DDI_SLV_2007_PHC_v01_M_v7.5_A_IPUMS 6th Census of Population IPUMS May 20, 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. 6th Census of Population - IPUMS Subset PHC El Salvador 2007 (IPUMS Harmonized Subset) SLV_2007_PHC_v01_M_v7.5_A_IPUMS General Directorate of Statistics and Censuses IPUMS (c) Copyright 2007, General Directorate of Statistics and Censuses and Minnesota Population Center MetadataEditor General Directorate of Statistics and Censuses 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 Other Household Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Dwelling Characteristics Variables -- HOUSEHOLD Nativity and Birthplace Variables -- PERSON Utilities Variables -- HOUSEHOLD Fertility and Mortality Variables -- PERSON Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Geography: A-E Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Ethnicity and Language Variables -- PERSON Household Economic Variables -- HOUSEHOLD Migration: A-E Variables -- PERSON Technical Person Variables -- PERSON Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Demographic Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Technical Household Variables -- HOUSEHOLD Education Variables -- PERSON Utilities Variables -- HOUSEHOLD Ethnicity and Language Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Nativity and Birthplace Variables -- PERSON Technical Person Variables -- PERSON Geography: A-E Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Other Person Variables -- PERSON Disability Variables -- PERSON Disability Variables -- PERSON Ethnicity and Language Variables -- PERSON Nativity and Birthplace Variables -- PERSON Migration: Global Variables -- PERSON Education Variables -- PERSON Demographic Variables -- PERSON Other Person Variables -- PERSON Income Variables -- PERSON Work Variables -- PERSON Fertility and Mortality Variables -- PERSON Work: Occupation Variables -- PERSON Work: Industry Variables -- PERSON El Salvador Municipality Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: An enclosure intended to be used as the living space [habitación] of one person or a group of persons who make up one or various households. The dwelling may be an independent house [casa independiente], an apartment, a room in a house, room in a tenement, a hut, an improvised dwelling, a premise not intended for human habitation, or other (mobile dwelling, tent, etc.) - Households: People who live together and share food expenses - Group quarters: This is a premise or building where a group of persons without family ties lives and which they share for reasons of accommodation, age, status as orphans, etc. The following are included in this category: homes for children or orphanages, retirement homes, jails, guest houses or boarding houses, boarding schools, etc. Homeless Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: El Salvador 2007 MICRODATA SOURCE: General Directorate of Statistics and Censuses SAMPLE SIZE (person records): 574364. SAMPLE DESIGN: Stratified systematic sample. Homeless Face-to-face [f2f] Census questionnaire containing questions on demographic and socio-economic characteristics of the population, dwelling unit characteristics, emigration, and mortality. de jure, CENSUS DAY: May 12-27, 2007 Self-weighting (expansion factor=10) IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS International are designed to extend this record. General Directorate of Statistics and Censuses 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: El Salvador, General Directorate of Statistics and Censuses. 6th Census of Population 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. SLV2007_PHC-H-H Household records 172 100 SLV2007_PHC-P-H Person records 574364 146 Record type H Household P Person RECTYPE identifies the type of record for the case: household or person. NOTE: RECTYPE is an alphabetic (character string) variable with a value of 'H' for household records and 'P' for person records. RECTYPE will not appear as a variable in the default rectangular extracts produced by the data extract system. It is only available in hierarchical extracts, to distinguish between the two record types. IPUMS Country 032 Argentina 051 Armenia 040 Austria 050 Bangladesh 112 Belarus 204 Benin 068 Bolivia 072 Botswana 076 Brazil 854 Burkina Faso 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 208 Denmark 214 Dominican Republic 218 Ecuador 818 Egypt 222 El Salvador 231 Ethiopia 242 Fiji 246 Finland 250 France 276 Germany 288 Ghana 300 Greece 320 Guatemala 324 Guinea 332 Haiti 340 Honduras 348 Hungary 352 Iceland 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 384 Ivory Coast 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 418 Laos 426 Lesotho 430 Liberia 454 Malawi 458 Malaysia 466 Mali 480 Mauritius 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 104 Myanmar 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 578 Norway 586 Pakistan 275 Palestine 591 Panama 598 Papua New Guinea 600 Paraguay 604 Peru 608 Philippines 616 Poland 620 Portugal 630 Puerto Rico 642 Romania 643 Russia 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 703 Slovak Republic 705 Slovenia 710 South Africa 728 South Sudan 724 Spain 729 Sudan 740 Suriname 752 Sweden 756 Switzerland 834 Tanzania 764 Thailand 768 Togo 780 Trinidad and Tobago 792 Turkey 800 Uganda 804 Ukraine 826 United Kingdom 840 United States 858 Uruguay 862 Venezuela 704 Vietnam 894 Zambia 716 Zimbabwe COUNTRY gives the country from which the sample was drawn. The codes assigned to each country are those used by the UN Statistics Division and the ISO (International Organization for Standardization). IPUMS Year 1703 1703 1729 1729 1787 1787 1801 1801 1819 1819 1845 1845 1848 1848 1850 1850 1851 1851 1852 1852 1860 1860 1861 1861 1865 1865 1868 1868 1870 1870 1871 1871 1875 1875 1880 1880 1881 1881 1885 1885 1890 1890 1891 1891 1900 1900 1901 1901 1910 1910 1911 1911 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1966 1966 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 YEAR gives the year in which the census or survey was taken. For samples that span years, the midpoint or first year of the interval is reported. IPUMS IPUMS sample identifier 032197001 Argentina 1970 032198001 Argentina 1980 032199101 Argentina 1991 032200101 Argentina 2001 032201001 Argentina 2010 051200101 Armenia 2001 051201101 Armenia 2011 040197101 Austria 1971 040198101 Austria 1981 040199101 Austria 1991 040200101 Austria 2001 040201101 Austria 2011 050199101 Bangladesh 1991 050200101 Bangladesh 2001 050201101 Bangladesh 2011 112199901 Belarus 1999 112200901 Belarus 2009 204197901 Benin 1979 204199201 Benin 1992 204200201 Benin 2002 204201301 Benin 2013 068197601 Bolivia 1976 068199201 Bolivia 1992 068200101 Bolivia 2001 068201201 Bolivia 2012 072198101 Botswana 1981 072199101 Botswana 1991 072200101 Botswana 2001 072201101 Botswana 2011 076196001 Brazil 1960 076197001 Brazil 1970 076198001 Brazil 1980 076199101 Brazil 1991 076200001 Brazil 2000 076201001 Brazil 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 116199801 Cambodia 1998 116200401 Cambodia 2004 116200801 Cambodia 2008 116201301 Cambodia 2013 116201901 Cambodia 2019 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124185201 Canada 1852 124187101 Canada 1871 124188101 Canada 1881 124189101 Canada 1891 124190101 Canada 1901 124191101 Canada 1911 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 124201101 Canada 2011 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 152201701 Chile 2017 156198201 China 1982 156199001 China 1990 156200001 China 2000 170196401 Colombia 1964 170197301 Colombia 1973 170198501 Colombia 1985 170199301 Colombia 1993 170200501 Colombia 2005 188196301 Costa Rica 1963 188197301 Costa Rica 1973 188198401 Costa Rica 1984 188200001 Costa Rica 2000 188201101 Costa Rica 2011 192200201 Cuba 2002 192201201 Cuba 2012 208178701 Denmark 1787 208180101 Denmark 1801 208184501 Denmark 1845 208188001 Denmark 1880 208188501 Denmark 1885 214196001 Dominican Republic 1960 214197001 Dominican Republic 1970 214198101 Dominican Republic 1981 214200201 Dominican Republic 2002 214201001 Dominican Republic 2010 218196201 Ecuador 1962 218197401 Ecuador 1974 218198201 Ecuador 1982 218199001 Ecuador 1990 218200101 Ecuador 2001 218201001 Ecuador 2010 818184801 Egypt 1848 818186801 Egypt 1868 818198601 Egypt 1986 818199601 Egypt 1996 818200601 Egypt 2006 222199201 El Salvador 1992 222200701 El Salvador 2007 231198401 Ethiopia 1984 231199401 Ethiopia 1994 231200701 Ethiopia 2007 242196601 Fiji 1966 242197601 Fiji 1976 242198601 Fiji 1986 242199601 Fiji 1996 242200701 Fiji 2007 242201401 Fiji 2014 246201001 Finland 2010 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 276181901 Germany 1819 (Mecklenburg) 276197001 Germany 1970 (West) 276197101 Germany 1971 (East) 276198101 Germany 1981 (East) 276198701 Germany 1987 (West) 288198401 Ghana 1984 288200001 Ghana 2000 288201001 Ghana 2010 300197101 Greece 1971 300198101 Greece 1981 300199101 Greece 1991 300200101 Greece 2001 300201101 Greece 2011 320196401 Guatemala 1964 320197301 Guatemala 1973 320198101 Guatemala 1981 320199401 Guatemala 1994 320200201 Guatemala 2002 324198301 Guinea 1983 324199601 Guinea 1996 324201401 Guinea 2014 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 340196101 Honduras 1961 340197401 Honduras 1974 340198801 Honduras 1988 340200101 Honduras 2001 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 348201101 Hungary 2011 352170301 Iceland 1703 352172901 Iceland 1729 352180101 Iceland 1801 352190101 Iceland 1901 352191001 Iceland 1910 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 356200941 India 2009 360197101 Indonesia 1971 360197601 Indonesia 1976 360198001 Indonesia 1980 360198501 Indonesia 1985 360199001 Indonesia 1990 360199501 Indonesia 1995 360200001 Indonesia 2000 360200501 Indonesia 2005 360201001 Indonesia 2010 364200601 Iran 2006 364201101 Iran 2011 368199701 Iraq 1997 372190101 Ireland 1901 372191101 Ireland 1911 372197101 Ireland 1971 372197901 Ireland 1979 372198101 Ireland 1981 372198601 Ireland 1986 372199101 Ireland 1991 372199601 Ireland 1996 372200201 Ireland 2002 372200601 Ireland 2006 372201101 Ireland 2011 372201601 Ireland 2016 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 376200801 Israel 2008 380200101 Italy 2001 380201101 Italy 2011 380201121 Italy 2011 Q1 LFS 380201221 Italy 2012 Q1 LFS 380201321 Italy 2013 Q1 LFS 380201421 Italy 2014 Q1 LFS 380201521 Italy 2015 Q1 LFS 380201621 Italy 2016 Q1 LFS 380201721 Italy 2017 Q1 LFS 380201821 Italy 2018 Q1 LFS 380201921 Italy 2019 Q1 LFS 380202021 Italy 2020 Q1 LFS 384198801 Ivory Coast 1988 384199801 Ivory Coast 1998 388198201 Jamaica 1982 388199101 Jamaica 1991 388200101 Jamaica 2001 400200401 Jordan 2004 404196901 Kenya 1969 404197901 Kenya 1979 404198901 Kenya 1989 404199901 Kenya 1999 404200901 Kenya 2009 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 418199501 Laos 1995 418200501 Laos 2005 418201501 Laos 2015 426199601 Lesotho 1996 426200601 Lesotho 2006 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 480199001 Mauritius 1990 480200001 Mauritius 2000 480201101 Mauritius 2011 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 484201501 Mexico 2015 484202001 Mexico 2020 484200521 Mexico 2005 Q1 LFS 484200522 Mexico 2005 Q2 LFS 484200523 Mexico 2005 Q3 LFS 484200524 Mexico 2005 Q4 LFS 484200621 Mexico 2006 Q1 LFS 484200622 Mexico 2006 Q2 LFS 484200623 Mexico 2006 Q3 LFS 484200624 Mexico 2006 Q4 LFS 484200721 Mexico 2007 Q1 LFS 484200722 Mexico 2007 Q2 LFS 484200723 Mexico 2007 Q3 LFS 484200724 Mexico 2007 Q4 LFS 484200821 Mexico 2008 Q1 LFS 484200822 Mexico 2008 Q2 LFS 484200823 Mexico 2008 Q3 LFS 484200824 Mexico 2008 Q4 LFS 484200921 Mexico 2009 Q1 LFS 484200922 Mexico 2009 Q2 LFS 484200923 Mexico 2009 Q3 LFS 484200924 Mexico 2009 Q4 LFS 484201021 Mexico 2010 Q1 LFS 484201022 Mexico 2010 Q2 LFS 484201023 Mexico 2010 Q3 LFS 484201024 Mexico 2010 Q4 LFS 484201121 Mexico 2011 Q1 LFS 484201122 Mexico 2011 Q2 LFS 484201123 Mexico 2011 Q3 LFS 484201124 Mexico 2011 Q4 LFS 484201221 Mexico 2012 Q1 LFS 484201222 Mexico 2012 Q2 LFS 484201223 Mexico 2012 Q3 LFS 484201224 Mexico 2012 Q4 LFS 484201321 Mexico 2013 Q1 LFS 484201322 Mexico 2013 Q2 LFS 484201323 Mexico 2013 Q3 LFS 484201324 Mexico 2013 Q4 LFS 484201421 Mexico 2014 Q1 LFS 484201422 Mexico 2014 Q2 LFS 484201423 Mexico 2014 Q3 LFS 484201424 Mexico 2014 Q4 LFS 484201521 Mexico 2015 Q1 LFS 484201522 Mexico 2015 Q2 LFS 484201523 Mexico 2015 Q3 LFS 484201524 Mexico 2015 Q4 LFS 484201621 Mexico 2016 Q1 LFS 484201622 Mexico 2016 Q2 LFS 484201623 Mexico 2016 Q3 LFS 484201624 Mexico 2016 Q4 LFS 484201721 Mexico 2017 Q1 LFS 484201722 Mexico 2017 Q2 LFS 484201723 Mexico 2017 Q3 LFS 484201724 Mexico 2017 Q4 LFS 484201821 Mexico 2018 Q1 LFS 484201822 Mexico 2018 Q2 LFS 484201823 Mexico 2018 Q3 LFS 484201824 Mexico 2018 Q4 LFS 484201921 Mexico 2019 Q1 LFS 484201922 Mexico 2019 Q2 LFS 484201923 Mexico 2019 Q3 LFS 484201924 Mexico 2019 Q4 LFS 484202021 Mexico 2020 Q1 LFS 484202023 Mexico 2020 Q3 LFS 496198901 Mongolia 1989 496200001 Mongolia 2000 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 104201401 Myanmar 2014 524200101 Nepal 2001 524201101 Nepal 2011 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 528201101 Netherlands 2011 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 578180101 Norway 1801 578186501 Norway 1865 578187501 Norway 1875 578190001 Norway 1900 578191001 Norway 1910 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 275199701 Palestine 1997 275200701 Palestine 2007 275201701 Palestine 2017 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 598198001 Papua New Guinea 1980 598199001 Papua New Guinea 1990 598200001 Papua New Guinea 2000 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 604201701 Peru 2017 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 608201001 Philippines 2010 616197801 Poland 1978 616198801 Poland 1988 616200201 Poland 2002 616201101 Poland 2011 620198101 Portugal 1981 620199101 Portugal 1991 620200101 Portugal 2001 620201101 Portugal 2011 630197001 Puerto Rico 1970 630198001 Puerto Rico 1980 630199001 Puerto Rico 1990 630200001 Puerto Rico 2000 630200501 Puerto Rico 2005 630201001 Puerto Rico 2010 630201501 Puerto Rico 2015 630202001 Puerto Rico 2020 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 642201101 Romania 2011 643200201 Russia 2002 643201001 Russia 2010 646199101 Rwanda 1991 646200201 Rwanda 2002 646201201 Rwanda 2012 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 686201301 Senegal 2013 694200401 Sierra Leone 2004 694201501 Sierra Leone 2015 703199101 Slovak Republic 1991 703200101 Slovak Republic 2001 703201101 Slovak Republic 2011 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 710201601 South Africa 2016 728200801 South Sudan 2008 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 724200521 Spain 2005 Q1 LFS 724200522 Spain 2005 Q2 LFS 724200523 Spain 2005 Q3 LFS 724200524 Spain 2005 Q4 LFS 724200621 Spain 2006 Q1 LFS 724200622 Spain 2006 Q2 LFS 724200623 Spain 2006 Q3 LFS 724200624 Spain 2006 Q4 LFS 724200721 Spain 2007 Q1 LFS 724200722 Spain 2007 Q2 LFS 724200723 Spain 2007 Q3 LFS 724200724 Spain 2007 Q4 LFS 724200821 Spain 2008 Q1 LFS 724200822 Spain 2008 Q2 LFS 724200823 Spain 2008 Q3 LFS 724200824 Spain 2008 Q4 LFS 724200921 Spain 2009 Q1 LFS 724200922 Spain 2009 Q2 LFS 724200923 Spain 2009 Q3 LFS 724200924 Spain 2009 Q4 LFS 724201021 Spain 2010 Q1 LFS 724201022 Spain 2010 Q2 LFS 724201023 Spain 2010 Q3 LFS 724201024 Spain 2010 Q4 LFS 724201121 Spain 2011 Q1 LFS 724201122 Spain 2011 Q2 LFS 724201123 Spain 2011 Q3 LFS 724201124 Spain 2011 Q4 LFS 724201221 Spain 2012 Q1 LFS 724201222 Spain 2012 Q2 LFS 724201223 Spain 2012 Q3 LFS 724201224 Spain 2012 Q4 LFS 724201321 Spain 2013 Q1 LFS 724201322 Spain 2013 Q2 LFS 724201323 Spain 2013 Q3 LFS 724201324 Spain 2013 Q4 LFS 724201421 Spain 2014 Q1 LFS 724201422 Spain 2014 Q2 LFS 724201423 Spain 2014 Q3 LFS 724201424 Spain 2014 Q4 LFS 724201521 Spain 2015 Q1 LFS 724201522 Spain 2015 Q2 LFS 724201523 Spain 2015 Q3 LFS 724201524 Spain 2015 Q4 LFS 724201621 Spain 2016 Q1 LFS 724201622 Spain 2016 Q2 LFS 724201623 Spain 2016 Q3 LFS 724201624 Spain 2016 Q4 LFS 724201721 Spain 2017 Q1 LFS 724201722 Spain 2017 Q2 LFS 724201723 Spain 2017 Q3 LFS 724201724 Spain 2017 Q4 LFS 724201821 Spain 2018 Q1 LFS 724201822 Spain 2018 Q2 LFS 724201823 Spain 2018 Q3 LFS 724201824 Spain 2018 Q4 LFS 724201921 Spain 2019 Q1 LFS 724201922 Spain 2019 Q2 LFS 724201923 Spain 2019 Q3 LFS 724201924 Spain 2019 Q4 LFS 724202021 Spain 2020 Q1 LFS 724202022 Spain 2020 Q2 LFS 724202023 Spain 2020 Q3 LFS 724202024 Spain 2020 Q4 LFS 729200801 Sudan 2008 740200401 Suriname 2004 740201201 Suriname 2012 752188001 Sweden 1880 752189001 Sweden 1890 752190001 Sweden 1900 752191001 Sweden 1910 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 756201101 Switzerland 2011 834198801 Tanzania 1988 834200201 Tanzania 2002 834201201 Tanzania 2012 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 768196001 Togo 1960 768197001 Togo 1970 768201001 Togo 2010 780197001 Trinidad and Tobago 1970 780198001 Trinidad and Tobago 1980 780199001 Trinidad and Tobago 1990 780200001 Trinidad and Tobago 2000 780201101 Trinidad and Tobago 2011 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 800201401 Uganda 2014 804200101 Ukraine 2001 826185101 United Kingdom 1851 (England and Wales) 826185102 United Kingdom 1851 (Scotland) 826185103 United Kingdom 1851 (2% sample) 826186101 United Kingdom 1861 (England and Wales) 826186102 United Kingdom 1861 (Scotland) 826187101 United Kingdom 1871 (Scotland) 826188101 United Kingdom 1881 (England and Wales) 826188102 United Kingdom 1881 (Scotland) 826189101 United Kingdom 1891 (England and Wales) 826189102 United Kingdom 1891 (Scotland) 826190101 United Kingdom 1901 (England and Wales) 826190102 United Kingdom 1901 (Scotland) 826191101 United Kingdom 1911 (England and Wales) 826196101 United Kingdom 1961 826197101 United Kingdom 1971 826199101 United Kingdom 1991 826200101 United Kingdom 2001 840185001 United States 1850 (100%) 840185002 United States 1850 (1%) 840186001 United States 1860 (1%) 840187001 United States 1870 (1%) 840188001 United States 1880 (100%) 840188002 United States 1880 (10%) 840190001 United States 1900 (5%) 840191001 United States 1910 (1%) 840196001 United States 1960 840197001 United States 1970 840198001 United States 1980 840199001 United States 1990 840200001 United States 2000 840200501 United States 2005 840201001 United States 2010 840201501 United States 2015 840202001 United States 2020 858196301 Uruguay 1963 858196302 Uruguay 1963 (full count) 858197501 Uruguay 1975 858197502 Uruguay 1975 (full count) 858198501 Uruguay 1985 858198502 Uruguay 1985 (full count) 858199601 Uruguay 1996 858199602 Uruguay 1996 (full count) 858200621 Uruguay 2006 858201101 Uruguay 2011 858201102 Uruguay 2011 (full count) 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 704201901 Vietnam 2019 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 716201201 Zimbabwe 2012 SAMPLE identifies the IPUMS sample from which the case is drawn. Each sample receives a unique 9-digit code. The code is structured as follows: The first 3 digits are the ISO/UN codes used in COUNTRY The next 4 digits are the year of the census/survey The final 2 digits identify the sample within the year. For the last two digits, censuses or large census-like surveys have a value "0" (e.g, 01) in the second-to-last digit, household surveys have a value of "2" (e.g., 21), and employment surveys have a value of "4" (e.g., 41). IPUMS Household serial number SERIAL is an identifying number unique to each household in a given sample. All person records are assigned the same serial number as the household record that they follow. (Person records also have their own unique identifiers -- see PERNUM.) The combination of SAMPLE and SERIAL provides a unique identifier for every household in the IPUMS-International database; SAMPLE, SERIAL and PERNUM uniquely identify every person in the database. SERIAL can be used to identify dwellings in some samples. In these samples, the first 7 digits of SERIAL provide the dwelling number common to all households that were sampled from the same structure. The last three digits give the sequence of the household within the dwelling. The following is a list of samples in which dwellings can be inferred: Chile 1970, 1992, 2002Colombia 1993, 2005Costa Rica 1984, 2000Cuba 2002Dominican Republic 1981, 2002, 2010Ecuador 1990, 2001Germany 1971Hungary 1980, 1990, 2001Jamaica 1982, 1991, 2001Malaysia 1970, 1991, 2000Mexico 1995, 1990, 2000, 2005Nigeria 2006Panama 2000Peru 1993, 2007Portugal 1981, 1991, 2001Spain 1991Uruguay 2011Venezuela 1990, 2001Vietnam 1989In all other samples, the last 3 digits are always zeroes. SERIAL was constructed for IPUMS-International, and has no relation to the serial number in the original datasets. The U.S. 1900 sample and 1880 10% sample have multi-household dwellings that can be identified using the last 3 digits of SERIAL. SERIAL is a 10-digit numeric variable. The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes. IPUMS Number of person records in the household PERSONS indicates how many person records are included in the household (i.e., the number of person records associated with the household record in the sample). These person records will all have the same serial number (SERIAL) as the household record. The information contained in the household record will normally apply to all of these persons. PERSONS is a 4-digit numeric variable. IPUMS Household weight HHWT indicates the number of households in the population represented by the household in the sample. For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics. NOTE: HHWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. IPUMS Subsample number 00 1st 1% subsample 01 2nd 1% subsample 02 3rd 1% subsample 03 4th 1% subsample 04 5th 1% subsample 05 6th 1% subsample 06 7th 1% subsample 07 8th 1% subsample 08 9th 1% subsample 09 10th 1% subsample 10 11th 1% subsample 11 12th 1% subsample 12 13th 1% subsample 13 14th 1% subsample 14 15th 1% subsample 15 16th 1% subsample 16 17th 1% subsample 17 18th 1% subsample 18 19th 1% subsample 19 20th 1% subsample 20 21st 1% subsample 21 22nd 1% subsample 22 23rd 1% subsample 23 24th 1% subsample 24 25th 1% subsample 25 26th 1% subsample 26 27th 1% subsample 27 28th 1% subsample 28 29th 1% subsample 29 30th 1% subsample 30 31st 1% subsample 31 32nd 1% subsample 32 33rd 1% subsample 33 34th 1% subsample 34 35th 1% subsample 35 36th 1% subsample 36 37th 1% subsample 37 38th 1% subsample 38 39th 1% subsample 39 40th 1% subsample 40 41st 1% subsample 41 42nd 1% subsample 42 43rd 1% subsample 43 44th 1% subsample 44 45th 1% subsample 45 46th 1% subsample 46 47th 1% subsample 47 48th 1% subsample 48 49th 1% subsample 49 50th 1% subsample 50 51st 1% subsample 51 52nd 1% subsample 52 53rd 1% subsample 53 54th 1% subsample 54 55th 1% subsample 55 56th 1% subsample 56 57th 1% subsample 57 58th 1% subsample 58 59th 1% subsample 59 60th 1% subsample 60 61st 1% subsample 61 62nd 1% subsample 62 63rd 1% subsample 63 64th 1% subsample 64 65th 1% subsample 65 66th 1% subsample 66 67th 1% subsample 67 68th 1% subsample 68 69th 1% subsample 69 70th 1% subsample 70 71st 1% subsample 71 72nd 1% subsample 72 73rd 1% subsample 73 74th 1% subsample 74 75th 1% subsample 75 76th 1% subsample 76 77th 1% subsample 77 78th 1% subsample 78 79th 1% subsample 79 80th 1% subsample 80 81st 1% subsample 81 82nd 1% subsample 82 83rd 1% subsample 83 84th 1% subsample 84 85th 1% subsample 85 86th 1% subsample 86 87th 1% subsample 87 88th 1% subsample 88 89th 1% subsample 89 90th 1% subsample 90 91st 1% subsample 91 92nd 1% subsample 92 93rd 1% subsample 93 94th 1% subsample 94 95th 1% subsample 95 96th 1% subsample 96 97th 1% subsample 97 98th 1% subsample 98 99th 1% subsample 99 100th 1% subsample SUBSAMP allocates each case to one of 100 subsample replicates, randomly numbered from 0 to 99. Each subsample is nationally representative and preserves any stratification of the sample from which it is drawn. Users who need a representative subset of a sample can use SUBSAMP to select their cases. For example, to randomly extract 10% of the cases from a sample, select any 10 of the 100 subsamples. IPUMS Group quarters (collective dwelling) status 00 Vacant 10 Households 20 Group quarters (collective), n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools. Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification. Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions. IPUMS Group quarters type 100 Institutional 110 Prisons, reformatories, or correctional institutions 120 Hospital, nursing home, hospice, or instutions for persons with disabilities 121 Institutions for persons with disabilities 122 Sanatorium or mental institutions 130 Homes for the elderly or orphanage 131 Retirement home 132 Orphanage, children's home 140 Shelter for homeless, youth, or others 150 Military or police institution 160 Boarding school or student housing 170 Religious institution, monastery, seminary, or convent 199 Other institutional n.e.c. 200 Non-institutional 210 Camps (refugees, workers, or others) 220 Hotel, pension, lodging, or boarding house 230 Floating population 299 Other non-institutional n.e.c. 300 Other group quarters 399 1-person unit created by splitting large household 998 Unknown 999 NIU (not in universe) GQTYPE identifies the type of group quarters -- collective dwellings -- which are broadly classified into institutional and non-institutional types. Institutions are a place of residence where people are subject to a common authority or bound by a common objective or personal interest. The definition encompasses correctional facilities, health institutions, retirement homes, orphanages, shelters (social welfare institutions), military or police establishments, boarding schools, and religious group dwellings. Non-institutional group quarters comprise refugee and workers' camps (temporary accommodation), hotels, pensions, and all types of boarding or lodging houses. The "floating population" is included as a category within the non-institutional group quarters, when identified by the corresponding sample. This group refers to outdoor sleepers, homeless persons, travelers, and persons in ships, boats, or other mobile dwellings. A more general classification of households between private and group quarters is available in GQ. 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 1st subnational geographic level, world [consistent boundaries over time] GEOLEV1 indicates the major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. First administrative units in GEOLEV1 have been spatiotemporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV1 is a 6-digit numeric variable. GEOLEV1 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO1_BR. IPUMS 2nd subnational geographic level, world [consistent boundaries over time] GEOLEV2 indicates the second major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. Second administrative units in GEOLEV2 have been spatio-temporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV2 is a 9-digit numeric variable. GEOLEV2 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO2_BR. IPUMS Population density of GEOLEV1 unit, in persons per square kilometer POPDENSGEO1 indicates the population density in persons per square kilometer of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO1 is an 8-digit string variable listing the population density in persons per square kilometer. IPUMS Population density of GEOLEV2 unit, in persons per square kilometer POPDENSGEO2 indicates the population density in persons per square kilometer of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO2 is a 12-digit string variable listing the population density in persons per square kilometer. IPUMS Area of GEOLEV1 unit in square kilometers AREAMOLLWGEO1 indicates the area in square kilometers of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO1 is a 10-digit string variable listing the area in square kilometers. IPUMS Area of GEOLEV2 unit in square kilometers AREAMOLLWGEO2 indicates the area in square kilometers of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO2 is a 10-digit string variable listing the area in square kilometers. IPUMS El Salvador, Department 1992 - 2007 [Level 1; consistent boundaries, GIS] 222001 Ahuachapán 222002 Santa Ana 222003 Sonsonate 222004 Chalatenango 222005 La Libertad 222006 San Salvador 222007 Cuscatlán 222008 La Paz 222009 Cabañas 222010 San Vicente 222011 Usulután 222012 San Miguel 222013 Morazán 222014 La Unión GEO1_SV identifies the household's department within El Salvador in all sample years. Departments are the first level administrative units of the country. GEO1_SV is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization. A GIS map (in shapefile format), corresponding to GEO1_SV can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for El Salvador 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 El Salvador, Department 2007 [Level 1, GIS] 001 Ahuachapán 002 Santa Ana 003 Sonsonate 004 Chalatenango 005 La Libertad 006 San Salvador 007 Cuscatlán 008 La Paz 009 Cabañas 010 San Vicente 011 Usulután 012 San Miguel 013 Morazán 014 La Unión GEO1_SV2007 identifies the household's department within El Salvador in 2007. Departments are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_SV2007 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for El Salvador can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS El Salvador, Municipality 1992 - 2007 [Level 2; consistent boundaries, GIS] 222001001 Ahuachapán, San Lorenzo 222001002 Turín, El Refugio, Atiquizaya 222001003 San Francisco Menéndez 222001004 Tacuba 222001005 Jujutla 222001006 San Pedro Puxtla, Guaymango 222001007 Apaneca, Concepción de Ataco 222002001 Santa Ana, San Sebastián Salitrillo 222002002 Metapán, San Antonio Pajonal, Santiago de la Frontera, Santa Rosa Guachipilín, Masahuat, Texistepeque 222002003 Chalchuapa 222002004 Coatepeque 222002005 Candelaria de la Frontera, El Porvenir 222002006 El Congo 222003001 San Julián, Izalco 222003002 Nahulingo, Sonsonate 222003003 Acajutla 222003004 Nahuizalco 222003005 Armenia 222003006 Santa Isabel Ishuatán, Cuisnahuat, Caluco 222003007 San Antonio del Monte 222003008 Sonzacate 222003009 Juayúa 222003010 Santa Catarina Masahuat, Salcoatitán, Santo Domingo de Guzmán 222004001 Agua Caliente, La Palma, San Ignacio, Citalá, San Fernando, San Francisco Morazán, Dulce Nombre de María 222004002 El Paraíso, San Rafael, Santa Rita, Concepción Quezaltepeque, Ojos de Agua, Comalapa, La Laguna, El Carrizal 222004003 Nueva Concepción 222004004 Chalatenango 222004005 Nueva Trinidad, Las Vueltas, San Isidro Labrador, Cancasque, Potonico, San Miguel de Mercedes, San Antonio Los Ranchos, Azacualpa, San Luis del Carmen, San Francisco Lempa, San Antonio de la Cruz, Nombre de Jesús, Las Flores, Arcatao 222004006 La Reina, Tejutla 222005001 Nuevo Cuscatlán, Santa Tecla 222005002 Colón 222005003 Sacacoyo, Ciudad Arce 222005004 San Juan Opico 222005005 Quezaltepeque 222005006 Jicalapa, Tamanique, Chiltiupán, Teotepeque 222005007 La Libertad 222005008 Antiguo Cuscatlán 222005009 San Matías, San Pablo Tacachico 222005010 San José Villanueva, Huizúcar 222005011 Jayaque, Tepecoyo 222005012 Zaragoza 222005013 Comasagua, Talnique 222006001 San Salvador 222006002 Soyapango 222006003 Mejicanos 222006004 Apopa 222006005 Ciudad Delgado 222006006 Ilopango 222006007 Tonacatepeque 222006008 San Martín 222006009 Cuscatancingo 222006010 San Marcos 222006011 Rosario de Mora, Panchimalco 222006012 Santo Tomás, Santiago Texacuangos 222006013 Ayutuxtepeque 222006014 Aguilares, El Paisnal 222006015 Nejapa 222006016 Guazapa 222007001 San Bartolomé Perulapía, San Pedro Perulapán 222007002 Cojutepeque 222007003 Suchitoto, Tenancingo, San José Guayabal, Oratorio de Concepción, El Rosario 222007004 San Rafael Cedros, El Carmen 222007005 San Cristóbal, Candelaria, San Ramón, Santa Cruz Analquito 222007006 Santa Cruz Michapa, Monte San Juan 222008001 Zacatecoluca, San Luis la Herradura 222008002 El Rosario, Santiago Nonualco 222008003 Olocuilta, San Juan Talpa, Cuyultitán 222008004 San Juan Nonualco, San Rafael Obrajuelo 222008005 San Antonio Masahuat, Tapalhuaca, San Francisco Chinameca, San Juan Tepezontes, San Emigdio, San Miguel Tepezontes 222008006 San Pedro Masahuat 222008007 San Pedro Nonualco, Santa María Ostuma, Paraíso de Osorio, Jerusalén, Mercedes la Ceiba 222008008 San Luis Talpa 222009001 San Isidro, Jutiapa, Tejutepeque, Cinquera, Sensuntepeque, Victoria, Guacotecti, Dolores 222009002 Ilobasco 222010001 San Vicente 222010002 San Sebastián, Verapaz, Santo Domingo, San Lorenzo, Tepetitán, San Cayetano Istepeque, Guadalupe 222010003 Apastepeque, San Ildefonso, Santa Clara, San Esteban Catarina 222010004 Tecoluca 222011001 Santa Elena, Ozatlán, Santa María, Ereguayquín, Usulután, San Dionisio 222011002 San Agustín, Jiquilisco, San Francisco Javier, Puerto El Triunfo 222011003 Santiago de María, Jucuapa, Alegría 222011004 Estanzuelas, Nueva Granada, El Triunfo, San Buenaventura, Mercedes Umaña 222011005 Berlín, Tecapán, California 222011006 Concepción Batres, Jucuarán 222012001 Quelepa, San Miguel, San Rafael Oriente, El Tránsito, Uluazapa, Comacarán 222012002 Nueva Guadalupe, Chinameca, San Jorge 222012003 Lolotique, Moncagua 222012004 Sesori, Nuevo Edén de San Juan, San Gerardo, San Luis de la Reina, Chapeltique 222012005 Carolina, San Antonio, Ciudad Barrios 222012006 Chirilagua 222013001 Guatajiagua, Sensembra, Yamabal, San Carlos, El Divisadero, Jocoro 222013002 Cacaopera, San Fernando, Arambala, Perquín, Jocoaitique, Torola, El Rosario, Meanguera, Joateca 222013003 Corinto, Sociedad 222013004 Chilanga, San Isidro, San Simón, Gualococti 222013005 Lolotiquillo, Delicias de Concepción, Yoloaiquín, Oscicala 222013006 San Francisco Gotera 222014001 Anamorós, Nueva Esparta, Lislique, Polorós, Concepción de Oriente 222014002 Conchagua, Meanguera del Golfo 222014003 San Alejo, Intipucá, El Carmen 222014004 La Unión 222014005 Santa Rosa de Lima 222014006 Pasaquina, El Sauce 222014007 Yucuaiquín, Bolívar, San José, Yayantique GEO2_SV identifies the household's municipalities within El Salvador in all sample years. Municipalities are the second level administrative units of the country, after departments. GEO2_SV is spatially harmonized accounting for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO2_SV can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for El Salvador 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 El Salvador, Municipality 2007 [Level 2, GIS] 001001 Ahuachapán, San Lorenzo 001002 Turín, El Refugio, Atiquizaya 001003 San Francisco Menéndez 001004 Tacuba 001005 Jujutla 001006 San Pedro Puxtla, Guaymango 001007 Apaneca, Concepción de Ataco 002001 Santa Ana, San Sebastián Salitrillo 002002 Metapán, San Antonio Pajonal, Santiago de la Frontera, Santa Rosa Guachipilín, Masahuat, Texistepeque 002003 Chalchuapa 002004 Coatepeque 002005 Candelaria de la Frontera, El Porvenir 002006 El Congo 003001 San Julián, Izalco 003002 Nahulingo, Sonsonate 003003 Acajutla 003004 Nahuizalco 003005 Armenia 003006 Santa Isabel Ishuatán, Cuisnahuat, Caluco 003007 San Antonio del Monte 003008 Sonzacate 003009 Juayúa 003010 Santa Catarina Masahuat, Salcoatitán, Santo Domingo de Guzmán 004001 Agua Caliente, La Palma, San Ignacio, Citalá, San Fernando, San Francisco Morazán, Dulce Nombre de María 004002 El Paraíso, San Rafael, Santa Rita, Concepción Quezaltepeque, Ojos de Agua, Comalapa, La Laguna, El Carrizal 004003 Nueva Concepción 004004 Chalatenango 004005 Nueva Trinidad, Las Vueltas, San Isidro Labrador, Cancasque, Potonico, San Miguel de Mercedes, San Antonio los Ranchos, Azacualpa, San Luis del Carmen, San Francisco Lempa, San Antonio de la Cruz, Nombre de Jesús, Las Flores, Arcatao 004006 La Reina, Tejutla 005001 Nuevo Cuscatlán, Santa Tecla 005002 Colón 005003 Sacacoyo, Ciudad Arce 005004 San Juan Opico 005005 Quezaltepeque 005006 Jicalapa, Tamanique, Chiltiupán, Teotepeque 005007 La Libertad 005008 Antiguo Cuscatlán 005009 San Matías, San Pablo Tacachico 005010 San José Villanueva, Huizúcar 005011 Jayaque, Tepecoyo 005012 Zaragoza 005013 Comasagua, Talnique 006001 San Salvador 006002 Soyapango 006003 Mejicanos 006004 Apopa 006005 Ciudad Delgado 006006 Ilopango 006007 Tonacatepeque 006008 San Martín 006009 Cuscatancingo 006010 San Marcos 006011 Rosario de Mora, Panchimalco 006012 Santo Tomás, Santiago Texacuangos 006013 Ayutuxtepeque 006014 Aguilares, El Paisnal 006015 Nejapa 006016 Guazapa 007001 San Bartolomé Perulapia, San Pedro Perulapán 007002 Cojutepeque 007003 Suchitoto, Tenancingo, San José Guayabal, Oratorio de Concepción, El Rosario 007004 San Rafael Cedros, El Carmen 007005 San Cristóbal, Candelaria, San Ramón, Santa Cruz Analquito 007006 Santa Cruz Michapa, Monte San Juan 008001 Zacatecoluca, San Luis la Herradura 008002 El Rosario, Santiago Nonualco 008003 Olocuilta, San Juan Talpa, Cuyultitán 008004 San Juan Nonualco, San Rafael Obrajuelo 008005 San Antonio Masahuat, Tapalhuaca, San Francisco Chinameca, San Juan Tepezontes, San Emigdio, San Miguel Tepezontes 008006 San Pedro Masahuat 008007 San Pedro Nonualco, Santa María Ostuma, Paraíso de Osorio, Jerusalén, Mercedes la Ceiba 008008 San Luis Talpa 009001 San Isidro, Jutiapa, Tejutepeque, Cinquera, Sensuntepeque, Victoria, Guacotecti, Dolores 009002 Ilobasco 010001 San Vicente 010002 San Sebastián, Verapaz, Santo Domingo, San Lorenzo, Tepetitán, San Cayetano Istepeque, Guadalupe 010003 Apastepeque, San Ildefonso, Santa Clara, San Esteban Catarina 010004 Tecoluca 011001 Santa Elena, Ozatlán, Santa María, Ereguayquín, Usulután, San Dionisio 011002 San Agustín, Jiquilisco, San Francisco Javier, Puerto El Triunfo 011003 Santiago de María, Jucuapa, Alegría 011004 Estanzuelas, Nueva Granada, El Triunfo, San Buenaventura, Mercedes Umaña 011005 Berlín, Tecapán, California 011006 Concepción Batres, Jucuarán 012001 Quelepa, San Miguel, San Rafael Oriente, El Tránsito, Uluazapa, Comacarán 012002 Nueva Guadalupe, Chinameca, San Jorge 012003 Lolotique, Moncagua 012004 Sesori, Nuevo Edén de San Juan, San Gerardo, San Luis de la Reina, Chapeltique 012005 Carolina, San Antonio, Ciudad Barrios 012006 Chirilagua 013001 Guatajiagua, Sensembra, Yamabal, San Carlos, El Divisadero, Jocoro 013002 Cacaopera, San Fernando, Arambala, Perquín, Jocoaitique, Torola, El Rosario, Meanguera, Joateca 013003 Corinto, Sociedad 013004 Chilanga, San Isidro, San Simón, Gualococti 013005 Lolotiquillo, Delicias de Concepción, Yoloaiquín, Oscicala 013006 San Francisco Gotera 014001 Anamorós, Nueva Esparta, Lislique, Polorós, Concepción de Oriente 014002 Conchagua, Meanguera del Golfo 014003 San Alejo, Intipucá, El Carmen 014004 La Unión 014005 Santa Rosa de Lima 014006 Pasaquina, El Sauce 014007 Yucuaiquín, Bolívar, San José, Yayantique GEO2_SV2007 identifies the household's municipality within El Salvador in 2007. Municipalities are the second level administrative units of the country, after departments. A GIS map (in shapefile format), corresponding to GEO2_SV2007 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for El Salvador can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS Ownership of dwelling [general version] NIU (not in universe) 1 Owned 2 Not owned 9 Unknown OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. IPUMS Ownership of dwelling [detailed version] 000 NIU (not in universe) 100 Owned 110 Owned, already paid 120 Owned, still paying 130 Owned, constructed 140 Owned, inherited 190 Owned, other 191 Owned, house 192 Owned, condominium 193 Apartment proprietor 194 Shared ownership 200 Not owned 210 Renting, not specified 211 Renting, government 212 Renting, local authority 213 Renting, parastatal 214 Renting, private 215 Renting, private company 216 Renting, individual 217 Renting, collective 218 Renting, joint state and individual 219 Renting, public subsidized 220 Renting, private subsidized 221 Renting, co-tenant 222 Renting, relative of tenant 223 Renting, cooperative 224 Renting, with a job or business 225 Renting, loan-backed habitation 226 Renting, mixed contract 227 Furnished dwelling 228 Sharecropping 230 Subletting 231 Rent to own 239 Renting, other 240 Occupied de facto/squatting 250 Free/usufruct (no cash rent) 251 Free, provided by employer 252 Free, without work or services 253 Free, provided by family or friend 254 Free, private 255 Free, public 256 Free, condemned 257 Free, other 260 Endowment, Waqf (Egypt historical) 290 Not owned, other 999 Unknown OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. IPUMS Number of international migrants 00 No migrants 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 or more 98 Unknown 99 NIU (not in universe) INTMIG1 indicates the number of people from the household who traveled to another country to live and have not permanently returned. IPUMS Electricity NIU (not in universe) 1 Yes 2 No 9 Unknown ELECTRIC indicates whether the household had access to electricity. IPUMS Water supply 00 NIU (not in universe) 10 Yes, piped water 11 Piped inside dwelling 12 Piped, exclusively to this household 13 Piped, shared with other households 14 Piped outside the dwelling 15 Piped outside dwelling, in building 16 Piped within the building or plot of land 17 Piped outside the building or lot 18 Have access to public piped water 20 No piped water 99 Unknown WATSUP describes the physical means by which the housing unit receives its water. The primary distinction is whether or not the household had piped (running) water. IPUMS Sewage 00 NIU (not in universe) 10 Connected to sewage system or septic tank 11 Sewage system (public sewage disposal) 12 Septic tank (private sewage disposal) 20 Not connected to sewage disposal system 99 Unknown SEWAGE indicates whether the household has access to a sewage system or septic tank. IPUMS Cooking fuel 00 NIU (not in universe) 10 None 20 Electricity 30 Petroleum gas, unspecified 31 Gas -- piped/utility 32 Gas -- tanked or bottled 33 Propane 34 Liquefied petroleum gas 35 Gas -- piped and bottled 40 Petroleum liquid 41 Oil, kerosene, and other liquid fuels 42 Kerosene/paraffin 43 Kerosene or oil 44 Kerosene or gasoline 45 Gasoline 46 Cocinol 47 Diesel 50 Wood, coal, and other solid fuels 51 Wood and other plant fuels 52 Non-wood plant materials 53 Coal or charcoal 54 Charcoal 55 Coal 56 Wood or charcoal 60 Multiple fuels 61 Bottled gas and wood 62 Propane and electricity 63 Propane, kerosene, and electricity 64 Propane and kerosene 65 Kerosene and electrictiy 66 Other combinations 70 Other 71 Alcohol 72 Biogas 73 Discarded or waste material 74 Dung/manure 75 Other combined organic waste materials 76 Solar energy 77 Candle 99 Unknown/missing FUELCOOK indicates the predominant type of fuel or energy used for cooking. IPUMS Telephone availability NIU (not in universe) 1 No 2 Yes 9 Unknown/missing PHONE indicates the availability of a telephone in the dwelling. IPUMS Cellular phone availability NIU (not in universe) 1 Yes 2 No 9 Unknown CELL indicates the availability of a cellular phone in the household. IPUMS Internet access NIU (not in universe) 1 No 2 Yes 9 Unknown INTERNET indicates whether or not the household had an internet connection. IPUMS Trash disposal 00 NIU (not in universe) 10 Collected by a sanitation service 11 Collected directly from the household or dwelling 12 Collected indirectly from a garbage container or deposit 13 Collected by a sanitation service only 14 Collected by a sanitation service and disposed of in some other manner 20 Disposed of in some other manner 21 Burned or buried 22 Burned 23 Buried 24 Thrown into street, vacant land, or common area 25 Thrown into river, lake, ocean, lagoon, etc. 26 Thrown into canyon or gulley 27 Dumped in pit 28 Communal refuse dump 29 Own refuse dump 30 Authorized refuse dump 31 Illegal refuse dump 32 Other dumping 33 Outside 34 In the fields 35 Fed to animals 36 Composted 37 Heap 38 Garden 39 Other, none 99 Unknown/missing This variable indicates whether the household's waste or garbage is collected by a sanitation service or disposed of in some other manner. IPUMS Automobiles available No autos 1 1 auto 2 2 autos 3 3 autos 4 4 autos 5 5 autos 6 6+ autos 7 Have auto, number unspecified 8 Unknown 9 NIU (not in universe) AUTOS records whether a member of the household owned or had use of a vehicle and, in many samples, the number of such vehicles. IPUMS Computer NIU (not in universe) 1 No 2 Yes 9 Unknown/missing COMPUTER indicates whether the household had a personal computer. IPUMS Clothes washing machine NIU (not in universe) 1 No 2 Yes 3 Automatic or semi-automatic 4 Wringer or other non-automatic 9 Unknown/missing WASHER indicates whether the household had a clothes washing machine. IPUMS Refrigerator NIU (not in universe) 1 No 2 Yes 9 Unknown/missing REFRIG indicates whether the household had a refrigerator. IPUMS Television set 00 NIU (not in universe) 10 No 20 Yes, color or black-and-white not specified 21 1 television 22 2 televisions 23 3 televisions 24 4 televisions 25 5 televisions 26 6 televisions 27 7 televisions 28 8 televisions 29 9+ televisions 30 Yes, at least one color tv 31 1 color tv 32 2 color tvs 33 3+ televisions 40 Yes, black-and-white only 41 1 black-white tv 42 2 black-white tvs 43 3+ black-white tvs 99 Unknown/missing TV indicates whether the household had a television. IPUMS Videocassette recorder NIU (not in universe) 1 No 2 Yes 9 Unknown/missing VCR indicates whether the household had a videocassette recorder or similar device. IPUMS Number of rooms 00 Part of a room; no rooms 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) ROOMS indicates the number of rooms occupied by the housing unit. IPUMS Number of bedrooms 00 No bedrooms 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+ 98 Unknown 99 NIU (not in universe) BEDROOMS indicates the number of rooms available to members of the household for sleeping. IPUMS Kitchen or cooking facilities 00 NIU (not in universe) 10 No kitchen 11 Food is prepared in a non-kitchen room 13 Does not prepare food in the dwelling 20 Yes, have a kitchen 21 Kitchen located inside the dwelling 22 Indoor kitchen, exclusive use 23 Indoor kitchen, shared use 24 Exclusive use of kitchen (indoor/outdoor status not specified) 25 Shared use of kitchen with another household (indoor/outdoor status not specified) 26 Kitchen located outside the dwelling 27 Outdoor kitchen, exclusive use 28 Outdoor kitchen, shared use 99 Unknown/missing KITCHEN indicates whether the household had a kitchen, cooking facilities, or room dedicated to food preparation. IPUMS Toilet 00 NIU (not in universe) 10 No toilet 11 No flush toilet 20 Have toilet, type not specified 21 Flush toilet 22 Non-flush, latrine 23 Non-flush, other and unspecified 99 Unknown TOILET indicates whether the household had access to a toilet and, in most cases, whether it was a flush toilet or other type of installation. IPUMS Floor material 000 NIU (not in universe) 100 None/unfinished (earth) 110 Sand 120 Dung 200 Finished 201 Cement, tile, or brick 202 Cement 203 Concrete 204 Cement screed 205 Ceramic tile 206 Paving stone, cement tile 207 Stone 208 Brick 209 Brick or stone 210 Brick or cement 211 Block 212 Terrazzo 213 Wood 214 Palm, bamboo 215 Parquet 216 Parquet, tile, vinyl 217 Parquet, tile, marble 218 Ceramic, marble, granite 219 Ceramic, marble, tile, or vinyl 220 Marble 221 Mosaic 222 Tile 223 Tile, linoleum, ceramic, etc 224 Tile, cement 225 Tile, stone 226 Tile, stone, brick 227 Tile, stone, vinyl, brick 228 Tile, vinyl, brick 229 Tile, vinyl 230 Vinyl, linoleum, etc 231 Asphalt sheet, vinyl, etc 232 Synthetic, plastic 233 Cane 234 Carpet, rug 235 Scrap material 236 Other finished, n.e.c. 999 Unknown/missing FLOOR indicates the dwelling's predominant flooring material. IPUMS Wall or building material 000 NIU (not in universe) 100 No walls 200 Cardboard, scrap, and miscellaneous materials 201 Waste, scrap, or discarded material 202 Fabric or discarded material 203 Zinc, fabric, cardboard, tins, and waste material 204 Cardboard sheet 205 Plastic sheeting, cardboard 206 Makeshift, salvaged, or improvised materials 207 Reused materials 300 Wood 310 Rough wood 320 Wood, fibercement or plywood 330 Wood, formica, and other 340 Wood or bamboo 350 Wood or straw 400 Other plant-based materials 401 Plantain leaves and similar material 402 Bamboo or cane 403 Bamboo, sawali, cogon, nipa 404 Straw or bamboo 405 Grass, straw or reed 406 Reed, bamboo, or palm 407 Cane, palm leaves, logs 408 Palm leaves or palm planks 409 Bark, sticks, or cane 500 Masonry, stone, cement, adobe, metal, glass, and other fabricated materials (sometimes mixed with wood) 501 Brick, block, stone, or cement 502 Brick, stone, concrete 503 Brick, stone, or substitutes (dividing panels made of reinforced concrete) 504 Brick, stone, or substitutes (dividing panels made of wood) 505 Brick or tile 506 Brick or stone 507 Brick or cement block 508 Brick with plaster exterior 509 Brick without plaster exterior 510 Burnt or stabilized brick 511 Covered brick 512 Brick 513 Unburnt brick 514 Unburnt brick with cement 515 Unburnt brick with mud 516 Concrete 517 Landcrete, sandcrete 518 Cement blocks 519 Cement blocks or brick 520 Cement blocks or brick, unfinished 521 Cement and adobe bricks 522 Cement and stone block 523 Cement and tiles 524 Reinforced concrete, pre-cast concrete panels, or steel skeleton framed concrete 525 Concrete, reinforced concrete, blocks, panels 526 Fibercement 527 Adobe 528 Adobe walls with plaster exterior 529 Adobe walls without plaster exterior 530 Adobe with cement exterior 531 Wood and earth adobe 532 Wood and cement adobe 533 Mud or adobe 534 Pressed dirt 535 Clay 536 Coated clay/mud with sticks/cane 537 Clay or clay-covered sticks 538 Netted bamboo or cane with mud 539 Bundle of mud, straw, other materials 540 Mud with wood/wattle 541 Pole and mud 542 Mud with cement 543 Unfinished lathe and plaster, stucco, etc. 544 Stone 545 Hand-laid stone 546 Quarried stone 547 Cut stone and concrete 548 Cemented stone 549 Stone with clay 550 Blocks of light material 551 Prefabricated material 552 Asbestos 553 Metal or asbestos sheet 554 Metal or iron sheet 555 Metal or fibercement sheeting 556 Galvanized iron or aluminum 557 Tin 558 Glass 559 Cloth 560 Covintec panels 561 Mixed material 562 Mixed material: part wood; part concrete, brick, or stone 563 Wood plastered with clay, adobe, other materials; wood pressed panels; rolled mud bricks; etc. 564 Mixed material: wood or galvanized metal 570 Mainly permanent materials 600 Other material 601 Partition wall, lined with wood or steel 602 Partition wall, unlined 999 Unknown/missing This variable indicates the primary material used in the construction of the dwelling, particularly the dwelling's exterior walls. IPUMS Roof material 00 NIU (not in universe) 10 Masonry, concrete, clay tile, or tiles of unspecified type 11 Concrete or cement 12 Reinforced concrete (slab) 13 Cement or sheet metal 14 Tile, unspecified material 15 Clay tile 16 Tile or cement 17 Modern tiles, industrial 18 Traditional tiles, locally made 19 Tile or flat stone 20 Tile, unspecified or mixed materials 21 Fibercement or plastic 22 Fibercement or metal sheets 23 Asphalt or laminate cover 24 Tile, cement, asphalt 25 Asphalt tile 26 Slate or tile 27 Slate or asbestos 28 Asbestos 29 Adobe 30 Tiles or wood planks 31 Roofing shingles 32 Tar paper 33 Metal 34 Sheet metal 35 Zinc or tin 36 Tin 37 Sheet metal or other sheet material 38 Sheet metal, tile, slate 40 Wood and other plant materials 41 Wood 42 Wood, including bamboo 43 Bamboo 44 Cogon, nipa, anahaw 45 Thatch (straw, grass, leaves, palm, etc.) 46 Cane, wood, straw 47 Grass or straw 48 Papyrus 49 Banana leaves or fiber 50 Palm or makuti 51 Straw, bamboo, polythene 52 Wood with clay 53 Grass and mud 54 Rustic mat 60 Mud or earth 61 Clay 70 Cardboard, scrap, and miscellaneous materials 71 Discarded or scrap material 72 Cardboard 73 Plastic, tarpaulin 80 Other, unspecified 90 No roof 99 Unknown/missing This variable indicates the dwelling's predominant roofing material. IPUMS Number of deaths in household last year None 1 1 death 2 2 deaths 3 3 deaths 4 4 deaths 5 5 deaths 6 6 deaths 7 7 or more deaths 8 Unknown 9 NIU (not in universe) MORTNUM indicates the number of deaths in the household in the past year. IPUMS Any deaths in household last year 1 Yes 2 No 8 Unknown/missing 9 NIU (not in universe) ANYMORT indicates whether there were any deaths in the household in the past year. IPUMS Household classification 00 Vacant household 01 One-person household 02 Married/cohab couple, no children 03 Married/cohab couple with children 04 Single-parent family 05 Polygamous family 06 Extended family, relatives only 07 Composite household, family and non-relatives 08 Non-family household 09 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable HHTYPE is a constructed variable that describes the composition of households. HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ. IPUMS Number of families in household Vacant household 1 1 family 2 2 families 3 3 families 4 4 families 5 5 families 6 6 families 7 7 families 8 8 families 9 9 or more families NFAMS is a constructed variable that indicates the number of families within each household. Family membership is defined by FAMUNIT. A "family" is any group of persons related by blood, adoption, or marriage. An unrelated individual within the household is considered a separate family. Thus, a household consisting of a widow and a domestic employee contains two families; a household consisting of a large, multi-generation extended family with no persons unrelated to the head counts as a single family. NFAMS is constructed from information in RELATE (relationship to head) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). See those variable descriptions for more detail. IPUMS Number of married couples in household No married couples in household 1 1 couple 2 2 couples 3 3 couples 4 4 couples 5 5 couples 6 6 couples 7 7 couples 8 8 couples 9 9 or more couples NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household. NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household). IPUMS Number of mothers in household No mothers in household 1 1 mother 2 2 mothers 3 3 mothers 4 4 mothers 5 5 mothers 6 6 mothers 7 7 mothers 8 8 mothers 9 9 or more mothers in household NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household. NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household). IPUMS Number of fathers in household No fathers in household 1 1 father 2 2 fathers 3 3 fathers 4 4 fathers 5 5 fathers 6 6 fathers 7 7 fathers 8 8 fathers 9 9 or more fathers in household NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household. NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household). IPUMS Head's location in household HEADLOC gives the person number (PERNUM) of the head of household in samples in which persons are organized into households. HEADLOC is a 3-digit numeric variable. IPUMS Dwelling number El Salvador 2007: All households This variable indicates the dwelling number. This is a 7-digit numeric variable with 0 implied decimal places IPUMS Household number (within dwelling) El Salvador 2007: All households 1 1 2 2 3 3 4 4 5 5 6 6 7 7 This variable indicates the household number (within dwelling). IPUMS Number of households in dwelling El Salvador 2007: All households 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 10 10 This variable indicates the number of households in the dwelling. IPUMS Number of persons in dwelling El Salvador 2007: All households 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 This variable indicates the number of persons in the dwelling. IPUMS Number of persons in household El Salvador 2007: All households 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 This variable indicates the number of persons in the household. IPUMS Dwelling created by splitting apart a large dwelling or household El Salvador 2007: All households No problem 1 Yes: households within a large dwelling were split apart into separate dwellings 2 Yes: persons within a large household were split apart into separate dwellings This variable indicates whether the dwelling is created by splitting apart a large dwelling or household. IPUMS Urban/rural status El Salvador 2007: All households 1 Urban 2 Rural This variable indicates whether the household is located in urban or rural area. IPUMS Type of dwelling <svar a="all" v="SV07A038">1. The dwelling is:<br /><div class="i1">A) Private</div><br /><div class="i2">[] 01 Independent house [<span class="lang">casa independiente</span>]<br /> [] 02 Apartment<br /> [] 03 Room in a house<br /> [] 04 Room in a tenement [<span class="lang">mesón</span>]<br /> [] 05 Hut or shack<br /> [] 06 Improvised house<br /> [] 07 Premise not intended for human habitation<br /> [] 08 Other (mobile dwelling, tent, etc.)<br /> [] 09 Homeless (go to Chapter VI)</div><br /><div class="i1">B) Institutional</div><br /><div class="i2">[] 10 Home for children or orphanage<br />[] 11 Retirement home<br />[] 12 Jail/prison<br />[] 13 Guest house or student boarding house [<span class="lang">pupilaje</span>]<br />[] 14 Juvenile correctional facility<br />[] 15 Convent or boarding school<br />[] 16 Barracks<br />[] 17 Other</div><br />[If the respondent answers options 10-17, go to Chapter VI]<br /></svar> El Salvador 2007: All households 01 Detached house 02 Apartment 03 Room in a house 04 Room in an inn 05 Ranch or hut 06 Improvised house 07 Other, including not designed for human habitation 09 Homeless 10 Orphanage or home for children 11 Asylum/home for the elderly 12 Jail 14 Juvenile rehabilitation center 15 Convent or seminary 16 Barracks 17 Other This variable indicates the type of the dwelling. IPUMS Wall material <svar a="all" v="SV07A039">2. What material are most of the walls made of?<br /><div class="i1">[] 1 Concrete or mixed [<span class="lang">mixto</span>]<br />[] 2 Wattle and daub<br />[] 3 Adobe<br />[] 4 Wood<br />[] 5 Metal laminate [<span class="lang">lámina metálica</span>]<br />[] 6 Straw, palm or other vegetable matter<br />[] 7 Discarded materials<br />[] 8 Other</div><br /></svar> El Salvador 2007: Private households [discrepancies: none] 1 Concrete or mixed 2 Bahareque or mud 3 Adobe 4 Wood 5 Metal sheets 6 Straw, palm leaves or other vegetation 7 Waste materials 8 Other 9 NIU (not in universe) This variable indicates the wall material of the dwelling. IPUMS Roof material <svar a="all" v="SV07A040">3. What material is most of the roof made of?<br /><div class="i1">[] 1 Concrete slab<br />[] 2 Asbestos laminate<br />[] 3 Fiber-cement laminate<br />[] 4 Tile<br />[] 5 Metallic laminate<br />[] 6 Straw, palm or other vegetable matter<br />[] 7 Discarded materials<br />[] 8 Other</div><br /></svar> El Salvador 2007: Private households [discrepancies: none] 1 Concrete slabs 2 Asbestos sheet 3 Fiber cement sheets 4 Tiles 5 Metal sheet 6 Straw, palm leaves or other vegetation 7 Waste materials 8 Other 9 NIU (not in universe) This variable indicates the roof material of the dwelling. IPUMS Occupancy status <svar a="all" v="SV07A041">4. The dwelling is:<br /><div class="i1">A. Occupied</div><br /><div class="i2">[] 1 With people present<br />[] 2 With people absent (return to this dwelling)</div><br /><div class="i1">B. Vacant</div><br /><div class="i2">[] 3 Occasional use<br />[] 4 For rent<br />[] 5 For sale<br />[] 6 Under repair/construction<br />[] 7 Other reason</div><br />[End the interview if the respondent selects any of options 3-7]<br /></svar> El Salvador 2007: Private households [discrepancies: none] 1 Occupied with people present 2 Occupied with people absent 3 Unoccupied, occasional used 4 Unoccupied, for rent 5 Unoccupied, for sale 6 Unoccupied, under construction 7 Unoccupied, for another reason 9 NIU (not in universe) This variable indicates the occupancy status of the dwelling. IPUMS Floor material <svar a="all" v="SV07A042">5. What material is most of the floor made of?<br /><div class="i1">[] 1 Ceramic tile<br />[] 2 Cement slab<br />[] 3 Cement brick<br />[] 4 Clay brick<br />[] 5 Wood<br />[] 6 Dirt<br />[] 7 Other</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Tile 2 Cement slabs 3 Cement blocks 4 Mud bricks 5 Wood 6 Dirt 7 Other 9 NIU (not in universe) This variable indicates the floor material of the dwelling. IPUMS Shared food expenses <svar a="all" v="SV07A044">7. Do all the people who live in this dwelling share food expenses?<br /><div class="i1">[] 1 Yes (go to Chapter III)<br />[] 2 No</div><br /></svar></p> <p><svar a="all" v="SV07A045">8. Then how many households or groups of persons, including yours, have separate food expenses? Write the number /_/_/<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether food expenses are shared within the dwelling. IPUMS Total number of rooms <svar a="all" v="SV07A047">1. How many rooms does this household have, not including the bathroom, hallway, kitchen or garage? Number /_/_/<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11+ 99 NIU (not in universe) This variable indicates the total number of rooms within the household. IPUMS Total number of bedrooms <svar a="all" v="SV07A048">2. How many of the rooms are used exclusively as bedrooms? Number /_/_/<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 1 2 2 3 3 4 4 5 5 6 6 7 7+ 9 NIU (not in universe) This variable indicates the total number of bedrooms in the household. IPUMS Rooms used exclusively for cooking <svar a="all" v="SV07A049">3. Does this household have a room used only for cooking?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates the number of rooms used exclusively for cooking in the household. IPUMS Tenancy of the household <svar a="all" v="SV07A050">4. What is the ownership status [<span class="lang">forma de tenencia</span>] of the dwelling occupied by this household?<br /><div class="i1">[] 1 Own dwelling<br />[] 2 Own dwelling paid in installments to a public institution<br />[] 3 Own dwelling paid in installments to a private institution<br />[] 4 Own dwelling being paid in installments to NGOs<br />[] 5 Rented<br />[] 6 Occupied for free<br />[] 7 Other status</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Own 2 Own, paying in installments to public institutions 3 Own, paying in installments to private institutions 4 Own, paying in installments to NGOs 5 Rented 6 Free occupancy 7 Other tenancy 9 NIU (not in universe) This variable indicates the tenancy of the household. IPUMS Type of toilet service <svar a="all" v="SV07A051">5. What type of sanitary service is available?<br /><div class="i1">[] 1 Toilet connected to sewer<br />[] 2 Toilet connect to septic tank<br />[] 3 Latrine<br />[] 4 Fertilizing latrine<br />[] 5 Does not have (go to question 7)</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Toilet connected to sewer 2 Toilet connected to septic tank 3 Latrine 4 Composting toilet 5 Does not have toilet service 9 NIU (not in universe) This variable indicates the type of toilet used in the household. IPUMS Use of toilet service <svar a="all" v="SV07A052">6. Is the sanitary service:<br /><div class="i1">[] 1 Exclusively for use of the household<br />[] 2 Shared with other households</div><br /></svar> El Salvador 2007: Occupied private dwellings (with people present) that have toilet service [discrepancies: none] 1 Used exclusively by the household 2 Shared with other households 9 NIU (not in universe) This variable indicates the household's use of toilet service. IPUMS Disposal of wastewater <svar a="all" v="SV07A053">7. How is waste water [<span class="lang">aguas grises o servidas</span>] disposed of?<br /><div class="i1">[] 1 Sewage system<br />[] 2 Septic tank<br />[] 3 Sump hole<br />[] 4 Gully/stream, river or lake<br />[] 5 Street or outside<br />[] 6 Other</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Sewer 2 Septic tank 3 Well or drain 4 River, lake or waterfall 5 A street or outdoors 6 Other 9 NIU (not in universe) This variable indicates the disposal of wastewater in the household. IPUMS Source of water <svar a="all" v="SV07A054">8. What is the source of the water used by the household?<br /><div class="i1">[] 01 Pipes inside the dwelling<br />[] 02 Pipes outside the dwelling but on the property<br />[] 03 Neighbor's pipes<br />[] 04 Basin or public tap<br />[] 05 Public well<br />[] 06 Private well<br />[] 07 Truck, cart or tanker<br />[] 08 Spring, river or stream<br />[] 09 Rain water<br />[] 10 Other</div><br />[Go to question 10 if any of options 05-10 are circled]<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 01 Piping inside the dwelling 02 Piping outside the dwelling but within the property 03 Piping from a neighbor 04 Public stream or trough 05 Public well 06 Private well 07 Truck, cart or tank truck 08 Water hole, river or waterfall 09 Rainwater 10 Other 99 NIU (not in universe) This variable indicates the water source of the household. IPUMS Frequency of receiving water <svar a="all" v="SV07A055">9. How many days per week do you get water?<br /><div class="i1">A) Daily</div><br /><div class="i2">[] 1 More than four hours<br />[] 2 Fewer than four hours</div><br /><div class="i1">B) On some days</div><br /><div class="i2">[] 3 Every other day<br />[] 4 Every three days<br />[] 5 Once a week<br />[] 6 From time to time</div><br /></svar> El Salvador 2007: Occupied private dwellings with access to piped water [discrepancies: none] 1 Daily, more than four hours 2 Daily, fewer than four hours 3 Every other day 4 Every third day 5 Once a week 6 Once in a while 9 NIU (not in universe) This variable indicates the number of days of the week that water is available to the household. IPUMS Main fuel for cooking <svar a="all" v="SV07A056">10. What is the main fuel used for cooking?<br /><div class="i1">[] 1 Electricity<br />[] 2 Propane gas<br />[] 3 Kerosene<br />[] 4 Wood<br />[] 5 Wood charcoal<br />[] 6 Straw, palm<br />[] 7 Discarded material<br />[] 8 Other<br />[] 9 Do not cook</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 01 Electricity 02 Propane gas 03 Kerosene (gas) 04 Firewood 05 Charcoal 06 Straw, palm leaf 08 Other 09 Do not cook 99 NIU (not in universe) This variable indicates the household's main fuel for cooking. IPUMS Type of lighting <svar a="all" v="SV07A057">11. What type of lighting do you have?<br /><div class="i1">[] 1 Electricity<br />[] 2 Kerosene<br />[] 3 Candle<br />[] 4 Solar panel<br />[] 5 Car battery<br />[] 6 Other</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Electricity 2 Propane gas 3 Candle 4 Solar panel 5 Car battery 6 Other 9 NIU (not in universe) This variable indicates the household's type of lighting. IPUMS Trash disposal <svar a="all" v="SV07A058">12. How is trash disposed of?<br /><div class="i1">[] 1 Municipal service<br />[] 2 Private service<br />[] 3 Burned<br />[] 4 Buried<br />[] 5 Put in dumpsters/bins<br />[] 6 Thrown into street, ravine or empty lot<br />[] 7 Thrown into a river, lake or sea<br />[] 8 Other</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Municipal service 2 Private service 3 Burning 4 Burying 5 Deposited in a container 6 Thrown in the street, gully or vacant lot 7 Thrown in the river, lake or sea 8 Another form of disposal 9 NIU (not in universe) This variable indicates the trash disposal of the household. IPUMS Television <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A059">Television<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 1.9%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a television. IPUMS Telephone (landline) <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A060">Landline phone<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.3%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a telephone (landline). IPUMS Cell phone <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A061">Cell phone<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.2%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a cellphone. IPUMS Refrigerator <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A062">Refrigerator<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.0%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a refrigerator. IPUMS Washing machine <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A063">Washing machine<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.1%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a washing machine. IPUMS VCR <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A064">Video-cassette player<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.2%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a VCR. IPUMS Sound system <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A065">Sound equipment<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.2%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a sound system. IPUMS Microwave oven <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A066">Microwave oven<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.1%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a microwave oven. IPUMS Computer <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A067">Computer<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.1%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a computer. IPUMS Automobile <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A068">Auto<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.2%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has an automobile. IPUMS Motorcycle <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A069">Motorcycle<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.5%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has a motorcycle. IPUMS Cable service <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A070">Cable service<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.3%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has access to a cable service. IPUMS Internet service <svar v="SV07A059 SV07A060 SV07A061 SV07A062 SV07A063 SV07A064 SV07A065 SV07A066 SV07A067 SV07A068 SV07A069 SV07A070 SV07A071">13. Does this household have appliances and services that belong to it?<br /></svar></p> <p><svar a="all" v="SV07A071">Internet service<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.4%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household has access to internet service. IPUMS Make tortillas, clothing, furniture, etc. <svar a="all" v="SV07A072">14. Does any member of the household perform any economic activity within the dwelling, such as: <br />Making tortillas, bread, clothes, shoes, furniture, hammocks, crafts, etc.?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 2.6%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household makes tortillas, clothing, furniture, etc.. IPUMS Sell products or items <svar a="all" v="SV07A073">Selling products or articles (which they do not produce or make), such as rice, corn, beans or sorghum [<span class="lang">granos básicos</span>], soft drinks, clothes, shoes, etc.?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 3.2%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household sells products or items. IPUMS Offer services <svar a="all" v="SV07A074">Providing a service, such as radio, TV or refrigerator repair; medical service; beauty salon, etc.?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 3.7%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household offers services. IPUMS Principal activity: farming <svar a="all" v="SV07A075 SV07A076">15. Does any member of the household perform the following as his/her principal activity:<br />Growing rice, corn, beans or sorghum [<span class="lang">granos básicos</span>], vegetables, coffee, etc.?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br />Raising animals?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br />If at least one of the answers is "Yes", continue. If the answer to both questions is "No", go to Chapter IV.<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 3.0%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household's principal activity is farming. IPUMS Principal activity: raising animals <svar a="all" v="SV07A075 SV07A076">15. Does any member of the household perform the following as his/her principal activity:<br />Growing rice, corn, beans or sorghum [<span class="lang">granos básicos</span>], vegetables, coffee, etc.?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br />Raising animals?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br />If at least one of the answers is "Yes", continue. If the answer to both questions is "No", go to Chapter IV.<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: type I none; type II 3.0%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the household's principal activity is raising animals. IPUMS Tenancy of land used for farming or raising animals <svar a="all" v="SV07A077">16. Is the land you cultivate, or where you raise animals:<br /><div class="i1">[] 1 Your own<br />[] 2 Rented<br />[] 3 Other</div><br /></svar> El Salvador 2007: Occupied private dwellings with people present whose principal activity is farming or raising animals [discrepancies: type I trace; type II 0.7%] 1 Own 2 Rented 3 Other 8 Unknown 9 NIU (not in universe) This variable indicates the household's tenancy of land used for farming or raising animals. IPUMS Any deaths in the household <svar a="all" v="SV07A078 SV07A079 SV07A082">1. Did anyone in this household die in the past 12 months?<br />[] 1 Yes<br /><div class="i1">How many persons? /_/_/<br />Write the information related to each person who died in the following box.</div><br /> [] 2 No (go to question 2)<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether there is any death in the household. IPUMS Number of deaths in the last 12 months <svar a="all" v="SV07A078 SV07A079 SV07A082">1. Did anyone in this household die in the past 12 months?<br />[] 1 Yes<br /><div class="i1">How many persons? /_/_/<br />Write the information related to each person who died in the following box.</div><br /> [] 2 No (go to question 2)<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 1 2 2 3 3+ 9 NIU (not in universe) This variable indicates the number of deaths in the household in the last 12 months. IPUMS Any residents emigrated from the household <svar a="all" v=" SV07A080 SV07A081 SV07A083">2. Did any member of this household go live permanently in another country?<br />[] 1 Yes<br /><div class="i1">How many persons? /_/_/ Write the information related to each person in the box.</div><br />[] 2 No (go to Chapter VI -- Information about persons in the household)<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether any resident emigrated from the household. IPUMS Number of residents emigrated <svar a="all" v=" SV07A080 SV07A081 SV07A083">2. Did any member of this household go live permanently in another country?<br />[] 1 Yes<br /><div class="i1">How many persons? /_/_/ Write the information related to each person in the box.</div><br />[] 2 No (go to Chapter VI -- Information about persons in the household)<br /></svar> El Salvador 2007: Occupied private dwellings with people present [discrepancies: none] 1 1 2 2 3 3 4 4 5 5 6 6 9 NIU (not in universe) This variable indicates the number of residents emigrated from the household. IPUMS Total number of mortality records <svar a="all" v="SV07A078 SV07A079 SV07A082">1. Did anyone in this household die in the past 12 months?<br />[] 1 Yes<br /><div class="i1">How many persons? /_/_/<br />Write the information related to each person who died in the following box.</div><br /> [] 2 No (go to question 2)<br /></svar> El Salvador 2007: All households 1 1 2 2 3 3+ This variable indicates the total number of mortality records in the household. IPUMS Total number of migration records <svar a="all" v=" SV07A080 SV07A081 SV07A083">2. Did any member of this household go live permanently in another country?<br />[] 1 Yes<br /><div class="i1">How many persons? /_/_/ Write the information related to each person in the box.</div><br />[] 2 No (go to Chapter VI -- Information about persons in the household)<br /></svar> El Salvador 2007: All households 1 1 2 2 3 3 4 4 5 5 6 6 This variable indicates the total number of migration records in the household. IPUMS Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. IPUMS Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. IPUMS Mother's location in household MOMLOC is a constructed variable that indicates whether or not the person's mother lived in the same household and, if so, gives the person number of the mother (see PERNUM). MOMLOC makes it easy for researchers to link the characteristics of children and their (probable) mothers. The method by which probable child-mother links are identified is described in PARRULE. The general design of MOMLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of MOMLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: MOMLOC identifies social relationships (such as stepmother and adopted mother) as well as biological relationships. The variable STEPMOM is designed to identify some of these social relationships. To restrict MOMLOC to biological mothers, such as for own children fertility estimation, MOMLOC should be reset to zero when STEPMOM is greater than zero. MOMLOC is a 3-digit numeric variable. Codes0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother IPUMS Father's location in household POPLOC is a constructed variable that indicates whether or not the person's father lived in the same household and, if so, gives the person number of the father (see PERNUM). POPLOC makes it easy for researchers to link the characteristics of children and their (probable) fathers. The method by which probable child-father links are identified is described in PARRULE. The general design of POPLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of POPLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: POPLOC identifies social relationships (such as stepfather and adopted father) as well as biological relationships. The variable STEPPOP is designed to identify some of these social relationships. To restrict POPLOC to biological mothers, such as for own children fertility estimation, POPLOC should be reset to zero when STEPPOP is greater than zero. POPLOC is a 3-digit numeric variable. Codes0 = No father of this person present in the household. 1 or higher = The person number of this person's father IPUMS Spouse's location in household SPLOC is a constructed variable that indicates whether or not the person's spouse lived in the same household and, if so, gives the person number (PERNUM) of the spouse. SPLOC makes it easy for researchers to link the characteristics of (probable) spouses. The method by which probable spouse-spouse links are identified is described in SPRULE. The general design of SPLOC and other constructed variables is modeled on the methods developed for IPUMS-USA "Family Interrelationships", but the details vary significantly. For more details on the construction of SPLOC, see the Comparability section of SPRULE and this paper on IPUMSI family linking methodology. SPLOC is a 3-digit numeric variable. Codes0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse IPUMS Rule for linking parent 00 No parent of person in household 11 Link to head or spouse, unambiguous 12 Link to head or spouse, ambiguous 21 Child-Grandchild, within empirical child cap 22 Child-Grandchild, within constructed child cap 23 Child-Grandchild, exceeds child cap 31 Specified Other Relatives, within empirical child cap 32 Specified Other Relatives, within constructed child cap 33 Specified Other Relatives, exceeds child cap 41 Other Relatives, within empirical child cap 42 Other Relatives, within constructed child cap 51 Non-Relatives, within empirical child cap 52 Non-Relatives, within constructed child cap PARRULE describes the criteria by which the IPUMS International variables MOMLOC and POPLOC linked the person to a probable mother and/or father. IPUMS International establishes child-parent links according to five basic rules, and PARRULE gives the number of the rule that applied to the link in question. A link to any parent automatically generates a second link to that parent's spouse or partner, so only one rule is needed to describe both MOMLOC and POPLOC. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. IPUMS Rule for linking spouse 00 No spouse present 01 Rule 1: strong relationship pairing, couple adjacent 02 Rule 2: strong relationship pairing, couple not adjacent 03 Rule 3: weak relationship pairing, couple adjacent 04 Rule 4: weak relationship pairing, couple not adjacent 05 Rule 5: weak consensual union pairings 06 Rule 6: sample-specific rules (usually child-to-child) SPRULE explains the criteria by which the IPUMS-International variable SPLOC linked the person to his/her probable spouse. IPUMS International establishes spouse-spouse links according to five basic rules, and SPRULE gives the number of the rule that applied to the link in question. A sixth rule identifies sample-specific linking procedures only imposed in selected instances. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. IPUMS Probable stepmother Biological mother or no mother present 1 Mother has no children born or surviving 2 Child reports mother is deceased 3 Explicitly identified step relationship 4 Mother reports no children in the home 5 Age difference implausible 6 Child exceeds known fertility of mother STEPMOM indicates whether a person's mother, as identified by MOMLOC, was most probably not the person's biological mother. Non-zero values of STEPMOM explain why it is probable that the person's mother was a step- or adopted mother. A value of 0 indicates no likely stepmother because (1) the mother identified in MOMLOC was probably the biological mother or (2) there is no mother of this person present in the household. The codes for STEPMOM are as follows: 0 = Biological mother or no mother of this person present in household. 1 = Mother has no children born or surviving. 2 = Child reports mother is deceased. 3 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner, stepchild/child-in-law). 4 = Mother reports no children in the home. 5 = Age difference between mother and child was less than 12 or greater than 54 years. 6 = Child exceeds known fertility of mother. In cases where more than one criterion for a likely stepmother is met, STEPMOM will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepmothers and adopted mothers in the population that cannot be identified with information available in the censuses. Therefore, STEPMOM will always under-represent their actual number in the population. IPUMS Probable stepfather Biological father or no father present 1 Child reports father is deceased 2 Explicitly identified step relationship 3 Age difference implausible 4 Spouse of mother 5 Identified as adopted 6 Surname difference -- male child or never-married female STEPPOP indicates whether a person's father, as identified by POPLOC, was most probably not the person's biological father. Non-zero values of STEPPOP explain why it is probable that the person's father was a step- or adopted father. A value of 0 indicates no likely stepfather because (1) the father identified in POPLOC was probably the biological father or (2) there is no father of this person present in the household. The codes for STEPPOP are as follows: 0 = Biological father or no father of this person present in household. 1 = Child reports father is deceased. 2 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner; stepchild/child-in-law). 3 = Age difference between father and child was less than 12 or greater than 54 years. In cases where more than one criterion for a likely stepfather is met, STEPPOP will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepfathers and adopted fathers in the population that cannot be identified with information available in the censuses. Therefore, STEPPOP will always under-represent their actual number in the population. IPUMS Man with more than one wife linked No more than one wife linked via SPLOC 1 More than one wife linked via SPLOC POLYMAL indicates if a man had more than one wife linked to him in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The point of POLYMAL is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. IPUMS Woman is second or higher order wife Person is not the 2nd or higher order wife linked via SPLOC 1 Person is the 2nd or higher order wife linked via SPLOC POLY2ND indicates if a woman was the second or higher order wife linked to a husband in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The variable does not suggest the actual marital order of wives, only their relative positions in the person order of the household as it was enumerated. The point of POLY2ND is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. IPUMS Family unit membership FAMUNIT is a constructed variable indicating to which family within the household a person belongs. All persons related to the household head receive a 1 (see RELATE). Each secondary family or secondary individual receives a higher code. For purposes of FAMUNIT, secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). FAMUNIT is a 4-digit numeric variable. CodesIf there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on. IPUMS Number of own family members in household 0001 1 family member present 0002 2 family members present 0003 3 family members present 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 or more persons FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them. FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membership). The primary family is defined as all persons related to the head in the RELATE variable. Secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). IPUMS Number of own children in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children in household NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Number of own children under age 5 in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more own children under age 5 in household 98 One or more children have unknown age NCHLT5 provides a count of the person's own children under age five living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Age of eldest own child in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. ELDCH is top-coded at age 50 or older. IPUMS Age of youngest own child in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. YNGCH is top-coded at age 50 or older. IPUMS Relationship to household head [general version] 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Relationship to household head [detailed version] 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling's sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder, or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Age 000 Less than 1 year 001 1 year 002 2 years 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100+ 999 Not reported/missing AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. IPUMS Age, grouped into intervals 01 0 to 4 02 5 to 9 03 10 to 14 04 15 to 19 05 0 to 5 06 6 to 10 07 10 to 15 08 11 to 14 09 15 to 17 10 16 to 19 11 18 to 24 12 20 to 24 13 25 to 29 14 30 to 34 15 35 to 39 16 40 to 44 17 45 to 49 18 50 to 54 19 55 to 59 20 60 to 64 21 65 to 69 22 70 to 74 23 75 to 79 24 80 to 84 25 85+ 98 Unknown AGE2 gives computed years of age grouped into intervals. IPUMS Sex 1 Male 2 Female 9 Unknown SEX reports the sex (gender) of the respondent. IPUMS Marital status [general version] NIU (not in universe) 1 Single/never married 2 Married/in union 3 Separated/divorced/spouse absent 4 Widowed 9 Unknown/missing MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. IPUMS Marital status [detailed version] 000 NIU (not in universe) 100 Single/never married 110 Engaged 111 Never married and never cohabited 200 Married or consensual union 210 Married, formally 211 Married, civil 212 Married, religious 213 Married, civil and religious 214 Married, civil or religious 215 Married, traditional/customary 216 Married, monogamous 217 Married, polygamous 219 Married, spouse absent (historical samples) 220 Consensual union 300 Separated/divorced/spouse absent 310 Separated or divorced 320 Separated or annulled 330 Separated 331 Separated legally 332 Separated de facto 333 Separated from marriage 334 Separated from consensual union 335 Separated from consensual union or marriage 340 Annulled 350 Divorced 400 Widowed 410 Widowed or divorced 411 Widowed from consensual union or marriage 412 Widowed from marriage 413 Widowed from consensual union 420 Widowed, divorced, or separated 999 Unknown/missing MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. IPUMS Consensual union 1 Yes, in consensual union 2 No, married 8 Unknown 9 NIU (not in universe) CONSENS indicates whether the respondent was in a consensual union -- a de facto marriage. IPUMS Year of birth 0000 NIU (not in universe) 1628 1628 1629 1629 1630 1630 1631 1631 1634 1634 1635 1635 1636 1636 1637 1637 1638 1638 1639 1639 1640 1640 1641 1641 1642 1642 1643 1643 1644 1644 1645 1645 1646 1646 1647 1647 1648 1648 1649 1649 1650 1650 1651 1651 1652 1652 1653 1653 1654 1654 1655 1655 1656 1656 1657 1657 1658 1658 1659 1659 1660 1660 1661 1661 1662 1662 1663 1663 1664 1664 1665 1665 1666 1666 1667 1667 1668 1668 1669 1669 1670 1670 1671 1671 1672 1672 1673 1673 1674 1674 1675 1675 1676 1676 1677 1677 1678 1678 1679 1679 1680 1680 1681 1681 1682 1682 1683 1683 1684 1684 1685 1685 1686 1686 1687 1687 1688 1688 1689 1689 1690 1690 1691 1691 1692 1692 1693 1693 1694 1694 1695 1695 1696 1696 1697 1697 1698 1698 1699 1699 1700 1700 1701 1701 1702 1702 1703 1703 1704 1704 1705 1705 1706 1706 1707 1707 1708 1708 1709 1709 1710 1710 1711 1711 1712 1712 1713 1713 1714 1714 1715 1715 1716 1716 1717 1717 1718 1718 1719 1719 1720 1720 1721 1721 1722 1722 1723 1723 1724 1724 1725 1725 1726 1726 1727 1727 1728 1728 1729 1729 1730 1730 1731 1731 1732 1732 1733 1733 1734 1734 1735 1735 1736 1736 1737 1737 1738 1738 1739 1739 1740 1740 1741 1741 1742 1742 1743 1743 1744 1744 1745 1745 1746 1746 1747 1747 1748 1748 1749 1749 1750 1750 1751 1751 1752 1752 1753 1753 1754 1754 1755 1755 1756 1756 1757 1757 1758 1758 1759 1759 1760 1760 1761 1761 1762 1762 1763 1763 1764 1764 1765 1765 1766 1766 1767 1767 1768 1768 1769 1769 1770 1770 1771 1771 1772 1772 1773 1773 1774 1774 1775 1775 1776 1776 1777 1777 1778 1778 1779 1779 1780 1780 1781 1781 1782 1782 1783 1783 1784 1784 1785 1785 1786 1786 1787 1787 1788 1788 1789 1789 1790 1790 1791 1791 1792 1792 1793 1793 1794 1794 1795 1795 1796 1796 1797 1797 1798 1798 1799 1799 1800 1800 1801 1801 1802 1802 1803 1803 1804 1804 1805 1805 1806 1806 1807 1807 1808 1808 1809 1809 1810 1810 1811 1811 1812 1812 1813 1813 1814 1814 1815 1815 1816 1816 1817 1817 1818 1818 1819 1819 1820 1820 1821 1821 1822 1822 1823 1823 1824 1824 1825 1825 1826 1826 1827 1827 1828 1828 1829 1829 1830 1830 1831 1831 1832 1832 1833 1833 1834 1834 1835 1835 1836 1836 1837 1837 1838 1838 1839 1839 1840 1840 1841 1841 1842 1842 1843 1843 1844 1844 1845 1845 1846 1846 1847 1847 1848 1848 1849 1849 1850 1850 1851 1851 1852 1852 1853 1853 1854 1854 1855 1855 1856 1856 1857 1857 1858 1858 1859 1859 1860 1860 1861 1861 1862 1862 1863 1863 1864 1864 1865 1865 1866 1866 1867 1867 1868 1868 1869 1869 1870 1870 1871 1871 1872 1872 1873 1873 1874 1874 1875 1875 1876 1876 1877 1877 1878 1878 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9999 Unknown BIRTHYR gives the person's year of birth. IPUMS Month of birth 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) BIRTHMO indicates the person's month of birth. IPUMS Children ever born 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living. IPUMS Children surviving 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHSURV reports the number of children born to a woman who were still living at the time of the census. IPUMS Number of female children ever born 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORNF indicates the number of female children ever born to a woman. Only live births are counted. IPUMS Number of male children ever born 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORNM indicates the number of male children ever born to a woman. Only live births are counted. IPUMS Month of last birth 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) LASTBMO indicates the month of birth of the last child born by the respondent. The data refer to live births. IPUMS Year of last birth 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 Unknown 9999 NIU (not in universe) LASTBYR indicates the year of birth of the last child born by the respondent. The data refer to live births. IPUMS Number of children dead 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown/missing 99 NIU (not in universe) CHDEAD reports how many of the children ever born to a woman were no longer living at the time of the census. Women were to consider all live births by all fathers; they were to exclude still births. IPUMS Mortality status of last birth NIU (not in universe) 1 Alive 2 Dead 9 Unknown LASTBMORT indicates the mortality status of the last child born to a woman. There is no constraint on how long ago the child may have been born. Only live births are considered. 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 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) HOMECHILD indicates the number of surviving biological children living in the household with their mother (the respondent) at the time of the census. 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 Year of immigration 0000 NIU (not in universe) 1790 1790 1800 1800 1801 1801 1802 1802 1803 1803 1804 1804 1805 1805 1806 1806 1807 1807 1808 1808 1809 1809 1810 1810 1811 1811 1812 1812 1813 1813 1814 1814 1815 1815 1816 1816 1817 1817 1818 1818 1819 1819 1820 1820 1821 1821 1822 1822 1823 1823 1824 1824 1825 1825 1826 1826 1827 1827 1828 1828 1829 1829 1830 1830 1831 1831 1832 1832 1833 1833 1834 1834 1835 1835 1836 1836 1837 1837 1838 1838 1839 1839 1840 1840 1841 1841 1842 1842 1843 1843 1844 1844 1845 1845 1846 1846 1847 1847 1848 1848 1849 1849 1850 1850 1851 1851 1852 1852 1853 1853 1854 1854 1855 1855 1856 1856 1857 1857 1858 1858 1859 1859 1860 1860 1861 1861 1862 1862 1863 1863 1864 1864 1865 1865 1866 1866 1867 1867 1868 1868 1869 1869 1870 1870 1871 1871 1872 1872 1873 1873 1874 1874 1875 1875 1876 1876 1877 1877 1878 1878 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 In transit 9999 Unknown YRIMM indicates the calendar year that a foreign-born person came to live in the country in which they were enumerated. IPUMS Years since immigrated 00 0 (within previous year) 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97+ 98 Unknown 99 NIU (not in universe) YRSIMM indicates the number of years since a foreign-born person immigrated to their country of enumeration. IPUMS Years since immigrated, categorized 1 Less than 1 year 2 1 to 4 years 3 5 to 9 years 4 10 or more years 8 Unknown 9 NIU (not in universe) YRSIMM2 indicates the number of years since a foreign-born person immigrated to the country. The number of years is grouped into intervals. IPUMS Department of birth, El Salvador 01 Ahuachapán 02 Santa Ana 03 Sonsonate 04 Chalatenango 05 La Libertad 06 San Salvador 07 Cuscatlán 08 La Paz 09 Cabañas 10 San Vicente 11 Usulután 12 San Miguel 13 Morazán 14 La Unión 99 Abroad BPLSV indicates the person's department of birth within El Salvador. 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 Member of an indigenous group NIU (not in universe) 1 Yes 2 No 9 Unknown INDIG indicates whether the person belonged to an indigenous group. IPUMS Speaks English 1 Yes 2 No 7 Does not speak 8 Unknown 9 NIU (not in universe) SPEAKENG indicates whether the respondent could speak English or if English was the respondent's language of literacy. IPUMS Non-Spanish language spoken, El Salvador 1 English 2 German 3 French 4 Portugese 5 Italian 6 Other 9 Speaks only Spanish LANGSV indicates the respondent's ability to speak a language other than Spanish. 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 Educational attainment, international recode [general version] NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS Educational attainment, international recode [detailed version] 000 NIU (not in universe) 100 Less than primary completed (n.s.) 110 No schooling 120 Some primary completed 130 Primary (4 yrs) completed 211 Primary (5 yrs) completed 212 Primary (6 yrs) completed 221 Lower secondary general completed 222 Lower secondary technical completed 311 Secondary, general track completed 312 Some college completed 320 Secondary or post-secondary technical completed 321 Secondary, technical track completed 322 Post-secondary technical education 400 University completed 999 Unknown/missing EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS Years of schooling 00 None or pre-school 01 1 year 02 2 years 03 3 years 04 4 years 05 5 years 06 6 years 07 7 years 08 8 years 09 9 years 10 10 years 11 11 years 12 12 years 13 13 years 14 14 years 15 15 years 16 16 years 17 17 years 18 18 years or more 90 Not specified 91 Some primary 92 Some technical after primary 93 Some secondary 94 Some tertiary 95 Adult literacy 96 Special education 98 Unknown/missing 99 NIU (not in universe) YRSCHOOL indicates the highest grade/level of schooling the person had completed, in years. Only formal schooling is counted. YRSCHOOL accounts for the number of years of study, regardless of the track or kind of study. Information on degree and/or technical track is available in EDATTAIN. Years of schooling for Israel, categorized into intervals, are given in YRSCHOOL2. Users should pay close attention to the top-codes in each sample, as discussed in the comparability section. IPUMS Educational attainment, El Salvador 000 NIU (not in universe) 100 None 110 Preschool 111 Preschool, grade 1 112 Preschool, grade 2 113 Preschool, grade 3 114 Preschool, grade unknown 200 Primary education 201 Primary education, grade 1 202 Primary education, grade 2 203 Primary education, grade 3 204 Primary education, grade 4 205 Primary education, grade 5 206 Primary education, grade 6 207 Primary education, grade 7 208 Primary education, grade 8 209 Primary education, grade 9 210 Primary education, grade unknown 300 Secondary education 301 Secondary education, grade 1 302 Secondary education, grade 2 303 Secondary education, grade 3 304 Secondary education, grade 4 310 Vocational course (after 6th grade primary) 311 Vocational course (after 6th grade primary), year 1 or 2 312 Vocational course (after 6th grade primary), year 3 400 Post-secondary non-university 401 Post-secondary non-university, year 1 402 Post-secondary non-university, year 2 403 Post-secondary non-university, year 3 404 Post-secondary non-university, year 4 405 Post-secondary non-university, year 5 406 Post-secondary non-university, year 6 407 Post-secondary non-university, year 7 408 Post-secondary non-university, year 8 409 Post-secondary non-university, year unknown 410 Technical university 411 Technical university, year 1 412 Technical university, year 2 413 Technical university, year 3 420 University 421 University, year 1 422 University, year 2 423 University, year 3 424 University, year 4 425 University, year 5 426 University, year 6 427 University, year 7 428 University, year 8 429 University, year unknown 430 Masters 431 Masters, year 1 432 Masters, year 2 433 Masters, year 3 440 Doctorate 998 Unknown EDUCSV indicates the person's educational attainment in El Salvador in terms of the level of schooling completed. IPUMS Activity status (employment status) [general version] NIU (not in universe) 1 Employed 2 Unemployed 3 Inactive 9 Unknown/missing EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". IPUMS Activity status (employment status) [detailed version] 000 NIU (not in universe) 100 Employed, not specified 110 At work 111 At work, and 'student' 112 At work, and 'housework' 113 At work, and 'seeking work' 114 At work, and 'retired' 115 At work, and 'no work' 116 At work, and other situation 117 At work, family holding, not specified 118 At work, family holding, not agricultural 119 At work, family holding, agricultural 120 Have job, not at work in reference period 130 Armed forces 131 Armed forces, at work 132 Armed forces, not at work in reference period 133 Military trainee 140 Marginally employed 200 Unemployed, not specified 201 Unemployed 6 or more months 202 Worked fewer than 6 months, permanent job 203 Worked fewer than 6 months, temporary job 210 Unemployed, experienced worker 220 Unemployed, new worker 230 No work available 240 Inactive unemployed 300 Inactive (not in labor force) 310 Housework 320 Unable to work, disabled or health reasons 321 Permanent disability 322 Temporary illness 323 Disabled or imprisoned 330 In school 340 Retirees and living on rent 341 Living on rents 342 Living on rents or pension 343 Retirees/pensioners 344 Retired 345 Pensioner 346 Non-retirement pension 347 Disability pension 348 Retired without benefits 350 Elderly 351 Elderly or disabled 360 Institutionalized 361 Prisoner 370 Intermittent worker 371 Not working, seasonal worker 372 Not working, occasional worker 380 Other income recipient 390 Inactive, other reasons 391 Too young to work 392 Dependent 999 Unknown/missing EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 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, unrecoded OCC records the person's primary occupation, classified according to the system used by the respective national census office at the time. For someone with more than one job, the primary occupation is usually the one in which the person spent the most time or earned the most money, although this may not have been explicit in the instructions for a specific census. To ensure confidentiality, very small occupations are recoded to a residual category indicating the persons had an occupation, but the job title is not identified. The number of cases recoded should be too small to affect analyses. OCC is a 4-digit numeric variable. Some samples use fewer than 4 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. CodesArgentina 1970 - Spanish Argentina 1980 - Spanish Argentina 1991 - Spanish Argentina 2001 - Spanish Armenia 2011 Austria 1971-2001 - German Belarus 1999 - Russian Belarus 2009 Benin 1979 Benin 1992 Benin 2002 Benin 2013 Bolivia 1976 Bolivia 1992 Bolivia 2001 Bolivia 2012 Botswana 1981 Botswana 1991 Botswana 2001 Botswana 2011 Brazil 1960 - Portuguese Brazil 1970 - Portuguese Brazil 1980 - Portuguese Brazil 1991 - Portuguese Brazil 2000 - Portuguese Brazil 2010 Burkina Faso 1985 Burkina Faso 1996 Cambodia 1998 Cambodia 2004 Cambodia 2008 Cambodia 2013 Cambodia 2019 Cameroon 1976 Cameroon 2005 Canada 1971 Canada 1981-1991 Canada 2001 Canada 2011 Chile 1960 Chile 1970 Chile 1982 Chile 1992 Chile 2002 China 1982 China 1990 China 2000 Colombia 1964 Colombia 1973 - Spanish Costa Rica 1973 Costa Rica 1984 Costa Rica 2000 Costa Rica 2011 Cote d'Ivoire 1988 Cote d'Ivoire 1998 Cuba 2002 Cuba 2012 Denmark 1845 Denmark 1880 Denmark 1885 Dominican Republic 1960 Dominican Republic 1970 Dominican Republic 1981 Dominican Republic 2002 Dominican Republic 2010 Ecuador 1962 Ecuador 1974 Ecuador 1982 Ecuador 1990 Ecuador 2001 Ecuador 2010 Egypt 1986 Egypt 2006 El Salvador 1992 El Salvador 2007 Ethiopia 1984 Ethiopia 1994 Fiji 1976 Fiji 1986 Fiji 1996 Fiji 2007 Fiji 2014 Finland 2010 France 1962-1990 - French France 1999 France 2006 France 2011 Germany 1970 Germany 1981 Germany 1987 Ghana 1984 Ghana 2000 Ghana 2010 Greece 1971-1991 - Greek Greece 2001 - Greek Greece 2011 Guatemala 1964 Guatemala 1973 Guatemala 1981 Guatemala 1994 Guatemala 2002 Guinea 1983 Guinea 1996 Guinea 2014 Haiti 1982 Haiti 2003 Honduras 1961 Honduras 1974 Honduras 1988 Honduras 2001 Hungary 1970-1990 Hungary 2001 Hungary 2011 India 1983-2004 India 2009 Indonesia 1971 Indonesia 1976 Indonesia 1980 Indonesia 1985 Indonesia 1990 Indonesia 1995 Indonesia 2005 Iran 2006 Iran 2011 Iraq 1997 Ireland 1901 Ireland 1911 Ireland 1971 Ireland 1981 Ireland 1986 Ireland 1991 Ireland 1996 Ireland 2002 Ireland 2006 Ireland 2011 Ireland 2016 Israel 1972 Israel 1983 Israel 1995 Israel 2008 Italy 2001 Italy 2011 Italy Surveys 2011-2020 Jamaica 1982 Jamaica 1991 Jamaica 2001 Jordan 2004 Kenya 1989 Kyrgyz Republic 1999 Laos 1995 Lesotho 1996 Lesotho 2006 Liberia 1974 Liberia 2008 Malawi 1987 Malawi 1998 Malawi 2008 Malaysia 1970 Malaysia 1980-1991 Malaysia 2000 Mali 1987 Mali 1998 Mali 2009 Mauritius 1990 Mauritius 2000 Mauritius 2011 Mexico 1960 - Spanish Mexico 1970 - Spanish Mexico 1990 - Spanish Mexico 1995 - Spanish Mexico 2000 - Spanish Mexico 2010 Mexico 2015 Mexico 2020 Mexico Surveys 2005-2020 Mongolia 2000 Morocco 1982 Morocco 1994 Morocco 2004 Morocco 2014 Mozambique 1997 Mozambique 2007 Myanmar 2014 Nepal 2001 Nepal 2011 Netherlands 1960 Netherlands 1971 Netherlands 2001 Netherlands 2011 Nicaragua 1971 Nicaragua 1995 Nicaragua 2005 Nigeria 2008 Nigeria 2009 Nigeria 2010 Pakistan 1973 Palestine 1997 Palestine 2007 Palestine 2017 Panama 1960 - Spanish Panama 1970 - Spanish Panama 1980 - Spanish Panama 1990 - Spanish Panama 2000 - Spanish Panama 2010 Papua New Guinea 1980 Papua New Guinea 1990 Papua New Guinea 2000 Paraguay 1962 Paraguay 1972 Paraguay 1982 Paraguay 1992 Paraguay 2002 Peru 1993 Peru 2007 Peru 2017 Philippines 1990 Philippines 2000 Philippines 2010 Poland 1978 Poland 1988 Poland 2002 Portugal 1981 - Portuguese Portugal 1991 - Portuguese Portugal 2001 - Portuguese Portugal 2011 Puerto Rico 1970 Puerto Rico 1980 Puerto Rico 1990 Puerto Rico 2000-2005 Puerto Rico 2010 Puerto Rico 2015 Puerto Rico 2020 Romania 1977 Romania 1992 Romania 2002 Romania 2011 Rwanda 2002 - French Rwanda 2012 Saint Lucia 1991 Senegal 1988 Senegal 2002 Senegal 2013 Slovak Republic 1991 Slovak Republic 2001 Slovak Republic 2011 Sierra Leone 2004 Sierra Leone 2015 Slovenia 2002 South Africa 1996 South Africa 2001 South Africa 2007 South Sudan 2008 Spain 1981 - Spanish Spain 1991 - Spanish Spain 2001 - Spanish Spain 2011 Spain Surveys 2005-2020 Sudan 2008 Suriname 2004 Suriname 2012 Switzerland 1970 Switzerland 1980 Switzerland 1990 Switzerland 2000 Switzerland 2011 Tanzania 1988 Tanzania 2002 Tanzania 2012 Thailand 1970 Thailand 1980 Thailand 1990 Thailand 2000 Togo 1960 Togo 1970 Togo 2010 Trinidad and Tobago 1990 Trinidad and Tobago 2000 Trinidad and Tobago 2011 Turkey 1985 Turkey 1990 Turkey 2000 Uganda 1991 Uganda 2002 Uganda 2014 United Kingdom 1961 United Kingdom 1971 United Kingdom 1991 United Kingdom 2001 United States 1960 United States 1970 United States 1980 United States 1990 United States 2000-2005 United States 2010 United States 2015 United States 2020 Uruguay 1963 Uruguay 1975 Uruguay 1996 Uruguay 2006 Venezuela 1981 Venezuela 1990 Venezuela 2001 - Spanish Vietnam 1989 Vietnam 1999 Vietnam 2009 Vietnam 2019 Zambia 1990 Zambia 2000 Zambia 2010 Zimbabwe 2012 IPUMS Occupation, ISCO-1988, 3-digit 010 Armed forces 111 Legislators 112 Senior government officials 113 Traditional chiefs and heads of villages 114 Senior officials of special-interest organizations 121 Directors and chief executives 122 Production and operations department managers 123 Other department managers 131 General managers 199 Legislators, senior officials and managers not elsewhere classified 211 Physicists, chemists and related professionals 212 Mathematicians, statisticians and related professionals 213 Computing professionals 214 Architects, engineers and related professionals 221 Life science professionals 222 Health professionals (except nursing) 223 Nursing and midwifery professionals 231 College, university and higher education teaching professionals 232 Secondary education teaching professionals 233 Primary and pre-primary education teaching professionals 234 Special education teaching professionals 235 Other teaching professionals 241 Business professionals 242 Legal professionals 243 Archivists, librarians and related information professionals 244 Social science and related professionals 245 Writers and creative or performing artists 246 Religious professionals 299 Professionals no elsewhere classified 311 Physical and engineering science technicians 312 Computer associate professionals 313 Optical and electronic equipment operators 314 Ship and aircraft controllers and technicians 315 Safety and quality inspectors 321 Life science technicians and related associate professionals 322 Modern health associate professionals (except nursing) 323 Nursing and midwifery associate professionals 324 Traditional medicine practitioners and faith healers 331 Primary education teaching associate professionals 332 Pre-primary education teaching associate professionals 333 Special education teaching associate professionals 334 Other teaching associate professionals 341 Finance and sales associate professionals 342 Business services agents and trade brokers 343 Administrative associate professionals 344 Customs, tax and related government associate professionals 345 Police inspectors and detectives 346 Social work associate professionals 347 Artistic, entertainment and sports associate professionals 348 Religious associate professionals 399 Technicians and associate professionals not elsewhere classified 411 Secretaries and keyboard-operating clerks 412 Numerical clerks 413 Material-recording and transport clerks 414 Library, mail and related clerks 419 Other office clerks 421 Cashiers, tellers and related clerks 422 Client information clerks 499 Clerks not elsewhere classified 511 Travel attendants and related workers 512 Housekeeping and restaurant services workers 513 Personal care and related workers 514 Other personal services workers 515 Astrologers, fortune-tellers and related workers 516 Protective services workers 521 Fashion and other models 522 Shop salespersons and demonstrators 523 Stall and market salespersons 599 Service workers and shop and market sales workers not elsewhere classified 611 Market gardeners and crop growers 612 Market-oriented animal producers and related workers 613 Market-oriented crop and animal producers 614 Forestry and related workers 615 Fishery workers, hunters and trappers 621 Subsistence agricultural and fishery workers 699 Skilled agricultural and fishery workers not elsewhere classified 711 Miners, shotfirers, stone cutters and carvers 712 Building frame and related trades workers 713 Building finishers and related trades workers 714 Painters, building structure cleaners and related trades workers 721 Metal moulders, welders, sheet-metal workers, structural- metal preparers, and related trades workers 722 Blacksmiths, tool-makers and related trades workers 723 Machinery mechanics and fitters 724 Electrical and electronic equipment mechanics and fitters 731 Precision workers in metal and related materials 732 Potters, glass-makers and related trades workers 733 Handicraft workers in wood, textile, leather and related materials 734 Printing and related trades workers 741 Food processing and related trades workers 742 Wood treaters, cabinet-makers and related trades workers 743 Textile, garment and related trades workers 744 Pelt, leather and shoemaking trades workers 799 Craft and related trade workers not elsewhere classified 811 Mining- and mineral-processing-plant operators 812 Metal-processing-plant operators 813 Glass, ceramics and related plant operators 814 Wood-processing- and papermaking-plant operators 815 Chemical-processing-plant operators 816 Power-production and related plant operators 817 Automated-assembly-line and industrial-robot operators 821 Metal- and mineral-products machine operators 822 Chemical-products machine operators 823 Rubber- and plastic-products machine operators 824 Wood-products machine operators 825 Printing-, binding- and paper-products machine operators 826 Textile-, fur- and leather-products machine operators 827 Food and related products machine operators 828 Assemblers 829 Other machine operators and assemblers 831 Locomotive-engine drivers and related workers 832 Motor-vehicle drivers 833 Agricultural and other mobile-plant operators 834 Ships' deck crews and related workers 899 Other plant and machine operaters and assemblers not elsewhere classified 911 Street vendors and related workers 912 Shoe cleaning and other street services elementary occupations 913 Domestic and related helpers, cleaners and launderers 914 Building caretakers, window and related cleaners 915 Messengers, porters, doorkeepers and related workers 916 Garbage collectors and related labourers 921 Agricultural, fishery and related labourers 931 Mining and construction labourers 932 Manufacturing labourers 933 Transport labourers and freight handlers 989 Elementary occupations not elsewhere classified 990 Other workers, not elsewhere classified 998 Unknown 999 NIU (not in universe) ISCO88A provides the 3-digit occupation code for the respondent using the ISCO-1988 occupation classification. IPUMS Industry, general recode 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. IPUMS Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. CodesArgentina 1970 - Spanish Argentina 1980 - Spanish Argentina 1991 - Spanish Argentina 2001 - Spanish Armenia 2001 Armenia 2011 Austria 1971-2001 - German Austria 2011 Bangladesh 1991 Bangladesh 2001 Bangladesh 2011 Belarus 2009 Benin 1979 Benin 1992 Benin 2002 Benin 2013 Bolivia 1976 Bolivia 1992 Bolivia 2001 Bolivia 2012 Botswana 1981 Botswana 1991 Botswana 2001 Botswana 2011 Brazil 1960 - Portuguese Brazil 1970 - Portuguese Brazil 1980 - Portuguese Brazil 1991 - Portuguese Brazil 2000 - Portuguese Brazil 2010 Burkina Faso 1996 Cambodia 1998 Cambodia 2004 Cambodia 2008 Cambodia 2013 Cambodia 2019 Cameroon 2005 Canada 1971 Canada 1981 Canada 1991-2001 Canada 2011 Chile 1960 Chile 1970 Chile 1982 Chile 1992 Chile 2002 Chile 2017 China 1982 China 1990 China 2000 Colombia 1964 - Spanish Colombia 1973 - Spanish Colombia 1993 - Spanish Colombia 2005 - Spanish Costa Rica 1963 Costa Rica 1973 Costa Rica 1984 Costa Rica 2000 Costa Rica 2011 Cote d’Ivoire 1988 Cote d’Ivoire 1998 Cuba 2002 Cuba 2012 Dominican Republic 1960 Dominican Republic 1970 Dominican Republic 1981 Dominican Republic 2002 Dominican Republic 2010 Ecuador 1962 Ecuador 1982 Ecuador 1990 Ecuador 2001 Ecuador 2010 Egypt 1986 Egypt 1996 Egypt 2006 El Salvador 1992 El Salvador 2007 Ethiopia 1984 Ethiopia 1994 Fiji 1966 Fiji 1976 Fiji 1986 Fiji 1996 Fiji 2007 Fiji 2014 Finland 2010 France 1962-1968 - French France 1975-1982 - French France 1990 - French France 1999 France 2006 France 2011 Germany 1970 Germany 1971 Germany 1981 Germany 1987 Ghana 1984 Ghana 2000 Ghana 2010 Greece 1971 Greece 1981 Greece 1991-2001 Greece 2011 Guatemala 1964 Guatemala 1973 Guatemala 1981 Guatemala 1994 Guatemala 2002 Guinea 1983 Guinea 2014 Haiti 1971 Haiti 1982 Haiti 2003 Honduras 1961 Honduras 1974 Honduras 2001 Hungary 2001 Hungary 2011 India 1983 India 1987 India 1993 India 1999 India 2004 India 2009 Indonesia 1971 Indonesia 1976 Indonesia 1980 Indonesia 1985 Indonesia 1990 Indonesia 1995 Indonesia 2000 Indonesia 2005 Indonesia 2010 Iran 2006 Iran 2011 Iraq 1997 Ireland 1971 Ireland 1981 Ireland 1986 Ireland 1991 Ireland 1996 Ireland 2002 Ireland 2006 Ireland 2011 Ireland 2016 Israel 1972 Israel 1983 Israel 1995 Israel 2008 Italy 2001 Italy 2011 Italy Surveys 2011-2013 Italy Surveys 2014-2020 Jamaica 1982 Jamaica 1991 Jamaica 2001 Jordan 2004 Kyrgyz Republic 1999 Kyrgyz Republic 2009 Laos 1995 Laos 2005 Laos 2015 Lesotho 2006 Liberia 1974 Liberia 2008 Malawi 1987 Malawi 1998 Malawi 2008 Malaysia 1970 Malaysia 1980-1991 Malaysia 2000 Mali 1987 Mali 1998 Mali 2009 Mauritius 1990 Mauritius 2000 Mauritius 2011 Mexico 1960 - Spanish Mexico 1970 - Spanish Mexico 1990 - Spanish Mexico 1995 - Spanish Mexico 2000 - Spanish Mexico 2010 Mexico 2015 Mexico 2020 Mexico surveys 2005-2019 Morocco 1982 Morocco 1994 Morocco 2004 Morocco 2014 Mozambique 1997 Mozambique 2007 Myanmar 2014 Nepal 2001 Nepal 2011 Netherlands 1960 Netherlands 1971 Netherlands 2001 Netherlands 2011 Nicaragua 1971 Nicaragua 1995 Nicaragua 2005 Nigeria 2006 Nigeria 2007 Nigeria 2008 Nigeria 2009 Nigeria 2010 Pakistan 1973 Palestine 1997 Palestine 2007 Palestine 2017 Panama 1960 - Spanish Panama 1970-1980 - Spanish Panama 1990-2000 - Spanish Panama 2010 Papua New Guinea 1980 Papua New Guinea 2000 Paraguay 1962 Paraguay 1972 Paraguay 1982 Paraguay 1992 Paraguay 2002 Peru 1993 Peru 2007 Peru 2017 Philippines 1990 Philippines 1995 Philippines 2000 Philippines 2010 Poland 1978 Poland 2002 Portugal 1981 - Portuguese Portugal 1991-2001 - Portuguese Portugal 2011 Puerto Rico 1970-2005 Puerto Rico 2010 Puerto Rico 2015 Puerto Rico 2020 Romania 1977 Romania 1992 Romania 2002 Romania 2011 Rwanda 2002 - French Rwanda 2012 Saint Lucia 1991 Senegal 1988 Senegal 2013 Sierra Leone 2004 South Africa 1996 South Africa 2001-2007 South Sudan 2008 Spain 1981 - Spanish Spain 1991 - Spanish Spain 2001 - Spanish Spain 2011 Spain Surveys 2005-2020 Sudan 2008 Suriname 2004 Suriname 2012 Switzerland 1970-2000 Switzerland 2011 Tanzania 2002 Tanzania 2012 Thailand 1970 Thailand 1980 Thailand 1990 Thailand 2000 Togo 1970 Togo 2010 Trinidad and Tobago 1980 Trinidad and Tobago 1990 Trinidad and Tobago 2000 Turkey 1985 Turkey 1990 Turkey 2000 Uganda 2002 United Kingdom 1961 United Kingdom 1971 United Kingdom 1991 United Kingdom 2001 United States 1960 United States 1970 United States 1980 United States 1990 United States 2000-2005 United States 2010 United States 2015 United States 2020 Uruguay 1963 Uruguay 1985 Uruguay 1996 Uruguay 2006 Venezuela 1981 Venezuela 1990 Venezuela 2001 - Spanish Vietnam 1989 Vietnam 1999 Vietnam 2009 Vietnam 2019 Zambia 1990 Zambia 2000 Zambia 2010 IPUMS Status in employment (class of worker) [general version] NIU (not in universe) 1 Self-employed 2 Wage/salary worker 3 Unpaid worker 4 Other 9 Unknown/missing CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. IPUMS Status in employment (class of worker) [detailed version] 000 NIU (not in universe) 100 Self-employed 101 Self-employed, unincorporated 102 Self-employed, incorporated 110 Employer 111 Sharecropper, employer 120 Working on own account 121 Own account, agriculture 122 Domestic worker, self-employed 123 Subsistence worker, own consumption 124 Own account, other 125 Own account, without temporary/unpaid help 126 Own account, with temporary/unpaid help 130 Member of cooperative 140 Sharecropper 141 Sharecropper, self-employed 142 Sharecropper, employee 150 Kibbutz member 199 Self-employed, not specified 200 Wage/salary worker 201 Management 202 Non-management 203 White collar (non-manual) 204 Blue collar (manual) 205 White or blue collar 206 Day laborer 207 Employee, with a permanent job 208 Employee, occasional, temporary, contract 209 Employee without legal contract 210 Wage/salary worker, private employer 211 Apprentice 212 Religious worker 213 Wage/salary worker, non-profit, NGO 214 White collar, private 215 Blue collar, private 216 Paid family worker 217 Cooperative employee 220 Wage/salary worker, government 221 Federal, government employee 222 State government employee 223 Local government employee 224 White collar, public 225 Blue collar, public 226 Public companies 227 Civil servants, local collectives 230 Domestic worker (work for private household) 240 Seasonal migrant 241 Seasonal migrant, no broker 242 Seasonal migrant, uses broker 250 Other wage and salary 251 Canal zone/commission employee 252 Government employment/training program 253 Mixed state/private enterprise/parastatal 254 Government public work program 255 State enterprise employee 256 Coordinated and continuous collaboration job 300 Unpaid worker 310 Unpaid family worker 320 Apprentice, unpaid or unspecified 330 Trainee 340 Apprentice or trainee 350 Works for others without wage 400 Other 999 Unknown/missing CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. IPUMS Sector of employment 00 NIU (not in universe) 10 Public 20 Private 21 Private, not elsewhere classified 22 Individual/family enterprise, and self-employed 23 Foreign 30 Mixed: public-private or parastatal 40 Collective or cooperative 50 Foreign government or non-governmental organization 60 Other, unspecified 61 Canal zone 62 Faith-based organization 63 Informal sector 99 Unknown EMPSECT indicates the economic sector in which the person was employed. Economic sector is defined in terms of ownership or control of the enterprise in which the person worked. IPUMS Hours worked per week 000 0 hours 001 1 hour 002 2 hours 003 3 hours 004 4 hours 005 5 hours 006 6 hours 007 7 hours 008 8 hours 009 9 hours 010 10 hours 011 11 hours 012 12 hours 013 13 hours 014 14 hours 015 15 hours 016 16 hours 017 17 hours 018 18 hours 019 19 hours 020 20 hours 021 21 hours 022 22 hours 023 23 hours 024 24 hours 025 25 hours 026 26 hours 027 27 hours 028 28 hours 029 29 hours 030 30 hours 031 31 hours 032 32 hours 033 33 hours 034 34 hours 035 35 hours 036 36 hours 037 37 hours 038 38 hours 039 39 hours 040 40 hours 041 41 hours 042 42 hours 043 43 hours 044 44 hours 045 45 hours 046 46 hours 047 47 hours 048 48 hours 049 49 hours 050 50 hours 051 51 hours 052 52 hours 053 53 hours 054 54 hours 055 55 hours 056 56 hours 057 57 hours 058 58 hours 059 59 hours 060 60 hours 061 61 hours 062 62 hours 063 63 hours 064 64 hours 065 65 hours 066 66 hours 067 67 hours 068 68 hours 069 69 hours 070 70 hours 071 71 hours 072 72 hours 073 73 hours 074 74 hours 075 75 hours 076 76 hours 077 77 hours 078 78 hours 079 79 hours 080 80 hours 081 81 hours 082 82 hours 083 83 hours 084 84 hours 085 85 hours 086 86 hours 087 87 hours 088 88 hours 089 89 hours 090 90 hours 091 91 hours 092 92 hours 093 93 hours 094 94 hours 095 95 hours 096 96 hours 097 97 hours 098 98 hours 099 99 hours 100 100 hours 101 101 hours 102 102 hours 103 103 hours 104 104 hours 105 105 hours 106 106 hours 107 107 hours 108 108 hours 109 109 hours 110 110 hours 111 111 hours 112 112 hours 113 113 hours 114 114 hours 115 115 hours 116 116 hours 117 117 hours 118 118 hours 119 119 hours 120 120 hours 121 121 hours 122 122 hours 123 123 hours 124 124 hours 125 125 hours 126 126 hours 127 127 hours 128 128 hours 129 129 hours 130 130 hours 131 131 hours 132 132 hours 133 133 hours 134 134 hours 135 135 hours 136 136 hours 137 137 hours 138 138 hours 139 139 hours 140 140+ hours 998 Unknown 999 NIU (not in universe) HRSWORK1 indicates the number of hours the respondent worked per week at all jobs. IPUMS Hours worked per week, categorized None 1 1 to 14 hours (except tt1980, tt1990 and tt2000) 2 15 to 29 hours (except de1970, ps2017, tt1980, tt1990, tt2000, and ve1971) 3 30 to 39 hours (except de1970, ps2017, tt1980, tt1990, tt2000, and ve1971) 4 40-48 hours (except il1972, tt1980, tt1990, and tt2000) 5 49 hours or more (except il1972 and tt2000) 8 Unknown 9 NIU (not in universe) HRSWORK2 indicates the number of hours the respondent worked per week at all jobs, categorized into intervals. IPUMS Actual hours worked per week 000 0 hours 001 1 hour 002 2 hours 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100 101 101 102 102 103 103 104 104 105 105 106 106 107 107 108 108 109 109 110 110 111 111 112 112 113 113 114 114 115 115 116 116 117 117 118 118 119 119 120 120 121 121 122 122 123 123 124 124 125 125 126 126 127 127 128 128 129 129 130 130 131 131 132 132 133 133 134 134 135 135 136 136 137 137 138 138 139 139 140 140+ hours 998 Unknown 999 NIU (not in universe) HRSACTUAL1 indicates the actual number of hours the respondent worked per week at all jobs.ss IPUMS Actual hours worked per week, categorized None 1 1 to 14 hours (except tt1980, tt1990, and tt2000) 2 15 to 29 hours (except ps2017, tt1980, tt1990, tt2000, and ve1971) 3 30 to 39 hours (except ps2017, tt1980, tt1990, tt2000, and ve1971) 4 40 to 48 hours (except tt1980, tt1990, and tt2000) 5 49 hours or more (except tt2000) 8 Unknown 9 NIU (not in universe) HRSACTUAL2 indicates the actual number of hours the respondent worked per week at all jobs, categorized into intervals. IPUMS Migration status, previous residence 00 NIU (not in universe) 10 Same major administrative unit 11 Same major, same minor administrative unit 12 Same major, different minor administrative unit 20 Different major administrative unit 30 Abroad 98 Response suppressed 99 Not reported/missing/unknown MIGRATEP indicates whether the person's most recent move (if any) was between minor administrative units, major units, or countries. IPUMS Country of previous residence 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12100 Sao Tome and Principe 12999 Middle Africa, n.s. 13000 Northern Africa 13010 Algeria 13020 Egypt/United Arab Rep. 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13990 Northern Africa, n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15150 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15160 Sierra Leone 15170 Togo 19999 Africa, 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 and the Grenadines 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21999 Caribbean, 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, 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 23990 South America, n.s. 23991 Central and Latin America 24000 North America 24010 Bermuda 24020 Canada 24030 Greenland 24040 Saint Pierre and Miquelon 24050 United States 24051 U.S. Outlying Areas and Territories 24999 U.S.A, Canada, Mexico 29999 Americas, 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 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33061 Malaysia and Singapore 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34060 Iraq 34070 Israel 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34190 Middle East, not specified 34191 Arabia 34199 Gulf countries 39999 Asia, n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Albania/Bulgaria/Romania 41030 Czech Republic 41031 Czechoslovakia/Yugoslavia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41999 Eastern Europe, n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42110 Sweden 42120 United Kingdom 42199 Scandinavia 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Serbia and Montenegro 43999 Southern Europe, n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44021 Belgium/Luxemburg 44022 Benelux (Belgium/Netherlands/Luxemburg) 44030 France 44040 Germany 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 49990 Europe, n.s. 49991 Central and Eastern Europe 49992 European Union 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51021 New Zealand/New Guinea 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) 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53999 Micronesia, n.e.c. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Samoa 54060 Tokelau 54070 Tonga 54080 Tuvalu 54090 Wallis and Futuna Isls. 59999 Oceania, n.s. 60000 Other 60010 Europe, Australia, New Zealand 60020 Asia and Oceania, n.s. 90000 Non-migrants (International) 99998 Response suppressed 99999 Unknown MIGCTRYP indicates the country of previous residence of international migrants. Persons who never lived abroad are coded to the "non-migrant" category. IPUMS 1st subnational geographic level of previous residence, world [consistent boundaries over time] 051901 Yerevan [Province: Armenia] 051902 Aragatsotn [Province: Armenia] 051903 Ararat [Province: Armenia] 051904 Armavir [Province: Armenia] 051905 Gegharkunik [Province: Armenia] 051906 Lori [Province: Armenia] 051907 Kotayk [Province: Armenia] 051908 Shirak [Province: Armenia] 051909 Syunik [Province: Armenia] 051910 Vayots Dzor [Province: Armenia] 051911 Tavush [Province: Armenia] 051912 Nagorno-Karabagh [Province: Armenia] 051997 Foreign country [Province: Armenia] 051998 Unknown [Province: Armenia] 051999 NIU (not in universe) [Province: Armenia] 112001 Brest [Region: Belarus] 112002 Vitebsk [Region: Belarus] 112003 Gomel [Region: Belarus] 112004 Grodno [Region: Belarus] 112006 Minsk, Minsk City [Region: Belarus] 112007 Mogilev [Region: Belarus] 112097 Foreign country [Region: Belarus] 112098 Unknown [Region: Belarus] 112099 NIU (not in universe) [Region: Belarus] 204001 Alibori [Department: Benin] 204002 Atacora [Department: Benin] 204003 Atlantique [Department: Benin] 204004 Borgou [Department: Benin] 204005 Collines [Department: Benin] 204006 Couffo [Department: Benin] 204007 Donga [Department: Benin] 204008 Littoral [Department: Benin] 204009 Mono [Department: Benin] 204010 Oueme [Department: Benin] 204011 Plateau [Department: Benin] 204012 Zou [Department: Benin] 204097 Abroad [Department: Benin] 204098 Unknown [Department: Benin] 204099 NIU (not in universe) [Department: Benin] 076011 Rondônia [State: Brazil] 076012 Acre [State: Brazil] 076013 Amazonas [State: Brazil] 076014 Roraima [State: Brazil] 076015 Pará [State: Brazil] 076016 Amapá [State: Brazil] 076021 Maranhão [State: Brazil] 076022 Piauí [State: Brazil] 076023 Ceará [State: Brazil] 076024 Rio Grande do Norte [State: Brazil] 076025 Paraíba [State: Brazil] 076026 Pernambuco, Arquipelago de Fernando de Noronha [State: Brazil] 076027 Alagoas [State: Brazil] 076028 Sergipe [State: Brazil] 076029 Bahia [State: Brazil] 076031 Minas Gerais [State: Brazil] 076032 Espírito Santo [State: Brazil] 076033 Rio de Janeiro, Guanabara [State: Brazil] 076035 São Paulo [State: Brazil] 076036 Serra dos Aimorés [State: Brazil] 076041 Paraná [State: Brazil] 076042 Santa Catarina [State: Brazil] 076043 Rio Grande do Sul [State: Brazil] 076051 Mato Grosso do Sul, Mato Grosso [State: Brazil] 076052 Goiás, Tocantins [State: Brazil] 076053 Distrito Federal [State: Brazil] 076054 Brazil, unspecified [State: Brazil] 076097 Abroad [State: Brazil] 076098 Unknown [State: Brazil] 076099 NIU (not in universe) [State: Brazil] 116001 Banteay Meanchey [Province: Cambodia] 116002 Battambang [Province: Cambodia] 116003 Kampong Cham, Tbong Khmum [Province: Cambodia] 116004 Kampong Chhnang [Province: Cambodia] 116005 Kampong Speu [Province: Cambodia] 116006 Kampong Thom [Province: Cambodia] 116007 Kampot [Province: Cambodia] 116008 Phnom Penh, Kandal [Province: Cambodia] 116009 Koh Kong, Preah Sihanouk [Province: Cambodia] 116010 Kratie [Province: Cambodia] 116011 Mondul Kiri [Province: Cambodia] 116013 Preah Vihear [Province: Cambodia] 116014 Prey Veng [Province: Cambodia] 116015 Pursat [Province: Cambodia] 116016 Ratanak Kiri [Province: Cambodia] 116017 Siem Reap, Otdar Meanchey [Province: Cambodia] 116019 Stung Treng [Province: Cambodia] 116020 Svay Rieng [Province: Cambodia] 116021 Takeo [Province: Cambodia] 116023 Kep [Province: Cambodia] 116024 Pailin [Province: Cambodia] 116097 Foreign country [Province: Cambodia] 116098 Unknown [Province: Cambodia] 116099 NIU (not in universe) [Province: Cambodia] 120002 Centre, Sud [Province: Cameroon] 120003 Est [Province: Cameroon] 120004 Nord, Adamoua, Extrème Nord [Province: Cameroon] 120005 Littoral [Province: Cameroon] 120007 Nord Ouest [Province: Cameroon] 120008 Ouest [Province: Cameroon] 120010 Sud Ouest [Province: Cameroon] 120096 Cameroon - unknown arrondissement [Province: Cameroon] 120097 Foreign country [Province: Cameroon] 120098 Unknown [Province: Cameroon] 120099 NIU (not in universe) [Province: Cameroon] 152001 Tarapaca [Province: Chile] 152002 Antofagasta [Province: Chile] 152003 Atacama [Province: Chile] 152004 Coquimbo [Province: Chile] 152005 Aconcagua [Province: Chile] 152006 Valparaíso [Province: Chile] 152007 Santiago [Province: Chile] 152008 O'Higgins [Province: Chile] 152009 Colchagua [Province: Chile] 152010 Curicó [Province: Chile] 152011 Talca [Province: Chile] 152012 Maule [Province: Chile] 152013 Linares [Province: Chile] 152014 Ñuble [Province: Chile] 152015 Concepción [Province: Chile] 152016 Arauco [Province: Chile] 152017 Bío Bío [Province: Chile] 152018 Malleco [Province: Chile] 152019 Cautín [Province: Chile] 152020 Valdivia [Province: Chile] 152021 Osorno [Province: Chile] 152022 Llanquihue [Province: Chile] 152023 Chiloé [Province: Chile] 152024 Aysén [Province: Chile] 152025 Magallanes [Province: Chile] 152097 Foreign country [Province: Chile] 152098 Unknown [Province: Chile] 152099 NIU (not in universe) [Province: Chile] 170005 Antioquia [Department: Colombia] 170008 Atlántico [Department: Colombia] 170011 Bogotá D.C., Cundinamarca [Department: Colombia] 170013 Bolívar, Sucre [Department: Colombia] 170015 Boyacá, Casanare [Department: Colombia] 170018 Caquetá [Department: Colombia] 170019 Cauca [Department: Colombia] 170023 Córdoba [Department: Colombia] 170027 Chocó [Department: Colombia] 170041 Huila [Department: Colombia] 170044 La Guajira [Department: Colombia] 170050 Meta [Department: Colombia] 170052 Nariño [Department: Colombia] 170054 Cesar, Norte De Santander, Magdalena [Department: Colombia] 170066 Caldas, Quindío, Risaralda [Department: Colombia] 170068 Santander [Department: Colombia] 170073 Tolima [Department: Colombia] 170076 Valle Del Cauca [Department: Colombia] 170081 Arauca [Department: Colombia] 170086 Putumayo [Department: Colombia] 170088 Archipiélago De San Andrés Y Providencia [Department: Colombia] 170095 Amazonas, Guaviare, Vaupés, Vichada, Guainía [Department: Colombia] 170097 Abroad [Department: Colombia] 170098 Unknown [Department: Colombia] 188001 San José [Province: Costa Rica] 188002 Alajuela [Province: Costa Rica] 188003 Cartago [Province: Costa Rica] 188004 Heredia [Province: Costa Rica] 188005 Guanacaste [Province: Costa Rica] 188006 Puntarenas [Province: Costa Rica] 188007 Limón [Province: Costa Rica] 188097 Foreign country [Province: Costa Rica] 188098 Unknown [Province: Costa Rica] 192021 Pinar del Río, Artemisa, Mayabeque [Province: Cuba] 192023 La Habana [Province: Cuba] 192025 Matanzas [Province: Cuba] 192026 Villa Clara [Province: Cuba] 192027 Cienfuegos [Province: Cuba] 192028 Sancti Spíritus [Province: Cuba] 192029 Ciego de Ávila [Province: Cuba] 192030 Camagüey [Province: Cuba] 192031 Las Tunas [Province: Cuba] 192032 Holguín [Province: Cuba] 192033 Granma [Province: Cuba] 192034 Santiago de Cuba [Province: Cuba] 192035 Guantánamo [Province: Cuba] 192040 Isla de la Juventud [Province: Cuba] 192997 Abroad [Province: Cuba] 192998 Unknown [Province: Cuba] 192999 NIU (not in universe) [Province: Cuba] 218001 Azuay [Province: Ecuador] 218002 Bolívar [Province: Ecuador] 218004 Carchi [Province: Ecuador] 218005 Cotopaxi [Province: Ecuador] 218006 Chimborazo [Province: Ecuador] 218007 El Oro [Province: Ecuador] 218009 Cañar, Esmeraldas, Guayas, Manabí, Manga del Cura [Disputed canton], Pichincha, El Piedrero [Disputed canton], Los Ríos, Santa Elena, Santo Domingo de las Tsáchilas, Galápagos [Province: Ecuador] 218010 Imbabura, Las Golondrinas [Disputed canton] [Province: Ecuador] 218011 Loja [Province: Ecuador] 218014 Morona Santiago [Province: Ecuador] 218016 Pastaza [Province: Ecuador] 218018 Tungurahua [Province: Ecuador] 218019 Zamora Chinchipe [Province: Ecuador] 218021 Napo, Orellana, Sucumbíos [Province: Ecuador] 218097 Foreign country [Province: Ecuador] 218098 Unknown and Disputed Zones [Province: Ecuador] 218999 NIU (not in universe) [Province: Ecuador] 818000 Reported same governorate as household location [Governorate: Egypt] 818001 Giza, 6th October City, Cairo, Helwan [Governorate: Egypt] 818002 Alexandria [Governorate: Egypt] 818003 Port Said [Governorate: Egypt] 818004 Suez [Governorate: Egypt] 818011 Demietta [Governorate: Egypt] 818012 Dakahlia [Governorate: Egypt] 818013 Sharkia [Governorate: Egypt] 818014 Kaliobia [Governorate: Egypt] 818015 Kafr Sheikh [Governorate: Egypt] 818016 Gharbia [Governorate: Egypt] 818018 Menoufia, Behera [Governorate: Egypt] 818019 Ismailia [Governorate: Egypt] 818022 Bani Swif [Governorate: Egypt] 818023 Fayoum [Governorate: Egypt] 818024 Menia [Governorate: Egypt] 818025 Asiut [Governorate: Egypt] 818026 Sohag [Governorate: Egypt] 818027 Qena, Luxor [Governorate: Egypt] 818028 Aswan [Governorate: Egypt] 818031 Red Sea [Governorate: Egypt] 818032 New Valley [Governorate: Egypt] 818033 Marsa Matroh [Governorate: Egypt] 818034 North Sinai [Governorate: Egypt] 818035 South Sinai [Governorate: Egypt] 818097 Abroad [Governorate: Egypt] 818098 Unknown [Governorate: Egypt] 818099 NIU (not in universe) [Governorate: Egypt] 222001 Ahuachapán [Department: El Salvador] 222002 Santa Ana [Department: El Salvador] 222003 Sonsonate [Department: El Salvador] 222004 Chalatenango [Department: El Salvador] 222005 La Libertad [Department: El Salvador] 222006 San Salvador [Department: El Salvador] 222007 Cuscatlán [Department: El Salvador] 222008 La Paz [Department: El Salvador] 222009 Cabañas [Department: El Salvador] 222010 San Vicente [Department: El Salvador] 222011 Usulután [Department: El Salvador] 222012 San Miguel [Department: El Salvador] 222013 Morazán [Department: El Salvador] 222014 La Unión [Department: El Salvador] 222098 Abroad [Department: El Salvador] 222099 NIU (not in universe) [Department: El Salvador] 231001 Tigray [Region: Ethiopia] 231002 Affar [Region: Ethiopia] 231003 Amhara [Region: Ethiopia] 231004 Oromia, Somali [Region: Ethiopia] 231006 Benishangul-Gumuz [Region: Ethiopia] 231007 Southern Nations, Nationalities, and Peoples (SNNP) [Region: Ethiopia] 231012 Gambela [Region: Ethiopia] 231013 Harari [Region: Ethiopia] 231014 Addis Ababa [Region: Ethiopia] 231015 Dire Dawa [Region: Ethiopia] 231097 Abroad [Region: Ethiopia] 231099 NIU [Region: Ethiopia] 250001 Guadeloupe [Region: France] 250002 Martinique [Region: France] 250003 French Guyana [Region: France] 250004 Réunion Island [Region: France] 250011 Île-de-France [Region: France] 250021 Champagne-Ardenne [Region: France] 250022 Picardy [Region: France] 250023 Upper Normandy [Region: France] 250024 Centre [Region: France] 250025 Lower Normandy [Region: France] 250026 Burgundy [Region: France] 250031 North Pas-de-Calais [Region: France] 250041 Lorraine [Region: France] 250042 Alsace [Region: France] 250043 Franche-Comté [Region: France] 250052 Loire Valley [Region: France] 250053 Brittany [Region: France] 250054 Poitou-Charentes [Region: France] 250072 Aquitaine [Region: France] 250073 Midi-Pyrénées [Region: France] 250074 Limousin [Region: France] 250082 Rhône-Alpes [Region: France] 250083 Auvergne [Region: France] 250091 Languedoc-Roussillon [Region: France] 250093 Provence-Alpes-Riviera [Region: France] 250094 Corsica [Region: France] 250097 Abroad [Region: France] 320001 Guatemala [Department: Guatemala] 320002 El Progreso [Department: Guatemala] 320003 Sacatepéquez [Department: Guatemala] 320004 Chimaltenango [Department: Guatemala] 320005 Escuintla [Department: Guatemala] 320006 Santa Rosa [Department: Guatemala] 320007 Sololá [Department: Guatemala] 320008 Totonicapán [Department: Guatemala] 320009 Quetzaltenango [Department: Guatemala] 320010 Suchitepéquez [Department: Guatemala] 320011 Retalhuleu [Department: Guatemala] 320012 San Marcos [Department: Guatemala] 320013 Huehuetenango [Department: Guatemala] 320014 Quiché [Department: Guatemala] 320015 Baja Verapaz [Department: Guatemala] 320016 Alta Verapaz [Department: Guatemala] 320017 Petén [Department: Guatemala] 320018 Izabal [Department: Guatemala] 320019 Zacapa [Department: Guatemala] 320020 Chiquimula [Department: Guatemala] 320021 Jalapa [Department: Guatemala] 320022 Jutiapa [Department: Guatemala] 320097 Foreign Country [Department: Guatemala] 320098 Unknown [Department: Guatemala] 320099 NIU [Department: Guatemala] 324011 Boffa [Region: Guinea] 324012 Boké [Region: Guinea] 324013 Fria [Region: Guinea] 324014 Gaoual [Region: Guinea] 324015 Koundara [Region: Guinea] 324021 Conakry [Region: Guinea] 324031 Dabola [Region: Guinea] 324032 Dinguiraye [Region: Guinea] 324033 Faranah [Region: Guinea] 324034 Kissidougou [Region: Guinea] 324041 Kankan [Region: Guinea] 324042 Kérouané [Region: Guinea] 324043 Kouroussa [Region: Guinea] 324044 Mandiana [Region: Guinea] 324045 Siguiri [Region: Guinea] 324051 Coyah, Dubréka [Region: Guinea] 324053 Forécariah [Region: Guinea] 324054 Kindia [Region: Guinea] 324055 Télimélé [Region: Guinea] 324061 Koubia [Region: Guinea] 324062 Labé [Region: Guinea] 324063 Lélouma [Region: Guinea] 324064 Mali [Region: Guinea] 324065 Tougué [Region: Guinea] 324071 Dalaba [Region: Guinea] 324072 Mamou [Region: Guinea] 324073 Pita [Region: Guinea] 324081 Beyla [Region: Guinea] 324082 Guéckédou [Region: Guinea] 324083 Lola [Region: Guinea] 324084 Macenta [Region: Guinea] 324085 Nzerekore [Region: Guinea] 324086 Yomou [Region: Guinea] 324096 Guinea, place unknown [Region: Guinea] 324097 Foreign country [Region: Guinea] 324098 Unknown [Region: Guinea] 324099 NIU (not in universe) [Region: Guinea] 332003 Nord (North) and Nord'est (North East) [Department: Haiti] 332006 Centre (Central), L'Artibonite, Ouest (West), Sud'Est (South East) [Department: Haiti] 332007 Grand'Anse, Nippes, Sud (South) [Department: Haiti] 332009 Nord'Ouest (North West) [Department: Haiti] 332097 Foreign Country [Department: Haiti] 332098 Unknown [Department: Haiti] 356001 Jammu and Kashmir [State: India] 356002 Himachal Pradesh [State: India] 356003 Punjab [State: India] 356004 Chandigarh [State: India] 356006 Haryana [State: India] 356007 Delhi [State: India] 356008 Rajasthan [State: India] 356009 Uttar Pradesh, Uttaranchal [State: India] 356010 Bihar, Jharkhand [State: India] 356011 Sikkim [State: India] 356012 Arunachal Pradesh [State: India] 356013 Nagaland [State: India] 356014 Manipur [State: India] 356015 Mizoram [State: India] 356016 Tripura [State: India] 356017 Meghalaya [State: India] 356018 Assam [State: India] 356019 West Bengal [State: India] 356021 Orissa [State: India] 356023 Madhya Pradesh, Chhattisgarh [State: India] 356024 Gujarat [State: India] 356026 Dadra and Nagar Haveli [State: India] 356027 Maharashtra [State: India] 356028 Andhra Pradesh [State: India] 356029 Karnataka [State: India] 356030 Goa, Daman and Diu [State: India] 356031 Lakshadweep [State: India] 356032 Kerala [State: India] 356033 Tamil Nadu [State: India] 356034 Pondicherry [State: India] 356035 Andaman and Nicobar Islands [State: India] 356097 Abroad [State: India] 356098 Unknown [State: India] 356099 NIU (not in universe) [State: India] 360011 Nanggroe Aceh Darussalam [Province: Indonesia] 360012 Sumatera Utara [Province: Indonesia] 360013 Sumatera Barat [Province: Indonesia] 360014 Kepulauan Riau, Riau [Province: Indonesia] 360015 Jambi [Province: Indonesia] 360016 Bangka Belitung, Sumatera Selatan [Province: Indonesia] 360017 Bengkulu [Province: Indonesia] 360018 Lampung [Province: Indonesia] 360031 DKI Jakarta [Province: Indonesia] 360032 Banten, Jawa Barat [Province: Indonesia] 360033 Jawa Tengah [Province: Indonesia] 360034 DKI Yogyakarta [Province: Indonesia] 360035 Jawa Timur [Province: Indonesia] 360051 Bali [Province: Indonesia] 360052 Nusa Tenggara Barat [Province: Indonesia] 360053 Nusa Tenggara Timur [Province: Indonesia] 360061 Kalimantan Barat [Province: Indonesia] 360062 Kalimantan Tengah [Province: Indonesia] 360063 Kalimantan Selatan [Province: Indonesia] 360064 Kalimantan Timur [Province: Indonesia] 360071 Gorontalo, Sulawesi Utara [Province: Indonesia] 360072 Sulawesi Tengah [Province: Indonesia] 360073 Sulawesi Barat, Sulawesi Selatan [Province: Indonesia] 360074 Sulawesi Tenggara [Province: Indonesia] 360081 Maluku, Maluku Utara [Province: Indonesia] 360094 Papua, Papua Barat [Province: Indonesia] 360097 Abroad [Province: Indonesia] 360098 Unknown [Province: Indonesia] 360099 NIU (not in universe) [Province: Indonesia] 360626 East Timor [Province: Indonesia] 364000 Markazi [Province: Iran] 364001 Gilan [Province: Iran] 364002 Mazandaran [Province: Iran] 364003 East Azarbayejan [Province: Iran] 364004 West Azarbayejan [Province: Iran] 364005 Kermanshah [Province: Iran] 364006 Khuzestan [Province: Iran] 364007 Fars [Province: Iran] 364008 Kerman [Province: Iran] 364009 Razavi Khorasan [Province: Iran] 364010 Esfahan [Province: Iran] 364011 Sistan and Baluchestan [Province: Iran] 364012 Kordestan [Province: Iran] 364013 Hamedan [Province: Iran] 364014 Chaharmahal and Bakhtiyari [Province: Iran] 364015 Lorestan [Province: Iran] 364016 Ilam [Province: Iran] 364017 Kohgiluyeh and Boyerahmad [Province: Iran] 364018 Bushehr [Province: Iran] 364019 Zanjan [Province: Iran] 364020 Semnan [Province: Iran] 364021 Yazd [Province: Iran] 364022 Hormozgan [Province: Iran] 364023 Tehran, Alborz [Province: Iran] 364024 Ardebil [Province: Iran] 364025 Qom [Province: Iran] 364026 Qazvin [Province: Iran] 364027 Golestan [Province: Iran] 364028 North Khorasan [Province: Iran] 364029 South Khorasan [Province: Iran] 364098 Unknown [Province: Iran] 364099 NIU (not in universe) [Province: Iran] 368000 Always lived in residential place of birth [Governorate: Iraq] 368001 In this governorate [Governorate: Iraq] 368011 Dahuk [Governorate: Iraq] 368012 Nineveh [Governorate: Iraq] 368013 Sulaymaniyah [Governorate: Iraq] 368014 Al-Tameem [Governorate: Iraq] 368015 Erbil [Governorate: Iraq] 368021 Diala [Governorate: Iraq] 368022 Al-Anbar [Governorate: Iraq] 368023 Baghdad [Governorate: Iraq] 368024 Babylon [Governorate: Iraq] 368025 Kerbela [Governorate: Iraq] 368026 Wasit [Governorate: Iraq] 368027 Salah Al-Deen [Governorate: Iraq] 368028 Al-Najaf [Governorate: Iraq] 368031 Al-Qadisiya [Governorate: Iraq] 368032 Al-Muthanna [Governorate: Iraq] 368033 Thi-Qar [Governorate: Iraq] 368034 Maysan [Governorate: Iraq] 368035 Al-Basrah [Governorate: Iraq] 368097 Other countries [Governorate: Iraq] 368098 Unknown [Governorate: Iraq] 388001 Kingston [Parish: Jamaica] 388002 Saint Andrew [Parish: Jamaica] 388003 Saint Thomas [Parish: Jamaica] 388004 Portland [Parish: Jamaica] 388005 Saint Mary [Parish: Jamaica] 388006 Saint Ann [Parish: Jamaica] 388007 Trelawny [Parish: Jamaica] 388008 Saint James [Parish: Jamaica] 388009 Hanover [Parish: Jamaica] 388010 Westmoreland [Parish: Jamaica] 388011 Saint Elizabeth [Parish: Jamaica] 388012 Manchester [Parish: Jamaica] 388013 Clarendon [Parish: Jamaica] 388014 Saint Catherine [Parish: Jamaica] 388098 Unknown [Parish: Jamaica] 388099 NIU (Not in universe) [Parish: Jamaica] 400011 Amman [Governorate: Jordan] 400012 Balqa [Governorate: Jordan] 400013 Zarqa [Governorate: Jordan] 400014 Madaba [Governorate: Jordan] 400021 Irbid [Governorate: Jordan] 400022 Mafraq [Governorate: Jordan] 400023 Jarash [Governorate: Jordan] 400024 Ajlun [Governorate: Jordan] 400031 Karak [Governorate: Jordan] 400032 Tafilah [Governorate: Jordan] 400033 Ma'an [Governorate: Jordan] 400034 Aqaba [Governorate: Jordan] 400997 Foreign Country [Governorate: Jordan] 400998 Unknown [Governorate: Jordan] 404001 Nairobi [Province: Kenya] 404002 Central [Province: Kenya] 404003 Coast [Province: Kenya] 404004 Eastern [Province: Kenya] 404005 Northeastern [Province: Kenya] 404006 Nyanza [Province: Kenya] 404007 Rift Valley [Province: Kenya] 404008 Western [Province: Kenya] 404097 Abroad [Province: Kenya] 404098 Unknown [Province: Kenya] 404099 NIU (not in universe) [Province: Kenya] 417001 Bishkek [Region: Kyrgyz Republic] 417002 Issyk-Kul region [Region: Kyrgyz Republic] 417003 Dzhalal-Abad region [Region: Kyrgyz Republic] 417004 Naryn region [Region: Kyrgyz Republic] 417005 Batken region [Region: Kyrgyz Republic] 417006 Oshskaya region, City of Osh [Region: Kyrgyz Republic] 417007 Talasskaya region [Region: Kyrgyz Republic] 417008 Chuya region [Region: Kyrgyz Republic] 417096 Other Kyrgyz Republic, not specified [Region: Kyrgyz Republic] 417097 Foreign country [Region: Kyrgyz Republic] 417098 Unknown [Region: Kyrgyz Republic] 417099 NIU (not in universe) [Region: Kyrgyz Republic] 418001 Vientiane Capital [Province: Laos] 418002 Phongsaly [Province: Laos] 418003 Luangnamtha [Province: Laos] 418004 Oudomxay [Province: Laos] 418005 Bokeo [Province: Laos] 418006 Luangprabang [Province: Laos] 418007 Huaphanh [Province: Laos] 418008 Xayaboury [Province: Laos] 418009 Xienkhuang [Province: Laos] 418010 Vientiane Province [Province: Laos] 418011 Borikhamxay [Province: Laos] 418012 Khammuane [Province: Laos] 418013 Savanakhet [Province: Laos] 418014 Saravane [Province: Laos] 418015 Sekong [Province: Laos] 418016 Champasack [Province: Laos] 418017 Attapeu [Province: Laos] 418018 Xaysomboune [Province: Laos] 418097 Foreign Country [Province: Laos] 418098 Unknown [Province: Laos] 418099 NIU [Province: Laos] 662003 Castries city, Castries rural, Castries suburban [District: Saint Lucia] 662009 Choiseul, Laborie, Vieux-Fort [District: Saint Lucia] 662010 Anse-la-Raye, Canaries, Micoud, Soufriere [District: Saint Lucia] 662012 Dennery, Gros-Islet [District: Saint Lucia] 662098 Unknown [District: Saint Lucia] 662099 NIU [District: Saint Lucia] 454101 Chitipa [District: Malawi] 454102 Karonga [District: Malawi] 454103 Nkhata Bay, Likoma [District: Malawi] 454104 Rumphi [District: Malawi] 454105 Mzimba, Mzuzu city [District: Malawi] 454201 Kasungu [District: Malawi] 454202 Nkhotakota [District: Malawi] 454203 Ntchisi [District: Malawi] 454204 Dowa [District: Malawi] 454205 Salima [District: Malawi] 454206 Lilongwe, Lilongwe city [District: Malawi] 454207 Mchinji [District: Malawi] 454208 Dedza [District: Malawi] 454209 Ntcheu [District: Malawi] 454301 Mangochi [District: Malawi] 454302 Machinga [District: Malawi] 454303 Zomba, Zomba city [District: Malawi] 454304 Chiradzulu [District: Malawi] 454305 Blantyre, Blantyre city [District: Malawi] 454307 Thyolo [District: Malawi] 454308 Mulanje [District: Malawi] 454309 Phalombe [District: Malawi] 454310 Chikwawa [District: Malawi] 454311 Nsanje [District: Malawi] 454312 Balaka [District: Malawi] 454313 Mwanza, Neno [District: Malawi] 454997 Abroad [District: Malawi] 454999 NIU (not in universe) [District: Malawi] 466001 Kayes [Region: Mali] 466002 Koulikoro [Region: Mali] 466003 Sikasso [Region: Mali] 466004 Ségou [Region: Mali] 466005 Mopti [Region: Mali] 466006 Tombouctou [Region: Mali] 466007 Gao, Kidal [Region: Mali] 466009 Bamako [Region: Mali] 466096 Mali, province unspecified [Region: Mali] 466097 Foreign country [Region: Mali] 466098 Unknown [Region: Mali] 466999 NIU (not in universe) [Region: Mali] 484001 Aguascalientes [State: Mexico] 484002 Baja California [State: Mexico] 484003 Baja California Sur [State: Mexico] 484004 Campeche [State: Mexico] 484005 Coahuila de Zaragoza [State: Mexico] 484006 Colima [State: Mexico] 484007 Chiapas [State: Mexico] 484008 Chihuahua [State: Mexico] 484009 Distrito Federal [State: Mexico] 484010 Durango [State: Mexico] 484011 Guanajuato [State: Mexico] 484012 Guerrero [State: Mexico] 484013 Hidalgo [State: Mexico] 484014 Jalisco [State: Mexico] 484015 México [State: Mexico] 484016 Michoacán de Ocampo [State: Mexico] 484017 Morelos [State: Mexico] 484018 Nayarit [State: Mexico] 484019 Nuevo León [State: Mexico] 484020 Oaxaca [State: Mexico] 484021 Puebla [State: Mexico] 484022 Querétaro [State: Mexico] 484023 Quintana Roo [State: Mexico] 484024 San Luis Potosí [State: Mexico] 484025 Sinaloa [State: Mexico] 484026 Sonora [State: Mexico] 484027 Tabasco [State: Mexico] 484028 Tamaulipas [State: Mexico] 484029 Tlaxcala [State: Mexico] 484030 Veracruz de Ignacio de la Llave [State: Mexico] 484031 Yucatán [State: Mexico] 484032 Zacatecas [State: Mexico] 484097 Abroad [State: Mexico] 484098 Unknown [State: Mexico] 484099 NIU (not in universe) [State: Mexico] 496001 Arkhangai [Province: Mongolia] 496002 Bayan-Olgii [Province: Mongolia] 496003 Bayankhongor [Province: Mongolia] 496004 Bulgan [Province: Mongolia] 496005 Govi-Altai [Province: Mongolia] 496006 Dornogovi, Govisumber [Province: Mongolia] 496007 Dornod [Province: Mongolia] 496008 Dundgovi [Province: Mongolia] 496009 Zavkhan [Province: Mongolia] 496010 Ovorkhangai [Province: Mongolia] 496011 Omnogovi [Province: Mongolia] 496012 Sukhbaatar [Province: Mongolia] 496013 Selenge [Province: Mongolia] 496014 Tov [Province: Mongolia] 496015 Uvs [Province: Mongolia] 496016 Khovd [Province: Mongolia] 496017 Khovsgol [Province: Mongolia] 496018 Khentii [Province: Mongolia] 496019 Darkhan-Uul [Province: Mongolia] 496020 Ulaanbaatar [Province: Mongolia] 496021 Orkhon [Province: Mongolia] 496097 Abroad [Province: Mongolia] 496099 NIU (not in universe) [Province: Mongolia] 104001 Kachin [State: Myanmar] 104002 Kayah [State: Myanmar] 104003 Kayin [State: Myanmar] 104004 Chin [State: Myanmar] 104005 Sagaing [State: Myanmar] 104006 Tanintharyi [State: Myanmar] 104007 Bago [State: Myanmar] 104008 Magway [State: Myanmar] 104009 Mandalay [State: Myanmar] 104010 Mon [State: Myanmar] 104011 Rakhine [State: Myanmar] 104012 Yangon [State: Myanmar] 104013 Shan [State: Myanmar] 104014 Ayeyawady [State: Myanmar] 104015 Nay Pyi Taw [State: Myanmar] 104097 Abroad [State: Myanmar] 104099 NIU [State: Myanmar] 591002 Coclé [Province: Panama] 591003 Colón, Comarca Kuna Yala (San Blas) [Province: Panama] 591004 Bocas de Toro, Chiriquí, Comarca Ngäbe Buglé, Veraguas [Province: Panama] 591005 Comarca Emberá, Darién [Province: Panama] 591006 Herrera [Province: Panama] 591007 Los Santos [Province: Panama] 591008 Panamá [Province: Panama] 591009 Unknown district in Panamá province [Province: Panama] 591097 Foreign country [Province: Panama] 591098 Unknown [Province: Panama] 591099 NIU (not in universe) [Province: Panama] 608001 Abra [Province: Philippines] 608002 Agusan del norte [Province: Philippines] 608003 Agusan del sur [Province: Philippines] 608004 Aklan [Province: Philippines] 608005 Albay [Province: Philippines] 608006 Antique [Province: Philippines] 608007 Basilan, City Of Isabela [Province: Philippines] 608008 Bataan [Province: Philippines] 608010 Batangas [Province: Philippines] 608011 Benguet [Province: Philippines] 608012 Bohol [Province: Philippines] 608013 Bukidnon [Province: Philippines] 608014 Bulacan [Province: Philippines] 608015 Cagayan, Batanes [Province: Philippines] 608016 Camarines norte [Province: Philippines] 608017 Camarines Sur [Province: Philippines] 608018 Camiguin [Province: Philippines] 608019 Capiz [Province: Philippines] 608020 Catanduanes [Province: Philippines] 608021 Cavite [Province: Philippines] 608022 Cebu [Province: Philippines] 608023 Davao (Davao del Norte) [Province: Philippines] 608024 Davao del Sur, Davao Occidental [Province: Philippines] 608025 Davao Oriental [Province: Philippines] 608026 Eastern Samar [Province: Philippines] 608027 Ifugao [Province: Philippines] 608028 Ilocos Norte [Province: Philippines] 608029 Ilocos Sur [Province: Philippines] 608030 Iloilo, Guimaras [Province: Philippines] 608031 Isabela [Province: Philippines] 608032 Kalinga-Apayao, Apayo, Kalinga [Province: Philippines] 608033 La Union [Province: Philippines] 608034 Laguna [Province: Philippines] 608035 Lanao del Norte [Province: Philippines] 608036 Lanao del Sur, Maguindanao, Marawi City and Cotabato city [Province: Philippines] 608037 Leyte, Biliran [Province: Philippines] 608039 Manila [Province: Philippines] 608040 Marinduque [Province: Philippines] 608041 Masbate [Province: Philippines] 608042 Misamis Occidental [Province: Philippines] 608043 Misamis Oriental [Province: Philippines] 608044 Mountain Province [Province: Philippines] 608045 Negros Occidental [Province: Philippines] 608046 Negros Oriental [Province: Philippines] 608047 Cotabato (North Cotabato) [Province: Philippines] 608048 Northern Samar [Province: Philippines] 608049 Nueva Ecija [Province: Philippines] 608050 Nueva Vizcaya [Province: Philippines] 608051 Occidental Mindoro [Province: Philippines] 608052 Oriental Mindoro [Province: Philippines] 608053 Palawan [Province: Philippines] 608054 Pampanga [Province: Philippines] 608055 Pangasinan [Province: Philippines] 608056 Quezon [Province: Philippines] 608057 Quirino [Province: Philippines] 608058 Rizal [Province: Philippines] 608059 Romblon [Province: Philippines] 608060 Samar (Western Samar) [Province: Philippines] 608061 Siquijor [Province: Philippines] 608062 Sorsogon [Province: Philippines] 608063 South Cotabato, Sarangani [Province: Philippines] 608064 Southern Leyte [Province: Philippines] 608065 Sultan Kudarat [Province: Philippines] 608066 Sulu [Province: Philippines] 608067 Surigao Del Norte, Dinagat islands [Province: Philippines] 608068 Surigao del Sur [Province: Philippines] 608069 Tarlac [Province: Philippines] 608070 Tawi-Tawi [Province: Philippines] 608071 Zambales [Province: Philippines] 608072 Zamboanga Norte [Province: Philippines] 608073 Zamboanga del Sur, Zamboanga Sibugay [Province: Philippines] 608074 Manila Metro, 2nd District [Province: Philippines] 608075 Manila Metro, 3rd District [Province: Philippines] 608076 Manila Metro, 4th District [Province: Philippines] 608077 Aurora [Province: Philippines] 608097 Foreign country [Province: Philippines] 608098 Unknown [Province: Philippines] 608099 NIU (not in universe) [Province: Philippines] 642001 Alba [County: Romania] 642002 Arad [County: Romania] 642003 Arges [County: Romania] 642004 Bacau [County: Romania] 642005 Bihor [County: Romania] 642006 Bistrita Nasaud [County: Romania] 642007 Botosani [County: Romania] 642008 Brasov [County: Romania] 642009 Braila [County: Romania] 642010 Buzau [County: Romania] 642011 Caras Severin [County: Romania] 642012 Cluj [County: Romania] 642013 Constanta [County: Romania] 642014 Covasna [County: Romania] 642015 Dambovita [County: Romania] 642016 Dolj [County: Romania] 642017 Galati [County: Romania] 642018 Gorj [County: Romania] 642019 Harghita [County: Romania] 642020 Hunedoara [County: Romania] 642022 Iasi [County: Romania] 642024 Maramures [County: Romania] 642025 Mehedinti [County: Romania] 642026 Mures [County: Romania] 642027 Neamt [County: Romania] 642028 Olt [County: Romania] 642029 Prahova [County: Romania] 642030 Satu Mare [County: Romania] 642031 Salaj [County: Romania] 642032 Sibiu [County: Romania] 642033 Suceava [County: Romania] 642034 Teleorman [County: Romania] 642035 Timis [County: Romania] 642036 Tulcea [County: Romania] 642037 Vaslui [County: Romania] 642038 Valcea [County: Romania] 642039 Vrancea [County: Romania] 642043 Bucharest Sector 1 to 6 [County: Romania] 642051 Calarasi, Giurgiu, Ialomita, Ilfov [County: Romania] 642097 Foreign country [County: Romania] 642098 Unknown [County: Romania] 642099 NIU (not in universe) [County: Romania] 646002 Byumba, Kigali Ngali, Kigali Ville, Kibungo, Umutara [Province: Rwanda] 646003 Gitarama [Province: Rwanda] 646004 Butare [Province: Rwanda] 646005 Gikongoro [Province: Rwanda] 646006 Cyangugu [Province: Rwanda] 646007 Kibuye [Province: Rwanda] 646008 Gisenyi [Province: Rwanda] 646009 Ruhengeri [Province: Rwanda] 646097 Foreign Countries [Province: Rwanda] 646098 Unknown [Province: Rwanda] 646099 NIU [Province: Rwanda] 705001 Pomurska [Region: Slovenia] 705002 Podravska [Region: Slovenia] 705003 Koroška [Region: Slovenia] 705004 Savinjska [Region: Slovenia] 705005 Zasavska [Region: Slovenia] 705006 Spodnjeposavska [Region: Slovenia] 705007 Jugovzhodna Slovenija [Region: Slovenia] 705008 Osrednjeslovenska [Region: Slovenia] 705009 Gorenjska [Region: Slovenia] 705010 Notranjsko-kraška [Region: Slovenia] 705011 Goriška [Region: Slovenia] 705012 Obalno-kraška [Region: Slovenia] 705097 Abroad [Region: Slovenia] 705999 NIU (not in universe) [Region: Slovenia] 710001 Western Cape [Province: South Africa] 710004 Free State [Province: South Africa] 710005 Eastern Cape, KwaZulu-Natal [Province: South Africa] 710007 Gauteng, Limpopo, Mpumalanga, North West, Northern Cape [Province: South Africa] 710097 Foreign country [Province: South Africa] 710098 Unknown [Province: South Africa] 710099 NIU (not in universe) [Province: South Africa] 724011 Galicia [Communities & autonomous city: Spain] 724012 Principado de Asturias [Communities & autonomous city: Spain] 724013 Cantabria [Communities & autonomous city: Spain] 724021 País Vasco [Communities & autonomous city: Spain] 724022 Comunidad Foral de Navarra [Communities & autonomous city: Spain] 724023 La Rioja [Communities & autonomous city: Spain] 724024 Aragón [Communities & autonomous city: Spain] 724030 Comunidad de Madrid [Communities & autonomous city: Spain] 724041 Castilla y León [Communities & autonomous city: Spain] 724042 Castilla-La Mancha [Communities & autonomous city: Spain] 724043 Extremadura [Communities & autonomous city: Spain] 724051 Cataluña [Communities & autonomous city: Spain] 724052 Comunidad Valenciana [Communities & autonomous city: Spain] 724053 Islas Baleares [Communities & autonomous city: Spain] 724061 Andalucía [Communities & autonomous city: Spain] 724062 Región de Murcia [Communities & autonomous city: Spain] 724063 Ciudad Autónoma de Ceuta [Communities & autonomous city: Spain] 724064 Ciudad Autónoma de Melilla [Communities & autonomous city: Spain] 724070 Canarias [Communities & autonomous city: Spain] 724097 Abroad [Communities & autonomous city: Spain] 724999 NIU (not in universe) [Communities & autonomous city: Spain] 740001 Paramaribo [District: Suriname] 740002 Wanica [District: Suriname] 740003 Nickerie [District: Suriname] 740005 Saramacca, Coronie [District: Suriname] 740006 Marowijne, Commewijne [District: Suriname] 740008 Brokopondo, Para [District: Suriname] 740010 Sipaliwini [District: Suriname] 740096 Suriname, district unknown [District: Suriname] 740097 Foreign [District: Suriname] 740098 Unknown [District: Suriname] 764010 Bangkok [Province: Thailand] 764011 Samut Prakan [Province: Thailand] 764012 Nonthaburi [Province: Thailand] 764013 Pathum Thani [Province: Thailand] 764014 Phra Nakhon Si Ayutthaya [Province: Thailand] 764015 Ang Thong [Province: Thailand] 764016 Lop Buri [Province: Thailand] 764017 Sing Buri [Province: Thailand] 764018 Chai Nat [Province: Thailand] 764019 Sa Kaeo, Prachin Buri [Province: Thailand] 764020 Chon Buri [Province: Thailand] 764021 Rayong [Province: Thailand] 764022 Chanthaburi [Province: Thailand] 764023 Trat [Province: Thailand] 764024 Chachoengsao [Province: Thailand] 764026 Nakhon Nayok [Province: Thailand] 764027 Saraburi [Province: Thailand] 764030 Nakhon Ratchasima [Province: Thailand] 764031 Buri Ram [Province: Thailand] 764032 Surin [Province: Thailand] 764033 Si Sa Ket [Province: Thailand] 764034 Ubon Ratchathani, Yasothon, Amnat Charoen [Province: Thailand] 764036 Chaiyaphum [Province: Thailand] 764039 Nong Bua Lam Phu, Udon Thani [Province: Thailand] 764040 Khon Kaen [Province: Thailand] 764042 Loei [Province: Thailand] 764043 Nong Khai [Province: Thailand] 764044 Maha Sarakham [Province: Thailand] 764045 Roi Et [Province: Thailand] 764046 Kalasin [Province: Thailand] 764047 Sakon Nakhon [Province: Thailand] 764048 Nakhon Phanom, Mukdahan [Province: Thailand] 764050 Chiang Mai [Province: Thailand] 764051 Lamphun [Province: Thailand] 764052 Lampang [Province: Thailand] 764053 Uttaradit [Province: Thailand] 764054 Phrae [Province: Thailand] 764055 Nan [Province: Thailand] 764057 Phayao, Chiang Rai [Province: Thailand] 764058 Mae Hong Son [Province: Thailand] 764060 Nakhon Sawan [Province: Thailand] 764061 Uthai Thani [Province: Thailand] 764062 Kamphaeng Phet [Province: Thailand] 764063 Tak [Province: Thailand] 764064 Sukhothai [Province: Thailand] 764065 Phitsanulok [Province: Thailand] 764066 Phichit [Province: Thailand] 764067 Phetchabun [Province: Thailand] 764070 Ratchaburi [Province: Thailand] 764071 Kanchanaburi [Province: Thailand] 764072 Suphanburi [Province: Thailand] 764073 Nakhon Pathom [Province: Thailand] 764074 Samut Sakhon [Province: Thailand] 764075 Samut Songkhram [Province: Thailand] 764076 Phetchaburi [Province: Thailand] 764077 Prachuap Khiri Khan [Province: Thailand] 764080 Nakhon Si Thammarat [Province: Thailand] 764082 Phangnga [Province: Thailand] 764083 Phuket [Province: Thailand] 764084 Krabi, Surat Thani [Province: Thailand] 764086 Ranong, Chumphon [Province: Thailand] 764090 Songkhla [Province: Thailand] 764091 Satun [Province: Thailand] 764092 Trang [Province: Thailand] 764093 Phatthalung [Province: Thailand] 764094 Pattani [Province: Thailand] 764095 Yala [Province: Thailand] 764096 Narathiwat [Province: Thailand] 764097 Same province [Province: Thailand] 764098 Unknown province, but within Thaliand [Province: Thailand] 764997 Abroad [Province: Thailand] 764998 Unknown [Province: Thailand] 764999 NIU (not in universe) [Province: Thailand] 768001 Maritime, Lomé [Region: Togo] 768002 Plateaux, Centrale, Kara [Region: Togo] 768003 Savanes [Region: Togo] 768097 Foreign Country [Region: Togo] 768098 Unknown [Region: Togo] 768099 NIU [Region: Togo] 780010 Port of Spain [Region: Trinidad and Tobago] 780020 San Fernando [Region: Trinidad and Tobago] 780080 Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] 780094 St. Paul, St. Mary, St. David, St. George, St. Patrick, St. Andrew, St. John, Tobago [Region: Trinidad and Tobago] 780098 Unknown [Region: Trinidad and Tobago] 800101 Kalangala [District: Uganda] 800102 Kampala [District: Uganda] 800103 Kiboga, Kyankwanzi [District: Uganda] 800104 Luwero, Nakasongola, Nakaseke [District: Uganda] 800105 Masaka, Ssembabule, Bukomansimbi, Kalungu, Lwengo [District: Uganda] 800106 Mpigi, Wakiso, Butambala, Gomba [District: Uganda] 800107 Mubende, Mityana [District: Uganda] 800108 Mukono, Kayunga, Buikwe, Buvuma [District: Uganda] 800110 Rakai, Lyantonde [District: Uganda] 800201 Bugiri, Iganga, Mayuge, Namutumba, Luuka, Namayingo [District: Uganda] 800202 Busia, Tororo, Butaleja [District: Uganda] 800204 Jinja [District: Uganda] 800205 Kamuli, Kaliro, Buyende [District: Uganda] 800206 Kapchorwa, Bukwo, Kween [District: Uganda] 800207 Katakwi, Soroti, Kaberamaido, Amuria, Serere [District: Uganda] 800208 Kumi, Bukedea, Ngora [District: Uganda] 800209 Mbale, Sironko, Bududa, Manafwa, Bulambuli [District: Uganda] 800210 Pallisa, Budaka, Kibuku [District: Uganda] 800301 Adjumani, Moyo [District: Uganda] 800302 Apac, Oyam, Kole [District: Uganda] 800303 Arua, Yumbe, Koboko, Maracha [District: Uganda] 800304 Gulu, Amuru, Nwoya, Omoro [District: Uganda] 800305 Kitgum, Pader, Agago, Lamwo [District: Uganda] 800306 Kotido, Moroto, Nakapiripirit, Abim, Kaabong, Amudat, Napak [District: Uganda] 800307 Lira, Amolatar, Dokolo, Alebtong, Otuke [District: Uganda] 800310 Nebbi, Zombo [District: Uganda] 800401 Bundibugyo, Ntoroko [District: Uganda] 800402 Bushenyi, Mbarara, Ntungamo, Ibanda, Isingiro, Kiruhura, Buhweju, Mitooma, Rubirizi, Sheema [District: Uganda] 800403 Hoima [District: Uganda] 800404 Kabale, Rubanda [District: Uganda] 800405 Kabarole, Kamwenge, Kyenjojo, Kyegegwa [District: Uganda] 800406 Kasese [District: Uganda] 800407 Kibaale, Kagadi, Kakumiro [District: Uganda] 800408 Kisoro [District: Uganda] 800409 Masindi, Buliisa, Kiryandongo [District: Uganda] 800412 Rukungiri, Kanungu [District: Uganda] 800096 Visitor [District: Uganda] 800097 Foreign country [District: Uganda] 800098 Unknown [District: Uganda] 804001 The Autonomous Republic of Crimea [Region: Ukraine] 804005 Vinnytska oblast [Region: Ukraine] 804007 Volynska oblast [Region: Ukraine] 804012 Dnipropetrovska oblast [Region: Ukraine] 804014 Donetska oblast [Region: Ukraine] 804018 Zhytomyrska oblast [Region: Ukraine] 804021 Zakarpatska oblast [Region: Ukraine] 804023 Zaporizka oblast [Region: Ukraine] 804026 Ivano-Frankivska oblast [Region: Ukraine] 804032 Kyivska oblast [Region: Ukraine] 804035 Kirovohradska oblast [Region: Ukraine] 804044 Luhanska oblast [Region: Ukraine] 804046 Lvivska oblast [Region: Ukraine] 804048 Mykolaivska oblast [Region: Ukraine] 804051 Odeska oblast [Region: Ukraine] 804053 Poltavska oblast [Region: Ukraine] 804056 Rivnenska oblast [Region: Ukraine] 804059 Sumska oblast [Region: Ukraine] 804061 Ternopilska oblast [Region: Ukraine] 804063 Kharkivska oblast [Region: Ukraine] 804065 Khersonska oblast [Region: Ukraine] 804068 Khmelnytska oblast [Region: Ukraine] 804071 Cherkaska oblast [Region: Ukraine] 804073 Chernivetska oblast [Region: Ukraine] 804074 Chernihivska oblast [Region: Ukraine] 804080 Kyiv (independent city) [Region: Ukraine] 804085 Sevastopol (independent city) [Region: Ukraine] 804097 Foreign country [Region: Ukraine] 804098 Unknown [Region: Ukraine] 804099 NIU (not in universe) [Region: Ukraine] 858001 Montevideo [Department: Uruguay] 858002 Artigas [Department: Uruguay] 858003 Canelones [Department: Uruguay] 858004 Cerro Largo [Department: Uruguay] 858005 Colonia [Department: Uruguay] 858006 Durazno [Department: Uruguay] 858007 Flores [Department: Uruguay] 858008 Florida [Department: Uruguay] 858009 Lavalleja [Department: Uruguay] 858010 Maldonado [Department: Uruguay] 858011 Paysandú [Department: Uruguay] 858012 Río Negro [Department: Uruguay] 858013 Rivera [Department: Uruguay] 858014 Rocha [Department: Uruguay] 858015 Salto [Department: Uruguay] 858016 San Jose [Department: Uruguay] 858017 Soriano [Department: Uruguay] 858018 Tacuarembó [Department: Uruguay] 858019 Treinta Y Tres [Department: Uruguay] 858097 Abroad [Department: Uruguay] 858098 Unknown [Department: Uruguay] 858999 NIU (not in universe) [Department: Uruguay] 862001 Federal District, Vargas [State: Venezuela] 862002 Amazonas Federal Territory [State: Venezuela] 862003 Anzoátegui [State: Venezuela] 862004 Apure [State: Venezuela] 862005 Aragua [State: Venezuela] 862007 Bolívar [State: Venezuela] 862008 Carabobo [State: Venezuela] 862009 Cojedes [State: Venezuela] 862010 Amacuros Delta Federal Territory [State: Venezuela] 862011 Falcón [State: Venezuela] 862012 Guárico [State: Venezuela] 862013 Lara [State: Venezuela] 862014 Barinas, Mérida [State: Venezuela] 862015 Miranda [State: Venezuela] 862016 Monagas [State: Venezuela] 862017 Nueva Esparta, Federal Dependencies [State: Venezuela] 862018 Portuguesa [State: Venezuela] 862019 Sucre [State: Venezuela] 862020 Táchira [State: Venezuela] 862021 Trujillo [State: Venezuela] 862022 Yaracuy [State: Venezuela] 862023 Zulia [State: Venezuela] 862097 Foreign country [State: Venezuela] 862098 Unknown [State: Venezuela] 862099 NIU (not in universe) [State: Venezuela] GEOMIG1_P indicates the major administrative unit in which the person previously resided prior to the survey. Only intra-national migrations are recorded; however, the variable incorporates geographies for every country that lists place of previous residence, to enable comparative analysis of subnational migration. Foreign migrants are coded 097 or 997. Codes for GEOMIG1_1 match the geographic codes in GEOLEV1 (current place of residence). For similar information for different time intervals since migration, see variables GEOMIG1_1, GEOMIG1_5, and GEOMIG1_10. More on migration and geography can be found here. IPUMS Years residing in current locality 00 Less than 1 year 01 1 year (or 1 year or less) 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95+ years 96 Less than 5 years 97 More than 5 years 98 Unknown 99 NIU (not in universe) MIGYRS1 indicates how many years the person has resided in their current locality of residence. IPUMS Department of previous residence, El Salvador; consistent boundaries, GIS 222001 Ahuachapán 222002 Santa Ana 222003 Sonsonate 222004 Chalatenango 222005 La Libertad 222006 San Salvador 222007 Cuscatlán 222008 La Paz 222009 Cabañas 222010 San Vicente 222011 Usulután 222012 San Miguel 222013 Morazán 222014 La Unión 222097 Abroad 222098 Unknown MIG1_P_SV indicates the person's department of previous residence within El Salvador. The migration could have occurred at any time in the past. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. IPUMS Municipality of previous residence, El Salvador; consistent boundaries, GIS 222001001 Ahuachapán, San Lorenzo 222001002 Turín, El Refugio, Atiquizaya 222001003 San Francisco Menéndez 222001004 Tacuba 222001005 Jujutla 222001006 San Pedro Puxtla, Guaymango 222001007 Apaneca, Concepción de Ataco 222001099 Ahuachapán department, unknown municipality 222002001 Santa Ana, San Sebastián Salitrillo 222002002 Metapán, San Antonio Pajonal, Santiago de la Frontera, Santa Rosa Guachipilín, Masahuat, Texistepeque 222002003 Chalchuapa 222002004 Coatepeque 222002005 Candelaria de la Frontera, El Porvenir 222002006 El Congo 222002099 Santa Ana department, unknown municipality 222003001 San Julián, Izalco 222003002 Nahulingo, Sonsonate 222003003 Acajutla 222003004 Nahuizalco 222003005 Armenia 222003006 Santa Isabel Ishuatán, Cuisnahuat, Caluco 222003007 San Antonio del Monte 222003008 Sonzacate 222003009 Juayúa 222003010 Santa Catarina Masahuat, Salcoatitán, Santo Domingo de Guzmán 222003099 Sonsonate department, unknown municipality 222004001 Agua Caliente, La Palma, San Ignacio, Citalá, San Fernando, San Francisco Morazán, Dulce Nombre de María 222004002 El Paraíso, San Rafael, Santa Rita, Concepción Quezaltepeque, Ojos de Agua, Comalapa, La Laguna, El Carrizal 222004003 Nueva Concepción 222004004 Chalatenango 222004005 Nueva Trinidad, Las Vueltas, San Isidro Labrador, Cancasque, Potonico, San Miguel de Mercedes, San Antonio Los Ranchos, Azacualpa, San Luis del Carmen, San Francisco Lempa, San Antonio de la Cruz, Nombre de Jesús, Las Flores, Arcatao 222004006 La Reina, Tejutla 222004099 Chalatenango department, unknown municipality 222005001 Nuevo Cuscatlán, Santa Tecla 222005002 Colón 222005003 Sacacoyo, Ciudad Arce 222005004 San Juan Opico 222005005 Quezaltepeque 222005006 Jicalapa, Tamanique, Chiltiupán, Teotepeque 222005007 La Libertad 222005008 Antiguo Cuscatlán 222005009 San Matías, San Pablo Tacachico 222005010 San José Villanueva, Huizúcar 222005011 Jayaque, Tepecoyo 222005012 Zaragoza 222005013 Comasagua, Talnique 222005099 La Libertad department, unknown municipality 222006001 San Salvador 222006002 Soyapango 222006003 Mejicanos 222006004 Apopa 222006005 Ciudad Delgado 222006006 Ilopango 222006007 Tonacatepeque 222006008 San Martín 222006009 Cuscatancingo 222006010 San Marcos 222006011 Rosario de Mora, Panchimalco 222006012 Santo Tomás, Santiago Texacuangos 222006013 Ayutuxtepeque 222006014 Aguilares, El Paisnal 222006015 Nejapa 222006016 Guazapa 222006099 San Salvador department, unknown municipality 222007001 San Bartolomé Perulapía, San Pedro Perulapán 222007002 Cojutepeque 222007003 Suchitoto, Tenancingo, San José Guayabal, Oratorio de Concepción, El Rosario 222007004 San Rafael Cedros, El Carmen 222007005 San Cristóbal, Candelaria, San Ramón, Santa Cruz Analquito 222007006 Santa Cruz Michapa, Monte San Juan 222007099 Cuscatlán department, unknown municipality 222008001 Zacatecoluca, San Luis la Herradura 222008002 El Rosario, Santiago Nonualco 222008003 Olocuilta, San Juan Talpa, Cuyultitán 222008004 San Juan Nonualco, San Rafael Obrajuelo 222008005 San Antonio Masahuat, Tapalhuaca, San Francisco Chinameca, San Juan Tepezontes, San Emigdio, San Miguel Tepezontes 222008006 San Pedro Masahuat 222008007 San Pedro Nonualco, Santa María Ostuma, Paraíso de Osorio, Jerusalén, Mercedes la Ceiba 222008008 San Luis Talpa 222008099 La Paz department, unknown municipality 222009001 San Isidro, Jutiapa, Tejutepeque, Cinquera, Sensuntepeque, Victoria, Guacotecti, Dolores 222009002 Ilobasco 222009099 Cabañas department, unknown municipality 222010001 San Vicente 222010002 San Sebastián, Verapaz, Santo Domingo, San Lorenzo, Tepetitán, San Cayetano Istepeque, Guadalupe 222010003 Apastepeque, San Ildefonso, Santa Clara, San Esteban Catarina 222010004 Tecoluca 222010099 San Vicente department, unknown municipality 222011001 Santa Elena, Ozatlán, Santa María, Ereguayquín, Usulután, San Dionisio 222011002 San Agustín, Jiquilisco, San Francisco Javier, Puerto El Triunfo 222011003 Santiago de María, Jucuapa, Alegría 222011004 Estanzuelas, Nueva Granada, El Triunfo, San Buenaventura, Mercedes Umaña 222011005 Berlín, Tecapán, California 222011006 Concepción Batres, Jucuarán 222011099 Usulután department, unknown municipality 222012001 Quelepa, San Miguel, San Rafael Oriente, El Tránsito, Uluazapa, Comacarán 222012002 Nueva Guadalupe, Chinameca, San Jorge 222012003 Lolotique, Moncagua 222012004 Sesori, Nuevo Edén de San Juan, San Gerardo, San Luis de la Reina, Chapeltique 222012005 Carolina, San Antonio, Ciudad Barrios 222012006 Chirilagua 222012099 San Miguel department, unknown municipality 222013001 Guatajiagua, Sensembra, Yamabal, San Carlos, El Divisadero, Jocoro 222013002 Cacaopera, San Fernando, Arambala, Perquín, Jocoaitique, Torola, El Rosario, Meanguera, Joateca 222013003 Corinto, Sociedad 222013004 Chilanga, San Isidro, San Simón, Gualococti 222013005 Lolotiquillo, Delicias de Concepción, Yoloaiquín, Oscicala 222013006 San Francisco Gotera 222013099 Morazán department, unknown municipality 222014001 Anamorós, Nueva Esparta, Lislique, Polorós, Concepción de Oriente 222014002 Conchagua, Meanguera del Golfo 222014003 San Alejo, Intipucá, El Carmen 222014004 La Unión 222014005 Santa Rosa de Lima 222014006 Pasaquina, El Sauce 222014007 Yucuaiquín, Bolívar, San José, Yayantique 222014099 La Unión department, unknown municipality 222097097 Abroad 222099098 Unknown MIG2_P_SV indicates the person's municipality of previous residence within El Salvador. Migration municipality codes from MIG2_P_SV are compatible with codes from GEO2_SV.The migration could have occurred at any time in the past. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. 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 Employment disability 1 Disabled 2 Not disabled 8 Unknown 9 NIU (not in universe) DISEMP indicates if the respondent was economically inactive because of disabilities or, in some instances, other health-related reasons. 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 Disability affecting upper extremities NIU (not in universe) 1 Yes 2 No 9 Unknown DISUPPR indicates whether the person lacked full use of at least one arm or hand. IPUMS Disability limiting ability to walk NIU (not in universe) 1 Yes 2 No 9 Unknown DISMOBIL indicates whether the person has difficulty walking or climbing stairs. 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 Personal care limitation NIU (not in universe) 1 Yes, personal care limitation 2 No personal care limitation 9 Unknown DISCARE indicates whether the respondent had any permanent condition that made it difficult for him/her to take care of their personal needs. IPUMS Person number (within household) El Salvador 2007: All households 00 Household record 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 This variable indicates the person number (within household). IPUMS Relationship to head of household <svar a="all" v="SV07A401">1. What is the connection or family relationship to the head of household?<br /><div class="i1">[] 01 Head of household<br />[] 02 Spouse or partner<br />[] 03 Child<br />[] 04 Son-in-law or daughter-in-law<br />[] 05 Grandchild or great-grandchild<br />[] 06 Brother or sister<br />[] 07 Nephew or niece<br />[] 08 Father or mother<br />[] 09 Father-in-law or mother-in-law<br />[] 10 Other relatives<br />[] 11 Domestic employee<br />[] 12 Other non-related person<br />[] 13 Person in institutional dwelling<br />[] 14 Homeless person</div><br /></svar> El Salvador 2007: All persons 01 Head 02 Spouse or partner 03 Daughter or son 04 Son/daughter-in-law 05 Grandchild or great grandchild 06 Brother or sister 07 Nephew or niece 08 Father or mother 09 Father/mother-in-law 10 Other relative 11 Domestic employee 12 Other non-relative 13 Person in a collective household 14 Homeless person This variable indicates the person's relationship to the head of household. IPUMS Sex <svar a="all" v="SV07A402">2. Is this person male or female?<br /><div class="i1">[] 1 Male<br />[] 2 Female</div><br /></svar> El Salvador 2007: All persons 1 Male 2 Female This variable indicates the person's sex. IPUMS Age (in years completed) <svar a="all" v="SV07A403 SV07A469">3a. How old is this person in completed years?<br /><div class="i1">Write "00" if younger than 1, and "98" if age 98 or older<br />/_/_/</div><br /></svar> El Salvador 2007: All persons 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 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 This variable indicates the person's age (in completed years). IPUMS Identity card <svar a="all" v="SV07A404">3b. Do you have a national identity card?<br /><div class="i1">[Persons age 18 or older]<br />[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 18+ [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person has an identity card. IPUMS Month of birth <svar a="all" v="SV07A405 SV07A406 SV07A407 SV07A408">4. Date of birth:<br /><div class="i1">Day /_/_/<br />Month /_/_/<br />Year /_/_/_/_/</div><br /></svar> El Salvador 2007: All persons 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 Unknown This variable indicates the person's month of birth. IPUMS Year of birth <svar a="all" v="SV07A405 SV07A406 SV07A407 SV07A408">4. Date of birth:<br /><div class="i1">Day /_/_/<br />Month /_/_/<br />Year /_/_/_/_/</div><br /></svar> El Salvador 2007: All persons 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 This variable indicates the person's year of birth. IPUMS Limitations in movement or walking <svar v="SV07A409 SV07A410 SV07A411 SV07A412 SV07A413 SV07A414 SV07A415 SV07A416">5. Do you/does the person have any permanent limitation in:<br /></svar></p> <p><svar a="all" v=" SV07A409">Moving or walking<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons in private occupied dwellings [discrepancies: type I 0.3%; type II 1.3%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person has limitations in movement or walking. IPUMS Limited movement of hands or arms <svar v="SV07A409 SV07A410 SV07A411 SV07A412 SV07A413 SV07A414 SV07A415 SV07A416">5. Do you/does the person have any permanent limitation in:<br /></svar></p> <p><svar a="all" v="SV07A410">Using his/her/your arms or hands<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons in private occupied dwellings [discrepancies: type I 0.3%; type II 1.4%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person has limited movement of hands or arms. IPUMS Limited vision (even when using glasses) <svar v="SV07A409 SV07A410 SV07A411 SV07A412 SV07A413 SV07A414 SV07A415 SV07A416">5. Do you/does the person have any permanent limitation in:<br /></svar></p> <p><svar a="all" v="SV07A411">Seeing, even when using glasses<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons in private occupied dwellings [discrepancies: type I 0.3%; type II 1.4%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person has limited vision (even when using glasses). IPUMS Limited hearing (even when using hearing aids) <svar v="SV07A409 SV07A410 SV07A411 SV07A412 SV07A413 SV07A414 SV07A415 SV07A416">5. Do you/does the person have any permanent limitation in:<br /></svar></p> <p><svar a="all" v="SV07A412">Hearing, even when using hearing aids [<span class="lang">aparatos especiales</span>]<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons in private occupied dwellings [discrepancies: type I 0.3%; type II 1.4%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person has limited hearing (even when using hearing aids). IPUMS Limited speech <svar v="SV07A409 SV07A410 SV07A411 SV07A412 SV07A413 SV07A414 SV07A415 SV07A416">5. Do you/does the person have any permanent limitation in:<br /></svar></p> <p><svar a="all" v="SV07A413">Speaking<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons in private occupied dwellings [discrepancies: type I 0.3%; type II 1.4%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person has limited speech. IPUMS Mental disability <svar v="SV07A409 SV07A410 SV07A411 SV07A412 SV07A413 SV07A414 SV07A415 SV07A416">5. Do you/does the person have any permanent limitation in:<br /></svar></p> <p><svar a="all" v="SV07A414">Does the person have a mental delay or impairment?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons in private occupied dwellings [discrepancies: type I 0.3%; type II 1.5%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person has mental disability. IPUMS Limitations in self-care <svar v="SV07A409 SV07A410 SV07A411 SV07A412 SV07A413 SV07A414 SV07A415 SV07A416">5. Do you/does the person have any permanent limitation in:<br /></svar></p> <p><svar a="all" v="SV07A415">Bathing, dressing or eating without assistance<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons in private occupied dwellings [discrepancies: type I 0.3%; type II 1.5%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person has limitations in self-care. IPUMS Other permanent limitation <svar v="SV07A409 SV07A410 SV07A411 SV07A412 SV07A413 SV07A414 SV07A415 SV07A416">5. Do you/does the person have any permanent limitation in:<br /></svar></p> <p><svar a="all" v="SV07A415">Other permanent limitation<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons in private occupied dwellings [discrepancies: type I 0.3%; type II 1.7%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person has other permanent limitation. IPUMS Race <svar a="all" v="SV07A417">6a. Are you:<br /><div class="i1">[] 1 White<br />[] 2 Mixed race (a mix of white and indigenous)<br />[] 3 Indigenous (go to question 6b)<br />[] 4 Black (by race)<br />[] 5 Other</div><br /></svar> El Salvador 2007: All persons 1 White 2 Mestizo (mix of white and indigenous) 3 Indigenous 4 Black 5 Other This variable indicates the person's race. IPUMS Ethnic group <svar a="all" v="SV07A418">6b. If you are indigenous, what group do you belong to?<br /><div class="i1">[] 6 Lenca<br />[] 7 Kakawira (Cacaopera)<br />[] 8 Nahua-Pipil<br />[] 9 Other ___________________ (specify)</div><br /></svar> El Salvador 2007: Indigenous persons [discrepancies: none] 1 Lenca 2 Kakawira (Cacaopera) 3 Nahua-Pipil 4 Other 9 NIU (not in universe) This variable indicates the person's ethnic group. IPUMS Place of birth <svar a="all" v="SV07A419 SV07A420 SV07A421 SV07A422 SV07A423 SV07A470 SV07A471 SV07A472 SV07A473">7. Where was your mother living when you were born?<br /><div class="i1">A) In this municipal capital [<span class="lang">cabecera municipal</span>] or canton (go to question 8)<br />B) Someplace else in this country</div><br /><div class="i2">Municipal capital or canton ________________<br />Municipality ________________<br />Department ________________</div><br /><div class="i1">C) In another country</div><br /><div class="i2">Name of country______________<br />Year of arrival in El Salvador /_/_/_/_/</div><br /></svar> El Salvador 2007: All persons 1 Somewhere else 2 Here This variable indicates the person's place of birth. IPUMS Year of arrival in El Salvador <svar a="all" v="SV07A419 SV07A420 SV07A421 SV07A422 SV07A423 SV07A470 SV07A471 SV07A472 SV07A473">7. Where was your mother living when you were born?<br /><div class="i1">A) In this municipal capital [<span class="lang">cabecera municipal</span>] or canton (go to question 8)<br />B) Someplace else in this country</div><br /><div class="i2">Municipal capital or canton ________________<br />Municipality ________________<br />Department ________________</div><br /><div class="i1">C) In another country</div><br /><div class="i2">Name of country______________<br />Year of arrival in El Salvador /_/_/_/_/</div><br /></svar> El Salvador 2007: Persons born outside El Salvador [discrepancies: type I none; type II 0.3%] 1969 1969 or earlier 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 9998 Unknown 9999 NIU (not in universe) This variable indicates the person's year of arrival in El Salvador. IPUMS Whether always lived in the current municipality <svar a="all" v="SV07A424 SV07A425 SV07A426 SV07A427 SV07A428 SV07A474 SV07A475 SV07A476 SV07A477">8. How long have you lived in this municipal capital [<span class="lang">cabecera</span>] or canton?<br /><div class="i1">A)<br />[] 1 Always (go to question 9)<br />Since the year /_/_/_/_/<br />B)<br />[] 2 Where did you live before?<br />Municipal capital or canton______________<br />Municipality ________________<br />Department ________________<br />C)<br />[] 3 In another country<br />Name of country _______________</div><br /></svar> El Salvador 2007: All persons 1 No 2 Yes This variable indicates the person's duration of residence in El Salvador. IPUMS Year of arrival to current municipality <svar a="all" v="SV07A424 SV07A425 SV07A426 SV07A427 SV07A428 SV07A474 SV07A475 SV07A476 SV07A477">8. How long have you lived in this municipal capital [<span class="lang">cabecera</span>] or canton?<br /><div class="i1">A)<br />[] 1 Always (go to question 9)<br />Since the year /_/_/_/_/<br />B)<br />[] 2 Where did you live before?<br />Municipal capital or canton______________<br />Municipality ________________<br />Department ________________<br />C)<br />[] 3 In another country<br />Name of country _______________</div><br /></svar> El Salvador 2007: Persons who ever lived in another municipality [discrepancies: type I none; type II 1.6%] 1930 1930 or earlier 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 9998 Unknown 9999 NIU (not in universe) This variable indicates the person's year of arrival to current residence. IPUMS Can read and write <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A429">9. Do you know how to read and write?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 5+ [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person can read and write. IPUMS School attendance <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A431 SV07A432 SV07A433 SV07A434">11a. What is the last grade or highest school year passed?<br /><div class="i1">[] 1 Nursery/kindergarten (go to questions 11d.) ____<br />[] 2 Primary or basic (go to questions 11d.) ____<br />[] 3 Secondary education [<span class="lang">educación media</span>] ____<br />[] 4 Short course of studies after the sixth grade leading to a degree ____<br />[] 5 Non-university, higher education ____<br />[] 6 University-level technical studies [<span class="lang">técnico universitaria</span>] ____<br />[] 7 Advanced university [<span class="lang">superior universitaria</span>] ____<br />[] 8 Master's ____<br />[] 9 Doctorate ____</div><br />11b: Have you completed your high school, technical, university, master's or doctorate degree?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 5+ [discrepancies: none] 1 Currently attends 2 Doesn't attend, but attended 3 Never attended 9 NIU (not in universe) This variable indicates the person's school attendance. IPUMS Grade attending/attended <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A431 SV07A432 SV07A433 SV07A434">11a. What is the last grade or highest school year passed?<br /><div class="i1">[] 1 Nursery/kindergarten (go to questions 11d.) ____<br />[] 2 Primary or basic (go to questions 11d.) ____<br />[] 3 Secondary education [<span class="lang">educación media</span>] ____<br />[] 4 Short course of studies after the sixth grade leading to a degree ____<br />[] 5 Non-university, higher education ____<br />[] 6 University-level technical studies [<span class="lang">técnico universitaria</span>] ____<br />[] 7 Advanced university [<span class="lang">superior universitaria</span>] ____<br />[] 8 Master's ____<br />[] 9 Doctorate ____</div><br />11b: Have you completed your high school, technical, university, master's or doctorate degree?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 5+ who attend or ever attended school [discrepancies: none] 10 Preschool 0 11 Preschool 1 12 Preschool 2 13 Preschool 3 20 Primary 0 21 Primary 1 22 Primary 2 23 Primary 3 24 Primary 4 25 Primary 5 26 Primary 6 27 Primary 7 28 Primary 8 29 Primary 9 31 Middle education 1 [middle school and early high school] 32 Middle education 2 [middle school and early high school] 33 Middle education 3 [middle school and early high school] 34 Middle education 4 [middle school and early high school] 41 Short course of study [after sixth grade] 1 42 Short course of study [after sixth grade] 2 43 Short course of Study [after sixth grade] 3 51 Post-secondary non-university 1 52 Post-secondary non-university 2 53 Post-secondary non-university 3 54 Post-secondary non-university 4 55 Post-secondary non-university 5 56 Post-secondary non-university 6 57 Post-secondary non-university 7 58 Post-secondary non-university 8 59 Post-secondary non-university (not specified) 61 Technical college 1 62 Technical college 2 63 Technical college 3 71 University (undergraduate) 1 72 University (undergraduate) 2 73 University (undergraduate) 3 74 University (undergraduate) 4 75 University (undergraduate) 5 76 University (undergraduate) 6 77 University (undergraduate) 7 78 University (undergraduate) 8 79 University (undegraduate) (not specified) 81 Masters 1 82 Masters 2 83 Masters 3 91 Doctorate 1 to 5 99 NIU (not in universe) This variable indicates the grade at which the person is attending or attended. IPUMS Highest level of education passed <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A431 SV07A432 SV07A433 SV07A434">11a. What is the last grade or highest school year passed?<br /><div class="i1">[] 1 Nursery/kindergarten (go to questions 11d.) ____<br />[] 2 Primary or basic (go to questions 11d.) ____<br />[] 3 Secondary education [<span class="lang">educación media</span>] ____<br />[] 4 Short course of studies after the sixth grade leading to a degree ____<br />[] 5 Non-university, higher education ____<br />[] 6 University-level technical studies [<span class="lang">técnico universitaria</span>] ____<br />[] 7 Advanced university [<span class="lang">superior universitaria</span>] ____<br />[] 8 Master's ____<br />[] 9 Doctorate ____</div><br />11b: Have you completed your high school, technical, university, master's or doctorate degree?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 5+ who attend or ever attended school [discrepancies: none] 01 Preschool 02 Primary or basic education 03 Middle education [middle school and early high school] 04 Short course of study after sixth grade 05 Preparatory 06 Technical college 07 University (undergraduate) 08 Master 09 Doctorate 99 NIU (not in universe) This variable indicates the highest level of education the person has passed. IPUMS Last grade or year passed in this level <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A431 SV07A432 SV07A433 SV07A434">11a. What is the last grade or highest school year passed?<br /><div class="i1">[] 1 Nursery/kindergarten (go to questions 11d.) ____<br />[] 2 Primary or basic (go to questions 11d.) ____<br />[] 3 Secondary education [<span class="lang">educación media</span>] ____<br />[] 4 Short course of studies after the sixth grade leading to a degree ____<br />[] 5 Non-university, higher education ____<br />[] 6 University-level technical studies [<span class="lang">técnico universitaria</span>] ____<br />[] 7 Advanced university [<span class="lang">superior universitaria</span>] ____<br />[] 8 Master's ____<br />[] 9 Doctorate ____</div><br />11b: Have you completed your high school, technical, university, master's or doctorate degree?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 5+ who attend or ever attended school [discrepancies: type I none; type II 0.9%] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 99 NIU (not in universe) This variable indicates the last grade or year that the person passed in this level. IPUMS Study completed <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A431 SV07A432 SV07A433 SV07A434">11a. What is the last grade or highest school year passed?<br /><div class="i1">[] 1 Nursery/kindergarten (go to questions 11d.) ____<br />[] 2 Primary or basic (go to questions 11d.) ____<br />[] 3 Secondary education [<span class="lang">educación media</span>] ____<br />[] 4 Short course of studies after the sixth grade leading to a degree ____<br />[] 5 Non-university, higher education ____<br />[] 6 University-level technical studies [<span class="lang">técnico universitaria</span>] ____<br />[] 7 Advanced university [<span class="lang">superior universitaria</span>] ____<br />[] 8 Master's ____<br />[] 9 Doctorate ____</div><br />11b: Have you completed your high school, technical, university, master's or doctorate degree?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 5+ whose education level is above primary school [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person completed his or her studies. IPUMS Major/course of study <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A435 SV07A482">11c: What is the name of your major? ______________________<br /></svar> El Salvador 2007: Persons age 5+ whose education level is above primary school [discrepancies: none] 2310 Short course of study after sixth grade 3110 General high school diploma 3121 Commercial vocational high school degree 3122 Industrial vocational high school degree 3123 Agricultural vocational high school degree 3124 Health vocational high school degree 3211 Academic high school degree 3212 Administration and commerce degree 3213 Agricultural degree 3214 Arts degree 3215 Industrial degree 3216 Health degree 3217 Vocational degree 3218 Educational degree 3222 Hotel and tourism degree 4110 Professorate 4121 Agricultural science 4122 Economic science and related studies 4123 Engineering and architecture 4124 Naturals sciences and mathematics 4125 Health sciences 4126 Mechanics 4127 Social sciences and humanities 4128 Environmental study and related 4129 Other technical studies 4130 Military studies 4131 Public safety 5111 Doctorate degree in science and health 5112 Degree in social sciences, humanities and arts 5113 Law degree 5114 Degree in economic sciences 5115 Natural sciences and mathematics degree 5116 Degree in chemistry and pharmacy 5117 Degree in agricultural science 5118 Degree in science education 5119 Other degrees 5121 General engineering 5122 Agricultural sciences degree 5123 Engineering of naturals science and mathematics 5129 Other engineering 5130 Architecture 5141 Master of health sciences 5142 Master of natural sciences and mathematics 5143 Master of social sciences and humanities 5144 Master of economic sciences 5145 Master in engineering and architecture 5149 Other masters degrees 5210 Master of education 5221 Economic sciences and related studies 5222 Engineering and architecture 5223 Natural sciences and math 5224 Health sciences 5225 Mechanics 5226 Social sciences and humanities 5227 Agronomic sciences 5229 Other technical studies 6110 Doctorates 7110 Other studies 9999 NIU (not in universe) This variable indicates the person's major or course of study. IPUMS Speaks another language (besides Spanish) <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A436 SV07A437 SV07A483">11d. Do you speak another language in addition to Spanish?<br /><div class="i1">[] 1 Yes (specify) ______________<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 5+ who attend or ever attended school [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person speaks another language (besides Spanish). IPUMS Language spoken <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A436 SV07A437 SV07A483">11d. Do you speak another language in addition to Spanish?<br /><div class="i1">[] 1 Yes (specify) ______________<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 5+ who speak another language besides Spanish [discrepancies: none] 01 English 02 German 03 French 07 Portugese 08 Italian 98 Other 99 NIU (not in universe) This variable indicates another language spoken by the person. IPUMS Attending/attended vocational educational center <svar v="SV07A429 SV07A430 SV07A431 SV07A432 SV07A433 SV07A434 SV07A435 SV07A436 SV07A437">[Questions 9-12 are for persons age 5 or older]<br /></svar></p> <p><svar a="all" v="SV07A438">12. Do you or did you attend a vocational school in the non-formal educational system [<span class="lang">dentro de la educacion no formal</span>]?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 5+ [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person is attending or attended vocational educational center. IPUMS Marital status <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A439">13. What is your marital status?<br /><div class="i1">[] 1 Partnered [<span class="lang">acompañado</span>]<br />[] 2 Married<br />[] 3 Widowed<br />[] 4 Separated<br />[] 5 Divorced<br />[] 6 Single</div><br /></svar> El Salvador 2007: Persons age 10+ [discrepancies: type I none; type II 1.2%] 1 Partner 2 Married 3 Widowed 4 Separated 5 Divorced 6 Single 8 Unknown 9 NIU (not in universe) This variable indicates the person's marital status. IPUMS Has an email account <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A440">14. Do you have an email account?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 10+ [discrepancies: type I none; type II 2.6%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person owns an email account. IPUMS Support from abroad (cash or in-kind) <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="SV07A441" v="SV07A441 SV07A442">15: Did you receive help in cash or kind from a family member outside the country in the last 12 months?<br /><div class="i1">[] 1 Yes<br />The person who sent the help was:</div><br /><div class="i2">[] 1 Male<br />[] 2 Female</div><br /><div class="i1">[] 2 No</div><br /></svar> El Salvador 2007: Persons age 10+ [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person receives support from abroad (cash or in-kind). IPUMS Sex of the sender(s) of remittances <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="SV07A441" v="SV07A441 SV07A442">15: Did you receive help in cash or kind from a family member outside the country in the last 12 months?<br /><div class="i1">[] 1 Yes<br />The person who sent the help was:</div><br /><div class="i2">[] 1 Male<br />[] 2 Female</div><br /><div class="i1">[] 2 No</div><br /></svar> El Salvador 2007: Persons age 10+ who receive support from abroad [discrepancies: none] 1 Male 2 Female 3 Both 9 NIU (not in universe) This variable indicates the sex of the sender(s) of remittances. IPUMS Worked the previous week <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A443">16a. Did you work for payment in cash or kind during the week prior to the start of the census?<br /><div class="i1">[] 1 Yes (go to question 20)<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 10+ [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person worked the previous week. IPUMS Did not work for a justified reason (e.g. illness, strike, vacations, bad weather, etc.) <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A444">16b. Did you have a job, business, company, or your own farm, at which you did not work (for reasons of illness, strike, vacations, bad weather, etc.)?<br /><div class="i1">[] 1 Yes (go to question 20)<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 10+ who did not work last week [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person did not work last week for a justified reason. IPUMS Other type of work <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A445">16c. Even though you told me that you did not work, did you perform in or out of the house any of the following activities which brought you income in cash or in kind?<br /><div class="i1">[] 1 Selling articles such as clothes, flowers, lottery tickets, food, handicrafts, papers, candy, etc. (go to question 20)<br />[] 2 Shoemaking, plumbing, bricklaying, car washing, etc. (go to question 20)<br />[] 3 Making bread, tortillas, food and other items for sale (go to question 20)<br />[] 4 Washing, ironing, sewing or other domestic services (go to question 20)<br />[] 5 Helping with agricultural jobs (go to question 20)<br />[] 6 Other (specify) _______________ (go to question 20)<br />[] 7 No activity</div><br /></svar> El Salvador 2007: Persons age 10+ who did not work last week and have no justified reason [discrepancies: none] 1 Selling items such as: clothing, flowers, lottery tickets, food, handicrafts, newspapers, candy, etc. 2 Shoemaking, plumbing, construction, car washing, etc. 3 Making bread, tortillas, food and other items for sale 4 Washing, ironing, sewing and other domestic services 5 Assist with agricultural activities 6 Others 7 No activity 9 NIU (not in universe) This variable indicates the person's other type of work. IPUMS Look for work and ever worked before <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A446">17. Did you look for job and had already worked?<br /><div class="i1">[] 1 Yes (go to question 20)<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 10+ who did not work last week and had no other activity [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person looked for work and ever worked before. IPUMS Looked for work for the first time <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A447">18. Did you look for work for the first time?<br /><div class="i1">[] 1 Yes (go to Section 4)<br />[] 2 No</div><br /></svar> El Salvador 2007: Persons age 10+ who did not work last week, did not look for work, and never worked before [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person looked for work for the first time. IPUMS Reason did not work the previous week <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A448">19. Why didn't you work the week prior to the census?<br /><div class="i1">[] 1 Performed housework<br />[] 2 Is a full-time student<br />[] 3 Is retired, has a pension, or is living off investment income<br />[] 4 Imprisoned<br />[] 5 Permanent disability<br />[] 6 Other reasons (specify) __________</div><br />[Go to Section 4 if any of options 1-6 are marked]<br /></svar> El Salvador 2007: Persons age 10+ who did not work last week and did not look for work for the first time last week [discrepancies: none] 1 Housework 2 Full-time student 3 Retired, pensioned or rentier 4 In prison 5 Permanent disability that limits working 6 Other reason 9 NIU (not in universe) This variable indicates the reason that the person did not work the previous week. IPUMS Industry (3-digit) <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A449 SV07A484 SV07A487">20. What is your job or what do you or the company you work for or last worked for produce?<br /> <div class="i1">________</div><br /></svar> El Salvador 2007: Persons age 10+ who worked, did not work for a justified reason, or were experienced and looking for work last week [discrepancies: none] 011 Growing of crops; market gardening; horticulture 012 Farming of animals 013 Growing of crops combined with farming of animals (mixed farming) 014 Agricultural and animal husbandry service activities, except veterinary activities 020 Forestry, logging and related service activities 050 Fishing, aquaculture and service activities incidental to fishing 132 Mining of non-ferrous metal ores, except uranium and thorium ores 141 Quarrying of stone, sand and clay 142 Mining and quarrying nec 151 Production, processing and preservation of meat, fish, fruit, vegetables, oils and fats 152 Manufacture of dairy products 153 Manufacture of grain mill products, starches and starch products, and prepared animal feeds 154 Manufacture of other food products 155 Manufacture of beverages 160 Manufacture of tobacco products 171 Spinning, weaving and finishing of textiles 172 Manufacture of other textiles 173 Manufacture of knitted and crocheted fabrics and articles 181 Manufacture of wearing apparel, except fur apparel 182 Dressing and dyeing of fur; manufacture of articles of fur 191 Tanning and dressing of leather; manufacture of luggage, handbags, saddlery and harness 192 Manufacture of footwear 201 Sawmilling and planing of wood 202 Manufacture of products of wood, cork, straw and plaiting materials 210 Manufacture of paper and paper products 221 Publishing 222 Printing and service activities related to printing 223 Reproduction of recorded media 232 Manufacture of refined petroleum products 241 Manufacture of basic chemicals 242 Manufacture of other chemical products 251 Manufacture of rubber products 252 Manufacture of plastics products 261 Manufacture of glass and glass products 269 Manufacture of non-metallic mineral products nec 271 Manufacture of basic iron and steel 272 Manufacture of basic precious and non-ferrous metals 273 Casting of metals 281 Manufacture of structural metal products, tanks, reservoirs and steam generators 289 Manufacture of other fabricated metal products; metalworking service activities 291 Manufacture of general-purpose machinery 292 Manufacture of special-purpose machinery 293 Manufacture of domestic appliances nec 300 Manufacture of office, accounting and computing machinery 311 Manufacture of electric motors, generators and transformers 312 Manufacture of electricity distribution and control apparatus 313 Manufacture of insulated wire and cable 314 Manufacture of accumulators, primary cells and primary batteries 315 Manufacture of electric lamps and lighting equipment 319 Manufacture of other electrical equipment nec 321 Manufacture of electronic valves and tubes and other electronic components 322 Manufacture of television and radio transmitters and apparatus for telephones and line telegraphy 323 Manufacture of television and radio receivers, sound or video recording or reproducing apparatus, and associated goods 331 Manufacture of medical appliances and instruments and appliances for measuring, checking, testing, navigating and other purposes, except optical instruments 332 Manufacture of optical instruments and photographic equipment 341 Manufacture of motor vehicles 342 Manufacture of bodies (coachwork) for motor vehicles; manufacture of trailers and semi-trailers 343 Manufacture of parts and accessories for motor vehicles and their engines 351 Building and repairing of ships and boats 352 Manufacture of railway and tramway locomotives and rolling stock 353 Manufacture of aircraft and spacecraft 359 Manufacture of transport equipment nec 361 Manufacture of furniture 369 Manufacturing nec 371 Recycling of metal waste and scrap 372 Recycling of non-metal waste and scrap 401 Production, transmission and distribution of electricity 410 Collection, purification and distribution of water 451 Site preparation 452 Building of complete constructions or parts thereof; civil engineering 453 Building installation 454 Building completion 455 Renting of construction or demolition equipment with operator 501 Sale of motor vehicles 502 Maintenance and repair of motor vehicles 503 Sale of motor vehicle parts and accessories 504 Sale, maintenance and repair of motorcycles and related parts and accessories 505 Retail sale of automotive fuel 511 Wholesale on a fee or contract basis 512 Wholesale of agricultural raw materials, live animals, food, beverages and tobacco 513 Wholesale of household goods 514 Wholesale of non-agricultural intermediate products, waste and scrap 515 Wholesale of machinery, equipment and supplies 519 Other wholesale 521 Non-specialized retail trade in stores 522 Retail sale of food, beverages and tobacco in specialized stores 523 Other retail trade of new goods in specialized stores 524 Retail sale of second-hand goods in stores 525 Retail trade not in stores 526 Repair of personal and household goods 551 Hotels; camping sites and other provision of short-stay accommodation 552 Restaurants, bars and canteens 601 Transport via railways 602 Other land transport 611 Sea and coastal water transport 612 Inland water transport 621 Scheduled air transport 622 Non-scheduled air transport 630 Supporting and auxiliary transport activities; activities of travel agencies 641 Post and courier activities 642 Telecommunications 651 Monetary intermediation 659 Other financial intermediation 660 Insurance and pension funding, except compulsory social security 671 Activities auxiliary to financial intermediation, except insurance and pension funding 672 Activities auxiliary to insurance and pension funding 701 Real estate activities with own or leased property 702 Real estate activities on a fee or contract basis 711 Renting of transport equipment 712 Renting of other machinery and equipment 713 Renting of personal and household goods nec 721 Hardware consultancy 722 Software publishing, consultancy and supply 723 Data processing 724 Database activities and online distribution of electronic content 725 Maintenance and repair of office, accounting and computing machinery 729 Other computer-related activities 731 Research and experimental development on natural sciences and engineering (NSE) 732 Research and experimental development on social sciences and humanities (SSH) 741 Legal, accounting, bookkeeping and auditing activities; tax consultancy; market research and public opinion polling; business and management consultancy 742 Architectural, engineering and other technical activities 743 Advertising 749 Business activities nec 751 Administration of the State and the economic and social policy of the community 752 Provision of services to the community as a whole 753 Compulsory social security activities 801 Primary education 802 Secondary education 803 Higher education 809 Other education 851 Human health activities 852 Veterinary activities 853 Social work activities 900 Sewage and refuse disposal, sanitation and similar activities 911 Activities of business, employers and professional organizations 912 Activities of trade unions 919 Activities of other membership organizations 921 Motion picture, radio, television and other entertainment activities 922 News agency activities 923 Library, archives, museums and other cultural activities 924 Sporting and other recreational activities 930 Other service activities 950 Activities of private households as employers of domestic staff 990 Extraterritorial organizations and bodies 999 NIU (not in universe) This variable indicates the industry in which the person worked. IPUMS Occupation (3-digit) <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A450 SV07A485 SV07A486">21. What is the occupation, job or position which you perform or used to perform at work?<br /><div class="i1">________</div><br /></svar> El Salvador 2007: Persons age 10+ who worked, did not work for a justified reason, or were experienced and looking for work last week [discrepancies: none] 011 Armed forces 111 Legislators 112 Senior government officials 113 Traditional chiefs and heads of villages 121 Directors and chief executives 122 Production and operations department managers 123 Other department managers 131 General managers 211 Physicists, chemists and related professionals 212 Mathematicians, statisticians and related professionals 213 Computing professionals 214 Architects, engineers and related professionals 221 Life science professionals 222 Health professionals (except nursing) 223 Nursing and midwifery professionals 231 College, university and higher education teaching professionals 232 Secondary education teaching professionals 233 Primary and pre-primary education teaching professionals 234 Special education teaching professionals 235 Other teaching professionals 241 Business professionals 242 Legal professionals 243 Archivists, librarians and related information professionals 244 Social science and related professionals 245 Writers and creative or performing artists 246 Religious professionals 311 Physical and engineering science technicians 312 Computer associate professionals 313 Optical and electronic equipment operators 314 Ship and aircraft controllers and technicians 315 Safety and quality inspectors 321 Life science technicians and related associate professionals 322 Modern health associate professionals (except nursing) 323 Nursing and midwifery associate professionals 324 Traditional medicine practitioners and faith healers 331 Primary education teaching associate professionals 332 Pre-primary education teaching associate professionals 333 Special education teaching associate professionals 334 Other teaching associate professionals 341 Finance and sales associate professionals 342 Business services agents and trade brokers 343 Administrative associate professionals 344 Customs, tax and related government associate professionals 345 Police inspectors and detectives 346 Social work associate professionals 347 Artistic, entertainment and sports associate professionals 348 Religious associate professionals 411 Secretaries and keyboard-operating clerks 412 Numerical clerks 413 Material-recording and transport clerks 414 Library, mail and related clerks 419 Other office clerks 421 Cashiers, tellers and related clerks 422 Client information clerks 511 Travel attendants and related workers 512 Housekeeping and restaurant services workers 513 Personal care and related workers 514 Other personal services workers 516 Protective services workers 521 Fashion and other models 522 Shop salespersons and demonstrators 523 Stall and market salespersons 611 Market gardeners and crop growers 612 Market-oriented animal producers and related workers 613 Market-oriented crop and animal producers 614 Forestry and related workers 615 Fishery workers, hunters and trappers 621 Subsistence agricultural and fishery workers 711 Miners, shotfirers, stone cutters and carvers 712 Building frame and related trades workers 713 Building finishers and related trades workers 714 Painters, building structure cleaners and related trades workers 721 Metal moulders, welders, sheet-metal workers, structural- metal preparers, and related trades workers 722 Blacksmiths, tool-makers and related trades workers 723 Machinery mechanics and fitters 724 Electrical and electronic equipment mechanics and fitters 731 Precision workers in metal and related materials 732 Potters, glass-blowers, -moulders, -cutters, glass etchers, glass painters, ceramics painters, painters of other materials, and related workers 733 Handicraft workers in wood, textile, leather and related materials 734 Compositors, typesetters, stereotypists, electrotypists, printing engravers and etchers, photography operators, bookbinders, screen printers and related workers 741 Food processing and related trades workers 742 Wood treaters, cabinet-makers and related trades workers 743 Textile, garment and related trades workers 744 Pelt, leather and shoemaking trades workers 811 Mining- and mineral-processing-plant operators 812 Metal-processing-plant operators 813 Glass, ceramics and related plant operators 814 Wood-processing- and papermaking-plant operators 815 Chemical-processing-plant operators 816 Power-production and related plant operators 821 Metal- and mineral-products machine operators 822 Chemical-products machine operators 823 Rubber- and plastic-products machine operators 824 Wood-products machine operators 825 Printing-, binding- and paper-products machine operators 826 Textile-, fur- and leather-products machine operators 827 Food and related products machine operators 828 Assemblers 829 Other machine operators and assemblers 831 Railway engine machinists, brakers, and switch operators 832 Motor-vehicle drivers 833 Agricultural and other mobile-plant operators 834 Ships' deck crews and related workers 911 Street vendors and related workers 912 Shoe cleaning and other street services elementary occupations 913 Domestic and related helpers, cleaners and launderers 914 Building caretakers, window and related cleaners 915 Messengers, porters, doorkeepers and related workers 916 Garbage collectors and related labourers 921 Agricultural, fishery and related labourers 931 Mining and construction labourers 932 Manufacturing labourers 933 Transport labourers and freight handlers 999 NIU (not in universe) This variable indicates the person's occupation (3-digit). IPUMS Work situation in the previous week <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A451">22. Are you or were you the following in this job:<br /><div class="i1">[] 1 Employee or worker in the public sector<br />[] 2 Employee or worker in the private sector<br />[] 3 Boss or employer<br />[] 4 Unpaid family worker<br />[] 5 Unpaid non-family worker<br />[] 6 Independent worker (self-employed)<br />[] 7 Domestic employee</div><br /></svar> El Salvador 2007: Persons age 10+ who worked, did not work for a justified reason, or were experienced and looking for work last week [discrepancies: none] 1 Employee or worker in the public sector 2 Employee or worker in the private sector 3 Owner or employer 4 Family worker without pay 5 Non-family worker without pay 6 Self-employed worker 7 Domestic worker 9 NIU (not in universe) This variable indicates the person's employment status in the previous week. IPUMS Total hours worked in the previous week <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A452">23. How many total hours did you work in the week prior to the beginning of the census, or in your last job? /_/_/<br /></svar> El Salvador 2007: Persons age 10+ who worked, did not work for a justified reason, or were experienced and looking for work last week [discrepancies: none] 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 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 NIU (not in universe) This variable indicates the number of total hours that the person worked in the previous week. IPUMS Location of the workplace <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A453 SV07A454 SV07A455 SV07A456 SV07A478 SV07A479 SV07A480 SV07A481">24. What is the location of the business, company or place where you worked in the week prior to the beginning of the census?<br /><div class="i1">A) In this municipal capital [<span class="lang">cabecera</span>] or canton (go to section 4)<br />B) Some other place in this country</div><br /><div class="i2">Municipality____________<br />Department_____________</div><br /><div class="i1">C) In another country</div><br /><div class="i2">Name of country______________</div><br />End the interview if the respondent is a male or a girl between the ages of 0 and 11.<br /></svar> El Salvador 2007: Persons age 10+ who worked, did not work for a justified reason, or were experienced and looking for work last week [discrepancies: type I none; type II 7.8%] Somewhere else 1 Here 9 NIU (not in universe) This variable indicates the location of the person's workplace. IPUMS Ever gave birth <svar v="SV07A458 SV07A459 SV07A460 SV07A461 SV07A462 SV07A463 SV07A464 SV07A465 SV07A466 SV07A467">[Questions 25-30 are for females age 12 or older]<br /></svar></p> <p><svar a="all" v="SV07A458">25. Have you had a live-born child?<br /><div class="i1">[] 1 Yes<br />[] 2 No (end the interview)</div><br /></svar> El Salvador 2007: Females age 12+ [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person ever gave birth. IPUMS Number of male children ever born <svar v="SV07A458 SV07A459 SV07A460 SV07A461 SV07A462 SV07A463 SV07A464 SV07A465 SV07A466 SV07A467">[Questions 25-30 are for females age 12 or older]<br /></svar></p> <p><svar a="all" v="SV07A459 SV07A460">26. How many live-born children have you had?<br /><div class="i1">Males /_/_/<br />Females /_/_/</div><br /></svar> El Salvador 2007: Females age 12+ who ever gave birth [discrepancies: type I none; type II trace] 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+ 98 Unknown 99 NIU (not in universe) This variable indicates the number of male children ever born. IPUMS Number of female children ever born <svar v="SV07A458 SV07A459 SV07A460 SV07A461 SV07A462 SV07A463 SV07A464 SV07A465 SV07A466 SV07A467">[Questions 25-30 are for females age 12 or older]<br /></svar></p> <p><svar a="all" v="SV07A459 SV07A460">26. How many live-born children have you had?<br /><div class="i1">Males /_/_/<br />Females /_/_/</div><br /></svar> El Salvador 2007: Females age 12+ who ever gave birth [discrepancies: type I none; type II trace] 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+ 98 Unknown 99 NIU (not in universe) This variable indicates the number of female children ever born. IPUMS Number of children in the household <svar v="SV07A458 SV07A459 SV07A460 SV07A461 SV07A462 SV07A463 SV07A464 SV07A465 SV07A466 SV07A467">[Questions 25-30 are for females age 12 or older]<br /></svar></p> <p><svar a="all" v="SV07A461">27. How many of your children currently live with you? /_/_/<br /></svar> El Salvador 2007: Females age 12+ who ever gave birth [discrepancies: type I none; type II 0.6%] 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+ 98 Unknown 99 NIU (not in universe) This variable indicates the number of children in the household. IPUMS Number of children that have died <svar v="SV07A458 SV07A459 SV07A460 SV07A461 SV07A462 SV07A463 SV07A464 SV07A465 SV07A466 SV07A467">[Questions 25-30 are for females age 12 or older]<br /></svar></p> <p><svar a="all" v="SV07A462">28. How many of the live-born children have died? /_/_/<br /></svar> El Salvador 2007: Females age 12+ who ever gave birth [discrepancies: type I none; type II 1.2%] 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+ 98 Unknown 99 NIU (not in universe) This variable indicates the number of children that have died. IPUMS Month of birth of last born child <svar v="SV07A458 SV07A459 SV07A460 SV07A461 SV07A462 SV07A463 SV07A464 SV07A465 SV07A466 SV07A467">[Questions 25-30 are for females age 12 or older]<br /></svar></p> <p><svar a="all" v="SV07A463 SV07A464 SV07A465 SV07A466">29. What was the date of birth of your last child?<br /><div class="i1">Day /_/_/<br />Month /_/_/<br />Year /_/_/_/</div><br /></svar> El Salvador 2007: Females age 12+ who ever gave birth [discrepancies: type I none; type II 1.7%] 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) This variable indicates the month of birth of the person's last born child. IPUMS Year of birth of last born child <svar v="SV07A458 SV07A459 SV07A460 SV07A461 SV07A462 SV07A463 SV07A464 SV07A465 SV07A466 SV07A467">[Questions 25-30 are for females age 12 or older]<br /></svar></p> <p><svar a="all" v="SV07A463 SV07A464 SV07A465 SV07A466">29. What was the date of birth of your last child?<br /><div class="i1">Day /_/_/<br />Month /_/_/<br />Year /_/_/_/</div><br /></svar> El Salvador 2007: Females age 12+ who ever gave birth [discrepancies: type I none; type II 1.4%] 1940 1940 or earlier 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 9998 Unknown 9999 NIU (not in universe) This variable indicates the year of birth of the person's last born child. IPUMS Last born child alive <svar v="SV07A458 SV07A459 SV07A460 SV07A461 SV07A462 SV07A463 SV07A464 SV07A465 SV07A466 SV07A467">[Questions 25-30 are for females age 12 or older]<br /></svar></p> <p><svar a="all" v="SV07A467">30. Is your last child alive?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> El Salvador 2007: Females age 12+ who ever gave birth [discrepancies: type I none; type II 0.8%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person's last born child is alive. IPUMS Status in economic activity El Salvador 2007: Persons age 10+ [discrepancies: none] 1 Employed 2 Unemployed 3 Applying for work 4 Not active 9 NIU (not in universe) This variable indicates the person's economic activity status. IPUMS Department of birth <svar a="all" v="SV07A419 SV07A420 SV07A421 SV07A422 SV07A423 SV07A470 SV07A471 SV07A472 SV07A473">7. Where was your mother living when you were born?<br /><div class="i1">A) In this municipal capital [<span class="lang">cabecera municipal</span>] or canton (go to question 8)<br />B) Someplace else in this country</div><br /><div class="i2">Municipal capital or canton ________________<br />Municipality ________________<br />Department ________________</div><br /><div class="i1">C) In another country</div><br /><div class="i2">Name of country______________<br />Year of arrival in El Salvador /_/_/_/_/</div><br /></svar> El Salvador 2007: Persons who were born in another place within El Salvador [discrepancies: none] 01 Ahuachapán 02 Santa Ana 03 Sonsonate 04 Chalatenango 05 La Libertad 06 San Salvador 07 Cuscatlán 08 La Paz 09 Cabañas 10 San Vicente 11 Usulután 12 San Miguel 13 Morazán 14 La Unión 99 NIU (not in universe) This variable indicates the person's department of birth. IPUMS Place of birth <svar a="all" v="SV07A419 SV07A420 SV07A421 SV07A422 SV07A423 SV07A470 SV07A471 SV07A472 SV07A473">7. Where was your mother living when you were born?<br /><div class="i1">A) In this municipal capital [<span class="lang">cabecera municipal</span>] or canton (go to question 8)<br />B) Someplace else in this country</div><br /><div class="i2">Municipal capital or canton ________________<br />Municipality ________________<br />Department ________________</div><br /><div class="i1">C) In another country</div><br /><div class="i2">Name of country______________<br />Year of arrival in El Salvador /_/_/_/_/</div><br /></svar> El Salvador 2007: All persons 1 In this municipality or town 2 In another place in this country 3 In another country This variable indicates the person's place of birth. IPUMS Municipality of birth <svar a="all" v="SV07A419 SV07A420 SV07A421 SV07A422 SV07A423 SV07A470 SV07A471 SV07A472 SV07A473">7. Where was your mother living when you were born?<br /><div class="i1">A) In this municipal capital [<span class="lang">cabecera municipal</span>] or canton (go to question 8)<br />B) Someplace else in this country</div><br /><div class="i2">Municipal capital or canton ________________<br />Municipality ________________<br />Department ________________</div><br /><div class="i1">C) In another country</div><br /><div class="i2">Name of country______________<br />Year of arrival in El Salvador /_/_/_/_/</div><br /></svar> El Salvador 2007: Persons who were born in another place within El Salvador [discrepancies: none] 0101 Ahuachapan 0102 Apaneca 0103 Atiquizaya 0104 Concepcion de Ataco 0105 El Refugio 0106 Guaymango 0107 Jujutla 0108 San Francisco Menendez 0109 San Lorenzo 0110 San Pedro Puxtla 0111 Tacuba 0112 Turin 0201 Candelaria de la Frontera 0202 Coatepeque 0203 Chalchuapa 0204 El Congo 0205 El Porvenir 0206 Masahuat 0207 Metapan 0208 San Antonio Pajonal 0209 San Sebastian Salitrillo 0210 Santa Ana 0211 Santa Rosa Guachipilin 0212 Santiago de la Frontera 0213 Texistepeque 0301 Acajutla 0302 Armenia 0303 Caluco 0304 Cuisnahuat 0305 Santa Isabel Ishuatan 0306 Izalco 0307 Juayua 0308 Nahuizalco 0309 Nahulingo 0310 Salcoatitan 0311 San Antonio del Monte 0312 San Julian 0313 Santa Catarina Masahuat 0314 Santo Domingo de Guzman 0315 Sonsonate 0316 Sonzacate 0401 Agua Caliente 0402 Arcatao 0403 Azacualpa 0404 Citala 0405 Comalapa 0406 Concepcion Quezaltepeque 0407 Chalatenango 0408 Dulce Nombre de Maria 0409 El Carrizal 0410 El Paraiso 0411 La Laguna 0412 La Palma 0413 La Reina 0414 Las Vueltas 0415 Nombre de Jesus 0416 Nueva Concepcion 0417 Nueva Trinidad 0418 Ojos de Agua 0419 Potonico 0420 San Antonio de la Cruz 0421 San Antonio los Ranchos 0422 San Fernando 0423 San Francisco Lempa 0424 San Francisco Morazan 0425 San Ignacio 0426 San Isidro Labrador 0427 Cancasque 0428 Las Flores 0429 San Luis del Carmen 0430 San Miguel de Mercedes 0431 San Rafael 0432 Santa Rita 0433 Tejutla 0501 Antiguo Cuscatlan 0502 Ciudad Arce 0503 Colon 0504 Comasagua 0505 Chiltiupan 0506 Huizucar 0507 Jayaque 0508 Jicalapa 0509 La Libertad 0510 Nuevo Cuscatlan 0511 Santa Tecla 0512 Quezaltepeque 0513 Sacacoyo 0514 San Jose Villanueva 0515 San Juan Opico 0516 San Matias 0517 San Pablo Tacachico 0518 Tamanique 0519 Talnique 0520 Teotepeque 0521 Tepecoyo 0522 Zaragoza 0601 Aguilares 0602 Apopa 0603 Ayutuxtepeque 0604 Cuscatancingo 0605 El Paisnal 0606 Guazapa 0607 Ilopango 0608 Mejicanos 0609 Nejapa 0610 Panchimalco 0611 Rosario de Mora 0612 San Marcos 0613 San Martin 0614 San Salvador 0615 Santiago Texacuangos 0616 Santo Tomas 0617 Soyapango 0618 Tonacatepeque 0619 Ciudad Delgado 0701 Candelaria 0702 Cojutepeque 0703 El Carmen 0704 El Rosario 0705 Monte San Juan 0706 Oratorio de Concepcion 0707 San Bartolome Perulapia 0708 San Cristobal 0709 San Jose Guayabal 0710 San Pedro Perulapan 0711 San Rafael Cedros 0712 San Ramon 0713 Santa Cruz Analquito 0714 Santa Cruz Michapa 0715 Suchitoto 0716 Tenancingo 0801 Cuyultitan 0802 El Rosario 0803 Jerusalen 0804 Mercedes la Ceiba 0805 Olocuilta 0806 Paraiso de Osorio 0807 San Antonio Masahuat 0808 San Emigdio 0809 San Francisco Chinameca 0810 San Juan Nonualco 0811 San Juan Talpa 0812 San Juan Tepezontes 0813 San Luis Talpa 0814 San Miguel Tepezontes 0815 San Pedro Masahuat 0816 San Pedro Nonualco 0817 San Rafael Obrajuelo 0818 Santa Maria Ostuma 0819 Santiago Nonualco 0820 Tapalhuaca 0821 Zacatecoluca 0822 San Luis la Herradura 0901 Cinquera 0902 Guacotecti 0903 Ilobasco 0904 Jutiapa 0905 San Isidro 0906 Sensuntepeque 0907 Tejutepeque 0908 Victoria 0909 Dolores 1001 Apastepeque 1002 Guadalupe 1003 San Cayetano Istepeque 1004 Santa Clara 1005 Santo Domingo 1006 San Esteban Catarina 1007 San Ildefonso 1008 San Lorenzo 1009 San Sebastian 1010 San Vicente 1011 Tecoluca 1012 Tepetitan 1013 Verapaz 1101 Alegria 1102 Berlin 1103 California 1104 Concepcion Batres 1105 El Triunfo 1106 Ereguayquin 1107 Estanzuelas 1108 Jiquilisco 1109 Jucuapa 1110 Jucuaran 1111 Mercedes Umaña 1112 Nueva Granada 1113 Ozatlan 1114 Puerto el Triunfo 1115 San Agustin 1116 San Buena Ventura 1117 San Dionisio 1118 Santa Elena 1119 San Francisco Javier 1120 Santa Maria 1121 Santiago de Maria 1122 Tecapan 1123 Usulutan 1201 Carolina 1202 Ciudad Barrios 1203 Comacaran 1204 Chapeltique 1205 Chinameca 1206 Chirilagua 1207 El Transito 1208 Lolotique 1209 Moncagua 1210 Nueva Guadalupe 1211 Nuevo Eden de San Juan 1212 Quelepa 1213 San Antonio 1214 San Gerardo 1215 San Jorge 1216 San Luis de la Reina 1217 San Miguel 1218 San Rafael Oriente 1219 Sesori 1220 Uluazapa 1301 Arambala 1302 Cacaopera 1303 Corinto 1304 Chilanga 1305 Delicias de Concepcion 1306 El Divisadero 1307 El Rosario 1308 Gualococti 1309 Guatajiagua 1310 Joateca 1311 Jocoaitique 1312 Jocoro 1313 Lolotiquillo 1314 Meanguera 1315 Oscicala 1316 Perquin 1317 San Carlos 1318 San Fernando 1319 San Francisco Gotera 1320 San Isidro 1321 San Simon 1322 Sensembra 1323 Sociedad 1324 Torola 1325 Yamabal 1326 Yoloaiquin 1401 Anamoros 1402 Bolivar 1403 Concepcion de Oriente 1404 Conchagua 1405 El carmen 1406 El Sauce 1407 Intipuca 1408 La Union 1409 Lislique 1410 Meanguera del Golfo 1411 Nueva Esparta 1412 Pasaquina 1413 Poloros 1414 San Alejo 1415 San Jose 1416 Santa Rosa de Lima 1417 Yayantique 1418 Yucuaiquin 9999 NIU (not in universe) This variable indicates the person's municipality of birth. IPUMS Country of birth <svar a="all" v="SV07A419 SV07A420 SV07A421 SV07A422 SV07A423 SV07A470 SV07A471 SV07A472 SV07A473">7. Where was your mother living when you were born?<br /><div class="i1">A) In this municipal capital [<span class="lang">cabecera municipal</span>] or canton (go to question 8)<br />B) Someplace else in this country</div><br /><div class="i2">Municipal capital or canton ________________<br />Municipality ________________<br />Department ________________</div><br /><div class="i1">C) In another country</div><br /><div class="i2">Name of country______________<br />Year of arrival in El Salvador /_/_/_/_/</div><br /></svar> El Salvador 2007: Persons who were born abroad [discrepancies: none] 076 Brazil 152 Chile 156 China 170 Colombia 188 Costa rica 320 Guatemala 340 Honduras 380 Italy 484 Mexico 558 Nicaragua 591 Panama 604 Peru 724 Spain 840 United states 862 Venezuela 990 Other country 998 Unknown 999 NIU (not in universe) This variable indicates the person's country of birth. IPUMS Department of previous residence <svar a="all" v="SV07A424 SV07A425 SV07A426 SV07A427 SV07A428 SV07A474 SV07A475 SV07A476 SV07A477">8. How long have you lived in this municipal capital [<span class="lang">cabecera</span>] or canton?<br /><div class="i1">A)<br />[] 1 Always (go to question 9)<br />Since the year /_/_/_/_/<br />B)<br />[] 2 Where did you live before?<br />Municipal capital or canton______________<br />Municipality ________________<br />Department ________________<br />C)<br />[] 3 In another country<br />Name of country _______________</div><br /></svar> El Salvador 2007: Persons who lived in another place within El Salvador [discrepancies: none] 01 Ahuachapán 02 Santa Ana 03 Sonsonate 04 Chalatenango 05 La Libertad 06 San Salvador 07 Cuscatlán 08 La Paz 09 Cabañas 10 San Vicente 11 Usulután 12 San Miguel 13 Morazán 14 La Unión 99 NIU (not in universe) This variable indicates the department of the person's previous residence. IPUMS Place of previous residence <svar a="all" v="SV07A424 SV07A425 SV07A426 SV07A427 SV07A428 SV07A474 SV07A475 SV07A476 SV07A477">8. How long have you lived in this municipal capital [<span class="lang">cabecera</span>] or canton?<br /><div class="i1">A)<br />[] 1 Always (go to question 9)<br />Since the year /_/_/_/_/<br />B)<br />[] 2 Where did you live before?<br />Municipal capital or canton______________<br />Municipality ________________<br />Department ________________<br />C)<br />[] 3 In another country<br />Name of country _______________</div><br /></svar> El Salvador 2007: All persons 1 In this municipality or town 2 In another place in the country 3 In another country This variable indicates the person's place of residence. IPUMS Country of previous residence <svar a="all" v="SV07A424 SV07A425 SV07A426 SV07A427 SV07A428 SV07A474 SV07A475 SV07A476 SV07A477">8. How long have you lived in this municipal capital [<span class="lang">cabecera</span>] or canton?<br /><div class="i1">A)<br />[] 1 Always (go to question 9)<br />Since the year /_/_/_/_/<br />B)<br />[] 2 Where did you live before?<br />Municipal capital or canton______________<br />Municipality ________________<br />Department ________________<br />C)<br />[] 3 In another country<br />Name of country _______________</div><br /></svar> El Salvador 2007: Persons who lived abroad [discrepancies: none] 084 Belize 124 Canada 156 China 170 Colombia 188 Costa Rica 320 Guatemala 340 Honduras 484 Mexico 558 Nicaragua 591 Panama 724 Spain 840 United States of America 862 Venezuela 900 Other country 998 Unknown 999 NIU (not in universe) This variable indicates the country of the person's previous residence. IPUMS Department of work in previous week <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A453 SV07A454 SV07A455 SV07A456 SV07A478 SV07A479 SV07A480 SV07A481">24. What is the location of the business, company or place where you worked in the week prior to the beginning of the census?<br /><div class="i1">A) In this municipal capital [<span class="lang">cabecera</span>] or canton (go to section 4)<br />B) Some other place in this country</div><br /><div class="i2">Municipality____________<br />Department_____________</div><br /><div class="i1">C) In another country</div><br /><div class="i2">Name of country______________</div><br />End the interview if the respondent is a male or a girl between the ages of 0 and 11.<br /></svar> El Salvador 2007: Persons age 10+ who worked in another place in El Salvador [discrepancies: none] 01 Ahuachapán 02 Santa Ana 03 Sonsonate 04 Chalatenango 05 La Libertad 06 San Salvador 07 Cuscatlán 08 La Paz 09 Cabañas 10 San Vicente 11 Usulután 12 San Miguel 13 Morazán 14 La Unión 99 NIU (not in universe) This variable indicates the department of the person's work in previous week. IPUMS Place of work in previous week <svar v="SV07A439 SV07A440 SV07A441 SV07A442 SV07A443 SV07A444 SV07A445 SV07A456">[Questions 13-24 are for persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SV07A453 SV07A454 SV07A455 SV07A456 SV07A478 SV07A479 SV07A480 SV07A481">24. What is the location of the business, company or place where you worked in the week prior to the beginning of the census?<br /><div class="i1">A) In this municipal capital [<span class="lang">cabecera</span>] or canton (go to section 4)<br />B) Some other place in this country</div><br /><div class="i2">Municipality____________<br />Department_____________</div><br /><div class="i1">C) In another country</div><br /><div class="i2">Name of country______________</div><br />End the interview if the respondent is a male or a girl between the ages of 0 and 11.<br /></svar> El Salvador 2007: Persons age 10+ who worked, did not work for a justified reason, or were experienced and looking for work last week [discrepancies: none] 1 In this municipality or town 2 In another place in the country 3 In another country 9 NIU (not in universe) This variable indicates the person's place of work in previous week. IPUMS