Danish Census 1845 DDI_DNK_1845_PHC_v01_M_v7.6_A_IPUMS IPUMS

Integrated Public Use Microdata Series (IPUMS) International

IPUMS April 2, 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. Danish Census 1845 - IPUMS Subset PHC dk1845a (IPUMS Harmonized Subset) DNK_1845_PHC_v01_M_v7.6_A_IPUMS Commission for the Collection of Statistical Tables IPUMS (c) Copyright 1845, Commission for the Collection of Statistical Tables and Minnesota Population Center Commission for the Collection of Statistical Tables 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. Geography: A-E Variables -- HOUSEHOLD Demographic Variables -- PERSON Technical Household Variables -- HOUSEHOLD Constructed Family Interrelationship Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Work Variables -- PERSON Technical Person Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Other Person Variables -- PERSON Nativity and Birthplace Variables -- PERSON Work: Occupation Variables -- PERSON February 1, 1845 Denmark Parish Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: Yes - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: No - Households: Yes - Group quarters: Yes All persons present at the time of the census and temporarily absent "natives" Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Denmark 1845 (100%) MICRODATA SOURCE: Commission for the Collection of Statistical Tables SAMPLE SIZE (person records): 1351098. SAMPLE DESIGN: Not applicable Face-to-face [f2f] De jure, CENSUS DAY: February 1, 1845 Not applicable 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. Commission for the Collection of Statistical Tables 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: Denmark, Commission for the Collection of Statistical Tables. Danish Census 1845 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 dk1845a, 2025 DNK1845_PHC-H-H.dat Household records 252,089 ascii Minnesota Population Center Version 7.5, IPUMS sample DNK1845_PHC-P-H.dat Person records 1351098 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 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 Number of unrelated persons UNREL indicates the number of persons in the household who are unrelated to the head as defined in the variable RELATE. 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ Group Quarters Variables -- HOUSEHOLD Urban-rural status URBAN indicates whether the household was located in a place designated as urban or as rural. 1 Rural 2 Urban 9 Unknown Geography: Global 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 Denmark, Region 1787 - 1885 GEO1_DK1787_1885 identifies the household's region for all the samples in Denmark. Regions are the largest geographical unit available from the 1787 to 1885 Denmark datasets. Other year-specific variables identifying regions include GEO1_DK1787, GEO1_DK1801, GEO1_DK1845, GEO1_DK1880, and GEO1_DK1885. Other geography variables for Denmark include administrative units as ADMINDK, counties identified in COUNTYDK, districts as DISTDK, parishes in 1787, 1801, and 1845 as PARISHDK1, and parishes in 1880 and 1885 as PARISHDK2. GEO1_DK1787_1885 is not mappable. 208001 Sjælland 208002 Andre øer 208003 Østjylland 208004 Nordjylland 208005 Vestjylland 208006 Sønderjylland 208007 Unknown Geography: A-E Variables -- HOUSEHOLD Denmark, Region 1845 GEO1_DK1845 identifies the household's region within Denmark in 1845. Regions are the largest geographical unit available in 1845 Denmark. Other variables include harmonized regions GEO1_DK1787_1885. The year-specific variables identifying regions include, GEO1_DK1787, GEO1_DK1801, and GEO1_DK1880, and GEO1_DK1885. Other geography variables for Denmark include administrative units as ADMINDK, counties identified in COUNTYDK, districts as DISTDK, parishes in 1787, 1801, and 1845 as PARISHDK1, and parishes in 1880 and 1885 as PARISHDK2. GEO1_DK1845 is not mappable. 1 Sjælland 2 Andre øer 3 Østjylland 4 Nordjylland 5 Vestjylland 6 Sønderjylland Geography: A-E Variables -- HOUSEHOLD Denmark, County COUNTYDK reports the county in Denmark where the household was located. Counties are larger than DISTDK (districts) and smaller than regions identified in GEO1_DK1787_1885. Other geography variables for Denmark include administrative units as ADMINDK, regions identified in variable GEO1_DK1787_1885, districts as DISTDK, parishes in 1787, 1801, and 1845 as PARISHDK1, and parishes in 1880 and 1885 as PARISHDK2. COUNTYDK is not mappable. 22 Aabenraa 23 Aalborg 24 Aarhus 25 Bornholm 27 Frederiksborg 29 Haderslev 30 Hjørring 31 Holbæk 32 København 34 Maribo 35 Odense 36 Præstø 37 Randers 38 Ribe 39 Ringkøbing 40 Roskilde 41 Skanderborg 42 Sorø 43 Svendborg 45 Thisted 46 Tønder 47 Vejle 48 Viborg 99 Unknown Geography: A-E Variables -- HOUSEHOLD Denmark, District of enumeration DISTDK reports the district in Denmark where the household was located. Districts are larger than PARISHDK1 and PARISHDK2 (parishes) and smaller than COUNTYDK (counties) in all Denmark samples. Other geography variables for Denmark include administrative units as ADMINDK, regions identified in variable GEO1_DK1787_1885, counties identified in COUNTYDK, parishes in 1787, 1801, and 1845 as PARISHDK1, and parishes in 1880 and 1885 as PARISHDK2. DISTDK is not mappable. 103 Aars 104 Aasum 107 Alsted 109 Anst 110 Ars 111 Baag 112 Baarse 114 Bjerge 115 Bjerre 116 Bjæverskov 117 Brusk 118 Bølling 119 Børglum 120 Djurs Nørre 121 Djurs Sønder 122 Dronninglund 123 Elbo 124 Fakse 125 Falsters Nørre 126 Falsters Sønder 127 Fjends 128 Fleskum 129 Framlev 132 Frøs 133 Fuglse 135 Galten 136 Ginding 137 Gislum 138 Gjerlev 139 Gjern 141 Gudme 142 Gørding 144 Hads 145 Hammer 146 Hammerum 147 Harre 148 Hasle 149 Hassing 150 Hatting 151 Hellum 152 Hids 153 Hillerslev 154 Hind 155 Hindborg 156 Hindsted 157 Hjelmslev 158 Hjerm 159 Holbo 160 Holmans 161 Horns [Sjælland Region] 162 Horns [Nordjylland Region] 163 Hornum 164 Houlbjerg 165 Hundborg 166 Hvetbo 167 Hviding 168 Jerlev 174 Kær 175 Langelands Nørre 176 Langelands Sønder 177 Lollands Nørre 178 Lollands Sønder 179 Lunde 181 Lynge-Frederiksborg 182 Lynge-Kronborg 183 Lysgaard 184 Læsø 185 Løve 186 Malt 187 Merløse 188 Middelsom 189 Mols 190 Morsø Nørre 191 Morsø Sønder 192 Musse 193 Mønbo 195 Nim 196 Ning 198 Nørhald 199 Nørlyng 200 Nørre [Andre øer Region] 201 Nørre [Vestjylland Region] 202 Nørre Horne 203 Nørre Rangstrup 204 Nørre Tyrstrup 205 Nørvang 206 Odense 207 Ods 208 Onsild 209 Ramsø 210 Refs 211 Ribe 212 Rinds 213 Ringsted 214 Rise 215 Rougsø 216 Rødding 217 Sabro 218 Sallinge 219 Samsø 220 Skam 221 Skast 222 Skippinge 223 Skodborg 224 Skovby 225 Slagelse 226 Slavs 227 Slet 229 Smørum 230 Sokkelund 231 Stevns 232 Strø 233 Støvring 234 Sunds 235 Sømme 236 Sønder 239 Sønderhald 240 Sønderlyng 241 Tune 242 Tuse 243 Tybjerg 244 Tyrsting 245 Tønder 246 Tørrild 247 Ulfborg 249 Vandfuld 250 Vends 251 Vennebjerg 252 Vester 253 Vester Flakkebjerg 254 Vester Han 255 Vester Horne 256 Vester Lisbjerg 257 Vindinge 258 Voer 259 Voldborg 260 Vrads 261 Ærø 262 Ølstykke 263 Øster 264 Øster Flakkebjerg 265 Øster Han 266 Øster Horne 267 Øster Lisbjerg 300 København (Staden) 999 Unknown Geography: A-E Variables -- HOUSEHOLD Civil parish/street, Denmark 1787-1845 PARISHDK1 reports the parish or quarter in Denmark where the household was located in the 1787 to 1845 samples. Parishes are the lowest levels of geography found in all Denmark samples. Other geography variables for Denmark include administrative units as ADMINDK, regions identified in variable GEO1_DK1787_1885, counties identified in COUNTYDK, districts as DISTDK, and parishes in 1880 and 1885 as PARISHDK2. PARISHDK1 is not mappable. 10002 Slotsholmen 10005 Sankt Hans Landsogn 10009 Vester Brønderslev 10113 Brønshøj 10194 Sankt Hans Hospital 10201 Hof & Militæretaten 10202 Øster Kvarter 10203 Vester Kvarter 10204 Udenbys Vester Kvarter 10205 Udenbys Klædebo Kvarter 10206 Strand Kvarter 10208 Snarens Kvarter 10209 Sankt Annæ Øster Kvarter 10210 Sankt Annæ Vester Kvarter 10211 Rosenborg Kvarter 10212 Nørre Kvarter 10213 Købmager Kvarter 10214 Klædebo Kvarter 10215 Christianshavn Kvart 10216 Frimand Kvarter 11503 Fole (Kongerigsk) 11546 Ødis (Kongerisk) 11548 København, parish unknown 11557 Gram (Kongerigsk) 11559 Hjerting (Kongerigsk 11561 Lintrup (Kongerigsk) 11563 Rødding (Kongerigsk) 11567 Sønder Hygum (Kongerigsk) 11570 Toftlund (Kongerigsk) 11571 Farup (Kongerigsk) 11573 Hjortlund (Kongerigsk) 11575 Kalvslund (Kongerigsk) 11577 Ribe Domkirke Landsogn (Kongerigsk) 11579 Seem (Kongerigsk) 11583 Vester Vedsted (Kongerigsk) 11587 Abild (Kongerigsk) 11589 Arrild (Kongerigsk) 11591 Brede (Kongerigsk) 11593 Brøns (Kongerigsk) 11595 Daler (Kongerigsk) 11597 Døstrup (Kongerigsk) 11599 Emmerlev (Kongerigsk) 11601 Hjerpsted (Kongerigsk) 11603 Hviding (Kongerigsk) 11609 Mjolden (Kongerigsk) 11611 Møgeltønder (Kongerigsk) 11613 Randerup (Kongerigsk) 11615 Rejsby (Kongerigsk) 11617 Roager (Kongerigsk) 11621 Skærbæk (Kongerigsk) 11623 Spandet (Kongerigsk) 11625 Sønder Skast (Kongerigsk) 11626 Visby (Kongerigsk) 11628 Vodder (Kongerigsk) 11653 Skælskør Landdistrikt 11729 Søetatens Laboratorium (Christianshavn) 11637 Baadsmandsstrædes Kaserne 12219 Ribe Sankt Katharinæ landsogn 12224 List Bye 12293 Tønder Mejerholm Kancelligods 12841 Nørresundby Landsogn 13677 Brarup 14702 Frederiksberg 15101 Ballerup 15102 Maaløv 15302 Brøndbyvester 15303 Brøndbyøster 15502 Store Magleby 15702 Gentofte 15903 Gladsakse 16101 Glostrup 16301 Herlev 16501 Herstedvester 16502 Herstedøster 16702 Hvidovre 16901 Fløng 16903 Høje Taastrup 16904 Reerslev 16906 Sengeløse 17101 Ledøje 17102 Smørum 17303 Lyngby 17504 Rødovre 18104 Søllerød 18301 Ishøj 18302 Torslunde 18504 Taarnby 18701 Vallensbæk 18901 Værløse 20101 Blovstrød 20102 Lillerød 20103 Lynge 20104 Uggeløse 20501 Birkerød 20701 Farum 20801 Asminderød 20802 Grønholt 20804 Fredensborg Slot 20901 Frederikssund 20902 Græse 20904 Oppesundby 20905 Sigerslevvester 20906 Snostrup 20991 Frederikssund 21102 Kregme 21103 Melby 21104 Vinderød 21105 Ølsted 21301 Blistrup 21302 Esbønderup 21303 Gilleleje 21304 Græsted 21305 Søborg 21501 Annisse 21502 Helsinge 21503 Maarum 21504 Ramløse 21505 Tibirke 21506 Valby 21507 Vejby 21702 Hellebæk 21708 Tikøb 21791 Helsingør Købstad 21901 Alsønderup 21902 Frederiksborg Slot 21904 Nødebo 21905 Nørre Herlev 21907 Tjæreby 21991 Hillerød Købstad 22101 Torup 22301 Hørsholm 22501 Draaby 22502 Gerlev 22503 Krogstrup 22504 Kyndby 22701 Karlebo 22901 Ferslev 22902 Selsø 22903 Skibby 22904 Skuldelev 22905 Vellerup 23101 Gørløse 23102 Lille Lyngby 23103 Skævinge 23104 Strø 23301 Slangerup 23302 Uvelse 23303 Slangerup Købstad 23304 Slangerup Landdistrikt 23501 Ganløse 23502 Slagslunde 23503 Stenløse 23504 Veksø 23701 Jørlunde 23702 Ølstykke 25101 Gershøj 25102 Hyllinge 25103 Lyndby 25104 Rye 25105 Sonnerup 25106 Sæby 25301 Greve 25302 Karlslunde 25304 Kildebrønde 25306 Tune 25501 Gundsømagle 25502 Hvedstrup 25503 Jyllinge 25504 Kirkerup 25505 Aagerup 25701 Hvalsø 25702 Kisserup 25703 Særløse 25704 Saaby 25902 Herfølge 25903 Højelse 25905 Lellinge 25906 Sædder 25907 Ølsemagle 25908 Køge Landdistrikt 25991 Køge Købstad 26101 Allerslev 26102 Gevninge 26103 Glim 26104 Herslev 26105 Kornerup 26106 Osted 26107 Rorup 26301 Daastrup 26302 Gadstrup 26303 Snoldelev 26304 Syv 26305 Ørsted 26501 Himmelev 26502 Roskilde Domsogn 26505 Sankt Jørgensbjerg 26506 Svogerslev 26507 Vindinge 26508 Vor Frue 26509 Roskilde Udenbys Jurisdiktion 26510 Roskilde Adelige Jomfrukloster 26591 Roskilde Købstad 26701 Bjæverskov 26702 Borup 26703 Ejby 26704 Gørslev 26705 Kimmerslev 26706 Lidemark 26707 Nørre Dalby 26708 Vollerslev 26901 Havdrup 26902 Jersie 26903 Karlstrup 26904 Skensved 26905 Solrød 27101 Endeslev 27102 Himlingøje 27103 Haarlev 27104 Strøby 27105 Taarnby 27106 Valløby 27107 Varpelev 27108 Vraaby 30101 Avnsø 30102 Bjergsted 30103 Bregninge 30104 Føllenslev 30105 Sejerø 30106 Særslev 30107 Viskinge 30301 Niløse 30302 Ruds Vedby 30303 Skellebjerg 30304 Tersløse 30501 Asnæs 30502 Faarevejle 30503 Grevinge 30504 Hørve 30505 Vallekilde 30701 Fuglebjerg 30702 Fyrendal 30703 Førslev 30704 Gunderslev 30705 Haldagerlille 30706 Haarslev 30707 Krummerup 30708 Kvislemark 30709 Ting Jellinge 30710 Tystrup 30901 Bakkendrup 30902 Drøsselbjerg 30903 Gørlev 30904 Kirke Helsinge 30905 Svallerup 31101 Flakkebjerg 31102 Faardrup 31103 Gerlev 31104 Gimlinge 31105 Hyllested 31106 Høve 31107 Kirkerup 31108 Lundforlund 31109 Skørpinge 31110 Slots Bjergby 31111 Sludstrup 31112 Sørbymagle 31301 Braaby 31302 Freerslev 31303 Haslev 31304 Teestrup 31305 Terslev 31306 Øde Førslev 31501 Butterup 31502 Grandløse 31503 Hagested 31504 Hørby 31505 Orø 31507 Sønder Asmindrup 31508 Tuse 31509 Tveje Merløse 31510 Udby 31511 Aagerup 31591 Holbæk Købstad 31701 Jorløse 31702 Lille Fuglede 31703 Rørby 31704 Store Fuglede 31705 Ubby 31706 Værslev 31902 Finderup 31903 Gierslev 31904 Hallenslev 31905 Reerslev 31906 Solbjerg 31907 Sæby 31908 Ørslev 32101 Kvanløse 32102 Nørre Jernløse 32103 Sønder Jernløse 32104 Søndersted 32105 Søstrup 32106 Undløse 32303 Raklev 32304 Røsnæs 32305 Tømmerup 32306 Aarby 32307 Kalundborg Landdistrikt 32391 Kalundborg Købstad 32502 Hemmeshøj 32504 Taarnborg 32505 Vemmelev 32591 Korsør Købstad 32702 Rørvig 32791 Nykøbing Sjælland Købstad 32901 Allindemagle 32902 Benløse 32903 Bringstrup 32904 Farendløse 32905 Gyrstinge 32906 Haraldsted 32907 Høm 32908 Jystrup 32909 Kværkeby 32910 Nordrupøster 32912 Sigersted 32913 Sneslev 32914 Valsølille 32915 Vetterslev 32916 Vigersted 32917 Ørslev 32991 Ringsted Købstad 33101 Agersø 33102 Boeslunde 33103 Eggeslevmagle 33104 Holsteinborg 33105 Magleby 33106 Omø 33108 Sønder Bjerge 33109 Tjæreby 33110 Venslev 33111 Ørslev 33191 Skælskør Købstad 33301 Gudum 33302 Havrebjerg 33303 Hejninge 33304 Kindertofte 33305 Nordrupvester 33307 Ottestrup 33310 Sorterup 33311 Stillinge 33312 Sønderup 33391 Slagelse Købstad 33501 Alsted 33502 Bjernede 33503 Bromme 33504 Fjenneslev 33505 Lynge 33506 Pedersborg 33507 Slaglille 33509 Vester Broby 33510 Sorø Landdistrikt 33591 Sorø Købstad 33701 Flinterup 33702 Munke Bjergby 33703 Stenlille 33704 Stenmagle 33901 Gislinge 33902 Hjembæk 33903 Kundby 33904 Svinninge 34101 Frydendal 34102 Holmstrup 34103 Jyderup 34104 Mørkøv 34105 Skamstrup 34106 Stigs Bjergby 34301 Egebjerg 34302 Højby 34303 Nørre Asmindrup 34304 Odden 34305 Vig 34501 Eskilstrup 34502 Soderup 34503 Store Taastrup 34504 Tølløse 34505 Ugerløse 35101 Alslev 35102 Fakse 35104 Karise 35105 Roholte 35106 Smerup 35107 Spjellerup 35108 Vemmetofte 35301 Everdrup 35302 Hammer 35303 Mogenstrup 35304 Næstelsø 35305 Snesere 35306 Vester Egesborg 35501 Bursø 35502 Errindlev 35503 Fuglse 35504 Holeby 35505 Krønge 35506 Olstrup 35507 Torslunde 35701 Fensmark 35702 Holme Olstrup 35703 Toksværd 35901 Avnede 35902 Gurreby 35903 Halsted 35904 Landet 35905 Ryde 35906 Skovlænge 35907 Søllested 35908 Vesterborg 36101 Kalvehave 36102 Mern 36104 Øster Egesborg 36301 Askø 36302 Bandholm 36303 Hillested 36304 Hunseby 36306 Stokkemarke 36307 Østofte 36391 Maribo Købstad 36501 Bogø 36502 Borre 36503 Damsholte 36504 Elmelunde 36505 Fanefjord 36506 Keldby 36507 Magleby 36508 Nyord 36591 Stege Købstad 36701 Branderslev 36704 Nakskov Landsogn 36791 Nakskov Købstad 36902 Systofte 36903 Tingsted 36904 Toreby 36905 Nykøbing Falster Landdistrikt 36991 Nykøbing Falster Købstad 37101 Bregninge 37102 Døllefjelde 37103 Godsted 37104 Herritslev 37105 Kettinge 37106 Musse 37109 Vester Ulslev 37110 Øster Ulslev 37191 Nysted Købstad 37301 Fodby 37302 Herlufsholm 37303 Hyllinge 37304 Karrebæk 37305 Marvede 37306 Rislev 37307 Rønnebæk 37309 Sankt Mortens 37310 Sankt Peders 37311 Vallensved 37312 Vejlø 37391 Næstved Købstad 37501 Brarup 37502 Eskilstrup 37503 Gundslev 37504 Kippinge 37505 Lillebrænde 37506 Nørre Alslev 37507 Nørre Kirkeby 37508 Nørre Vedby 37509 Stadager 37510 Torkilstrup 37511 Vaalse 37512 Ønslev 37701 Allerslev 37702 Beldringe 37703 Baarse 37704 Jungshoved 37706 Skibinge 37791 Præstø Købstad 37901 Birket 37902 Fejø 37903 Femø 37904 Herredskirke 37905 Horslunde 37906 Købelev 37907 Løjtofte 37908 Nordlunde 37909 Sandby 37910 Utterslev 37911 Vindeby 38101 Arninge 38102 Dannemare 38103 Gloslunde 38104 Græshave 38105 Kappel 38106 Tillitse 38107 Vestenskov 38301 Nebbelunde 38302 Ringsebølle 38305 Skørringe 38306 Sædinge 38307 Tirsted 38308 Taagerup 38309 Vejleby 38391 Rødby Købstad 38501 Kongsted 38502 Sønder Dalby 38503 Tureby 38504 Ulse 38505 Vester Egede 38506 Øster Egede 38701 Engestofte 38702 Fjelde 38703 Majbølle 38704 Radsted 38706 Slemminge 38707 Taars 38708 Vigsnæs 38709 Vaabensted 38791 Sakskøbing Købstad 38901 Frøslev 38902 Havnelev 38903 Hellested 38904 Holtug 38905 Højerup 38906 Lille Heddinge 38907 Lyderslev 38908 Magleby Stevns 38991 Store Heddinge Købstad 39101 Falkerslev 39102 Horbelev 39103 Horreby 39104 Karleby 39105 Maglebrænde 39106 Nørre Ørslev 39108 Sønder Alslev 39109 Sønder Kirkeby 39110 Aastrup 39191 Stubbekøbing Købstad 39301 Aversi 39302 Bavelse 39303 Glumsø 39304 Herlufmagle 39305 Næsby 39306 Sandby 39307 Skelby 39308 Tybjerg 39309 Tyvelse 39310 Vrangstrup 39501 Gedesby 39502 Idestrup 39503 Skelby 39504 Væggerløse 39701 Kastrup 39702 Køng 39703 Lundby 39704 Sværdborg 39705 Udby 39707 Ørslev 39708 Vordingborg Landsogn 39791 Vordingborg Købstad 40102 Gudhjem 40103 Olsker 40104 Rø 40105 Østerlarsker 40106 Østermarie 40107 Allinge Landsogn 40108 Sandvig Købstad 40191 Allinge-Sandvig Købstæder 40302 Klemensker 40303 Nyker 40304 Rutsker 40391 Hasle Købstad 40501 Bodilsker 40502 Ibsker 40504 Povlsker 40591 Neksø Købstad 40592 Svaneke Købstad 40701 Knudsker 40791 Rønne Købstad 40901 Nylarsker 40902 Pedersker 40903 Vestermarie 40904 Aaker 40991 Aakirkeby Købstad 41101 Christiansø 42102 Barløse 42103 Baagø 42104 Gamtofte 42105 Helnæs 42106 Holevad 42107 Kærum 42108 Sandager 42109 Søby 42110 Sønderby 42111 Turup 42191 Assens Købstad 42302 Grindløse 42303 Guldbjerg 42304 Klinte 42305 Nørre Sandager 42306 Ore 42307 Skovby 42391 Bogense Købstad 42501 Allested 42502 Nørre Broby 42503 Sandholts Lyndelse 42504 Sønder Broby 42505 Vejle 42506 Vester Hæsinge 42701 Hundstrup 42702 Kirkeby 42703 Lunde 42704 Ollerup 42705 Stenstrup 42706 Ulbølle 42707 Vester Skerninge 42708 Øster Skerninge 42901 Balslev 42902 Brenderup 42903 Ejby 42904 Fjelsted 42905 Gelsted 42906 Harndrup 42907 Husby 42908 Ingslev 42909 Tanderup 42910 Ørslev 43101 Avernakø 43102 Brahetrolleborg 43103 Diernæs 43105 Horne 43106 Haastrup 43107 Lyø 43108 Svanninge 43109 Vester Aaby 43110 Øster Hæsinge 43111 Aastrup 43191 Faaborg Købstad 43301 Flemløse 43302 Køng 43303 Søllested 43304 Vedtofte 43305 Ørsted 43501 Brudager 43502 Gudbjerg 43503 Gudme 43504 Hesselager 43505 Oure 43506 Vejstrup 43701 Dreslette 43702 Haarby 43703 Jordløse 43901 Dalby 43902 Drigstrup 43904 Kølstrup 43905 Mesinge 43906 Revninge 43907 Rynkeby 43908 Stubberup 43909 Viby 43991 Kerteminde Købstad 44101 Birkende 44102 Marslev 44103 Rønninge 44302 Marstal Handelsplads 44501 Gamborg 44502 Kavslunde 44505 Vejlby 44591 Middelfart Købstad 44701 Munkebo 44901 Avnslev 44902 Bovense 44904 Vindinge 44991 Nyborg Købstad 45101 Asperup 45102 Føns 45103 Nørre Aaby 45104 Rorslev 45105 Udby 46101 Agedrup 46102 Allerup 46103 Allesø 46105 Bellinge 46107 Brændekilde 46108 Dalum 46109 Davinde 46111 Fangel 46112 Fraugde 46116 Højby 46118 Korup 46119 Lumby 46122 Næsbyhoved Broby 46123 Paarup 46124 Sanderum 46126 Sankt Knuds 46127 Seden 46128 Stenløse 46130 Ubberud 46132 Vor Frue 46133 Aasum 46191 Odense Købstad 47101 Bederslev 47102 Hjadstrup 47103 Krogsbølle 47104 Lunde 47105 Norup 47106 Nørre Højrup 47107 Nørre Næraa 47108 Otterup 47109 Skeby 47110 Uggerslev 47111 Østrup 47301 Espe 47302 Gestelev 47303 Heden 47304 Hellerup 47305 Herringe 47306 Hillerslev 47307 Krarup 47308 Ringe 47309 Søllinge 47310 Sønder Højrup 47311 Vantinge 47501 Fuglsbølle 47502 Longelse 47504 Simmerbølle 47505 Skrøbelev 47506 Strynø 47591 Rudkøbing Købstad 47701 Gislev 47702 Kværndrup 47703 Ryslinge 47901 Bjerreby 47902 Bregninge (Taasinge) 47903 Drejø 47904 Egense 47906 Landet 47907 Sankt Jørgens 47909 Skaarup 47910 Sørup 47911 Thurø 47912 Tved 47991 Svendborg Købstad 48101 Fodslette 48102 Humble 48103 Lindelse 48104 Magleby 48105 Tryggelev 48301 Ejlby 48302 Haarslev 48303 Melby 48304 Skamby 48305 Særslev 48306 Søndersø 48307 Veflinge 48308 Vigerslev 48502 Brylle 48503 Tommerup 48504 Verninge 48701 Bøstrup 48703 Snøde 48704 Stoense 48705 Tranekær 48706 Tullebølle 48901 Ellinge 48902 Flødstrup 48903 Skellerup 48904 Ullerslev 49101 Vissenbjerg 49301 Bregninge (Ærø) 49302 Rise 49303 Søby 49304 Tranderup 49501 Ellested 49502 Frørup 49503 Herrested 49504 Kullerup 49505 Langaa 49506 Refsvindinge 49507 Svindinge 49508 Øksendrup 49509 Ørbæk 49701 Nørre Lyndelse 49702 Nørre Søby 49703 Rolsted 49704 Sønder Næraa 49705 Aarslev 49901 Kerte 49902 Orte 49903 Rørup 49904 Skydebjerg 50501 Ballum 50906 Hejls 50909 Taps 50911 Vejstrup 51101 Fole 51102 Gram 51103 Højrup 52507 Toftlund 52701 Hjerting 52703 Lintrup 52704 Rødding 52707 Sønder Hygum 53101 Brøns 53104 Rejsby 53105 Rømø 54502 Løjt 55101 Grene 55102 Vorbasse 55301 Henne 55302 Kvong 55303 Lunde 55304 Lydum 55305 Lønne 55306 Nørre Nebel 55307 Ovtrup 55501 Ho 55502 Oksby 55503 Aal 55701 Bramming 55702 Darum 55703 Gørding 55704 Hunderup 55705 Vejrup 55706 Vester Nykirke 55901 Brørup 55902 Folding 55903 Lindknud 56101 Bryndum 56104 Guldager 56106 Hostrup 56107 Jerne 56109 Skast 56110 Sneum 56112 Tjæreborg 56114 Vester Nebel 56301 Nordby 56302 Sønderho 56502 Grindsted 56503 Hejnsvig 56505 Sønder Omme 56701 Faaborg 56702 Grimstrup 56703 Næsbjerg 56704 Vester Starup 56705 Øse 56706 Aarre 56901 Føvling 56902 Holsted 56903 Aastrup 57101 Farup 57102 Hjortlund 57103 Hviding 57104 Jernved 57105 Kalvslund 57106 Mandø 57109 Roager 57111 Seem 57113 Vester Vedsted 57114 Vilslev 57191 Ribe Købstad 57301 Alslev 57302 Billum 57303 Horne 57304 Janderup 57305 Torstrup 57307 Varde Landsogn 57391 Varde Købstad 57501 Andst 57503 Bække 57504 Gesten 57505 Læborg 57506 Malt 57507 Veerst 57508 Vejen 57701 Ansager 57702 Hodde 57704 Strellev 57705 Tistrup 57706 Ølgod 60101 Føvling 60102 Grædstrup 60103 Nim 60104 Ring 60105 Sønder Vissing 60106 Træden 60107 Tyrsting 60108 Tønning 60109 Underup 60110 Voerladegaard 60301 Gauerslund 60302 Gaarslev 60303 Skærup 60304 Smidstrup 60501 Bredsten 60502 Egtved 60503 Jerlev 60504 Nørup 60505 Randbøl 60506 Vester Nebel 60507 Ødsted 60508 Øster Starup 60701 Bredstrup 60703 Erritsø 60705 Herslev 60706 Pjedsted 60708 Taulov 60710 Vejlby 60711 Kongsted 60791 Fredericia Købstad 60901 Gangsted 60902 Kattrup 60903 Søvind 60904 Tolstrup 60905 Vedslet 60906 Yding 60907 Ørridslev 60908 Østbirk 61101 Gadbjerg 61102 Give 61103 Givskud 61104 Lindeballe 61105 Ringive 61106 Thyregod 61107 Vester 61108 Øster Nykirke 61301 Daugaard 61302 Hedensted 61303 Korning 61304 Løsning 61305 Store Dalby 61306 Urlev 61307 Ølsted 61308 Ørum 61309 Øster Snede 61501 Endelave 61502 Hansted 61503 Hatting 61505 Lundum 61506 Nebel 61508 Tamdrup 61509 Torsted 61510 Tyrsted 61511 Uth 61513 Vær 61591 Horsens Købstad 61701 Hvejsel 61702 Jelling 61703 Kollerup 61704 Vindelev 61901 As 61902 Barrit 61903 Bjerre 61904 Glud 61905 Hjarnø 61906 Hornum 61908 Klakring 61909 Nebsager 61910 Raarup 61911 Skjold 61912 Stenderup 61913 Stouby 61914 Vrigsted 62101 Almind 62104 Eltang 62105 Harte 62107 Nørre Bjert 62108 Nørre Bramdrup 62110 Seest 62112 Sønder Bjert 62113 Sønder Stenderup 62114 Sønder Vilstrup 62115 Viuf 62116 Vonsild 62117 Kolding Landdistrikt 62191 Kolding Købstad 62301 Jordrup 62302 Lejrskov 62303 Skanderup 62501 Ejstrup 62502 Klovborg 62503 Nørre Snede 62701 Grejs 62702 Hammer 62703 Hornborg 62704 Hvirring 62705 Langskov 62706 Linnerup 62707 Sindbjerg 62708 Tørring 62709 Uldum 62710 Aale 62901 Hjarup 62902 Vamdrup 62903 Ødis 63102 Engum 63103 Hornstrup 63104 Hover 63105 Højen 63110 Skibet 63111 Vinding 63113 Vejle Landdistrikt 63191 Vejle Købstad 65101 Avlum 65103 Haderup 65104 Hodsager 65302 Brande 65501 Egvad 65502 Hemmet 65503 Hoven 65504 Lyne 65505 Lønborg 65506 Nørre Bork 65507 Sønder Bork 65508 Sønder Vium 65510 Aadum 65701 Arnborg 65703 Gjellerup 65707 Herning 65711 Rind 65714 Sinding 65715 Snejbjerg 65717 Sunds 65718 Tjørring 65719 Ørre 65901 Gammelsogn 65903 Nysogn 66101 Borbjerg 66103 Idom 66105 Mejrup 66106 Maabjerg 66107 Navr 66108 Nørre Felding 66110 Raasted 66111 Sir 66112 Tvis 66191 Holstebro Købstad 66301 Bording 66303 Ikast 66501 Bøvling 66502 Dybe 66503 Fabjerg 66504 Ferring 66505 Fjaltring 66506 Flynder 66507 Gudum 66508 Heldum 66509 Hove 66510 Hygum 66512 Lomborg 66513 Møborg 66514 Nees 66515 Nørlem 66516 Nørre Nissum 66517 Ramme 66518 Rom 66519 Trans 66520 Tørring 66521 Vandborg 66591 Lemvig Købstad 66701 Hee 66702 Hover 66703 No 66704 Rindum 66706 Stadil 66707 Sønder Lem 66708 Tim 66709 Torsted 66710 Vedersø 66711 Velling 66712 Ølstrup 66713 Holmsland Klit 66791 Ringkøbing Købstad 66901 Bølling 66902 Dejbjerg 66903 Faster 66904 Hanning 66905 Skjern 66906 Stavning 66907 Sædding 66908 Sønder Borris 67101 Asp 67102 Fovsing 67103 Gimsing 67104 Hjerm 67105 Humlum 67106 Resen 67108 Vejrum 67109 Venø 67110 Ølby 67301 Engbjerg 67302 Harboør 67501 Hvidbjerg 67502 Jegindø 67503 Lyngs 67504 Odby 67505 Søndbjerg 67701 Nørre Omme 67702 Nøvling 67703 Timring 67704 Vildbjerg 67705 Vind 67706 Vinding 67901 Bur 67902 Gørding 67903 Husby 67904 Madum 67905 Staby 67906 Sønder Nissum 67907 Ulfborg 67908 Vemb 68101 Brejning 68103 Nørre Vium 68106 Vorgod 68301 Ejsing 68302 Handbjerg 68303 Ryde 68304 Sahl 68305 Sevel 68501 Assing 68503 Skarrild 68504 Sønder Felding 70101 Agri 70102 Draaby 70104 Egens 70105 Fuglslev 70106 Helgenæs 70107 Hyllested 70108 Knebel 70109 Rolsø 70110 Rosmus 70111 Tirstrup 70112 Tved 70113 Vistoft 70191 Ebeltoft Købstad 70301 Galten (Sønder) 70302 Sjelle 70303 Skivholme 70304 Skovby 70305 Skørring 70306 Stjær 70307 Storring 70501 Dallerup 70502 Gjern 70503 Skannerup 70504 Skorup 70505 Svostrup 70506 Tvilum 70701 Albøge 70702 Anholt 70703 Enslev 70705 Hammelev 70706 Hoed 70707 Homaa 70708 Lyngby 70709 Vejlby 70710 Aalsø 70791 Grenaa Købstad 70901 Hadbjerg 70902 Hadsten 70903 Lerbjerg 70904 Lyngaa 70905 Nørre Galten 70907 Rud 70908 Vissing 70909 Voldum 70910 Ødum 71101 Hammel 71102 Haurum 71103 Lading 71104 Røgen 71105 Sall 71106 Skjød 71107 Sporup 71108 Søby 71109 Voldby 71301 Foldby 71302 Grundfør 71303 Haldum 71304 Søften 71305 Vitten 71501 Adslev 71502 Blegind 71503 Hørning 71504 Mesing 71505 Veng 71701 Granslev 71702 Grensten 71703 Helstrup 71704 Houlbjerg 71705 Langaa 71706 Laurbjerg 71707 Torup 71708 Værum 71709 Ørum 71710 Øster Velling 71901 Falslev 71902 Hem 71903 Kastbjerg 71905 Sem 71906 Svenstrup 71907 Udbyneder 71908 Vester Tørslev 71909 Vindblæs 71991 Mariager Købstad 72101 Ebdrup 72102 Koed 72103 Kolind 72104 Marie Magdalene 72105 Nimtofte 72106 Nødager 72107 Skarresø 72108 Tøstrup 72301 Albæk 72302 Dalbyneder 72303 Dalbyover 72304 Enslev 72305 Gjerlev 72306 Hald 72307 Harridslev 72308 Kærby 72309 Linde 72310 Mellerup 72311 Raaby 72312 Støvring 72313 Sødring 72314 Tvede 72315 Øster Tørslev 72501 Fjellerup 72502 Ginnerup 72503 Gjerrild 72504 Glesborg 72505 Hemmed 72506 Karlby 72507 Kastbjerg 72508 Rimsø 72509 Veggerslev 72510 Villersø 72511 Voldby 72512 Ørum (Djurs) 72701 Alrø 72702 Bjerager 72703 Falling 72704 Gosmer 72705 Gylling 72706 Halling 72707 Hundslund 72708 Nølev 72709 Odder 72710 Randlev 72711 Saksild 72712 Torrild 72713 Tunø 72714 Ørting 72901 Asferg 72902 Faarup 72903 Gassum 72904 Kousted 72905 Læsten 72906 Nørbæk 72907 Spentrup 72908 Sønderbæk 72909 Øster Bjerregrav 72910 Aalum 73101 Borup 73102 Dronningborg 73103 Gimming 73104 Haslund 73105 Hornbæk 73106 Kristrup 73107 Lem 73108 Raasted 73113 Taanum 73114 Vorup 73115 Ølst 73116 Dronningborg Slot 73191 Randers Købstad 73301 Halling 73302 Hornslet 73303 Hvilsager 73304 Krogsbæk 73305 Lime 73306 Mygind 73307 Mørke 73308 Skader 73309 Skørring 73310 Søby 73501 Estruplund 73502 Gjesing 73503 Holbæk 73504 Nørager 73505 Udby 73506 Vejlby 73507 Vivild 73508 Voer 73509 Ørsted 73701 Alling 73702 Dover 73703 Gammel Rye 73704 Laasby 73706 Tulstrup 73901 Bregnet 73902 Feldballe 73903 Thorsager 74101 Besser 74102 Kolby 74103 Nordby 74104 Onsbjerg 74105 Tranebjerg 74106 Kyholm 74302 Balle 74303 Funder 74304 Gødvad 74305 Kragelund 74306 Lemming 74307 Linaa 74309 Sejling 74311 Serup 74313 Sinding 74501 Fruering 74502 Hylke 74503 Ovsted 74505 Skanderup 74506 Stilling 74507 Taaning 74508 Vitved 74591 Skanderborg Købstad 74701 Auning 74702 Essenbæk 74703 Fausing 74704 Hørning 74705 Vester Alling 74706 Virring 74707 Øster Alling 74708 Aarslev 74901 Bryrup 74902 Them 74903 Vinding 74904 Vrads 75101 Astrup 75102 Beder 75103 Borum 75104 Brabrand 75106 Egaa 75107 Elev 75109 Elsted 75110 Framlev 75112 Faarup 75114 Harlev 75115 Hasle 75117 Hjortshøj 75118 Holme 75119 Hvilsted 75120 Kasted 75121 Kolt 75123 Lisbjerg 75124 Lyngby 75126 Malling 75127 Mejlby 75129 Maarslet 75130 Ormslev 75133 Sabro 75138 Skejby 75141 Skødstrup 75143 Spørring 75144 Sønder Aarslev 75145 Tilst 75146 Tiset 75147 Todbjerg 75148 Tranbjerg 75149 Trige 75150 Tulstrup 75151 Vejlby 75152 Viby 75154 Ølsted 75155 Aaby 75191 Aarhus Købstad 76101 Bjerring 76103 Elsborg 76104 Gullev 76105 Hjermind 76106 Hjorthede 76107 Høbjerg 76108 Lee 76109 Mammen 76110 Sahl 76111 Skjern 76112 Vindum 76301 Daugbjerg 76302 Feldingbjerg 76303 Fly 76304 Gammelstrup 76305 Kobberup 76306 Mønsted 76307 Nørre Borris 76308 Resen 76309 Smollerup 76310 Vridsted 76311 Vroue 76501 Hansted 76502 Hjardemaal 76504 Lild 76505 Ræhr 76506 Tømmerby 76507 Vigsø 76701 Aidt 76702 Gerning 76703 Hvorslev 76704 Sønder Vinge 76705 Thorsø 76707 Vejerslev 76708 Vellev 76709 Vester Velling 76901 Frederiks 76902 Karup 77101 Grønbæk 77102 Hinge 77103 Hørup 77104 Levring 77105 Sjørslev 77106 Thorning 77107 Vinderslev 77108 Vium 77301 Alsted 77302 Bjergby 77303 Blidstrup 77304 Dragstrup 77305 Ejerslev 77306 Elsø 77307 Erslev 77308 Flade 77309 Frøslev 77310 Galtrup 77311 Hvidbjerg 77312 Jørsby 77313 Karby 77314 Ljørslev 77315 Lødderup 77316 Mollerup 77318 Ovtrup 77319 Rakkeby 77320 Redsted 77321 Sejerslev 77322 Skallerup 77323 Solbjerg 77324 Sundby 77325 Sønder Draaby 77326 Tæbring 77327 Tødsø 77328 Vejerslev 77329 Vester Assels 77330 Ørding 77331 Øster Assels 77332 Øster Jølby 77333 Nykøbing Mors Landdistrikt 77391 Nykøbing Mors Købstad 77501 Hersom 77502 Klejtrup 77503 Lynderup 77504 Laastrup 77505 Roum 77506 Skals 77507 Ulbjerg 77508 Vester Bjerregrav 77509 Vester Tostrup 77701 Durup 77703 Harre 77704 Hjerk 77705 Nautrup 77706 Roslev 77707 Rybjerg 77708 Sæby 77709 Tøndering 77710 Vile 77901 Dommerby 77902 Dølby 77904 Estvad 77905 Hem 77906 Hindborg 77907 Højslev 77908 Lundø 77909 Resen 77910 Rønbjerg 77912 Ørslevkloster 77913 Ørum 77991 Skive Købstad 78101 Balling 78102 Brøndum 78103 Hvidbjerg 78104 Haasum 78105 Krejbjerg 78106 Lem 78107 Lihme 78108 Oddense 78109 Otting 78110 Ramsing 78111 Rødding 78112 Vejby 78113 Volling 78301 Fur 78302 Grinderslev 78303 Grønning 78304 Jebjerg 78305 Junget 78306 Lyby 78307 Selde 78308 Thise 78309 Torum 78310 Aasted 78501 Agger 78502 Bedsted 78503 Boddum 78504 Gettrup 78505 Grurup 78506 Hassing 78507 Helligsø 78508 Heltborg 78509 Hurup 78510 Hvidbjerg Vesten Aa 78511 Hørdum 78512 Lodbjerg 78513 Skyum 78514 Vestervig 78515 Villerslev 78516 Visby 78517 Ydby 78518 Ørum 78701 Arup 78702 Harring 78703 Hillerslev 78704 Hundborg 78705 Hunstrup 78706 Hørsted 78707 Jannerup 78708 Kallerup 78709 Kaastrup 78710 Nors 78711 Nørhaa 78712 Sennels 78713 Sjørring 78714 Skinnerup 78715 Skjoldborg 78716 Snedsted 78717 Stagstrup 78718 Sønderhaa 78720 Tilsted 78721 Torsted 78722 Tved 78723 Vang 78724 Vesløs 78725 Vester Vandet 78727 Øsløs 78728 Øster Vandet 78729 Østerild 78730 Torup 78791 Thisted Købstad 78901 Bigum 78902 Hammershøj 78903 Kvorning 78904 Lindum 78905 Løvel 78906 Nørre Vinge 78907 Pederstrup 78908 Rødding 78909 Tjele 78910 Vammen 78911 Vejrum 78912 Viskum 78913 Vorning 78914 Ørum 79101 Almind 79102 Asmild 79103 Dollerup 79104 Finderup 79105 Fiskbæk 79106 Kvols 79107 Lysgaard 79108 Ravnstrup 79109 Romlund 79110 Sønder Rind 79113 Tapdrup 79114 Taarup 79117 Vinkel 79118 Vorde 79191 Viborg Købstad 79301 Fjeldsø 79302 Gedsted 79303 Hvam 79304 Hvilsom 79305 Simested 79306 Testrup 79307 Vester Bølle 79308 Øster Bølle 80101 Astrup 80102 Ove 80103 Rold 80104 Rostrup 80105 Store Arden 80106 Valsgaard 80107 Vebbestrup 80301 Brovst 80302 Lerup 80303 Torslev 80304 Tranum 80305 Øland 80306 Øster Svenstrup 80502 Hallund 80503 Hellum 80504 Jerslev 80505 Serritslev 80506 Stenum 80507 Tise 80508 Tolstrup 80509 Øster Brønderslev 80702 Dronninglund 80703 Hellevad 80705 Voer 80706 Ørum 80901 Alstrup 80902 Farsø 80903 Flejsborg 80904 Fovlum 80905 Hyllebjerg 80906 Lovns 80907 Strandby 80909 Ullits 80910 Vester Hornum 81101 Bejstrup 81102 Gøttrup 81103 Haverslev 81104 Hjortdal 81105 Kettrup 81106 Klim 81107 Kollerup 81108 Skræm 81109 Vester Torup 81110 Vust 81303 Elling 81304 Flade 81306 Gærum 81307 Hirsholmene 81308 Skærum 81309 Aasted 81310 Frederikshavn Landdistrikt 81311 Fladstrand 81391 Frederikshavn 81501 Als 81503 Skelund 81504 Visborg 81505 Vive 81701 Hals 81702 Ulsted 81703 Vester Hassing 81704 Øster Hassing 81901 Asdal 81902 Bindslev 81904 Horne 81905 Tornby 81906 Tversted 81907 Uggerby 81908 Vidstrup 82102 Bjergby 82104 Hæstrup 82105 Mygdal 82106 Maarup 82107 Sankt Hans 82108 Sankt Olai 82109 Skallerup 82110 Taars 82111 Vennebjerg 82112 Vrejlev 82191 Hjørring Købstad 82301 Døstrup 82302 Glenstrup 82304 Hvornum 82305 Hørby 82306 Nørre Onsild 82307 Skjellerup 82308 Snæbum 82309 Sønder Onsild 82310 Øls 82391 Hobro Købstad 82501 Byrum 82502 Hals 82503 Vesterø 82701 Aggersborg 82702 Kornum 82703 Løgsted 82704 Løgstør 82705 Malle 82706 Næsborg 82707 Oudrup 82710 Skarp Salling 82711 Vilsted 82712 Vindblæs 82713 Bjørnsholm 82901 Børglum 82902 Em 82903 Furreby 82904 Harritslev 82905 Jelstrup 82906 Lyngby 82907 Rakkeby 82908 Rubjerg 82909 Sejlstrup 82910 Vejby 82911 Vrensted 82912 Vraa 83101 Bislev 83102 Ejdrup 83103 Farstrup 83104 Lundby 83106 Sebber 83107 Store Ajstrup 83108 Vokslev 83191 Nibe Købstad 83301 Binderup 83302 Brorstrup 83303 Durup 83304 Grynderup 83305 Haverslev 83306 Kongens Tisted 83307 Ravnkilde 83308 Rørbæk 83309 Stenild 83501 Alstrup 83502 Hune 83503 Ingstrup 83504 Jetsmark 83505 Saltum 83506 Vester Hjermitslev 83701 Gudum 83702 Komdrup 83703 Lillevorde 83704 Mou 83705 Nørre Kongerslev 83706 Sejlflod 83707 Storvorde 83708 Sønder Kongerslev 83901 Astrup 83902 Hørmested 83903 Lendum 83904 Mosbjerg 83905 Sindal 83906 Tolne 83907 Ugilt 84101 Raabjerg 84191 Skagen Købstad 84301 Blenstrup 84302 Bælum 84303 Fræer 84304 Gerding 84305 Lyngby 84306 Siem 84307 Skibsted 84308 Skørping 84309 Solbjerg 84310 Store Brøndum 84311 Torup 84501 Buderup 84502 Gravlev 84503 Suldrup 84504 Sønderup 84505 Veggerby 84506 Øster Hornum 84507 Aarestrup 84701 Albæk 84702 Hørby 84703 Karup 84704 Skæve 84706 Torslev 84707 Understed 84708 Volstrup 84791 Sæby Købstad 84901 Biersted 84902 Gjøl 84904 Aaby 84905 Aaby 85101 Ajstrup 85104 Dall 85105 Ellidshøj 85106 Ferslev 85107 Frejlev 85109 Gunderup 85110 Hammer 85113 Horsens 85114 Hvorup 85115 Klarup 85118 Nørholm 85119 Nørre Tranders 85121 Nøvling 85122 Romdrup 85125 Sulsted 85126 Svenstrup 85127 Sønder Tranders 85128 Sønderholm 85129 Vadum 85133 Volsted 85136 Store Restrup 85137 Budolfi Landsogn 85191 Nørresundby Købstad 85192 Aalborg Købstad 86101 Blære 86102 Gislum 86103 Giver 86104 Gundersted 86105 Havbro 86106 Skivum 86107 Ulstrup 86108 Vognsild 86109 Aars 86302 Ebeltoft Landsogn 86303 Faaborg Landdistrikt 86307 Mariager Landsogn 86308 Maribo Landdistrikt 86310 Middelfart Landdistrikt 86312 Nyborg Landsogn 86313 Nysted Landsogn 86314 Præstø Landdistrikt 86315 Ribe Landsogn 86316 Ringsted Landsogn 86317 Sakskøbing Landdistrikt 86318 Sankt Mikkels Landsogn 86319 Sankt Peders Landsogn 86320 Skagen Landsogn 86321 Skive Landsogn 86322 Stege Landdistrikt 86323 Store Heddinge Landsogn 86324 Thisted Landsogn 86326 Ude Sundby Landdistrikt 86327 Viborg Graabrødre Landsogn 86328 Aalborg Frue Landsogn 86501 Gammelsogn 86502 Sankt Ibs 86503 Ullerup 86505 Vallø Stiftsmenighed 86506 Aageby 92001 Sankt Clemens 92002 Sankt Laurentii 99999 Unknown Geography: A-E Variables -- HOUSEHOLD Denmark, Administrative unit ADMINDK reports the type of administrative unit in Denmark where the household was located. Other geography variables for Denmark include regions identified in variable GEO1_DK1787_1885, counties identified in COUNTYDK, districts as DISTDK, parishes in 1787, 1801, and 1845 as PARISHDK1, and parishes in 1880 and 1885 as PARISHDK2. ADMINDK is not mappable. 1 Street 5 Parish 6 Part of parish 7 Quarter 8 Royal borough 9 Unknown Geography: A-E 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 Denmark 1845: All records This variable indicates the dwelling number. This is a 6-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Number of persons in household Denmark 1845: All records This variable indicates the number of persons in the household. 0001 1 0002 2 0003 3 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 0073 73 0074 74 0082 82 0085 85 0089 89 0091 91 0094 94 0095 95 0098 98 0100 100 0104 104 0106 106 0122 122 0123 123 0128 128 0129 129 0133 133 0145 145 0153 153 0161 161 0164 164 0234 234 0267 267 0318 318 0402 402 0434 434 0455 455 0592 592 1419 1419 Technical Household Variables -- HOUSEHOLD Year of census Year:</p> <div class="i1">The year of the census.</div> Denmark 1845: All households This variable indicates the year of the census. 1845 1845 Technical Household Variables -- HOUSEHOLD Name of locality within census unit (string) Place name:</p> <div class="i1">Name of locality within the specific census unit.</div> Denmark 1845: All households This variable indicates the name of the locality within the census unit. This is a 96-digit numeric variable with 0 implied decimal places Geography: A-E Variables -- HOUSEHOLD Address (string) Name of village or place with specification of farms, houses, etc. ____ Title:</p> <div class="i1">Additional information on the address.</div> Denmark 1845: All households This variable indicates the household's address. This is a 80-digit numeric variable with 0 implied decimal places Geography: A-E Variables -- HOUSEHOLD Number of families in farm or house Number of families in each farm and every house ____ Families in house:</p> <div class="i1">Number of families in each farm or house.</div> Denmark 1845: All households This variable indicates the number of families in farm or house. 000 No families 001 1 family 002 2 families 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100 101 101 102 102 103 103 104 104 105 105 106 106 107 107 108 108 109 109 110 110 111 111 112 112 113 113 114 114 115 115 116 116 117 117 118 118 119 119 120 120 121 121 122 122 123 123 124 124 125 125 126 126 127 127 128 128 129 129 130 130 131 131 132 132 133 133 134 134 135 135 136 136 137 137 138 138 139 139 140 140 141 141 142 142 143 143 144 144 145 145 146 146 147 147 148 148 149 149 150 150 151 151 152 152 153 153 154 154 155 155 156 156 157 157 158 158 159 159 160 160 161 161 162 162 163 163 164 164 165 165 166 166 167 167 168 168 169 169 170 170 171 171 172 172 173 173 174 174 175 175 176 176 177 177 178 178 179 179 180 180 181 181 182 182 183 183 184 184 185 185 186 186 187 187 188 188 189 189 190 190 191 191 192 192 193 193 194 194 195 195 196 196 197 197 198 198 199 199 200 200 201 201 202 202 203 203 204 204 205 205 206 206 207 207 208 208 209 209 210 210 211 211 212 212 213 213 214 214 215 215 216 216 217 217 218 218 219 219 220 220 221 221 222 222 223 223 224 224 999 Unknown Constructed Household Variables -- HOUSEHOLD Parish Name of village or place with specification of farms, houses, etc. ____ Geographic code:</p> <div class="i1">Geographical reference. Refers to the tables 'administrative types, parish, counties, districts and regions.'</div><p>Geographic code:</p> <div class="i1">The same as the geographic code in the census.</div> Denmark 1845: All households This variable indicates the parish where the household is located. 10002 Slotsholmen 10005 Sankt Hans Landsogn 10009 Vester Brønderslev 10113 Brønshøj 10202 Øster Kvarter 10203 Vester Kvarter 10204 Udenbys Vester Kvarter 10205 Udenbys Klædebo Kvarter 10206 Strand Kvarter 10208 Snarens Kvarter 10209 Sankt Annæ Øster Kvarter 10210 Sankt Annæ Vester Kvarter 10211 Rosenborg Kvarter 10212 Nørre Kvarter 10213 Købmager Kvarter 10214 Klædebo Kvarter 10215 Christianshavn Kvarter 10216 Frimand Kvarter 11546 Ødis (Kongerisk) 11548 København, parish unknown 11571 Farup (Kongerigsk) 11583 Vester Vedsted (Kongerigsk) 11587 Abild (Kongerigsk) 11589 Arrild (Kongerigsk) 11591 Brede (Kongerigsk) 11595 Daler (Kongerigsk) 11597 Døstrup (Kongerigsk) 11599 Emmerlev (Kongerigsk) 11601 Hjerpsted (Kongerigsk) 11609 Mjolden (Kongerigsk) 11611 Møgeltønder (Kongerigsk) 11613 Randerup (Kongerigsk) 11625 Sønder Skast (Kongerigsk) 11626 Visby (Kongerigsk) 11637 Baadsmandsstrædes Kaserne 11653 Skælskør Landdistrikt 11729 Søetatens Laboratorium (Christianshavn) 12219 Ribe Sankt Katharinæ landsogn 12224 List Bye 12293 Tønder Mejerholm Kancelligods 12841 Nørresundby Landsogn 13677 Brarup 14702 Frederiksberg 15101 Ballerup 15102 Maaløv 15302 Brøndbyvester 15303 Brøndbyøster 15502 Store Magleby 15702 Gentofte 15903 Gladsakse 16101 Glostrup 16301 Herlev 16501 Herstedvester 16502 Herstedøster 16702 Hvidovre 16901 Fløng 16903 Høje Taastrup 16904 Reerslev 16906 Sengeløse 17101 Ledøje 17102 Smørum 17303 Lyngby 17504 Rødovre 18104 Søllerød 18301 Ishøj 18302 Torslunde 18504 Taarnby 18701 Vallensbæk 18901 Værløse 20101 Blovstrød 20102 Lillerød 20103 Lynge 20104 Uggeløse 20501 Birkerød 20701 Farum 20801 Asminderød 20802 Grønholt 20804 Fredensborg Slot 20902 Græse 20904 Oppesundby 20905 Sigerslevvester 20906 Snostrup 20991 Frederikssund 21102 Kregme 21103 Melby 21104 Vinderød 21105 Ølsted 21301 Blistrup 21302 Esbønderup 21303 Gilleleje 21304 Græsted 21305 Søborg 21501 Annisse 21502 Helsinge 21503 Maarum 21504 Ramløse 21505 Tibirke 21506 Valby 21507 Vejby 21702 Hellebæk 21708 Tikøb 21791 Helsingør Købstad 21901 Alsønderup 21902 Frederiksborg Slot 21904 Nødebo 21905 Nørre Herlev 21907 Tjæreby 21991 Hillerød Købstad 22101 Torup 22301 Hørsholm 22501 Draaby 22502 Gerlev 22503 Krogstrup 22504 Kyndby 22701 Karlebo 22901 Ferslev 22902 Selsø 22903 Skibby 22904 Skuldelev 22905 Vellerup 23101 Gørløse 23102 Lille Lyngby 23103 Skævinge 23104 Strø 23301 Slangerup 23302 Uvelse 23501 Ganløse 23502 Slagslunde 23503 Stenløse 23504 Veksø 23701 Jørlunde 23702 Ølstykke 25101 Gershøj 25102 Hyllinge 25103 Lyndby 25104 Rye 25105 Sonnerup 25106 Sæby 25301 Greve 25302 Karlslunde 25304 Kildebrønde 25306 Tune 25501 Gundsømagle 25502 Hvedstrup 25503 Jyllinge 25504 Kirkerup 25505 Aagerup 25701 Hvalsø 25702 Kisserup 25703 Særløse 25704 Saaby 25902 Herfølge 25903 Højelse 25905 Lellinge 25906 Sædder 25907 Ølsemagle 25908 Køge Landdistrikt 25991 Køge Købstad 26101 Allerslev 26102 Gevninge 26103 Glim 26104 Herslev 26105 Kornerup 26106 Osted 26107 Rorup 26301 Daastrup 26302 Gadstrup 26303 Snoldelev 26304 Syv 26305 Ørsted 26501 Himmelev 26505 Sankt Jørgensbjerg 26506 Svogerslev 26507 Vindinge 26508 Vor Frue 26591 Roskilde Købstad 26701 Bjæverskov 26702 Borup 26703 Ejby 26704 Gørslev 26705 Kimmerslev 26706 Lidemark 26707 Nørre Dalby 26708 Vollerslev 26901 Havdrup 26902 Jersie 26903 Karlstrup 26904 Skensved 26905 Solrød 27101 Endeslev 27102 Himlingøje 27103 Haarlev 27104 Strøby 27105 Taarnby 27106 Valløby 27107 Varpelev 27108 Vraaby 30101 Avnsø 30102 Bjergsted 30103 Bregninge 30104 Føllenslev 30105 Sejerø 30106 Særslev 30107 Viskinge 30301 Niløse 30302 Ruds Vedby 30303 Skellebjerg 30304 Tersløse 30501 Asnæs 30502 Faarevejle 30503 Grevinge 30504 Hørve 30505 Vallekilde 30701 Fuglebjerg 30702 Fyrendal 30703 Førslev 30704 Gunderslev 30705 Haldagerlille 30706 Haarslev 30707 Krummerup 30708 Kvislemark 30709 Ting Jellinge 30710 Tystrup 30901 Bakkendrup 30902 Drøsselbjerg 30903 Gørlev 30904 Kirke Helsinge 30905 Svallerup 31101 Flakkebjerg 31102 Faardrup 31103 Gerlev 31104 Gimlinge 31105 Hyllested 31106 Høve 31107 Kirkerup 31108 Lundforlund 31109 Skørpinge 31110 Slots Bjergby 31111 Sludstrup 31112 Sørbymagle 31301 Braaby 31302 Freerslev 31303 Haslev 31304 Teestrup 31305 Terslev 31306 Øde Førslev 31501 Butterup 31502 Grandløse 31503 Hagested 31504 Hørby 31505 Orø 31507 Sønder Asmindrup 31508 Tuse 31509 Tveje Merløse 31510 Udby 31511 Aagerup 31591 Holbæk Købstad 31701 Jorløse 31702 Lille Fuglede 31703 Rørby 31704 Store Fuglede 31705 Ubby 31706 Værslev 31902 Finderup 31903 Gierslev 31904 Hallenslev 31905 Reerslev 31906 Solbjerg 31907 Sæby 31908 Ørslev 32101 Kvanløse 32102 Nørre Jernløse 32103 Sønder Jernløse 32104 Søndersted 32105 Søstrup 32106 Undløse 32303 Raklev 32304 Røsnæs 32305 Tømmerup 32306 Aarby 32307 Kalundborg Landdistrikt 32391 Kalundborg Købstad 32502 Hemmeshøj 32504 Taarnborg 32505 Vemmelev 32591 Korsør Købstad 32702 Rørvig 32791 Nykøbing Sjælland Købstad 32901 Allindemagle 32902 Benløse 32903 Bringstrup 32904 Farendløse 32905 Gyrstinge 32906 Haraldsted 32907 Høm 32908 Jystrup 32909 Kværkeby 32910 Nordrupøster 32912 Sigersted 32913 Sneslev 32914 Valsølille 32915 Vetterslev 32916 Vigersted 32917 Ørslev 32991 Ringsted Købstad 33101 Agersø 33102 Boeslunde 33103 Eggeslevmagle 33104 Holsteinborg 33105 Magleby 33106 Omø 33108 Sønder Bjerge 33109 Tjæreby 33110 Venslev 33111 Ørslev 33191 Skælskør Købstad 33301 Gudum 33302 Havrebjerg 33303 Hejninge 33304 Kindertofte 33305 Nordrupvester 33307 Ottestrup 33310 Sorterup 33311 Stillinge 33312 Sønderup 33391 Slagelse Købstad 33501 Alsted 33502 Bjernede 33503 Bromme 33504 Fjenneslev 33505 Lynge 33506 Pedersborg 33507 Slaglille 33509 Vester Broby 33510 Sorø Landdistrikt 33591 Sorø Købstad 33701 Flinterup 33702 Munke Bjergby 33703 Stenlille 33704 Stenmagle 33901 Gislinge 33902 Hjembæk 33903 Kundby 33904 Svinninge 34101 Frydendal 34102 Holmstrup 34103 Jyderup 34104 Mørkøv 34105 Skamstrup 34106 Stigs Bjergby 34301 Egebjerg 34302 Højby 34303 Nørre Asmindrup 34304 Odden 34305 Vig 34501 Eskilstrup 34502 Soderup 34503 Store Taastrup 34504 Tølløse 34505 Ugerløse 35101 Alslev 35102 Fakse 35104 Karise 35105 Roholte 35106 Smerup 35107 Spjellerup 35108 Vemmetofte 35301 Everdrup 35302 Hammer 35303 Mogenstrup 35304 Næstelsø 35305 Snesere 35306 Vester Egesborg 35501 Bursø 35502 Errindlev 35503 Fuglse 35504 Holeby 35505 Krønge 35506 Olstrup 35507 Torslunde 35701 Fensmark 35702 Holme Olstrup 35703 Toksværd 35901 Avnede 35902 Gurreby 35903 Halsted 35904 Landet 35905 Ryde 35906 Skovlænge 35907 Søllested 35908 Vesterborg 36101 Kalvehave 36102 Mern 36104 Øster Egesborg 36301 Askø 36303 Hillested 36304 Hunseby 36306 Stokkemarke 36307 Østofte 36391 Maribo Købstad 36501 Bogø 36502 Borre 36503 Damsholte 36504 Elmelunde 36505 Fanefjord 36506 Keldby 36507 Magleby 36591 Stege Købstad 36701 Branderslev 36704 Nakskov Landsogn 36791 Nakskov Købstad 36902 Systofte 36903 Tingsted 36904 Toreby 36905 Nykøbing Falster Landdistrikt 36991 Nykøbing Falster Købstad 37101 Bregninge 37102 Døllefjelde 37103 Godsted 37104 Herritslev 37105 Kettinge 37106 Musse 37109 Vester Ulslev 37110 Øster Ulslev 37191 Nysted Købstad 37301 Fodby 37302 Herlufsholm 37303 Hyllinge 37304 Karrebæk 37305 Marvede 37306 Rislev 37307 Rønnebæk 37309 Sankt Mortens 37310 Sankt Peders 37311 Vallensved 37312 Vejlø 37391 Næstved Købstad 37502 Eskilstrup 37503 Gundslev 37504 Kippinge 37505 Lillebrænde 37506 Nørre Alslev 37507 Nørre Kirkeby 37508 Nørre Vedby 37509 Stadager 37510 Torkilstrup 37511 Vaalse 37512 Ønslev 37701 Allerslev 37702 Beldringe 37703 Baarse 37704 Jungshoved 37706 Skibinge 37791 Præstø Købstad 37901 Birket 37902 Fejø 37903 Femø 37904 Herredskirke 37905 Horslunde 37906 Købelev 37907 Løjtofte 37908 Nordlunde 37909 Sandby 37910 Utterslev 37911 Vindeby 38101 Arninge 38102 Dannemare 38103 Gloslunde 38104 Græshave 38105 Kappel 38106 Tillitse 38107 Vestenskov 38301 Nebbelunde 38302 Ringsebølle 38305 Skørringe 38306 Sædinge 38307 Tirsted 38308 Taagerup 38309 Vejleby 38391 Rødby Købstad 38501 Kongsted 38502 Sønder Dalby 38503 Tureby 38504 Ulse 38505 Vester Egede 38506 Øster Egede 38701 Engestofte 38702 Fjelde 38703 Majbølle 38704 Radsted 38706 Slemminge 38707 Taars 38708 Vigsnæs 38709 Vaabensted 38791 Sakskøbing Købstad 38901 Frøslev 38902 Havnelev 38903 Hellested 38904 Holtug 38905 Højerup 38906 Lille Heddinge 38907 Lyderslev 38908 Magleby Stevns 38991 Store Heddinge Købstad 39101 Falkerslev 39102 Horbelev 39103 Horreby 39104 Karleby 39105 Maglebrænde 39106 Nørre Ørslev 39108 Sønder Alslev 39109 Sønder Kirkeby 39110 Aastrup 39191 Stubbekøbing Købstad 39301 Aversi 39302 Bavelse 39303 Glumsø 39304 Herlufmagle 39305 Næsby 39306 Sandby 39307 Skelby 39308 Tybjerg 39309 Tyvelse 39310 Vrangstrup 39501 Gedesby 39502 Idestrup 39503 Skelby 39504 Væggerløse 39701 Kastrup 39702 Køng 39703 Lundby 39704 Sværdborg 39705 Udby 39707 Ørslev 39708 Vordingborg Landsogn 39791 Vordingborg Købstad 40102 Gudhjem 40103 Olsker 40104 Rø 40105 Østerlarsker 40106 Østermarie 40191 Allinge-Sandvig Købstæder 40302 Klemensker 40303 Nyker 40304 Rutsker 40391 Hasle Købstad 40501 Bodilsker 40502 Ibsker 40504 Povlsker 40591 Neksø Købstad 40592 Svaneke Købstad 40701 Knudsker 40791 Rønne Købstad 40901 Nylarsker 40902 Pedersker 40903 Vestermarie 40904 Aaker 40991 Aakirkeby Købstad 41101 Christiansø 42102 Barløse 42103 Baagø 42104 Gamtofte 42105 Helnæs 42106 Holevad 42107 Kærum 42108 Sandager 42109 Søby 42110 Sønderby 42111 Turup 42191 Assens Købstad 42302 Grindløse 42303 Guldbjerg 42304 Klinte 42305 Nørre Sandager 42306 Ore 42307 Skovby 42391 Bogense Købstad 42501 Allested 42502 Nørre Broby 42503 Sandholts Lyndelse 42504 Sønder Broby 42505 Vejle 42506 Vester Hæsinge 42701 Hundstrup 42702 Kirkeby 42703 Lunde 42704 Ollerup 42705 Stenstrup 42706 Ulbølle 42707 Vester Skerninge 42708 Øster Skerninge 42901 Balslev 42902 Brenderup 42903 Ejby 42904 Fjelsted 42905 Gelsted 42906 Harndrup 42907 Husby 42908 Ingslev 42909 Tanderup 42910 Ørslev 43101 Avernakø 43102 Brahetrolleborg 43103 Diernæs 43105 Horne 43106 Haastrup 43107 Lyø 43108 Svanninge 43109 Vester Aaby 43110 Øster Hæsinge 43111 Aastrup 43191 Faaborg Købstad 43301 Flemløse 43302 Køng 43303 Søllested 43304 Vedtofte 43305 Ørsted 43501 Brudager 43502 Gudbjerg 43503 Gudme 43504 Hesselager 43505 Oure 43506 Vejstrup 43701 Dreslette 43702 Haarby 43703 Jordløse 43901 Dalby 43902 Drigstrup 43904 Kølstrup 43905 Mesinge 43906 Revninge 43907 Rynkeby 43908 Stubberup 43909 Viby 43991 Kerteminde Købstad 44101 Birkende 44102 Marslev 44103 Rønninge 44501 Gamborg 44502 Kavslunde 44505 Vejlby 44591 Middelfart Købstad 44701 Munkebo 44901 Avnslev 44902 Bovense 44904 Vindinge 44991 Nyborg Købstad 45101 Asperup 45102 Føns 45103 Nørre Aaby 45104 Rorslev 45105 Udby 46101 Agedrup 46102 Allerup 46103 Allesø 46105 Bellinge 46107 Brændekilde 46108 Dalum 46109 Davinde 46111 Fangel 46112 Fraugde 46116 Højby 46118 Korup 46119 Lumby 46122 Næsbyhoved Broby 46123 Paarup 46124 Sanderum 46126 Sankt Knuds 46127 Seden 46128 Stenløse 46130 Ubberud 46132 Vor Frue 46133 Aasum 46191 Odense Købstad 47101 Bederslev 47102 Hjadstrup 47103 Krogsbølle 47104 Lunde 47105 Norup 47106 Nørre Højrup 47107 Nørre Næraa 47108 Otterup 47109 Skeby 47110 Uggerslev 47111 Østrup 47301 Espe 47302 Gestelev 47303 Heden 47304 Hellerup 47305 Herringe 47306 Hillerslev 47307 Krarup 47308 Ringe 47309 Søllinge 47310 Sønder Højrup 47311 Vantinge 47501 Fuglsbølle 47502 Longelse 47504 Simmerbølle 47505 Skrøbelev 47506 Strynø 47591 Rudkøbing Købstad 47701 Gislev 47702 Kværndrup 47703 Ryslinge 47901 Bjerreby 47902 Bregninge (Taasinge) 47903 Drejø 47904 Egense 47906 Landet 47907 Sankt Jørgens 47909 Skaarup 47910 Sørup 47911 Thurø 47912 Tved 47991 Svendborg Købstad 48101 Fodslette 48102 Humble 48103 Lindelse 48104 Magleby 48105 Tryggelev 48301 Ejlby 48302 Haarslev 48303 Melby 48304 Skamby 48305 Særslev 48306 Søndersø 48307 Veflinge 48308 Vigerslev 48502 Brylle 48503 Tommerup 48504 Verninge 48701 Bøstrup 48703 Snøde 48704 Stoense 48705 Tranekær 48706 Tullebølle 48901 Ellinge 48902 Flødstrup 48903 Skellerup 48904 Ullerslev 49101 Vissenbjerg 49501 Ellested 49502 Frørup 49503 Herrested 49504 Kullerup 49505 Langaa 49506 Refsvindinge 49507 Svindinge 49508 Øksendrup 49509 Ørbæk 49701 Nørre Lyndelse 49702 Nørre Søby 49703 Rolsted 49704 Sønder Næraa 49705 Aarslev 49901 Kerte 49902 Orte 49903 Rørup 49904 Skydebjerg 50501 Ballum 51101 Fole 51102 Gram 51103 Højrup 52507 Toftlund 52701 Hjerting 52703 Lintrup 52704 Rødding 52707 Sønder Hygum 53101 Brøns 53104 Rejsby 53105 Rømø 54502 Løjt 55101 Grene 55102 Vorbasse 55301 Henne 55302 Kvong 55303 Lunde 55304 Lydum 55305 Lønne 55306 Nørre Nebel 55307 Ovtrup 55501 Ho 55502 Oksby 55503 Aal 55701 Bramming 55702 Darum 55703 Gørding 55704 Hunderup 55705 Vejrup 55706 Vester Nykirke 55901 Brørup 55902 Folding 55903 Lindknud 56101 Bryndum 56104 Guldager 56106 Hostrup 56107 Jerne 56109 Skast 56110 Sneum 56112 Tjæreborg 56114 Vester Nebel 56301 Nordby 56302 Sønderho 56502 Grindsted 56503 Hejnsvig 56505 Sønder Omme 56701 Faaborg 56702 Grimstrup 56703 Næsbjerg 56704 Vester Starup 56705 Øse 56706 Aarre 56901 Føvling 56902 Holsted 56903 Aastrup 57102 Hjortlund 57103 Hviding 57104 Jernved 57105 Kalvslund 57106 Mandø 57109 Roager 57111 Seem 57114 Vilslev 57191 Ribe Købstad 57301 Alslev 57302 Billum 57303 Horne 57304 Janderup 57305 Torstrup 57307 Varde Landsogn 57391 Varde Købstad 57501 Andst 57503 Bække 57504 Gesten 57505 Læborg 57506 Malt 57507 Veerst 57508 Vejen 57701 Ansager 57702 Hodde 57704 Strellev 57705 Tistrup 57706 Ølgod 60101 Føvling 60102 Grædstrup 60103 Nim 60104 Ring 60105 Sønder Vissing 60106 Træden 60107 Tyrsting 60108 Tønning 60109 Underup 60110 Voerladegaard 60301 Gauerslund 60302 Gaarslev 60303 Skærup 60304 Smidstrup 60501 Bredsten 60502 Egtved 60503 Jerlev 60504 Nørup 60505 Randbøl 60506 Vester Nebel 60507 Ødsted 60508 Øster Starup 60701 Bredstrup 60703 Erritsø 60705 Herslev 60706 Pjedsted 60708 Taulov 60710 Vejlby 60791 Fredericia Købstad 60901 Gangsted 60902 Kattrup 60903 Søvind 60904 Tolstrup 60905 Vedslet 60906 Yding 60907 Ørridslev 60908 Østbirk 61101 Gadbjerg 61102 Give 61103 Givskud 61104 Lindeballe 61105 Ringive 61106 Thyregod 61107 Vester 61108 Øster Nykirke 61301 Daugaard 61302 Hedensted 61303 Korning 61304 Løsning 61305 Store Dalby 61306 Urlev 61307 Ølsted 61308 Ørum 61309 Øster Snede 61501 Endelave 61502 Hansted 61503 Hatting 61505 Lundum 61506 Nebel 61508 Tamdrup 61509 Torsted 61510 Tyrsted 61511 Uth 61513 Vær 61591 Horsens Købstad 61701 Hvejsel 61702 Jelling 61703 Kollerup 61704 Vindelev 61901 As 61902 Barrit 61903 Bjerre 61904 Glud 61905 Hjarnø 61906 Hornum 61908 Klakring 61909 Nebsager 61910 Raarup 61911 Skjold 61912 Stenderup 61913 Stouby 61914 Vrigsted 62101 Almind 62104 Eltang 62105 Harte 62107 Nørre Bjert 62108 Nørre Bramdrup 62110 Seest 62114 Sønder Vilstrup 62115 Viuf 62117 Kolding Landdistrikt 62191 Kolding Købstad 62303 Skanderup 62501 Ejstrup 62502 Klovborg 62503 Nørre Snede 62701 Grejs 62702 Hammer 62703 Hornborg 62704 Hvirring 62705 Langskov 62706 Linnerup 62707 Sindbjerg 62708 Tørring 62709 Uldum 62710 Aale 62901 Hjarup 62902 Vamdrup 63102 Engum 63103 Hornstrup 63104 Hover 63105 Højen 63110 Skibet 63111 Vinding 63113 Vejle Landdistrikt 63191 Vejle Købstad 65101 Avlum 65103 Haderup 65104 Hodsager 65302 Brande 65501 Egvad 65502 Hemmet 65503 Hoven 65504 Lyne 65505 Lønborg 65506 Nørre Bork 65507 Sønder Bork 65508 Sønder Vium 65510 Aadum 65701 Arnborg 65703 Gjellerup 65707 Herning 65711 Rind 65714 Sinding 65715 Snejbjerg 65717 Sunds 65718 Tjørring 65719 Ørre 65901 Gammelsogn 65903 Nysogn 66101 Borbjerg 66103 Idom 66105 Mejrup 66106 Maabjerg 66107 Navr 66108 Nørre Felding 66110 Raasted 66111 Sir 66112 Tvis 66191 Holstebro Købstad 66301 Bording 66303 Ikast 66501 Bøvling 66502 Dybe 66503 Fabjerg 66504 Ferring 66505 Fjaltring 66506 Flynder 66507 Gudum 66508 Heldum 66509 Hove 66510 Hygum 66512 Lomborg 66513 Møborg 66514 Nees 66515 Nørlem 66516 Nørre Nissum 66517 Ramme 66518 Rom 66519 Trans 66520 Tørring 66521 Vandborg 66591 Lemvig Købstad 66701 Hee 66702 Hover 66704 Rindum 66706 Stadil 66707 Sønder Lem 66708 Tim 66709 Torsted 66710 Vedersø 66711 Velling 66712 Ølstrup 66713 Holmsland Klit 66791 Ringkøbing Købstad 66901 Bølling 66902 Dejbjerg 66903 Faster 66904 Hanning 66905 Skjern 66906 Stavning 66907 Sædding 66908 Sønder Borris 67101 Asp 67102 Fovsing 67103 Gimsing 67104 Hjerm 67105 Humlum 67106 Resen 67108 Vejrum 67109 Venø 67110 Ølby 67301 Engbjerg 67302 Harboør 67501 Hvidbjerg 67502 Jegindø 67503 Lyngs 67504 Odby 67505 Søndbjerg 67701 Nørre Omme 67702 Nøvling 67703 Timring 67704 Vildbjerg 67705 Vind 67706 Vinding 67901 Bur 67902 Gørding 67904 Madum 67905 Staby 67907 Ulfborg 67908 Vemb 68101 Brejning 68103 Nørre Vium 68106 Vorgod 68301 Ejsing 68302 Handbjerg 68303 Ryde 68304 Sahl 68305 Sevel 68501 Assing 68503 Skarrild 68504 Sønder Felding 70101 Agri 70102 Draaby 70104 Egens 70105 Fuglslev 70106 Helgenæs 70107 Hyllested 70108 Knebel 70109 Rolsø 70110 Rosmus 70111 Tirstrup 70112 Tved 70113 Vistoft 70191 Ebeltoft Købstad 70301 Galten (Sønder) 70302 Sjelle 70303 Skivholme 70304 Skovby 70305 Skørring 70306 Stjær 70307 Storring 70501 Dallerup 70502 Gjern 70503 Skannerup 70504 Skorup 70505 Svostrup 70506 Tvilum 70701 Albøge 70702 Anholt 70703 Enslev 70705 Hammelev 70706 Hoed 70707 Homaa 70708 Lyngby 70709 Vejlby 70710 Aalsø 70791 Grenaa Købstad 70901 Hadbjerg 70902 Hadsten 70903 Lerbjerg 70904 Lyngaa 70905 Nørre Galten 70907 Rud 70908 Vissing 70909 Voldum 70910 Ødum 71101 Hammel 71102 Haurum 71103 Lading 71104 Røgen 71105 Sall 71106 Skjød 71107 Sporup 71108 Søby 71109 Voldby 71301 Foldby 71302 Grundfør 71303 Haldum 71304 Søften 71305 Vitten 71501 Adslev 71502 Blegind 71503 Hørning 71504 Mesing 71505 Veng 71701 Granslev 71702 Grensten 71703 Helstrup 71704 Houlbjerg 71705 Langaa 71706 Laurbjerg 71707 Torup 71708 Værum 71709 Ørum 71710 Øster Velling 71901 Falslev 71902 Hem 71903 Kastbjerg 71905 Sem 71906 Svenstrup 71907 Udbyneder 71908 Vester Tørslev 71909 Vindblæs 71991 Mariager Købstad 72101 Ebdrup 72102 Koed 72103 Kolind 72104 Marie Magdalene 72105 Nimtofte 72106 Nødager 72107 Skarresø 72108 Tøstrup 72301 Albæk 72302 Dalbyneder 72303 Dalbyover 72304 Enslev 72305 Gjerlev 72306 Hald 72307 Harridslev 72308 Kærby 72309 Linde 72310 Mellerup 72311 Raaby 72312 Støvring 72313 Sødring 72314 Tvede 72315 Øster Tørslev 72501 Fjellerup 72502 Ginnerup 72503 Gjerrild 72504 Glesborg 72505 Hemmed 72506 Karlby 72507 Kastbjerg 72508 Rimsø 72509 Veggerslev 72510 Villersø 72511 Voldby 72512 Ørum (Djurs) 72701 Alrø 72702 Bjerager 72703 Falling 72704 Gosmer 72705 Gylling 72706 Halling 72707 Hundslund 72708 Nølev 72709 Odder 72710 Randlev 72711 Saksild 72712 Torrild 72713 Tunø 72714 Ørting 72901 Asferg 72902 Faarup 72903 Gassum 72904 Kousted 72905 Læsten 72906 Nørbæk 72907 Spentrup 72908 Sønderbæk 72909 Øster Bjerregrav 72910 Aalum 73101 Borup 73102 Dronningborg 73103 Gimming 73104 Haslund 73105 Hornbæk 73106 Kristrup 73107 Lem 73108 Raasted 73113 Taanum 73114 Vorup 73115 Ølst 73191 Randers Købstad 73301 Halling 73302 Hornslet 73303 Hvilsager 73304 Krogsbæk 73305 Lime 73306 Mygind 73307 Mørke 73308 Skader 73309 Skørring 73310 Søby 73501 Estruplund 73502 Gjesing 73503 Holbæk 73504 Nørager 73505 Udby 73506 Vejlby 73507 Vivild 73508 Voer 73509 Ørsted 73701 Alling 73702 Dover 73703 Gammel Rye 73704 Laasby 73706 Tulstrup 73901 Bregnet 73902 Feldballe 73903 Thorsager 74101 Besser 74102 Kolby 74103 Nordby 74104 Onsbjerg 74105 Tranebjerg 74106 Kyholm 74302 Balle 74303 Funder 74304 Gødvad 74305 Kragelund 74306 Lemming 74307 Linaa 74309 Sejling 74311 Serup 74313 Sinding 74501 Fruering 74502 Hylke 74503 Ovsted 74505 Skanderup 74506 Stilling 74507 Taaning 74508 Vitved 74591 Skanderborg Købstad 74701 Auning 74702 Essenbæk 74703 Fausing 74704 Hørning 74705 Vester Alling 74706 Virring 74707 Øster Alling 74708 Aarslev 74901 Bryrup 74902 Them 74903 Vinding 74904 Vrads 75101 Astrup 75102 Beder 75103 Borum 75104 Brabrand 75106 Egaa 75107 Elev 75109 Elsted 75110 Framlev 75112 Faarup 75114 Harlev 75115 Hasle 75117 Hjortshøj 75118 Holme 75119 Hvilsted 75120 Kasted 75121 Kolt 75123 Lisbjerg 75124 Lyngby 75126 Malling 75127 Mejlby 75129 Maarslet 75130 Ormslev 75133 Sabro 75138 Skejby 75141 Skødstrup 75143 Spørring 75144 Sønder Aarslev 75145 Tilst 75146 Tiset 75147 Todbjerg 75148 Tranbjerg 75149 Trige 75150 Tulstrup 75151 Vejlby 75152 Viby 75154 Ølsted 75155 Aaby 75191 Aarhus Købstad 76101 Bjerring 76103 Elsborg 76104 Gullev 76105 Hjermind 76106 Hjorthede 76107 Høbjerg 76108 Lee 76109 Mammen 76110 Sahl 76111 Skjern 76112 Vindum 76301 Daugbjerg 76302 Feldingbjerg 76303 Fly 76304 Gammelstrup 76305 Kobberup 76306 Mønsted 76307 Nørre Borris 76308 Resen 76309 Smollerup 76310 Vridsted 76311 Vroue 76501 Hansted 76502 Hjardemaal 76504 Lild 76505 Ræhr 76506 Tømmerby 76507 Vigsø 76701 Aidt 76702 Gerning 76703 Hvorslev 76704 Sønder Vinge 76705 Thorsø 76707 Vejerslev 76708 Vellev 76709 Vester Velling 76901 Frederiks 76902 Karup 77101 Grønbæk 77102 Hinge 77103 Hørup 77104 Levring 77105 Sjørslev 77106 Thorning 77107 Vinderslev 77108 Vium 77301 Alsted 77302 Bjergby 77303 Blidstrup 77304 Dragstrup 77305 Ejerslev 77306 Elsø 77307 Erslev 77308 Flade 77309 Frøslev 77310 Galtrup 77311 Hvidbjerg 77312 Jørsby 77313 Karby 77314 Ljørslev 77315 Lødderup 77316 Mollerup 77318 Ovtrup 77319 Rakkeby 77320 Redsted 77321 Sejerslev 77322 Skallerup 77323 Solbjerg 77324 Sundby 77325 Sønder Draaby 77326 Tæbring 77327 Tødsø 77328 Vejerslev 77329 Vester Assels 77330 Ørding 77331 Øster Assels 77332 Øster Jølby 77333 Nykøbing Mors Landdistrikt 77391 Nykøbing Mors Købstad 77501 Hersom 77502 Klejtrup 77503 Lynderup 77504 Laastrup 77505 Roum 77506 Skals 77507 Ulbjerg 77508 Vester Bjerregrav 77509 Vester Tostrup 77701 Durup 77703 Harre 77704 Hjerk 77705 Nautrup 77706 Roslev 77707 Rybjerg 77708 Sæby 77709 Tøndering 77710 Vile 77901 Dommerby 77902 Dølby 77904 Estvad 77905 Hem 77906 Hindborg 77907 Højslev 77908 Lundø 77909 Resen 77910 Rønbjerg 77912 Ørslevkloster 77913 Ørum 77991 Skive Købstad 78101 Balling 78102 Brøndum 78103 Hvidbjerg 78104 Haasum 78105 Krejbjerg 78106 Lem 78107 Lihme 78108 Oddense 78109 Otting 78110 Ramsing 78111 Rødding 78112 Vejby 78113 Volling 78301 Fur 78302 Grinderslev 78303 Grønning 78304 Jebjerg 78305 Junget 78306 Lyby 78307 Selde 78308 Thise 78309 Torum 78310 Aasted 78501 Agger 78502 Bedsted 78503 Boddum 78504 Gettrup 78505 Grurup 78506 Hassing 78507 Helligsø 78508 Heltborg 78509 Hurup 78510 Hvidbjerg Vesten Aa 78511 Hørdum 78512 Lodbjerg 78513 Skyum 78514 Vestervig 78515 Villerslev 78516 Visby 78517 Ydby 78518 Ørum 78701 Arup 78702 Harring 78703 Hillerslev 78704 Hundborg 78705 Hunstrup 78706 Hørsted 78707 Jannerup 78708 Kallerup 78709 Kaastrup 78710 Nors 78711 Nørhaa 78712 Sennels 78713 Sjørring 78714 Skinnerup 78715 Skjoldborg 78716 Snedsted 78717 Stagstrup 78718 Sønderhaa 78720 Tilsted 78721 Torsted 78722 Tved 78723 Vang 78724 Vesløs 78725 Vester Vandet 78727 Øsløs 78728 Øster Vandet 78729 Østerild 78791 Thisted Købstad 78901 Bigum 78902 Hammershøj 78903 Kvorning 78904 Lindum 78905 Løvel 78906 Nørre Vinge 78907 Pederstrup 78908 Rødding 78909 Tjele 78910 Vammen 78911 Vejrum 78912 Viskum 78913 Vorning 78914 Ørum 79101 Almind 79102 Asmild 79103 Dollerup 79104 Finderup 79105 Fiskbæk 79106 Kvols 79107 Lysgaard 79108 Ravnstrup 79109 Romlund 79110 Sønder Rind 79113 Tapdrup 79114 Taarup 79117 Vinkel 79118 Vorde 79191 Viborg Købstad 79301 Fjeldsø 79302 Gedsted 79303 Hvam 79304 Hvilsom 79305 Simested 79306 Testrup 79307 Vester Bølle 79308 Øster Bølle 80101 Astrup 80102 Ove 80103 Rold 80104 Rostrup 80105 Store Arden 80106 Valsgaard 80107 Vebbestrup 80301 Brovst 80302 Lerup 80303 Torslev 80304 Tranum 80305 Øland 80306 Øster Svenstrup 80502 Hallund 80503 Hellum 80504 Jerslev 80505 Serritslev 80506 Stenum 80507 Tise 80508 Tolstrup 80509 Øster Brønderslev 80702 Dronninglund 80703 Hellevad 80705 Voer 80706 Ørum 80901 Alstrup 80902 Farsø 80903 Flejsborg 80904 Fovlum 80905 Hyllebjerg 80906 Lovns 80907 Strandby 80909 Ullits 80910 Vester Hornum 81101 Bejstrup 81102 Gøttrup 81103 Haverslev 81104 Hjortdal 81105 Kettrup 81106 Klim 81107 Kollerup 81108 Skræm 81109 Vester Torup 81110 Vust 81303 Elling 81304 Flade 81306 Gærum 81307 Hirsholmene 81308 Skærum 81309 Aasted 81310 Frederikshavn Landdistrikt 81391 Frederikshavn 81501 Als 81503 Skelund 81504 Visborg 81505 Vive 81701 Hals 81702 Ulsted 81703 Vester Hassing 81704 Øster Hassing 81901 Asdal 81902 Bindslev 81904 Horne 81905 Tornby 81906 Tversted 81907 Uggerby 81908 Vidstrup 82102 Bjergby 82104 Hæstrup 82105 Mygdal 82106 Maarup 82107 Sankt Hans 82108 Sankt Olai 82109 Skallerup 82110 Taars 82111 Vennebjerg 82112 Vrejlev 82191 Hjørring Købstad 82301 Døstrup 82302 Glenstrup 82304 Hvornum 82305 Hørby 82306 Nørre Onsild 82307 Skjellerup 82308 Snæbum 82309 Sønder Onsild 82310 Øls 82391 Hobro Købstad 82501 Byrum 82502 Hals 82503 Vesterø 82701 Aggersborg 82702 Kornum 82703 Løgsted 82705 Malle 82706 Næsborg 82707 Oudrup 82710 Skarp Salling 82711 Vilsted 82712 Vindblæs 82713 Bjørnsholm 82901 Børglum 82902 Em 82903 Furreby 82904 Harritslev 82905 Jelstrup 82906 Lyngby 82907 Rakkeby 82908 Rubjerg 82909 Sejlstrup 82910 Vejby 82911 Vrensted 82912 Vraa 83101 Bislev 83102 Ejdrup 83103 Farstrup 83104 Lundby 83106 Sebber 83107 Store Ajstrup 83108 Vokslev 83191 Nibe Købstad 83301 Binderup 83302 Brorstrup 83303 Durup 83304 Grynderup 83305 Haverslev 83306 Kongens Tisted 83307 Ravnkilde 83308 Rørbæk 83309 Stenild 83501 Alstrup 83502 Hune 83503 Ingstrup 83504 Jetsmark 83505 Saltum 83506 Vester Hjermitslev 83701 Gudum 83702 Komdrup 83703 Lillevorde 83704 Mou 83705 Nørre Kongerslev 83706 Sejlflod 83707 Storvorde 83708 Sønder Kongerslev 83901 Astrup 83902 Hørmested 83903 Lendum 83904 Mosbjerg 83905 Sindal 83906 Tolne 83907 Ugilt 84101 Raabjerg 84191 Skagen Købstad 84301 Blenstrup 84302 Bælum 84303 Fræer 84304 Gerding 84305 Lyngby 84306 Siem 84307 Skibsted 84308 Skørping 84309 Solbjerg 84310 Store Brøndum 84311 Torup 84501 Buderup 84502 Gravlev 84503 Suldrup 84504 Sønderup 84505 Veggerby 84506 Øster Hornum 84507 Aarestrup 84701 Albæk 84702 Hørby 84703 Karup 84704 Skæve 84706 Torslev 84707 Understed 84708 Volstrup 84791 Sæby Købstad 84901 Biersted 84902 Gjøl 84904 Aaby 84905 Aaby 85101 Ajstrup 85104 Dall 85105 Ellidshøj 85106 Ferslev 85107 Frejlev 85109 Gunderup 85110 Hammer 85113 Horsens 85114 Hvorup 85115 Klarup 85118 Nørholm 85119 Nørre Tranders 85121 Nøvling 85122 Romdrup 85125 Sulsted 85126 Svenstrup 85127 Sønder Tranders 85128 Sønderholm 85129 Vadum 85133 Volsted 85136 Store Restrup 85137 Budolfi Landsogn 85191 Nørresundby Købstad 85192 Aalborg Købstad 86101 Blære 86102 Gislum 86103 Giver 86104 Gundersted 86105 Havbro 86106 Skivum 86107 Ulstrup 86108 Vognsild 86109 Aars 86302 Ebeltoft Landsogn 86303 Faaborg Landdistrikt 86307 Mariager Landsogn 86308 Maribo Landdistrikt 86310 Middelfart Landdistrikt 86312 Nyborg Landsogn 86313 Nysted Landsogn 86314 Præstø Landdistrikt 86315 Ribe Landsogn 86316 Ringsted Landsogn 86317 Sakskøbing Landdistrikt 86318 Sankt Mikkels Landsogn 86319 Sankt Peders Landsogn 86320 Skagen Landsogn 86321 Skive Landsogn 86322 Stege Landdistrikt 86323 Store Heddinge Landsogn 86324 Thisted Landsogn 86326 Ude Sundby Landdistrikt 86327 Viborg Graabrødre Landsogn 86328 Aalborg Frue Landsogn 86501 Gammelsogn 86503 Ullerup 86505 Vallø Stiftsmenighed Geography: A-E Variables -- HOUSEHOLD Type of administrative unit Geographic code:</p> <div class="i1">Geographical reference. Refers to the tables 'administrative types, parish, counties, districts and regions.'</div><p>Type of unit:</p> <div class="i1">Code for administrative unit: parish, town, ...</div> Denmark 1845: All households This variable indicates the type of administrative unit (either parish or street). 05 Parish 06 Part of parish 08 Quarter 09 Royal borough 99 Unknown Geography: A-E Variables -- HOUSEHOLD County Geographic code:</p> <div class="i1">Geographical reference. Refers to the tables 'administrative types, parish, counties, districts and regions.'</div><p>County:</p> <div class="i1">Code for the county. Refers to the table counties.</div> Denmark 1845: All households This variable indicates the county where the household is located. 22 Aabenraa 23 Aalborg 24 Aarhus 25 Bornholm 27 Frederiksborg 29 Haderslev 30 Hjørring 31 Holbæk 32 København 34 Maribo 35 Odense 36 Præstø 37 Randers 38 Ribe 39 Ringkøbing 40 Roskilde 41 Skanderborg 42 Sorø 43 Svendborg 45 Thisted 46 Tønder 47 Vejle 48 Viborg 98 Unknown Geography: A-E Variables -- HOUSEHOLD District Geographic code:</p> <div class="i1">Geographical reference. Refers to the tables 'administrative types, parish, counties, districts and regions.'</div><p>District:</p> <div class="i1">Code for district. Links to the table districts.</div> Denmark 1845: All households This variable indicates the district where the household is located. 00103 Aars 00104 Aasum 00107 Alsted 00109 Anst 00110 Ars 00111 Baag 00112 Baarse 00114 Bjerge 00115 Bjerre 00116 Bjæverskov 00117 Brusk 00118 Bølling 00119 Børglum 00120 Djurs Nørre 00121 Djurs Sønder 00122 Dronninglund 00123 Elbo 00124 Fakse 00125 Falsters Nørre 00126 Falsters Sønder 00127 Fjends 00128 Fleskum 00129 Framlev 00132 Frøs 00133 Fuglse 00135 Galten 00136 Ginding 00137 Gislum 00138 Gjerlev 00139 Gjern 00141 Gudme 00142 Gørding 00144 Hads 00145 Hammer 00146 Hammerum 00147 Harre 00148 Hasle 00149 Hassing 00150 Hatting 00151 Hellum 00152 Hids 00153 Hillerslev 00154 Hind 00155 Hindborg 00156 Hindsted 00157 Hjelmslev 00158 Hjerm 00159 Holbo 00160 Holmans 00161 Horns (Sjælland Region) 00162 Horns (Nordjylland Region) 00163 Hornum 00164 Houlbjerg 00165 Hundborg 00166 Hvetbo 00167 Hviding 00168 Jerlev 00174 Kær 00175 Langelands Nørre 00176 Langelands Sønder 00177 Lollands Nørre 00178 Lollands Sønder 00179 Lunde 00181 Lynge-Frederiksborg 00182 Lynge-Kronborg 00183 Lysgaard 00184 Læsø 00185 Løve 00186 Malt 00187 Merløse 00188 Middelsom 00189 Mols 00190 Morsø Nørre 00191 Morsø Sønder 00192 Musse 00193 Mønbo 00195 Nim 00196 Ning 00198 Nørhald 00199 Nørlyng 00200 Nørre (Andre øer Region) 00201 Nørre (Vestjylland Region) 00202 Nørre Horne 00203 Nørre Rangstrup 00204 Nørre Tyrstrup 00205 Nørvang 00206 Odense 00207 Ods 00208 Onsild 00209 Ramsø 00210 Refs 00211 Ribe 00212 Rinds 00213 Ringsted 00214 Rise 00215 Rougsø 00216 Rødding 00217 Sabro 00218 Sallinge 00219 Samsø 00220 Skam 00221 Skast 00222 Skippinge 00223 Skodborg 00224 Skovby 00225 Slagelse 00226 Slavs 00227 Slet 00229 Smørum 00230 Sokkelund 00231 Stevns 00232 Strø 00233 Støvring 00234 Sunds 00235 Sømme 00236 Sønder 00239 Sønderhald 00240 Sønderlyng 00241 Tune 00242 Tuse 00243 Tybjerg 00244 Tyrsting 00245 Tønder 00246 Tørrild 00247 Ulfborg 00249 Vandfuld 00250 Vends 00251 Vennebjerg 00252 Vester 00253 Vester Flakkebjerg 00254 Vester Han 00255 Vester Horne 00256 Vester Lisbjerg 00257 Vindinge 00258 Voer 00259 Voldborg 00260 Vrads 00262 Ølstykke 00263 Øster 00264 Øster Flakkebjerg 00265 Øster Han 00266 Øster Horne 00267 Øster Lisbjerg 10003 København (Staden) 99998 Unknown Geography: A-E Variables -- HOUSEHOLD Region Geographic code:</p> <div class="i1">Geographical reference. Refers to the tables 'administrative types, parish, counties, districts and regions.'</div><p>Region:</p> <div class="i1">Name of region in Denmark.</div> Denmark 1845: All households This variable indicates the region where the household is located. 1 Sjælland 2 Andre øer 3 Østjylland 4 Nordjylland 5 Vestjylland 6 Sønderjylland Geography: A-E Variables -- HOUSEHOLD Urban areas from Parishes Geographic code:</p> <div class="i1">Geographical reference. Refers to the tables 'administrative types, parish, counties, districts and regions.'</div><p>Urban:</p> <div class="i1">Rural or urban.</div> Denmark 1845: All households 1 Urban (Copenhagen) 2 Market Towns 3 Rural Geography: A-E Variables -- HOUSEHOLD Urban or rural Urban:</p> <div class="i1">Rural or urban.</div> Denmark 1845: All households This variable indicates whether the household is located in an urban or rural area. 1 Rural 2 Urban Geography: A-E 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 household head, historical RELATEH is the NAPP version of the RELATE variable, which describes an individual's relationship to the head of household. This variable is largely compatible with the IPUMS-International variable RELATE, though some changes have been made. The relationship codes are divided into two categories-relatives (codes 1- 10) and non-relatives (codes 11-12). The codes for relatives are self- explanatory. The non-relative codes are divided into three groups: "Partner, friend, visitor", roughly described as persons who do not pay or work for their accommodations (unless they share ownership); "Other non-relatives", including those persons paying or working for accommodations; and "Institutional inmates". 0101 Head/householder 0201 Spouse 0202 2nd/3rd wife (polygamous) 0203 Concubine/mistress 0204 Fiance/fiancee 0301 Child 0302 Adopted Child 0303 Stepchild 0304 Adopted, n.s. 0305 Adopted/fostered child (Great Britain) 0306 Fostered child 0401 Child-in-law 0402 Step child-in-law 0501 Parent 0502 Stepparent 0503 Adoptive parent 0601 Parent-in-law 0602 Stepparent-in-law 0603 Retired people with special benefits from farm (karfolk) 0701 Sibling 0702 Step/half/adopted sibling 0703 Step sibling 0704 Half-sibling 0801 Sibling-in-Law 0802 Step/half sibling-in-law 0901 Grandchild 0902 Adopted grandchild 0903 Step grandchild 0904 Grandchild-in-law 1000 Other Relatives: 1001 Other relatives, n.s. 1011 Grandparent 1012 Step grandparent 1013 Grandparent-in-law 1021 Aunt or uncle 1022 Aunt,uncle-in-law 1023 Step aunt or uncle 1024 Great aunt or uncle 1031 Nephew, niece 1032 Nephew/niece-in-law 1033 Step/adopted nephew/niece 1034 Grand niece/nephew 1035 Step nephew/niece 1036 Adopted nephew/niece 1037 Grand step nephew/niece 1038 Grand nephew/niece in law 1041 Cousin 1042 Cousin-in-law 1043 First cousin 1044 Second cousin 1045 Step cousin 1051 Great grandchild 1061 Other relatives, n.e.c. 1100 Partner, friend, visitor 1110 Partner/friend 1111 Friend 1112 Partner 1113 Partner/roommate (1960/70 residual category for other non-relatives) 1114 Unmarried partner 1115 Housemate/roommate 1120 Relative of partner 1131 Visitor 1132 Companion and companion's family 1139 Allocated partner/friend/visitor 1201 Roomers/boarders/lodgers 1202 Boarders 1203 Lodgers 1204 Roomer 1205 Tenant 1207 Poor or receiver of charity by head of household 1208 Pauper staying with others at expense of municipality 1209 Illicit Vagrant 1210 Employees: 1211 Servant 1212 Housekeeper 1213 Maid 1214 Cook 1215 Nurse 1216 Other probable domestic employee 1217 Other employees 1218 Employees of guests 1219 Relative of employee 1221 Military 1222 Students 1223 Members of religious orders 1224 Harim (Egypt) 1225 Slave (Egypt) 1226 Child of slave (Egypt) 1230 Other non-relatives 1239 Allocated other non-relative 1301 Institutional inmates 1302 Families of inmates 1303 Foundlings/orphans 9999 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 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 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, 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 Occupation, HISCO classification OCCHISCO is a uniformly coded classification of occupations that is consistent across all countries. It is the most complicated variable to code consistently in the pre-1950 samples, and the present documentation does not fully cover the issues addressed. We will be progressively adding to the level of detail available on this variable. For example, we will occasionally provide examples of common responses below each code so that users will be able to see what responses were coded where. Users with queries about the coding of specific occupations should contact the IPUMS staff in the first instance. Users interested in variation in occupational responses below the level of detail provided in the codes (e.g., distinguishing "caretakers" from "janitors") should look at the OCCSTRNG variable. The codes for OCC were adapted from the Historical International Standard Classification of Occupations (HISCO) coding scheme. More information on HISCO is available in M.H.D. van Leeuwen, I. Maas and A. Miles. (2002) HISCO: Historical International Standard Classification of Occupations. Leuven: Leuven University Press. HISCO in turn is based on the International Standard Classification of Occupations from 1968, commonly known as ISCO-68. Information on HISCO can also be located at the HISCO database of occupational titles, and the International Institute of Social History. More information on the adaptations IPUMS made to HISCO can be found in the article "Occupational Classification in the North Atlantic Population Project" (2003), Historical Methods, Vol. 36, No. 2 (Part 2), pp.89-96. Structure of the classification scheme The classification scheme is hierarchical, in the sense that each digit in the 5 digit codes introduces a new level of detail. Codes sharing the same first 1, 2 or 3 digits are considered to be increasingly similar. For example, all people working in agriculture have the first digit 6. The first digit of a code indicates the "Major group" a person's occupation is in. The second digit indicates a "Minor group" distinction. Continuing the previous example, people who have the first two digits "61" are farmers - who may specify what they are cultivating or tending - and farm managers. Thus, as well as sharing the characteristic of working in agriculture (6) they also share the characteristic of being owners or managers (61). The first 3 digits denote the "Unit group" of an occupation. At the third digit level, we introduce more detail. For example, the unit group "612" indicates "Specialized farmers". Within this unit group, 4th and 5th digit distinctions known as "titles" or "headings" are made. For example, "61220" indicates "Field crop farmers," and "61230" indicates "Orchardists and fruit farmers." Understanding headings In general, if the last two digits of a code are "00" the heading is reserved for general titles. For example, in unit group "721" for "Metal smelter and furnace workers", the heading "72100" is reserved for responses such as "Metal smelter" and "Furnace men." If the last two digits of a code are "10" the heading is reserved for "not further specified" titles (often abbreviated "n.f.s." or "nfs" in syntax files), and codes ending in "20", "30" and higher multiples of 10 are reserved for responses with more detail on some aspect of the occupation. For example, "58210" is the code for "Policemen and detectives, employer unknown," whereas "58220" and "58230" are the codes for "Policemen and detectives, public service," and "Policemen and detectives, private service" respectively. Headings ending in digits other than "0" (e.g., 2, 3, 4, 9) are generally reserved for frequent responses specific to a particular country that probably belong with responses sharing the same first four digits of the heading. For example, "61115" ("Husbandman or cottar") in Norway and Sweden and "61117" ("Female farmer") in Canada could be classified with "Other general farmers" ("61110"), but occurred frequently enough that we felt they should be given a separate code for easier identification. If the last two digits of a code are "90", the heading is reserved for "not elsewhere classified" responses. For example, "58290" is the code for "Other law enforcement officers". The difference between "n.f.s." and "n.e.c." responses is that "n.f.s." responses are quite general, and may not offer much detail on the tasks and duties of the job. Conversely, "n.e.c." responses are typically quite detailed in the information provided, but there are not enough similar responses to justify a separate heading. Alterations to HISCO Compared to HISCO we have reduced the overall number of headings, while still introducing new ones, and retaining more detail from vaguely specified occupations. In general, we made the fewest changes to the structure of the HISCO codes in major groups 0 and 1 (professional workers). We re-organized the codes within major groups 2 (administrative and managerial workers), 3 (clerical workers), 4 (sales workers), 5 (service workers), and 6 (workers in agriculture). We made the most substantial revisions in moving people between major groups in the manufacturing and transport major groups (7, 8, and 9). In particular, we created codes for vague responses of the form "Works in [specified type of] factory," such as "Works in cotton mill." We grouped these workers with "Laborers" and titled, skilled workers in the same general industry. We eliminated codes where HISCO made distinctions that were not consistently made in nineteenth century census data. For example, HISCO distinguished between hand and machine spinners. We found that most spinners did not specify whether they were spinning by hand or machine, more often giving information on what they were spinning (e.g., cotton, wool, silk), or a firm's name. We introduced codes to handle vague occupations, as discussed above. We also created codes to retain linguistic and nominal distinctions above a rough frequency level. These distinctions are generally made in the fourth and fifth digit of the codes. For example, we distinguish between "Farm workers, specialisation unknown" (62110) and "Farmer's sons and other male relatives" (62113), because "farmer's son" was a numerically significant response in Canada. Both are considered part of the "Farm labourers and helpers, general farming and n.f.s" unit group (621). Other variables Responses to the occupational questions also returned information that cannot be classified within an occupational classification scheme, such as relationship to workers, or indications of status. Please see the documentation for the variables OCRELATE and OCSTATUS. Information on the products sold by retail workers (Major Group 4) is available in the variable PRODUCT. Occupations were also coded into domestic occupational classification schemes in Great Britain, Norway, and the United States. See the documentation for the following variables for more information. Norway OC1HIRNO OC1TRDNO OC2HIRNO OC2TRDNO United Kingdom OCCICEM United States OCC95US 01100 Chemists 01200 Physicists 01300 Physical scientists nec 01400 Physical science assistants and technicians 02000 Professional engineers, specialisation unknown 02100 Architects 02200 Civil engineers 02300 Electrical engineers 02410 Mechanical engineers, general or nfs 02420 Industrial machinery or tools engineers 02430 Mechanical engineer (motors and engines, except marine) 02440 Marine engineers 02450 Ship construction engineers 02460 Heating, ventilation and refrigeration engineers 02490 Other mechanical engineers 02500 Chemical engineers 02600 Metallurgists and assayers 02700 Mining engineers 02800 Industrial engineers 02900 Professional engineers nec 03010 Surveyors, general and nfs 03020 Land surveyors 03030 Mine surveyors 03040 Hydrographic surveyors 03090 Other surveyors 03100 Draughtsmen 03200 Technician, specialisation unknown 03210 Technicians 03220 Civil engineering technicians 03230 Electrical engineering technicians 03240 Mechanical engineering technicians 03250 Chemical engineering technicals 03260 Metallurgical technicians 03270 Mining technicians 03290 Engineering technicians nec 04200 Ship's deck officer or pilot 04210 Ships officers nfs 04220 Ship's masters and captains (sea) 04230 Ship's masters and captains (sea or inland waterways) 04240 Ship's masters and captains (inland waterways) 04250 Ship's navigating officers and ship's mates 04260 Ship and boat pilots 04270 Marine superintendents (deck) 04290 Other ship deck officers and pilots 04300 Ship's engineers 05100 Biologists, botanists, zoologists and related scientists 05200 Medical scientists 05300 Agronomists and related scientists 05400 Life sciences technicians 06100 Medical doctors and surgeons 06110 Medical doctors and physicians (UK: Medical doctors only) 06130 Surgeons 06140 Specialised physicians 06150 Specialised surgeons 06160 Public health physicians 06170 Oculist 06190 Medical doctors, nec 06200 Dentists 06300 Veterinarians 06400 Pharmacists 06500 Medical and related assistants 07110 Trained nurses 07210 Nurses nfs 07220 Medical nurses, untrained or level of training unknown 07320 Midwives 07330 Monthly nurses 07500 Opticians and optometrists 07600 Healers and therapists nec 07920 Osteopaths 07930 Chiropractors 07940 Sanitarians 07990 Other medical, dental, veterinary and related workers 08000 Mathematicians and actuaries, etc. 09000 Economists 11010 Accountants 11020 Auditors 11090 Accountants nec 12110 Lawyers 12120 Barristers 12130 Solicitors 12200 Judge 12220 Justice of the peace 12300 Notary 12900 Jurists (except lawyer, judge or solicitor) 13100 Teachers in higher education 13200 Teachers not in higher education 13210 Teachers (unspecified) 13220 Teachers (secondary) 13230 Teachers (primary) 13240 Teachers (pre-primary) 13250 Teachers (of the disabled) 13300 School administrators and principals 13920 Governesses 13990 Other teaching personnel 14120 Ministers of religion 14130 Missionaries 14140 Members of religious orders 14190 Other ministers of religion 14900 Workers in religion nec 15100 Authors 15220 Editors 15230 Journalists, reporters and correspondents 15900 Others writers 16110 Artists nfs and art teachers 16120 Sculptors 16130 Artistic painters 16140 Cartoonists 16150 Engravers and etchers (artistic) 16190 Other specified creative artists 16200 Designers 16300 Photographers 16400 Engravers 17120 Musical performers and musicians nfs 17130 Music teachers 17190 Others in music 17200 Dancers and dancing teachers 17300 Actors and related workers 17400 Producers, performing arts 17900 Performing artists nec 18000 Athletes, sportsmen and related workers 19100 Librarians, archivists and curators 19200 Social scientists and historians 19300 Social workers 19500 Interpreters, translators and philologists 19920 Patent agents 19930 Underwriters 19990 Other professional, technical and related workers nec 20100 Legislative officials and heads of government 20200 Government administrators 21110 Proprietors, nfs 21112 Executive officers, nfs (U.S. only) 21120 Manufacturers nfs 21122 Executive officers of manufacturing concerns nfs 21130 Manufacturers or proprietors of specified manufacturing concerns 21132 Executive officers of specified manufacturing concerns 21140 Proprietor, mining, quarrying, oil and natural gas extraction 21141 Oil producer 21142 Executive officers of extractive industry 21150 Proprietor, railway company 21152 Executive officers of railway concerns 21160 Proprietor, other transport and communications 21162 Executive officer of other transport and communications 21170 Proprietor, public utilities (i.e., water, gas, etc.) 21172 Executive officer of public utilities 21180 Proprietor, finance 21182 Executive officer finance company 21190 Other owners of large scale productive enterprises 21192 Executive officers of other large scale productive enterprises 21194 Publisher 21210 Contractors nfs 21220 Construction contractors 21230 Builders 21290 Other specified contractors 21330 Capitalists 21340 Speculators 21390 Investors nec 22110 Superintendents and managers nfs 22120 Superintendents and managers, manufacturing 22130 Superintendents and managers, mining, quarrying, etc. 22140 Superintendents and managers, railways 22150 Superintendents and managers, other transport and communications 22160 Superintendents and managers, public utilities 22170 Superintendents and managers, construction, except railway construction 22180 Superintendents and managers, commerce 22190 Superintendents and managers, nec 23110 Foremen and supervisors nfs 23120 Foremen and supervisors, manufacturing 23130 Foremen and supervisors, mining 23140 Foremen and supervisors, railways 23150 Foremen and supervisors, other transport and communications 23160 Foremen and supervisors, public utilities 23170 Foremen and supervisors, construction, except railway construction 23180 Foremen and supervisors, commerce 23190 Foremen and supervisors, nec 24100 Inspectors of manufactories, companies etc. 31010 Civil servants, title unknown 31020 Tax collectors 31030 Tax assessors 31040 Customs officers 31050 Postmasters or postmistresses 31060 Clerks of court and other court clerks 31090 Government functionaries, nec 32000 Typists, stenographers and secretaries 33120 Bookkeepers and bookkeeping clerks 33130 Cashiers, bank or office 33140 Bank clerks 33142 Bank tellers (US) 33150 Money collector 33160 Cash desk cashier 33170 Toll collectors 33180 Collector (cash or account) 33190 Bookkeeping, account and cash handling workers nec 33210 Railway clerks (UK) and railway agents (CA/US) 33220 Baggage agents and baggage men 33320 Agent, water transport (principally steamship and steamboat) 33330 Agent, land transport (non-rail) 34000 Office machine operators 36010 Conductors, nfs 36020 Railway guards (UK) and railroad conductors (US/CAN) 36030 Sleeping- or pullman-car attendants 36040 Bus, tram or streetcar conductors 36090 Transport conductors, nec 37020 Postal, mail and telegraph clerks 37030 Mail carriers, aka postmen (UK) 37040 Messengers 37050 Mail sorters 37090 Post office, mail, and message workers nec 38010 Tel. operator 38020 Telephone operator 38030 Telegraph operator 38090 Other telephone/telegraph operators 39000 Clerk, nfs 39100 Stock, weight and shipping clerks 39130 Stock records clerk 39310 Office clerks, specialisation unknown 39320 Correspondence clerks 39340 Legal clerks 39350 Insurance clerks 39390 Other correspondence and reporting clerks 39400 Hotel clerk or other receptionist 39500 Library and filing clerks 39600 Railroad, railway clerk 39720 Timekeepers, railway 39730 Timekeepers, factory 39790 Timekeepers, undefined and nec 39900 Other specified clerks 39990 Proofreader 40000 Sales workers, nfs 41000 Working proprietors, nfs 41010 Dealer, merchant etc. (wholesale and retail trade) 41015 Merchants, specified large-scale wholesaleing 41020 Hirers out 42000 Buyers 42200 Buyers nec 43010 Agents nfs 43020 Commercial travellers 43030 Manufacturers and sales agents 43090 Other specialized agents 44110 Insurance, real state or securities salesmen, nfs 44120 Insurance salesmen and agents 44130 Real estate agents 44140 Brokers 44150 Stockbrokers 44160 Patent Agents 44190 Insurance, real estate and securities salesmen nec 44200 Advertising salesmen 44320 Auctioneers 44330 Appraisers 45120 Salespeople, wholesale or retail trade 45130 Clerks in shops and stores 45140 Fashion models 45190 Other sales personnel men, shop assistants and demonstrators 45220 Street sellers, pedlars and hawkers, non-food items 45230 Street sellers, pedlars and hawkers, food items 45240 Newsvendors 45250 Canvassers 45290 Other street traders for coffee and food 49020 Pawnbrokers 49030 Scrap and junk dealers, scavengers 49040 Street vendors, canvassers and news vendors, newsvendors 49090 Dealers and salesworkers nec 51020 Hotel keepers and managers 51030 Restaurant keepers and managers 51040 Boarding and lodging house keepers and managers 51050 Pub, saloon, tavern and coffee house keepers 51060 Ship's pursers 51090 Other hospitality and entertainment keepers and managers 52020 Housekeeper 52030 Stewards 52040 Matrons 52050 Butlers 52090 Other housekeeping service supervisors 53100 Cooks 53101 Cook (domestic) UK only 53102 Cook (not domestic) 53103 Ship's cooks 53220 Waiter or waitress 53230 Bartender 53290 Other food and drink service workers 54010 Servants nfs 54020 House servants nfs and maids 54030 Personal servants and valets 54040 Nursemaids 54050 Companions 54060 Chambermaids and room attendants 54090 Other specified servants 55100 Caretakers and janitors 55200 Charworkers 55230 Window cleaners 55240 Chimney sweeps 55250 Refuse collectors and removers 55290 Other charworkers, cleaners and related workers 56000 Washing and laundry services 57020 Hairdressers 57030 Barbers 57040 Bath attendants 57090 Other barbers, hairdressers and related workers 58100 Firefighters 58210 Policemen and detectives, employer unknown 58220 Policemen and detectives, public service 58230 Policemen and detectives, private service 58240 Sheriffs and their deputies 58290 Other law enforcement officers 58300 Watchmen and guards 58410 Military, rank unknown 58420 Military officers 58430 Other members of the armed forces 58500 Prison keepers and guards 58900 Other protective service workers 59100 Guides 59200 Undertakers and embalmers 59300 Prostitutes 59920 Bookmakers (sport) 59930 Croupiers 59940 Nursing aids and attendents 59950 Errand boys and errand girls 59960 Practical aid (veterinary) 59990 Other service workers nec 61110 General farmers and farmers nfs 61115 Husbandmen or cottars 61117 Female farmer 61120 Major landowner 61220 Field crop farmers 61230 Orchardists and fruit farmers 61240 Market gardeners 61250 Nurserymen and florists 61260 Livestock farmers 61270 Dairy farmers 61280 Poultry farmers 61290 Other specialised farmers 61320 Farmer and fisherman 61330 Cottar and fisherman 61400 Farm managers, foremen and supervisors nfs 62110 Farm workers, specialisation unknown 62113 Farmer's sons and other male relatives 62200 Farm workers (field crop and vegetables) 62300 Farm labourers, orchard and fruit farm workers 62410 Livestock workers, general or nfs 62420 Cattle workers, except specified dairy 62430 Sheep workers 62440 Pig workers 62450 Fur-bearing animal workers 62460 Horse workers 62461 Grooms and horse keepers (domestic) 62463 Grooms and horse keepers (not domestic) 62470 Horse breaker 62490 Livestock workers, nec 62500 Farm workers (dairy) 62600 Farm workers (poultry) 62710 Gardeners nfs 62711 Gardener (domestic) 62713 Gardener (not domestic) 62720 Market garden labourers 62730 Nursery labourers 62740 Landscape gardeners 62790 Other nursery workers and gardeners 62800 Farm machinery operators 62920 Other animal workers e.g., dogs, elephants 62930 Other plant workers e.g., gathers of herbs etc. 62940 Groundskeepers, etc. 62990 Others in agricultural or husbandry 63110 Woodsmen and workers in the woods, nfs 63120 Lumbermen, loggers and kindred workers 63130 River drivers 63140 Wood cutters and choppers 63190 Others in logging and wood cutting 63220 Foresters and wood wardens 63230 Forestry workers 63240 Timber cruisers 63250 Forest fire-fighters 63290 Other forestry workers 64100 Fishermen 64920 Fish farm workers 64930 Oyster farm workers 64940 Whale hunters 64950 Whale or seal hunters 64960 Seal hunters 64970 Trappers or hunters 64990 Other fishermen, hunters and related workers 71120 Miners 71130 Quarrymen 71190 Others working in mines and quarries 71200 Mineral or stone treaters 71300 Well drillers, borers and related workers 72000 Metal workers, specialisation unknown 72100 Metal smelter and furnacemen 72200 Metal rollers 72300 Metal melters and reheaters, and workers in metal melting mills 72400 Metal casters and workers in metal casting plants 72500 Metal moulders and coremakers 72600 Metal annealers, temperers and hardeners 72700 Metal drawers and workers in metal drawing 72800 Metal platers and coaters 72900 Other (specialised) metal workers 73100 Wood treaters 73200 Sawyers and other titled wood/sawmill operatives 73300 Papermill machine operators and paper makers 74000 Chemical workers, product nfs 74100 Drug workers 74200 Gunpowder and explosive makers 74320 Charcoal burners 74330 Coal gas makers 74340 Tar makers 74390 Other coal product makers e.g., coke 74420 Salt makers 74430 Alkali and soda makers 74500 Oil mill workers 74620 Paint and varnish makers 74630 Dye makers 74640 Ink, blacking, colouring, etc., makers 74720 Tallow chandlers, candle makers and grease makers 74730 Soap and perfume makers 74740 Glue, size and gelatine makers 74750 Wax and polish makers 74920 Fertilizer and manure makers 74930 Starch makers 74940 Turpentine makers 74990 Specified chemical workers nec 75000 Textile workers, specialisation unknown 75100 Fibre preparers 75200 Spinners, doublers, twisters and winders 75300 Weaving and knitting-machine setters and pattern-card preparers 75400 Weavers 75500 Knitters 75600 Bleachers, dyer or textile product finisher 75700 Rope makers 75920 Net maker 75990 Other specialised textile workers nec 76110 Tanners or fellmongers, specialisation unknown 76120 Fellmongers 76130 Tanners 76140 Leather curriers and finishers 76190 Other specified leather curers 76200 Fur and pelt dressers 77100 Millers and related workers 77200 Sugar refiners 77310 Butchers 77320 Pork butchers 77340 Slaughterer, meat cutters or meat packer 77350 Sausage makers 77360 Fish butchers 77380 Meat cannery workers and other meat preservers (not sausages) 77390 Other workers in meat preparation 77400 Cannery workers and other food preservers 77500 Butter, cheese and dairy product makers 77610 Baker and confectioner 77620 Bakers 77630 Confectioners and pastry makers 77640 Candy makers 77650 Chocolate makers 77690 Other baked goods makers 77700 Tea, coffee and cocoa preparers 77820 Brewers 77830 Maltsters 77840 Wine workers 77850 Vinegar makers and workers 77860 Distillers 77870 Makers of soft drinks 77880 Bottlers 77890 Other drinks makers and workers 77990 Other food and beverage processors 78100 Tobacco preparers and tobacco factory workers 78200 Cigar makers 78300 Cigarette makers 78400 Other tobacco product makers 79120 Tailors and tailoresses 79130 Dressmakers 79190 Other garment makers 79200 Furriers and fur workers 79320 Milliners 79330 Hat makers 79340 Straw hat makers 79390 Other hat makers 79400 Glove makers and related workers 79520 Seamstresses 79530 Sewers and sewing machine operators 79540 Embroiderers 79590 Others hand sewers 79620 Upholsterers (except vehicle) 79630 Vehicle trimmers and upholsterers 79640 Mattress makers 79690 Others working in upholstery jobs 79920 Sail, tent and awning makers 79930 Umbrella makers 79940 Artificial flower makers 79990 Other cloth and related product manufacturing workers 80100 Boot and shoe makers and repairers 80200 Specialised occupations in the boot and shoe making industry 80320 Saddlers and harness makers 80330 Trunk or bag maker 80390 Other leather goods makers 81120 Cabinet makers 81130 Chair makers 81140 Wicker furniture makers 81190 Other furniture makers 81210 Woodworkers 81220 Sawyers, woodworking 81230 Wood turners and handle makers 81240 Wood planers 81250 Wood carvers 81290 Other woodworking machine operators 81300 Coach, carriage and wagon makers 81400 Wheelwrights and cartwrights 81500 Coopers, hoop makers and benders 81600 Clog makers 81710 Box makers nfs 81720 Wooden box makers 81730 Paper box makers 81790 Box makers nec 81920 Wooden tool makers 81930 Ski makers 81990 Other makers of wooden products 82000 Stone carvers or cutters and stone yard workers 83120 Blacksmiths 83130 Hammersmiths 83140 Forgemen 83150 Farriers or horseshoers 83160 Specialised makers of forged metal products 83190 Other blacksmiths, hammermen and forgeing-press operators 83210 Tool makers nfs 83220 Tool and die makers 83230 Pattern makers nfs and nec 83290 Other tool makers and metal markers 83310 Metalworking machine operators 83320 Metal turners 83390 Other metal working machine operators 83400 Machinists 83520 Metal polishers and finishers 83530 Metal grinders and sharpeners 83540 Cutlers and cutting instrument makers 83550 Cutler (knives, forks, spoon) 83590 Other metal grinders, polishers and tool sharpeners nec 83600 Gunsmiths 83700 Locksmiths 83820 Saw makers 83830 Saw, spade, shovel and half wood/half metal agricultural instrument type things 83840 Chain makers 83850 Nailer and nail makers 83860 Wire makers 83890 Other metal workers nec 84110 Mechanics 84120 Millwrights 84130 Machine makers, builders and fitters 84140 Engine and locomotive builders 84150 Sewing machine makers and builders 84190 Other machinery fitters and machine assemblers 84220 Watch and clock makers 84230 Optical instrument makers and workers (not opticians) 84290 Other specialized instrument makers (not musical instrument makers) 84300 Bicycle makers 84400 Motor vehicle manufacturing and repair workers, specialization unknown 84460 Automobile manufacturing workers 84900 Others in machinery 85100 Electrical fitters and electrical equipment assemblers 85500 Electricians and wiremen 85600 Telephone and telegraph installers 85700 Linesmen: telephone, telegraph and electric 85920 Electrical products inspector or tester 85990 Other electrical fitters and related electrical workers 87120 Plumbers 87130 Pipe fitters 87220 Welders 87230 Braziers 87250 Flamecutter 87290 Other welders, braziers, solderers 87320 Sheet metal worker, general 87330 Coppersmith or copperware maker 87340 Tinsmith, tinner or tinker 87350 Boilermaker 87390 Other sheet metal workers 87420 Structural metal workers 87430 Rivetters nec 87490 Other structural metal preparers and erectors 87520 Ship and boat builders 87530 Shipwrights and ship joiners 87540 Ship's carpenters 87550 Block, mast and tackle makers 87560 Caulker 87590 Other ship builders 88020 Jewellers 88030 Goldsmith 88040 Silversmith 88050 Working with gems and stones 88090 Other jewellery and precious metal workers 89120 Glass makers 89130 Glass bottle makers 89190 Other specific glass makers 89200 Pottery and porcelain makers and workers 89300 Brick and tile makers 89400 Glass engravers, etchers and finishers 89500 Pottery and porcelain painters 89620 Cement makers 89630 Lime burners 89700 Clay-based products makers 90100 Rubber product makers 90200 Tire makers and vulcanisers 91020 Paper and paperboard products makers, except boxes 91090 Other paper product makers 91100 Paper and paper board product makers 92000 Printers nec 92110 Printers nfs 92120 Compositors 92190 Other compositors and typesetters 92200 Lithographic printers 92300 Stereotypers and electrotypers 92400 Lithographers 92500 Photo-engravers 92600 Bookbinders and related workers 92800 Textile printers 92900 Other printers and related workers 93110 Painters, nfs 93120 Painters, construction 93130 Painters, ship 93190 Other specialised painters nec 93200 Decorators 93320 Lacquerers and enamellers 93330 Japanners 93400 Gilders 94110 Musical instrument maker nfs 94120 Piano maker 94130 Piano tuner 94140 Organ builder 94190 Other musical instrument makers and tuner 94220 Basket makers 94230 Brush makers 94240 Broom makers 94290 Bristle and straw workers nec 94300 Non-metallic mineral product makers 94910 Other production or related worker, specialisation unknown 94920 Animal stuffers, taxidermists and shell workers 94930 Linoleum makers and floor cloth makers 94940 Toy and doll makers 94990 Production and related workers nec 95110 Mason nfs or combined 95120 Bricklayers 95130 Stone masons 95140 Plasterers 95150 Paviours 95160 Marble mason 95190 Others in construction 95200 Cement masons and finishers 95310 Roofer, specialisation unknown 95320 Slate and tile roofers 95330 Thatchers 95390 Other roofers 95410 Carpenter and joiner 95420 Carpenters 95430 Joiners 95440 Scaffolders 95490 Other wooden construction workers 95600 Pipe coverers and insulators 95700 Glaziers 95910 Construction workers nec 95920 Paperhangers 95930 Carpet planners 95940 Whitewashers 95950 Demolition workers 95960 Marblers 95990 Others in building construction 96100 Electricity generators 96220 Engineers (US) nfs 96230 Stationary engineers and engine men 96240 Stationary firemen and firemen nfs 96900 Other stationary engine and related equipment operators 97120 Ship boat loaders and dock workers 97130 Railway freight handlers 97140 Porters 97150 Packers 97190 Other freight handlers 97210 Riggers nec or nfs 97220 Ship riggers 97300 Crane and hoist operators 97410 Navvy, excavator and diggers, nfs 97420 Road builders, workers and labourers 97430 Railway builders, workers and labourers 97440 Waterway and harbour builders, workers and labourers 97490 Other road, railway and related construction labourers 97900 Material handling equipment operators nec 98120 Seamen 98130 Boatmen and canalmen 98190 Other crew of boats, ships, etc. 98200 Ship's engine men 98300 Railway/railroad locomotive operators 98320 Railway/railroad engineers and enginemen 98330 Railway/railroad firemen and stokers 98420 Railway brakemen 98430 Railway signallers 98440 Railway switchmen and shunters 98490 Others skilled railway workers 98510 Drivers, nec 98520 Drivers (private) 98530 Drivers (personal, for hire) 98540 Drivers (public) 98550 Delivery men and drivers of goods 98560 Drivers (general haulage) 98562 Carter (agricultural) 98570 Teamsters (inc. mine driver, etc.) 98590 Others drivers 98700 Lock and gate keepers 98720 Lock keepers 98730 Gate keepers 98900 Other transport equipment operators 99120 Labourers nfs 99130 Common labourers or general labourers 99140 Day labourers (e.g., journalier) 99150 Worker nfs 99200 Factory labourers (unspecified) 99300 Occupational title unclassifiable 99420 Assistants nfs 99430 Helpers nfs 99440 Helpers of relative or helping at home 99450 Apprentices nfs 99500 Ambiguous responses 99998 Alternative occupation (Sweden) 99999 No occupation/unknown Work Variables -- PERSON Person number (within household) Denmark 1845: All records This variable indicates the person number (within the household). 0000 Household record 0001 1 0002 2 0003 3 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 0100 100 0101 101 0102 102 0103 103 0104 104 0105 105 0106 106 0107 107 0108 108 0109 109 0110 110 0111 111 0112 112 0113 113 0114 114 0115 115 0116 116 0117 117 0118 118 0119 119 0120 120 0121 121 0122 122 0123 123 0124 124 0125 125 0126 126 0127 127 0128 128 0129 129 0130 130 0131 131 0132 132 0133 133 0134 134 0135 135 0136 136 0137 137 0138 138 0139 139 0140 140 0141 141 0142 142 0143 143 0144 144 0145 145 0146 146 0147 147 0148 148 0149 149 0150 150 0151 151 0152 152 0153 153 0154 154 0155 155 0156 156 0157 157 0158 158 0159 159 0160 160 0161 161 0162 162 0163 163 0164 164 0165 165 0166 166 0167 167 0168 168 0169 169 0170 170 0171 171 0172 172 0173 173 0174 174 0175 175 0176 176 0177 177 0178 178 0179 179 0180 180 0181 181 0182 182 0183 183 0184 184 0185 185 0186 186 0187 187 0188 188 0189 189 0190 190 0191 191 0192 192 0193 193 0194 194 0195 195 0196 196 0197 197 0198 198 0199 199 0200 200 0201 201 0202 202 0203 203 0204 204 0205 205 0206 206 0207 207 0208 208 0209 209 0210 210 0211 211 0212 212 0213 213 0214 214 0215 215 0216 216 0217 217 0218 218 0219 219 0220 220 0221 221 0222 222 0223 223 0224 224 0225 225 0226 226 0227 227 0228 228 0229 229 0230 230 0231 231 0232 232 0233 233 0234 234 0235 235 0236 236 0237 237 0238 238 0239 239 0240 240 0241 241 0242 242 0243 243 0244 244 0245 245 0246 246 0247 247 0248 248 0249 249 0250 250 0251 251 0252 252 0253 253 0254 254 0255 255 0256 256 0257 257 0258 258 0259 259 0260 260 0261 261 0262 262 0263 263 0264 264 0265 265 0266 266 0267 267 0268 268 0269 269 0270 270 0271 271 0272 272 0273 273 0274 274 0275 275 0276 276 0277 277 0278 278 0279 279 0280 280 0281 281 0282 282 0283 283 0284 284 0285 285 0286 286 0287 287 0288 288 0289 289 0290 290 0291 291 0292 292 0293 293 0294 294 0295 295 0296 296 0297 297 0298 298 0299 299 0300 300 0301 301 0302 302 0303 303 0304 304 0305 305 0306 306 0307 307 0308 308 0309 309 0310 310 0311 311 0312 312 0313 313 0314 314 0315 315 0316 316 0317 317 0318 318 0319 319 0320 320 0321 321 0322 322 0323 323 0324 324 0325 325 0326 326 0327 327 0328 328 0329 329 0330 330 0331 331 0332 332 0333 333 0334 334 0335 335 0336 336 0337 337 0338 338 0339 339 0340 340 0341 341 0342 342 0343 343 0344 344 0345 345 0346 346 0347 347 0348 348 0349 349 0350 350 0351 351 0352 352 0353 353 0354 354 0355 355 0356 356 0357 357 0358 358 0359 359 0360 360 0361 361 0362 362 0363 363 0364 364 0365 365 0366 366 0367 367 0368 368 0369 369 0370 370 0371 371 0372 372 0373 373 0374 374 0375 375 0376 376 0377 377 0378 378 0379 379 0380 380 0381 381 0382 382 0383 383 0384 384 0385 385 0386 386 0387 387 0388 388 0389 389 0390 390 0391 391 0392 392 0393 393 0394 394 0395 395 0396 396 0397 397 0398 398 0399 399 0400 400 0401 401 0402 402 0403 403 0404 404 0405 405 0406 406 0407 407 0408 408 0409 409 0410 410 0411 411 0412 412 0413 413 0414 414 0415 415 0416 416 0417 417 0418 418 0419 419 0420 420 0421 421 0422 422 0423 423 0424 424 0425 425 0426 426 0427 427 0428 428 0429 429 0430 430 0431 431 0432 432 0433 433 0434 434 0435 435 0436 436 0437 437 0438 438 0439 439 0440 440 0441 441 0442 442 0443 443 0444 444 0445 445 0446 446 0447 447 0448 448 0449 449 0450 450 0451 451 0452 452 0453 453 0454 454 0455 455 0456 456 0457 457 0458 458 0459 459 0460 460 0461 461 0462 462 0463 463 0464 464 0465 465 0466 466 0467 467 0468 468 0469 469 0470 470 0471 471 0472 472 0473 473 0474 474 0475 475 0476 476 0477 477 0478 478 0479 479 0480 480 0481 481 0482 482 0483 483 0484 484 0485 485 0486 486 0487 487 0488 488 0489 489 0490 490 0491 491 0492 492 0493 493 0494 494 0495 495 0496 496 0497 497 0498 498 0499 499 0500 500 0501 501 0502 502 0503 503 0504 504 0505 505 0506 506 0507 507 0508 508 0509 509 0510 510 0511 511 0512 512 0513 513 0514 514 0515 515 0516 516 0517 517 0518 518 0519 519 0520 520 0521 521 0522 522 0523 523 0524 524 0525 525 0526 526 0527 527 0528 528 0529 529 0530 530 0531 531 0532 532 0533 533 0534 534 0535 535 0536 536 0537 537 0538 538 0539 539 0540 540 0541 541 0542 542 0543 543 0544 544 0545 545 0546 546 0547 547 0548 548 0549 549 0550 550 0551 551 0552 552 0553 553 0554 554 0555 555 0556 556 0557 557 0558 558 0559 559 0560 560 0561 561 0562 562 0563 563 0564 564 0565 565 0566 566 0567 567 0568 568 0569 569 0570 570 0571 571 0572 572 0573 573 0574 574 0575 575 0576 576 0577 577 0578 578 0579 579 0580 580 0581 581 0582 582 0583 583 0584 584 0585 585 0586 586 0587 587 0588 588 0589 589 0590 590 0591 591 0592 592 0593 593 0594 594 0595 595 0596 596 0597 597 0598 598 0599 599 0600 600 0601 601 0602 602 0603 603 0604 604 0605 605 0606 606 0607 607 0608 608 0609 609 0610 610 0611 611 0612 612 0613 613 0614 614 0615 615 0616 616 0617 617 0618 618 0619 619 0620 620 0621 621 0622 622 0623 623 0624 624 0625 625 0626 626 0627 627 0628 628 0629 629 0630 630 0631 631 0632 632 0633 633 0634 634 0635 635 0636 636 0637 637 0638 638 0639 639 0640 640 0641 641 0642 642 0643 643 0644 644 0645 645 0646 646 0647 647 0648 648 0649 649 0650 650 0651 651 0652 652 0653 653 0654 654 0655 655 0656 656 0657 657 0658 658 0659 659 0660 660 0661 661 0662 662 0663 663 0664 664 0665 665 0666 666 0667 667 0668 668 0669 669 0670 670 0671 671 0672 672 0673 673 0674 674 0675 675 0676 676 0677 677 0678 678 0679 679 0680 680 0681 681 0682 682 0683 683 0684 684 0685 685 0686 686 0687 687 0688 688 0689 689 0690 690 0691 691 0692 692 0693 693 0694 694 0695 695 0696 696 0697 697 0698 698 0699 699 0700 700 0701 701 0702 702 0703 703 0704 704 0705 705 0706 706 0707 707 0708 708 0709 709 0710 710 0711 711 0712 712 0713 713 0714 714 0715 715 0716 716 0717 717 0718 718 0719 719 0720 720 0721 721 0722 722 0723 723 0724 724 0725 725 0726 726 0727 727 0728 728 0729 729 0730 730 0731 731 0732 732 0733 733 0734 734 0735 735 0736 736 0737 737 0738 738 0739 739 0740 740 0741 741 0742 742 0743 743 0744 744 0745 745 0746 746 0747 747 0748 748 0749 749 0750 750 0751 751 0752 752 0753 753 0754 754 0755 755 0756 756 0757 757 0758 758 0759 759 0760 760 0761 761 0762 762 0763 763 0764 764 0765 765 0766 766 0767 767 0768 768 0769 769 0770 770 0771 771 0772 772 0773 773 0774 774 0775 775 0776 776 0777 777 0778 778 0779 779 0780 780 0781 781 0782 782 0783 783 0784 784 0785 785 0786 786 0787 787 0788 788 0789 789 0790 790 0791 791 0792 792 0793 793 0794 794 0795 795 0796 796 0797 797 0798 798 0799 799 0800 800 0801 801 0802 802 0803 803 0804 804 0805 805 0806 806 0807 807 0808 808 0809 809 0810 810 0811 811 0812 812 0813 813 0814 814 0815 815 0816 816 0817 817 0818 818 0819 819 0820 820 0821 821 0822 822 0823 823 0824 824 0825 825 0826 826 0827 827 0828 828 0829 829 0830 830 0831 831 0832 832 0833 833 0834 834 0835 835 0836 836 0837 837 0838 838 0839 839 0840 840 0841 841 0842 842 0843 843 0844 844 0845 845 0846 846 0847 847 0848 848 0849 849 0850 850 0851 851 0852 852 0853 853 0854 854 0855 855 0856 856 0857 857 0858 858 0859 859 0860 860 0861 861 0862 862 0863 863 0864 864 0865 865 0866 866 0867 867 0868 868 0869 869 0870 870 0871 871 0872 872 0873 873 0874 874 0875 875 0876 876 0877 877 0878 878 0879 879 0880 880 0881 881 0882 882 0883 883 0884 884 0885 885 0886 886 0887 887 0888 888 0889 889 0890 890 0891 891 0892 892 0893 893 0894 894 0895 895 0896 896 0897 897 0898 898 0899 899 0900 900 0901 901 0902 902 0903 903 0904 904 0905 905 0906 906 0907 907 0908 908 0909 909 0910 910 0911 911 0912 912 0913 913 0914 914 0915 915 0916 916 0917 917 0918 918 0919 919 0920 920 0921 921 0922 922 0923 923 0924 924 0925 925 0926 926 0927 927 0928 928 0929 929 0930 930 0931 931 0932 932 0933 933 0934 934 0935 935 0936 936 0937 937 0938 938 0939 939 0940 940 0941 941 0942 942 0943 943 0944 944 0945 945 0946 946 0947 947 0948 948 0949 949 0950 950 0951 951 0952 952 0953 953 0954 954 0955 955 0956 956 0957 957 0958 958 0959 959 0960 960 0961 961 0962 962 0963 963 0964 964 0965 965 0966 966 0967 967 0968 968 0969 969 0970 970 0971 971 0972 972 0973 973 0974 974 0975 975 0976 976 0977 977 0978 978 0979 979 0980 980 0981 981 0982 982 0983 983 0984 984 0985 985 0986 986 0987 987 0988 988 0989 989 0990 990 0991 991 0992 992 0993 993 0994 994 0995 995 0996 996 0997 997 0998 998 0999 999 1000 1000 1001 1001 1002 1002 1003 1003 1004 1004 1005 1005 1006 1006 1007 1007 1008 1008 1009 1009 1010 1010 1011 1011 1012 1012 1013 1013 1014 1014 1015 1015 1016 1016 1017 1017 1018 1018 1019 1019 1020 1020 1021 1021 1022 1022 1023 1023 1024 1024 1025 1025 1026 1026 1027 1027 1028 1028 1029 1029 1030 1030 1031 1031 1032 1032 1033 1033 1034 1034 1035 1035 1036 1036 1037 1037 1038 1038 1039 1039 1040 1040 1041 1041 1042 1042 1043 1043 1044 1044 1045 1045 1046 1046 1047 1047 1048 1048 1049 1049 1050 1050 1051 1051 1052 1052 1053 1053 1054 1054 1055 1055 1056 1056 1057 1057 1058 1058 1059 1059 1060 1060 1061 1061 1062 1062 1063 1063 1064 1064 1065 1065 1066 1066 1067 1067 1068 1068 1069 1069 1070 1070 1071 1071 1072 1072 1073 1073 1074 1074 1075 1075 1076 1076 1077 1077 1078 1078 1079 1079 1080 1080 1081 1081 1082 1082 1083 1083 1084 1084 1085 1085 1086 1086 1087 1087 1088 1088 1089 1089 1090 1090 1091 1091 1092 1092 1093 1093 1094 1094 1095 1095 1096 1096 1097 1097 1098 1098 1099 1099 1100 1100 1101 1101 1102 1102 1103 1103 1104 1104 1105 1105 1106 1106 1107 1107 1108 1108 1109 1109 1110 1110 1111 1111 1112 1112 1113 1113 1114 1114 1115 1115 1116 1116 1117 1117 1118 1118 1119 1119 1120 1120 1121 1121 1122 1122 1123 1123 1124 1124 1125 1125 1126 1126 1127 1127 1128 1128 1129 1129 1130 1130 1131 1131 1132 1132 1133 1133 1134 1134 1135 1135 1136 1136 1137 1137 1138 1138 1139 1139 1140 1140 1141 1141 1142 1142 1143 1143 1144 1144 1145 1145 1146 1146 1147 1147 1148 1148 1149 1149 1150 1150 1151 1151 1152 1152 1153 1153 1154 1154 1155 1155 1156 1156 1157 1157 1158 1158 1159 1159 1160 1160 1161 1161 1162 1162 1163 1163 1164 1164 1165 1165 1166 1166 1167 1167 1168 1168 1169 1169 1170 1170 1171 1171 1172 1172 1173 1173 1174 1174 1175 1175 1176 1176 1177 1177 1178 1178 1179 1179 1180 1180 1181 1181 1182 1182 1183 1183 1184 1184 1185 1185 1186 1186 1187 1187 1188 1188 1189 1189 1190 1190 1191 1191 1192 1192 1193 1193 1194 1194 1195 1195 1196 1196 1197 1197 1198 1198 1199 1199 1200 1200 1201 1201 1202 1202 1203 1203 1204 1204 1205 1205 1206 1206 1207 1207 1208 1208 1209 1209 1210 1210 1211 1211 1212 1212 1213 1213 1214 1214 1215 1215 1216 1216 1217 1217 1218 1218 1219 1219 1220 1220 1221 1221 1222 1222 1223 1223 1224 1224 1225 1225 1226 1226 1227 1227 1228 1228 1229 1229 1230 1230 1231 1231 1232 1232 1233 1233 1234 1234 1235 1235 1236 1236 1237 1237 1238 1238 1239 1239 1240 1240 1241 1241 1242 1242 1243 1243 1244 1244 1245 1245 1246 1246 1247 1247 1248 1248 1249 1249 1250 1250 1251 1251 1252 1252 1253 1253 1254 1254 1255 1255 1256 1256 1257 1257 1258 1258 1259 1259 1260 1260 1261 1261 1262 1262 1263 1263 1264 1264 1265 1265 1266 1266 1267 1267 1268 1268 1269 1269 1270 1270 1271 1271 1272 1272 1273 1273 1274 1274 1275 1275 1276 1276 1277 1277 1278 1278 1279 1279 1280 1280 1281 1281 1282 1282 1283 1283 1284 1284 1285 1285 1286 1286 1287 1287 1288 1288 1289 1289 1290 1290 1291 1291 1292 1292 1293 1293 1294 1294 1295 1295 1296 1296 1297 1297 1298 1298 1299 1299 1300 1300 1301 1301 1302 1302 1303 1303 1304 1304 1305 1305 1306 1306 1307 1307 1308 1308 1309 1309 1310 1310 1311 1311 1312 1312 1313 1313 1314 1314 1315 1315 1316 1316 1317 1317 1318 1318 1319 1319 1320 1320 1321 1321 1322 1322 1323 1323 1324 1324 1325 1325 1326 1326 1327 1327 1328 1328 1329 1329 1330 1330 1331 1331 1332 1332 1333 1333 1334 1334 1335 1335 1336 1336 1337 1337 1338 1338 1339 1339 1340 1340 1341 1341 1342 1342 1343 1343 1344 1344 1345 1345 1346 1346 1347 1347 1348 1348 1349 1349 1350 1350 1351 1351 1352 1352 1353 1353 1354 1354 1355 1355 1356 1356 1357 1357 1358 1358 1359 1359 1360 1360 1361 1361 1362 1362 1363 1363 1364 1364 1365 1365 1366 1366 1367 1367 1368 1368 1369 1369 1370 1370 1371 1371 1372 1372 1373 1373 1374 1374 1375 1375 1376 1376 1377 1377 1378 1378 1379 1379 1380 1380 1381 1381 1382 1382 1383 1383 1384 1384 1385 1385 1386 1386 1387 1387 1388 1388 1389 1389 1390 1390 1391 1391 1392 1392 1393 1393 1394 1394 1395 1395 1396 1396 1397 1397 1398 1398 1399 1399 1400 1400 1401 1401 1402 1402 1403 1403 1404 1404 1405 1405 1406 1406 1407 1407 1408 1408 1409 1409 1410 1410 1411 1411 1412 1412 1413 1413 1414 1414 1415 1415 1416 1416 1417 1417 1418 1418 1419 1419 Technical Person Variables -- PERSON Name of person (string) The names of every person in every farm, every house, and every family ____ Name:</p> <div class="i1">Name of the person.</div> Denmark 1845: All persons This variable indicates the name of the person. This is a 96-digit numeric variable with 0 implied decimal places Other Person Variables -- PERSON Sex Gender:</p> <div class="i1">Gender of the person.</div> Denmark 1845: All persons This variable indicates the sex of the person. 1 Male 2 Female 9 Unknown Demographic Variables -- PERSON Age (at next birthday) The age of every person, the current year included ____ Age:</p> <div class="i1">Age is not the age you have but the next age, e.g. you are 25 then you will be stated as 26. New born should have the age: 1.</div> Denmark 1845: All persons This variable indicates the person's age at next birthday. 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 99 100 100 101 101 102 102 103 103 104 104 106 106 years 999 Unknown Demographic Variables -- PERSON Marital status Married, unmarried, widower or widow ____ Marital status:</p> <div class="i1">Marital status.</div> Denmark 1845: All persons This variable indicates the marital status of the person. 1 Unmarried 2 Married 3 Widowed 9 Unknown Demographic Variables -- PERSON Town or parish of birth (string) Place of birth ____</p> <div class="i1">That is the name of the town and in the countryside, and name of the parish and county</div> Birthplace:</p> <div class="i1">Name of town or parish where the person was born.</div> Denmark 1845: All persons This variable indicates the person's town or parish of birth. This is a 100-digit numeric variable with 0 implied decimal places Nativity and Birthplace Variables -- PERSON Relationship to head of household Position in the household:</p> <div class="i1">Position in household in relation to the head of household.</div> Denmark 1845: All persons This variable indicates the person's relationship to the household head. 001 Head of household 002 Spouse 003 Co-owner 004 Spouse of co-owner 005 Common child 006 Separate child 007 Separate child of spouse 008 Foster child 009 Parent 010 Sibling 011 Parent of spouse 012 Sibling of spouse 013 Child of sibling of spouse 014 Spouse of common child 015 Spouse of separate child 016 Spouse of parent 017 Servant 018 Lodger 019 Spouse of lodger 020 Child of lodger 021 Resident 022 Child of resident 023 Room renter 024 Spouse of parent of spouse 025 Child of common child 026 Housekeeper 027 Widow 028 In-house 029 Servant of lodger 030 Child of separate child 031 Apprentice 032 Sibling of parent 033 Sibling of parent of spouse 034 Child of servant 035 Child of sibling 036 Journeyman 037 Child of room renter 038 Child of separate child of spouse 039 Quartered 040 Servant of resident 041 Spouse of servant 042 Spouse of room renter 043 Child of widow 044 Spouse of separate child of spouse 045 Spouse of resident 046 Child of in-house 047 Pensioner ("aftægt") 048 Spouse of sibling 049 Head clerk 050 Working boy 051 Book keeper 052 Administrative employee 053 Professional employee 054 Master of court 055 Spouse of pensioner ("aftægt") 056 Spouse of in-house 057 Child of pensioner ("aftægt") 058 Servant by pensioner ("aftægt") 059 Spouse of quartered 060 Member or prisoner 061 Parent of former spouse 062 Separate child of former spouse of spouse 063 Family 064 Servant of room renter 066 Child of member or prisoner 067 Servant of parent 068 Grandparent 069 Child of housekeeper 070 Child of quartered 071 Grandchild of lodger 072 Spouse of sibling of parent 073 Grandchild of sibling 074 Parent of former spouse of spouse 075 Separate child of separate child of spouse 077 Spouse of child of room renter 078 Servant of widow 081 Fiancée 082 Spouse of member or prisoner 083 Child of sibling of parent 084 Grandparent of spouse 085 Sibling of parent of former spouse 086 Sibling of former spouse 087 Separate child of former spouse 089 Sibling of parent of spouse of separate child 090 Grandchild of in-house 091 Grandchild of room renter 092 Spouse of sibling of spouse 093 Separate child of former spouse 094 Child of sibling of lodger 102 Child of co-owner 103 Foster child of parent 106 Sibling of spouse of sibling 107 Foster parent 108 Foster parent of spouse 111 Family of spouse 112 Pupils at institute or like 113 Separate child of spouse of common child 114 Child of sibling of parent of spouse 115 Poor or receiver of charity 117 Servant by quartered 118 Spouse of child of sibling 119 Sibling of resident 127 Day-labourer 128 Child of sibling of former spouse 129 Child of foster child 131 Servant by co-owner 132 Spouse of journeyman 133 Sibling of in-house 134 Sweetheart 136 Child of poor or receiver of charity 137 Sibling of room renter 138 Foster child of widow 139 Foster child of lodger 140 Sibling of lodger 141 Spouse of poor or receiver of charity 144 Spouse of sibling of former spouse 145 Spouse of separate child of former spouse 146 Grand child of poor or receiver of charity 147 Separate child of fiancée 148 Separate child of sweetheart 149 Child of day-labourer 150 Spouse of day-labourer 151 Grandchild of widow 152 Foster child of poor or receiver of charity 153 Pensioner 154 Servant by pensioner 155 Child of separate child of former spouse of spouse 156 Child of Journeyman 158 Child of sibling of room renter 159 Manager 161 Servant by manager 162 Sibling of former spouse of spouse 163 Master 165 Child of sibling of widow 166 Relative of lodger 167 Grandchild of house keeper 169 Separate child of former spouse of widow 175 Parent of spouse of separate child 179 Child of family 181 Sibling of widow 182 Child of pensioner 184 Grandchild of member or prisoner 186 Child of professional employee 187 Collegians 188 Sibling of co-owner 189 Spouse of pensioner 190 Sibling of servant 191 Parent of spouse of co-owner 193 Servant of in-house 195 Sibling of pensioner ("aftægt") 196 Separate child of spouse of parent 202 Servant of common child 204 Spouse of manager 205 Sibling of spouse of common child 212 Child of sibling of pensioner ("aftægt") 214 Parent of servant 216 Spouse of master of court 217 Child of master of court 221 Child of manager 222 Spouse of foster child 223 Foster child by member or prisoner 226 Handicapped 228 Fiancée of common child 230 Spouse of administrative employee 232 Sibling of manager 233 Spouse of professional employee 236 Parent of member or prisoner 244 Fiancée of separate child 246 Child of family of spouse 249 Grandchild of separate child 250 Spouse of family 251 Parent of house keeper 253 Sibling of poor or receiver of charity 254 Sibling of spouse of resident 260 Sibling of spouse of in-house 269 Separate child of spouse of sibling 276 Child of administrative employee 278 Sibling of Spouse of Quartered 281 Grandchild of pensioneer ("aftægt") 282 Foster child of lodger ("indsidder") 283 Housekeeper by pensioneer ("aftægt") 284 Foster child of seperate child 285 Child of spouse of pensioneer ("aftægt") 286 Child of sibling of manager 289 Parent of lodger ("indsidder") 290 Child of sibling of present ("til huse") 291 Child of spouse of lodger ("indsidder") 294 Spouse of head clerk 295 Child of head clerk 298 Parent of present ("til huse") 301 Sibling of fiance 302 Sibling of pensioneer 303 Parent of spouse of lodger ("indsidder") 305 Parent of manager 309 Child of father 310 Child of mother 313 Foster child of pensioneer ("aftægt") 314 Separate child of spouse of parent of spouse 320 Spouse of grandchild 322 Child of sibling of servant 324 Ward 326 Child of sibling of housekeeper 328 Supported 330 Fiance of room renter 331 Grandchild of sibling of room renter 332 Foster child of in-house by household 334 Previous wife 335 Parent of spouse of sibling 338 Professional employee of room renter 340 Foster child of manager 341 Sibling of spouse of manager 344 Foster child of daylabourer 347 Child of supported 348 Sibling of spouse of pensioneer ("aftægt") 350 Spouse of child of day-labourer 351 Separate child of fiancée of child 353 Grandchild of pensionerd 355 Foster child of resident 357 Foster child of pensioner 359 Spouse of child of manager 361 Grandchild of manager 362 Foster child of child of manager 363 Foster child of sibling 365 Apprentice of lodger 366 Foster child of child 369 Sibling of housekeeper 370 Grandchild of Day-labourer 999 Unknown Demographic Variables -- PERSON Occupation (string) Title, office, business, handicraft, occupation, position in the family or what they live by ____ Occupation:</p> <div class="i1">Occupation as stated in the census in Danish.</div> Denmark 1845: All persons This variable indicates the person's occupation. This is a 150-digit numeric variable with 0 implied decimal places Work: Occupation Variables -- PERSON Nationality Nationality:</p> <div class="i1">Nationality. Here da=Danish.</div> Denmark 1845: All persons This variable indicates the person's nationality. 1 Danish Nativity and Birthplace Variables -- PERSON Primary occupation (2-digit OCCHISCO) Title, office, business, handicraft, occupation, position in the family or what they live by ____ Occupation:</p> <div class="i1">Occupation as stated in the census in Danish.</div> Denmark 1845: All persons This variable indicates the primary occupation of the person. This variable is encoded to NAPP HISCO codes using the string variable. 003 Architects, engineers and related technicians 004 Aircraft and ships' officers 005 Life scientists and related technicians 006 Medical, dental, veterinary and related workers 007 Medical, dental, veterinary and related workers 009 Economists 012 Jurists 013 Teachers 014 Workers in religion 015 Authors, journalists and related writers 016 Sculptors, painters, photographers and related creative artists 017 Composers and performing artists 019 Professional, technical and related workers, not elsewhere classified 020 Legislative officials and government administrators 021 Managers 022 Superintendents and managers 023 Foremen and supervisors 031 Government executive officials 032 Typists, stenographers and secretaries 033 Bookkeepers, cashiers and related workers 036 Transport conductors 037 Mail distribution clerks 038 Telephone and telegraph operators 039 Clerical and related workers, not elsewhere classified 041 Working proprietors (wholesale and retail trade) 043 Technical salesmen, commercial travellers and manufacturers agents 044 Insurance, real estate, securities and business services salesmen and auctioneers 045 Salesmen, shop assistants and related workers 049 Sales workers, not elsewhere classified 051 Working proprietors (catering, lodging and leisure services) 052 Housekeeping workers 053 Cooks, waiters, bartenders and related workers 054 Maids and related housekeeping service workers, not elsewhere classified 055 Building caretakers, charworkers, cleaners and related workers 056 Launderers, dry-cleaners and pressers 057 Hairdressers, barbers, beauticians and related workers 058 Protective service workers 059 Service workers, not elsewhere classified 061 Farmers 062 Agricultural and animal husbandry workers 063 Forestry workers 064 Fishermen, hunters and related workers 071 Miners, quarrymen, well-drillers and related workers 072 Metal processors 074 Chemical processors and related workers 075 Spinners, weavers, knitters, dyers and related workers 076 Tanners, fellmongers and pelt dressers 077 Food and beverage processors 078 Tobacco preparers and tobacco product makers 079 Tailors, dressmakers, sewers, upholsterers and related workers 080 Shoemakers and leather goods makers 081 Cabinetmakers and related woodworkers 083 Blacksmiths, toolmakers and machine-tool operators 084 Machinery fitters, machine assemblers and precision-instrument makers (except electrical) 087 Plumbers, welders, sheet-metal, and structural metal preparers and erectors 088 Jewellers and precious metal workers 089 Glass formers, potters and related workers 091 Paper and paperboard products makers 092 Printers and related workers 093 Painters 094 Production and related workers, not elsewhere classified 095 Bricklayers, carpenters and other construction workers 096 Stationary engine and related equipment operators 097 Material handling and related equipment operators, dockers and freight handlers 098 Transport equipment operators 099 Workers, not elsewhere classified 999 No occupation reported or unknown Work: Occupation Variables -- PERSON Primary occupation (5-digit OCCHISCO) Title, office, business, handicraft, occupation, position in the family or what they live by ____ Occupation:</p> <div class="i1">Occupation as stated in the census in Danish.</div> Denmark 1845: All persons This variable indicates the secondary occupation of the person. This variable is encoded to NAPP HISCO codes using the string variable. 03020 Land surveyors 04220 Ship's masters and captains (sea) 04230 Ship's masters and captains (sea or inland waterways) 04260 Ship and boat pilots 05200 Medical scientists 06110 Medical doctors and physicians 06130 Surgeons 06200 Dentists 06300 Veterinarians 06400 Pharmacists 07210 Nurses, not further specified 07220 Medical nurses, untrained or level of training unknown 07320 Midwives 07500 Opticians and optometrists 07990 Other medical, dental, veterinary and related workers 09000 Economists 12110 Lawyers 12200 Judge 12300 Notary 12900 Jurists (except lawyer, judge or solicitor) 13100 Teachers in higher education 13210 Teachers (unspecified) 13300 School administrators and principals 14120 Ministers of religion 14140 Members of religious orders 14900 Workers in religion, not elsewhere classified 15100 Authors 15220 Editors 15230 Journalists, reporters and correspondents 16120 Sculptors 16130 Artistic painters 16400 Engravers 17120 Musical performers and musicians, not further specified 17130 Music teachers 17200 Dancers and dancing teachers 17300 Actors and related workers 17500 Artist 19100 Librarians, archivists and curators 19500 Interpreters, translators and philologists 20100 Legislative officials and heads of government 20200 Government administrators 21130 Manufacturers or proprietors of specified manufacturing concerns 21160 Proprietor, other transport and communications 22110 Superintendents and managers, not further specified 22120 Superintendents and managers, manufacturing 22190 Superintendents and managers, not elsewhere clssified 23110 Foremen and supervisors, not further specified 31010 Civil servants, title unknown 31020 Tax collectors 31040 Customs officers 31050 Postmasters or postmistresses 31090 Government functionaries, not elsewhere clssified 32000 Typists, stenographers and secretaries 33120 Bookkeepers and bookkeeping clerks 33130 Cashiers, bank or office 33140 Bank clerks 36010 Conductors, not further specified 37020 Postal, mail and telegraph clerks 37030 Mail carriers, aka postmen (UK) 37040 Messengers 38030 Telegraph operator 39000 Clerk, not further specified 39100 Stock, weight and shipping clerks 39130 Stock records clerk 39310 Office clerks, specialisation unknown 39320 Correspondence clerks 39340 Legal clerks 39900 Other specified clerks 41010 Dealer, merchant etc. (wholesale and retail trade) 41015 Merchants, specified large-scale wholesaleing 43030 Manufacturers and sales agents 44140 Brokers 44320 Auctioneers 45120 Salespeople, wholesale or retail trade 45190 Other sales personnel men, shop assistants and demonstrators 45220 Street sellers, pedlars and hawkers, non-food items 45240 Newsvendors 49090 Dealers and salesworkers, not elsewhere classified 51030 Restaurant keepers and managers 51040 Boarding and lodging house keepers and managers 51090 Other hospitality and entertainment keepers and managers 52020 Housekeeper 52040 Matrons 53100 Cooks 53220 Waiter or waitress 53290 Other food and drink service workers 54020 House servants not further specified and maids 54030 Personal servants and valets 54040 Nursemaids 54050 Companions 55240 Chimney sweeps 55250 Refuse collectors and removers 56000 Washing and laundry services 57030 Barbers 57040 Bath attendants 58100 Firefighters 58220 Policemen and detectives, public service 58410 Military, rank unknown 58420 Military officers 58500 Prison keepers and guards 58900 Other protective service workers 59200 Undertakers and embalmers 59980 Cellarman 61110 General farmers and farmers, not further specified 61115 Husbandmen or cottars 61120 Major landowner 61290 Other specialised farmers 61400 Farm managers, foremen and supervisors, not further specified 62200 Farm workers (field crop and vegetables) 62300 Farm labourers, orchard and fruit farm workers 62410 Livestock workers, general or not further specified 62420 Cattle workers, except specified dairy 62430 Sheep workers 62450 Fur-bearing animal workers 62490 Livestock workers, not elsewhere clssified 62600 Farm workers (poultry) 62711 Gardener (domestic) 62713 Gardener (not domestic) 63110 Woodsmen and workers in the woods, not further specified 63220 Foresters and wood wardens 63230 Forestry workers 63290 Other forestry workers 64100 Fishermen 64970 Trappers or hunters 71130 Quarrymen 71300 Well drillers, borers and related workers 72000 Metal workers, specialisation unknown 72100 Metal smelter and furnacemen 72400 Metal casters and workers in metal casting plants 72500 Metal moulders and coremakers 74320 Charcoal burners 74490 Distillery apprentice 74720 Tallow chandlers, candle makers and grease makers 74730 Soap and perfume makers 75100 Fibre preparers 75200 Spinners, doublers, twisters and winders 75400 Weavers 75500 Knitters 75600 Bleachers, dyer or textile product finisher 75700 Rope makers 75990 Other specialised textile workers, not elsewhere classified 76130 Tanners 77100 Millers and related workers 77200 Sugar refiners 77310 Butchers 77400 Cannery workers and other food preservers 77500 Butter, cheese and dairy product makers 77620 Bakers 77630 Confectioners and pastry makers 77820 Brewers 77830 Maltsters 77860 Distillers 77990 Other food and beverage processors 78100 Tobacco preparers and tobacco factory workers 78200 Cigar makers 79120 Tailors and tailoresses 79200 Furriers and fur workers 79330 Hat makers 79400 Glove makers and related workers 79520 Seamstresses 79590 Others hand sewers 79920 Sail, tent and awning makers 80100 Boot and shoe makers and repairers 80200 Specialised occupations in the boot and shoe making industry 80320 Saddlers and harness makers 81120 Cabinet makers 81130 Chair makers 81230 Wood turners and handle makers 81300 Coach, carriage and wagon makers 81500 Coopers, hoop makers and benders 81600 Clog makers 81990 Other makers of wooden products 83120 Blacksmiths 83520 Metal polishers and finishers 83550 Cutler (knives, forks, spoon) 83600 Gunsmiths 83890 Other metal workers, not elsewhere classified 84110 Mechanics 84220 Watch and clock makers 84290 Other specialized instrument makers (not musical instrument makers) 87230 Braziers 87290 Other welders, braziers, solderers 87330 Coppersmith or copperware maker 87340 Tinsmith, tinner or tinker 87520 Ship and boat builders 88030 Goldsmith 89120 Glass makers 89200 Pottery and porcelain makers and workers 89300 Brick and tile makers 89630 Lime burners 91020 Paper and paperboard products makers, except boxes 92000 Printers, not elsewhere classified 92110 Printers, not further specified 92400 Lithographers 92600 Bookbinders and related workers 93110 Painters, not further specified 94110 Musical instrument maker, not further specified 94140 Organ builder 94220 Basket makers 94230 Brush makers 94240 Broom makers 94990 Production and related workers, not elsewhere classified 95120 Bricklayers 95150 Paviours 95190 Others in construction 95200 Cement masons and finishers 95330 Thatchers 95410 Carpenter and joiner 95700 Glaziers 95990 Others in building construction 96230 Stationary engineers and engine men 96900 Other stationary engine and related equipment operators 97140 Porters 97150 Packers 97440 Waterway and harbour builders, workers and labourers 98120 Seamen 98130 Boatmen and canalmen 98190 Other crew of boats, ships, etc. 98510 Drivers, not elsewhere clssified 98520 Drivers (private) 98730 Gate keepers 98900 Other transport equipment operators 99120 Labourers, not further specified 99140 Day labourers (e.g., journalier) 99150 Worker, not further specified 99200 Factory labourers (unspecified) 99999 No occupation reported or unknown Work: Occupation Variables -- PERSON Secondary occupation (2-digit OCCHISCO) Title, office, business, handicraft, occupation, position in the family or what they live by ____ Occupation:</p> <div class="i1">Occupation as stated in the census in Danish.</div> Denmark 1845: All persons This variable indicates the third occupation of the person. This variable is encoded to NAPP HISCO codes using the string variable. 002 Architects, engineers and related technicians 003 Architects, engineers and related technicians 004 Aircraft and ships' officers 005 Life scientists and related technicians 006 Medical, dental, veterinary and related workers 007 Medical, dental, veterinary and related workers 012 Jurists 013 Teachers 014 Workers in religion 015 Authors, journalists and related writers 016 Sculptors, painters, photographers and related creative artists 017 Composers and performing artists 020 Legislative officials and government administrators 021 Managers 022 Superintendents and managers 023 Foremen and supervisors 031 Government executive officials 033 Bookkeepers, cashiers and related workers 037 Mail distribution clerks 038 Telephone and telegraph operators 039 Clerical and related workers, not elsewhere classified 041 Working proprietors (wholesale and retail trade) 043 Technical salesmen, commercial travellers and manufacturers agents 045 Salesmen, shop assistants and related workers 049 Sales workers, not elsewhere classified 051 Working proprietors (catering, lodging and leisure services) 052 Housekeeping workers 053 Cooks, waiters, bartenders and related workers 054 Maids and related housekeeping service workers, not elsewhere classified 055 Building caretakers, charworkers, cleaners and related workers 057 Hairdressers, barbers, beauticians and related workers 058 Protective service workers 059 Service workers, not elsewhere classified 061 Farmers 062 Agricultural and animal husbandry workers 063 Forestry workers 064 Fishermen, hunters and related workers 071 Miners, quarrymen, well-drillers and related workers 072 Metal processors 074 Chemical processors and related workers 075 Spinners, weavers, knitters, dyers and related workers 076 Tanners, fellmongers and pelt dressers 077 Food and beverage processors 078 Tobacco preparers and tobacco product makers 079 Tailors, dressmakers, sewers, upholsterers and related workers 080 Shoemakers and leather goods makers 081 Cabinetmakers and related woodworkers 083 Blacksmiths, toolmakers and machine-tool operators 084 Machinery fitters, machine assemblers and precision-instrument makers (except electrical) 087 Plumbers, welders, sheet-metal, and structural metal preparers and erectors 088 Jewellers and precious metal workers 089 Glass formers, potters and related workers 091 Paper and paperboard products makers 092 Printers and related workers 093 Painters 094 Production and related workers, not elsewhere classified 095 Bricklayers, carpenters and other construction workers 096 Stationary engine and related equipment operators 097 Material handling and related equipment operators, dockers and freight handlers 098 Transport equipment operators 099 Workers, not elsewhere classified 999 No occupation reported or unknown Work: Occupation Variables -- PERSON Secondary occupation (5-digit OCCHISCO) Title, office, business, handicraft, occupation, position in the family or what they live by ____ Occupation:</p> <div class="i1">Occupation as stated in the census in Danish.</div> Denmark 1845: All persons This variable indicates the fourth occupation of the person. This variable is encoded to NAPP HISCO codes using the string variable. 02100 Architects 03020 Land surveyors 03210 Technicians 04220 Ship's masters and captains (sea) 04230 Ship's masters and captains (sea or inland waterways) 04260 Ship and boat pilots 05200 Medical scientists 06110 Medical doctors and physicians 06130 Surgeons 06200 Dentists 06300 Veterinarians 06400 Pharmacists 07210 Nurses nfs 07220 Medical nurses, untrained or level of training unknown 07320 Midwives 07990 Other medical, dental, veterinary and related workers 12110 Lawyers 12200 Judge 12300 Notary 12900 Jurists (except lawyer, judge or solicitor) 13100 Teachers in higher education 13210 Teachers (unspecified) 13300 School administrators and principals 14120 Ministers of religion 14140 Members of religious orders 14900 Workers in religion nec 15100 Authors 15220 Editors 16120 Sculptors 16130 Artistic painters 17120 Musical performers and musicians nfs 17300 Actors and related workers 20100 Legislative officials and heads of government 20200 Government administrators 21130 Manufacturers or proprietors of specified manufacturing concerns 21160 Proprietor, other transport and communications 22110 Superintendents and managers nfs 22190 Superintendents and managers, nec 23110 Foremen and supervisors nfs 31010 Civil servants, title unknown 31020 Tax collectors 31040 Customs officers 31050 Postmasters or postmistresses 31090 Government functionaries, nec 33120 Bookkeepers and bookkeeping clerks 33130 Cashiers, bank or office 37030 Mail carriers, aka postmen (UK) 37040 Messengers 38030 Telegraph operator 39000 Clerk, nfs 39100 Stock, weight and shipping clerks 39130 Stock records clerk 39310 Office clerks, specialisation unknown 39320 Correspondence clerks 39340 Legal clerks 41010 Dealer, merchant etc. (wholesale and retail trade) 43030 Manufacturers and sales agents 45120 Salespeople, wholesale or retail trade 45190 Other sales personnel men, shop assistants and demonstrators 49090 Dealers and salesworkers nec 51030 Restaurant keepers and managers 51040 Boarding and lodging house keepers and managers 52020 Housekeeper 53100 Cooks 53220 Waiter or waitress 53290 Other food and drink service workers 54020 House servants nfs and maids 54030 Personal servants and valets 54040 Nursemaids 54050 Companions 55240 Chimney sweeps 57030 Barbers 57040 Bath attendants 58100 Firefighters 58220 Policemen and detectives, public service 58410 Military, rank unknown 58420 Military officers 58500 Prison keepers and guards 58900 Other protective service workers 59200 Undertakers and embalmers 61110 General farmers and farmers nfs 61115 Husbandmen or cottars 61120 Major landowner 61400 Farm managers, foremen and supervisors nfs 62200 Farm workers (field crop and vegetables) 62300 Farm labourers, orchard and fruit farm workers 62410 Livestock workers, general or nfs 62420 Cattle workers, except specified dairy 62430 Sheep workers 62450 Fur-bearing animal workers 62711 Gardener (domestic) 62713 Gardener (not domestic) 63110 Woodsmen and workers in the woods, nfs 63220 Foresters and wood wardens 63230 Forestry workers 64100 Fishermen 64970 Trappers or hunters 71130 Quarrymen 71300 Well drillers, borers and related workers 72000 Metal workers, specialisation unknown 72100 Metal smelter and furnacemen 72500 Metal moulders and coremakers 74320 Charcoal burners 74720 Tallow chandlers, candle makers and grease makers 75100 Fibre preparers 75200 Spinners, doublers, twisters and winders 75400 Weavers 75500 Knitters 75600 Bleachers, dyer or textile product finisher 75700 Rope makers 75990 Other specialised textile workers nec 76130 Tanners 77100 Millers and related workers 77310 Butchers 77500 Butter, cheese and dairy product makers 77620 Bakers 77820 Brewers 77830 Maltsters 77860 Distillers 78100 Tobacco preparers and tobacco factory workers 79120 Tailors and tailoresses 79200 Furriers and fur workers 79330 Hat makers 79400 Glove makers and related workers 79520 Seamstresses 79590 Others hand sewers 79920 Sail, tent and awning makers 80100 Boot and shoe makers and repairers 80320 Saddlers and harness makers 81120 Cabinet makers 81130 Chair makers 81230 Wood turners and handle makers 81300 Coach, carriage and wagon makers 81500 Coopers, hoop makers and benders 81600 Clog makers 81990 Other makers of wooden products 83120 Blacksmiths 83520 Metal polishers and finishers 83600 Gunsmiths 83890 Other metal workers nec 84110 Mechanics 84220 Watch and clock makers 87230 Braziers 87290 Other welders, braziers, solderers 87330 Coppersmith or copperware maker 87340 Tinsmith, tinner or tinker 87520 Ship and boat builders 88030 Goldsmith 89200 Pottery and porcelain makers and workers 89300 Brick and tile makers 89630 Lime burners 91020 Paper and paperboard products makers, except boxes 92110 Printers nfs 92400 Lithographers 92600 Bookbinders and related workers 93110 Painters, nfs 94110 Musical instrument maker nfs 94140 Organ builder 94220 Basket makers 94230 Brush makers 94240 Broom makers 94990 Production and related workers nec 95120 Bricklayers 95150 Paviours 95190 Others in construction 95200 Cement masons and finishers 95330 Thatchers 95390 Other roofers 95410 Carpenter and joiner 95700 Glaziers 96900 Other stationary engine and related equipment operators 97150 Packers 97440 Waterway and harbour builders, workers and labourers 98120 Seamen 98130 Boatmen and canalmen 98190 Other crew of boats, ships, etc. 98510 Drivers, nec 98520 Drivers (private) 98730 Gate keepers 98900 Other transport equipment operators 99120 Labourers nfs 99140 Day labourers (e.g., journalier) 99150 Worker nfs 99200 Factory labourers (unspecified) 99999 No occupation reported or unknown Work: Occupation Variables -- PERSON Third occupation (5-digit OCCHISCO) Title, office, business, handicraft, occupation, position in the family or what they live by ____ Occupation:</p> <div class="i1">Occupation as stated in the census in Danish.</div> Denmark 1845: All persons This variable indicates the fifth occupation of the person. This variable is encoded to NAPP HISCO codes using the string variable. 03020 Land surveyors 04220 Ship's masters and captains (sea) 04260 Ship and boat pilots 06300 Veterinarians 07320 Midwives 07990 Other medical, dental, veterinary and related workers 12200 Judge 12300 Notary 12900 Jurists (except lawyer, judge or solicitor) 13210 Teachers (unspecified) 13300 School administrators and principals 14120 Ministers of religion 14900 Workers in religion nec 17120 Musical performers and musicians nfs 20100 Legislative officials and heads of government 20200 Government administrators 21130 Manufacturers or proprietors of specified manufacturing concerns 23110 Foremen and supervisors nfs 31010 Civil servants, title unknown 31020 Tax collectors 31040 Customs officers 39000 Clerk, nfs 39310 Office clerks, specialisation unknown 39320 Correspondence clerks 41010 Dealer, merchant etc. (wholesale and retail trade) 43030 Manufacturers and sales agents 45120 Salespeople, wholesale or retail trade 45190 Other sales personnel men, shop assistants and demonstrators 51030 Restaurant keepers and managers 51040 Boarding and lodging house keepers and managers 52020 Housekeeper 54020 House servants nfs and maids 57040 Bath attendants 58100 Firefighters 58410 Military, rank unknown 58420 Military officers 58900 Other protective service workers 59200 Undertakers and embalmers 61110 General farmers and farmers nfs 61115 Husbandmen or cottars 61120 Major landowner 61400 Farm managers, foremen and supervisors nfs 62200 Farm workers (field crop and vegetables) 62711 Gardener (domestic) 62713 Gardener (not domestic) 63110 Woodsmen and workers in the woods, nfs 63220 Foresters and wood wardens 64100 Fishermen 71130 Quarrymen 71300 Well drillers, borers and related workers 74320 Charcoal burners 75100 Fibre preparers 75200 Spinners, doublers, twisters and winders 75400 Weavers 75500 Knitters 76130 Tanners 77100 Millers and related workers 77310 Butchers 79120 Tailors and tailoresses 79520 Seamstresses 79590 Others hand sewers 80100 Boot and shoe makers and repairers 81120 Cabinet makers 81230 Wood turners and handle makers 81300 Coach, carriage and wagon makers 81500 Coopers, hoop makers and benders 81600 Clog makers 81990 Other makers of wooden products 83120 Blacksmiths 84110 Mechanics 84220 Watch and clock makers 87290 Other welders, braziers, solderers 87340 Tinsmith, tinner or tinker 89300 Brick and tile makers 93110 Painters, nfs 94220 Basket makers 95120 Bricklayers 95150 Paviours 95190 Others in construction 95330 Thatchers 95410 Carpenter and joiner 95700 Glaziers 98130 Boatmen and canalmen 98520 Drivers (private) 99140 Day labourers (e.g., journalier) 99150 Worker nfs 99999 No occupation reported or unknown Work: Occupation Variables -- PERSON Fourth occupation (5-digit OCCHISCO) Title, office, business, handicraft, occupation, position in the family or what they live by ____ Occupation:</p> <div class="i1">Occupation as stated in the census in Danish.</div> Denmark 1845: All persons 12200 Judge 12300 Notary 13210 Teachers (unspecified) 14120 Ministers of religion 14900 Workers in religion nec 20200 Government administrators 39100 Stock, weight and shipping clerks 41010 Dealer, merchant etc. (wholesale and retail trade) 58420 Military officers 61110 General farmers and farmers nfs 61115 Husbandmen or cottars 61120 Major landowner 61400 Farm managers, foremen and supervisors nfs 63220 Foresters and wood wardens 64100 Fishermen 75400 Weavers 75500 Knitters 77100 Millers and related workers 77310 Butchers 80100 Boot and shoe makers and repairers 94220 Basket makers 95410 Carpenter and joiner 98130 Boatmen and canalmen 99140 Day labourers (e.g., journalier) 99999 No occupation reported or unknown Work: Occupation Variables -- PERSON