 - Principal occupation (3-digits) Guatemala 1981 - see Variable: GT1981A_OCC3 - Principal occupation (3-digits) Guatemala 1994 - see Variable: GT1994A_OCC - Principal occupation (1-digit) Guatemala 2002 - see Variable: GT2002A_OCC3 - Principal occupation (3-digits) Guinea 1983 - see Variable: GN1983A_OCC2 - Occupation, 2 digits Guinea 1996 - see Variable: GN1996A_OCC - Occupation Guinea 2014 - see Variable: GN2014A_OCC - Occupation (3-digit) Haiti 1982 - see Variable: HT1982A_OCC - Main occupation or profession Haiti 2003 - see Variable: HT2003A_OCC2 - Occupation, 3 digits Honduras 1961 - see Variable: HN1961A_OCC - Occupation (2-digits) Honduras 1974 - see Variable: HN1974A_OCC2 - Occupation (3-digits) Honduras 1988 - see Variable: HN1988A_OCC4 - Occupation (4-digits) Honduras 2001 - see Variable: HN2001A_OCC - Occupation (4-digit) Honduras 2013 - see Variable: HN2013A_OCC3 - Occupation (3-digit) Hungary 1970 - see Variable: HU1970A_OCC - Occupation Hungary 1980 - see Variable: HU1980A_OCC - Occupation, scope of activity Hungary 1990 - see Variable: HU1990A_OCC - Occupation Hungary 2001 - see Variable: HU2001A_OCC - Occupation Hungary 2011 - see Variable: HU2011A_OCC - Occupation Indonesia 1971 - see Variable: ID1971A_OCC - Occupation Indonesia 1976 - see Variable: ID1976A_OCC - Primary occupation during past week Indonesia 1980 - see Variable: ID1980A_OCC - Primary occupation during the previous week (3 digit version) Indonesia 1985 - see Variable: ID1985A_OCC - Primary occupation Indonesia 1990 - see Variable: ID1990A_OCC - Main occupation last week Indonesia 1995 - see Variable: ID1995A_OCC - Occupation Indonesia 2005 - see Variable: ID2005A_OCC - Occupation Iran 2006 - see Variable: IR2006A_OCC4 - Occupation Iran 2011 - see Variable: IR2011A_OCC - Occupation (3-digit) Iraq 1997 - see Variable: IQ1997A_OCC - Occupation Ireland 1971 - see Variable: IE1971A_OCC - Occupation Ireland 1981 - see Variable: IE1981A_OCC - Occupation Ireland 1986 - see Variable: IE1986A_OCC - Occupation group Ireland 1991 - see Variable: IE1991A_OCC - Occupation group Ireland 1996 - see Variable: IE1996A_OCC - Occupation Ireland 2002 - see Variable: IE2002A_OCC - Occupation Ireland 2006 - see Variable: IE2006A_OCC - Occupation group Ireland 2011 - see Variable: IE2011A_OCC - Occupation (shuffled) Ireland 2016 - see Variable: IE2016A_OCC - Occupation (groups) Israel 1972 - see Variable: IL1972A_OCC - Occupation Israel 1983 - see Variable: IL1983A_OCC - Occupation Israel 1995 - see Variable: IL1995A_OCC - Occupation Israel 2008 - see Variable: IL2008A_OCC - Occupation Italy 2001 - see Variable: IT2001A_OCC - Occupation Italy 2011 - see Variable: IT2011A_WKTYPE - Type of work Jamaica 1982 - see Variable: JM1982A_OCC - Occupation during past week / in last job Jamaica 1991 - see Variable: JM1991A_OCC - Occupation during past week/in last job Jamaica 2001 - see Variable: JM2001A_OCC3 - Occupation 3-digit Jordan 2004 - see Variable: JO2004A_OCC3 - Major current occupation (3-digit) Kenya 1989 - see Variable: KE1989A_OCC4 - Occupation, 4 digits Kenya 2019 - see Variable: KE2019A_OCC3 - Occupation (3-digit) Kyrgyzstan 1999 - see Variable: KG1999A_OCC - Main activity Laos 1995 - see Variable: LA1995A_OCC1 - Main occupation in the last 12 months (1-digit) Lesotho 1996 - see Variable: LS1996A_OCC - Occupation (2-digits) Lesotho 2006 - see Variable: LS2006A_OCC - Occupation (2-digits) Liberia 1974 - see Variable: LR1974A_OCC2 - Occupation (2-digit) Liberia 2008 - see Variable: LR2008A_OCC - Occupation Malawi 1987 - see Variable: MW1987A_OCC2 - Occupation, 2 digit Malawi 1998 - see Variable: MW1998A_OCC2 - Occupation, 2-digit Malawi 2008 - see Variable: MW2008A_OCC2 - Occupation (2 digits) Malawi 2018 - see Variable: MW2018A_OCC1 - Main occupation (1-digit) Malaysia 1970 - see Variable: MY1970A_OCC - Occupation last week Malaysia 1980 - see Variable: MY1980A_OCC3 - Principal occupation last week (3 digits) Malaysia 1991 - see Variable: MY1991A_OCC3 - Principal occupation (3 digits) Malaysia 2000 - see Variable: MY2000A_OCC3 - Occupation -- 3 digits Mali 1987 - see Variable: ML1987A_OCC - Occupation last month Mali 1998 - see Variable: ML1998A_OCC - Main occupation Mali 2009 - see Variable: ML2009A_OCC - Principal occupation Mauritius 1990 - see Variable: MU1990A_OCC3 - Occupation (3-digit) Mauritius 2000 - see Variable: MU2000A_OCC4 - Occupation (4 digit) Mauritius 2011 - see Variable: MU2011A_OCC4 - Occupation (4-digit) Mexico 1960 - see Variable: MX1960A_OCC2 - Principal occupation, 2 digits Mexico 1970 - see Variable: MX1970A_OCC3 - Occupation 3 digit Mexico 1990 - see Variable: MX1990A_OCC - Occupation, 4 digits Mexico 1995 - see Variable: MX1995A_OCC - Occupation Mexico 2000 - see Variable: MX2000A_OCC4 - Occupation, 4 digits Mexico 2010 - see Variable: MX2010A_OCC - Occupation or trade Mexico 2015 - see Variable: MX2015A_OCC - Occupation Mexico 2020 - see Variable: MX2020A_OCC3 - Occupation (3-digits) Mongolia 2000 - see Variable: MN2000A_OCC - Occupation Mongolia 2010 - see Variable: MN2010A_OCC3 - Occupation 3 digits (ISCO-2008) Mongolia 2020 - see Variable: MN2020A_OCC3 - Occupation (3-digit) Morocco 1982 - see Variable: MA1982A_OCC3 - Occupation (3-digit) Morocco 1994 - see Variable: MA1994A_OCC3 - Occupation, 3-digit Morocco 2004 - see Variable: MA2004A_OCC3 - Occupation (3-digit) Morocco 2014 - see Variable: MA2014A_OCC2 - Occupation (2-digit) Mozambique 1997 - see Variable: MZ1997A_OCC2 - Occupation 3-digit Mozambique 2007 - see Variable: MZ2007A_OCC - Occupation Mozambique 2017 - see Variable: MZ2017A_OCC3 - Main occupation (3-digits ISCO 2008) Myanmar 2014 - see Variable: MM2014A_OCC - Occupation Nepal 2001 - see Variable: NP2001A_OCC - Usual occupation Nepal 2011 - see Variable: NP2011A_OCC1 - Occupation (1-digit) Netherlands 1960 - see Variable: NL1960A_OCC - Occupation Netherlands 1971 - see Variable: NL1971A_OCC - Occupation Netherlands 2001 - see Variable: NL2001A_OCC - Occupation Netherlands 2011 - see Variable: NL2011A_OCC - Occupation (1-digit) Nicaragua 1971 - see Variable: NI1971A_OCC - Occupation Nicaragua 1995 - see Variable: NI1995A_OCC - Occupation (ISCO 88, 3 digits) Nicaragua 2005 - see Variable: NI2005A_OCC3 - Occupation (ISCO 88, 3 digits) Pakistan 1973 - see Variable: PK1973A_OCC3 - Occupation Palestine 1997 - see Variable: PS1997A_OCC - Main occupation Palestine 2007 - see Variable: PS2007A_OCC - Main occupation Palestine 2017 - see Variable: PS2017A_OCC - Occupation Panama 1960 - see Variable: PA1960A_OCC4 - Occupation (4-digit) Panama 1970 - see Variable: PA1970A_OCC2 - Occupation, 2-digit Panama 1980 - see Variable: PA1980A_OCC2 - Occupation (3-digit) Panama 1990 - see Variable: PA1990A_OCC - Occupation Panama 2000 - see Variable: PA2000A_OCC - Occupation Panama 2010 - see Variable: PA2010A_OCC - Occupation, 3 digits Papua New Guinea 1980 - see Variable: PG1980A_OCC - Occupation, 3 digits Papua New Guinea 1990 - see Variable: PG1990A_OCC - Occupation Papua New Guinea 2000 - see Variable: PG2000A_OCC - Occupation (4-digit) Paraguay 1962 - see Variable: PY1962A_OCC1 - Occupation (1-digit) Paraguay 1972 - see Variable: PY1972A_OCC3 - Occupation (3 digits) Paraguay 1982 - see Variable: PY1982A_OCC3 - Occupation, 3-digits Paraguay 1992 - see Variable: PY1992A_OCC2 - Main occupation, 3 digits Paraguay 2002 - see Variable: PY2002A_OCC - Occupation (4 digits) Peru 1993 - see Variable: PE1993A_OCC - Occupation (3 digits) Peru 2007 - see Variable: PE2007A_OCC - Main occupation last week (3 digits) Peru 2017 - see Variable: PE2017A_OCC1 - Occupation (1-digit, in primary job last week) Philippines 1990 - see Variable: PH1990A_OCC - Occupation Philippines 2000 - see Variable: PH2000A_OCC - Occupation Philippines 2010 - see Variable: PH2010A_OCC3 - Usual occupation (3-digit) Poland 1978 - see Variable: PL1978A_OCC - Occupation Poland 1988 - see Variable: PL1988A_OCC - Main occupation Poland 2002 - see Variable: PL2002A_OCC - Occupation Portugal 1981 - see Variable: PT1981A_OCC - Main occupation Portugal 1991 - see Variable: PT1991A_OCC - Main occupation Portugal 2001 - see Variable: PT2001A_OCC - Main occupation Portugal 2011 - see Variable: PT2011A_OCC - Main occupation Puerto Rico 1970 - see Variable: PR1970A_OCC - Occupation Puerto Rico 1980 - see Variable: PR1980A_OCC - Occupation Puerto Rico 1990 - see Variable: PR1990A_OCC - Occupation Puerto Rico 2000 - see Variable: PR2000A_OCC - Occupation Puerto Rico 2005 - see Variable: PR2005A_OCC - Occupation Puerto Rico 2010 - see Variable: PR2010A_OCC - Occupation Puerto Rico 2015 - see Variable: PR2015A_OCC - Occupation last week Puerto Rico 2020 - see Variable: PR2020A_OCC2010 - Occupation last week, 2010 basis Romania 1992 - see Variable: RO1992A_OCC - Occupation Romania 2002 - see Variable: RO2002A_OCC4 - Occupation, 4 digits Romania 2011 - see Variable: RO2011A_OCC - Occupation (unrecoded) Rwanda 2002 - see Variable: RW2002A_OCC - Occupation Rwanda 2012 - see Variable: RW2012A_OCC2 - Occupation (3-digit) Saint Lucia 1991 - see Variable: LC1991A_OCC - Occupation Senegal 1988 - see Variable: SN1988A_OCC - Occupation Senegal 2002 - see Variable: SN2002A_OCC3 - Occupation, 3 digits Senegal 2013 - see Variable: SN2013A_OCC3 - Profession or occupation (3-digit) Sierra Leone 2004 - see Variable: SL2004A_OCC - Occupation Sierra Leone 2015 - see Variable: SL2015A_OCC - Main occupation in the past 12 months Slovakia 1991 - see Variable: SK1991A_OCC - Occupation (2-digit) Slovakia 2001 - see Variable: SK2001A_OCC2 - Occupation (2-digit) Slovakia 2011 - see Variable: SK2011A_OCC2 - Occupation (2-digit) Slovenia 2002 - see Variable: SI2002A_OCC - Occupation South Africa 1996 - see Variable: ZA1996A_OCC3 - Occupation, 3 digits South Africa 2001 - see Variable: ZA2001A_OCC - Occupation, 3 digit South Africa 2007 - see Variable: ZA2007A_OCC3 - Occupation, 3 digits South Sudan 2008 - see Variable: SS2008A_OCC - Occupation Spain 1981 - see Variable: ES1981A_OCC - Occupation Spain 1991 - see Variable: ES1991A_OCC - Occupation Spain 2001 - see Variable: ES2001A_OCC - Occupation Spain 2011 - see Variable: ES2011A_OCC - Occupation, 2-digits Sudan 2008 - see Variable: SD2008A_OCC - Occupation Suriname 2004 - see Variable: SR2004A_OCC - Occupation Suriname 2012 - see Variable: SR2012A_OCC - Occupation (groups) Switzerland 1970 - see Variable: CH1970A_ISCO - Present occupation (ISCO) Switzerland 1980 - see Variable: CH1980A_ISCO - Present occupation (ISCO-COM) Switzerland 1990 - see Variable: CH1990A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2000 - see Variable: CH2000A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2011 - see Variable: CH2011A_OCC - Current occupation (1-digit, ISCO-08) Tanzania 1988 - see Variable: TZ1988A_OCC - Occupation Tanzania 2002 - see Variable: TZ2002A_OCC - Occupation last week Tanzania 2012 - see Variable: TZ2012A_OCC - Occupation Thailand 1970 - see Variable: TH1970A_OCC - Principal occupation last year Thailand 1980 - see Variable: TH1980A_OCC - Occupation last year Thailand 1990 - see Variable: TH1990A_OCC3 - Occupation last year Thailand 2000 - see Variable: TH2000A_OCC3 - Occupation last year, 3 digits Togo 1960 - see Variable: TG1960A_OCC - Occupation (3-digits) Togo 1970 - see Variable: TG1970A_OCC3 - Occupation (3-digits) Togo 2010 - see Variable: TG2010A_OCC2 - Occupation (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_OCC - Main occupation (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_OCC - Main occupation during previous week (three digits) Trinidad and Tobago 2000 - see Variable: TT2000A_OCC - Main occupation (3 digits) Turkey 1985 - see Variable: TR1985A_OCC2 - Occupation (2-digit) Turkey 1990 - see Variable: TR1990A_OCC2 - Current occupation (2 digits) Turkey 2000 - see Variable: TR2000A_OCC2 - Current occupation, 2 digit Uganda 1991 - see Variable: UG1991A_OCC - Occupation, 3 digits Uganda 2002 - see Variable: UG2002A_OCC - Occupation, 3 digits Uganda 2014 - see Variable: UG2014A_OCC - Occupation (2-digits) United Kingdom 1961 - see Variable: UK1961A_OCC - Occupation United Kingdom 1971 - see Variable: UK1971A_OCC - Occupation United Kingdom 1991 - see Variable: UK1991A_OCC - Occupational classification United Kingdom 2001 - see Variable: UK2001A_OCC3 - Standard occupational classification 2000-minor United States 1960 - see Variable: US1960A_OCC - Occupation United States 1970 - see Variable: US1970A_OCC - Occupation United States 1980 - see Variable: US1980A_OCC - Occupation United States 1990 - see Variable: US1990A_OCC - Occupation United States 2000 - see Variable: US2000A_OCC - Occupation United States 2005 - see Variable: US2005A_OCC2000M - Occupation, 2000 basis, modal category assignment United States 2010 - see Variable: US2010A_OCC - Occupation United States 2015 - see Variable: US2015A_OCC - Occupation last week United States 2020 - see Variable: US2020A_OCC - Occupation last week Uruguay 1963 - see Variable: UY1963A_OCC2 - Primary occupation [2-digit] Uruguay 1975 - see Variable: UY1975A_OCC - Occupation (COTA, 3 digits) Uruguay 1985 - see Variable: UY1985A_OCC - Occupation during the past week Uruguay 1996 - see Variable: UY1996A_OCC - Occupation (ISCO 88, 3 digits) Uruguay 2006 - see Variable: UY2006A_OCC3 - Occupation (ISCO-88, 3 digits) Venezuela 1981 - see Variable: VE1981A_OCC3 - Occupation, 3 digits Venezuela 1990 - see Variable: VE1990A_OCC - Occupation, 3 digits Venezuela 2001 - see Variable: VE2001A_OCC - Occupation Vietnam 1989 - see Variable: VN1989A_OCC2 - Occupation, 2 digits Vietnam 1999 - see Variable: VN1999A_OCC3 - Occupation, 3 digit Vietnam 2009 - see Variable: VN2009A_OCC - Occupation Vietnam 2019 - see Variable: VN2019A_OCC1 - Occupation, 1 digit Zambia 1990 - see Variable: ZM1990A_OCC - Occupation Zambia 2000 - see Variable: ZM2000A_OCC - Main occupation last 12 months, 3 digits Zambia 2010 - see Variable: ZM2010A_OCC2 - Main occupation last 12 months, 3 digits Zimbabwe 2012 - see Variable: ZW2012A_OCC - Occupation (3-digits) Work Variables -- PERSON Industry, general recode INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown Work Variables -- PERSON Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_IND4 - Industry [4 digit] Argentina 1980 - see Variable: AR1980A_IND - Industry Argentina 1991 - see Variable: AR1991A_IND - Industry Argentina 2001 - see Variable: AR2001A_IND - Industry Armenia 2001 - see Variable: AM2001A_IND - Principal activity at place of work Armenia 2011 - see Variable: AM2011A_IND - Industry Austria 1971 - see Variable: AT1971A_INDBR - Economic activity of supporter: branch Austria 1981 - see Variable: AT1981A_INDBR - Economic activity of supporter: branch Austria 1991 - see Variable: AT1991A_INDBR - Economic activity of supporter: branch Austria 2001 - see Variable: AT2001A_INDBR - Economic activity of supporter: branch Austria 2011 - see Variable: AT2011A_IND - Industry Bangladesh 1991 - see Variable: BD1991A_IND - Industry Bangladesh 2001 - see Variable: BD2001A_IND - Main work field Bangladesh 2011 - see Variable: BD2011A_IND - Industry Belarus 2009 - see Variable: BY2009A_ECONACT - Industry Benin 1979 - see Variable: BJ1979A_IND - Industry (1-digit) Benin 1992 - see Variable: BJ1992A_IND3 - Industry (2-digits) Benin 2002 - see Variable: BJ2002A_IND2 - Industry (2-digits) Benin 2013 - see Variable: BJ2013A_IND3 - Industry (3-digit) Bolivia 1976 - see Variable: BO1976A_IND - Industry Bolivia 1992 - see Variable: BO1992A_IND3 - Activity, 3 digits Bolivia 2001 - see Variable: BO2001A_IND3 - Industry, 3 digits Bolivia 2012 - see Variable: BO2012A_IND2 - Industry (2 digit) Botswana 1981 - see Variable: BW1981A_IND - Industry Botswana 1991 - see Variable: BW1991A_IND - Industry Botswana 2001 - see Variable: BW2001A_IND - Industry Botswana 2011 - see Variable: BW2011A_IND - Industry, 3-digits Brazil 1960 - see Variable: BR1960A_INDUSTRY - Industry Brazil 1970 - see Variable: BR1970A_INDUSTRY - Industry Brazil 1980 - see Variable: BR1980A_INDUSTRY - Industry Brazil 1991 - see Variable: BR1991A_IND - Industry Brazil 2000 - see Variable: BR2000A_IND - Industry, 5 digits Brazil 2010 - see Variable: BR2010A_IND - Industry of work from July 25 to July 31, 2010 Burkina Faso 1996 - see Variable: BF1996A_IND - Branch of activity Cambodia 1998 - see Variable: KH1998A_IND - Industry Cambodia 2004 - see Variable: KH2004A_IND3 - Industry (3-digits) Cambodia 2008 - see Variable: KH2008A_IND - Industry Cambodia 2013 - see Variable: KH2013A_IND - Industry (3-digits) Cambodia 2019 - see Variable: KH2019A_IND3 - Industy (ISIC rev 4, 3-digit) Cameroon 2005 - see Variable: CM2005A_IND - Industry Canada 1971 - see Variable: CA1971A_IND - Industry Canada 1981 - see Variable: CA1981A_IND - Industry (1981 standard industrial classification) Canada 1991 - see Variable: CA1991A_IND80 - Industry (1980 standard industrial classification) Canada 2001 - see Variable: CA2001A_IND80P - Industry (1980 Standard Industrial Classification) Canada 2011 - see Variable: CA2011A_IND - Industry Chile 1960 - see Variable: CL1960A_IND - Industry Chile 1970 - see Variable: CL1970A_IND4 - Industry (4-digit) Chile 1982 - see Variable: CL1982A_IND4 - Industry (4-digit) Chile 1992 - see Variable: CL1992A_IND - Industry Chile 2002 - see Variable: CL2002A_IND - Industry Chile 2017 - see Variable: CL2017A_IND - Industry (1-digit) China 1982 - see Variable: CN1982A_INDUSTRY - Industry China 1990 - see Variable: CN1990A_IND - Industry China 2000 - see Variable: CN2000A_IND - Industry (2-digit) Colombia 1964 - see Variable: CO1964A_IND4 - Industry, 4 digits Colombia 1973 - see Variable: CO1973A_IND - Industry Colombia 1993 - see Variable: CO1993A_IND - Industry Colombia 2005 - see Variable: CO2005A_IND - Industry (2-digit) Costa Rica 1963 - see Variable: CR1963A_IND3 - Industry, 3 digits Costa Rica 1973 - see Variable: CR1973A_IND4 - Industry, 4 digits Costa Rica 1984 - see Variable: CR1984A_IND4 - Industry, 4 digits Costa Rica 2000 - see Variable: CR2000A_IND3 - Industry, 3 digits Costa Rica 2011 - see Variable: CR2011A_IND - Industry 2-digit Cuba 2002 - see Variable: CU2002A_IND - Industry Cuba 2012 - see Variable: CU2012A_IND - Industry Côte d'Ivoire 1988 - see Variable: CI1988A_IND - Industry (1-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_IND2 - Industry sector (detailed) Dominican Republic 1960 - see Variable: DO1960A_IND - Industry Dominican Republic 1970 - see Variable: DO1970A_IND1 - Industry, 3 digits Dominican Republic 1981 - see Variable: DO1981A_IND - Industry (3-digit) Dominican Republic 2002 - see Variable: DO2002A_IND - Industry Dominican Republic 2010 - see Variable: DO2010A_IND - Main activity of business Ecuador 1962 - see Variable: EC1962A_IND3 - Industry, 3 digits Ecuador 1982 - see Variable: EC1982A_IND3 - Industry Ecuador 1990 - see Variable: EC1990A_IND3 - Industry, 3 digits Ecuador 2001 - see Variable: EC2001A_IND - Industry, 3 digits Ecuador 2010 - see Variable: EC2010A_IND3 - Industry (3 digits, ISIC rev 4) Egypt 1986 - see Variable: EG1986A_IND3 - Industry (3-digit) Egypt 1996 - see Variable: EG1996A_IND3 - Industry (ISIC) Egypt 2006 - see Variable: EG2006A_IND - Industry, 3-digit El Salvador 1992 - see Variable: SV1992A_IND - Industry (3-digit) El Salvador 2007 - see Variable: SV2007A_IND3DIG - Industry (3-digit) Ethiopia 1984 - see Variable: ET1984A_IND2 - Industry Ethiopia 1994 - see Variable: ET1994A_IND - Industry Fiji 1966 - see Variable: FJ1966A_IND - Industry Fiji 1976 - see Variable: FJ1976A_IND - Industry Fiji 1986 - see Variable: FJ1986A_IND - Industry 3 digits Fiji 1996 - see Variable: FJ1996A_IND2DIG - Industry (2 digits) Fiji 2007 - see Variable: FJ2007A_IND2 - Industry, 2 digits Fiji 2014 - see Variable: FJ2014A_IND - Industry Finland 2010 - see Variable: FI2010A_IND - Industry France 1962 - see Variable: FR1962A_IND - Industry France 1968 - see Variable: FR1968A_IND41 - Industry, 41 categories France 1975 - see Variable: FR1975A_INDUN - Industry, UNO France 1982 - see Variable: FR1982A_INDUN - Industry, United Nations nomenclature France 1990 - see Variable: FR1990A_IND15 - Industry, 15 categories France 1999 - see Variable: FR1999A_INDCITI - Industry, ISIC France 2006 - see Variable: FR2006A_IND700N - Economic activity in 700 categories (2003 classification) numeric recode France 2011 - see Variable: FR2011A_IND - Industry, 732 categories Germany 1970 - see Variable: DE1970A_IND - Industry Germany 1971 - see Variable: DE1971A_IND - Industry Germany 1981 - see Variable: DE1981A_IND - Industry Germany 1987 - see Variable: DE1987A_IND - Industry Ghana 2000 - see Variable: GH2000A_IND - Industry Ghana 2010 - see Variable: GH2010A_IND - Industry (major groups) Greece 1971 - see Variable: GR1971A_IND - Industry Greece 1981 - see Variable: GR1981A_IND - Industry Greece 1991 - see Variable: GR1991A_IND - Industry Greece 2001 - see Variable: GR2001A_IND - Industry Greece 2011 - see Variable: GR2011A_IND - Industry Guatemala 1964 - see Variable: GT1964A_IND3 - Field of economic activity (3-digits) Guatemala 1973 - see Variable: GT1973A_IND3 - Industry (3-digits) Guatemala 1981 - see Variable: GT1981A_IND3 - Industry (3-digits) Guatemala 1994 - see Variable: GT1994A_IND2 - Field of economic activity (2-digits) Guatemala 2002 - see Variable: GT2002A_IND1 - Field of economic activity (1-digit) Guinea 1983 - see Variable: GN1983A_IND2 - Branch of economic activity, 2 digits Guinea 2014 - see Variable: GN2014A_IND - Industry (3-digit) Haiti 1982 - see Variable: HT1982A_IND - Branch of work Haiti 2003 - see Variable: HT2003A_IND2 - Industry, 3 digits Honduras 1961 - see Variable: HN1961A_IND - Industry (2-digits) Honduras 1974 - see Variable: HN1974A_IND - Industry (3-digits) Honduras 2001 - see Variable: HN2001A_IND - Industry (4-digit) Honduras 2013 - see Variable: HN2013A_IND3 - Economic activity (3-digit) Hungary 2001 - see Variable: HU2001A_IND - Industry, branch of economy Hungary 2011 - see Variable: HU2011A_IND - Industry Indonesia 1971 - see Variable: ID1971A_IND - Industry Indonesia 1976 - see Variable: ID1976A_IND - Industry Indonesia 1980 - see Variable: ID1980A_IND - Industry Indonesia 1985 - see Variable: ID1985A_IND - Industry of primary occupation Indonesia 1990 - see Variable: ID1990A_IND - Industry of main occupation last week Indonesia 1995 - see Variable: ID1995A_IND - Industry Indonesia 2000 - see Variable: ID2000A_IND - Industry of primary occupation Indonesia 2005 - see Variable: ID2005A_IND - Industry Indonesia 2010 - see Variable: ID2010A_IND - Industry Iran 2006 - see Variable: IR2006A_IND4 - Industry Iran 2011 - see Variable: IR2011A_IND - Industry (3-digit) Iraq 1997 - see Variable: IQ1997A_IND - Industry Ireland 1971 - see Variable: IE1971A_IND - Industry Ireland 1981 - see Variable: IE1981A_IND - Industry class Ireland 1986 - see Variable: IE1986A_IND - Industry class Ireland 1991 - see Variable: IE1991A_IND - Industry class Ireland 1996 - see Variable: IE1996A_IND - Industry class Ireland 2002 - see Variable: IE2002A_IND - Industry class Ireland 2006 - see Variable: IE2006A_IND - Industry class Ireland 2011 - see Variable: IE2011A_IND - Industry Ireland 2016 - see Variable: IE2016A_IND - Industry Israel 1972 - see Variable: IL1972A_IND - Industry Israel 1983 - see Variable: IL1983A_IND - Industry Israel 1995 - see Variable: IL1995A_IND - Industry Israel 2008 - see Variable: IL2008A_IND - Branch of economy Italy 2001 - see Variable: IT2001A_IND - Industry Italy 2011 - see Variable: IT2011A_IND - Sector of economic activity Jamaica 1982 - see Variable: JM1982A_IND - Industry or type of business during past week / in last job Jamaica 1991 - see Variable: JM1991A_IND3 - Industry during past week or in last job, 3 digits Jamaica 2001 - see Variable: JM2001A_IND3 - Industry 3-digit Jordan 2004 - see Variable: JO2004A_IND - Major current economic activity of the establishment Kenya 2019 - see Variable: KE2019A_IND1 - Industry, ISIC section Kyrgyzstan 1999 - see Variable: KG1999A_IND - Activity type of an enterprise you are working in Kyrgyzstan 2009 - see Variable: KG2009A_IND - Type of industry, enterprise or organization Laos 1995 - see Variable: LA1995A_IND2 - Main industry in the last 12 months (2-digit) Laos 2005 - see Variable: LA2005A_IND3 - Industry (ISIC 3-digit) Laos 2015 - see Variable: LA2015A_IND2 - Industry (2-digit ISIC Rev. 4) Lesotho 2006 - see Variable: LS2006A_IND - Industry (2-digits) Liberia 1974 - see Variable: LR1974A_IND - Industry (3-digit) Liberia 2008 - see Variable: LR2008A_IND - Industry Malawi 1987 - see Variable: MW1987A_IND2 - Industry, 2 digit Malawi 1998 - see Variable: MW1998A_IND4 - Industry, 4-digit Malawi 2008 - see Variable: MW2008A_IND2 - Main industry Malawi 2018 - see Variable: MW2018A_IND3 - Main industry (ISIC 2008 3-digit) Malaysia 1970 - see Variable: MY1970A_IND3 - Industry last week Malaysia 1980 - see Variable: MY1980A_IND3 - Industry last week (3 digits) Malaysia 1991 - see Variable: MY1991A_IND3 - Main industry (3 digits) Malaysia 2000 - see Variable: MY2000A_IND3 - Main industry - 3 digits Mali 1987 - see Variable: ML1987A_IND - Principal branch of employment last month Mali 1998 - see Variable: ML1998A_IND - Branch of economic activity Mali 2009 - see Variable: ML2009A_IND - Industry Mauritius 1990 - see Variable: MU1990A_IND - Industry (1-digit) Mauritius 2000 - see Variable: MU2000A_IND1 - Industry (1 digit) Mauritius 2011 - see Variable: MU2011A_IND2 - Industry (2-digit) Mexico 1960 - see Variable: MX1960A_IND - Industry Mexico 1970 - see Variable: MX1970A_IND - Industry Mexico 1990 - see Variable: MX1990A_IND5 - Industry, 5 digits Mexico 1995 - see Variable: MX1995A_IND - Industry Mexico 2000 - see Variable: MX2000A_IND3 - Industry, 3 digits Mexico 2010 - see Variable: MX2010A_IND - Industry Mexico 2015 - see Variable: MX2015A_IND - Industry Mexico 2020 - see Variable: MX2020A_IND - Industry (4-digits) Mongolia 2000 - see Variable: MN2000A_IND - Industry Mongolia 2010 - see Variable: MN2010A_IND2 - Industry, division (ISIC Revision 4) Mongolia 2020 - see Variable: MN2020A_IND3 - Main industry (3-digit) Morocco 1982 - see Variable: MA1982A_IND3 - Industry (3-digit) Morocco 1994 - see Variable: MA1994A_IND2 - Industry (2 digits) Morocco 2004 - see Variable: MA2004A_IND2 - Sector of economic activity (2-digit) Morocco 2014 - see Variable: MA2014A_IND2 - Industry (2-digit) Mozambique 1997 - see Variable: MZ1997A_IND1 - Industry Mozambique 2007 - see Variable: MZ2007A_IND - Industry Mozambique 2017 - see Variable: MZ2017A_IND2 - Main economic activity (2-digits CAE Rev.2) Myanmar 2014 - see Variable: MM2014A_IND - Industry Nepal 2001 - see Variable: NP2001A_IND - Usual industry Nepal 2011 - see Variable: NP2011A_IND - Industry (2-digit) Netherlands 1960 - see Variable: NL1960A_IND - Industry Netherlands 1971 - see Variable: NL1971A_IND - Industry Netherlands 2001 - see Variable: NL2001A_IND - Industry Netherlands 2011 - see Variable: NL2011A_IND - Industry (1-digit) Nicaragua 1971 - see Variable: NI1971A_IND3 - Industry (ISIC2), 3 digits Nicaragua 1995 - see Variable: NI1995A_IND - Industry (ISIC 3.1, 3 digits) Nicaragua 2005 - see Variable: NI2005A_IND3 - Industry (ISIC 3.1, 3 digits)) Pakistan 1973 - see Variable: PK1973A_IND2 - Industry, 2 digit Palestine 1997 - see Variable: PS1997A_IND - Industry Palestine 2007 - see Variable: PS2007A_IND - Industry Palestine 2017 - see Variable: PS2017A_IND - Industry Panama 1960 - see Variable: PA1960A_IND3 - Industry (3 digit) Panama 1970 - see Variable: PA1970A_IND3 - Industry [3 digit] Panama 1980 - see Variable: PA1980A_IND - Industry, 3-digit Panama 1990 - see Variable: PA1990A_IND3 - Industry - 3 Digits Panama 2000 - see Variable: PA2000A_IND - Economic activity, 3 digits Panama 2010 - see Variable: PA2010A_IND - Economic activity, 4 digits Papua New Guinea 1980 - see Variable: PG1980A_IND - Industry, 3 digits Papua New Guinea 2000 - see Variable: PG2000A_IND3 - Industry (3-digit) Paraguay 1962 - see Variable: PY1962A_IND3 - Industry (3 digits) Paraguay 1972 - see Variable: PY1972A_IND3 - Industry (3 digits) Paraguay 1982 - see Variable: PY1982A_IND3 - Industry, 3-digits Paraguay 1992 - see Variable: PY1992A_IND3 - Industry, 3 digits Paraguay 2002 - see Variable: PY2002A_IND - Industry (4 digits) Peru 1993 - see Variable: PE1993A_IND - Economic activity (4 digits) Peru 2007 - see Variable: PE2007A_IND - Economic activity (4-digits) Peru 2017 - see Variable: PE2017A_IND4 - Economic activity (4-digits, in primary job last week) Philippines 1990 - see Variable: PH1990A_IND - Industry Philippines 1995 - see Variable: PH1995A_IND - Industry Philippines 2000 - see Variable: PH2000A_IND - Industry Philippines 2010 - see Variable: PH2010A_IND3 - Kind of business or industry (3-digit) Poland 1978 - see Variable: PL1978A_IND - Industry (of person providing support) Poland 2002 - see Variable: PL2002A_IND - Industry (main employer) Portugal 1981 - see Variable: PT1981A_IND - Industry Portugal 1991 - see Variable: PT1991A_IND - Industry Portugal 2001 - see Variable: PT2001A_IND - Industry Portugal 2011 - see Variable: PT2011A_IND - Industry Puerto Rico 1970 - see Variable: PR1970A_IND1990 - Industry, 1990 basis Puerto Rico 1980 - see Variable: PR1980A_IND1990 - Industry, 1990 basis Puerto Rico 1990 - see Variable: PR1990A_IND - Industry Puerto Rico 2000 - see Variable: PR2000A_IND1990 - Industry, 1990 basis Puerto Rico 2005 - see Variable: PR2005A_IND1990 - Industry, 1990 basis Puerto Rico 2010 - see Variable: PR2010A_IND - Industry Puerto Rico 2015 - see Variable: PR2015A_IND - Industry Puerto Rico 2020 - see Variable: PR2020A_IND - Industry Romania 1977 - see Variable: RO1977A_IND - Industry of supporter Romania 1977 - see Variable: RO1977A_WKACT - Activity category Romania 1992 - see Variable: RO1992A_IND - Industry Romania 2002 - see Variable: RO2002A_IND - Industry Romania 2011 - see Variable: RO2011A_INDGEN - Industry (general categories) Rwanda 2002 - see Variable: RW2002A_IND - Industry Rwanda 2012 - see Variable: RW2012A_IND2 - Industry (3-digit) Saint Lucia 1991 - see Variable: LC1991A_IND3 - Industry, 2 digit Senegal 1988 - see Variable: SN1988A_IND - Industry Senegal 2013 - see Variable: SN2013A_IND3 - Industry (3-digit) Sierra Leone 2004 - see Variable: SL2004A_IND - Industry Slovenia 2002 - see Variable: SI2002A_IND - Industry South Africa 1996 - see Variable: ZA1996A_IND2 - Industry, 2 digits South Africa 2001 - see Variable: ZA2001A_IND3 - Industry, 3 digit South Africa 2007 - see Variable: ZA2007A_IND3 - Industry, 3 digit South Sudan 2008 - see Variable: SS2008A_IND - Industry Spain 1981 - see Variable: ES1981A_IND - Industry Spain 1991 - see Variable: ES1991A_IND - Activity of the establishment Spain 2001 - see Variable: ES2001A_IND - Industry Spain 2011 - see Variable: ES2011A_IND - Industry, 2-digits Sudan 2008 - see Variable: SD2008A_IND - Industry Suriname 2004 - see Variable: SR2004A_IND - Industry Suriname 2012 - see Variable: SR2012A_IND - Industry (groups) Switzerland 1970 - see Variable: CH1970A_IND - Branch of economic activity (industry) Switzerland 1980 - see Variable: CH1980A_IND - Branch of economic activity (industry) Switzerland 1990 - see Variable: CH1990A_IND - Branch of economic activity (industry) Switzerland 2000 - see Variable: CH2000A_IND - Branch of economic activity (industry) Switzerland 2011 - see Variable: CH2011A_IND2 - Industry of local unit, workplace (NOGA 2-digit) Tanzania 2002 - see Variable: TZ2002A_IND - Industry last week Tanzania 2012 - see Variable: TZ2012A_IND - Industry Thailand 1970 - see Variable: TH1970A_IND - Principal industry last year Thailand 1980 - see Variable: TH1980A_IND - Principal industry last year Thailand 1990 - see Variable: TH1990A_IND3 - Principal industry last year, 3 digits Thailand 2000 - see Variable: TH2000A_IND3 - Industry last year, 3 digits Togo 1970 - see Variable: TG1970A_IND - Industry (1-digit) Togo 2010 - see Variable: TG2010A_IND3 - Industry (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_IND - Industry (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_IND - Industry Trinidad and Tobago 2000 - see Variable: TT2000A_IND - Industry (2 digits) Turkey 1985 - see Variable: TR1985A_INDALT - Industry (2-digit) Turkey 1990 - see Variable: TR1990A_IND2 - Industry (2 digits) Turkey 2000 - see Variable: TR2000A_IND2 - Industry, 2 digit Uganda 2002 - see Variable: UG2002A_IND - Industry United Kingdom 1961 - see Variable: UK1961A_IND - Industry United Kingdom 1971 - see Variable: UK1971A_IND - Industry United Kingdom 1991 - see Variable: UK1991A_IND - Industrial classification United Kingdom 2001 - see Variable: UK2001A_IND - Industry classification United States 1960 - see Variable: US1960A_IND - Industry United States 1970 - see Variable: US1970A_IND - Industry United States 1980 - see Variable: US1980A_IND - Industry United States 1990 - see Variable: US1990A_IND - Industry United States 2000 - see Variable: US2000A_IND - Industry United States 2005 - see Variable: US2005A_IND - Industry United States 2010 - see Variable: US2010A_IND - Industry United States 2015 - see Variable: US2015A_IND - Industry United States 2020 - see Variable: US2020A_IND - Industry Uruguay 1963 - see Variable: UY1963A_IND2 - Primary industry [2-digit] Uruguay 1985 - see Variable: UY1985A_IND - Industry during the past week Uruguay 1996 - see Variable: UY1996A_IND2 - Industry (ISIC 3, 2 digits) Uruguay 2006 - see Variable: UY2006A_IND3 - Industry (ISIC rev 3, 3 digits) Venezuela 1981 - see Variable: VE1981A_IND - Industry Venezuela 1990 - see Variable: VE1990A_IND - Industry Venezuela 2001 - see Variable: VE2001A_IND - Industry Vietnam 1989 - see Variable: VN1989A_IND2 - Industry, 2 digits Vietnam 1999 - see Variable: VN1999A_IND3 - Industry, 3 digit Vietnam 2009 - see Variable: VN2009A_IND - Industry Vietnam 2019 - see Variable: VN2019A_IND3 - Industry, 3 digit Zambia 1990 - see Variable: ZM1990A_IND - Industry Zambia 2000 - see Variable: ZM2000A_IND - Type of industry, 3 digits Zambia 2010 - see Variable: ZM2010A_IND2 - Industry, 3 digits Work Variables -- PERSON Status in employment (class of worker) [general version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 0 NIU (not in universe) 1 Self-employed 2 Wage/salary worker 3 Unpaid worker 4 Other 9 Unknown/missing Work Variables -- PERSON Status in employment (class of worker) [detailed version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 000 NIU (not in universe) 100 Self-employed 101 Self-employed, unincorporated 102 Self-employed, incorporated 110 Employer 111 Sharecropper, employer 120 Working on own account 121 Own account, agriculture 122 Domestic worker, self-employed 123 Subsistence worker, own consumption 124 Own account, other 125 Own account, without temporary/unpaid help 126 Own account, with temporary/unpaid help 130 Member of cooperative 140 Sharecropper 141 Sharecropper, self-employed 142 Sharecropper, employee 150 Kibbutz member 199 Self-employed, not specified 200 Wage/salary worker 201 Management 202 Non-management 203 White collar (non-manual) 204 Blue collar (manual) 205 White or blue collar 206 Day laborer 207 Employee, with a permanent job 208 Employee, occasional, temporary, contract 209 Employee without legal contract 210 Wage/salary worker, private employer 211 Apprentice 212 Religious worker 213 Wage/salary worker, non-profit, NGO 214 White collar, private 215 Blue collar, private 216 Paid family worker 217 Cooperative employee 220 Wage/salary worker, government or public sector 221 Federal, government employee 222 State government employee 223 Local government employee 224 White collar, public 225 Blue collar, public 226 Public companies 227 Civil servants, local collectives 230 Domestic worker (work for private household) 240 Seasonal migrant 241 Seasonal migrant, no broker 242 Seasonal migrant, uses broker 250 Other wage and salary 251 Canal zone/commission employee 252 Government employment/training program 253 Mixed state/private enterprise/parastatal 254 Government public work program 255 State enterprise employee 256 Coordinated and continuous collaboration job 300 Unpaid worker 310 Unpaid family worker 320 Apprentice, unpaid or unspecified 330 Trainee 340 Apprentice or trainee 350 Works for others without wage 400 Other 999 Unknown/missing Work Variables -- PERSON Status in employment (class of worker), Europe ECLASSWK refers in European Samples to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. ECLASSWK is related to EEMPSTAT (employment status), which is used to define the universe for the variable in many samples. ECLASSWK has been classified according to the recommendations given by the Conference of European Statisticians for the 2010 Population and Housing Censuses. "Class of worker" is referred to as "Status in Employment" in the CES recommendations. The former term is used to maintain concordance with IPUMS practice. 0 NIU (not in universe) 1 Employees 2 Employers 3 Own-account worker 4 Contributing family workers 5 Members of producers' co-operatives 6 Persons not classificable by status 9 Unknown Work Variables -- PERSON Sector of employment EMPSECT indicates the economic sector in which the person was employed. Economic sector is defined in terms of ownership or control of the enterprise in which the person worked. 00 NIU (not in universe) 10 Public 20 Private 21 Private, not elsewhere classified 22 Individual/family enterprise, and self-employed 23 Foreign 30 Mixed: public-private or parastatal 40 Collective or cooperative 50 Foreign government or non-governmental organization 60 Other, unspecified 61 Canal zone 62 Faith-based organization 63 Informal sector 99 Unknown Work Variables -- PERSON Person number (within household) Hungary 2011: All records This variable indicates the person number (within the household). 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 Technical Person Variables -- PERSON Serial number of household in the dwelling Hungary 2011: All persons This variable indicates the serial number of household in the dwelling. 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 Technical Person Variables -- PERSON Serial number of family in the household Hungary 2011: Persons not living in institutions or homeless [discrepancies: none] This variable indicates the serial number of the family in the household. 0 NIU (not in universe) 1 1 2 2 3 3 4 4 5 5 Technical Person Variables -- PERSON Family status Hungary 2011: All persons This variable indicates the family status. 01 Husband, wife 02 Cohabiting partner 03 Father, mother (lone parent living together with her or his children, if the children do not live in a couple relationship) 04 Child (including fostered and adopted children) 05 Ascendant (parents and grandparents living together with the family), other relative, non relative 06 Person living alone 10 Person living in institution, homeless with no home address Demographic Variables -- PERSON Tenure status of the housing unit <span class="h1">Personal questionnaire</span></p> <p>4.2 Under what title do you live there?</p> <div class="i1">[] Owner or dependent relative<br />[] Tenant the whole of the dwelling or relative of tenant<br />[] Tenant of a part of the dwelling<br />[] Others</div> <span class="h2"> I. Demography</span></p> <p><span class="em">4. Data on the address provided on the dwelling questionnaire</span> <br /><span class="em">4.2. Under what title do you live there?</span> <br />The owner or beneficial owner (full or partial) is to be selected if the owner of the dwelling is a member of the household. <br />This category also includes the households where the owner or beneficiary owner of the dwelling is not a member but at least one person of the household is a close relative (e.g. spouse, consensual partner, parent, brother or sister, grandchild) and no rent is paid.</p> <p>There can be more than one owner or beneficial owner in a dwelling. This answer can be marked only in dwellings owned by private persons.</p> <p>The household has tenant status if one of its members pays rent for the whole dwelling irrespectively whether he/she lives there alone or with others. This category includes "partner tenants" (only in case of dwellings owned by the municipality) and the tenant partners when more persons (e.g. students) rent a dwelling together. Also included are the households living in service dwellings when the use of the dwelling relates to a work or official relation of a member of the household, irrespectively whether they pay rent or not.</p> <p>One subgroup of the tenant category is the household renting a part of a dwelling when the household lives together with the owner in the dwelling and at least one premise (e.g. a room) is rented.</p> <p>The household lives in the dwelling by other tenure title if it cannot be classified in the previous categories (e.g. living there in favor, without any title, for sustenance). Hungary 2011: Persons not living in institutions or homeless [discrepancies: none] This variable indicates the tenure status of the housing unit. 1 Owner or relative, beneficial owner 2 Tenant of the whole dwelling or relative of tenant 3 Tenant of a part of the dwelling, other tenure 9 NIU (not in universe) Other Person Variables -- PERSON Sex <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>[Questions 1 through 3 were asked of all persons]</p> <p>1. Sex</p> <div class="i1">[] Male<br />[] Female</div> Hungary 2011: All persons This variable indicates the person's sex. 1 Male 2 Female Demographic Variables -- PERSON Age <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>[Questions 1 through 3 were asked of all persons]</p> <p>2. Date of birth:</p> <div class="i1">Year_ _ _ _<br />Month_ _<br />Day_ _</div> Hungary 2011: All persons This variable indicates the person's age in years. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 and over Demographic Variables -- PERSON Citizenship <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>[Questions 1 through 3 were asked of all persons]</p> <p>3. Citizenship</p> <div class="i1">[] 1 Hungarian<br />[] 2 Hungarian and foreign, specify other: ____ (1)<br />[] 3 Foreign, specify____ (2)<br />[] 4 Displaced person</div> <span class="h2"> I. Demography</span></p> <p><span class="em">3. Citizenship</span> <br />Citizenship that is not Hungarian should be specified in the white box. <br />Persons with dual citizenship <span class="em">Hungarian and other </span> should specify the other citizenship by writing it in the white box. Persons without Hungarian citizenship should fill the box next to not Hungarian, and write the citizenship in the white box. Two citizenships can be marked at this option. <span class="em">Displaced </span>is the person who is not citizen of any country. Hungary 2011: All persons This variable indicates the person's country of citizenship. 1 Hungarian, Hungarian and foreign 2 Other (foreign, stateless) Nativity and Birthplace Variables -- PERSON Legal marital status <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>[Questions 1 through 3 were asked of all persons]</p> <p>10. What is your legal marital status?</p> <div class="i1">[] 1 Single<br />[] 2 Married<br />[] 3 Widow(er)<br />[] 4 Divorced<br />[] 5 Registered cohabiting partner<br />[] 6 Widowed registered cohabiting partner<br />[] 7 Divorced registered cohabiting partner<br />[For responses 5, 6 and 7], these answers can be marked only in case of same-sex cohabiting partners registered after July 1, 2009.</div> <span class="h2"> I. Demography</span></p> <p><span class="em">10. What is your legal marital status?</span> <br />The <span class="em">legal </span>marital status must be taken into account. Also the legal marital status has to be marked in case of cohabiting partnership.</p> <div class="i1"><span class="em">Never married </span>is a person who has not yet married and not registered as cohabiting partner.<br /><br /><span class="em">Married </span>is a person whose legal marriage is not dissolved by a legal judgement, independently of the fact whether he/she lives together with his/her spouse or not.<br /><br /><span class="em">Widowed </span>is a person whose legal spouse deceased and who has not remarried or been registered as a cohabiting partner.<br /><br /><span class="em">Divorced </span>is a person whose marriage is dissolved by a legal judgement and who has not remarried or been registered as a cohabiting partner.<br /><br /><span class="em">Registered cohabiting partner </span>is a person who is registered with his/her same-sex partner by official authorities. According to the current legal status, registered cohabiting partnership can be registered since 1st July 2009. Registered at the notary public is not registered cohabiting partnership, as this does not change the person's legal marital status.<br /><br />In case the respondent is not married, continue the questionnaire at question 12.</div> Hungary 2011: All persons This variable indicates the person's marital status. 1 Never married 2 Married or registered cohabiting partner, living together with spouse, partner 3 Married or registered cohabiting partner, not living together with spouse, partner 4 Widowed, widowed registered cohabiting partner 5 Divorced, divorced registered cohabiting partner Demographic Variables -- PERSON In consensual union <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>[Questions 1 through 3 were asked of all persons]</p> <p>[Questions 12.1 and 12.2 are asked of persons in a cohabiting partnership] <br />12. Do you have a cohabiting partner?</p> <div class="i1">[] No [go to question 13]</div> <span class="h2"> I. Demography</span></p> <p><span class="em">12. Do you have a cohabiting partner?</span> <br />The question refers to both registered or recorded or unregistered or unrecorded cohabiting partnership.</p> <p>A person living in cohabiting partnership lives together with a partner without marriage permanently in a relationship similar to marriage, irrespectively of his/her sex, marital status and the fact whether he/she lives with the partner in the same household at the reference date of the census.</p> <p>In case of no answer, continue at question 13. Hungary 2011: All persons This variable indicates whether the person lives in consensual union. 0 No 1 Yes Demographic Variables -- PERSON Number of liveborn children <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>[Questions 1 through 3 were asked of all persons]</p> <p>15. Number of children born alive</p> <div class="i1">[] Children_ _<br />[] No children born alive [skip to question 17.1]</div> <span class="h2"> I. Demography</span></p> <p><span class="em">15. Number of children born alive:</span> <br />Both man and woman have to answer to this question irrespectively of their age. <br />Please take into account also those live-born children who live elsewhere, in another family or under state care, moved away or died. Adopted or fostered children must not be taken into account. <br />In case the person does not have live-born children, questionnaire has to be followed with question 17.1. Hungary 2011: All persons Number of liveborn children. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 or more Fertility and Mortality Variables -- PERSON Type of family Hungary 2011: Persons not living in institutions or homeless [discrepancies: none] This variable indicates the type of family. 01 Couple type family without child (child only refers to never married son or daughter) 02 Couple type family with child(ren) (child only refers to never married son or daughter) 05 Lone parent with child(ren) (child only refers to never married son or daughter) 08 Lone parent with ever married child(ren) type family, person living in non-family household with other(s) 09 Person living alone 99 NIU (not in universe) Constructed Family Interrelationship Variables -- PERSON Relationship to the head of family Hungary 2011: Persons not living in institutions or homeless [discrepancies: none] This variable indicates the person's relationship to the head of family. 00 Other person living with the head of family 01 Head of family, male 02 Head of family, female 03 Spouse of the head of family 04 Cohabiting partner of the head of family, male 05 Cohabiting partner of the head of family, female 06 Child living with the head of family, male 07 Child living with the head of family, female 08 Ascendant living with the head of family, male 09 Ascendant living with the head of family, female 99 NIU (not in universe) Demographic Variables -- PERSON Relationship to the head of household Hungary 2011: Persons not living in institutions or homeless [discrepancies: none] This variable indicates the relationship to the head of household. 00 Neither the head nor his or her spouse or partner 01 Head of household, male 02 Head of household, female 03 Wife of the head of household 04 Cohabiting partner of the head of household, male 05 Cohabiting partner of the head of household, female 99 NIU (not in universe) Constructed Family Interrelationship Variables -- PERSON Highest educational attainment completed in the school system <span class="h1">Personal questionnaire</span></p> <p><span class="h2">II. Education attainment</span> <br /><span class="em">Take into account studies and qualifications only in formal education.</span></p> <p>[Question were of all persons] <br />19. What is your highest completed level of education?</p> <div class="i1">[] 1 Lower than eight grade in primary (general higher general) school [Skip to question 21]<br />[] 2 Eight grade in primary (general, higher general) school [Skip to question 21]<br />[] 3 Certificate of apprentice school education<br />[] 4 Certificate of vocational school education<br />[] 5 General certificate of education without qualifications<br />[] 6 General certificate of education with qualifications school- leaving certificate<br />[] 7 Certificate of vocational programs built on general certificate of education<br />[] 8 Certificated of higher (also accredited) vocational programs (granted only after 1998)<br />[] 9 College (or equivalent e.g. BA/BSc) diploma<br />[] 10 University (or equivalent e.g. MA/MSc) diploma<br />[] 11 PhD or DLA degree</div> <span class="h2">II. Educational attainment</span></p> <p>Studies and qualifications obtained in formal education have to be taken into account in questions 17.1.--20</p> <p>Persons in formal education are in legal status with the school as pupils or students. Questions regarding school attendance must be answered only in case the respondent is in legal status with the school as pupil or student (question 17.1 must be answered also in case of attending infant nursery or kindergarten), completed educational attainment must be taken into account only if it had been obtained in formal education. Persons attending schools outside formal education (e.g. trainings) are not in legal status with the school, so these studies and certificates must not be counted.</p> <p><span class="em">19. What is your highest completed level of education? </span> <br />The order of the pre-printed answers defines the possible educational levels: the first is the lowest and the last is the highest educational level. The only one answer has to be marked which relates to the person.</p> <p><span class="em">The highest educational attainment </span>relates to the schools completed only in the educational system.</p> <p>Qualifications obtained in courses and vocational training or apprentice school certificates obtained during part-time education must not be taken into account. These qualifications are not part of the educational system.</p> <p>If the person got a university or colleague degree but did not get final exam, it is not meant to be education completed, so this should not be taken into account when defining the highest educational level.</p> <p>Qualifications attained abroad have to be classified according to the Hungarian school system levels.</p> <p><span class="em">Not even the first grade of general (primary) school completed </span>is the education of those having completed 1--7th years of general (primary) school, 1--3rd years in civil school, 1st year in 6 grades secondary school and 1-3rd years in 8 grades secondary school. Moreover include those who not even attend one grade of any school.</p> <p><span class="em">General (primary) school </span>is the education of those having completed the 8th grade of general (primary) school, 4-6th years of the civil school and do not have higher education or attended some years in secondary level of education but did not get either vocational exam or final examination.</p> <p><span class="em">Secondary level without final examination, with final vocational exam </span>is the education of those having attained certificate of profession in vocational training school or certificate of profession in apprentice school. Defining the highest educational attainment from the earlier vocational training schools only those are included in this category which had been completed in 1961 or later, and from the sanitary apprentice schools or typing schools only those which had been completed in 1976 or later all attended in full-time.</p> <p><span class="em">Secondary level with final examination </span>is the education of those having secondary level with final examinations either general or with vocational and of those who completed some grades in university or college etc. but did not get any diploma, certification. Secondary level with final examination educational attainment comprises of the following groups:</p> <p><span class="em">General certificate of education </span>is the highest educational attainment of those who got general certificate of education in secondary general school or secondary vocational school and do not have a vocational exam based on the general certification or higher education. This group includes also those persons who got final secondary examination between 1974 and 1986.</p> <p><span class="em">General certificate of education with qualifications </span>is the highest educational attainment of those who got their general certificate with qualifications in secondary vocational school, technical school, upper-commercial school, secondary level teacher and kindergarten teacher institution and do not have higher education completed. This group includes also those persons who completed a vocational final exam between 1949 and 1955.</p> <p><span class="em">Certificate of vocational programs </span>is the highest educational attainment of those who got general certificate in secondary vocational school between 1985 and 2002 and after the general certificate they got technical certificate in 1-3 grades and those who got secondary or higher level vocational certification listed in the National Vocational Register (OKJ) in secondary vocational school after doing general certificate and do not have higher education completed. This group includes also those persons who got general certificate of education in secondary vocational school for apprentice school for skilled workman.</p> <p><span class="em">Certificate of higher vocational programs </span>is the highest educational attainment of those who got higher vocational certification in secondary vocational school or tertiary educational institution after 1998 and do not have college or university diploma.</p> <p><span class="em">University, college, etc. with degree </span>is the education of those having a college (or equivalent, e.g. BA/BSc) degree or a university (or equivalent, e.g. MA/Msc) degree, or completed supplementary university courses (PhD or DLA).</p> <p>College diploma (or equivalent, e.g. BA/BSc) is the highest educational attainment of those who got diploma in college, tertiary level technical school, tertiary level vocational school, tertiary level kindergarten teacher or teacher institution etc. This group includes also those persons who got BA, BSc degree in tertiary educational system in basic training.</p> <p><span class="em">University diploma (or equivalent, e.g. MA, MSc) </span>is the highest educational attainment of those who got certificate or diploma in university, equivalent level tertiary level institution in basic or supplementary training and in professional further training. This group includes also those persons who got master degree (MA MSc) in the current tertiary educational system in master training or unified training.</p> <p><span class="em">PhD or DLA degree </span>is the highest educational attainment of those who got doctoral scientific degree achieved in doctoral regulations. Defining the highest educational attainment only those scientific doctoral degrees are included in this category which had been attained in 1991 or after. Those who got doctoral name together with the university diploma (lawyer, doctor, dentist, chemist, or veterinarian) do not belong to this group. Hungary 2011: All persons This variable indicates the person's highest educational level achieved. 0 No formal education (isced 0) 1 Primary education (isced 1) 2 Lower secondary education (isced 2) 3 Upper secondary education (isced 3a, 3b, 3c) 4 Post secondary non-tertiary education (isced 4) 5 First stage of tertiary education (isced 5) 6 Second stage of tertiary education (isced 6) Education Variables -- PERSON Current activity status <span class="h1">Personal questionnaire</span></p> <p><span class="h2">IV. Occupation, workplace and transport</span></p> <p>22. Mark which of the following groups you belong to.</p> <div class="i1">If you belong to more than one group (e.g. you work while receiving a pension), please mark all of them.<br />[] 1 Working (employee, entrepreneur, helping family member, casual worker, primary producer, member of a cooperative<br />[] 2 Jobless, job seeker<br />[] 3 Old age pension and retirement provision recipient on own right<br />[] 4 Disability pensioner and accident annuity beneficiary on own right, survivors (widows/widowers, parent), pension and retirement provision recipient)<br />[] 5 Child care benefit (child care allowance, child care fee, child care support) recipient<br />[] 6 Nursing allowance recipient<br />[] 7 Child attending infant nursery or kindergarten, student, student of a tertiary education institution<br />[] 8 0-15 years old child not attending infant nursery, kindergarten or school living on own assert or on real estate leasing<br />[] 9 Housewife<br />[] 10 Social support recipient<br />[] 11 Other, specify____</div> <span class="h2"> IV. Occupation, workplace and transport</span></p> <p><span class="em">22. Mark which of the following groups you belong to.</span> <br />More than one answer can be marked for this question (e.g. in case of working beside studying or pension, child-care allowance etc. working and studying, pension, child-care allowance also has to be marked.) In case the respondent cannot be classified into any category, write in the respondent's answer about himself/herself in the white box next to other. Hungary 2011: All persons This variable indicates the person's current activity status. 1 Employed 2 Unemployed 3 Persons receiving childcare benefit (child-care allowance, child-care fee, child-care support) 4 Pensioner (old-age pensioner, disability pensioner, survivers' pensioner) 5 Other inactive earner 6 Dependants Work Variables -- PERSON Occupation <span class="h1">Personal questionnaire</span></p> <p><span class="h2">IV. Occupation, workplace and transport</span></p> <p>27. Your (present or last) occupation: ____ <span class="h2"> IV. Occupation, workplace and transport</span></p> <p><span class="em">27. Your (present or last) occupation: </span> <br />Write here the occupation the respondent does as his/her main job, or if he/she does not work currently, the main occupation he/she last did. In the case of somebody who does more than two jobs at the same time, indicate the most significant one, which is the one of which he/she spends most of the time.</p> <p>Indicate the occupation/ field of activity with enough detail as to clearly establish the activity performed. Do not use general terms which do not refer to the activity or refer only to the assignment or rank in the office.</p> <p>In the case of persons doing seasonal work, casual work, work for public and helping family members, it is not enough to write 'seasonal worker', 'casual worker', 'helping family member' but write in detail the activity done (e.g. sinking the garden, cleaning the road, cleaning, renovating the roof, stowage).</p> <p>In case of military corps of the Hungarian Army the note should be 'official soldier' or 'soldier with contract'. Hungary 2011: Persons 15+ who ever worked [discrepancies: type I: trace, type II: 1.3%] This variable indicates the present or last occupation of the person. 001 Commissioned armed forces officers 002 Non-commissioned armed forces officers and other ranks 011 Chief executives, senior officials and legislators 012 Administrative and commercial managers 013 Production and specialized services managers 014 Hospitality, retail and other services managers 021 Science and engineering professionals 022 Health professionals 023 Teaching professionals 024 Business and administration professionals 025 Information and communications technology professionals 026 Legal, social and cultural professionals 031 Science and engineering associate professionals 032 Health associate professionals 033 Business and administration associate professionals 034 Legal, social, cultural and related associate professionals 035 Information and communications technicians 041 General and keyboard clerks 042 Customer services clerks 043 Numerical and material recording clerks 044 Other clerical support workers 051 Personal service workers 052 Sales workers and street sales workers 053 Personal care workers 054 Protective services workers 061 Market-oriented skilled agricultural workers 062 Market-oriented skilled forestry, fishing and hunting workers 071 Building and related trades workers, excluding electricians 072 Metal, machinery and related trades workers 073 Handicraft and printing workers 074 Electrical and electronic trades workers 075 Food processing, wood working, garment and other craft and related trades workers 081 Stationary plant and machine operators 082 Assemblers 083 Drivers and mobile plant operators 091 Cleaners and helpers 092 Agricultural, forestry and fishery labourers 093 Labourers in mining, construction, manufacturing and transport 094 Food preparation assistants 096 Refuse workers and other elementary workers 998 Unknown 999 NIU (not in universe) Work: Occupation Variables -- PERSON Class of worker <span class="h1">Personal questionnaire</span></p> <p><span class="h2">IV. Occupation, workplace and transport</span></p> <p>28. What is (was) your status in employment?</p> <div class="i1">[] 1 Employee<br />[] 2 Sole proprietor, self-employed<br />[] 3 Working member of a company<br />[] 4 Working member of a co-operative<br />[] 5 Causal employee (working by special commission contract, casual workers, day workers)<br />[] 6 Employed in public works (doing work for public benefit, public purposes etc., employed in public employment)<br />[] 7 Helping family member</div> <span class="h2"> IV. Occupation, workplace and transport</span></p> <p><span class="em">28. What is (was) your status in employment?</span> <br />Employee is the person who is in labor relation with an employer generally based on working contract. This category includes civil servants, public functionaries, persons acting as judges or attorneys, as well as professional and contracted members of armed forces and public defense (their legal status being civil servant or public services worker).</p> <div class="i1"><span class="em">Sole proprietor, self-employed </span>is the person working alone or with some employees -- generally on the basis of a license of activity -- as sole proprietor (like artisans, retailers, farmers, free-lancers etc.), not as member of a joint undertaking.<br /><br /><span class="em">Working member of a company </span>is the person, who parallel to his/her partnership in possessing a non-co-operative venture, is obliged to contribute to the activity of the venture by personal activity, work.<br /><br /><span class="em">Working member of a co-operative </span>is the person who as a member of any kind of economic organization in co-operative form (e.g. consumption co-operative, agrarian co-operative) is obliged for work.<br /><br /><span class="em">Casual employee </span>(working by special commission contract, casual worker, day worker) is the person, who neither has a stable working contract, nor is an entrepreneur, though -- with, or without a special document -- is working, usually lasting for a short period of time (e.g. agricultural day-work, shoveling the snow, unskilled work in construction). The day-worker, based on an agreement with the employer, is working either for a negotiated period of time (one day, week etc.), or is performing a given job (digging of a piece of land, painting the fence etc.). Odd job performers are also the persons, who on the basis of an individual contract, not as entrepreneurs, perform an intellectual job (e.g. translation of a text, holding a lecture etc.).<br /><br /><span class="em">Employed in public works </span>(doing work for public benefit, public purposes etc., employed in public employment) is the person who is employed by the local government in public benefit work or public work program.<br /><br /><span class="em">Contributing family worker </span>is the participating family member who helps the sole proprietors, members of a company or members of a co-operative in their activity without pay, but receiving from the achievements of the enterprise or economic company as a member of the household.</div> Hungary 2011: Persons 15+ who ever worked [discrepancies: none] This variable indicates the class of worker. 1 Employee 2 Sole proprietor, self-employed 3 Working member of a company 4 Working member of a co-operative 5 Casual employee (working by special commission contract, casual worker, day worker) 6 Employed in public works (doing work for public benefit, public purposes etc., employed in public employment) 7 Helping family member 9 NIU (not in universe) Work Variables -- PERSON Industry <span class="h1">Personal questionnaire</span></p> <p><span class="h2">IV. Occupation, workplace and transport</span></p> <p>30. Name the typical activity of your employer or enterprise or description of the activity of your employer or enterprise (current or last employer): ________ <span class="h2"> IV. Occupation, workplace and transport</span></p> <p><span class="em">30. Name the typical activity of your employer or enterprise, OR description of the activity of your employer or enterprise (current or last employer):</span> <br />The company, enterprise (factory, unit, premises, shop, school, etc.) where the respondent actually works must be indicated as the employer. For those who are in employment relationship with a company hiring manpower must indicate the enterprise where he/she is actually working and not the agency as employer. Beside the name of the employer, the main activity has to be indicated by all means (e.g. Kontroll Kft, tax consultancy, Magveto Kiadó, book publisher, Lakópark Kft., building dwellings, József Attila Primary school, basic education). If the respondent does not want to give the name, he/she should provide detailed answers which enable to establish the activity, tasks of the enterprise (factor making preparatory work for printing office, manufactory producing food, book publishing, impatient service, private road goods transport). In case the firm has more activity, write the most typical one.</p> <p>In the employer is a private household, it is enough to write 'private household'. Hungary 2011: Persons 15+ who are working or unemployed [discrepancies: type I: 0.2%, type II: 0.5%] This variable indicates the industry (2-digit) of workers and unemployed persons. 001 Crop and animal production, hunting and related service activities 002 Forestry, logging, fishing, and aquaculture 005 Mining of coal, lignite, and metal ores, extraction of crude petroleum and natural gas 008 Other mining and quarrying 009 Mining support service activities 010 Manufacture of food products 011 Manufacture of beverages 012 Manufacture of tobacco products 013 Manufacture of textiles 014 Manufacture of wearing apparel 015 Manufacture of leather and related products 016 Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials 017 Manufacture of paper and paper products 018 Printing and reproduction of recorded media 019 Manufacture of coke and refined petroleum products 020 Manufacture of chemicals and chemical products 021 Manufacture of basic pharmaceutical products and pharmaceutical preparations 022 Manufacture of rubber and plastic products 023 Manufacture of other non-metallic mineral products 024 Manufacture of basic metals 025 Manufacture of fabricated metal products, except machinery and equipment 026 Manufacture of computer, electronic and optical products 027 Manufacture of electrical equipment 028 Manufacture of machinery and equipment, not elsewhere classified 029 Manufacture of motor vehicles, trailers and semi-trailers 030 Manufacture of other transport equipment 031 Manufacture of furniture 032 Other manufacturing 033 Repair and installation of machinery and equipment 035 Electricity, gas, steam and air conditioning supply 036 Water collection, treatment and supply 037 Sewerage 038 Waste collection, treatment and disposal activities; materials recovery 039 Remediation activities and other waste management services 041 Construction of buildings 042 Civil engineering 043 Specialised construction activities 045 Wholesale and retail trade and repair of motor vehicles and motorcycles 046 Wholesale trade, except of motor vehicles and motorcycles 047 Retail trade, except of motor vehicles and motorcycles 049 Land transport and transport via pipelines 050 Water transport 051 Air transport 052 Warehousing and support activities for transportation 053 Postal and courier activities 055 Accommodation 056 Food and beverage service activities 058 Publishing activities 059 Motion picture, video and television programme production, sound recording and music publishing activities 060 Programming and broadcasting activities 061 Telecommunications 062 Computer programming, consultancy and related activities 063 Information service activities 064 Financial service activities, except insurance and pension funding 065 Insurance, reinsurance and pension funding, except compulsory social security 066 Activities auxiliary to financial services and insurance activities 068 Real estate activities 069 Legal and accounting activities 070 Activities of head offices; management consultancy activities 071 Architectural and engineering activities; technical testing and analysis 072 Scientific research and development 073 Advertising and market research 074 Other professional, scientific and technical activities 075 Veterinary activities 077 Rental and leasing activities 078 Employment activities 079 Travel agency, tour operator and other reservation service and related activities 080 Security and investigation activities 081 Services to buildings and landscape activities 082 Office administrative, office support and other business support activities 084 Public administration and defence; compulsory social security 085 Education 086 Human health activities 087 Residential care activities 088 Social work activities without accommodation 090 Creative, arts and entertainment activities 091 Libraries, archives, museums and other cultural activities 092 Gambling and betting activities 093 Sports activities and amusement and recreation activities 094 Activities of membership organisations 095 Repair of computers and personal and household goods 096 Other personal service activities 097 Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use 099 Activities of extraterritorial organisations and bodies 998 Unknown 999 NIU (not in universe) Work: Industry Variables -- PERSON Number of subordinates or employees <span class="h1">Personal questionnaire</span></p> <p><span class="h2">IV. Occupation, workplace and transport</span></p> <p>29. Do you have employees?</p> <div class="i1">[] No<br />[] 1-2 person(s)<br />[] 3-9 person(s)<br />[] 10-19 person(s)<br />[] 20 or more person(s)</div> <span class="h2"> IV. Occupation, workplace and transport</span></p> <p><span class="em">29. Do you have employees?</span> <br />In the case of the first leaders of business organization, enterprises, budgetary authority, take into account not only the employee right under them but the whole staff belonging to the firm. Hungary 2011: Persons 15+ who are working or unemployed [discrepancies: type I: 0.3%, type II: 0.5%] This variable indicates how many persons worked in the place of employment. 0 No employees 1 1 to 9 2 10 to 19 3 20 or more 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Year of ending last job <span class="h1">Personal questionnaire</span></p> <p><span class="h2">IV. Occupation, workplace and transport</span></p> <p>26. When did you last work?</p> <div class="i1">[] Year_ _ _ _<br /> Month _ _<br />[] You have never worked [skip to question 31]</div> <span class="h2"> IV. Occupation, workplace and transport</span></p> <p><span class="em">26. When did you work last time?</span> <br /> Write the year and month when the respondent last had regular work. In case he/she does not remember exactly, please estimate at least the year. Work done in school holiday or occasional work should not be taken into account.</p> <p>In the case where the respondent had a job earlier sometime, filling the questions 27-30 depending on whether he/she is looking for a job.</p> <p>In the case he/she is looking for a job, questions 27-30 have to be answered regarding the last job. <br />In the case he/she is not looking for a job, write only the last job (question 27) and the last status in employment (question 28) and do not answer questions 29 and 30.</p> <p>For those respondents who have never worked before, leave questions 27-30 blank. Hungary 2011: Persons 15+ who are currently not working [discrepancies: none] This variable indicates the year of ending last job. 0000 Never worked 1949 1949 or earlier 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 9998 Unknown 9999 NIU (not in universe) Work Variables -- PERSON School attendance at present <span class="h1">Personal questionnaire</span></p> <p><span class="h2">II. Education attainment</span> <br /><span class="em">Take into account studies and qualifications only in formal education.</span></p> <p>17.1 Are you currently studying including infant nursery/kindergarten?</p> <div class="i1">[] 1 No [skip to question 18]<br />[] 2 Attend infant nursery [skip to question 21]<br />[] 3 Attend primary school [skip to question 21]<br />[] 4 Attend vocational school<br />[] 5 Attend secondary grammar school<br />[] 6 Attend secondary vocational school (including secondary vocational programs built on general certificate of education)<br />[] 7 Attend higher vocational programs<br />[] 8 Attend college- level or BA/BSc training<br />[] 9 Attend university- level or MA/MSc training or unified undivided training<br />[] 10 Attend college- or university level professional further training<br />[] 11 Attend PhD or DLA training</div> <span class="h2">II. Educational attainment</span></p> <p>Studies and qualifications obtained in formal education have to be taken into account in questions 17.1.--20</p> <p>Persons in formal education are in legal status with the school as pupils or students. Questions regarding school attendance must be answered only in case the respondent is in legal status with the school as pupil or student (question 17.1 must be answered also in case of attending infant nursery or kindergarten), completed educational attainment must be taken into account only if it had been obtained in formal education. Persons attending schools outside formal education (e.g. trainings) are not in legal status with the school, so these studies and certificates must not be counted.</p> <p><span class="em">17.1. Are you currently studying or attending school, including infant nursery/kindergarten? </span> <br /><span class="em">The question has to be answered irrespectively of the person's age.</span> In case the person goes to nursery or kindergarten please follow at question 21. In case a person attends more than one school the same time, the highest level has to be taken into account (the later one in the list). <span class="em">In case of answer no, please continue at question 18. </span> Hungary 2011: All persons This variable indicates if the person is currently attending school. 0 No 1 Yes Education Variables -- PERSON Region of residence Hungary 2011: All persons This variable indicates the person's region of residence. 1 Central Hungary 2 Transdanubia 3 Great Plains and Northern Hungary Migration: Global Variables -- PERSON Region of birth <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>6. Where was your address when born?_____</p> <div class="i1">Locality (town, village) or district in Budapest. In case of a foreign address the current name of the country</div> <span class="h2"> I. Demography</span></p> <p><span class="em">6. Where was your address when born?</span> <br />The address at birth can differ from the address of the place of registration (for most persons it differs). In case the person does not know the address at birth, then write the locality or district of Budapest of the registration.</p> <p>The person was born abroad in case the address at birth is over the current borders of Hungary. In such cases, write the name of the country (without the name of the locality). Hungary 2011: All persons This variable indicates the person's region of birth. 1 Central Hungary 2 Transdanubia 3 Great Plains and Northern Hungary 4 Abroad 5 Unknown Nativity and Birthplace Variables -- PERSON Living in the same place since birth <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>4.3 How long have you lived there?</p> <div class="i1">[] Since birth [go to question 7]<br />Year _ _ _ _<br />Month_ _</div> <span class="h2"> I. Demography</span></p> <p><span class="em">4.3. How long have you lived there?</span> <br />If the person lives on the address on the Dwelling Questionnaire since birth, the filling should be continued at question 7. In case the respondent does not remember exactly the time of moving to the dwelling, please estimate at least the year of moving. Hungary 2011: All persons This variable indicates whether the person lives in the same region since birth. 1 Yes 0 No Migration: Global Variables -- PERSON Year of move to current (usual) place of residence <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>4.3 How long have you lived there?</p> <div class="i1">[] Since birth [go to question 7]<br />Year _ _ _ _<br />Month_ _</div> <span class="h2"> I. Demography</span></p> <p><span class="em">4.3. How long have you lived there?</span> <br />If the person lives on the address on the Dwelling Questionnaire since birth, the filling should be continued at question 7. In case the respondent does not remember exactly the time of moving to the dwelling, please estimate at least the year of moving. Hungary 2011: Persons who ever moved [discrepancies: none] This variable indicates the year of move to current, usual place of residence. 1934 1934 or earlier 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 9998 Unknown 9999 NIU (not in universe) Migration: Global Variables -- PERSON Month of move to current, usual place of residence <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>9.2. When did you return or actually move to Hungary?</p> <div class="i1">Year _ _ _ _<br />Month _ _</div> <span class="h2"> I. Demography</span></p> <p><span class="em">9.2. When did you return or actually move to Hungary?</span> <br />In case the respondent does not remember exactly the date of moving to Hungary, please try to write at least the year. Hungary 2011: Persons who ever moved [discrepancies: type I: trace, type II: none] This variable indicates the month of move to current, usual place of residence. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 99 NIU (not in universe) Migration: Global Variables -- PERSON Year of current marriage <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>11. If you are married <br />[Questions 11.1 and 11.2 are asked of married persons]</p> <p>11.1. Date of current marriage</p> <div class="i1">Year_ _ _ _<br />Month_ _</div> Hungary 2011: Persons currently married [discrepancies: type I: trace, type II: trace} This variable indicates the person's year of current marriage. 1942 1942 or earlier 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 9998 Unknown 9999 NIU (not in universe) Demographic Variables -- PERSON Month of current marriage <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>11. If you are married <br />[Questions 11.1 and 11.2 are asked of married persons]</p> <p>11.1. Date of current marriage</p> <div class="i1">Year_ _ _ _<br />Month_ _</div> Hungary 2011: Persons currently married [discrepancies: type I: trace, type II: trace} This variable indicates the person's month of current marriage. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Married person living together with his or her spouse <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>11. If you are married <br />[Questions 11.1 and 11.2 are asked of married persons]</p> <p>11.2 Do you live with your spouse?</p> <div class="i1">[] Yes [go to question 13]<br />[] No</div> <span class="h2"> I. Demography</span></p> <p><span class="em">11.2. Do you live with your spouse?</span> <br />Answer yes must be marked even if the person is not living in the same dwelling with his/her spouse but the marital community is maintained. Answer no must be marked if the marital community is broken irrespective of living in the same dwelling or not.</p> <p>For person who is married and lives with his/her spouse together, continue the questionnaire at question 13. Hungary 2011: Persons currently married [discrepancies: type I: trace, type II: trace] This variable indicates whether the married person lives together with his or her spouse. 0 No 1 Yes 8 Unknown 9 NIU (not in universe) Demographic Variables -- PERSON Year of the beginning of current cohabiting partnership <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>[Questions 12.1 and 12.2 are asked of persons in a cohabiting partnership] <br />12. Do you have a cohabiting partner?</p> <div class="i1">[] No [go to question 13]</div><p>12.1 Yes, beginning of the cohabiting partnership</p> <div class="i1">[] Year_ _ _ _ Month_ _</div> <span class="h2"> I. Demography</span></p> <p><span class="em">12.1. Beginning of the cohabiting partnership</span> <br />In case of registered cohabiting partners the beginning of the cohabiting partnership is not the date of the registration, but the real beginning of the partnership. The same has to be used in case at other cohabiting partners. Hungary 2011: Persons who have a cohabiting partnership [discrepancies: type I: trace, type II: trace] This variable indicates the person's year of the beginning of current cohabiting partnership. 1969 1969 or earlier 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 9998 Unknown 9999 NIU (not in universe) Demographic Variables -- PERSON Month of the beginning of current cohabiting partnership <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>[Questions 12.1 and 12.2 are asked of persons in a cohabiting partnership] <br />12. Do you have a cohabiting partner?</p> <div class="i1">[] No [go to question 13]</div><p>12.1 Yes, beginning of the cohabiting partnership</p> <div class="i1">[] Year_ _ _ _ Month_ _</div> <span class="h2"> I. Demography</span></p> <p><span class="em">12.1. Beginning of the cohabiting partnership</span> <br />In case of registered cohabiting partners the beginning of the cohabiting partnership is not the date of the registration, but the real beginning of the partnership. The same has to be used in case at other cohabiting partners. Hungary 2011: Persons who have a cohabiting partnership [discrepancies: type I none; type II trace] This variable indicates the person's month of the beginning of current cohabiting partnership. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Living in the same dwelling as his or her cohabiting partner <span class="h1">Personal questionnaire</span></p> <p><span class="h2">I. Demography</span></p> <p>[Questions 12.1 and 12.2 are asked of persons in a cohabiting partnership] <br />12. Do you have a cohabiting partner?</p> <div class="i1">[] No [go to question 13]</div><p>12.2 Do you live in the same dwelling as your cohabiting partner?</p> <div class="i1">[] Yes<br />[] No</div> Hungary 2011: Persons who have a cohabiting partnership [discrepancies: type I none; type II trace] This variable indicates whether the person lives in the same dwelling as his/her cohabiting partner. 0 No 1 Yes 8 Unknown 9 NIU (not in universe) Demographic Variables -- PERSON