DDI_USA_1850_PHC-1PCT_v01_M_v7.5_A_IPUMS United States Census of 1850 IPUMS May 21, 2024 MetadataEditor Version 7.5 October 2024. NEW FEATURES. --Historical data from NAPP project now available from IPUMS-International. --Historical census data from Canada, Denmark, the United Kingdom, Germany, Iceland, Norway, Sweden, and the United States for the period 1703 to 1911 are now available from IPUMS-International. The complete count and sample datasets were previously disseminated by the North Atlantic Population Project (NAPP). Where possible, the data have been integrated into existing IPUMS-International variable coding schema. Some new variables have been created that are available only for these pre-1960 datasets. NAPP data users should note that many NAPP variables are available from IPUMS-International by different names. For a complete list of NAPP variables that have been renamed in IPUMS-Interational, refer to the crosswalk. --Individual country shapefiles for the third-level administrative level of geography are now available for a few IPUMS samples. --New spatially harmonized previous-residence variables at the second administrative level of geography are available for several samples in this data release. More information is available here. Users should note that many older migration variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. --IPUMS now hosts the Census Mosaic data collection. Census Mosaic identifies, gathers, harmonizes, and distributes surviving historical census microdata from regions of Continental Europe where complete centralized records are not available. The Mosaic project was founded by a consortium of historical social scientists in Europe. Data can be downloaded as static files from the Census Mosaic website. Although the data are not yet integrated fully into IPUMS International, variables have been standardized and harmonized to be roughly compatible with IPUMS coding structures. NEW SAMPLES. --Full-count datasets for Great Britain 1851, 1861, 1871 (Scotland only), 1891, and 1901. --Full-count dataset for Sweden 1910. Denmark (1845, 1880, and 1885) --Labor force surveys from Spain and eight new labor force surveys from Italy added to the series. Newly added countries: Benin, Cote d'Ivoire, Finland, Guatemala, Honduras, Laos, Lesotho, Mauritius, Myanmar, Papua New Guinea, Russia, Slovak Republic, Suriname, Togo, and Zimbabwe New samples for: Bolivia, Cambodia, Cambodia, Chile, Cuba, Cote d'Ivoire, Egypt (1848 and 1868, historical samples), Fiji, Guinea, Ireland, Israel, Italy, Lao PDR, Mexico, Morocco, Nepal, Netherlands, Palestine, Peru, Philippines, Puerto Rico, Rwanda, Senegal, Sierra Leone, South Africa, Switzerland, Uganda, United States, United Kingdom, United States, Vietnam, and Zimbabwe SUPPLEMENTAL DATA. Data from censuses from Benin and Lesotho that record individual fertility and/or mortality events were made available in IPUMS-International. These files can be downloaded and linked to data produced by the extract system. NEW VARIABLES. --IPUMS-International now provides harmonized and year-specific geography variables for all countries including 13 new samples from Dominican Republic, Germany, Indonesia, Israel, Malaysia, Mongolia, Nicaragua, Nigeria, Palestine, Paraguay, Thailand, United Kingdom, and Uruguay. First-level and second-level year specific geography variables are also available for all countries. IPUMS provides corresponding, downloadable GIS boundary files for all harmonized and year specific geography variables. More information about IPUMS geography variables is available here. --IPUMS International now provides spatially harmonized previous-residence variables at the first administrative level of geography. The codes for the spatially harmonized previous-residence variables match the spatially harmonized place of current residence. More information is available here. --IPUMS International provides spatially harmonized previous-residence variables at the first administrative level of geography for all samples; previously available country-specific migration variables at the first administrative level that were not fully harmonized spatially have been phased out. Spatially harmonized previous-residence variables at the second administrative level of geography are available for selected samples. More information is available here. Users should note that many older migration variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. --IPUMS International now provides spatially harmonized previous-residence variables at the first administrative level of geography for all samples. Spatially harmonized previous-residence variables at the second administrative level of geography are available for several samples in this data release. More information is available here. Users should note that many older migration variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. --Lower (third) level geography codes and GIS files have been added for Bangladesh, China, Ethiopia, Mali, Rwanda, and Zimbabwe. Some geography codes and labels might have changed for these countries to accommodate the newer lower level geography. --Added more detailed 3-digit industry and occupation variables for China 2000. EDITED SAMPLES. --Revised full-count data for Great Britain 1881 --Revised full-count datasets for Sweden 1890 and 1900. The revision includes the following changes that improve comparability across Sweden datasets: --Revisions to certain ethnicity and work variables (and the underlying source data): ORIGIN, LABFORCE, OCCHISCO, OCRELATE, OCSTATUS. --Revisions to unharmonized source variables: SE1890A_HISCOSE, SE1890A_HISCRELSE, SE1890A_HISCSTATSE, SE1890A_OCCMULTISE, SE1900A_HISCOSE, SE1900A_HISCRELSE, SE1900A_HISCSTATSE, SE1900A_OCCMULTISE. --A new United States 1850 full-count dataset now matches the corresponding dataset distributed by the USA IPUMS data project. The source variable US1850A_0502 (HISTID) provides a linking key to match person records to the USA version of the data. The IPUMS International version of the data contains names, which the USA version cannot distribute. EDITED VARIABLES. An error affecting HHWT for South Africa 2007 was corrected. The existing values were adjusted by a factor of 0.01. AGEMARR was edited to add data for Hungary 1980 and 1990. Harmonized and year-specific geography variables for Brazil and Colombia have been edited to accommodate for the availability of refined municipal boundaries. Users should be aware that codes and labels have changed in all harmonized and year specific geography varaibles for these two countries. Errors affecting BPLSE2 (formerly BPLPARSE) for Sweden 1890 and the underlying source variable were corrected. Several thousand cases were incorrectly coded as 258101000. These cases have been updated with the correct code: 258171000. Harmonized geography variables for Italy, Philippines, Rwanda, and United States have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year specific geography varaibles for these countries. More information about IPUMS geography variables is available here. The codes for the source variable RW2002A_0419 were corrected to include 0 and 8 as possible responses, which were previously identified as 'unknown years' within primary education. Errors affecting EDUCFJ for Fiji 2006 were corrected. A problem with PERWT for Tanzania 2012 was corrected. The previous weights were adjusted to properly reflect population totals. MOMLOC, POPLOC, and PARRULE were updated for the United States 2010 and 2015 samples to include additional information on subfamilies. Prior to this correction, persons above age 17 were not receiving links to their co-resident mothers and fathers. An error affecting codes for the URBAN variable in Egypt 1986 for Cairo, Alexandria, Port-Said, and Suez was corrected. An error in INCEARN affecting Venezuela 2001 was corrected. Earned income in the source variable VE2001A_0440 is interpreted as a monthly amount, thus adjustments previously applied to convert data from daily or weekly income were supressed. All the six Brazil samples in IPUMS International were replaced with higher density samples. An edited version of the Chile 2017 sample was introduced to correct an error in household breaks. Errors affecting codes for GEO1_ZA in South Africa 2011 and ENUTS1 in United Kingdom 1991 were corrected. Harmonized geography variables for Cambodia, Fiji, and Nepal have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography varaibles for these countries. More information about IPUMS geography variables is available here. An error in PERWT affecting Nepal 2001 was corrected. Errors affecting a code in GQ for Brazil 2010 and Indonesia 2010 were corrected. Both census samples now identify 1-person units created by splitting a large household. An error in MARRNUM affecting Indonesia 1976 was corrected. Some codes for GEO1_EG2006 and GEO2_EG2006 were edited. Harmonized geography variables for Bolivia, Cuba, Guinea, Ireland, Morocco, Palestine, Senegal, South Africa, and Uganda have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography variables for these countries. More information about IPUMS geography variables is available here. An error in INCEARN affecting Brazil 1980 was corrected. An error in EDATTAIN affecting Ireland 1971 and 1981 was corrected. A small proportion of person records in Mexico 1960 were re-classified in MIGRATEP based on information about their current and previous residence. These were previously coded to 'different major administrative unit', even though their place of residence suggests that their last move was within the same major administrative unit. The second-level technician (higher) degrees for Spain 1991, 2001, and 2011 were re-classified into post-secondary technical education in EDATTAIN. An error affecting codes for SEX for Egypt 1848 and 1868 was corrected. The values for male and female had been reversed. A problem with HHWT and PERWT for Canada 2011 was corrected. The previous weights were adjusted to properly reflect population totals. Harmonized geography variables for Cambodia, Lao PDR, Mexico, Peru, Switzerland, Vietnam, Puerto Rico, United Kingdom, and United States have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography variables for these countries. More information about IPUMS geography variables is available here. Harmonized geography variables for Chile and Sierra Leone have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography variables for these countries. More information about IPUMS geography variables is available here. An error affecting codes for COMPUTER for Senegal 2013 was corrected. An error affecting labels available in IND for Peru 1993 was corrected. An error affecting codes for persons previously residing abroad for MIG1_5_BO in Bolivia 2001 and 2012 was corrected. EDUCAR, EDATTAIN, and YRSCHOOL were adjusted in the Argentina samples to incorporate information on completion of education levels in the data harmonization. HHWT and PERWT were calibrated in Kenya 1979 to properly reflect the population distribution by province. In GQ (group quarters status), persons residing in hospitals of all types were reclassified to 'institutional group quarters' from 'other group quarters,' making their treatment consistent with GQTYPE. Errors affecting codes for BPLBJ2 in Benin 1979, 1992, and 2002 were corrected. Errors affecting codes for GEO2_BR1970 in Brazil 1970 were corrected. United States Census of 1850 - IPUMS Subset PHC United States 1850 (1%) (IPUMS Harmonized Subset) USA_1850_PHC-1PCT_v01_M_v7.5_A_IPUMS Department of the Interior IPUMS (c) Copyright 1850, Department of the Interior and Minnesota Population Center MetadataEditor Department of the Interior Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.5 Version 7.5. The datasets contain selected variables from the original census microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Nativity and Birthplace Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Technical Household Variables -- HOUSEHOLD Geography: O-Z Variables -- HOUSEHOLD Disability Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Household Economic Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Ethnicity and Language Variables -- PERSON Work Variables -- PERSON Education Variables -- PERSON Other Person Variables -- PERSON Technical Person Variables -- PERSON Other Household Variables -- HOUSEHOLD Geography: O-Z Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Technical Household Variables -- HOUSEHOLD Technical Person Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Demographic Variables -- PERSON Ethnicity and Language Variables -- PERSON Nativity and Birthplace Variables -- PERSON Education Variables -- PERSON Work Variables -- PERSON Other Person Variables -- PERSON Disability Variables -- PERSON United States County Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: A separate inhabited tenement, containing one or more families under one roof. Where several tenements are in one block, with walls either of brick or wood to divide them, having separate entrances, they are each to be numbered as separate houses; but where not so divided, they are to be numbered as one house.  - Households: One person living separately in a house, or a part of a house, and providing for him or herself, or several persons living together in a house, or in part of a house, upon one common means of support, and separately from others in similar circumstances - Group quarters: Yes All persons living in the United States including temporarily absent residents Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: United States 1850 (1%) MICRODATA SOURCE: Department of the Interior SAMPLE SIZE (person records): 197796. SAMPLE DESIGN: 1-in-100 national random sample of the free population. African-American slaves are not included in this dataset. Individual-level data on the 1850 slave population is available at the Face-to-face [f2f] The census operation involved six forms. Form 1 was used to enumerate free persons and collected information on individual characteristics. Form 2 was used to enumerate slaves. Other forms were used to record information about agriculture and industry. de jure, CENSUS DAY: June 1, 1850 Self-weighting (expansion factor=100) 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. Department of the Interior Steven Ruggles, Lara Cleveland, Rodrigo Lovaton, Sula Sarkar, Matthew Sobek, Derek Burk, Dan Ehrlich, Quinn Heimann, Jane Lee. Integrated Public Use Microdata Series, International: Version 7.5 [dataset]. Minneapolis, MN: IPUMS, 2024. https://doi.org/10.1 [dataset]. Minneapolis, MN: IPUMS, 2024. https://doi.org/10.18128/D020.V7.5 Researchers should also acknowledge the statistical agency that originally produced the data: United States, Department of the Interior. United States Census of 1850 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. USA1850_PHC-1PCT-H-H Household records 37 77 USA1850_PHC-1PCT-P-H Person records 197796 110 Record type H Household P Person RECTYPE identifies the type of record for the case: household or person. NOTE: RECTYPE is an alphabetic (character string) variable with a value of 'H' for household records and 'P' for person records. RECTYPE will not appear as a variable in the default rectangular extracts produced by the data extract system. It is only available in hierarchical extracts, to distinguish between the two record types. IPUMS Country 032 Argentina 051 Armenia 040 Austria 050 Bangladesh 112 Belarus 204 Benin 068 Bolivia 072 Botswana 076 Brazil 854 Burkina Faso 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 208 Denmark 214 Dominican Republic 218 Ecuador 818 Egypt 222 El Salvador 231 Ethiopia 242 Fiji 246 Finland 250 France 276 Germany 288 Ghana 300 Greece 320 Guatemala 324 Guinea 332 Haiti 340 Honduras 348 Hungary 352 Iceland 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 384 Ivory Coast 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 418 Laos 426 Lesotho 430 Liberia 454 Malawi 458 Malaysia 466 Mali 480 Mauritius 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 104 Myanmar 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 578 Norway 586 Pakistan 275 Palestine 591 Panama 598 Papua New Guinea 600 Paraguay 604 Peru 608 Philippines 616 Poland 620 Portugal 630 Puerto Rico 642 Romania 643 Russia 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 703 Slovak Republic 705 Slovenia 710 South Africa 728 South Sudan 724 Spain 729 Sudan 740 Suriname 752 Sweden 756 Switzerland 834 Tanzania 764 Thailand 768 Togo 780 Trinidad and Tobago 792 Turkey 800 Uganda 804 Ukraine 826 United Kingdom 840 United States 858 Uruguay 862 Venezuela 704 Vietnam 894 Zambia 716 Zimbabwe COUNTRY gives the country from which the sample was drawn. The codes assigned to each country are those used by the UN Statistics Division and the ISO (International Organization for Standardization). IPUMS Year 1703 1703 1729 1729 1787 1787 1801 1801 1819 1819 1845 1845 1848 1848 1850 1850 1851 1851 1852 1852 1860 1860 1861 1861 1865 1865 1868 1868 1870 1870 1871 1871 1875 1875 1880 1880 1881 1881 1885 1885 1890 1890 1891 1891 1900 1900 1901 1901 1910 1910 1911 1911 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1966 1966 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 YEAR gives the year in which the census or survey was taken. For samples that span years, the midpoint or first year of the interval is reported. IPUMS IPUMS sample identifier 032197001 Argentina 1970 032198001 Argentina 1980 032199101 Argentina 1991 032200101 Argentina 2001 032201001 Argentina 2010 051200101 Armenia 2001 051201101 Armenia 2011 040197101 Austria 1971 040198101 Austria 1981 040199101 Austria 1991 040200101 Austria 2001 040201101 Austria 2011 050199101 Bangladesh 1991 050200101 Bangladesh 2001 050201101 Bangladesh 2011 112199901 Belarus 1999 112200901 Belarus 2009 204197901 Benin 1979 204199201 Benin 1992 204200201 Benin 2002 204201301 Benin 2013 068197601 Bolivia 1976 068199201 Bolivia 1992 068200101 Bolivia 2001 068201201 Bolivia 2012 072198101 Botswana 1981 072199101 Botswana 1991 072200101 Botswana 2001 072201101 Botswana 2011 076196001 Brazil 1960 076197001 Brazil 1970 076198001 Brazil 1980 076199101 Brazil 1991 076200001 Brazil 2000 076201001 Brazil 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 116199801 Cambodia 1998 116200401 Cambodia 2004 116200801 Cambodia 2008 116201301 Cambodia 2013 116201901 Cambodia 2019 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124185201 Canada 1852 124187101 Canada 1871 124188101 Canada 1881 124189101 Canada 1891 124190101 Canada 1901 124191101 Canada 1911 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 124201101 Canada 2011 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 152201701 Chile 2017 156198201 China 1982 156199001 China 1990 156200001 China 2000 170196401 Colombia 1964 170197301 Colombia 1973 170198501 Colombia 1985 170199301 Colombia 1993 170200501 Colombia 2005 188196301 Costa Rica 1963 188197301 Costa Rica 1973 188198401 Costa Rica 1984 188200001 Costa Rica 2000 188201101 Costa Rica 2011 192200201 Cuba 2002 192201201 Cuba 2012 208178701 Denmark 1787 208180101 Denmark 1801 208184501 Denmark 1845 208188001 Denmark 1880 208188501 Denmark 1885 214196001 Dominican Republic 1960 214197001 Dominican Republic 1970 214198101 Dominican Republic 1981 214200201 Dominican Republic 2002 214201001 Dominican Republic 2010 218196201 Ecuador 1962 218197401 Ecuador 1974 218198201 Ecuador 1982 218199001 Ecuador 1990 218200101 Ecuador 2001 218201001 Ecuador 2010 818184801 Egypt 1848 818186801 Egypt 1868 818198601 Egypt 1986 818199601 Egypt 1996 818200601 Egypt 2006 222199201 El Salvador 1992 222200701 El Salvador 2007 231198401 Ethiopia 1984 231199401 Ethiopia 1994 231200701 Ethiopia 2007 242196601 Fiji 1966 242197601 Fiji 1976 242198601 Fiji 1986 242199601 Fiji 1996 242200701 Fiji 2007 242201401 Fiji 2014 246201001 Finland 2010 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 276181901 Germany 1819 (Mecklenburg) 276197001 Germany 1970 (West) 276197101 Germany 1971 (East) 276198101 Germany 1981 (East) 276198701 Germany 1987 (West) 288198401 Ghana 1984 288200001 Ghana 2000 288201001 Ghana 2010 300197101 Greece 1971 300198101 Greece 1981 300199101 Greece 1991 300200101 Greece 2001 300201101 Greece 2011 320196401 Guatemala 1964 320197301 Guatemala 1973 320198101 Guatemala 1981 320199401 Guatemala 1994 320200201 Guatemala 2002 324198301 Guinea 1983 324199601 Guinea 1996 324201401 Guinea 2014 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 340196101 Honduras 1961 340197401 Honduras 1974 340198801 Honduras 1988 340200101 Honduras 2001 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 348201101 Hungary 2011 352170301 Iceland 1703 352172901 Iceland 1729 352180101 Iceland 1801 352190101 Iceland 1901 352191001 Iceland 1910 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 356200941 India 2009 360197101 Indonesia 1971 360197601 Indonesia 1976 360198001 Indonesia 1980 360198501 Indonesia 1985 360199001 Indonesia 1990 360199501 Indonesia 1995 360200001 Indonesia 2000 360200501 Indonesia 2005 360201001 Indonesia 2010 364200601 Iran 2006 364201101 Iran 2011 368199701 Iraq 1997 372190101 Ireland 1901 372191101 Ireland 1911 372197101 Ireland 1971 372197901 Ireland 1979 372198101 Ireland 1981 372198601 Ireland 1986 372199101 Ireland 1991 372199601 Ireland 1996 372200201 Ireland 2002 372200601 Ireland 2006 372201101 Ireland 2011 372201601 Ireland 2016 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 376200801 Israel 2008 380200101 Italy 2001 380201101 Italy 2011 380201121 Italy 2011 Q1 LFS 380201221 Italy 2012 Q1 LFS 380201321 Italy 2013 Q1 LFS 380201421 Italy 2014 Q1 LFS 380201521 Italy 2015 Q1 LFS 380201621 Italy 2016 Q1 LFS 380201721 Italy 2017 Q1 LFS 380201821 Italy 2018 Q1 LFS 380201921 Italy 2019 Q1 LFS 380202021 Italy 2020 Q1 LFS 384198801 Ivory Coast 1988 384199801 Ivory Coast 1998 388198201 Jamaica 1982 388199101 Jamaica 1991 388200101 Jamaica 2001 400200401 Jordan 2004 404196901 Kenya 1969 404197901 Kenya 1979 404198901 Kenya 1989 404199901 Kenya 1999 404200901 Kenya 2009 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 418199501 Laos 1995 418200501 Laos 2005 418201501 Laos 2015 426199601 Lesotho 1996 426200601 Lesotho 2006 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 480199001 Mauritius 1990 480200001 Mauritius 2000 480201101 Mauritius 2011 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 484201501 Mexico 2015 484202001 Mexico 2020 484200521 Mexico 2005 Q1 LFS 484200522 Mexico 2005 Q2 LFS 484200523 Mexico 2005 Q3 LFS 484200524 Mexico 2005 Q4 LFS 484200621 Mexico 2006 Q1 LFS 484200622 Mexico 2006 Q2 LFS 484200623 Mexico 2006 Q3 LFS 484200624 Mexico 2006 Q4 LFS 484200721 Mexico 2007 Q1 LFS 484200722 Mexico 2007 Q2 LFS 484200723 Mexico 2007 Q3 LFS 484200724 Mexico 2007 Q4 LFS 484200821 Mexico 2008 Q1 LFS 484200822 Mexico 2008 Q2 LFS 484200823 Mexico 2008 Q3 LFS 484200824 Mexico 2008 Q4 LFS 484200921 Mexico 2009 Q1 LFS 484200922 Mexico 2009 Q2 LFS 484200923 Mexico 2009 Q3 LFS 484200924 Mexico 2009 Q4 LFS 484201021 Mexico 2010 Q1 LFS 484201022 Mexico 2010 Q2 LFS 484201023 Mexico 2010 Q3 LFS 484201024 Mexico 2010 Q4 LFS 484201121 Mexico 2011 Q1 LFS 484201122 Mexico 2011 Q2 LFS 484201123 Mexico 2011 Q3 LFS 484201124 Mexico 2011 Q4 LFS 484201221 Mexico 2012 Q1 LFS 484201222 Mexico 2012 Q2 LFS 484201223 Mexico 2012 Q3 LFS 484201224 Mexico 2012 Q4 LFS 484201321 Mexico 2013 Q1 LFS 484201322 Mexico 2013 Q2 LFS 484201323 Mexico 2013 Q3 LFS 484201324 Mexico 2013 Q4 LFS 484201421 Mexico 2014 Q1 LFS 484201422 Mexico 2014 Q2 LFS 484201423 Mexico 2014 Q3 LFS 484201424 Mexico 2014 Q4 LFS 484201521 Mexico 2015 Q1 LFS 484201522 Mexico 2015 Q2 LFS 484201523 Mexico 2015 Q3 LFS 484201524 Mexico 2015 Q4 LFS 484201621 Mexico 2016 Q1 LFS 484201622 Mexico 2016 Q2 LFS 484201623 Mexico 2016 Q3 LFS 484201624 Mexico 2016 Q4 LFS 484201721 Mexico 2017 Q1 LFS 484201722 Mexico 2017 Q2 LFS 484201723 Mexico 2017 Q3 LFS 484201724 Mexico 2017 Q4 LFS 484201821 Mexico 2018 Q1 LFS 484201822 Mexico 2018 Q2 LFS 484201823 Mexico 2018 Q3 LFS 484201824 Mexico 2018 Q4 LFS 484201921 Mexico 2019 Q1 LFS 484201922 Mexico 2019 Q2 LFS 484201923 Mexico 2019 Q3 LFS 484201924 Mexico 2019 Q4 LFS 484202021 Mexico 2020 Q1 LFS 484202023 Mexico 2020 Q3 LFS 496198901 Mongolia 1989 496200001 Mongolia 2000 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 104201401 Myanmar 2014 524200101 Nepal 2001 524201101 Nepal 2011 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 528201101 Netherlands 2011 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 578180101 Norway 1801 578186501 Norway 1865 578187501 Norway 1875 578190001 Norway 1900 578191001 Norway 1910 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 275199701 Palestine 1997 275200701 Palestine 2007 275201701 Palestine 2017 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 598198001 Papua New Guinea 1980 598199001 Papua New Guinea 1990 598200001 Papua New Guinea 2000 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 604201701 Peru 2017 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 608201001 Philippines 2010 616197801 Poland 1978 616198801 Poland 1988 616200201 Poland 2002 616201101 Poland 2011 620198101 Portugal 1981 620199101 Portugal 1991 620200101 Portugal 2001 620201101 Portugal 2011 630197001 Puerto Rico 1970 630198001 Puerto Rico 1980 630199001 Puerto Rico 1990 630200001 Puerto Rico 2000 630200501 Puerto Rico 2005 630201001 Puerto Rico 2010 630201501 Puerto Rico 2015 630202001 Puerto Rico 2020 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 642201101 Romania 2011 643200201 Russia 2002 643201001 Russia 2010 646199101 Rwanda 1991 646200201 Rwanda 2002 646201201 Rwanda 2012 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 686201301 Senegal 2013 694200401 Sierra Leone 2004 694201501 Sierra Leone 2015 703199101 Slovak Republic 1991 703200101 Slovak Republic 2001 703201101 Slovak Republic 2011 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 710201601 South Africa 2016 728200801 South Sudan 2008 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 724200521 Spain 2005 Q1 LFS 724200522 Spain 2005 Q2 LFS 724200523 Spain 2005 Q3 LFS 724200524 Spain 2005 Q4 LFS 724200621 Spain 2006 Q1 LFS 724200622 Spain 2006 Q2 LFS 724200623 Spain 2006 Q3 LFS 724200624 Spain 2006 Q4 LFS 724200721 Spain 2007 Q1 LFS 724200722 Spain 2007 Q2 LFS 724200723 Spain 2007 Q3 LFS 724200724 Spain 2007 Q4 LFS 724200821 Spain 2008 Q1 LFS 724200822 Spain 2008 Q2 LFS 724200823 Spain 2008 Q3 LFS 724200824 Spain 2008 Q4 LFS 724200921 Spain 2009 Q1 LFS 724200922 Spain 2009 Q2 LFS 724200923 Spain 2009 Q3 LFS 724200924 Spain 2009 Q4 LFS 724201021 Spain 2010 Q1 LFS 724201022 Spain 2010 Q2 LFS 724201023 Spain 2010 Q3 LFS 724201024 Spain 2010 Q4 LFS 724201121 Spain 2011 Q1 LFS 724201122 Spain 2011 Q2 LFS 724201123 Spain 2011 Q3 LFS 724201124 Spain 2011 Q4 LFS 724201221 Spain 2012 Q1 LFS 724201222 Spain 2012 Q2 LFS 724201223 Spain 2012 Q3 LFS 724201224 Spain 2012 Q4 LFS 724201321 Spain 2013 Q1 LFS 724201322 Spain 2013 Q2 LFS 724201323 Spain 2013 Q3 LFS 724201324 Spain 2013 Q4 LFS 724201421 Spain 2014 Q1 LFS 724201422 Spain 2014 Q2 LFS 724201423 Spain 2014 Q3 LFS 724201424 Spain 2014 Q4 LFS 724201521 Spain 2015 Q1 LFS 724201522 Spain 2015 Q2 LFS 724201523 Spain 2015 Q3 LFS 724201524 Spain 2015 Q4 LFS 724201621 Spain 2016 Q1 LFS 724201622 Spain 2016 Q2 LFS 724201623 Spain 2016 Q3 LFS 724201624 Spain 2016 Q4 LFS 724201721 Spain 2017 Q1 LFS 724201722 Spain 2017 Q2 LFS 724201723 Spain 2017 Q3 LFS 724201724 Spain 2017 Q4 LFS 724201821 Spain 2018 Q1 LFS 724201822 Spain 2018 Q2 LFS 724201823 Spain 2018 Q3 LFS 724201824 Spain 2018 Q4 LFS 724201921 Spain 2019 Q1 LFS 724201922 Spain 2019 Q2 LFS 724201923 Spain 2019 Q3 LFS 724201924 Spain 2019 Q4 LFS 724202021 Spain 2020 Q1 LFS 724202022 Spain 2020 Q2 LFS 724202023 Spain 2020 Q3 LFS 724202024 Spain 2020 Q4 LFS 729200801 Sudan 2008 740200401 Suriname 2004 740201201 Suriname 2012 752188001 Sweden 1880 752189001 Sweden 1890 752190001 Sweden 1900 752191001 Sweden 1910 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 756201101 Switzerland 2011 834198801 Tanzania 1988 834200201 Tanzania 2002 834201201 Tanzania 2012 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 768196001 Togo 1960 768197001 Togo 1970 768201001 Togo 2010 780197001 Trinidad and Tobago 1970 780198001 Trinidad and Tobago 1980 780199001 Trinidad and Tobago 1990 780200001 Trinidad and Tobago 2000 780201101 Trinidad and Tobago 2011 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 800201401 Uganda 2014 804200101 Ukraine 2001 826185101 United Kingdom 1851 (England and Wales) 826185102 United Kingdom 1851 (Scotland) 826185103 United Kingdom 1851 (2% sample) 826186101 United Kingdom 1861 (England and Wales) 826186102 United Kingdom 1861 (Scotland) 826187101 United Kingdom 1871 (Scotland) 826188101 United Kingdom 1881 (England and Wales) 826188102 United Kingdom 1881 (Scotland) 826189101 United Kingdom 1891 (England and Wales) 826189102 United Kingdom 1891 (Scotland) 826190101 United Kingdom 1901 (England and Wales) 826190102 United Kingdom 1901 (Scotland) 826191101 United Kingdom 1911 (England and Wales) 826196101 United Kingdom 1961 826197101 United Kingdom 1971 826199101 United Kingdom 1991 826200101 United Kingdom 2001 840185001 United States 1850 (100%) 840185002 United States 1850 (1%) 840186001 United States 1860 (1%) 840187001 United States 1870 (1%) 840188001 United States 1880 (100%) 840188002 United States 1880 (10%) 840190001 United States 1900 (5%) 840191001 United States 1910 (1%) 840196001 United States 1960 840197001 United States 1970 840198001 United States 1980 840199001 United States 1990 840200001 United States 2000 840200501 United States 2005 840201001 United States 2010 840201501 United States 2015 840202001 United States 2020 858196301 Uruguay 1963 858196302 Uruguay 1963 (full count) 858197501 Uruguay 1975 858197502 Uruguay 1975 (full count) 858198501 Uruguay 1985 858198502 Uruguay 1985 (full count) 858199601 Uruguay 1996 858199602 Uruguay 1996 (full count) 858200621 Uruguay 2006 858201101 Uruguay 2011 858201102 Uruguay 2011 (full count) 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 704201901 Vietnam 2019 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 716201201 Zimbabwe 2012 SAMPLE identifies the IPUMS sample from which the case is drawn. Each sample receives a unique 9-digit code. The code is structured as follows: The first 3 digits are the ISO/UN codes used in COUNTRY The next 4 digits are the year of the census/survey The final 2 digits identify the sample within the year. For the last two digits, censuses or large census-like surveys have a value "0" (e.g, 01) in the second-to-last digit, household surveys have a value of "2" (e.g., 21), and employment surveys have a value of "4" (e.g., 41). IPUMS Household serial number SERIAL is an identifying number unique to each household in a given sample. All person records are assigned the same serial number as the household record that they follow. (Person records also have their own unique identifiers -- see PERNUM.) The combination of SAMPLE and SERIAL provides a unique identifier for every household in the IPUMS-International database; SAMPLE, SERIAL and PERNUM uniquely identify every person in the database. SERIAL can be used to identify dwellings in some samples. In these samples, the first 7 digits of SERIAL provide the dwelling number common to all households that were sampled from the same structure. The last three digits give the sequence of the household within the dwelling. The following is a list of samples in which dwellings can be inferred: Chile 1970, 1992, 2002Colombia 1993, 2005Costa Rica 1984, 2000Cuba 2002Dominican Republic 1981, 2002, 2010Ecuador 1990, 2001Germany 1971Hungary 1980, 1990, 2001Jamaica 1982, 1991, 2001Malaysia 1970, 1991, 2000Mexico 1995, 1990, 2000, 2005Nigeria 2006Panama 2000Peru 1993, 2007Portugal 1981, 1991, 2001Spain 1991Uruguay 2011Venezuela 1990, 2001Vietnam 1989In all other samples, the last 3 digits are always zeroes. SERIAL was constructed for IPUMS-International, and has no relation to the serial number in the original datasets. The U.S. 1900 sample and 1880 10% sample have multi-household dwellings that can be identified using the last 3 digits of SERIAL. SERIAL is a 10-digit numeric variable. The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes. IPUMS Number of person records in the household PERSONS indicates how many person records are included in the household (i.e., the number of person records associated with the household record in the sample). These person records will all have the same serial number (SERIAL) as the household record. The information contained in the household record will normally apply to all of these persons. PERSONS is a 4-digit numeric variable. IPUMS Household weight HHWT indicates the number of households in the population represented by the household in the sample. For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics. NOTE: HHWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. IPUMS Group quarters (collective dwelling) status 00 Vacant 10 Households 20 Group quarters (collective), n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools. Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification. Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions. IPUMS Group quarters type, historical 000 NA (non-group quarters households) 010 Family group, someone related to head 020 Unrelated individuals, no one related to head 200 Correctional institution 210 Federal/state correctional 211 Prison 212 Penitentiary 213 Military prison 220 Local correctional 221 Jail 230 School juvenile delinquents--private 240 Reformatory 250 Camp or chaingang 260 House of correction 300 Mental institutions 400 Institutions for the elderly, handicapped, and poor 410 Homes for elderly 411 Aged, dependent home 412 Nursing and convalescent home 413 Old soldiers home 420 Other Institutions (not aged) 421 Other Institutions nec 430 Homes neglected/depend children 431 Orphan school 432 Orphans home, asylum 440 Other instits for children 441 Childrens home, asylum 450 Homes physically handicapped 451 Deaf, blind school 452 Deaf, blind, epilepsy 460 Mentally handicapped home 461 School for feeblemind 470 TB and chronic disease hospital 471 Chronic hospitals 472 Sanataria 480 Poor houses and farms 481 Poor house, almshouse 482 Poor farm, workhouse 491 Maternity homes for unmarried mothers 492 Homes for widows, single, fallen women 493 Detention homes 494 Misc asylums 495 Home, other dependent 499 Instit combo or unknown 500 Non-Institutional group quarters 501 Household (including co-resident unrelated individuals) formerly in institutional group quarters 502 Employees (and their co-resident relatives) formerly in institutional group quarters 600 Military 601 U.S. army installation 602 Navy, marine intallation 603 Navy ships 700 College dormitory 701 Military service academies 800 Rooming house 801 Hotel 802 House, lodging apartments 803 YMCA, YWCA 804 Club 900 Other Non-Instit GQ 901 Other Non-Instit GQ 910 Schools 911 Boarding schools 912 Academy, institute 913 Industrial training 914 Indian school 915 Nursery or children's day care 920 Hospitals 921 Hospital, charity 922 Infirmary 923 Maternity hospital 924 Childrens hospital 925 Hospice 931 Church, Abbey 932 Convent 933 Monastery 934 Mission 935 Seminary 936 Religious commune 937 Other religious 940 Work sites 941 Construction, except rr 942 Lumber 943 Mining 944 Railroad 945 Farms, ranches 946 Ships, boats 947 Other industrial 948 Other worksites 950 Nurses home, dorm 955 Passenger ships 960 Other group quarters 971 Indian reservation 997 Unknown 998 Illegible 999 Fragment (boarders and lodgers, 1900) GQTYPEH reports the type of group quarters in selected historical samples. With this variable, users can distinguish between institutions and non-institutional group quarters, identify broad categories of institutions (e.g., mental institutions versus correctional institutions), and, for some years, isolate very specific types of group quarters (e.g., old soldiers home). IPUMS Number of unrelated persons 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ UNREL indicates the number of persons in the household who are unrelated to the head as defined in the variable RELATE. IPUMS Urban-rural status 1 Rural 2 Urban 9 Unknown URBAN indicates whether the household was located in a place designated as urban or as rural. IPUMS Continent and region of country 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia REGIONW identifies the continent and region of each country. IPUMS North American region, historical 11 New England Division 12 Middle Atlantic Division 14 Ontario 15 Quebec 16 Maritimes 21 East North Central Division 22 West North Central Division 24 Midwest Canada 31 South Atlantic Division 32 East South Central Division 33 West South Central Division 41 Mountain Division 42 Pacific Division 44 Western Canada 91 Overseas Military/Military Installations 93 Unorganized Canadian territory REGIONH identifies the household's census region and division in Canada and the United States. It adds second digit codes to the Northeast, Midwest and West regions to accommodate the contiguous Canadian provinces. IPUMS City, historical US and Canada 0000 Not in identifiable city (or size group) 0001 Aberdeen, SD 0002 Aberdeen, WA 0003 Abilene, TX 0005 Adams, MA 0006 Adrian, MI 0010 Akron, OH 0030 Alameda, CA 0050 Albany, NY 0051 Albany, GA 0070 Albuquerque, NM 0090 Alexandria, VA 0091 Alexandria, LA 0110 Allegheny, PA 0130 Allentown, PA 0131 Alliance, OH 0132 Alpena, MI 0140 Alton, IL 0150 Altoona, PA 0160 Amarillo, TX 0163 Amesbury, MA 0170 Amsterdam, NY 0171 Anaconda, MT 0190 Anaheim, CA 0230 Anderson, IN 0270 AnnArbor, MI 0271 Annapolis, MD 0272 Anniston, AL 0273 Ansonia, CT 0280 Appleton, WI 0282 Argenta, AR 0311 Arlington, MA 0313 Asbury Park, NJ 0330 Asheville, NC 0331 Ashland, OH 0340 Ashland, KY 0341 Ashland, WI 0342 Ashtabula, OH 0343 Astoria, OR 0344 Atchison, KS 0345 Athens, GA 0346 Athol, MA 0350 Atlanta, GA 0370 Atlantic City, NJ 0371 Attleboro, MA 0390 Auburn, NY 0391 Auburn, ME 0410 Augusta, GA 0430 Augusta, ME 0470 Aurora, IL 0490 Austin, TX 0510 Bakersfield, CA 0530 Baltimore, MD 0550 Bangor, ME 0552 Barre, VT 0554 Batavia, NY 0570 Bath, ME 0590 Baton Rouge, LA 0610 Battle Creek, MI 0630 Bay City, MI 0650 Bayonne, NJ 0652 Beatrice, NE 0660 Belleville, IL 0670 Beaumont, TX 0671 Beaver Falls, PA 0672 Bedford, IN 0673 Bellaire, OH 0690 Bellingham, WA 0701 Bellevue, PA 0702 Belmont, OH 0703 Belmont, MA 0704 Beloit, WI 0705 Bennington, VT 0710 Berkeley, CA 0711 Berlin, NH 0712 Berwick, PA 0721 Bessemer, AL 0730 Bethlehem, PA 0740 Biddeford, ME 0742 Billings, MT 0743 Biloxi, MS 0750 Binghamton, NY 0760 Beverly, MA 0770 Birmingham, AL 0771 Birmingham, CT 0780 Bloomfield, NJ 0790 Bloomington, IL 0791 Bloomington, IN 0792 Blue Island, IL 0793 Bluefield, WV 0800 Boise, ID 0801 Boone, IA 0810 Boston, MA 0811 Boulder, CO 0813 Braddock, PA 0814 Braden, WA 0815 Bradford, PA 0816 Brainerd, MN 0817 Braintree, MA 0830 Bridgeport, CT 0831 Bridgeton, NJ 0832 Bristol, CT 0834 Bristol, VA 0835 Bristol, TN 0850 Brockton, MA 0870 Brookline, MA 0880 Brownsville, TX 0881 Brownwood, TX 0882 Brunswick, GA 0883 Bucyrus, OH 0890 Buffalo, NY 0900 Burlington, IA 0905 Burlington, VT 0906 Burlington, NJ 0907 Bushkill, PA 0910 Butte, MT 0911 Butler, PA 0926 Cairo, IL 0930 Cambridge, MA 0931 Cambridge, OH 0950 Camden, NJ 0952 Canonsburg, PA 0970 Camden, NY 0990 Canton, OH 0991 Canton, IL 0992 Cape Girardeau, MO 0993 Carbondale, PA 0994 Carlisle, PA 0995 Carnegie, PA 1010 Cedar Rapids, IA 1020 Central Falls, RI 1021 Centralia, IL 1023 Chambersburg, PA 1024 Champaign, IL 1026 Charleroi, PA 1030 Charlestown, MA 1050 Charleston, SC 1070 Charleston, WV 1090 Charlotte, NC 1091 Charlottesville, VA 1110 Chattanooga, TN 1130 Chelsea, MA 1170 Chester, PA 1171 Cheyenne, WY 1190 Chicago, IL 1191 Chicago Heights, IL 1192 Chickasha, OK 1210 Chicopee, MA 1230 Chillicothe, OH 1270 Cicero, IL 1290 Cincinnati, OH 1311 Clarksdale, MS 1312 Cleburne, TX 1330 Cleveland, OH 1351 Clinton, IN 1370 Clinton, IA 1371 Clinton, MA 1372 Coatesville, PA 1373 Coffeyville, KS 1374 Cohoes, NY 1375 Collingswood, NJ 1390 Colorado Springs, CO 1400 Cohoes, NY 1410 Columbia, SC 1411 Columbia, PA 1420 Columbia City, IN 1430 Columbus, GA 1450 Columbus, OH 1451 Columbus, MS 1490 Concord, NH 1491 Concord, NC 1492 Connellsville, PA 1493 Connellsville, IN 1494 Conshohocken, PA 1496 Corning, NY 1510 Council Bluffs, IA 1520 Corpus Christi, TX 1521 Corsicana, TX 1522 Cortland, NY 1523 Coshocton, OH 1530 Covington, KY 1550 Cranston, RI 1551 Crawfordsville, IN 1552 Cripple Creek, CO 1570 Cumberland, MD 1571 Cumberland, RI 1590 Dallas, TX 1591 Danbury, CT 1630 Danville, IL 1631 Danville, VA 1650 Davenport, IA 1670 Dayton, OH 1690 Decatur, IL 1691 Decatur, AL 1692 Decatur, GA 1693 Dedham, MA 1695 Denison, TX 1710 Denver, CO 1711 Derby, CT 1713 Derry, PA 1730 Des Moines, IA 1750 Detroit, MI 1790 Dover, NH 1791 Dover, NJ 1792 Du Bois, PA 1810 Dubuque, IA 1830 Duluth, MN 1831 Dunkirk, NY 1832 Dunmore, PA 1833 Duquesne, PA 1850 Durham, NC 1870 East Chicago, IN 1891 East Hartford, CT 1892 East Liverpool, OH 1930 East Orange, NJ 1931 East Providence, RI 1940 East Saginaw, MI 1950 East St. Louis, IL 1952 Easthampton, MA 1970 Easton, PA 1971 Eau Claire, WI 2010 El Paso 2030 Elgin, IL 2040 Elyria, OH 2050 Elizabeth, NJ 2060 Elkhart, IN 2062 Elmhurst, IL 2070 Elmira, NY 2072 Elwood, IN 2073 Emporia, KS 2075 Enfield, CT 2080 Enid, OK 2090 Erie, PA 2091 Escanaba 2131 Eureka 2150 Evanston, IL 2170 Evansville, IN 2190 Everett 2210 Everett 2212 Fairfield, CT 2213 Fairhaven, MA 2220 Fargo 2221 Faribault, MN 2230 Fall River, MA 2240 Fayetteville, NC 2242 Findlay, OH 2250 Fitchburg, MA 2270 Flint, MI 2273 Florence, AL 2275 Flushing, NY 2280 Fond du Lac, WI 2301 Fort Dodge, IA 2302 Fort Madison, IA 2303 Fort Scott, KS 2310 Fort Smith, AR 2330 Fort Wayne, IN 2350 Fort Worth, TX 2352 Framingham, MA 2353 Frankfort, IN 2354 Frankfort, KY 2355 Franklin, PA 2356 Frederick, MD 2357 Freeport, NY 2358 Freeport, IL 2359 Fremont, OH 2370 Fresno, CA 2391 Fulton, NY 2392 Gadsden, AL 2393 Galena, KS 2400 Galesburg, IL 2410 Galveston, TX 2411 Gardner, MA 2440 Garfield, NJ 2470 Gary, IN 2472 Geneva, NY 2491 Glens Falls, NY 2510 Gloucester, MA 2511 Gloucester, NJ 2512 Gloversville, NY 2513 Goldsboro, NC 2514 Goshen, IN 2515 Grand Forks, ND 2516 Grand Island, NE 2530 Grand Rapids, MI 2531 Grandville, MI 2540 Great Falls, MT 2550 Green Bay, WI 2551 Greenfield, MA 2570 Greensboro, NC 2571 Greensburg, PA 2572 Greenville, MS 2573 Greenville, SC 2574 Greenville, TX 2575 Greenwich, CT 2576 Greenwood, MS 2577 Greenwood, SC 2578 Griffin, GA 2581 Groton, CT 2583 Guthrie, OK 2584 Hackensack, NJ 2590 Hagerstown, MD 2591 Hamden, CT 2610 Hamilton, OH 2630 Hammond, IN 2650 Hampton, VA 2680 Hannibal, MO 2681 Hanover, PA 2690 Harrisburg, PA 2692 Harrison, NJ 2710 Hartford, CT 2711 Harvey, IL 2713 Hattiesburg, MS 2730 Haverhill, MA 2731 Hawthorne, NJ 2750 Hazleton, PA 2751 Helena, MT 2752 Hempstead, NY 2753 Henderson, KY 2754 Herkimer, NY 2756 Hibbing, MN 2781 Highland Park, IL 2810 Hoboken, NJ 2811 Holland 2850 Holyoke, MA 2851 Homestead, PA 2870 Honolulu, HI 2872 Hopkinsville, KY 2873 Hoquiam, WA 2874 Hornell, NY 2875 Hot Springs, AR 2890 Houston, TX 2891 Hudson, NY 2892 Huntington, IN 2910 Huntington, WV 2950 Huntsville, AL 2960 Hutchinson, KS 2961 Hyde Park, MA 2962 Ilion, NY 2963 Independence, KS 2970 Independence, MO 2990 Indianapolis, IN 3011 Iowa City, IA 3012 Iron Mountain, MI 3013 Ironton, OH 3014 Ironwood, MI 3050 Irvington, NJ 3051 Ishpeming, MI 3052 Ithaca, NY 3070 Jackson, MI 3071 Jackson, MN 3090 Jackson, MS 3091 Jackson, TN 3110 Jacksonville, FL 3111 Jacksonville, IL 3130 Jamestown , NY 3131 Janesville, WI 3132 Jeannette, PA 3133 Jefferson City, MO 3134 Jeffersonville, IN 3150 Jersey City, NJ 3161 Johnstown, NY 3170 Johnstown, PA 3190 Joliet, IL 3191 Jonesboro, AR 3210 Joplin, MO 3230 Kalamazoo, MI 3231 Kankakee, IL 3250 Kansas City, KS 3260 Kansas City, MO 3270 Kearney, NJ 3271 Keene, NH 3290 Kenosha, WI 3291 Keokuk, IA 3293 Key West, FL 3310 Kingston, NY 3312 Kinston, NC 3330 Knoxville, TN 3350 Kokomo, IN 3370 LaCrosse, WI 3380 Lafayette, IN 3390 Lafayette, LA 3391 La Grange, IL 3392 La Grange, GA 3393 La Porte, IN 3394 La Salle, IL 3395 Lackawanna, NY 3396 Laconia, NH 3430 Lakewood, OH 3450 Lancaster, PA 3451 Lancaster, OH 3470 Lansing, MI 3471 Lansingburgh, NY 3480 Laredo, TX 3482 Laurel, MS 3510 Lawrence, MA 3511 Lawrence, KS 3513 Leadville, CO 3520 Leavenworth, KS 3521 Lebanon, PA 3522 Leominster, MA 3530 Lehigh, PA 3550 Lewiston, ME 3551 Lewistown, PA 3570 Lexington, KY 3610 Lima, OH 3630 Lincoln, NE 3631 Lincoln, IL 3633 Lincoln, RI 3635 Little Falls, NY 3638 Lodi, NJ 3639 Logansport, IN 3650 Little Rock, AR 3680 Lockport, NY 3690 Long Beach, CA 3691 Long Branch, NJ 3692 Long Island City, NY 3710 Lorain, OH 3730 Los Angeles, CA 3750 Louisville, KY 3770 Lowell, MA 3790 Macon, GA 3810 Lynn, MA 3830 Macon, GA 3850 Madison, IN 3870 Madison, WI 3871 Mahanoy City, PA 3890 Malden, MA 3891 Mamaroneck, NY 3910 Manchester, NH 3911 Manchester, CT 3912 Manhattan, KS 3913 Manistee, MI 3914 Manitowoc, WI 3915 Mankato, MN 3930 Mansfield, OH 3932 Marietta, OH 3933 Marinette, WI 3934 Marion, IN 3950 Marion, OH 3951 Marlborough, MA 3952 Marquette, MI 3953 Marshall, TX 3954 Marshalltown, IA 3955 Maywood, IL 3956 Martinsburg, WV 3957 Mason City, IA 3958 Massena, NY 3959 Massillon, OH 3961 Mattoon, IL 3962 Mcalester, OK 3963 Mccomb, MS 3964 Mckees Rocks, PA 3970 McKeesport, PA 3971 Meadville, PA 3990 Medford, MA 3992 Melrose, MA 4010 Memphis, TN 4011 Menominee, MI 4030 Meriden, CT 4040 Meridian, MS 4041 Methuen, MA 4120 Michigan City, IN 4122 Middletown, CT 4123 Middletown, NY 4124 Middletown, OH 4125 Milford, CT 4126 Milford, MA 4127 Millville, NJ 4130 Milwaukee, WI 4150 Minneapolis, MN 4151 Minot, ND 4160 Mishawaka, IN 4161 Missoula, MT 4163 Moberly, MO 4170 Mobile, AL 4210 Moline, IL 4211 Monessen, PA 4212 Monroe, MI 4213 Monroe, LA 4230 Montclair, NJ 4250 Montgomery, AL 4251 Morgantown, WV 4252 Morristown, NJ 4253 Moundsville, WV 4255 Mount Carmel, PA 4256 Mount Clemens, MI 4290 Mount Vernon, NY 4291 Mount Vernon, Il 4310 Muncie, IN 4312 Murphysboro, IL 4313 Muscatine, IA 4330 Muskegon, MI 4350 Muskogee, OK 4351 Nanticoke, PA 4390 Nashua, NH 4410 Nashville-Davidson, TN 4411 Nashville, TN 4413 Natchez, MS 4414 Natick, MA 4415 Naugatuck, CT 4430 New Albany, IN 4450 New Bedford, MA 4451 New Bern, NC 4452 New Brighton, NY 4470 New Britain, CT 4490 New Brunswick, NJ 4510 New Castle, PA 4511 New Castle, IN 4530 New Haven, CT 4550 New London, CT 4570 New Orleans, LA 4571 New Philadelphia, OH 4590 New Rochelle, NY 4610 New York, NY 4611 Brooklyn, NY 4630 Newark, NJ 4650 Newark, OH 4670 Newburgh, NY 4690 Newburyport, MA 4710 Newport, KY 4730 Newport, RI 4750 Newport News, VA 4770 Newton, MA 4771 Newton, IA 4790 Niagara Falls, NY 4791 Niles, MI 4792 Niles, OH 4810 Norfolk, VA 4830 Norristown Boro, PA 4831 North Adams, MA 4833 North Bennington, VT 4834 North Braddock, PA 4835 North Branford, CT 4836 North Haven, CT 4839 North Providence, RI 4840 Northampton, MA 4841 North Tonawanda, NY 4842 North Yakima, WA 4843 Northbridge, MA 4870 Norwalk, CT 4890 Norwich, CT 4900 Norwood, OH 4901 Norwood, MA 4910 Oak Park Village 4930 Oakland, CA 4970 Ogden, UT 4971 Ogdensburg, NY 4972 Oil City, PA 4990 Oklahoma City, OK 4993 Old Forge, PA 4994 Olean, NY 4996 Olyphant, PA 5010 Omaha, NE 5012 Oneonta, NY 5050 Orange, NJ 5051 Orange, CT 5090 Oshkosh, WI 5092 Ossining, NY 5110 Oswego, NY 5111 Ottawa, IL 5112 Ottumwa, IA 5113 Owensboro, KY 5116 Painesville, OH 5117 Palestine, TX 5118 Palo Alto, CA 5121 Paris, TX 5122 Park Ridge, IL 5123 Parkersburg, WV 5125 Parsons, KS 5150 Pasadena, CA 5180 Paducah, KY 5190 Passaic, NJ 5210 Paterson, NJ 5230 Pawtucket, RI 5231 Peabody, MA 5232 Peekskill, NY 5233 Pekin, IL 5250 Pensacola, FL 5270 Peoria, IL 5290 Perth Amboy, NJ 5291 Peru, IN 5310 Petersburg, VA 5311 Phenix City, AL 5330 Philadelphia, PA 5331 Kensington 5332 Mayamensing 5333 Northern Liberties 5334 Southwark 5335 Spring Garden 5341 Phillipsburg, NJ 5350 Phoenix, AZ 5351 Phoenixville, PA 5352 Pine Bluff, AR 5353 Piqua, OH 5354 Pittsburg, KS 5370 Pittsburgh, PA 5390 Pittsfield, MA 5391 Pittston, PA 5410 Plainfield, NJ 5411 Plattsburg, NY 5413 Plymouth, PA 5414 Plymouth, MA 5415 Pocatello, ID 5430 Plano, TX 5450 Pomona, CA 5154 Ponca City, OK 5470 Pontiac, MI 5471 Port Angeles, WA 5481 Port Chester, NY 5490 Port Huron, MI 5510 Portland, ME 5511 Portland, IL 5530 Portland, OR 5550 Portsmouth, NH 5570 Portsmouth, OH 5590 Portsmouth, VA 5591 Pottstown, PA 5610 Pottsville, PA 5630 Poughkeepsie, NY 5650 Providence, RI 5660 Provo, UT 5670 Pueblo, CO 5671 Punxsutawney, PA 5690 Quincy, IL 5710 Quincy, MA 5730 Racine, WI 5731 Rahway, NJ 5750 Raleigh, NC 5752 Rapid City, SD 5790 Reading, PA 5791 Red Bank, NJ 5792 Redlands, CA 5810 Reno, NV 5811 Rensselaer, NY 5830 Revere, MA 5850 Richmond, IN 5870 Richmond, VA 5890 Riverside, CA 5910 Roanoke, VA 5930 Rochester, NY 5931 Rochester, NH 5932 Rochester, MN 5933 Rock Hill, SC 5950 Rock Island, IL 5970 Rockford, IL 5971 Rockland, ME 5973 Rockville Centre, NY 5990 Rome, NY 5991 Rome, GA 5993 Roselle, NJ 5994 Roswell, NM 6010 Roxbury, MA 6011 Royal Oak, MI 6012 Rumford Falls, ME 6014 Rutland, VT 6030 Sacramento, CA 6050 Saginaw, MI 6070 Saint Joseph, MO 6090 Saint Louis, MO 6110 Saint Paul, MN 6130 Saint Petersburg, FL 6150 Salem, MA 6170 Salem, OR 6171 Salem, OH 6172 Salina, KS 6190 Salinas, CA 6191 Salisbury, NC 6192 Salisbury, MD 6210 Salt Lake City, UT 6211 San Angelo, TX 6230 San Antonio, TX 6250 San Bernadino, CA 6270 San Diego, CA 6280 Sandusky, OH 6282 Sanford, ME 6290 San Francisco, CA 6310 San Jose, CA 6311 San Leandro, CA 6312 San Mateo, CA 6320 Santa Barbara, CA 6321 Santa Cruz, CA 6322 Santa Fe, NM 6330 Santa Ana, CA 6350 Santa Rosa, CA 6352 Saratoga Springs, NY 6353 Saugus, MA 6354 Sault Ste. Marie, MI 6370 Savannah, GA 6390 Schenectedy, NY 6410 Scranton, PA 6430 Seattle, WA 6431 Sedalia, MO 6432 Selma, AL 6435 Shamokin, PA 6437 Sharpsville, PA 6438 Shawnee, OK 6440 Sharon, PA 6450 Sheboygan, WI 6451 Shelby, NC 6452 Shelbyville, IN 6470 Shenandoah Borough, PA 6471 Sherman, TX 6490 Shreveport, LA 6510 Sioux City, IA 6530 Sioux Falls, SD 6550 Smithfield, RI 6570 Somerville, MA 6590 South Bend, IN 6591 South Bethlehem, PA 6592 South Boise, ID 6594 South Milwaukee, WI 6595 South Norwalk, CT 6610 South Omaha, NE 6611 South Orange, NJ 6613 South Pittsburgh, PA 6614 South Portland, ME 6615 South River, NJ 6616 South St. Paul, MN 6617 Southbridge, MA 6620 Spartanburg, SC 6630 Spokane, WA 6650 Springfield, IL 6670 Springfield, MA 6690 Springfield, MO 6691 St. Augustine, FL 6692 St. Charles, MO 6693 St. Cloud, MN 6710 Springfield, OH 6730 Stamford, CT 6732 Staunton, VA 6733 Steelton, PA 6770 Steubenville, OH 6772 Stillwater, MN 6790 Stockton, CA 6791 Stoneham, MA 6792 Stonington, CT 6793 Stratford, CT 6794 Streator, IL 6797 Summit, NJ 6798 Sumter, SC 6799 Sunbury, PA 6830 Superior, WI 6831 Swampscott, MA 6832 Sweetwater, TX 6833 Swissvale, PA 6850 Syracuse, NY 6870 Tacoma, WA 6872 Tamaqua, PA 6890 Tampa, FL 6910 Taunton, MA 6912 Temple, TX 6950 Terre Haute, IN 6951 Texarkana, TX 6954 Tiffin, OH 6970 Toledo, OH 6990 Topeka, KS 6991 Torrington, CT 6992 Traverse City, MI 7010 Trenton, NJ 7011 Trinidad, CO 7030 Troy, NY 7050 Tucson, AZ 7070 Tulsa, OK 7071 Turtle Creek, PA 7072 Tuscaloosa, AL 7073 Two Rivers, WI 7074 Tyler, TX 7080 Union City, NJ 7081 Uniontown, PA 7083 Urbana, IL 7090 Utica, NY 7091 Valdosta, GA 7092 Vallejo, CA 7110 Vallejo, CA 7120 Vicksburg, MS 7121 Vincennes, IN 7122 Virginia, MN 7123 Virginia City, NV 7150 Waco, TX 7151 Wakefield, MA 7152 Walla Walla, WA 7153 Wallingford, CT 7170 Waltham, MA 7190 Warren, OH 7191 Warren, PA 7210 Warwick Town, RI 7230 Washington, DC 7231 Georgetown, DC 7241 Washington, PA 7250 Waterbury, CT 7270 Waterloo, IA 7290 Waterloo, NY 7310 Watertown, NY 7311 Watertown, WI 7313 Watertown, MA 7314 Waterville, ME 7315 Watervliet, NY 7316 Waukegan, IL 7318 Wausau, WI 7319 Wauwatosa, WI 7321 Waycross, GA 7322 Waynesboro, PA 7323 Webb City, MO 7325 Webster, MA 7326 Wellesley, MA 7329 West Bay City, MI 7330 West Hoboken, NJ 7331 West Bethlehem, PA 7332 West Chester, PA 7334 West Hartford, CT 7335 West Haven, CT 7350 West New York, NJ 7351 West Orange, NJ 7353 West Springfield, MA 7370 West Troy, NY 7372 Westbrook, ME 7373 Westerly, RI 7374 Westfield, MA 7377 Weymouth, MA 7390 Wheeling, WV 7400 White Plains, NY 7401 Whiting, IN 7410 Wichita, KS 7430 Wichita Falls, TX 7450 Wilkes-Barre, PA 7451 Wilkinsburg, PA 7470 Williamsport, PA 7471 Willimantic, CT 7472 Wilmette, IL 7490 Wilmington, DE 7510 Wilmington, NC 7511 Wilson, NC 7512 Winchester, VA 7513 Winchester, MA 7514 Windham 7515 Winnetka, IL 7516 Winona, MN 7530 Winston-Salem, NC 7531 Winthrop, MA 7532 Woburn, MA 7550 Woonsocket, RI 7551 Wooster, OH 7570 Worcester, MA 7571 Wyandotte, MI 7572 Xenia, OH 7590 Yonkers, NY 7610 York, PA 7630 Youngstown, OH 7631 Ypsilanti, MI 7650 Zanesville, OH 9010 Summerside, PEI 9020 Charlottetown , PEI 9030 Georgetown Royalty, PEI 9105 Cheticamp, NS 9110 Lingan, NS 9115 Sydney, NS 9120 Halifax, NS 9125 Dartmouth, NS 9130 Shelburne, NS 9140 Marshall, NS 9145 Windsor, NS 9150 Scotch, NS 9155 Truro, NS 9160 Pictou, NS 9165 New Glasgow, NS 9170 Mills, NS 9210 St. John, NB 9215 Portland , NB 9220 St. Stephen, NB 9230 St. Andrews, NB 9240 Miltown, NB 9250 Upper Mills, NB 9260 Fredericton, NB 9270 Moncton, NB 9301 Schoolbred, QC 9302 Escuminac, QC 9303 Gaspé, QC 9304 Rimouski, QC 9305 Fraserville, QC 9306 Cacouna, QC 9307 Kamouraska, QC 9308 Montmagny, QC 9309 Lévis, QC 9310 Lauzon, QC 9311 Bienville, QC 9312 Ste. Émélie, Leclercville, QC 9313 Plessisville, QC 9314 Larochelle, QC 9315 Nicolet, QC 9316 Arthabaskaville, QC 9317 Warwick, QC 9318 Princeville, QC 9319 Drummondville, QC 9320 Victoriaville, QC 9321 Richmond, QC 9322 Windsor Mills, QC 9323 Danville, QC 9324 Melbourne, QC 9325 Waterville, QC 9326 Sherbrooke, QC 9327 Lennoxville, QC 9328 Coaticook, QC 9329 Stanstead Plain, QC 9330 Dixville, QC 9331 Beebe Plains, QC 9332 Yamaska, QC 9333 Actonvale, QC 9334 St. Ephrem d'Upton, QC 9335 Waterloo, QC 9336 Roxton Falls, QC 9337 Granby, QC 9338 Sorel, QC 9339 St. Ours, QC 9340 St-Hyacinthe, QC 9341 St. Césaire, QC 9342 Marieville, QC 9343 Richelieu, QC 9344 Canrobert, QC 9345 Iberville, QC 9346 Farnham, QC 9347 Dunham, QC 9348 Frelighsburg, QC 9349 Philipsburg, QC 9350 Varennes, QC 9351 Longueuil, QC 9352 Chambly, QC 9353 Boucherville, QC 9354 St. Jean, QC 9355 Laprairie, QC 9356 Napierville, QC 9357 St. Rémi, QC 9358 Howick, QC 9359 Huntingdon, QC 9360 Valleyfield, QC 9361 Beauharnois, QC 9362 Coteau Landing, QC 9363 Les Cèdres, QC 9364 Rigaud, QC 9365 Vaudreuil, QC 9366 Chicoutimi, QC 9367 Bagotville, QC 9368 Pointe-au-Pic, QC 9369 Ste-Pétronille-de-Beaulieu, QC 9370 Québec, QC 9371 Trois-Rivières, QC 9372 Louiseville, QC 9373 Berthier, QC 9374 Joliette, QC 9375 L'Assomption, QC 9376 Montréal, QC 9377 St-Henri, QC 9378 St-Jean-Baptiste, QC 9379 Ste-Cunégonde, QC 9380 St-Gabriel, QC 9381 Hochelaga, QC 9382 Côte-St-Louis, QC 9383 St-Louis, Mile End, QC 9384 Notre-Dame-de-Grâce, QC 9385 Côte-des-Neiges, QC 9386 Côte-St-Paul, QC 9387 Côte-St-Antoine, QC 9388 Côte-la-Visitation, QC 9389 Outremont, QC 9390 Verdun, QC 9391 Lachine, QC 9392 Ste-Anne-de-Bellevue, QC 9393 Ste-Geneviève, QC 9394 Pointe-Claire, QC 9395 Ste-Rose, QC 9396 St-Jérôme, QC 9397 Terrebonne, QC 9398 Ste-Thérèse, QC 9399 New Glasgow, QC 9400 St-Eustache, QC 9401 Ste-Scholastique, QC 9402 Grenville, QC 9403 Hull , QC 9404 Aylmer, QC 9405 L'Ange-Gardien, QC 9406 Buckingham, QC 9407 Gatineau, QC 9408 Monte Bello, QC 9409 Shawville, QC 9410 Chapeau, Calumet Island, QC 9411 Bryson, Litchfield, QC 9412 Quyon, Onlow, QC 9500 Cornwall, ON 9501 Morrisburg, ON 9502 Hawkesbury, ON 9503 L'Orignal, ON 9504 New-Edinburg, ON 9505 Ottawa, ON 9506 Prescott, ON 9507 Kemptville, ON 9508 Merrickville, ON 9509 Richmond, ON 9510 Brockville, ON 9511 Gananoque, ON 9512 Newboro, ON 9513 Perth, ON 9514 Smith's Falls, ON 9515 Carleton Place, ON 9516 Almonte, ON 9517 Lanark, ON 9518 Arnprior, ON 9519 Renfrew, ON 9520 Pembroke, ON 9521 Portsmouth, ON 9522 Garden Island, ON 9523 Kingston, ON 9524 Napanee, ON 9525 Bath, ON 9526 Newburg, ON 9527 Picton, ON 9528 Wellington, ON 9529 Mill Point , ON 9530 Belleville, ON 9531 Trenton, ON 9532 Madoc, ON 9533 Sterling, ON 9534 Brighton, ON 9535 Campbelford, ON 9536 Colborne, ON 9537 Hastings, ON 9538 Cobourg, ON 9539 Ashburnham, ON 9540 Norwood, ON 9541 Hastings, ON 9542 Peterborough, ON 9543 Port Hope, ON 9544 Millbrook, ON 9545 Bowmanville, ON 9546 Newcastle, ON 9547 Lindsay, ON 9548 Bobcaygeon, ON 9549 Omemee, ON 9550 Fenelon Falls, ON 9551 Macauly, Bracebridge, ON 9552 Parrysound, ON 9553 Oshawa, ON 9554 Whitby, ON 9555 Uxbridge, ON 9556 Port Perry, ON 9557 Cannington, ON 9558 Toronto, ON 9559 Yorkville, ON 9560 Markham, ON 9561 Stouffville, ON 9562 Parkdale, ON 9563 Richmond Hill, ON 9564 Brockton, ON 9565 Newmarket, ON 9566 Aurora, ON 9567 Holland Landing, ON 9568 Stouffville, ON 9569 Bradford, ON 9570 Alleston, ON 9571 Barrie, ON 9572 Collingwood, ON 9573 Orillia, ON 9574 Midland, ON 9575 Stayner, ON 9576 Brampton, ON 9577 Streetsville, ON 9578 Bolton, ON 9579 Thorold, ON 9580 Clifton, ON 9581 Welland, ON 9582 Port Colborne, ON 9583 Port Erie, ON 9584 Chippawa, ON 9585 Niagara, ON 9586 Dunville, ON 9587 St. Catharines, ON 9588 Merritton, ON 9589 Port Dalhousie, ON 9590 Grimsby, ON 9591 Beamsville, ON 9592 Caledonia, ON 9593 Cayuga, ON 9594 Dundas, ON 9595 Hamilton, ON 9596 Oakville, ON 9597 Georgetown, ON 9598 Milton, ON 9599 Burlington, ON 9600 Acton, ON 9601 Guelph, ON 9602 Orangeville, ON 9603 Fergus, ON 9604 Elora, ON 9605 Drayton, ON 9606 Mount Forest, ON 9607 Harriston, ON 9608 Arthur, ON 9609 Clifford, ON 9610 Palmerston, ON 9611 Shelburne, ON 9612 Durham, ON 9613 Meaford, ON 9614 Shelburne, ON 9615 Owen Sound, ON 9616 Brook, ON 9617 Port Dover, ON 9618 Simcoe, ON 9619 Waterford, ON 9620 Tilsonburg, ON 9621 Brantford, ON 9622 Paris, ON 9623 Galt, ON 9624 Preston, ON 9625 New Hamburg, ON 9626 Hespeler, ON 9627 Berlin, ON 9628 Waterloo, ON 9629 St. Thomas, ON 9630 Aylmer, ON 9631 Port Stanley, ON 9632 Springfield, ON 9633 Vienna, ON 9634 Ingersoll, ON 9635 Norwich, ON 9636 Woodstock, ON 9639 Petersville, ON 9640 Strathrey, ON 9641 Glencoe, ON 9642 Newbury, ON 9643 Wardsville, ON 9644 Park Hill, ON 9645 Lucan, ON 9646 Ailsa Craig, ON 9647 London, ON 9648 St. Mary's, ON 9649 Mitchell, ON 9650 Stratford, ON 9651 Listowell, ON 9652 Palmerston, ON 9653 Milverton, ON 9654 Clinton, ON 9655 Exeter, ON 9656 Bayfield, ON 9657 Goderich, ON 9658 Seaforth, ON 9659 Wingham, ON 9660 Blyth, ON 9661 Wroxeter, ON 9662 Brussels, ON 9663 Lucknow, ON 9664 Kincardiné, ON 9665 Walkerton, ON 9666 Teeswater, ON 9667 Lucknow, ON 9668 Tiverton, ON 9669 Port Elgin, ON 9670 Paisley, ON 9671 Southampton, ON 9672 Chesley, ON 9673 Wiarton, ON 9674 Tara, ON 9675 Dresden, ON 9676 Ridgetown, ON 9677 Thamesville, ON 9678 Sarnia, ON 9679 Petrolia, ON 9680 Forest, ON 9681 Point Edward, ON 9682 Watford, ON 9683 Wyoming, ON 9684 Alvinston, ON 9685 Thedford, ON 9686 Arkona, ON 9687 Oil Springs, ON 9688 Chatham, ON 9689 Wallaceburgh, ON 9690 Blenheim, ON 9691 Windsor, ON 9692 Amherstburg, ON 9693 Leamington, ON 9694 Sandwich, ON 9695 Kingsville, ON 9696 Belle River, ON 9710 Winnipeg, MB 9720 Emerson, MB 9810 Victoria, BC 9820 Vancouver CITYH identifies the city of residence for the United States historical samples and Canada 1881. Canadian cities are numbered from 9010 to 9810, and the codes do not overlap with the existing range of values for cities in the United States. IPUMS City population, historical US and Canada 002853 011485 001118 002726 004125 003667 036100 003786 002055 001077 003019 002611 003461 003403 002595 003340 026127 015226 003412 002338 002128 001664 000318 006218 005032 000369 000221 000174 001417 002291 000648 000771 001738 007597 003556 001022 001269 000776 002164 000371 000992 000929 000900 000764 000699 001571 000879 000825 000305 000413 007227 000788 002682 000578 000380 000372 000456 001860 000814 001617 001170 001040 005791 000808 005321 001103 000999 000785 000347 001847 001880 000286 000278 000259 000612 002355 001506 001165 004314 001340 000922 000909 000203 000856 003906 001499 000511 000208 000607 000439 001935 000508 000376 000333 062446 008670 001381 002156 003268 001313 140747 006415 005874 004849 004506 004111 001537 001524 000988 000949 000884 000462 000387 002406 001163 000751 000443 000839 002032 001398 001314 000300 000790 000568 006890 001762 001549 001479 001460 000597 001827 001715 001603 001332 004468 001719 001920 000853 000995 027412 002999 001188 000819 007609 002871 000418 002467 002087 001975 002684 000752 002147 001605 002820 001734 000495 014091 003680 000546 000834 002975 000598 001670 009516 003042 001065 000874 001547 001418 001079 000193 004957 001266 000692 006812 005585 001148 003504 001060 005080 000750 000744 001155 002135 001300 003992 003140 001824 001800 086415 004825 000954 000459 000867 000786 002006 001540 000580 000407 001176 001099 004854 004445 002910 001095 001028 002920 000755 000606 002456 002347 001870 001716 000722 000664 001441 001808 009631 001798 001129 000685 001242 000830 003709 035961 001710 001471 001302 001068 000848 009890 002847 001733 001387 000587 002170 001772 001257 000536 000242 001059 001866 000491 004426 001146 002645 000066 009616 003173 005187 001419 001240 000698 004054 002066 008367 000674 000555 000528 004318 001411 005373 001601 003817 000801 000540 001539 000976 000872 019746 003415 002284 008239 002688 001292 000562 002606 001725 000679 004564 002480 001918 000914 000590 000561 000444 002876 002604 000861 000718 000545 001400 001154 001141 000893 000796 001979 001538 000740 003874 003465 001614 001293 001132 000886 000569 000552 007873 001525 001212 006561 002672 001143 000863 000556 007985 000977 005925 000000 CITYPOPH reports the population, in hundreds, for all incorporated municipalities in United States census datasets from 1850 to 1910. For the 1881 Canadian census, CITYPOPH is defined similarly as the population of incorporated places. For the U.S. 1880 complete count census, CITYPOPH reports the population for all incorporated municipalities and for the portion of New England towns considered "urban" by the Census Bureau, as well as for a few other non-incorporated areas in other parts of the country. (See URBAN for discussion of how the U.S. Census Bureau defined the urban population.) See CITYH for identification of specific U.S. and Canadian cities. Aggregate data for the 1880 complete count census for cities and counties is available in digital format for users with access to ICPSR, from datasets DS16, DS17, DS18, and DS48 in ICPSR File 02896. The original publications for the aggregate data are available to all users from the U.S. Census Bureau in PDF format. Publications from censuses other than 1880 are also available from the Census Bureau. The source for Canadian city populations is Table I in the publication, Census of Canada, 1880-81, Volume 1 (Ottawa: MacLean, Roger and Co. Printers, Wellington Street, 1882). A scanned copy of this table is available. It contains aggregate statistics for each Canadian census sub-district (SDSTCA) and district (DISTCA) on the number of Dwellings, sub-divided into vessels, shanties, inhabited, uninhabited, and under construction Families Population, by sex Married population, by sex Widowed population, by sex Children and unmarried population, by sex Additionally, the scanned table reports the area in square miles, square kilometers, and acres for every Canadian district in 1881. The latter information is available in the variable CNTYAREAH. The final page of the document contains summary statistics for the provinces (GEO1_CA1852_1911) and the country for all the aforementioned variables. IPUMS Size of place, historical US and Canada 00 Not identifiable 01 Under 1,000 or unincorporated 02 1,000-2,499 03 2,500-3,999 04 4,000-4,999 05 5,000-9,999 06 10,000-24,999 07 25,000-49,999 08 50,000-74,999 09 75,000-99,999 10 100,000-199,999 20 200,000-299,999 30 300,000-399,999 40 400,000-499,999 50 500,000-599,999 60 600,000-749,999 70 750,000-999,999 80 1,000,000-1,999,999 90 2,000,000+ SIZEPLH is a recode of CITYPOPH, grouping places of similar size. See CITYPOPH for more precise figures of city population (in hundreds) for the U.S. and Canada, and see CITYH for identification of specific cities. IPUMS United States, State 1850 - 2020 [Level 1; consistent boundaries, GIS] 840001 Alabama 840002 Alaska 840004 Arizona 840005 Arkansas 840006 California 840008 Colorado 840009 Connecticut 840010 Delaware 840011 District of Columbia 840012 Florida 840013 Georgia 840015 Hawaii 840016 Idaho 840017 Illinois 840018 Indiana 840019 Iowa 840020 Kansas 840021 Kentucky 840022 Louisiana 840023 Maine 840024 Maryland 840025 Massachusetts 840026 Michigan 840027 Minnesota 840028 Mississippi 840029 Missouri 840030 Montana 840031 Nebraska 840032 Nevada 840033 New Hampshire 840034 New Jersey 840035 New Mexico 840036 New York 840037 North Carolina 840038 North Dakota 840039 Ohio 840040 Oklahoma 840041 Oregon 840042 Pennsylvania 840044 Rhode Island 840045 South Carolina 840046 South Dakota 840047 Tennessee 840048 Texas 840049 Utah 840050 Vermont 840051 Virginia 840053 Washington 840054 West Virginia 840055 Wisconsin 840056 Wyoming 840099 State unknown GEO1_US identifies the household's state within the United States in all sample years. States are the first level administrative units of the country. GEO1_US is spatially harmonized to account for political boundary changes across census years; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_US can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for the United States can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS United States, State 1850 001 Alabama 005 Arkansas 006 California 009 Connecticut 010 Delaware 011 District of Columbia 012 Florida 013 Georgia 017 Illinois 018 Indiana 019 Iowa 021 Kentucky 022 Louisiana 023 Maine 024 Maryland 025 Massachusetts 026 Michigan 027 Minnesota 028 Mississippi 029 Missouri 033 New Hampshire 034 New Jersey 035 New Mexico 036 New York 037 North Carolina 039 Ohio 041 Oregon 042 Pennsylvania 044 Rhode Island 045 South Carolina 047 Tennessee 048 Texas 049 Utah 050 Vermont 051 Virginia 053 Washington 054 West Virginia 055 Wisconsin GEO1_US1850 identifies the household's state within the United States in 1850. States are the primary level of geography for the United States. GEO1_US1850 harmonizes both the complete count and the 1-in-100 national random sample of the free population. Other geography variables from 1850 United States include STATICUS, COUNTYUS, and METRO. IPUMS United States, County COUNTYUS identifies the household's county of enumeration using the Inter-University Consortium for Political and Social Research (ICPSR) coding scheme. Counties are assigned codes alphabetically within states. The first 3 digits are identical to the FIPS county codes used in other datasets; ICPSR adds a digit to the FIPS codes to accommodate change over time. COUNTY allows the IPUMS-USA and IPUMS International pre-1950 data to be easily merged with ICPSR data. The variable also identifies areas that were not part of any county, including the independent cities of Virginia and some Indian lands. For more information, see "ICPSR County Codes" on the IPUMS-USA website. COUNTY is a state-dependent variable; it must be read in combination with the State variable (last two digits of GEO1_US) to distinguish between counties located in different states. Note that many county boundaries and some county names changed over time. We have not attempted to impose a uniform county boundary system on the data, so a particular county listed for a particular year should be assumed to have the boundaries that it had in that year. GIS boundary files can be obtained from the IPUMS NHGIS site. COUNTYUS is completely compatible with the IPUMS-USA variable COUNTY. COUNTY is a 4-digit numeric variable. CodesSee "ICPSR County Codes," on the IPUMS website under "Geographic Tools," Volume 2: User's Guide Supplement for county codes. 9999: Unknown IPUMS United States, Metropolitan area 000 Household not in an identifiable metropolitan area 004 Abilene, TX 008 Akron, OH 012 Albany, GA 016 Albany-Schenectady-Troy, NY 020 Albuquerque, NM 022 Alexandria, LA 024 Allentown-Bethlehem-Easton, PA/NJ 028 Altoona, PA 032 Amarillo, TX 038 Anchorage, AK 040 Anderson, IN 044 Ann Arbor, MI 045 Anniston, AL 046 Appleton-Oskosh-Neenah, WI 048 Asheville, NC 050 Athens, GA 052 Atlanta, GA 056 Atlantic City, NJ 058 Auburn-Opelika, AL 060 Augusta-Aiken, GA-SC 064 Austin, TX 068 Bakersfield, CA 072 Baltimore, MD 073 Bangor, ME 074 Barnstable-Yarmouth, MA 076 Baton Rouge, LA 078 Battle Creek, MI 084 Beaumont-Port Arthur-Orange, TX 086 Bellingham, WA 087 Benton Harbor, MI 088 Billings, MT 092 Biloxi-Gulfport, MS 096 Binghamton, NY 100 Birmingham, AL 101 Bismarck, ND 102 Bloomington, IN 104 Bloomington-Normal, IL 108 Boise City, ID 112 Boston, MA 114 Bradenton, FL 115 Bremerton, WA 116 Bridgeport, CT 120 Brockton, MA 124 Brownsville - Harlingen-San Benito, TX 126 Bryan-College Station, TX 128 Buffalo-Niagara Falls, NY 130 Burlington, NC 131 Burlington, VT 132 Canton, OH 135 Casper, WY 136 Cedar Rapids, IA 140 Champaign-Urbana-Rantoul, IL 144 Charleston-N.Charleston,SC 148 Charleston, WV 152 Charlotte-Gastonia-Rock Hill, SC 154 Charlottesville, VA 156 Chattanooga, TN/GA 158 Cheyenne, WY 160 Chicago-Gary-Lake IL 162 Chico, CA 164 Cincinnati, OH/KY/IN 166 Clarksville- Hopkinsville, TN/KY 168 Cleveland, OH 172 Colorado Springs, CO 174 Columbia, MO 176 Columbia, SC 180 Columbus, GA/AL 184 Columbus, OH 188 Corpus Christi, TX 190 Cumberland, MD/WV 192 Dallas-Fort Worth, TX 193 Danbury, CT 195 Danville, VA 196 Davenport, IA-Rock Island-Moline, IL 200 Dayton-Springfield, OH 202 Daytona Beach, FL 203 Decatur, AL 204 Decatur, IL 208 Denver-Boulder-Longmont, CO 212 Des Moines, IA 216 Detroit, MI 218 Dothan, AL 219 Dover, DE 220 Dubuque, IA 224 Duluth-Superior, MN/WI 228 Dutchess County, NY 229 Eau Claire, WI 231 El Paso, TX 232 Elkhart-Goshen, IN 233 Elmira, NY 234 Enid, OK 236 Erie, PA 240 Eugene-Springfield, OR 244 Evansville, IN/KY 252 Fargo-Moorhead, ND/MN 256 Fayetteville, NC 258 Fayetteville-Springdale, AR 260 Fitchburg-Leominster, MA 262 Flagstaff, AZ 264 Flint, MI 265 Florence, AL 266 Florence, SC 267 Fort Collins-Loveland, CO 268 Fort Lauderdale-Hollywood-Pompano Beach, FL 270 Fort Myers-Cape Coral, FL 271 Fort Pierce, FL 272 Fort Smith, AR/OK 275 Fort Walton Beach, FL 276 Fort Wayne, IN 284 Fresno, CA 288 Gadsden, AL 290 Gainesville, FL 292 Galveston-Texas City, TX 297 Glens Falls, NY 298 Goldsboro, NC 299 Grand Forks, ND/MN 300 Grand Rapids, MI 301 Grand Junction, CO 304 Great Falls, MT 306 Greeley, CO 308 Green Bay, WI 312 Greensboro-Winston Salem-High Point, NC 315 Greenville, NC 316 Greenville-Spartenburg-Anderson, SC 318 Hagerstown, MD 320 Hamilton-Middleton, OH 324 Harrisburg-Lebanon-Carlisle, PA 328 Hartford-Bristol-Middletown-New Britian, CT 329 Hickory-Morgantown, NC 330 Hattiesburg, MS 332 Honolulu, HI 335 Houma-Thibodoux, LA 336 Houston-Brazoria, TX 340 Huntington-Ashland, WV/KY/OH 344 Huntsville, AL 348 Indianapolis, IN 350 Iowa City, IA 352 Jackson, MI 356 Jackson, MS 358 Jackson, TN 359 Jacksonville, FL 360 Jacksonville, NC 361 Jamestown-Dunkirk, NY 362 Janesville-Beloit, WI 366 Johnson City-Kingsport-Bristol, TN/VA 368 Johnstown, PA 371 Joplin, MO 372 Kalamazoo-Portage, MI 374 Kankakee, IL 376 Kansas City, MO-KS 380 Kenosha, WI 381 Killeen-Temple, TX 384 Knoxville, TN 385 Kokomo, IN 387 LaCrosse, WI 388 Lafayette, LA 392 Lafayette-W. Lafayette,IN 396 Lake Charles, LA 398 Lakeland-Winterhaven, FL 400 Lancaster, PA 404 Lansing-E. Lansing, MI 408 Laredo, TX 410 Las Cruces, NM 412 Las Vegas, NV 415 Lawrence, KS 420 Lawton, OK 424 Lewiston-Auburn, ME 428 Lexington-Fayette, KY 432 Lima, OH 436 Lincoln, NE 440 Little Rock-North Little Rock, AR 441 Long Branch-Asbury Park, NJ 442 Longview-Marshall, TX 444 Lorain-Elyria, OH 448 Los Angeles-Long Beach, CA 452 Louisville, KY/IN 460 Lubbock, TX 464 Lynchburg, VA 468 Macon-Warner Robins, GA 472 Madison, WI 476 Manchester, NH 480 Mansfield, OH 488 McAllen-Edinburg-Pharr-Mission, TX 489 Medford, OR 490 Melbourne-Titusville-Cocoa-Palm Bay, FL 492 Memphis, TN/AR/MS 494 Merced, CA 500 Miami-Hialeah, FL 504 Midland, TX 508 Milwaukee, WI 512 Minneapolis-St. Paul, MN 516 Mobile, AL 517 Modesto, CA 519 Monmouth-Ocean, NJ 520 Monroe, LA 524 Montgomery, AL 528 Muncie, IN 532 Muskegon-Norton Shores-Muskegon Heights, MI 533 Myrtle Beach, SC 534 Naples, FL 535 Nashua, NH 536 Nashville, TN 540 New Bedford, MA 546 New Brunswick-Perth Amboy-Sayreville, NJ 548 New Haven-Meriden, CT 552 New London-Norwich, CT/RI 556 New Orleans, LA 560 New York-Northeastern NJ 564 Newark, OH 566 Newburgh-Middletown, NY 572 Norfolk-VA Beach-Newport News, VA 576 Norwalk, CT 579 Ocala, FL 580 Odessa, TX 588 Oklahoma City, OK 591 Olympia, WA 592 Omaha, NE/IA 595 Orange County, NY 596 Orlando, FL 599 Owensboro, KY 601 Panama City, FL 602 Parkersburg-Marietta,WV/OH 603 Pascagoula-Moss Point, MS 608 Pensacola, FL 612 Peoria, IL 616 Philadelphia, PA/NJ 620 Phoenix, AZ 624 Pine Bluff, AR 628 Pittsburgh-Beaver Valley, PA 632 Pittsfield, MA 640 Portland, ME 644 Portland-Vancouver, OR 645 Portsmouth-Dover-Rochester, NH/ME 646 Poughkeepsie, NY 648 Providence-Fall River-Pawtuckett, MA 652 Provo-Orem, UT 656 Pueblo, CO 658 Punta Gorda, FL 660 Racine, WI 664 Raleigh-Durham, NC 666 Rapid City, SD 668 Reading, PA 669 Redding, CA 672 Reno, NV 674 Richland-Kennewick-Pasco, WA 676 Richmond-Petersburg, VA 678 Riverside-San Bernadino,CA 680 Roanoke, VA 682 Rochester, MN 684 Rochester, NY 688 Rockford, IL 689 Rocky Mount, NC 692 Sacramento, CA 696 Saginaw-Bay City-Midland, MI 698 St. Cloud, MN 700 St. Joseph, MO 704 St. Louis, MO-IL 708 Salem, OR 712 Salinas-Sea Side-Monterey, CA 714 Salisbury-Concord, NC 716 Salt Lake City-Ogden, UT 720 San Angelo, TX 724 San Antonio, TX 732 San Diego, CA 736 San Francisco-Oakland-Vallejo, CA 740 San Jose, CA 746 San Luis Obispo-Atascad-P Robles, CA 747 Santa Barbara-Santa Maria-Lompoc, CA 748 Santa Cruz, CA 749 Santa Fe, NM 750 Santa Rosa-Petaluma, CA 751 Sarasota, FL 752 Savannah, GA 756 Scranton-Wilkes-Barre, PA 760 Seattle-Everett, WA 761 Sharon, PA 762 Sheboygan, WI 764 Sherman-Denison, TX 768 Shreveport, LA 772 Sioux City, IA/NE 776 Sioux Falls, SD 780 South Bend-Mishawaka, IN 784 Spokane, WA 788 Springfield, IL 792 Springfield, MO 800 Springfield-Holyoke-Chicopee, MA 804 Stamford, CT 805 State College, PA 808 Steubenville-Weirton,OH/WV 812 Stockton, CA 814 Sumter, SC 816 Syracuse, NY 820 Tacoma, WA 824 Tallahassee, FL 828 Tampa-St. Petersburg-Clearwater, FL 832 Terre Haute, IN 836 Texarkana, TX/AR 840 Toledo, OH/MI 844 Topeka, KS 848 Trenton, NJ 852 Tucson, AZ 856 Tulsa, OK 860 Tuscaloosa, AL 864 Tyler, TX 868 Utica-Rome, NY 873 Ventura-Oxnard-Simi Valley 875 Victoria, TX 876 Vineland-Milville-Bridgetown, NJ 878 Visalia-Tulare -Porterville, CA 880 Waco, TX 884 Washington, DC/MD/VA 888 Waterbury, CT 892 Waterloo-Cedar Falls, IA 894 Wausau, WI 896 West Palm Beach-Boca Raton -Delray Beach, FL 900 Wheeling, WV/OH 904 Wichita, KS 908 Wichita Falls, TX 914 Williamsport, PA 916 Wilmington, DE/NJ/MD 920 Wilmington, NC 924 Worcester, MA 926 Yakima, WA 927 Yolo, CA 928 York, PA 932 Youngstown-Warren, OH-PA 934 Yuba City, CA 936 Yuma, AZ METROUS indicates the household's census metropolitan area in the United States from 1850 to present. METROUS is harmonized by name and does not account for boundary changes over time. Metropolitan areas are counties or combinations of counties centering on a substantial urban area. METROUS identifies the household's metropolitan area of enumeration if the household was located in a metropolitan area large enough to meet confidentiality requirements. The full set of geography variables for the United States can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS United States, State Economic Area SEAUS stands for State Economic Area, a concept described fully in Donald J. Bogue, State Economic Areas, (Washington D.C., 1951). SEAs are generally either single counties or groups of contiguous counties within the same state that had similar economic characteristics when they were originally defined prior to the 1950 census. IPUMS United States, County GIS identifier NHGISJOIN is a county identifier that can be used to match IPUMS International pre 1950 data with the county-level boundary files and aggregate data from the National Historical Geographic Information System (NHGIS). The corresponding variable in NHGIS is called "GISJOIN2." Researchers can use this variable to match IPUMS International pre 1950 data with NHGIS boundary files (to make maps) or to match NHGIS county-level data with NAPP microdata for the United States (to facilitate multi-level analysis). For user convenience, copies of the NHGIS boundary files are available on the IPUMS County Codes page. NHGIS aggregate data are available via the "Data Finder" link on the front page of the NHGIS homepage. CodesNHGISJOIN is a 7-digit numeric variable. A small number of cases in NAPP cannot be matched to the NHGIS. These are coded as 9999999 in NHGISJOIN. These were non-county areas such as Indian reservations and military installations. There were 6 such counties in 1900 and 1 in 1910. A small number of counties in NHGIS cannot be matched to NAPP data for the United States. In all cases, these were very small counties that were not captured by the IPUMS sampling procedures. All of these counties contained fewer than 1,000 people; many were administrative areas with no population at all. There were 9 such counties in 1850, 56 in 1860, 32 in 1870, 33 in 1880, 2 in 1900 and 1910, and none in 1920 and 1930. IPUMS Farm status, IPUMS historical 1 Non-farm 2 Farm FARMIPUM identifies farm households according to the IPUMS-USA definition. Any household containing a person with the occupation "farmer" is coded as a farm, including group quarters. Farmers are identified as individuals with an OCCHISCO code between 61110 and 61400. In the United States, we also check if there is anyone in the household with an US1880A_0406 code of 100. For the two percent sample of United Kingdom 1851, we use the OCCUK code of 100. Any household containing a farmer under these definitions is regarded as a farm. FARMIPUM does not require the household to be in a non-urban area. The variable FARM restricts farm status to non-urban areas only, based on the (URBAN) variable. IPUMS Farm status, historical 1 No one in household with any connection to agriculture 2 At least one household member works as farmer 3 At least one household member works as agricultural laborer 4 At least one household member works as a cottar 9 Unknown FARM indicates the connection of a household to agriculture. To accommodate differences in census enumeration practices and occupational structure, FARM is not constructed in the same way as FARMIPUM. FARM classifies a household's connections to agriculture into four levels: 1: Nobody in the household indicates any connection with agriculture 2: At least one member of the household is a farmer, and the household's location meets the population [density] threshold. Farmers are identified by having an occupation in minor group 6-1 (See the OCCHISCO codes). If the only agricultural occupation(s) in the household were husbandmen or cottars (61115), the household did not receive this code. Husbandmen and cottars are found in Denmark, Norway, Sweden, and Iceland, and their residence was not always on a farm.For all full-count England and Wales datasets and for Scotland 1881, a parish population density threshold of 75 persons per acre was applied. For the two percent United Kingdom 1851 sample, a population density threshold of 64 persons per acre was applied. Households with farmers that were in locations with greater population [densities] were not given this code. Parish density information is not available in Scotland 1861, 1871, or 1891. FARM is defined based on occupation alone in these samples.3: At least one member of the household was an agricultural laborer; or in Norway there was a cottar in the household, who had no other trade. IPUMS Microfilm reel number REEL reports the microfilm reel number. For each sample, REEL can be used in conjunction with PAGENUM to locate the case on a microfilmed version of the original census form. REEL is a 6-digit numeric variable. IPUMS Household classification 00 Vacant household 01 One-person household 02 Married/cohab couple, no children 03 Married/cohab couple with children 04 Single-parent family 05 Polygamous family 06 Extended family, relatives only 07 Composite household, family and non-relatives 08 Non-family household 09 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable HHTYPE is a constructed variable that describes the composition of households. HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ. IPUMS Number of families in household Vacant household 1 1 family 2 2 families 3 3 families 4 4 families 5 5 families 6 6 families 7 7 families 8 8 families 9 9 or more families NFAMS is a constructed variable that indicates the number of families within each household. Family membership is defined by FAMUNIT. A "family" is any group of persons related by blood, adoption, or marriage. An unrelated individual within the household is considered a separate family. Thus, a household consisting of a widow and a domestic employee contains two families; a household consisting of a large, multi-generation extended family with no persons unrelated to the head counts as a single family. NFAMS is constructed from information in RELATE (relationship to head) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). See those variable descriptions for more detail. IPUMS Number of married couples in household No married couples in household 1 1 couple 2 2 couples 3 3 couples 4 4 couples 5 5 couples 6 6 couples 7 7 couples 8 8 couples 9 9 or more couples NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household. NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household). IPUMS Number of mothers in household No mothers in household 1 1 mother 2 2 mothers 3 3 mothers 4 4 mothers 5 5 mothers 6 6 mothers 7 7 mothers 8 8 mothers 9 9 or more mothers in household NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household. NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household). IPUMS Number of fathers in household No fathers in household 1 1 father 2 2 fathers 3 3 fathers 4 4 fathers 5 5 fathers 6 6 fathers 7 7 fathers 8 8 fathers 9 9 or more fathers in household NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household. NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household). IPUMS Head's location in household HEADLOC gives the person number (PERNUM) of the head of household in samples in which persons are organized into households. HEADLOC is a 3-digit numeric variable. IPUMS Size of primary family, historical PRMFAMSZ is the size of the primary, or first, family in the household. It is the FAMSIZE of the first family unit (FAMUNIT) recorded in the household. PRMFAMSZ and FAMSIZE are constructed from information in RELATE (relationship to head of household) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). Note: Users should be aware that in the United States census of 1880, where relationship to the head was not transcribed for non-relatives, FAMSIZE and PRMFAMSZ may be inaccurate in some cases. PRMFAMSZ is a 4-digit numeric variable. IPUMS Household number United States 1850 (1%): All records Household number. This is a 5-digit numeric variable with 0 implied decimal places IPUMS Census year United States 1850 (1%): All records 1850 1850 Census year. IPUMS Data set number United States 1850 (1%): All records 1 1850 1% sample Data set number. IPUMS Household serial number United States 1850 (1%): All records Household serial number. This is a 8-digit numeric variable with 0 implied decimal places IPUMS Number of person records following United States 1850 (1%): All households 01 1 person record 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 25 25 26 26 27 27 28 28 29 29 30 30 Number of person records following. IPUMS Subsample number United States 1850 (1%): All households 00 First 1% subsample 01 2nd 1% subsample 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98 99 99 Subsample number. IPUMS Household weight United States 1850 (1%): All households Household weight. This is a 3-digit numeric variable with 0 implied decimal places IPUMS Dwelling size United States 1850 (1%): All households Dwelling size. This is a 4-digit numeric variable with 0 implied decimal places IPUMS Number of households in dwelling United States 1850 (1%): All households Number of households in dwelling. This is a 2-digit numeric variable with 0 implied decimal places IPUMS Number of households sampled from dwelling United States 1850 (1%): All households 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 Number of households sampled from dwelling. IPUMS Household strata for variance estimation United States 1850 (1%): All households (Not available for Puerto Rico, Alaska, Hawaii, or the American Indian schedules) Household strata for variance estimation. This is a 12-digit numeric variable with 0 implied decimal places IPUMS Household cluster for variance estimation United States 1850 (1%): All households (Not available for Puerto Rico, Alaska, Hawaii, or the American Indian schedules) Household cluster for variance estimation. This is a 13-digit numeric variable with 0 implied decimal places IPUMS Census region and division <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 11 New England Division 12 Middle Atlantic Division 21 East North Central Division 22 West North Central Division 31 South Atlantic Division 32 East South Central Division 33 West South Central Division 41 Mountain Division 42 Pacific Division Census region and division. IPUMS State (ICPSR code) <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 01 Connecticut 02 Maine 03 Massachusetts 04 New Hampshire 05 Rhode Island 06 Vermont 11 Delaware 12 New Jersey 13 New York 14 Pennsylvania 21 Illinois 22 Indiana 23 Michigan 24 Ohio 25 Wisconsin 31 Iowa 33 Minnesota 34 Missouri 40 Virginia 41 Alabama 42 Arkansas 43 Florida 44 Georgia 45 Louisiana 46 Mississippi 47 North Carolina 48 South Carolina 49 Texas 51 Kentucky 52 Maryland 54 Tennessee 56 West Virginia 66 New Mexico 67 Utah 71 California 72 Oregon 98 District of Columbia State (ICPSR code). IPUMS State (FIPS code) <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 01 Alabama 05 Arkansas 06 California 09 Connecticut 10 Delaware 11 District of Columbia 12 Florida 13 Georgia 17 Illinois 18 Indiana 19 Iowa 21 Kentucky 22 Louisiana 23 Maine 24 Maryland 25 Massachusetts 26 Michigan 27 Minnesota 28 Mississippi 29 Missouri 33 New Hampshire 34 New Jersey 35 New Mexico 36 New York 37 North Carolina 39 Ohio 41 Oregon 42 Pennsylvania 44 Rhode Island 45 South Carolina 47 Tennessee 48 Texas 49 Utah 50 Vermont 51 Virginia 54 West Virginia 55 Wisconsin State (FIPS code). IPUMS County <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households County. This is a 4-digit numeric variable with 0 implied decimal places IPUMS Urban/rural status <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 1 Rural 2 Urban Urban/rural status. IPUMS Metropolitan status <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 1 Not in metro area 2 In metro area: Central city 3 In metro area: Outside central city Metropolitan status. IPUMS Metropolitan area <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 000 Not identifiable or not in an MSA 016 Albany-Schenectady-Troy, NY 072 Baltimore, MD 112 Boston, MA-NH 164 Cincinnati-Hamilton, OH/KY/IN 452 Louisville, KY/IN 556 New Orleans, LA 560 New York-Northeastern NJ 616 Philadelphia, PA/NJ 628 Pittsburgh, PA 704 St. Louis, MO-IL Metropolitan area. IPUMS Metropolitan area (detailed codes) <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 0000 Not identifiable or not in an MSA 0160 Albany-Schenectady-Troy, NY 0720 Baltimore, MD 1120 Boston, MA 1640 Cincinnati, OH/KY/IN 4520 Louisville, KY/IN 5560 New Orleans, LA 5600 New York-Northeastern NJ 6160 Philadelphia, PA/NJ 6280 Pittsburgh-Beaver Valley, PA 7040 St. Louis, MO-IL Metropolitan area (detailed codes). IPUMS City <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 0000 Not in identifiable city (or size group) 0050 Albany, NY 0110 Allegheny, PA 0530 Baltimore, MD 0550 Bangor, ME 0810 Boston, MA 0890 Buffalo, NY 0930 Cambridge, MA 1030 Charlestown, MA 1050 Charleston, SC 1190 Chicago, IL 1290 Cincinnati, OH 1330 Cleveland, OH 1450 Columbus, OH 1670 Dayton, OH 1750 Detroit, MI 2230 Fall River, MA 2710 Hartford, CT 3390 Lafayette, LA 3450 Lancaster, PA 3750 Louisville, KY 3770 Lowell, MA 3810 Lynn, MA 3910 Manchester, NH 4130 Milwaukee, WI 4170 Mobile, AL 4411 Nashville, TN 4450 New Bedford, MA 4530 New Haven, CT 4570 New Orleans, LA 4610 New York, NY 4611 Brooklyn, NY 4630 Newark, NJ 4810 Norfolk, VA 4890 Norwich, CT 5110 Oswego, NY 5210 Paterson, NJ 5310 Petersburg, VA 5330 Philadelphia, PA 5331 Kensington 5332 Mayamensing 5333 Northern Liberties 5334 Southwark 5335 Spring Garden 5370 Pittsburgh, PA 5510 Portland, ME 5650 Providence, RI 5790 Reading, PA 5870 Richmond, VA 5930 Rochester, NY 6010 Roxbury, MA 6090 Saint Louis, MO 6150 Salem, MA 6550 Smithfield, RI 6670 Springfield, MA 6850 Syracuse, NY 6910 Taunton, MA 7030 Troy, NY 7090 Utica, NY 7230 Washington, DC 7390 Wheeling, WV 7490 Wilmington, DE 7570 Worcester, MA City. IPUMS City population <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households in identifiable cities 0000 City not identified or unincorporated place 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 0053 53 0055 55 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0064 64 0067 67 0068 68 0069 69 0071 71 0072 72 0075 75 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0085 85 0087 87 0088 88 0089 89 0094 94 0095 95 0097 97 0101 101 0104 104 0109 109 0113 113 0114 114 0115 115 0117 117 0122 122 0123 123 0135 135 0139 139 0140 140 0141 141 0142 142 0143 143 0144 144 0152 152 0157 157 0164 164 0170 170 0172 172 0175 175 0178 178 0183 183 0200 200 0202 202 0203 203 0205 205 0208 208 0210 210 0212 212 0222 222 0269 269 0275 275 0288 288 0299 299 0333 333 0364 364 0387 387 0388 388 0400 400 0415 415 0422 422 0429 429 0431 431 0466 466 0467 467 0472 472 0507 507 0588 588 0778 778 0968 968 1154 1154 1163 1163 1213 1213 1368 1368 1690 1690 5155 5155 City population. IPUMS Size of place <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 01 Under 1,000 or unincorporated 02 1,000-2,499 03 2,500-3,999 04 4,000-4,999 05 5,000-9,999 06 10,000-24,999 07 25,000-49,999 08 50,000-74,999 09 75,000-99,999 10 100,000-199,999 50 500,000-599,999 Size of place. IPUMS New England population in minor civil division <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households in the six New England states New England population in minor civil division. This is a 4-digit numeric variable with 0 implied decimal places IPUMS Population of urban places <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households Population of urban places. This is a 4-digit numeric variable with 0 implied decimal places IPUMS State Economic Area <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households State Economic Area. This is a 3-digit numeric variable with 0 implied decimal places IPUMS Metropolitan district status <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 1 Not Metropolitan District 2 Central City 3 Urbanized Fringe 4 Metropolitan Fringe Metropolitan district status. IPUMS Metropolitan district <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 0000 Not in a metropolitan district 0160 Albany-Troy, N.Y. 0720 Baltimore, Md. 1120 Boston, Mass. 1640 Cincinnati, Ohio-Ky. 4520 Louisville, Ky. 5560 New Orleans, La. 5600 New York, N.Y.-Northeastern New Jersey 6160 Philadelphia, Pa.-N.J. 6280 Pittsburgh, Pa. 7040 St. Louis, Mo.-Ill. Metropolitan district. IPUMS Urbanized area <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households 0000 N/A (household does not reside in an urbanized area) 0160 Albany-Schenectady-Troy, NY 0720 Baltimore, MD 1120 Boston, MA 1640 Cincinnati, OH/KY/IN 4520 Louisville, KY/IN 5560 New Orleans, LA 5600 New York-Northeastern NJ 6160 Philadelphia, PA/NJ 6280 Pittsburgh-Beaver Valley, PA 7040 St. Louis, MO-IL Urbanized area. IPUMS Minor Civil Division code <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households (Not available in Alaska, Hawaii, Puerto Rico) Minor Civil Division code. This is a 5-digit numeric variable with 0 implied decimal places IPUMS Incorporated municipality code <svar a="all" v=" US50A014 US50A015 US50A016 US50A017 US50A018 US50A019 US50A020 US50A021 US50A022 US50A023 US50A024 US50A025 US50A026 US50A027 US50A028 US50A029 US50A030 US50A031 US50A032 US50A033 US50A050 US50A051">Free inhabitants in _________, in the County of ________, State of _________, enumerated by me, on the _____ day of ___________, 1850.<br /></svar> United States 1850 (1%): All households (Not available in Alaska, Hawaii, Puerto Rico) Incorporated municipality code. This is a 5-digit numeric variable with 0 implied decimal places IPUMS Country United States 1850 (1%): All households 840 United States Country. IPUMS Group quarters status United States 1850 (1%): All households 1 Households under 1970 definition 2 Additional households under 1990 definition 3 Institutions 4 Other group quarters 6 Fragment Group quarters status. IPUMS Group quarters type United States 1850 (1%): All group quarters NA (non-group quarters households) 2 Correctional institutions 3 Mental institutions 4 Institutions for the elderly, handicapped, and poor 6 Military 7 College dormitory 8 Rooming house 9 Other non-institutional GQ and unknown Group quarters type. IPUMS Group quarters type (detailed codes) United States 1850 (1%): All group quarters 000 NIU (not in universe) 010 Family group, someone related to head 020 Unrelated individuals, no one related to head 211 Prison 212 Penitentiary 221 Jail 240 Reformatory 250 Camp or chaingang 260 House of correction 300 Mental institutions 411 Aged, dependent home 413 Old soldiers home 432 Orphan's home, asylum 441 Children's home, asylum 451 Deaf, blind school 452 Deaf, blind, epilepsy 481 Poor house, almshouse 492 Homes for widows, single, fallen women 495 Home, other dependent 496 Institution combination or unknown 600 Military 601 U.S. army installation 602 Navy, marine intallation 603 Navy ships 700 College dormitory 701 Military service academies 801 Hotel 802 House, lodging apartments 910 Schools 912 Academy, institute 920 Hospitals 921 Hospital, charity 922 Infirmary 932 Convent 933 Monastery 935 Seminary 936 Religious commune 937 Other religious 943 Mining 944 Railroad 946 Ships, boats 948 Other worksites 960 Other group quarters Group quarters type (detailed codes). IPUMS Group quarters funding United States 1850 (1%): All group quarters 00 NIU (not in universe) 11 Federal support 13 State support 14 Local support 16 Government, not specified 21 Private, nonprofit 22 Private, commercial 23 Religious 25 Private, unknown 99 Fragment or Unknown Group quarters funding. IPUMS Farm status United States 1850 (1%): All households except group quarters or Alaska or Hawaii 1 Non-Farm 2 Farm Farm status. IPUMS Number of families in household United States 1850 (1%): All sample units 01 1 family or NIU (not in universe) 02 2 families 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 25 25 Number of families in household. IPUMS Number of married couples in household United States 1850 (1%): All sample units 0 couples or NIU (not in universe) 1 1 2 2 3 3 4 4 5 5 Number of married couples in household. IPUMS Number of mothers in household United States 1850 (1%): All sample units 0 mothers or NIU (not in universe) 1 1 2 2 3 3 4 4 Number of mothers in household. IPUMS Number of fathers in household United States 1850 (1%): All sample units 0 fathers or NIU (Not in universe) 1 1 2 2 3 3 4 4 Number of fathers in household. IPUMS Detailed household weight, based on low-level geography United States 1850 (1%): All households Detailed household weight, based on low-level geography. This is a 6-digit numeric variable with 0 implied decimal places IPUMS Sampling rule United States 1850 (1%): All households 1 Complete dwelling or household taken under ordinary sampling rules 2 Complete household sampled from within large dwelling 3 Related group sampled from within a large household or institution 4 Individual sampled from within a large household or institution 5 Fragment Sampling rule. IPUMS Verified data record United States 1850 (1%): All households 1 Unverified data record 2 Verified data record Verified data record. IPUMS Microfilm reel number United States 1850 (1%): All households Microfilm reel number. This is a 4-digit numeric variable with 0 implied decimal places IPUMS Microfilm page number United States 1850 (1%): All households Microfilm page number. This is a 3-digit numeric variable with 0 implied decimal places IPUMS Line number United States 1850 (1%): All households Line number. This is a 3-digit numeric variable with 0 implied decimal places IPUMS Microfilm sequence number United States 1850 (1%): All households 1 1 2 2 3 3 Microfilm sequence number. IPUMS Month of enumeration United States 1850 (1%): All households 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 99 Missing Month of enumeration. IPUMS Day of enumeration United States 1850 (1%): All households 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 99 Missing Day of enumeration. IPUMS Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. IPUMS Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. IPUMS Mother's location in household MOMLOC is a constructed variable that indicates whether or not the person's mother lived in the same household and, if so, gives the person number of the mother (see PERNUM). MOMLOC makes it easy for researchers to link the characteristics of children and their (probable) mothers. The method by which probable child-mother links are identified is described in PARRULE. The general design of MOMLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of MOMLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: MOMLOC identifies social relationships (such as stepmother and adopted mother) as well as biological relationships. The variable STEPMOM is designed to identify some of these social relationships. To restrict MOMLOC to biological mothers, such as for own children fertility estimation, MOMLOC should be reset to zero when STEPMOM is greater than zero. MOMLOC is a 3-digit numeric variable. Codes0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother IPUMS Father's location in household POPLOC is a constructed variable that indicates whether or not the person's father lived in the same household and, if so, gives the person number of the father (see PERNUM). POPLOC makes it easy for researchers to link the characteristics of children and their (probable) fathers. The method by which probable child-father links are identified is described in PARRULE. The general design of POPLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of POPLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: POPLOC identifies social relationships (such as stepfather and adopted father) as well as biological relationships. The variable STEPPOP is designed to identify some of these social relationships. To restrict POPLOC to biological mothers, such as for own children fertility estimation, POPLOC should be reset to zero when STEPPOP is greater than zero. POPLOC is a 3-digit numeric variable. Codes0 = No father of this person present in the household. 1 or higher = The person number of this person's father IPUMS Spouse's location in household SPLOC is a constructed variable that indicates whether or not the person's spouse lived in the same household and, if so, gives the person number (PERNUM) of the spouse. SPLOC makes it easy for researchers to link the characteristics of (probable) spouses. The method by which probable spouse-spouse links are identified is described in SPRULE. The general design of SPLOC and other constructed variables is modeled on the methods developed for IPUMS-USA "Family Interrelationships", but the details vary significantly. For more details on the construction of SPLOC, see the Comparability section of SPRULE and this paper on IPUMSI family linking methodology. SPLOC is a 3-digit numeric variable. Codes0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse IPUMS Family unit membership FAMUNIT is a constructed variable indicating to which family within the household a person belongs. All persons related to the household head receive a 1 (see RELATE). Each secondary family or secondary individual receives a higher code. For purposes of FAMUNIT, secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). FAMUNIT is a 4-digit numeric variable. CodesIf there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on. IPUMS Number of own family members in household 0001 1 family member present 0002 2 family members present 0003 3 family members present 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 or more persons FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them. FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membership). The primary family is defined as all persons related to the head in the RELATE variable. Secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). IPUMS Number of own children in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children in household NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Number of own children under age 5 in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more own children under age 5 in household 98 One or more children have unknown age NCHLT5 provides a count of the person's own children under age five living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Age of eldest own child in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. ELDCH is top-coded at age 50 or older. IPUMS Age of youngest own child in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. YNGCH is top-coded at age 50 or older. IPUMS Number of own siblings in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 or more NSIBS counts the number of the person's own siblings (including half- siblings) living in the household with her/him. NSIBS is generally based on information contained in RELATE (Relationship to household head). Persons with no siblings present are coded "0." IPUMS Number of generations in family unit 1 1 2 2 3 3 4 4 5 5 6 6 or more NUMGEN describes the number of generations in a given family unit. (See the documentation for FAMUNIT). For example, a family unit comprised of parents and children has a NUMGEN of 2. A family unit which has co-resident grandparents, parents and children has a NUMGEN of 3. A family unit with only grandparents and grandchildren has a NUMGEN of 2, as the intervening generation is not resident. IPUMS Relationship to household head [general version] 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Relationship to household head [detailed version] 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling's sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder, or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Relationship to household head, historical 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 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". IPUMS Imputed relationship to household head 00 Not applicable 01 Head/householder 02 Spouse 03 Child 04 Child-in-law 05 Parent 06 Parent-in-law 07 Sibling 08 Sibling-in-law 09 Grandchild 10 Other relatives 12 Other non-relatives 13 Institutional inmates IMPREL reports the person's imputed relationship to the head of household. The variable was created for the 1850-1870 samples because these censuses did not collect the explicit family interrelationship information available for all other years (see RELATE). IMPREL relationships are the result of logical inference and statistical imputation, not direct transcriptions from the census forms. IMPREL is constructed in identical fashion for 1910 as well, to facilitate comparisons. The most important IMPREL determinants are the order in which names appeared on the census form, surname similarity, age, sex, occupation, and birthplace. For about 75 percent of cases, the IPUMS assigns IMPREL according to logical rules based upon these determinants. For the remaining cases, the IPUMS uses a hot deck allocation procedure that examines a wider set of determinants to probabilistically assign IMPREL. See Family Interrelationships for more information. IPUMS Age 000 Less than 1 year 001 1 year 002 2 years 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100+ 999 Not reported/missing AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. IPUMS Sex 1 Male 2 Female 9 Unknown SEX reports the sex (gender) of the respondent. IPUMS Age in months 00 Less than 1 month old 01 1 month old 02 2 months old 03 3 months old 04 4 months old 05 5 months old 06 6 months old 07 7 months old 08 8 months old 09 9 months old 10 10 months old 11 11 months old 98 Unknown 99 NIU (1 year and older) AGEMONTH gives the age in months of persons younger than one year old (AGE =0) on census day. IPUMS Married within the past year 1 Blank (No) 2 Yes 9 Unknown MARRINYR identifies persons who had married within the 12 months preceding June 1. IPUMS Nativity status NIU (not in universe) 1 Native-born 2 Foreign-born 9 Unknown/missing NATIVITY indicates whether the person was native-born or foreign-born. IPUMS Country of birth 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11005 British Indian Ocean Territory 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11051 Ethiopia (including Eritrea) 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, other or n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15021 Upper Volta 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15081 Guinea-Bissau and Cape Verde 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15180 Canary Islands 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21200 St. Croix 21210 St. John 21220 St. Lucia 21230 St Thomas 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21991 Caribbean commonwealth, n.s. 21999 Caribbean, other or n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, other or n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, other or n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32042 India/Pakistan/Bangladesh/Sri Lanka 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32101 Pakistan/Bangladesh 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32999 South-Central Asia, other or n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33999 South-Eastern Asia, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34071 Israel/Palestine 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34111 West Bank 34112 Gaza Strip 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41991 Albania, Bulgaria, Czech, Hungary, Romania, Yugoslavia 41992 Central-Eastern Europe 41999 Eastern Europe, other or n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43121 Spain/Portugal 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43991 Gibraltar/Malta 43992 Portugal/Greece 43993 Italy, Holy See, San Marino 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44021 Belgium/Luxemburg 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44042 West Germany 44043 Germany/Austria 44044 Mecklenburg-Schwerin 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44991 Belgium, Denmark, Luxembourg, Netherlands 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (original 15) 49994 Other European Union (not original 15) 49999 Europe, other or n.s. 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53060 Federated States of Micronesia 53999 Micronesia, other or n.s. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 80000 AT SEA 90000 Other countries n.s. 99999 Unknown BPLCOUNTRY indicates the person's country of birth. IPUMS State of birth, United States 01 Alabama 02 Alaska 04 Arizona 05 Arkansas 06 California 08 Colorado 09 Connecticut 10 Delaware 11 District of Columbia 12 Florida 13 Georgia 15 Hawaii 16 Idaho 17 Illinois 18 Indiana 19 Iowa 20 Kansas 21 Kentucky 22 Louisiana 23 Maine 24 Maryland 25 Massachusetts 26 Michigan 27 Minnesota 28 Mississippi 29 Missouri 30 Montana 31 Nebraska 32 Nevada 33 New Hampshire 34 New Jersey 35 New Mexico 36 New York 37 North Carolina 38 North Dakota 39 Ohio 40 Oklahoma 41 Oregon 42 Pennsylvania 44 Rhode Island 45 South Carolina 46 South Dakota 47 Tennessee 48 Texas 49 Utah 50 Vermont 51 Virginia 53 Washington 54 West Virginia 55 Wisconsin 56 Wyoming 60 United States, n.s. 98 Foreign-born 99 Unknown BPLUS indicates the person's state of birth within the United States. IPUMS Race or color 10 White 20 Black 21 Black African 22 Black Caribbean 23 Afro-Ecuadorian 24 Other Black 30 Indigenous 31 American Indian 32 Latin American Indian 40 Asian 41 Chinese 42 Japanese 43 Korean 44 Vietnamese 45 Filipino 46 Indian 47 Pakistani 48 Bangladeshi 49 Other Asian 50 Mixed race 51 Brown (Brazil) 52 Mestizo (Indigenous and White) 53 Mulatto (Black and White) 54 Coloured (South Africa) 55 Two or more races 60 Other 61 Montubio (Ecuador) 99 Unknown Race identifies the racial group with which a person identified himself or herself, or to which an enumerator assigned them. Determinations of race are based largely on appearance or ancestral place of origin. IPUMS Race, United States 100 White 200 Black 210 Mulatto (1850-1910) 300 American Indian/Alaska Native, not specified 301 Alaskan Athabaskan 302 Aleut 303 Apache 304 Blackfoot 305 Cherokee 306 Cheyenne 307 Chickasaw 308 Chippewa 309 Choctaw 310 Colville 311 Comanche 312 Creek 313 Crow 314 Delaware 315 Eskimo 316 Hopi 317 Houma 318 Inupiat 319 Iroquois 320 Kiowa 321 Lumbee 322 Menominee 323 Navajo 324 Osage 325 Paiute 326 Pima 327 Potawatomi 328 Pueblo 329 Puget Sound Salish 330 Seminole 331 Shoshone 332 Sioux 333 Tlingit (Tlingit-Haida, 2000-2005) 334 Tohono O''Odham 335 Yakama 336 Yaqui 337 Yuman 338 Yup'ik 340 All other tribes 341 AIAN, tribe not specified 342 Other specified Indian tribe (2000-2005) 343 Two or more Indian tribes (2000-2005) 344 Other Alaskan tribe(s) (2000-2005) 345 Both Indian and Alaskan (2000-2005) 346 Tribal responses, n.e.c. 350 Latin American Indian 400 Chinese 410 Taiwanese 420 Chinese and Taiwanese 500 Japanese 600 Filipino 610 Asian Indian 620 Korean 630 Native Hawaiian 631 Asiatic Hawiian 632 Caucasian Hawaiian 640 Vietnamese 641 Bhutanese 642 Mongolian 643 Nepalese 660 Cambodian 661 Hmong 662 Laotian 663 Thai 664 Bangladeshi 665 Burmese 666 Indonesian 667 Malaysian 668 Okinawan 669 Pakistani 670 Sri Lankan 671 All other Asian, n.e.c. 672 Asian, not specified 673 Chinese and Japanese 674 Chinese and Filipino 675 Chinese and Vietnamese 676 Chinese and Asian write-in 677 Japanese and Filipino 678 Asian Indian and Asian write-in 679 Other Asian race combinations 680 Samoan 681 Tahitian 682 Tongan 684 One or more other Polynesian races (2000-2005) 685 Guamanian/Chamorro 686 Northern Mariana Islander 687 Palauan 688 Other Micronesian 689 One or more other Micronesian races (2000-2005) 690 Fijian 691 Other Melanesian 692 One or more Melanesian races (2000-2005) 698 Two or more PI races from multiple regions 699 Pacific Islander (PI), n.s. 700 Other race, n.e.c. 800 Two or more races RACEUS identifies the "race" of the respondent in the United States. Race is a social construct, not a scientific or anthropological concept. Many detailed categories consist of national origin groups. IPUMS Hispanic origin, U.S. and Puerto Rico 000 Not hispanic 100 Mexican 101 Mexican, n.e.c. 102 Mexican American 103 Mexicano/Mexicana 104 Chicano/Chicana 105 La Raza 106 Mexican American Indian 107 Mexico 200 Puerto Rican 300 Cuban 400 Other Spanish, 1980 410 Central/South American, 1970 411 Costa Rican 412 Guatemalan 413 Honduran 414 Nicaraguan 415 Panamanian 416 Salvadoran 417 Central American 418 Central American Indian 419 Canal Zone 420 Argentinean 421 Bolivian 422 Chilean 423 Colombian 424 Ecuadorian 425 Paraguayan 426 Peruvian 427 Uruguayan 428 Venezuelan 429 South American Indian 430 Criollo 431 South American 440 Other Spanish, 1970 450 Spaniard 451 Andalusian 452 Asturian 453 Castillian 454 Catalonian 455 Balearic Islander 456 Gallego 457 Valencian 458 Canarian 459 Spanish Basque 460 Dominican 465 Latin American 470 Hispanic 480 Spanish 490 Californio 491 Tejano 492 Nuevo Mexicano 493 Spanish American 494 Spanish American Indian 495 Meso American Indian 496 Mestizo 497 Other Spanish, Hispanic, Latino 498 Not specified (FOSDIC) 499 Not classified 999 Not reported HISPAN identifies and classifies persons of Hispanic origin in the United States and Puerto Rico. IPUMS Spanish surname, historical 1 No Spanish surname 2 Yes, Spanish surname SPANNAME identifies persons with Spanish surnames, based on comparisons of surnames with lists of Spanish surnames. IPUMS School attendance NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census. IPUMS Literacy NIU (not in universe) 1 No, illiterate 2 Yes, literate 9 Unknown/missing LIT indicates whether or not the respondent could read and write in any language. A person is typically considered literate if he or she can both read and write. All other persons are illiterate, including those who can either read or write but cannot do both. IPUMS Labor force participation 1 No, not in the labor force 2 Yes, in the labor force 8 Unknown 9 NIU (not in universe) LABFORCE is a dichotomous variable identifying whether a person participated in the labor force. Labor force participation generally means working or seeking work within a specified reference period. For most samples LABFORCE is a recode of EMPSTAT (employment status). A consistent lower age universe of 15 or older has been applied to increase comparability across samples. Full detail is retained in EMPSTAT, which should be used for any study of child labor. IPUMS Occupation, ISCO general 01 Legislators, senior officials and managers 02 Professionals 03 Technicians and associate professionals 04 Clerks 05 Service workers and shop and market sales 06 Skilled agricultural and fishery workers 07 Crafts and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 10 Armed forces 11 Other occupations, unspecified or n.e.c. 97 Response suppressed 98 Unknown 99 NIU (not in universe) OCCISCO records the person's primary occupation, coded according to the major categories in the International Standard Classification of Occupations (ISCO) scheme for 1988. For someone with more than one job, the primary occupation is typically the one in which the person had spent the most time or earned the most money. IPUMS Occupation 1950 basis, U.S. 000 Accountants and auditors 001 Actors and actresses 002 Airplane pilots and navigators 003 Architects 004 Artists and art teachers 005 Athletes 006 Authors 007 Chemists 008 Chiropractors 009 Clergymen 010 College presidents and deans 012 Agricultural sciences 013 Biological sciences 014 Chemistry 015 Economics 016 Engineering 017 Geology and geophysics 018 Mathematics 019 Medical sciences 023 Physics 024 Psychology 025 Statistics 026 Natural science (n.e.c.) 027 Social sciences (n.e.c.) 028 Nonscientific subjects 029 Subject not specified 031 Dancers and dancing teachers 032 Dentists 033 Designers 034 Dieticians and nutritionists 035 Draftsmen 036 Editors and reporters 041 Engineers, aeronautical 042 Engineers, chemical 043 Engineers, civil 044 Engineers, electrical 045 Engineers, industrial 046 Engineers, mechanical 047 Engineers, metallurgical, metallurgists 048 Engineers, mining 049 Engineers (n.e.c.) 051 Entertainers (n.e.c.) 052 Farm and home management advisors 053 Foresters and conservationists 054 Funeral directors and embalmers 055 Lawyers and judges 056 Librarians 057 Musicians and music teachers 058 Nurses, professional 059 Nurses, student professional 061 Agricultural scientists 062 Biological scientists 063 Geologists and geophysicists 067 Mathematicians 068 Physicists 069 Miscellaneous natural scientists 070 Optometrists 071 Osteopaths 072 Personnel and labor relations workers 073 Pharmacists 074 Photographers 075 Physicians and surgeons 076 Radio operators 077 Recreation and group workers 078 Religious workers 079 Social and welfare workers, except group 081 Economists 082 Psychologists 083 Statisticians and actuaries 084 Miscellaneous social scientists 091 Sports instructors and officials 092 Surveyors 093 Teachers (n.e.c.) 094 Technicians, medical and dental 095 Technicians, testing 096 Technicians (n.e.c.) 097 Therapists and healers (n.e.c.) 098 Veterinarians 099 Professional, technical and kindred workers (n.e.c.) 100 Farmers (owners and tenants) 123 Farm managers 200 Buyers and department heads, store 201 Buyers and shippers, farm products 203 Conductors, railroad 204 Credit men 205 Floormen and floor managers, store 210 Inspectors, public administration 230 Managers and superintendents, building 240 Officers, pilots, pursers and engineers, ship 250 Officials and administrators (n.e.c.), public administration 260 Officials, lodge, society, union, etc. 270 Postmasters 280 Purchasing agents and buyers (n.e.c.) 290 Managers, officials, and proprietors (n.e.c.) 300 Agents (n.e.c.) 301 Attendants and assistants, library 302 Attendants, physician's and dentist's office 304 Baggagemen, transportation 305 Bank tellers 310 Bookkeepers 320 Cashiers 321 Collectors, bill and account 322 Dispatchers and starters, vehicle 325 Express messengers and railway mail clerks 335 Mail carriers 340 Messengers and office boys 341 Office machine operators 342 Shipping and receiving clerks 350 Stenographers, typists, and secretaries 360 Telegraph messengers 365 Telegraph operators 370 Telephone operators 380 Ticket, station, and express agents 390 Clerical and kindred workers (n.e.c.) 400 Advertising agents and salesmen 410 Auctioneers 420 Demonstrators 430 Hucksters and peddlers 450 Insurance agents and brokers 460 Newsboys 470 Real estate agents and brokers 480 Stock and bond salesmen 490 Salesmen and sales clerks (n.e.c.) 500 Bakers 501 Blacksmiths 502 Bookbinders 503 Boilermakers 504 Brickmasons, stonemasons, and tile setters 505 Cabinetmakers 510 Carpenters 511 Cement and concrete finishers 512 Compositors and typesetters 513 Cranemen, derrickmen, and hoistmen 514 Decorators and window dressers 515 Electricians 520 Electrotypers and stereotypers 521 Engravers, except photoengravers 522 Excavating, grading, and road machinery operators 523 Foremen (n.e.c.) 524 Forgemen and hammermen 525 Furriers 530 Glaziers 531 Heat treaters, annealers, temperers 532 Inspectors, scalers, and graders, log and lumber 533 Inspectors (n.e.c.) 534 Jewelers, watchmakers, goldsmiths, and silversmiths 535 Job setters, metal 540 Linemen and servicemen, telegraph, telephone, and power 541 Locomotive engineers 542 Locomotive firemen 543 Loom fixers 544 Machinists 545 Mechanics and repairmen, airplane 550 Mechanics and repairmen, automobile 551 Mechanics and repairmen, office machine 552 Mechanics and repairmen, radio and television 553 Mechanics and repairmen, railroad and car shop 554 Mechanics and repairmen (n.e.c.) 555 Millers, grain, flour, feed, etc. 560 Millwrights 561 Molders, metal 562 Motion picture projectionists 563 Opticians and lens grinders and polishers 564 Painters, construction and maintenance 565 Paperhangers 570 Pattern and model makers, except paper 571 Photoengravers and lithographers 572 Piano and organ tuners and repairmen 573 Plasterers 574 Plumbers and pipe fitters 575 Pressmen and plate printers, printing 580 Rollers and roll hands, metal 581 Roofers and slaters 582 Shoemakers and repairers, except factory 583 Stationary engineers 584 Stone cutters and stone carvers 585 Structural metal workers 590 Tailors and tailoresses 591 Tinsmiths, coppersmiths, and sheet metal workers 592 Tool makers, and die makers and setters 593 Upholsterers 594 " 595 Members of the armed services 600 Apprentice auto mechanics 601 Apprentice bricklayers and masons 602 Apprentice carpenters 603 Apprentice electricians 604 Apprentice machinists and toolmakers 605 Apprentice mechanics, except auto 610 Apprentice plumbers and pipe fitters 611 Apprentices, building trades (n.e.c.) 612 Apprentices, metalworking trades (n.e.c.) 613 Apprentices, printing trades 614 Apprentices, other specified trades 615 Apprentices, trade not specified 620 Asbestos and insulation workers 621 Attendants, auto service and parking 622 Blasters and powdermen 623 Boatmen, canalmen, and lock keepers 624 Brakemen, railroad 625 Bus drivers 630 Chainmen, rodmen, and axmen, surveying 631 Conductors, bus and street railway 632 Deliverymen and routemen 633 Dressmakers and seamstresses, except factory 634 Dyers 635 Filers, grinders, and polishers, metal 640 Fruit, nut, and vegetable graders, and packers, except factory 641 Furnacemen, smeltermen and pourers 642 Heaters, metal 643 Laundry and dry cleaning operatives 644 Meat cutters, except slaughter and packing house 645 Milliners 650 Mine operatives and laborers 660 Motormen, mine, factory, logging camp, etc. 661 Motormen, street, subway, and elevated railway 662 Oilers and greaser, except auto 670 Painters, except construction or maintenance 671 Photographic process workers 672 Power station operators 673 Sailors and deck hands 674 Sawyers 675 Spinners, textile 680 Stationary firemen 681 Switchmen, railroad 682 Taxicab drivers and chauffers 683 Truck and tractor drivers 684 Weavers, textile 685 Welders and flame cutters 690 Operative and kindred workers (n.e.c.) 700 Housekeepers, private household 710 Laundressses, private household 720 Private household workers (n.e.c.) 730 Attendants, hospital and other institution 731 Attendants, professional and personal service (n.e.c.) 732 Attendants, recreation and amusement 740 Barbers, beauticians, and manicurists 750 Bartenders 751 Bootblacks 752 Boarding and lodging house keepers 753 Charwomen and cleaners 754 Cooks, except private household 760 Counter and fountain workers 761 Elevator operators 762 Firemen, fire protection 763 Guards, watchmen, and doorkeepers 764 Housekeepers and stewards, except private household 770 Janitors and sextons 771 Marshals and constables 772 Midwives 773 Policemen and detectives 780 Porters 781 Practical nurses 782 Sheriffs and bailiffs 783 Ushers, recreation and amusement 784 Waiters and waitresses 785 Watchmen (crossing) and bridge tenders 790 Service workers, except private household (n.e.c.) 810 Farm foremen 820 Farm laborers, wage workers 830 Farm laborers, unpaid family workers 840 Farm service laborers, self-employed 910 Fishermen and oystermen 920 Garage laborers and car washers and greasers 930 Gardeners, except farm, and groundskeepers 940 Longshoremen and stevedores 950 Lumbermen, raftsmen, and woodchoppers 960 Teamsters 970 Laborers (n.e.c.) 975 Employed, unclassifiable 980 Keeps house/house work/housewife 981 Imputed keeping house (1860-1880) 982 At home/ helps in home 983 At school 984 Retired 985 Unemployed/ without occupation 986 Invalid/sick/disabled 987 Inmate/prisoner 991 Capitalist/gentleman 995 Other non-occupational response 997 Occupation missing/unknown 999 NIU (not in universe) OCC95US provides a consistent classification of occupation across U.S. samples. Occupation describes the type of (usually market-oriented) work the person performs. Note regarding universe: "New workers" are persons seeking employment for the first time who have not yet secured their first job. IPUMS Industry 1950 basis, U.S. 000 NIU (not in universe) 105 Agriculture 106 Own farm 116 Forestry 126 Fisheries 136 Hunting 206 Metal mining 216 Coal mining 226 Crude petroleum and natural gas extraction 236 Nonmetallic mining and quarrying, except fuel 239 Mining, not specified 246 Construction 306 Logging 307 Sawmills, planing mills, and mill work 308 Miscellaneous wood products 309 Furniture and fixtures 316 Glass and glass products 317 Cement, concrete, gypsum and plaster products 318 Structural clay products 319 Pottery and related products 326 Miscellaneous nonmetallic mineral and stone products 336 Blast furnaces, steel works, and rolling mills 337 Other primary iron and steel industries 338 Primary nonferrous industries 346 Fabricated steel products 347 Fabricated nonferrous metal products 348 Not specified metal industries 356 Agricultural machinery and tractors 357 Office and store machines and devices 358 Miscellaneous machinery 367 Electrical machinery, equipment, and supplies 376 Motor vehicles and motor vehicle equipment 377 Aircraft and parts 378 Ship and boat building and repairing 379 Railroad and miscellaneous transportation equipment 386 Professional equipment and supplies 387 Photographic equipment and supplies 388 Watches, clocks, and clockwork-operated devices 399 Miscellaneous manufacturing industries 406 Meat products 407 Dairy products 408 Canning and preserving fruits, vegetables, and seafoods 409 Grain-mill products 416 Bakery products 417 Confectionery and related products 418 Beverage industries 419 Miscellaneous food preparations and kindred products 426 Not specified food industries 429 Tobacco manufactures 436 Knitting mills 437 Dyeing and finishing textiles, except knit goods 438 Carpets, rugs, and other floor coverings 439 Yarn, thread, and fabric mills 446 Miscellaneous textile mill products 448 Apparel and accessories 449 Miscellaneous fabricated textile products 456 Pulp, paper, and paperboard mills 457 Paperboard containers and boxes 458 Miscellaneous paper and pulp products 459 Printing, publishing, and allied industries 466 Synthetic fibers 467 Drugs and medicines 468 Paints, varnishes, and related products 469 Miscellaneous chemicals and allied products 476 Petroleum refining 477 Miscellaneous petroleum and coal products 478 Rubber products 487 Leather: tanned, curried, and finished 488 Footwear, except rubber 489 Leather products, except footwear 499 Not specified manufacturing industries 506 Railroads and railway express service 516 Street railways and bus lines 526 Trucking service 527 Warehousing and storage 536 Taxicab service 546 Water transportation 556 Air transportation 567 Petroleum and gasoline pipe lines 568 Services incidental to transportation 578 Telephone 579 Telegraph 586 Electric light and power 587 Gas and steam supply systems 588 Electric-gas utilities 596 Water supply 597 Sanitary services 598 Other and not specified utilities 606 Motor vehicles and equipment 607 Drugs, chemicals, and allied products 608 Dry goods apparel 609 Food and related products 616 Electrical goods, hardware, and plumbing equipment 617 Machinery, equipment, and supplies 618 Petroleum products 619 Farm products--raw materials 626 Miscellaneous wholesale trade 627 Not specified wholesale trade 636 Food stores, except dairy products 637 Dairy products stores and milk retailing 646 General merchandise stores 647 Five and ten cent stores 656 Apparel and accessories stores, except shoe 657 Shoe stores 658 Furniture and house furnishing stores 659 Household appliance and radio stores 667 Motor vehicles and accessories retailing 668 Gasoline service stations 669 Drug stores 679 Eating and drinking places 686 Hardware and farm implement stores 687 Lumber and building material retailing 688 Liquor stores 689 Retail florists 696 Jewelry stores 697 Fuel and ice retailing 698 Miscellaneous retail stores 699 Not specified retail trade 716 Banking and credit agencies 726 Security and commodity brokerage and investment companies 736 Insurance 746 Real estate 756 Real estate-insurance-law offices 806 Advertising 807 Accounting, auditing, and bookkeeping services 808 Miscellaneous business services 816 Auto repair services and garages 817 Miscellaneous repair services 826 Private households 836 Hotels and lodging places 846 Laundering, cleaning, and dyeing services 847 Dressmaking shops 848 Shoe repair shops 849 Miscellaneous personal services 856 Radio broadcasting and television 857 Theaters and motion pictures 858 Bowling alleys, and billiard and pool parlors 859 Miscellaneous entertainment and recreation services 868 Medical and other health services, except hospitals 869 Hospitals 879 Legal services 888 Educational services 896 Welfare and religious services 897 Nonprofit membership organizations 898 Engineering and architectural services 899 Miscellaneous professional and related services 900 Library, museum, and other related institutions 906 Postal service 916 Federal public administration 926 State public administration 936 Local public administration 946 Public Administration, level not specified 976 Common or General laborer 982 Housework at home 983 School response (students, etc.) 984 Retired 986 Sick or disabled 987 Institution response 991 Lady/Man of leisure 995 Non-industrial response 997 Nonclassifiable 998 Industry not reported IND95US provides a consistent classification of industry across U.S. samples and the 1891 and 1911 censuses of Canada. Industry describes the type of goods or services produced by the place in which a person worked. Note regarding universe: "New workers" are persons seeking employment for the first time who had not yet secured their first job. IPUMS Duncan Socioeconomic Index, United States SEIUS is a constructed variable that assigns a Duncan Socioeconomic Index (SEI) score to each occupation. The SEI, based on the 1950 occupational classification system, is a measure of occupational status based upon the income level and educational attainment associated with each occupation in 1950. The score was derived by using median income and education levels for men in 1950 to predict prestige assessments from a 1947 survey (of a select group of occupations). The resulting statistical model was used to generate scores for the entire range of 1950 occupations. See O. D. Duncan, "A Socioeconomic Index for All Occupations," in A. Reiss et al., Occupations and Social Status (Free Press, 1961). CodesSEIUS is a 2-digit numeric variable. IPUMS Occupational income score, United States OCSCORUS is a constructed variable that assigns occupational income scores to each occupation on the basis of OCC50US. The construction of this variable is described in the IPUMS USA documentation, Chapter 4, "Occupation Codes and Income Scores", which users should read before using this variable. In essence, OCSCORUS assigns each occupation in all years a value representing the median total income (in hundreds of 1950 dollars) of all persons with that particular occupation in 1950. That is, it provides a continuous measure of occupations according to the economic rewards enjoyed by people working at them in 1950. OCSCORUS is a 2-digit numeric variable. Codes00=N/A Maximum value: 80 IPUMS Occupation as transcribed OCCSTRNG is an alphabetic variable that preserves the transcription of an individual's response to questions about their occupation. Although the various occupation and industry codes preserve significant detail on occupation and industry, much variation exists in the occupational strings. OCCSTRNG will primarily be of interest to researchers who are linking census data to other sources, or are investigating occupations at a much more detailed level than offered by the various coding schemes. The collection of occupation information was extensively covered in the instructions to enumerators. Researchers who are interested in OCCSTRNG should also read the enumerator instructions for assistance in interpreting occupational responses. Because of the size of this variable (30 columns), users should not select this variable unless it is essential for their research. Users should be aware that some responses are truncated at this length. OCCSTRNG is a 30-character string variable. IPUMS Disability status NIU (not in universe) 1 Yes, disabled 2 No, not disabled 9 Unknown DISABLED indicates whether the person reported a disability of any kind. IPUMS Blind or vision-impaired NIU (not in universe) 1 Yes 2 No 9 Unknown DISBLND indicates whether the person was blind or had limited vision. IPUMS Deaf or hearing-impaired NIU (not in universe) 1 Yes 2 No 9 Unknown DISDEAF indicates whether the person was deaf or had limited hearing. IPUMS Mute or speech impaired NIU (not in universe) 1 Yes 2 No 9 Unknown DISMUTE indicates if the person could not speak or had a significant speech impediment. IPUMS Mental disability NIU (not in universe) 1 Yes 2 No 9 Unknown DISMNTL indicates whether the person suffered a mental disability in the form of diminished capacity. IPUMS Psychological disability NIU (not in universe) 1 Yes 2 No 9 Unknown DISPSYC indicates whether the person was disabled due to mental illness. IPUMS Real estate value REALPROP reports the contemporary dollar value of any real estate owned by the respondent. The full value was to be reported, even if the property was encumbered by a lien, mortgage, or other debt. This is a 6-digit numeric variable with 0 implied decimal places IPUMS Surname similarity 001 1st surname in household 002 2 003 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 SURSIM assigns the same code to all persons within each household who had the same surname. Persons coded 1, including the household head, had the same surname as the household head. Other surnames are assigned codes in the order in which they appear within the household on the census form. Persons within a household who shared a surname will have the same code for this variable. IPUMS Last name NAMELAST is an alphabetic variable giving a person's full last name. It will primarily be of use to researchers linking the IPUMS historical census data to other sources of demographic data, or researchers whose research topic involves naming patterns. Because of the length of this variable (32 columns), and the size of the dataset, other researchers should not select this variable. NAMELAST is used to produce the variable SURSIM which assigns the same code to all persons within each household who had a shared surname. This is a 32-digit numeric variable with 0 implied decimal places IPUMS First name NAMEFRST is an alphabetic variable giving a person's full first name. It will primarily be of use to researchers linking the historical census data to other sources of demographic data, or researchers whose research topic involves naming patterns. Because of the length of this variable (32 columns), and the size of the dataset other researchers should not select this variable. This is a 32-digit numeric variable with 0 implied decimal places IPUMS Person number (within household) United States 1850 (1%): All records Person number (within household). This is a 2-digit numeric variable with 0 implied decimal places IPUMS Person number in sample unit United States 1850 (1%): All persons Person number in sample unit. This is a 4-digit numeric variable with 0 implied decimal places IPUMS Person weight United States 1850 (1%): All persons 101 101 102 102 Person weight. IPUMS Sample-line weight United States 1850 (1%): All persons Sample-line weight. This is a 3-digit numeric variable with 0 implied decimal places IPUMS Mother's location in the household United States 1850 (1%): All persons Mother's location in the household. This is a 2-digit numeric variable with 0 implied decimal places IPUMS Probable step/adopted mother United States 1850 (1%): All persons No stepmother present 1 Improbable age difference 2 Spouse of father Probable step/adopted mother. IPUMS Rule for linking mother United States 1850 (1%): All persons No mother link 1 Unambiguous mother link 2 Daughter/grandchild link 3 Preceding female (no intervening person) 4 Preceding female (surname similarity) 7 Spouse of father becomes stepmother Rule for linking mother. IPUMS Imputed location of mother United States 1850 (1%): All persons Imputed location of mother. This is a 2-digit numeric variable with 0 implied decimal places IPUMS Father's location in the household United States 1850 (1%): All persons Father's location in the household. This is a 2-digit numeric variable with 0 implied decimal places IPUMS Probable step/adopted father United States 1850 (1%): All persons No stepfather present 1 Improbable age difference 2 Spouse of mother 7 Surname difference -- male child or never-married female Probable step/adopted father. IPUMS Rule for linking father United States 1850 (1%): All persons No father link 1 Unambiguous father link 2 Son/granchild link 3 Preceding male (no intervening person) 4 Preceding male (surname similarity) 7 Husband of mother becomes stepfather Rule for linking father. IPUMS Imputed location of father United States 1850 (1%): All persons Imputed location of father. This is a 2-digit numeric variable with 0 implied decimal places IPUMS Spouse's location in household United States 1850 (1%): All persons Spouse's location in household. This is a 2-digit numeric variable with 0 implied decimal places IPUMS Rule for linking spouse United States 1850 (1%): All persons No spouse link 1 Wife follows husband 2 Wife precedes husband 3 Non-adjacent links -- consistent relationship to head/age differences 4 Adjacent links (wife follows husband -- no age, other relative conflicts) 5 Adjacent links (wife precedes husband -- no age, other relative conflicts) Rule for linking spouse. IPUMS Imputed location of spouse United States 1850 (1%): All persons Imputed location of spouse. This is a 2-digit numeric variable with 0 implied decimal places IPUMS Number of own family members in household United States 1850 (1%): All persons 01 1 family member present 02 2 family member present 03 3 family member present 04 4 family member present 05 5 family member present 06 6 family member present 07 7 family member present 08 8 family member present 09 9 family member present 10 10 family member present 11 11 family member present 12 12 family member present 13 13 family member present 14 14 family member present 15 15 family member present 16 16 family member present 17 17 family member present 19 19 family member present Number of own family members in household. IPUMS Number of own children in the household United States 1850 (1%): All persons 0 children present 1 1 child present 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 Number of own children in the household. IPUMS Number of own children under age 5 in household United States 1850 (1%): All persons No children under age 5 1 1 child under age 5 2 2 3 3 4 4 5 5 7 7 Number of own children under age 5 in household. IPUMS Family unit membership United States 1850 (1%): All persons 01 1st family in household or group quarters 02 2nd family in household or group quarters 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 Family unit membership. IPUMS Age of eldest own child in household United States 1850 (1%): Persons with own children in the household 00 Less than 1 year old 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 67 67 70 70 73 73 98 98 99 N/A Age of eldest own child in household. IPUMS Age of youngest own child in household United States 1850 (1%): Persons with own children in the household 00 Less than 1 year old 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 67 67 70 70 73 73 98 98 99 N/A Age of youngest own child in household. IPUMS Number of own siblings in household United States 1850 (1%): All persons 0 siblings 1 1 siblings 2 2 siblings 3 3 siblings 4 4 siblings 5 5 siblings 6 6 siblings 7 7 siblings 8 8 siblings 9 9 or more siblings Number of own siblings in household. IPUMS Relationship to household head United States 1850 (1%): All persons 01 Head/Householder 02 Spouse 03 Child 04 Child-in-law 05 Parent 06 Parent-in-Law 07 Sibling 08 Sibling-in-Law 09 Grandchild 10 Other relatives 12 Other non-relatives 13 Institutional inmates Relationship to household head. IPUMS Relationship to household head (detailed codes) United States 1850 (1%): All persons 0101 Head/Householder 0201 Spouse 0301 Child 0401 Child-in-law 0501 Parent 0601 Parent-in-Law 0701 Sibling 0801 Sibling-in-Law 0901 Grandchild 1001 Other relatives, n.s. 1201 Roomers/boarders/lodgers 1301 Institutional inmates Relationship to household head (detailed codes). IPUMS Imputed relationship to household head United States 1850 (1%): All persons 01 Head/householder 02 Spouse 03 Child 04 Child-in-law 05 Parent 06 Parent-in-law 07 Sibling 08 Sibling-in-law 09 Grandchild 10 Other relatives 12 Other non-relatives 13 Institutional inmates Imputed relationship to household head. IPUMS Age <svar a="all" v="US50A424 US50A426">4. ____ Age.<br /></svar> United States 1850 (1%): All persons 000 Less than 1 year old 001 1 002 2 003 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 99 100 100 101 101 103 103 104 104 106 106 110 110 998 Unknown/illegible 999 NIU (not in universe) or blank Age. IPUMS Sex <svar a="all" v="US50A425">5. ____ Sex.<br /></svar> United States 1850 (1%): All persons 1 Male 2 Female 9 Unknown Sex. IPUMS Age in months <svar a="all" v="US50A424 US50A426">4. ____ Age.<br /></svar> United States 1850 (1%): Persons below 1 year old 00 0 months old 01 1 month old 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 99 NIU (not in universe) or blank Age in months. IPUMS Married within the past year <svar a="all" v="US50A427">10. ____ Married within the year.<br /></svar> United States 1850 (1%): All persons 1 Blank (No) 2 Yes Married within the past year. IPUMS Race <svar a="all" v="US50A428 US50A429 US50A436 US50A437">6. ____ Color -- White, black, mulatto, or American Indian.<br /></svar> United States 1850 (1%): All persons 1 White 2 Black/Negro 3 American Indian or Alaska Native Race. IPUMS Race (detailed) <svar a="all" v="US50A428 US50A429 US50A436 US50A437">6. ____ Color -- White, black, mulatto, or American Indian.<br /></svar> United States 1850 (1%): All persons 100 White 120 Blank (white) 200 Black/Negro 210 Mulatto 300 American Indian/Alaska Native (AIAN) Race (detailed). IPUMS Birthplace <svar a=" US50A430 US50A431" v=" US50A430 US50A431 US50A432 US50A433 US50A435">9. ____ Place of birth, naming the state, territory, or country.<br /></svar> United States 1850 (1%): All persons 001 Alabama 002 Alaska 005 Arkansas 006 California 008 Colorado 009 Connecticut 010 Delaware 011 District of Columbia 012 Florida 013 Georgia 015 Hawaii 017 Illinois 018 Indiana 019 Iowa 020 Kansas 021 Kentucky 022 Louisiana 023 Maine 024 Maryland 025 Massachusetts 026 Michigan 027 Minnesota 028 Mississippi 029 Missouri 033 New Hampshire 034 New Jersey 035 New Mexico 036 New York 037 North Carolina 039 Ohio 040 Oklahoma 041 Oregon 042 Pennsylvania 044 Rhode Island 045 South Carolina 047 Tennessee 048 Texas 049 Utah 050 Vermont 051 Virginia 054 West Virginia 055 Wisconsin 099 United States, ns 115 U.S. Virgin Islands 150 Canada 160 Atlantic Islands 200 Mexico 210 Central America 250 Cuba 260 West Indies 300 South America 400 Denmark 404 Norway 405 Sweden 410 England 411 Scotland 412 Wales 413 United Kingdom, ns 414 Ireland 420 Belgium 421 France 425 Netherlands 426 Switerland 433 Greece 434 Italy 435 Malta 436 Portugal 438 Spain 450 Austria 452 Czechoslovakia 453 Germany 454 Hungary 455 Poland 465 Other USSR/Russia 499 Europe, ns 500 China 512 Indonesia 521 India 534 Israel/Palestine 600 Africa 900 Abroad (unknown) or at sea 999 Missing/blank Birthplace. IPUMS Birthplace (detailed codes) <svar a=" US50A430 US50A431" v=" US50A430 US50A431 US50A432 US50A433 US50A435">9. ____ Place of birth, naming the state, territory, or country.<br /></svar> United States 1850 (1%): All persons 00100 Alabama 00200 Alaska 00500 Arkansas 00600 California 00800 Colorado 00900 Connecticut 01000 Delaware 01100 District of Columbia 01200 Florida 01300 Georgia 01500 Hawaii 01700 Illinois 01800 Indiana 01900 Iowa 02000 Kansas 02100 Kentucky 02200 Louisiana 02300 Maine 02400 Maryland 02500 Massachusetts 02600 Michigan 02700 Minnesota 02800 Mississippi 02900 Missouri 03300 New Hampshire 03400 New Jersey 03500 New Mexico 03510 New Mexico Territory 03600 New York 03700 North Carolina 03900 Ohio 04010 Indian Territory 04100 Oregon 04200 Pennsylvania 04400 Rhode Island 04500 South Carolina 04700 Tennessee 04800 Texas 04910 Utah Territory 05000 Vermont 05100 Virginia 05400 West Virginia 05500 Wisconsin 09900 United States, n.s. 11520 St. John 15000 Canada 15010 English Canada 15030 Ontario/Upper Canada 15031 Upper Canada 15032 Canada West 15040 New Brunswick 15050 Nova Scotia 15060 Prince Edward Island 15070 Newfoundland 15081 Quebec 15083 Canada East 16010 Bermuda 20000 Mexico 21070 Panama 25000 Cuba 26000 West Indies 26010 Dominican Republic 26030 Jamaica 26043 Bahamas 26044 Barbados 30000 South America 30015 Brazil 30020 Chile 30040 Guyana/British Guiana 30090 South America, n.s. 40000 Denmark 40400 Norway 40500 Sweden 41000 England 41012 Jersey 41020 Isle of Man 41100 Scotland 41200 Wales 41300 United Kingdom, n.s./ n.e.c. 41400 Ireland 42000 Belgium 42100 France 42500 Netherlands 42600 Switzerland 43300 Greece 43400 Italy 43500 Malta 43600 Portugal 43800 Spain 45000 Austria 45210 Bohemia 45300 Germany 45311 Baden 45312 Bavaria 45315 Hamburg 45316 Hanover 45317 Hessen 45318 Hesse-Nassau 45319 Lippe 45328 Wurttemberg 45345 Mecklinburg 45346 Saxony 45347 Thuringian States 45360 Prussia, n.e.c. 45400 Hungary 45500 Poland 46500 Other USSR/"Russia" 49900 Europe, n.s. 50000 China 51210 East Indies 52100 India 53400 Israel/Palestine 60099 Africa, n.s./n.e.c. 90010 Abroad, n.s. 90020 At sea 99900 Missing/blank Birthplace (detailed codes). IPUMS Hispanic origin <svar a="all" v=" US50A432 US50A433 US50A434 US50A435 US50A456 US50A457">3. ____ The name of every person whose usual place of abode on the 1st day of June, 1850 was in this family.<br /></svar></p> <p><svar a=" US50A430 US50A431" v=" US50A430 US50A431 US50A432 US50A433 US50A435">9. ____ Place of birth, naming the state, territory, or country.<br /></svar> United States 1850 (1%): All persons Not Hispanic 1 Mexican 3 Cuban 4 Other Hispanic origin. IPUMS Hispanic origin (detailed codes) <svar a="all" v=" US50A432 US50A433 US50A434 US50A435 US50A456 US50A457">3. ____ The name of every person whose usual place of abode on the 1st day of June, 1850 was in this family.<br /></svar></p> <p><svar a=" US50A430 US50A431" v=" US50A430 US50A431 US50A432 US50A433 US50A435">9. ____ Place of birth, naming the state, territory, or country.<br /></svar> United States 1850 (1%): All persons 000 Not Hispanic 100 Mexican 300 Cuban 415 Panamanian 422 Chilean 429 South American Indian 430 Criollo 460 Dominican 480 Spanish 498 Other, not specified Hispanic origin (detailed codes). IPUMS Spanish surname <svar a="all" v=" US50A432 US50A433 US50A434 US50A435 US50A456 US50A457">3. ____ The name of every person whose usual place of abode on the 1st day of June, 1850 was in this family.<br /></svar> United States 1850 (1%): All persons 1 No, not Spanish surname 2 Yes, Spanish surname Spanish surname. IPUMS Hispanic origin rule <svar a="all" v=" US50A432 US50A433 US50A434 US50A435 US50A456 US50A457">3. ____ The name of every person whose usual place of abode on the 1st day of June, 1850 was in this family.<br /></svar></p> <p><svar a=" US50A430 US50A431" v=" US50A430 US50A431 US50A432 US50A433 US50A435">9. ____ Place of birth, naming the state, territory, or country.<br /></svar> United States 1850 (1%): All persons Not assigned as Hispanic 1 Birthplace is Hispanic 6 Spanish surname Hispanic origin rule. IPUMS Race: Single race identification <svar a="all" v="US50A428 US50A429 US50A436 US50A437">6. ____ Color -- White, black, mulatto, or American Indian.<br /></svar> United States 1850 (1%): All persons 1 White 2 Black 3 American Indian/Alaska Native Race: Single race identification. IPUMS Race: Single race identification (detailed codes) <svar a="all" v="US50A428 US50A429 US50A436 US50A437">6. ____ Color -- White, black, mulatto, or American Indian.<br /></svar> United States 1850 (1%): All persons 10 White 20 Black 21 Mulatto 32 AI/AN (American Indian/Alaskan Native) Race: Single race identification (detailed codes). IPUMS School attendance <svar a="all" v="US50A438">11. ____ Attended school within the year.<br /></svar> United States 1850 (1%): All persons 1 No, not in school 2 Yes, in school School attendance. IPUMS Literacy <svar a="all" v="US50A439">12. ____ Persons over 20 years of age who cannot read and write.<br /></svar> United States 1850 (1%): Persons age 20+ NIU (not in universe) 1 No, illiterate (cannot read nor write) 4 Yes, literate (reads and writes) Literacy. IPUMS Labor force status <svar a="all" v="US50A440 US50A441 US50A442 US50A443">7. ____ Profession, occupation, or trade of each male person over 15 years of age.<br /></svar> United States 1850 (1%): Males age 16+ NIU (not in universe) 1 No, not in the labor force 2 Yes, in the labor force Labor force status. IPUMS Occupation <svar a="all" v="US50A440 US50A441 US50A442 US50A443">7. ____ Profession, occupation, or trade of each male person over 15 years of age.<br /></svar> United States 1850 (1%): Males age 15+ Occupation. This is a 3-digit numeric variable with 0 implied decimal places IPUMS Occupation, 1950 basis <svar a="all" v="US50A440 US50A441 US50A442 US50A443">7. ____ Profession, occupation, or trade of each male person over 15 years of age.<br /></svar> United States 1850 (1%): Free males age 15+ 000 Accountants and auditors 001 Actors and actresses 003 Architects 004 Artists and art teachers 005 Athletes 006 Authors 007 Chemists 009 Clergymen 010 College presidents and deans 018 Mathematics 028 Nonscientific subjects 029 Subject not specified 031 Dancers and dancing teachers 032 Dentists 033 Designers 035 Draftsmen 036 Editors and reporters 043 Engineers, civil 046 Engineers, mechanical 051 Entertainers (n.e.c.) 053 Foresters and conservationists 054 Funeral directors and embalmers 055 Lawyers and judges 057 Musicians and music teachers 062 Biological scientists 073 Pharmacists 074 Photographers 075 Physicians and surgeons 078 Religious workers 092 Surveyors 093 Teachers (n.e.c.) 097 Therapists and healers (n.e.c.) 099 Professional, technical and kindred workers (n.e.c.) 100 Farmers (owners and tenants) 123 Farm managers 201 Buyers and shippers, farm products 203 Conductors, railroad 210 Inspectors, public administration 230 Managers and superintendents, building 240 Officers, pilots, pursers and engineers, ship 250 Officials and administrators (n.e.c.), public administration 270 Postmasters 290 Managers, officials, and proprietors (n.e.c.) 300 Agents (n.e.c.) 304 Baggagemen, transportation 305 Bank tellers 310 Bookkeepers 320 Cashiers 321 Collectors, bill and account 335 Mail carriers 340 Messengers and office boys 360 Telegraph messengers 365 Telegraph operators 380 Ticket, station, and express agents 390 Clerical and kindred workers (n.e.c.) 410 Auctioneers 430 Hucksters and peddlers 450 Insurance agents and brokers 460 Newsboys 470 Real estate agents and brokers 490 Salesmen and sales clerks (n.e.c.) 500 Bakers 501 Blacksmiths 502 Bookbinders 503 Boilermakers 504 Brickmasons, stonemasons, and tile setters 505 Cabinetmakers 510 Carpenters 512 Compositors and typesetters 514 Decorators and window dressers 521 Engravers, except photoengravers 523 Foremen (n.e.c.) 524 Forgemen and hammermen 525 Furriers 532 Inspectors, scalers, and graders, log and lumber 533 Inspectors (n.e.c.) 534 Jewelers, watchmakers, goldsmiths, and silversmiths 541 Locomotive engineers 544 Machinists 554 Mechanics and repairmen (n.e.c.) 555 Millers, grain, flour, feed, etc. 560 Millwrights 561 Molders, metal 563 Opticians and lens grinders and polishers 564 Painters, construction and maintenance 565 Paperhangers 570 Pattern and model makers, except paper 571 Photoengravers and lithographers 573 Plasterers 574 Plumbers and pipe fitters 575 Pressmen and plate printers, printing 580 Rollers and roll hands, metal 581 Roofers and slaters 582 Shoemakers and repairers, except factory 583 Stationary engineers 584 Stone cutters and stone carvers 585 Structural metal workers 590 Tailors and tailoresses 591 Tinsmiths, coppersmiths, and sheet metal workers 592 Tool makers, and die makers and setters 593 Upholsterers 594 Craftsmen and kindred workers (n.e.c.) 595 Members of the armed services 602 Apprentice carpenters 611 Apprentices, building trades (n.e.c.) 614 Apprentices, other specified trades 615 Apprentices, trade not specified 622 Blasters and powdermen 623 Boatmen, canalmen, and lock keepers 624 Brakemen, railroad 625 Bus drivers 632 Deliverymen and routemen 634 Dyers 635 Filers, grinders, and polishers, metal 641 Furnacemen, smeltermen and pourers 642 Heaters, metal 644 Meat cutters, except slaughter and packing house 645 Milliners 650 Mine operatives and laborers 670 Painters, except construction or maintenance 671 Photographic process workers 673 Sailors and deck hands 674 Sawyers 675 Spinners, textile 680 Stationary firemen 681 Switchmen, railroad 682 Taxicab drivers and chauffers 683 Truck and tractor drivers 684 Weavers, textile 685 Welders and flame cutters 690 Operative and kindred workers (n.e.c.) 710 Laundressses, private household 720 Private household workers (n.e.c.) 730 Attendants, hospital and other institution 732 Attendants, recreation and amusement 740 Barbers, beauticians, and manicurists 750 Bartenders 752 Boarding and lodging house keepers 753 Charwomen and cleaners 754 Cooks, except private household 763 Guards, watchmen, and doorkeepers 764 Housekeepers and stewards, except private household 770 Janitors and sextons 771 Marshals and constables 773 Policemen and detectives 780 Porters 781 Practical nurses 782 Sheriffs and bailiffs 784 Waiters and waitresses 785 Watchmen (crossing) and bridge tenders 790 Service workers, except private household (n.e.c.) 810 Farm foremen 820 Farm laborers, wage workers 840 Farm service laborers, self-employed 910 Fishermen and oystermen 930 Gardeners, except farm, and groundskeepers 940 Longshoremen and stevedores 950 Lumbermen, raftsmen, and woodchoppers 970 Laborers (n.e.c.) 983 At school/student 984 Retired 986 Invalid/disabled w/ no occupation reported 987 Inmate 995 Other non-occupational response 999 NIU (not in universe) (blank) Occupation, 1950 basis. IPUMS Industry, 1950 basis <svar a="all" v="US50A440 US50A441 US50A442 US50A443">7. ____ Profession, occupation, or trade of each male person over 15 years of age.<br /></svar> United States 1850 (1%): Males of any age with an occupation recorded 000 NIU (not in universe) or none reported 105 Agriculture 116 Forestry 126 Fisheries 206 Metal mining 216 Coal mining 236 Nonmetallic mining and quarrying, except fuel 239 Mining, not specified 246 Construction 306 Logging 307 Sawmills, planing mills, and mill work 308 Miscellaneous wood products 309 Furniture and fixtures 316 Glass and glass products 317 Cement, concrete, gypsum and plaster products 318 Structural clay products 319 Pottery and related products 326 Miscellaneous nonmetallic mineral and stone products 336 Blast furnaces, steel works, and rolling mills 337 Other primary iron and steel industries 338 Primary nonferrous industries 346 Fabricated steel products 347 Fabricated nonferrous metal products 348 Not specified metal industries 356 Agricultural machinery and tractors 358 Miscellaneous machinery 367 Electrical machinery, equipment, and supplies 378 Ship and boat building and repairing 379 Railroad and miscellaneous transportation equipment 386 Professional equipment and supplies 388 Watches, clocks, and clockwork-operated devices 399 Miscellaneous manufacturing industries 406 Meat products 408 Canning and preserving fruits, vegetables, and seafoods 409 Grain-mill products 416 Bakery products 417 Confectionery and related products 418 Beverage industries 419 Miscellaneous food preparations and kindred products 429 Tobacco manufactures 436 Knitting mills 437 Dyeing and finishing textiles, except knit goods 438 Carpets, rugs, and other floor coverings 439 Yarn, thread, and fabric mills 446 Miscellaneous textile mill products 448 Apparel and accessories 449 Miscellaneous fabricated textile products 456 Pulp, paper, and paperboard mills 457 Paperboard containers and boxes 458 Miscellaneous paper and pulp products 459 Printing, publishing, and allied industries 467 Drugs and medicines 468 Paints, varnishes, and related products 469 Miscellaneous chemicals and allied products 476 Petroleum refining 478 Rubber products 487 Leather: tanned, curried, and finished 488 Footwear, except rubber 489 Leather products, except footwear 499 Not specified manufacturing industries 506 Railroads and railway express service 516 Street railways and bus lines 526 Trucking service 527 Warehousing and storage 536 Taxicab service 546 Water transportation 568 Services incidental to transportation 579 Telegraph 587 Gas and steam supply systems 596 Water supply 597 Sanitary services 607 Drugs, chemicals, and allied products 608 Dry goods apparel 609 Food and related products 617 Machinery, equipment, and supplies 619 Farm products--raw materials 626 Miscellaneous wholesale trade 627 Not specified wholesale trade 636 Food stores, except dairy products 637 Dairy products stores and milk retailing 646 General merchandise stores 647 Five and ten cent stores 656 Apparel and accessories stores, except shoe 657 Shoe stores 658 Furniture and house furnishing stores 659 Household appliance and radio stores 667 Motor vehicles and accessories retailing 669 Drug stores 679 Eating and drinking places 686 Hardware and farm implement stores 687 Lumber and building material retailing 688 Liquor stores 696 Jewelry stores 697 Fuel and ice retailing 698 Miscellaneous retail stores 699 Not specified retail trade 716 Banking and credit agencies 726 Security and commodity brokerage and investment companies 736 Insurance 746 Real estate 806 Advertising 807 Accounting, auditing, and bookkeeping services 808 Miscellaneous business services 817 Miscellaneous repair services 826 Private households 836 Hotels and lodging places 846 Laundering, cleaning, and dyeing services 849 Miscellaneous personal services 857 Theaters and motion pictures 858 Bowling alleys, and billiard and pool parlors 859 Miscellaneous entertainment and recreation services 868 Medical and other health services, except hospitals 869 Hospitals 879 Legal services 888 Educational services 896 Welfare and religious services 898 Engineering and architectural services 899 Miscellaneous professional and related services 906 Postal service 916 Federal public administration 926 State public administration 936 Local public administration 946 Public Administration, level not specified 997 Nonclassifiable Industry, 1950 basis. IPUMS Real estate value <svar a="all" v="US50A444">8. ____ Value of real estate owned.<br /></svar> United States 1850 (1%): All persons Real estate value. This is a 6-digit numeric variable with 0 implied decimal places IPUMS Occupational income score United States 1850 (1%): Persons with an occupational response Occupational income score. This is a 2-digit numeric variable with 0 implied decimal places IPUMS Duncan Socioeconomic Index United States 1850 (1%): Persons with an occupational response Duncan Socioeconomic Index. This is a 2-digit numeric variable with 0 implied decimal places IPUMS Occupational prestige score, Siegel United States 1850 (1%): Persons with an occupational response Occupational prestige score, Siegel. This is a 3-digit numeric variable with 0 implied decimal places IPUMS Occupational earnings score, 1950 basis United States 1850 (1%): Persons with an occupational response Occupational earnings score, 1950 basis. This is a 4-digit numeric variable with 0 implied decimal places IPUMS Occupational education score, 1950 basis United States 1850 (1%): Persons with an occupational response Occupational education score, 1950 basis. This is a 4-digit numeric variable with 0 implied decimal places IPUMS Nam-Powers-Boyd occupational status score, 1950 basis United States 1850 (1%): Persons with an occupational response Nam-Powers-Boyd occupational status score, 1950 basis. This is a 4-digit numeric variable with 0 implied decimal places IPUMS Blind <svar a="all" v="US50A451 US50A452 US50A453 US50A454">13. ____ Whether deaf and dumb, blind, insane, idiotic, pauper or convict.<br /></svar> United States 1850 (1%): All persons 1 No (blank) 2 Yes Blind. IPUMS Deaf and dumb <svar a="all" v="US50A451 US50A452 US50A453 US50A454">13. ____ Whether deaf and dumb, blind, insane, idiotic, pauper or convict.<br /></svar> United States 1850 (1%): All persons 1 No (blank) 2 Yes Deaf and dumb. IPUMS Idiotic <svar a="all" v="US50A451 US50A452 US50A453 US50A454">13. ____ Whether deaf and dumb, blind, insane, idiotic, pauper or convict.<br /></svar> United States 1850 (1%): All persons 1 No (blank) 2 Yes Idiotic. IPUMS Insane <svar a="all" v="US50A451 US50A452 US50A453 US50A454">13. ____ Whether deaf and dumb, blind, insane, idiotic, pauper or convict.<br /></svar> United States 1850 (1%): All persons 1 No (blank) 2 Yes Insane. IPUMS Detailed person weight, based on low-level geography United States 1850 (1%): All persons Detailed person weight, based on low-level geography. This is a 6-digit numeric variable with 0 implied decimal places IPUMS Last name <svar a="all" v=" US50A432 US50A433 US50A434 US50A435 US50A456 US50A457">3. ____ The name of every person whose usual place of abode on the 1st day of June, 1850 was in this family.<br /></svar> United States 1850 (1%): All persons Last name. This is a 16-digit numeric variable with 0 implied decimal places IPUMS First name <svar a="all" v=" US50A432 US50A433 US50A434 US50A435 US50A456 US50A457">3. ____ The name of every person whose usual place of abode on the 1st day of June, 1850 was in this family.<br /></svar> United States 1850 (1%): All persons First name. This is a 16-digit numeric variable with 0 implied decimal places IPUMS Surname similarity United States 1850 (1%): All persons 01 1st surname in household 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 Surname similarity. IPUMS Occupation, original alphabetic string United States 1850 (1%): All persons who reported an occupation; not available for Puerto Rico Occupation, original alphabetic string. This is a 52-digit numeric variable with 0 implied decimal places IPUMS Pauper <svar a="all" v="US50A451 US50A452 US50A453 US50A454">13. ____ Whether deaf and dumb, blind, insane, idiotic, pauper or convict.<br /></svar> United States 1850 (1%): All persons 1 No (blank) 2 Yes Pauper. IPUMS Crime <svar a="all" v="US50A451 US50A452 US50A453 US50A454">13. ____ Whether deaf and dumb, blind, insane, idiotic, pauper or convict.<br /></svar> United States 1850 (1%): All persons 1 Drunk or disorderly 2 Theft, burglary, larceny 3 Assault 4 Rape 5 Murder, manslaughter 6 Miscellaneous 7 Convict/in jail 8 Unknown 9 Missing Crime. IPUMS