XIII National Population and II Housing Census 1964 DDI_COL_1964_PHC_v01_M_v7.6_A_IPUMS IPUMS

Integrated Public Use Microdata Series (IPUMS) International

 IPUMS April 1, 2025 IPUMS, 50 Willey Hall, 225 - 19th Avenue South, Minneapolis, MN 55455 Organization for Economic Co-operation and Development, Development Co-operation Directorate JADE#:60525;MEHLB(2010)12 IPUMS Version 7.6 October 2025 : NEW FEATURES. --NO "new features" listed in Revision History NEW SAMPLES. --Six new census samples for Honduras (2013), Kenya (2019), Malawi (2018), Mongolia (2010, 2020), and Mozambique (2017) were added to the data series. All census samples extend pre-existing series for those countries. --91 quarterly labor force surveys from the Philippines (1997 - 2019) were added to IPUMS. SUPPLEMENTAL DATA. --No "supplemental data" listed in revision history NEW VARIABLES. --New spatially harmonized birthplace and previous-residence variables are available for samples in this data release. More information is available here (https://international.ipums.org/international/geo_mig.shtml). --Users should note that many older migration and birthplace variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. For birthplace variables refer to this table (https://international.ipums.org/international/resources/misc_docs/migCrosswalk_names.pdf). EDITED SAMPLES. --For the Zambia 2000 sample, an error in the household breaks was corrected, resulting in the creation of 1,988 new households (1% increase) that were previously combined with other households. The person records included in the sample did not change. Due to an inconsistency in the original file, no household-level information other than geographic location is available for these newly identified households, necessitating the addition of "unknown" values for this sample to the following variables: BEDROOMS, ELECTRIC, FLOOR, FUELCOOK, FUELHEAT, OWNERSHIP, PHONE, RADIO, REFRIG, ROOMS, SEWAGE, TRASH, WATSRC, TV, TOILET, GQ, ROOF, WATSUP, BIKE, MOTORCYCLE, KITCHEN, GQTYPE, AUTOS, and WALL. EDITED VARIABLES. --For the 1998 and 2008 Malawi samples, the family interrelationship pointer variables MOMLOC and POPLOC were modified to allow a "Spouse/partner" of the household head to be linked as a parent to an "Other relative", because the enumeration instructions specify that adopted and stepchildren were categorized as "Other relative". These samples are now consistent with the links made in the newly released 2018 Malawi sample, which had the same enumeration instructions for adopted and stepchildren. --In the samples for Côte d'Ivoire 1988 and 1998, Rwanda 1991 and 2002, Togo 1960 and 2010, and South Africa 2001, for the harmonized variable POLYGAM, persons in consensual unions were previously coded as "No, in monogamous union". Because there was no response option in these samples for polygamous consensual unions, it is more appropriate to treat these cases as not-in-universe, so they have been recoded to "NIU (not in universe)". --MARST has been edited for Honduras 1974 to reclassify the source variable responses "married, wife lives separately" and "consensual union, companion lives separately" as separations. The documentation suggests that "separately" actually indicates a relationship separation and not an absent spouse or companion. Other minor edits were implemented for MARST for Mozambique 1997 and 2007. --In the Mozambique 1997 sample, an error was corrected that recoded persons with a relationship of "Unknown" in the source data to "Other relative or non-relative" (6000) in the harmonized variable RELATE. These persons are now coded as "Not Stated/Unknown" (9999). --In the Malawi 1987, 1998, and 2008 samples, for variable WATSUP, a programming error was corrected such that any households who reported having piped water in either the wet or the dry season are classified as having access to piped water. This programming was also applied to the newly released 2018 sample. --The NATIVITY variable has been edited in the Chile 2017 sample to correct a programming error that mistakenly classified as foreign-born about 20 thousand person records that were actually native-born. --The MIGRATE5 variable has been edited in the Chile 2017 sample, given a programming error that classified most migrants as having changed their major geographic unit. The MIGRATE5 variable for the Chile 1982 and 1992 samples has been edited to use spatially harmonized geographic units to calculate migration status. --In the 1989, 1999, and 2009 Kenya samples, households who indicated that their lighting type or fuel was "Solar" were recoded from "No" to "Yes" in ELECTRIC, based on secondary sources documenting the spread of home solar energy systems in Kenya beginning in the mid-1980s. In the 1989 and 1999 Kenya samples, programming was removed that previously recoded households that reported using electricity as their main cooking fuel to "Yes" in the access to electricity variable ELECTRIC, making it more consistent across samples. Other minor edits were implemented for ELECTRIC in Botswana 2011, Ethiopia 1984 and 1994, Mongolia 1989, Mozambique 2007. --Some samples in DISCARE classified responses indicating "some" difficulty into "yes". These cases were revised to consistently include in "yes" only responses indicating "a lot of difficulty" or "cannot do at all". --Some codes were improperly labeled for municipalities in Honduras 1961 and 1974, which affect variables on place of residence, birthplace, and previous residence. XIII National Population and II Housing Census - IPUMS Subset 1964 PHC co1964a (IPUMS Harmonized Subset) COL_1964_PHC_v01_M_v7.6_A_IPUMS Departmento Administrativo Nacional de Estadística (DANE) IPUMS (c) Copyright 1964, Departmento Administrativo Nacional de Estadística (DANE) and Minnesota Population Center Departmento Administrativo Nacional de Estadística (DANE) Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.6 Version 7.6. The datasets contain selected variables from the original microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Nativity and Birthplace Variables -- PERSON Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Education Variables -- PERSON Geography: A-E Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Migration: A-E Variables -- PERSON Technical Person Variables -- PERSON Work: Industry Variables -- PERSON Work: Occupation Variables -- PERSON July 15, 1964 Urban population and settlements with 20 or more dwellings were "immobilized" and enumerated on census day. Dispersed population was enumerated 20 days prior to census date. The National Territories (intendances and commissaries) were enumerated over a period of two months, following census day. Colombia Municipalities with 20,000+ population in 1993 combined by IPUMS Persons UNITS IDENTIFIED: - Dwellings: no - Vacant Units: No - Households: no - Individuals: yes - Group quarters: no UNIT DESCRIPTIONS: - Dwellings: Separated space with independent access that serves as a human lodging - Households: Individuals living in the same dwelling and sharing at least one meal. If a household is identified within a group quarters unit, it is enumerated separately as a private household - Group quarters: Group of persons who share a common roof and food because of work, health, religion, etc. Population census included people in territories, sailors, diplomats and their families. The indigenous population residing in remote areas was not enumerated. People in transit included in microdata sample Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Colombia 1964 Note: Persons not organized into households MICRODATA SOURCE: Departmento Administrativo Nacional de Estadística (DANE) SAMPLE SIZE (person records): 349652. SAMPLE DESIGN: Systematic sample of every 50th individual after a random start. Drawn by DANE from the original census enumeration forms. People in transit included in microdata sample Face-to-face [f2f] A single form was used for the entire country. It requested information about buildings, dwellings, households and individuals. de facto, CENSUS DAY: July 15, 1964 Self-weighting. Expansion factor = 50. 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. Departmento Administrativo Nacional de Estadística (DANE) Steven Ruggles, Lara Cleveland, Rodrigo Lovaton, Sula Sarkar, Matthew Sobek, Derek Burk, Dan Ehrlich, Quinn Heimann, Jane Lee, and Nate Merrill. Integrated Public Use Microdata Series, International: Version 7.6 [dataset]. Minneapolis, MN: IPUMS, 2025. https://doi.org/10.18128/D020.V7.6 Researchers should also acknowledge the statistical agency that originally produced the data: Colombia, Departmento Administrativo Nacional de Estadística (DANE). XIII National Population and II Housing Census The licensing agreement for use of IPUMS International data requires that users supply IPUMS International with the title and full citation for any publications, research reports, or educational materials making use of the data or documentation. Copies of such materials are also gratefully received at ipums@umn.edu. Printed matter should be sent to: IPUMS International Minnesota Population Center University of Minnesota 50 Willey Hall 225 19th Avenue South Minneapolis, MN 55455 An adapted version of the dataset, harmonized for international comparability, is available from IPUMS International (https://international.ipums.org/international/) under the following conditions: IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. User-provided description: DOI:10.18128/D020.V7.6 Extract for co1964a, 2025 COL1964_PHC-H-H.dat Household records n.a. ascii Minnesota Population Center Version 7.5, IPUMS sample COL1964_PHC-P-H.dat Person records 349652 ascii Minnesota Population Center Version 7.5, IPUMS sample Record type RECTYPE identifies the type of record for the case: household or person. NOTE: RECTYPE is an alphabetic (character string) variable with a value of 'H' for household records and 'P' for person records. RECTYPE will not appear as a variable in the default rectangular extracts produced by the data extract system. It is only available in hierarchical extracts, to distinguish between the two record types. H Household P Person Technical Household Variables -- HOUSEHOLD Country COUNTRY gives the country from which the sample was drawn. The codes assigned to each country are those used by the UN Statistics Division and the ISO (International Organization for Standardization). 032 Argentina 051 Armenia 040 Austria 050 Bangladesh 112 Belarus 204 Benin 068 Bolivia 072 Botswana 076 Brazil 854 Burkina Faso 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 208 Denmark 214 Dominican Republic 218 Ecuador 818 Egypt 222 El Salvador 231 Ethiopia 242 Fiji 246 Finland 250 France 276 Germany 288 Ghana 300 Greece 320 Guatemala 324 Guinea 332 Haiti 340 Honduras 348 Hungary 352 Iceland 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 384 Côte d'Ivoire 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 418 Laos 426 Lesotho 430 Liberia 454 Malawi 458 Malaysia 466 Mali 480 Mauritius 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 104 Myanmar 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 578 Norway 586 Pakistan 275 Palestine 591 Panama 598 Papua New Guinea 600 Paraguay 604 Peru 608 Philippines 616 Poland 620 Portugal 630 Puerto Rico 642 Romania 643 Russia 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 703 Slovak Republic 705 Slovenia 710 South Africa 728 South Sudan 724 Spain 729 Sudan 740 Suriname 752 Sweden 756 Switzerland 834 Tanzania 764 Thailand 768 Togo 780 Trinidad and Tobago 792 Turkey 800 Uganda 804 Ukraine 826 United Kingdom 840 United States 858 Uruguay 862 Venezuela 704 Vietnam 894 Zambia 716 Zimbabwe Technical Household Variables -- HOUSEHOLD Year YEAR gives the year in which the census or survey was taken. For samples that span years, the midpoint or first year of the interval is reported. 1703 1703 1729 1729 1787 1787 1801 1801 1819 1819 1845 1845 1848 1848 1850 1850 1851 1851 1852 1852 1860 1860 1861 1861 1865 1865 1868 1868 1870 1870 1871 1871 1875 1875 1880 1880 1881 1881 1885 1885 1890 1890 1891 1891 1900 1900 1901 1901 1910 1910 1911 1911 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1966 1966 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 Technical Household Variables -- HOUSEHOLD IPUMS sample identifier SAMPLE identifies the IPUMS sample from which the case is drawn. Each sample receives a unique 9-digit code. The code is structured as follows: The first 3 digits are the ISO/UN codes used in COUNTRY The next 4 digits are the year of the census/survey The final 2 digits identify the sample within the year. For the last two digits, censuses or large census-like surveys have a value "0" (e.g, 01) in the second-to-last digit, household surveys have a value of "2" (e.g., 21), and employment surveys have a value of "4" (e.g., 41). 032197001 Argentina 1970 032198001 Argentina 1980 032199101 Argentina 1991 032200101 Argentina 2001 032201001 Argentina 2010 051200101 Armenia 2001 051201101 Armenia 2011 040197101 Austria 1971 040198101 Austria 1981 040199101 Austria 1991 040200101 Austria 2001 040201101 Austria 2011 050199101 Bangladesh 1991 050200101 Bangladesh 2001 050201101 Bangladesh 2011 112199901 Belarus 1999 112200901 Belarus 2009 204197901 Benin 1979 204199201 Benin 1992 204200201 Benin 2002 204201301 Benin 2013 068197601 Bolivia 1976 068199201 Bolivia 1992 068200101 Bolivia 2001 068201201 Bolivia 2012 072198101 Botswana 1981 072199101 Botswana 1991 072200101 Botswana 2001 072201101 Botswana 2011 076196001 Brazil 1960 076197001 Brazil 1970 076198001 Brazil 1980 076199101 Brazil 1991 076200001 Brazil 2000 076201001 Brazil 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 116199801 Cambodia 1998 116200401 Cambodia 2004 116200801 Cambodia 2008 116201301 Cambodia 2013 116201901 Cambodia 2019 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124185201 Canada 1852 124187101 Canada 1871 124188101 Canada 1881 124189101 Canada 1891 124190101 Canada 1901 124191101 Canada 1911 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 124201101 Canada 2011 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 152201701 Chile 2017 156198201 China 1982 156199001 China 1990 156200001 China 2000 170196401 Colombia 1964 170197301 Colombia 1973 170198501 Colombia 1985 170199301 Colombia 1993 170200501 Colombia 2005 188196301 Costa Rica 1963 188197301 Costa Rica 1973 188198401 Costa Rica 1984 188200001 Costa Rica 2000 188201101 Costa Rica 2011 192200201 Cuba 2002 192201201 Cuba 2012 208178701 Denmark 1787 208180101 Denmark 1801 208184501 Denmark 1845 208188001 Denmark 1880 208188501 Denmark 1885 214196001 Dominican Republic 1960 214197001 Dominican Republic 1970 214198101 Dominican Republic 1981 214200201 Dominican Republic 2002 214201001 Dominican Republic 2010 218196201 Ecuador 1962 218197401 Ecuador 1974 218198201 Ecuador 1982 218199001 Ecuador 1990 218200101 Ecuador 2001 218201001 Ecuador 2010 818184801 Egypt 1848 818186801 Egypt 1868 818198601 Egypt 1986 818199601 Egypt 1996 818200601 Egypt 2006 222199201 El Salvador 1992 222200701 El Salvador 2007 231198401 Ethiopia 1984 231199401 Ethiopia 1994 231200701 Ethiopia 2007 242196601 Fiji 1966 242197601 Fiji 1976 242198601 Fiji 1986 242199601 Fiji 1996 242200701 Fiji 2007 242201401 Fiji 2014 246201001 Finland 2010 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 276181901 Germany 1819 (Mecklenburg) 276197001 Germany 1970 (West) 276197101 Germany 1971 (East) 276198101 Germany 1981 (East) 276198701 Germany 1987 (West) 288198401 Ghana 1984 288200001 Ghana 2000 288201001 Ghana 2010 300197101 Greece 1971 300198101 Greece 1981 300199101 Greece 1991 300200101 Greece 2001 300201101 Greece 2011 320196401 Guatemala 1964 320197301 Guatemala 1973 320198101 Guatemala 1981 320199401 Guatemala 1994 320200201 Guatemala 2002 324198301 Guinea 1983 324199601 Guinea 1996 324201401 Guinea 2014 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 340196101 Honduras 1961 340197401 Honduras 1974 340198801 Honduras 1988 340200101 Honduras 2001 340201301 Honduras 2013 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 348201101 Hungary 2011 352170301 Iceland 1703 352172901 Iceland 1729 352180101 Iceland 1801 352190101 Iceland 1901 352191001 Iceland 1910 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 356200941 India 2009 360197101 Indonesia 1971 360197601 Indonesia 1976 360198001 Indonesia 1980 360198501 Indonesia 1985 360199001 Indonesia 1990 360199501 Indonesia 1995 360200001 Indonesia 2000 360200501 Indonesia 2005 360201001 Indonesia 2010 364200601 Iran 2006 364201101 Iran 2011 368199701 Iraq 1997 372190101 Ireland 1901 372191101 Ireland 1911 372197101 Ireland 1971 372197901 Ireland 1979 372198101 Ireland 1981 372198601 Ireland 1986 372199101 Ireland 1991 372199601 Ireland 1996 372200201 Ireland 2002 372200601 Ireland 2006 372201101 Ireland 2011 372201601 Ireland 2016 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 376200801 Israel 2008 380200101 Italy 2001 380201101 Italy 2011 380201121 Italy 2011 Q1 LFS 380201221 Italy 2012 Q1 LFS 380201321 Italy 2013 Q1 LFS 380201421 Italy 2014 Q1 LFS 380201521 Italy 2015 Q1 LFS 380201621 Italy 2016 Q1 LFS 380201721 Italy 2017 Q1 LFS 380201821 Italy 2018 Q1 LFS 380201921 Italy 2019 Q1 LFS 380202021 Italy 2020 Q1 LFS 384198801 Côte d'Ivoire 1988 384199801 Côte d'Ivoire 1998 388198201 Jamaica 1982 388199101 Jamaica 1991 388200101 Jamaica 2001 400200401 Jordan 2004 404196901 Kenya 1969 404197901 Kenya 1979 404198901 Kenya 1989 404199901 Kenya 1999 404200901 Kenya 2009 404201901 Kenya 2019 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 418199501 Laos 1995 418200501 Laos 2005 418201501 Laos 2015 426199601 Lesotho 1996 426200601 Lesotho 2006 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 454201801 Malawi 2018 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 480199001 Mauritius 1990 480200001 Mauritius 2000 480201101 Mauritius 2011 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 484201501 Mexico 2015 484202001 Mexico 2020 484200521 Mexico 2005 Q1 LFS 484200522 Mexico 2005 Q2 LFS 484200523 Mexico 2005 Q3 LFS 484200524 Mexico 2005 Q4 LFS 484200621 Mexico 2006 Q1 LFS 484200622 Mexico 2006 Q2 LFS 484200623 Mexico 2006 Q3 LFS 484200624 Mexico 2006 Q4 LFS 484200721 Mexico 2007 Q1 LFS 484200722 Mexico 2007 Q2 LFS 484200723 Mexico 2007 Q3 LFS 484200724 Mexico 2007 Q4 LFS 484200821 Mexico 2008 Q1 LFS 484200822 Mexico 2008 Q2 LFS 484200823 Mexico 2008 Q3 LFS 484200824 Mexico 2008 Q4 LFS 484200921 Mexico 2009 Q1 LFS 484200922 Mexico 2009 Q2 LFS 484200923 Mexico 2009 Q3 LFS 484200924 Mexico 2009 Q4 LFS 484201021 Mexico 2010 Q1 LFS 484201022 Mexico 2010 Q2 LFS 484201023 Mexico 2010 Q3 LFS 484201024 Mexico 2010 Q4 LFS 484201121 Mexico 2011 Q1 LFS 484201122 Mexico 2011 Q2 LFS 484201123 Mexico 2011 Q3 LFS 484201124 Mexico 2011 Q4 LFS 484201221 Mexico 2012 Q1 LFS 484201222 Mexico 2012 Q2 LFS 484201223 Mexico 2012 Q3 LFS 484201224 Mexico 2012 Q4 LFS 484201321 Mexico 2013 Q1 LFS 484201322 Mexico 2013 Q2 LFS 484201323 Mexico 2013 Q3 LFS 484201324 Mexico 2013 Q4 LFS 484201421 Mexico 2014 Q1 LFS 484201422 Mexico 2014 Q2 LFS 484201423 Mexico 2014 Q3 LFS 484201424 Mexico 2014 Q4 LFS 484201521 Mexico 2015 Q1 LFS 484201522 Mexico 2015 Q2 LFS 484201523 Mexico 2015 Q3 LFS 484201524 Mexico 2015 Q4 LFS 484201621 Mexico 2016 Q1 LFS 484201622 Mexico 2016 Q2 LFS 484201623 Mexico 2016 Q3 LFS 484201624 Mexico 2016 Q4 LFS 484201721 Mexico 2017 Q1 LFS 484201722 Mexico 2017 Q2 LFS 484201723 Mexico 2017 Q3 LFS 484201724 Mexico 2017 Q4 LFS 484201821 Mexico 2018 Q1 LFS 484201822 Mexico 2018 Q2 LFS 484201823 Mexico 2018 Q3 LFS 484201824 Mexico 2018 Q4 LFS 484201921 Mexico 2019 Q1 LFS 484201922 Mexico 2019 Q2 LFS 484201923 Mexico 2019 Q3 LFS 484201924 Mexico 2019 Q4 LFS 484202021 Mexico 2020 Q1 LFS 484202023 Mexico 2020 Q3 LFS 496198901 Mongolia 1989 496200001 Mongolia 2000 496201001 Mongolia 2010 496202001 Mongolia 2020 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 508201701 Mozambique 2017 104201401 Myanmar 2014 524200101 Nepal 2001 524201101 Nepal 2011 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 528201101 Netherlands 2011 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 578180101 Norway 1801 578186501 Norway 1865 578187501 Norway 1875 578190001 Norway 1900 578191001 Norway 1910 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 275199701 Palestine 1997 275200701 Palestine 2007 275201701 Palestine 2017 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 598198001 Papua New Guinea 1980 598199001 Papua New Guinea 1990 598200001 Papua New Guinea 2000 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 604201701 Peru 2017 608199721 Philippines 1997 Q1 LFS 608199722 Philippines 1997 Q2 LFS 608199723 Philippines 1997 Q3 LFS 608199724 Philippines 1997 Q4 LFS 608199821 Philippines 1998 Q1 LFS 608199822 Philippines 1998 Q2 LFS 608199823 Philippines 1998 Q3 LFS 608199824 Philippines 1998 Q4 LFS 608199921 Philippines 1999 Q1 LFS 608199922 Philippines 1999 Q2 LFS 608199923 Philippines 1999 Q3 LFS 608199924 Philippines 1999 Q4 LFS 608200021 Philippines 2000 Q1 LFS 608200022 Philippines 2000 Q2 LFS 608200023 Philippines 2000 Q3 LFS 608200024 Philippines 2000 Q4 LFS 608200121 Philippines 2001 Q1 LFS 608200122 Philippines 2001 Q2 LFS 608200123 Philippines 2001 Q3 LFS 608200124 Philippines 2001 Q4 LFS 608200221 Philippines 2002 Q1 LFS 608200222 Philippines 2002 Q2 LFS 608200223 Philippines 2002 Q3 LFS 608200224 Philippines 2002 Q4 LFS 608200321 Philippines 2003 Q1 LFS 608200322 Philippines 2003 Q2 LFS 608200323 Philippines 2003 Q3 LFS 608200324 Philippines 2003 Q4 LFS 608200421 Philippines 2004 Q1 LFS 608200422 Philippines 2004 Q2 LFS 608200423 Philippines 2004 Q3 LFS 608200424 Philippines 2004 Q4 LFS 608200521 Philippines 2005 Q1 LFS 608200522 Philippines 2005 Q2 LFS 608200523 Philippines 2005 Q3 LFS 608200524 Philippines 2005 Q4 LFS 608200621 Philippines 2006 Q1 LFS 608200622 Philippines 2006 Q2 LFS 608200623 Philippines 2006 Q3 LFS 608200624 Philippines 2006 Q4 LFS 608200721 Philippines 2007 Q1 LFS 608200722 Philippines 2007 Q2 LFS 608200723 Philippines 2007 Q3 LFS 608200724 Philippines 2007 Q4 LFS 608200821 Philippines 2008 Q1 LFS 608200822 Philippines 2008 Q2 LFS 608200823 Philippines 2008 Q3 LFS 608200824 Philippines 2008 Q4 LFS 608200921 Philippines 2009 Q1 LFS 608200922 Philippines 2009 Q2 LFS 608200923 Philippines 2009 Q3 LFS 608200924 Philippines 2009 Q4 LFS 608201021 Philippines 2010 Q1 LFS 608201022 Philippines 2010 Q2 LFS 608201023 Philippines 2010 Q3 LFS 608201024 Philippines 2010 Q4 LFS 608201121 Philippines 2011 Q1 LFS 608201122 Philippines 2011 Q2 LFS 608201123 Philippines 2011 Q3 LFS 608201124 Philippines 2011 Q4 LFS 608201221 Philippines 2012 Q1 LFS 608201222 Philippines 2012 Q2 LFS 608201223 Philippines 2012 Q3 LFS 608201224 Philippines 2012 Q4 LFS 608201321 Philippines 2013 Q1 LFS 608201322 Philippines 2013 Q2 LFS 608201323 Philippines 2013 Q3 LFS 608201324 Philippines 2013 Q4 LFS 608201421 Philippines 2014 Q1 LFS 608201422 Philippines 2014 Q2 LFS 608201423 Philippines 2014 Q3 LFS 608201424 Philippines 2014 Q4 LFS 608201521 Philippines 2015 Q1 LFS 608201522 Philippines 2015 Q2 LFS 608201523 Philippines 2015 Q3 LFS 608201524 Philippines 2015 Q4 LFS 608201621 Philippines 2016 Q1 LFS 608201622 Philippines 2016 Q2 LFS 608201623 Philippines 2016 Q3 LFS 608201624 Philippines 2016 Q4 LFS 608201721 Philippines 2017 Q1 LFS 608201722 Philippines 2017 Q2 LFS 608201723 Philippines 2017 Q3 LFS 608201724 Philippines 2017 Q4 LFS 608201821 Philippines 2018 Q1 LFS 608201822 Philippines 2018 Q2 LFS 608201823 Philippines 2018 Q3 LFS 608201824 Philippines 2018 Q4 LFS 608201921 Philippines 2019 Q1 LFS 608201922 Philippines 2019 Q2 LFS 608201923 Philippines 2019 Q3 LFS 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 608201001 Philippines 2010 616197801 Poland 1978 616198801 Poland 1988 616200201 Poland 2002 616201101 Poland 2011 620198101 Portugal 1981 620199101 Portugal 1991 620200101 Portugal 2001 620201101 Portugal 2011 630197001 Puerto Rico 1970 630198001 Puerto Rico 1980 630199001 Puerto Rico 1990 630200001 Puerto Rico 2000 630200501 Puerto Rico 2005 630201001 Puerto Rico 2010 630201501 Puerto Rico 2015 630202001 Puerto Rico 2020 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 642201101 Romania 2011 643200201 Russia 2002 643201001 Russia 2010 646199101 Rwanda 1991 646200201 Rwanda 2002 646201201 Rwanda 2012 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 686201301 Senegal 2013 694200401 Sierra Leone 2004 694201501 Sierra Leone 2015 703199101 Slovak Republic 1991 703200101 Slovak Republic 2001 703201101 Slovak Republic 2011 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 710201601 South Africa 2016 728200801 South Sudan 2008 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 724200521 Spain 2005 Q1 LFS 724200522 Spain 2005 Q2 LFS 724200523 Spain 2005 Q3 LFS 724200524 Spain 2005 Q4 LFS 724200621 Spain 2006 Q1 LFS 724200622 Spain 2006 Q2 LFS 724200623 Spain 2006 Q3 LFS 724200624 Spain 2006 Q4 LFS 724200721 Spain 2007 Q1 LFS 724200722 Spain 2007 Q2 LFS 724200723 Spain 2007 Q3 LFS 724200724 Spain 2007 Q4 LFS 724200821 Spain 2008 Q1 LFS 724200822 Spain 2008 Q2 LFS 724200823 Spain 2008 Q3 LFS 724200824 Spain 2008 Q4 LFS 724200921 Spain 2009 Q1 LFS 724200922 Spain 2009 Q2 LFS 724200923 Spain 2009 Q3 LFS 724200924 Spain 2009 Q4 LFS 724201021 Spain 2010 Q1 LFS 724201022 Spain 2010 Q2 LFS 724201023 Spain 2010 Q3 LFS 724201024 Spain 2010 Q4 LFS 724201121 Spain 2011 Q1 LFS 724201122 Spain 2011 Q2 LFS 724201123 Spain 2011 Q3 LFS 724201124 Spain 2011 Q4 LFS 724201221 Spain 2012 Q1 LFS 724201222 Spain 2012 Q2 LFS 724201223 Spain 2012 Q3 LFS 724201224 Spain 2012 Q4 LFS 724201321 Spain 2013 Q1 LFS 724201322 Spain 2013 Q2 LFS 724201323 Spain 2013 Q3 LFS 724201324 Spain 2013 Q4 LFS 724201421 Spain 2014 Q1 LFS 724201422 Spain 2014 Q2 LFS 724201423 Spain 2014 Q3 LFS 724201424 Spain 2014 Q4 LFS 724201521 Spain 2015 Q1 LFS 724201522 Spain 2015 Q2 LFS 724201523 Spain 2015 Q3 LFS 724201524 Spain 2015 Q4 LFS 724201621 Spain 2016 Q1 LFS 724201622 Spain 2016 Q2 LFS 724201623 Spain 2016 Q3 LFS 724201624 Spain 2016 Q4 LFS 724201721 Spain 2017 Q1 LFS 724201722 Spain 2017 Q2 LFS 724201723 Spain 2017 Q3 LFS 724201724 Spain 2017 Q4 LFS 724201821 Spain 2018 Q1 LFS 724201822 Spain 2018 Q2 LFS 724201823 Spain 2018 Q3 LFS 724201824 Spain 2018 Q4 LFS 724201921 Spain 2019 Q1 LFS 724201922 Spain 2019 Q2 LFS 724201923 Spain 2019 Q3 LFS 724201924 Spain 2019 Q4 LFS 724202021 Spain 2020 Q1 LFS 724202022 Spain 2020 Q2 LFS 724202023 Spain 2020 Q3 LFS 724202024 Spain 2020 Q4 LFS 729200801 Sudan 2008 740200401 Suriname 2004 740201201 Suriname 2012 752188001 Sweden 1880 752189001 Sweden 1890 752190001 Sweden 1900 752191001 Sweden 1910 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 756201101 Switzerland 2011 834198801 Tanzania 1988 834200201 Tanzania 2002 834201201 Tanzania 2012 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 768196001 Togo 1960 768197001 Togo 1970 768201001 Togo 2010 780197001 Trinidad and Tobago 1970 780198001 Trinidad and Tobago 1980 780199001 Trinidad and Tobago 1990 780200001 Trinidad and Tobago 2000 780201101 Trinidad and Tobago 2011 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 800201401 Uganda 2014 804200101 Ukraine 2001 826185101 United Kingdom 1851 (England and Wales) 826185102 United Kingdom 1851 (Scotland) 826185103 United Kingdom 1851 (2% sample) 826186101 United Kingdom 1861 (England and Wales) 826186102 United Kingdom 1861 (Scotland) 826187101 United Kingdom 1871 (Scotland) 826188101 United Kingdom 1881 (England and Wales) 826188102 United Kingdom 1881 (Scotland) 826189101 United Kingdom 1891 (England and Wales) 826189102 United Kingdom 1891 (Scotland) 826190101 United Kingdom 1901 (England and Wales) 826190102 United Kingdom 1901 (Scotland) 826191101 United Kingdom 1911 (England and Wales) 826196101 United Kingdom 1961 826197101 United Kingdom 1971 826199101 United Kingdom 1991 826200101 United Kingdom 2001 840185001 United States 1850 (100%) 840185002 United States 1850 (1%) 840186001 United States 1860 (1%) 840187001 United States 1870 (1%) 840188001 United States 1880 (100%) 840188002 United States 1880 (10%) 840190001 United States 1900 (5%) 840191001 United States 1910 (1%) 840196001 United States 1960 840197001 United States 1970 840198001 United States 1980 840199001 United States 1990 840200001 United States 2000 840200501 United States 2005 840201001 United States 2010 840201501 United States 2015 840202001 United States 2020 858196301 Uruguay 1963 858196302 Uruguay 1963 (full count) 858197501 Uruguay 1975 858197502 Uruguay 1975 (full count) 858198501 Uruguay 1985 858198502 Uruguay 1985 (full count) 858199601 Uruguay 1996 858199602 Uruguay 1996 (full count) 858200621 Uruguay 2006 858201101 Uruguay 2011 858201102 Uruguay 2011 (full count) 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 704201901 Vietnam 2019 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 716201201 Zimbabwe 2012 Technical Household Variables -- HOUSEHOLD Household serial number SERIAL is an identifying number unique to each household in a given sample. All person records are assigned the same serial number as the household record that they follow. (Person records also have their own unique identifiers -- see PERNUM.) The combination of SAMPLE and SERIAL provides a unique identifier for every household in the IPUMS-International database; SAMPLE, SERIAL and PERNUM uniquely identify every person in the database. SERIAL can be used to identify dwellings in some samples. In these samples, the first 7 digits of SERIAL provide the dwelling number common to all households that were sampled from the same structure. The last three digits give the sequence of the household within the dwelling. The following is a list of samples in which dwellings can be inferred: Chile 1970, 1992, 2002Colombia 1993, 2005Costa Rica 1984, 2000Cuba 2002Dominican Republic 1981, 2002, 2010Ecuador 1990, 2001Germany 1971Hungary 1980, 1990, 2001Jamaica 1982, 1991, 2001Malaysia 1970, 1991, 2000Mexico 1995, 1990, 2000, 2005Nigeria 2006Panama 2000Peru 1993, 2007Portugal 1981, 1991, 2001Spain 1991Uruguay 2011Venezuela 1990, 2001Vietnam 1989In all other samples, the last 3 digits are always zeroes. SERIAL was constructed for IPUMS-International, and has no relation to the serial number in the original datasets. The U.S. 1900 sample and 1880 10% sample have multi-household dwellings that can be identified using the last 3 digits of SERIAL. SERIAL is a 10-digit numeric variable. The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes. Technical Household Variables -- HOUSEHOLD Number of person records in the household PERSONS indicates how many person records are included in the household (i.e., the number of person records associated with the household record in the sample). These person records will all have the same serial number (SERIAL) as the household record. The information contained in the household record will normally apply to all of these persons. PERSONS is a 4-digit numeric variable. Technical Household Variables -- HOUSEHOLD Household weight HHWT indicates the number of households in the population represented by the household in the sample. For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics. NOTE: HHWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Household Variables -- HOUSEHOLD Subsample number SUBSAMP allocates each case to one of 100 subsample replicates, randomly numbered from 0 to 99. Each subsample is nationally representative and preserves any stratification of the sample from which it is drawn. Users who need a representative subset of a sample can use SUBSAMP to select their cases. For example, to randomly extract 10% of the cases from a sample, select any 10 of the 100 subsamples. 00 1st 1% subsample 01 2nd 1% subsample 02 3rd 1% subsample 03 4th 1% subsample 04 5th 1% subsample 05 6th 1% subsample 06 7th 1% subsample 07 8th 1% subsample 08 9th 1% subsample 09 10th 1% subsample 10 11th 1% subsample 11 12th 1% subsample 12 13th 1% subsample 13 14th 1% subsample 14 15th 1% subsample 15 16th 1% subsample 16 17th 1% subsample 17 18th 1% subsample 18 19th 1% subsample 19 20th 1% subsample 20 21st 1% subsample 21 22nd 1% subsample 22 23rd 1% subsample 23 24th 1% subsample 24 25th 1% subsample 25 26th 1% subsample 26 27th 1% subsample 27 28th 1% subsample 28 29th 1% subsample 29 30th 1% subsample 30 31st 1% subsample 31 32nd 1% subsample 32 33rd 1% subsample 33 34th 1% subsample 34 35th 1% subsample 35 36th 1% subsample 36 37th 1% subsample 37 38th 1% subsample 38 39th 1% subsample 39 40th 1% subsample 40 41st 1% subsample 41 42nd 1% subsample 42 43rd 1% subsample 43 44th 1% subsample 44 45th 1% subsample 45 46th 1% subsample 46 47th 1% subsample 47 48th 1% subsample 48 49th 1% subsample 49 50th 1% subsample 50 51st 1% subsample 51 52nd 1% subsample 52 53rd 1% subsample 53 54th 1% subsample 54 55th 1% subsample 55 56th 1% subsample 56 57th 1% subsample 57 58th 1% subsample 58 59th 1% subsample 59 60th 1% subsample 60 61st 1% subsample 61 62nd 1% subsample 62 63rd 1% subsample 63 64th 1% subsample 64 65th 1% subsample 65 66th 1% subsample 66 67th 1% subsample 67 68th 1% subsample 68 69th 1% subsample 69 70th 1% subsample 70 71st 1% subsample 71 72nd 1% subsample 72 73rd 1% subsample 73 74th 1% subsample 74 75th 1% subsample 75 76th 1% subsample 76 77th 1% subsample 77 78th 1% subsample 78 79th 1% subsample 79 80th 1% subsample 80 81st 1% subsample 81 82nd 1% subsample 82 83rd 1% subsample 83 84th 1% subsample 84 85th 1% subsample 85 86th 1% subsample 86 87th 1% subsample 87 88th 1% subsample 88 89th 1% subsample 89 90th 1% subsample 90 91st 1% subsample 91 92nd 1% subsample 92 93rd 1% subsample 93 94th 1% subsample 94 95th 1% subsample 95 96th 1% subsample 96 97th 1% subsample 97 98th 1% subsample 98 99th 1% subsample 99 100th 1% subsample Technical Household Variables -- HOUSEHOLD Strata identifier This variable is the strata identifier for the sample. The STRATA variable provides information about the sample design that can be used to improve estimation. STRATA is a 12-digit numeric variable. Technical Household Variables -- HOUSEHOLD Group quarters (collective dwelling) status GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools. Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification. Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions. 00 Vacant 10 Households 20 Group quarters (collective), n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified Group Quarters Variables -- HOUSEHOLD Urban-rural status URBAN indicates whether the household was located in a place designated as urban or as rural. 1 Rural 2 Urban 9 Unknown Geography: Global Variables -- HOUSEHOLD Continent and region of country REGIONW identifies the continent and region of each country. 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia Geography: Global Variables -- HOUSEHOLD 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. Geography: Global Variables -- HOUSEHOLD 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 numeric variable listing the population density in persons per square kilometer. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD 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 numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Colombia, Department 1964 - 2005 [Level 1; consistent boundaries, GIS] GEO1_CO identifies the household's department within Colombia in all sample years. Departments are the first level administrative units of the country. GEO1_CO is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_CO can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Colombia 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. 170005 Antioquia 170008 Atlántico 170011 Bogotá D.C., Cundinamarca 170013 Bolívar, Sucre 170015 Boyacá, Casanare 170018 Caquetá 170019 Cauca 170023 Córdoba 170027 Chocó 170041 Huila 170044 La Guajira 170050 Meta 170052 Nariño 170054 Cesar, Norte De Santander, Magdalena 170066 Caldas, Quindío, Risaralda 170068 Santander 170073 Tolima 170076 Valle Del Cauca 170081 Arauca 170086 Putumayo 170088 Archipiélago De San Andrés Y Providencia 170095 Amazonas, Guaviare, Vaupés, Vichada, Guainía Geography: A-E Variables -- HOUSEHOLD Colombia, Department 1964 [Level 1, GIS] GEO1_CO1964 identifies the household's department within Colombia in 1964. Departments are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_CO1964 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Colombia 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. 001 Antioquia 002 Atlántico 003 Bolívar, Sucre 004 Boyacá, Casanare 005 Caldas, Quindío, Risaralda 006 Cauca 007 Córdoba 008 Cundinamarca, Federal District 010 Chocó 011 Huila 012 La Guajira 013 Magdalena 014 Meta 015 Nariño 016 Norte Santander 017 Santander 018 Tolima 019 Valle 021 Arauca 022 San Andres 023 Caqueta 033 Putumayo 034 Amazonas, Guainía, Vaupés, Vichada Geography: A-E Variables -- HOUSEHOLD Colombia, Region REGNCO indicates the metropolitan region within Colombia in which the household was enumerated. REGNCO is harmonized by name and does not account for boundary changes over time. The full set of geography variables for Colombia 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. 01 Central 02 Bogotá 03 Pacífico Norte 04 Eje Cafetero 05 Andina Norte 06 Andina Sur 07 Pacífico Sur 08 Caribe 09 Orinoquía 10 Amazonía 99 Unknown Geography: A-E Variables -- HOUSEHOLD Colombia, Metropolitan area METROCO indicates the metropolitan area in Colombia in which the household was enumerated for the 1964 - 2005 sample years. METROCO is harmonized by name and does not account for boundary changes over time. The full set of geography variables for Colombia 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. 00 Not a metropolitan area 01 Barranquilla 02 Bogotá D.C. 03 Bucaramanga 04 Cali 05 Cartagena 06 Centro occidente 07 Cúcuta 08 Manizales 09 Medellín y Valle de Aburrá 10 Santa Marta 99 Unknown Geography: A-E Variables -- HOUSEHOLD Colombia, Municipality head town MUNHDCO indicates the municipality head town in Colombia in which the household was enumerated. MUNHDCO is harmonized solely based on the names of the geographical unit. It does not take into account the changes that may have occurred in the political boundaries of the units. The full set of geography variables for Colombia 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. 10 Head town 20 Not head town 21 Population center 22 Administrative center 23 Small village 24 Dispersed population 29 Not head town, unspecified 99 Unknown Geography: A-E Variables -- HOUSEHOLD Department <span class="h1">A--Geographic location</span></p> <p><svar v="CO64A001 CO64A002 CO64A005 CO64A006 CO64A007 CO64A008" a="all"><div class="i1">____ I- Department, Administration, or Precinct<br />____ II- Municipality<br />____ III- Administrative unit<br />____ Judicial Precinct<br />____ IV- Administrative section<br />____ Hamlet<br />V-</div><br /><div class="i2">[ ] Urban Area <br />[ ] Rural</div><br /><div class="i1">____ VI- Zone number<br />____ VII- Sector<br />____ VIII- Section<br />____ IX- Block<br />____ X- Address of the building<br />____ XI- Apartment number</div><br /></svar> <svar v="CO64A001 CO64A002" a="all"><span class="em">I - Department, Administration, or Precinct of . . .</span><br /><br />In each one of the forms the name of the Department, Administration or Precinct should be written down where the enumeration is taking place.<br /><br /><span class="em">II - Municipality of. . .</span><br /><br />The name of the Municipality where the enumerating is being done should be written down.<br /><br /><span class="pg">[p. 13]</span><br /><br /><span class="em">III - Administrative Unit. . .</span><br /><br />The name of the Administrative unit should be written down in all the forms that are used within this municipal division. Each time that the registering of a new form is begun, the name of the administrative unit should be obtained by asking for it.<br /><br /><span class="em"> Judicial Precinct</span><br /><br />If you are doing the enumeration in the territory of a Police Inspectorate, the name of the Inspectorate should be written down.<br /><br /><span class="em">IV - Administrative section</span><br /><br />The Administrative section or rural fragment should be written down in all the forms that are used within this municipal division, observing the same recommendations that were given for writing down the name of the Administrative unit.<br /><br /><span class="em">Hamlet of. . .</span><br /><br />A group of houses of habitation forms a hamlet. Many of them have authority like Administrative unit or Police inspectorate, and others lack it. The name should be registered of all hamlets without authority that are more than 10 houses of habitation.<br /><br />The name should be written down of all hamlets with authority, whatever the number of its houses of habitation.<br /><br />Houses of habitation that are not grouped but rather are dispersed, do not form a hamlet and therefore should not be taken into account in this question.<br /></svar> Colombia 1964: All records This variable indicates the department. 01 Antioquia 02 Atlantico 03 Bolivar/Sucre 04 Boyaca/Casanare 05 Caldas/Quindio/Risaralda 06 Cauca 07 Cordoba 08 Cundinamarca/Federal District 09 Choco 10 Huila 11 Magdalena 12 Meta 13 Nariño 14 Norte Santander 15 Santander 16 Tolima 17 Valle 21 Arauca 22 San Andres 23 La Guajira 24 Caqueta 31 Amazonas 33 Putumayo 34 Vaupes Geography: A-E Variables -- HOUSEHOLD Area <span class="h1">A--Geographic location</span></p> <p><svar v="CO64A001 CO64A002 CO64A005 CO64A006 CO64A007 CO64A008" a="all"><div class="i1">____ I- Department, Administration, or Precinct<br />____ II- Municipality<br />____ III- Administrative unit<br />____ Judicial Precinct<br />____ IV- Administrative section<br />____ Hamlet<br />V-</div><br /><div class="i2">[ ] Urban Area <br />[ ] Rural</div><br /><div class="i1">____ VI- Zone number<br />____ VII- Sector<br />____ VIII- Section<br />____ IX- Block<br />____ X- Address of the building<br />____ XI- Apartment number</div><br /></svar> <svar v="CO64A005" a="all"><span class="em">V - Urban area</span><br /><br />For enumerating purposes urban areas will be considered surfaces occupied by cities, municipal capitals, capitals of administrative units, police inspectorates, and hamlets without authority where buildings are grouped.<br /><br />A cross should be marked if the area has these characteristics.<br /><br /><span class="em">Rural area</span><br /><br />Rural area is understood to be the surface occupied by agricultural farms, livestock farms or unexploited or unproductive regions. In these surfaces the houses of habitation are not considered to be grouped.<br /><br />A cross should be marked in the areas that have these characteristics.<br /></svar> Colombia 1964: All records This variable indicates whether the area of location is a headtown (urban) or not (rural). 1 Head town/urban 2 Not head town/rural Geography: A-E Variables -- HOUSEHOLD Strata Colombia 1964: All households This variable is the strata identifier for the sample. Strata is a constructed variable that captures implicit geographic stratification resulting from the sample design. It is created by assigning a unique identifier to groups of between 10 and 19 adjacent households. Additional documentation is available on the Variance Estimation page. This is a 5-digit numeric variable with 0 implied decimal places Geography: A-E Variables -- HOUSEHOLD Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. Technical Person Variables -- PERSON Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Person Variables -- PERSON Relationship to household head [general version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown Demographic Variables -- PERSON Relationship to household head [detailed version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling's sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder, or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown Demographic Variables -- PERSON Age AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. 000 Less than 1 year 001 1 year 002 2 years 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100+ 999 Not reported/missing Demographic Variables -- PERSON Age, grouped into intervals AGE2 gives computed years of age grouped into intervals. 01 0 to 4 02 5 to 9 03 10 to 14 04 15 to 19 05 0 to 5 06 6 to 10 07 10 to 15 08 11 to 14 09 15 to 17 10 16 to 19 11 18 to 24 12 20 to 24 13 25 to 29 14 30 to 34 15 35 to 39 16 40 to 44 17 45 to 49 18 50 to 54 19 55 to 59 20 60 to 64 21 65 to 69 22 70 to 74 23 75 to 79 24 80 to 84 25 85+ 98 Unknown Demographic Variables -- PERSON Sex SEX reports the sex (gender) of the respondent. 1 Male 2 Female 9 Unknown Demographic Variables -- PERSON Marital status [general version] MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. 0 NIU (not in universe) 1 Single/never married 2 Married/in union 3 Separated/divorced/spouse absent 4 Widowed 9 Unknown/missing Demographic Variables -- PERSON Marital status [detailed version] MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. 000 NIU (not in universe) 100 Single/never married 110 Engaged 111 Never married and never cohabited 200 Married or consensual union 210 Married, formally 211 Married, civil 212 Married, religious 213 Married, civil and religious 214 Married, civil or religious 215 Married, traditional/customary 216 Married, monogamous 217 Married, polygamous 219 Married, spouse absent (historical samples) 220 Consensual union 300 Separated/divorced/spouse absent 310 Separated or divorced 320 Separated or annulled 330 Separated 331 Separated legally 332 Separated de facto 333 Separated from marriage 334 Separated from consensual union 335 Separated from consensual union or marriage 340 Annulled 350 Divorced 400 Widowed 410 Widowed or divorced 411 Widowed from consensual union or marriage 412 Widowed from marriage 413 Widowed from consensual union 420 Widowed, divorced, or separated 999 Unknown/missing Demographic Variables -- PERSON Consensual union CONSENS indicates whether the respondent was in a consensual union -- a de facto marriage. 1 Yes, in consensual union 2 No, married 8 Unknown 9 NIU (not in universe) Demographic Variables -- PERSON Nativity status NATIVITY indicates whether the person was native-born or foreign-born. 0 NIU (not in universe) 1 Native-born 2 Foreign-born 9 Unknown/missing Nativity and Birthplace Variables -- PERSON Country of birth BPLCOUNTRY indicates the person's 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 Nativity and Birthplace Variables -- PERSON Department of birth, Colombia BPLCO1 indicates the person's department of birth within Colombia. 01 Unknown 02 Foreign-born 05 Antioquia 08 Atlántico 11 Bogotá 13 Bolívar 15 Boyacá 17 Caldas 18 Caquetá 19 Cauca 20 Cesar 23 Córdoba 25 Cundinamarca 27 Chocó 41 Huila 44 La Guajira 47 Magdalena 50 Meta 52 Nariño 54 Norte Santander 63 Quindio 66 Risaralda 68 Santander 70 Sucre 73 Tolima 76 Valle 81 Arauca 85 Casanare 86 Putumayo 88 San Andrés 91 Amazonas 94 Guanía 95 Guaviare 97 Vaupés 99 Vichada Nativity and Birthplace Variables -- PERSON Born in this municipality, Colombia BPLCO3 indicates whether the person was born in a different municipality in which they were enumerated in the census, and if so, whether they were born in a different department. 1 Born in this municipality 2 Born other municipality, same department 3 Born other department 4 Foreign-born 9 Unknown Nativity and Birthplace Variables -- PERSON Literacy 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. 0 NIU (not in universe) 1 No, illiterate 2 Yes, literate 9 Unknown/missing Education Variables -- PERSON Educational attainment, international recode [general version] EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. 0 NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown Education Variables -- PERSON Educational attainment, international recode [detailed version] EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. 000 NIU (not in universe) 100 Less than primary completed (n.s.) 110 No schooling 120 Some primary completed 130 Primary (4 yrs) completed 211 Primary (5 yrs) completed 212 Primary (6 yrs) completed 221 Lower secondary general completed 222 Lower secondary technical completed 311 Secondary, general track completed 312 Some college completed 320 Secondary or post-secondary technical completed 321 Secondary, technical track completed 322 Post-secondary technical education 400 University completed 999 Unknown/missing Education Variables -- PERSON Years of schooling 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. 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) Education Variables -- PERSON Educational attainment, Colombia EDUCCO indicates the person's educational attainment in Colombia in terms of the level of schooling completed and the number of years completed at that level. 000 None 100 Preschool 110 Preschool, years unspecified 120 Preschool, 0 years 130 Preschool, 1 year 140 Preschool, 2 years 200 Primary 210 Primary, 0 years 220 Primary, 1 year 230 Primary, 2 years 240 Primary, 3 years 250 Primary, 4 years 260 Primary, 5 years 270 Primary, years unspecified 300 Secondary 310 Secondary, 0 years 320 Secondary, 1 year 330 Secondary, 2 years 340 Secondary, 3 years 350 Secondary, 4 years 360 Secondary, 5 years 370 Secondary, 6 years 380 Secondary, years unspecified 390 Teaching school (2005) 391 3 years 392 4 years 399 Years unspecified 400 Unspecified level 401 University, 0 years 402 University, 1 year 403 University, 2 years 404 University, 3 years 405 University, 4 years 406 University, 5 years 407 University, 6 years 408 University, 7 years 409 University, 8 years 410 University, 9 years 419 University, level unspecified 420 Professional technical (2005) 421 Professional technical, 1 year 422 Professional technical, 2 years 429 Professional technical, years unspecified 430 Technological (2005) 431 Technological, 1 year 432 Technological, 2 years 433 Technological, 3 years 439 Technological, years unspecified 440 Undergraduate college (2005) 441 Undergraduate college, 1 year 442 Undergraduate college, 2 years 443 Undergraduate college, 3 years 444 Undergraduate college, 4 years 445 Undergraduate college, 5 years 446 Undergraduate college, 6 years 449 Undergraduate college, years unspecified 500 Graduate education 510 Specialization (2005) 511 Graduate education, specialization, 1 year 512 Graduate education, specialization, 2 years 519 Graduate education, specialization, years unspecified 520 Masters program (2005) 521 Masters program, 1 year 522 Masters program, 2 years 523 Masters program, 3 years 529 Masters program, years unspecified 530 Doctoral program (2005) 531 Doctoral program, 1 year 532 Doctoral program, 2 years 533 Doctoral program, 3 years 534 Doctoral program, 4 years 535 Doctoral program, 5 years 536 Doctoral program, 6 years 539 Doctoral program, years unspecified 590 University graduate, years unspecified 600 Other 601 Other, 0 years 602 Other, 1 year 603 Other, 2 years 604 Other, 3 years 605 Other, 4 years 606 Other, 5 years 607 Other, 6 years 610 Special education, years unspecified 620 Fundamental education, years unspec 998 Unknown/missing 999 NIU (not in universe) Education Variables -- PERSON Activity status (employment status) [general version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 0 NIU (not in universe) 1 Employed 2 Unemployed 3 Inactive 9 Unknown/missing Work Variables -- PERSON Activity status (employment status) [detailed version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 000 NIU (not in universe) 100 Employed, not specified 110 At work 111 At work, and 'student' 112 At work, and 'housework' 113 At work, and 'seeking work' 114 At work, and 'retired' 115 At work, and 'no work' 116 At work, and other situation 117 At work, family holding, not specified 118 At work, family holding, not agricultural 119 At work, family holding, agricultural 120 Have job, not at work in reference period 130 Armed forces 131 Armed forces, at work 132 Armed forces, not at work in reference period 133 Military trainee 140 Marginally employed 200 Unemployed, not specified 201 Unemployed 6 or more months 202 Worked fewer than 6 months, permanent job 203 Worked fewer than 6 months, temporary job 210 Unemployed, experienced worker 220 Unemployed, new worker 230 No work available 240 Inactive unemployed 300 Inactive (not in labor force) 301 Unavailable jobseekers 302 Available potential jobseekers 310 Housework 320 Health reasons, unable to work, or disabled 321 Permanent disability 322 Temporary illness 323 Disabled or imprisoned 330 In school 340 Retirees and living on rent 341 Living on rents 342 Living on rents or pension 343 Retirees/pensioners 344 Retired 345 Pensioner 346 Non-retirement pension 347 Disability pension 348 Retired without benefits 350 Elderly 351 Elderly or disabled 360 Institutionalized 361 Prisoner 370 Intermittent worker 371 Not working, seasonal worker 372 Not working, occasional worker 380 Other income recipient 390 Inactive, other reasons 391 Too young to work 392 Dependent 999 Unknown/missing Work Variables -- PERSON Labor force participation LABFORCE is a dichotomous variable identifying whether a person participated in the labor force. Labor force participation generally means working or seeking work within a specified reference period. For most samples LABFORCE is a recode of EMPSTAT (employment status). A consistent lower age universe of 15 or older has been applied to increase comparability across samples. Full detail is retained in EMPSTAT, which should be used for any study of child labor. 1 No, not in the labor force 2 Yes, in the labor force 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Occupation, ISCO general OCCISCO records the person's primary occupation, coded according to the major categories in the International Standard Classification of Occupations (ISCO) scheme for 1988. For someone with more than one job, the primary occupation is typically the one in which the person had spent the most time or earned the most money. 01 Legislators, senior officials and managers 02 Professionals 03 Technicians and associate professionals 04 Clerks 05 Service workers and shop and market sales 06 Skilled agricultural and fishery workers 07 Crafts and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 10 Armed forces 11 Other occupations, unspecified or n.e.c. 97 Response suppressed 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Occupation, unrecoded OCC records the person's primary occupation, classified according to the system used by the respective national census office at the time. For someone with more than one job, the primary occupation is usually the one in which the person spent the most time or earned the most money, although this may not have been explicit in the instructions for a specific census. To ensure confidentiality, very small occupations are recoded to a residual category indicating the persons had an occupation, but the job title is not identified. The number of cases recoded should be too small to affect analyses. OCC is a 4-digit numeric variable. Some samples use fewer than 4 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_OCC3 - Occupation [3 digit] Argentina 1980 - see Variable: AR1980A_OCC - Occupation Argentina 1991 - see Variable: AR1991A_OCC - Occupation Argentina 2001 - see Variable: AR2001A_OCC4 - Occupation (4-digits) Armenia 2011 - see Variable: AM2011A_OCC - Occupation Austria 1971 - see Variable: AT1971A_OCCSM - Occupation of supporter: sub-major groups Austria 1981 - see Variable: AT1981A_OCCSM - Occupation of supporter: sub-major groups Austria 1991 - see Variable: AT1991A_OCCSM - Occupation of supporter: sub-major groups Austria 2001 - see Variable: AT2001A_OCCSM - Occupation of supporter: sub-major groups Belarus 1999 - see Variable: BY1999A_OCC2 - Occupation, 2 digits Belarus 2009 - see Variable: BY2009A_OCC - Occupation Benin 1979 - see Variable: BJ1979A_OCC - Occupation (2-digits) Benin 1992 - see Variable: BJ1992A_OCC3 - Occupation (3-digits) Benin 2002 - see Variable: BJ2002A_OCC - Occupation (3-digits) Benin 2013 - see Variable: BJ2013A_OCC - Occupation (3-digit) Bolivia 1976 - see Variable: BO1976A_OCC2 - Occupation, 2 digits Bolivia 1992 - see Variable: BO1992A_OCC - Occupation Bolivia 2001 - see Variable: BO2001A_OCC - Occupation, 3 digits Bolivia 2012 - see Variable: BO2012A_OCC2 - Occupation (3 digit) Botswana 1981 - see Variable: BW1981A_OCC - Occupation Botswana 1991 - see Variable: BW1991A_OCC - Occupation (last 30 days) Botswana 2001 - see Variable: BW2001A_OCC - Occupation in the past 7 days, 3 digit Botswana 2011 - see Variable: BW2011A_OCC - Occupation, 3-digits Brazil 1960 - see Variable: BR1960A_USUALOCC - Usual occupation Brazil 1970 - see Variable: BR1970A_MAINOCC - Principal occupation Brazil 1980 - see Variable: BR1980A_OCC - Occupation Brazil 1991 - see Variable: BR1991A_OCC - Occupation Brazil 2000 - see Variable: BR2000A_OCC - Occupation, 4 digits Brazil 2010 - see Variable: BR2010A_OCC - Occupation held from July 25 to July 31, 2010 Burkina Faso 1985 - see Variable: BF1985A_OCC - Principal occupation Burkina Faso 1996 - see Variable: BF1996A_OCC - Principal occupation Cambodia 1998 - see Variable: KH1998A_OCC - Occupation Cambodia 2004 - see Variable: KH2004A_OCC3 - Occupation (3-digits) Cambodia 2008 - see Variable: KH2008A_OCC - Occupation Cambodia 2013 - see Variable: KH2013A_OCC - Occupation (3-digits) Cambodia 2019 - see Variable: KH2019A_OCC1 - Occupation, 1-digit Cameroon 1976 - see Variable: CM1976A_OCC2 - Occupation (2 digits) Cameroon 2005 - see Variable: CM2005A_OCC - Occupation Canada 1971 - see Variable: CA1971A_OCC - Occupation Canada 1981 - see Variable: CA1981A_OCC - Occupation (1981 classification basis) Canada 1991 - see Variable: CA1991A_OCC80 - Occupation (1980 classification basis) Canada 2001 - see Variable: CA2001A_NOCS01P - Occupation (2001 national occupational classification for statistics) Canada 2011 - see Variable: CA2011A_OCC - Occupation Chile 1960 - see Variable: CL1960A_OCC - Occupation Chile 1970 - see Variable: CL1970A_OCC3 - Occupation (3-digit) Chile 1982 - see Variable: CL1982A_OCC3 - Occupation (3-digit) Chile 1992 - see Variable: CL1992A_OCC3 - Occupation (3-digit) Chile 2002 - see Variable: CL2002A_OCC - Occupation China 1982 - see Variable: CN1982A_OCC - Occupation China 1990 - see Variable: CN1990A_OCC - Occupation China 2000 - see Variable: CN2000A_OCC - Occupation (2-digit) Colombia 1964 - see Variable: CO1964A_OCC2 - Occupation (COTA, 4 digits) Colombia 1973 - see Variable: CO1973A_OCC - Occupation last week Costa Rica 1973 - see Variable: CR1973A_OCC3 - Occupation, 3 digits Costa Rica 1984 - see Variable: CR1984A_OCC - Occupation, 3 digits Costa Rica 2000 - see Variable: CR2000A_OCC3 - Occupation, 3 digits Costa Rica 2011 - see Variable: CR2011A_OCC - Occupation, 2-digit Cuba 2002 - see Variable: CU2002A_OCC - Occupation Cuba 2012 - see Variable: CU2012A_OCC3 - Main occupation (3-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_OCC2 - Current occupation (2-digit) Dominican Republic 1960 - see Variable: DO1960A_OCC - Occupation Dominican Republic 1970 - see Variable: DO1970A_OCC1 - Current occupation, 3 digits Dominican Republic 1981 - see Variable: DO1981A_OCC - Occupation Dominican Republic 2002 - see Variable: DO2002A_OCC - Occupation Dominican Republic 2010 - see Variable: DO2010A_OCC - Occupation Ecuador 1962 - see Variable: EC1962A_OCC - Occupation Ecuador 1974 - see Variable: EC1974A_OCC3 - Occupation, three digits Ecuador 1982 - see Variable: EC1982A_OCC3 - Occupation, 3 digits Ecuador 1990 - see Variable: EC1990A_OCC3 - Occupation, 3 digits Ecuador 2001 - see Variable: EC2001A_OCC - Occupation, 3 digits Ecuador 2010 - see Variable: EC2010A_OCC3 - Occupation (3 digits, ISCO 08) Egypt 1986 - see Variable: EG1986A_OCC3 - Occupation (3-digit) Egypt 2006 - see Variable: EG2006A_OCC - Primary occupation, 3-digit El Salvador 1992 - see Variable: SV1992A_OCC - Occupation (3-digit) El Salvador 2007 - see Variable: SV2007A_OCC3DIG - Occupation (3-digit) Ethiopia 1984 - see Variable: ET1984A_OCC2 - Occupation (2-digit) Ethiopia 1994 - see Variable: ET1994A_OCC - Occupation Fiji 1976 - see Variable: FJ1976A_OCC - Occupation Fiji 1986 - see Variable: FJ1986A_OCC - Occupation Fiji 1996 - see Variable: FJ1996A_OCC3 - Occupation (3 digits) Fiji 2007 - see Variable: FJ2007A_OCC3 - Occupation, 3 digits Fiji 2014 - see Variable: FJ2014A_OCC3 - Occupation (3 digits) Finland 2010 - see Variable: FI2010A_OCC - Occupation France 1962 - see Variable: FR1962A_SOCCUP - SAPHIR occupation France 1968 - see Variable: FR1968A_SOCC - SAPHIR occupation France 1975 - see Variable: FR1975A_SOCC - SAPHIR occupation France 1982 - see Variable: FR1982A_SOCC - SAPHIR occupation France 1990 - see Variable: FR1990A_SOCC - Saphir occupation France 1999 - see Variable: FR1999A_OCC - Occupation, ISCO France 2006 - see Variable: FR2006A_PROF486 - Detailed profession (4-digit) France 2011 - see Variable: FR2011A_PROF - Profession, 486 categories Germany 1970 - see Variable: DE1970A_OCC - Occupation Germany 1981 - see Variable: DE1981A_OCC - Occupation Germany 1987 - see Variable: DE1987A_OCC - Occupation Ghana 1984 - see Variable: GH1984A_OCC2 - Occupation, 2 digits Ghana 2000 - see Variable: GH2000A_OCC - Occupation Ghana 2010 - see Variable: GH2010A_OCC - Occupation (major groups) Greece 1971 - see Variable: GR1971A_OCC - Occupation Greece 1981 - see Variable: GR1981A_OCC - Occupation Greece 1991 - see Variable: GR1991A_OCC - Occupation Greece 2001 - see Variable: GR2001A_OCC - Occupation Greece 2011 - see Variable: GR2011A_OCC - Occupation Guatemala 1964 - see Variable: GT1964A_OCC3 - Occupation (3-digits) Guatemala 1973 - see Variable: GT1973A_OCC3 - Principal occupation (3-digits) Guatemala 1981 - see Variable: GT1981A_OCC3 - Principal occupation (3-digits) Guatemala 1994 - see Variable: GT1994A_OCC - Principal occupation (1-digit) Guatemala 2002 - see Variable: GT2002A_OCC3 - Principal occupation (3-digits) Guinea 1983 - see Variable: GN1983A_OCC2 - Occupation, 2 digits Guinea 1996 - see Variable: GN1996A_OCC - Occupation Guinea 2014 - see Variable: GN2014A_OCC - Occupation (3-digit) Haiti 1982 - see Variable: HT1982A_OCC - Main occupation or profession Haiti 2003 - see Variable: HT2003A_OCC2 - Occupation, 3 digits Honduras 1961 - see Variable: HN1961A_OCC - Occupation (2-digits) Honduras 1974 - see Variable: HN1974A_OCC2 - Occupation (3-digits) Honduras 1988 - see Variable: HN1988A_OCC4 - Occupation (4-digits) Honduras 2001 - see Variable: HN2001A_OCC - Occupation (4-digit) Honduras 2013 - see Variable: HN2013A_OCC3 - Occupation (3-digit) Hungary 1970 - see Variable: HU1970A_OCC - Occupation Hungary 1980 - see Variable: HU1980A_OCC - Occupation, scope of activity Hungary 1990 - see Variable: HU1990A_OCC - Occupation Hungary 2001 - see Variable: HU2001A_OCC - Occupation Hungary 2011 - see Variable: HU2011A_OCC - Occupation Indonesia 1971 - see Variable: ID1971A_OCC - Occupation Indonesia 1976 - see Variable: ID1976A_OCC - Primary occupation during past week Indonesia 1980 - see Variable: ID1980A_OCC - Primary occupation during the previous week (3 digit version) Indonesia 1985 - see Variable: ID1985A_OCC - Primary occupation Indonesia 1990 - see Variable: ID1990A_OCC - Main occupation last week Indonesia 1995 - see Variable: ID1995A_OCC - Occupation Indonesia 2005 - see Variable: ID2005A_OCC - Occupation Iran 2006 - see Variable: IR2006A_OCC4 - Occupation Iran 2011 - see Variable: IR2011A_OCC - Occupation (3-digit) Iraq 1997 - see Variable: IQ1997A_OCC - Occupation Ireland 1971 - see Variable: IE1971A_OCC - Occupation Ireland 1981 - see Variable: IE1981A_OCC - Occupation Ireland 1986 - see Variable: IE1986A_OCC - Occupation group Ireland 1991 - see Variable: IE1991A_OCC - Occupation group Ireland 1996 - see Variable: IE1996A_OCC - Occupation Ireland 2002 - see Variable: IE2002A_OCC - Occupation Ireland 2006 - see Variable: IE2006A_OCC - Occupation group Ireland 2011 - see Variable: IE2011A_OCC - Occupation (shuffled) Ireland 2016 - see Variable: IE2016A_OCC - Occupation (groups) Israel 1972 - see Variable: IL1972A_OCC - Occupation Israel 1983 - see Variable: IL1983A_OCC - Occupation Israel 1995 - see Variable: IL1995A_OCC - Occupation Israel 2008 - see Variable: IL2008A_OCC - Occupation Italy 2001 - see Variable: IT2001A_OCC - Occupation Italy 2011 - see Variable: IT2011A_WKTYPE - Type of work Jamaica 1982 - see Variable: JM1982A_OCC - Occupation during past week / in last job Jamaica 1991 - see Variable: JM1991A_OCC - Occupation during past week/in last job Jamaica 2001 - see Variable: JM2001A_OCC3 - Occupation 3-digit Jordan 2004 - see Variable: JO2004A_OCC3 - Major current occupation (3-digit) Kenya 1989 - see Variable: KE1989A_OCC4 - Occupation, 4 digits Kenya 2019 - see Variable: KE2019A_OCC3 - Occupation (3-digit) Kyrgyzstan 1999 - see Variable: KG1999A_OCC - Main activity Laos 1995 - see Variable: LA1995A_OCC1 - Main occupation in the last 12 months (1-digit) Lesotho 1996 - see Variable: LS1996A_OCC - Occupation (2-digits) Lesotho 2006 - see Variable: LS2006A_OCC - Occupation (2-digits) Liberia 1974 - see Variable: LR1974A_OCC2 - Occupation (2-digit) Liberia 2008 - see Variable: LR2008A_OCC - Occupation Malawi 1987 - see Variable: MW1987A_OCC2 - Occupation, 2 digit Malawi 1998 - see Variable: MW1998A_OCC2 - Occupation, 2-digit Malawi 2008 - see Variable: MW2008A_OCC2 - Occupation (2 digits) Malawi 2018 - see Variable: MW2018A_OCC1 - Main occupation (1-digit) Malaysia 1970 - see Variable: MY1970A_OCC - Occupation last week Malaysia 1980 - see Variable: MY1980A_OCC3 - Principal occupation last week (3 digits) Malaysia 1991 - see Variable: MY1991A_OCC3 - Principal occupation (3 digits) Malaysia 2000 - see Variable: MY2000A_OCC3 - Occupation -- 3 digits Mali 1987 - see Variable: ML1987A_OCC - Occupation last month Mali 1998 - see Variable: ML1998A_OCC - Main occupation Mali 2009 - see Variable: ML2009A_OCC - Principal occupation Mauritius 1990 - see Variable: MU1990A_OCC3 - Occupation (3-digit) Mauritius 2000 - see Variable: MU2000A_OCC4 - Occupation (4 digit) Mauritius 2011 - see Variable: MU2011A_OCC4 - Occupation (4-digit) Mexico 1960 - see Variable: MX1960A_OCC2 - Principal occupation, 2 digits Mexico 1970 - see Variable: MX1970A_OCC3 - Occupation 3 digit Mexico 1990 - see Variable: MX1990A_OCC - Occupation, 4 digits Mexico 1995 - see Variable: MX1995A_OCC - Occupation Mexico 2000 - see Variable: MX2000A_OCC4 - Occupation, 4 digits Mexico 2010 - see Variable: MX2010A_OCC - Occupation or trade Mexico 2015 - see Variable: MX2015A_OCC - Occupation Mexico 2020 - see Variable: MX2020A_OCC3 - Occupation (3-digits) Mongolia 2000 - see Variable: MN2000A_OCC - Occupation Mongolia 2010 - see Variable: MN2010A_OCC3 - Occupation 3 digits (ISCO-2008) Mongolia 2020 - see Variable: MN2020A_OCC3 - Occupation (3-digit) Morocco 1982 - see Variable: MA1982A_OCC3 - Occupation (3-digit) Morocco 1994 - see Variable: MA1994A_OCC3 - Occupation, 3-digit Morocco 2004 - see Variable: MA2004A_OCC3 - Occupation (3-digit) Morocco 2014 - see Variable: MA2014A_OCC2 - Occupation (2-digit) Mozambique 1997 - see Variable: MZ1997A_OCC2 - Occupation 3-digit Mozambique 2007 - see Variable: MZ2007A_OCC - Occupation Mozambique 2017 - see Variable: MZ2017A_OCC3 - Main occupation (3-digits ISCO 2008) Myanmar 2014 - see Variable: MM2014A_OCC - Occupation Nepal 2001 - see Variable: NP2001A_OCC - Usual occupation Nepal 2011 - see Variable: NP2011A_OCC1 - Occupation (1-digit) Netherlands 1960 - see Variable: NL1960A_OCC - Occupation Netherlands 1971 - see Variable: NL1971A_OCC - Occupation Netherlands 2001 - see Variable: NL2001A_OCC - Occupation Netherlands 2011 - see Variable: NL2011A_OCC - Occupation (1-digit) Nicaragua 1971 - see Variable: NI1971A_OCC - Occupation Nicaragua 1995 - see Variable: NI1995A_OCC - Occupation (ISCO 88, 3 digits) Nicaragua 2005 - see Variable: NI2005A_OCC3 - Occupation (ISCO 88, 3 digits) Pakistan 1973 - see Variable: PK1973A_OCC3 - Occupation Palestine 1997 - see Variable: PS1997A_OCC - Main occupation Palestine 2007 - see Variable: PS2007A_OCC - Main occupation Palestine 2017 - see Variable: PS2017A_OCC - Occupation Panama 1960 - see Variable: PA1960A_OCC4 - Occupation (4-digit) Panama 1970 - see Variable: PA1970A_OCC2 - Occupation, 2-digit Panama 1980 - see Variable: PA1980A_OCC2 - Occupation (3-digit) Panama 1990 - see Variable: PA1990A_OCC - Occupation Panama 2000 - see Variable: PA2000A_OCC - Occupation Panama 2010 - see Variable: PA2010A_OCC - Occupation, 3 digits Papua New Guinea 1980 - see Variable: PG1980A_OCC - Occupation, 3 digits Papua New Guinea 1990 - see Variable: PG1990A_OCC - Occupation Papua New Guinea 2000 - see Variable: PG2000A_OCC - Occupation (4-digit) Paraguay 1962 - see Variable: PY1962A_OCC1 - Occupation (1-digit) Paraguay 1972 - see Variable: PY1972A_OCC3 - Occupation (3 digits) Paraguay 1982 - see Variable: PY1982A_OCC3 - Occupation, 3-digits Paraguay 1992 - see Variable: PY1992A_OCC2 - Main occupation, 3 digits Paraguay 2002 - see Variable: PY2002A_OCC - Occupation (4 digits) Peru 1993 - see Variable: PE1993A_OCC - Occupation (3 digits) Peru 2007 - see Variable: PE2007A_OCC - Main occupation last week (3 digits) Peru 2017 - see Variable: PE2017A_OCC1 - Occupation (1-digit, in primary job last week) Philippines 1990 - see Variable: PH1990A_OCC - Occupation Philippines 2000 - see Variable: PH2000A_OCC - Occupation Philippines 2010 - see Variable: PH2010A_OCC3 - Usual occupation (3-digit) Poland 1978 - see Variable: PL1978A_OCC - Occupation Poland 1988 - see Variable: PL1988A_OCC - Main occupation Poland 2002 - see Variable: PL2002A_OCC - Occupation Portugal 1981 - see Variable: PT1981A_OCC - Main occupation Portugal 1991 - see Variable: PT1991A_OCC - Main occupation Portugal 2001 - see Variable: PT2001A_OCC - Main occupation Portugal 2011 - see Variable: PT2011A_OCC - Main occupation Puerto Rico 1970 - see Variable: PR1970A_OCC - Occupation Puerto Rico 1980 - see Variable: PR1980A_OCC - Occupation Puerto Rico 1990 - see Variable: PR1990A_OCC - Occupation Puerto Rico 2000 - see Variable: PR2000A_OCC - Occupation Puerto Rico 2005 - see Variable: PR2005A_OCC - Occupation Puerto Rico 2010 - see Variable: PR2010A_OCC - Occupation Puerto Rico 2015 - see Variable: PR2015A_OCC - Occupation last week Puerto Rico 2020 - see Variable: PR2020A_OCC2010 - Occupation last week, 2010 basis Romania 1992 - see Variable: RO1992A_OCC - Occupation Romania 2002 - see Variable: RO2002A_OCC4 - Occupation, 4 digits Romania 2011 - see Variable: RO2011A_OCC - Occupation (unrecoded) Rwanda 2002 - see Variable: RW2002A_OCC - Occupation Rwanda 2012 - see Variable: RW2012A_OCC2 - Occupation (3-digit) Saint Lucia 1991 - see Variable: LC1991A_OCC - Occupation Senegal 1988 - see Variable: SN1988A_OCC - Occupation Senegal 2002 - see Variable: SN2002A_OCC3 - Occupation, 3 digits Senegal 2013 - see Variable: SN2013A_OCC3 - Profession or occupation (3-digit) Sierra Leone 2004 - see Variable: SL2004A_OCC - Occupation Sierra Leone 2015 - see Variable: SL2015A_OCC - Main occupation in the past 12 months Slovakia 1991 - see Variable: SK1991A_OCC - Occupation (2-digit) Slovakia 2001 - see Variable: SK2001A_OCC2 - Occupation (2-digit) Slovakia 2011 - see Variable: SK2011A_OCC2 - Occupation (2-digit) Slovenia 2002 - see Variable: SI2002A_OCC - Occupation South Africa 1996 - see Variable: ZA1996A_OCC3 - Occupation, 3 digits South Africa 2001 - see Variable: ZA2001A_OCC - Occupation, 3 digit South Africa 2007 - see Variable: ZA2007A_OCC3 - Occupation, 3 digits South Sudan 2008 - see Variable: SS2008A_OCC - Occupation Spain 1981 - see Variable: ES1981A_OCC - Occupation Spain 1991 - see Variable: ES1991A_OCC - Occupation Spain 2001 - see Variable: ES2001A_OCC - Occupation Spain 2011 - see Variable: ES2011A_OCC - Occupation, 2-digits Sudan 2008 - see Variable: SD2008A_OCC - Occupation Suriname 2004 - see Variable: SR2004A_OCC - Occupation Suriname 2012 - see Variable: SR2012A_OCC - Occupation (groups) Switzerland 1970 - see Variable: CH1970A_ISCO - Present occupation (ISCO) Switzerland 1980 - see Variable: CH1980A_ISCO - Present occupation (ISCO-COM) Switzerland 1990 - see Variable: CH1990A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2000 - see Variable: CH2000A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2011 - see Variable: CH2011A_OCC - Current occupation (1-digit, ISCO-08) Tanzania 1988 - see Variable: TZ1988A_OCC - Occupation Tanzania 2002 - see Variable: TZ2002A_OCC - Occupation last week Tanzania 2012 - see Variable: TZ2012A_OCC - Occupation Thailand 1970 - see Variable: TH1970A_OCC - Principal occupation last year Thailand 1980 - see Variable: TH1980A_OCC - Occupation last year Thailand 1990 - see Variable: TH1990A_OCC3 - Occupation last year Thailand 2000 - see Variable: TH2000A_OCC3 - Occupation last year, 3 digits Togo 1960 - see Variable: TG1960A_OCC - Occupation (3-digits) Togo 1970 - see Variable: TG1970A_OCC3 - Occupation (3-digits) Togo 2010 - see Variable: TG2010A_OCC2 - Occupation (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_OCC - Main occupation (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_OCC - Main occupation during previous week (three digits) Trinidad and Tobago 2000 - see Variable: TT2000A_OCC - Main occupation (3 digits) Turkey 1985 - see Variable: TR1985A_OCC2 - Occupation (2-digit) Turkey 1990 - see Variable: TR1990A_OCC2 - Current occupation (2 digits) Turkey 2000 - see Variable: TR2000A_OCC2 - Current occupation, 2 digit Uganda 1991 - see Variable: UG1991A_OCC - Occupation, 3 digits Uganda 2002 - see Variable: UG2002A_OCC - Occupation, 3 digits Uganda 2014 - see Variable: UG2014A_OCC - Occupation (2-digits) United Kingdom 1961 - see Variable: UK1961A_OCC - Occupation United Kingdom 1971 - see Variable: UK1971A_OCC - Occupation United Kingdom 1991 - see Variable: UK1991A_OCC - Occupational classification United Kingdom 2001 - see Variable: UK2001A_OCC3 - Standard occupational classification 2000-minor United States 1960 - see Variable: US1960A_OCC - Occupation United States 1970 - see Variable: US1970A_OCC - Occupation United States 1980 - see Variable: US1980A_OCC - Occupation United States 1990 - see Variable: US1990A_OCC - Occupation United States 2000 - see Variable: US2000A_OCC - Occupation United States 2005 - see Variable: US2005A_OCC2000M - Occupation, 2000 basis, modal category assignment United States 2010 - see Variable: US2010A_OCC - Occupation United States 2015 - see Variable: US2015A_OCC - Occupation last week United States 2020 - see Variable: US2020A_OCC - Occupation last week Uruguay 1963 - see Variable: UY1963A_OCC2 - Primary occupation [2-digit] Uruguay 1975 - see Variable: UY1975A_OCC - Occupation (COTA, 3 digits) Uruguay 1985 - see Variable: UY1985A_OCC - Occupation during the past week Uruguay 1996 - see Variable: UY1996A_OCC - Occupation (ISCO 88, 3 digits) Uruguay 2006 - see Variable: UY2006A_OCC3 - Occupation (ISCO-88, 3 digits) Venezuela 1981 - see Variable: VE1981A_OCC3 - Occupation, 3 digits Venezuela 1990 - see Variable: VE1990A_OCC - Occupation, 3 digits Venezuela 2001 - see Variable: VE2001A_OCC - Occupation Vietnam 1989 - see Variable: VN1989A_OCC2 - Occupation, 2 digits Vietnam 1999 - see Variable: VN1999A_OCC3 - Occupation, 3 digit Vietnam 2009 - see Variable: VN2009A_OCC - Occupation Vietnam 2019 - see Variable: VN2019A_OCC1 - Occupation, 1 digit Zambia 1990 - see Variable: ZM1990A_OCC - Occupation Zambia 2000 - see Variable: ZM2000A_OCC - Main occupation last 12 months, 3 digits Zambia 2010 - see Variable: ZM2010A_OCC2 - Main occupation last 12 months, 3 digits Zimbabwe 2012 - see Variable: ZW2012A_OCC - Occupation (3-digits) Work Variables -- PERSON Industry, general recode INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown Work Variables -- PERSON Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_IND4 - Industry [4 digit] Argentina 1980 - see Variable: AR1980A_IND - Industry Argentina 1991 - see Variable: AR1991A_IND - Industry Argentina 2001 - see Variable: AR2001A_IND - Industry Armenia 2001 - see Variable: AM2001A_IND - Principal activity at place of work Armenia 2011 - see Variable: AM2011A_IND - Industry Austria 1971 - see Variable: AT1971A_INDBR - Economic activity of supporter: branch Austria 1981 - see Variable: AT1981A_INDBR - Economic activity of supporter: branch Austria 1991 - see Variable: AT1991A_INDBR - Economic activity of supporter: branch Austria 2001 - see Variable: AT2001A_INDBR - Economic activity of supporter: branch Austria 2011 - see Variable: AT2011A_IND - Industry Bangladesh 1991 - see Variable: BD1991A_IND - Industry Bangladesh 2001 - see Variable: BD2001A_IND - Main work field Bangladesh 2011 - see Variable: BD2011A_IND - Industry Belarus 2009 - see Variable: BY2009A_ECONACT - Industry Benin 1979 - see Variable: BJ1979A_IND - Industry (1-digit) Benin 1992 - see Variable: BJ1992A_IND3 - Industry (2-digits) Benin 2002 - see Variable: BJ2002A_IND2 - Industry (2-digits) Benin 2013 - see Variable: BJ2013A_IND3 - Industry (3-digit) Bolivia 1976 - see Variable: BO1976A_IND - Industry Bolivia 1992 - see Variable: BO1992A_IND3 - Activity, 3 digits Bolivia 2001 - see Variable: BO2001A_IND3 - Industry, 3 digits Bolivia 2012 - see Variable: BO2012A_IND2 - Industry (2 digit) Botswana 1981 - see Variable: BW1981A_IND - Industry Botswana 1991 - see Variable: BW1991A_IND - Industry Botswana 2001 - see Variable: BW2001A_IND - Industry Botswana 2011 - see Variable: BW2011A_IND - Industry, 3-digits Brazil 1960 - see Variable: BR1960A_INDUSTRY - Industry Brazil 1970 - see Variable: BR1970A_INDUSTRY - Industry Brazil 1980 - see Variable: BR1980A_INDUSTRY - Industry Brazil 1991 - see Variable: BR1991A_IND - Industry Brazil 2000 - see Variable: BR2000A_IND - Industry, 5 digits Brazil 2010 - see Variable: BR2010A_IND - Industry of work from July 25 to July 31, 2010 Burkina Faso 1996 - see Variable: BF1996A_IND - Branch of activity Cambodia 1998 - see Variable: KH1998A_IND - Industry Cambodia 2004 - see Variable: KH2004A_IND3 - Industry (3-digits) Cambodia 2008 - see Variable: KH2008A_IND - Industry Cambodia 2013 - see Variable: KH2013A_IND - Industry (3-digits) Cambodia 2019 - see Variable: KH2019A_IND3 - Industy (ISIC rev 4, 3-digit) Cameroon 2005 - see Variable: CM2005A_IND - Industry Canada 1971 - see Variable: CA1971A_IND - Industry Canada 1981 - see Variable: CA1981A_IND - Industry (1981 standard industrial classification) Canada 1991 - see Variable: CA1991A_IND80 - Industry (1980 standard industrial classification) Canada 2001 - see Variable: CA2001A_IND80P - Industry (1980 Standard Industrial Classification) Canada 2011 - see Variable: CA2011A_IND - Industry Chile 1960 - see Variable: CL1960A_IND - Industry Chile 1970 - see Variable: CL1970A_IND4 - Industry (4-digit) Chile 1982 - see Variable: CL1982A_IND4 - Industry (4-digit) Chile 1992 - see Variable: CL1992A_IND - Industry Chile 2002 - see Variable: CL2002A_IND - Industry Chile 2017 - see Variable: CL2017A_IND - Industry (1-digit) China 1982 - see Variable: CN1982A_INDUSTRY - Industry China 1990 - see Variable: CN1990A_IND - Industry China 2000 - see Variable: CN2000A_IND - Industry (2-digit) Colombia 1964 - see Variable: CO1964A_IND4 - Industry, 4 digits Colombia 1973 - see Variable: CO1973A_IND - Industry Colombia 1993 - see Variable: CO1993A_IND - Industry Colombia 2005 - see Variable: CO2005A_IND - Industry (2-digit) Costa Rica 1963 - see Variable: CR1963A_IND3 - Industry, 3 digits Costa Rica 1973 - see Variable: CR1973A_IND4 - Industry, 4 digits Costa Rica 1984 - see Variable: CR1984A_IND4 - Industry, 4 digits Costa Rica 2000 - see Variable: CR2000A_IND3 - Industry, 3 digits Costa Rica 2011 - see Variable: CR2011A_IND - Industry 2-digit Cuba 2002 - see Variable: CU2002A_IND - Industry Cuba 2012 - see Variable: CU2012A_IND - Industry Côte d'Ivoire 1988 - see Variable: CI1988A_IND - Industry (1-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_IND2 - Industry sector (detailed) Dominican Republic 1960 - see Variable: DO1960A_IND - Industry Dominican Republic 1970 - see Variable: DO1970A_IND1 - Industry, 3 digits Dominican Republic 1981 - see Variable: DO1981A_IND - Industry (3-digit) Dominican Republic 2002 - see Variable: DO2002A_IND - Industry Dominican Republic 2010 - see Variable: DO2010A_IND - Main activity of business Ecuador 1962 - see Variable: EC1962A_IND3 - Industry, 3 digits Ecuador 1982 - see Variable: EC1982A_IND3 - Industry Ecuador 1990 - see Variable: EC1990A_IND3 - Industry, 3 digits Ecuador 2001 - see Variable: EC2001A_IND - Industry, 3 digits Ecuador 2010 - see Variable: EC2010A_IND3 - Industry (3 digits, ISIC rev 4) Egypt 1986 - see Variable: EG1986A_IND3 - Industry (3-digit) Egypt 1996 - see Variable: EG1996A_IND3 - Industry (ISIC) Egypt 2006 - see Variable: EG2006A_IND - Industry, 3-digit El Salvador 1992 - see Variable: SV1992A_IND - Industry (3-digit) El Salvador 2007 - see Variable: SV2007A_IND3DIG - Industry (3-digit) Ethiopia 1984 - see Variable: ET1984A_IND2 - Industry Ethiopia 1994 - see Variable: ET1994A_IND - Industry Fiji 1966 - see Variable: FJ1966A_IND - Industry Fiji 1976 - see Variable: FJ1976A_IND - Industry Fiji 1986 - see Variable: FJ1986A_IND - Industry 3 digits Fiji 1996 - see Variable: FJ1996A_IND2DIG - Industry (2 digits) Fiji 2007 - see Variable: FJ2007A_IND2 - Industry, 2 digits Fiji 2014 - see Variable: FJ2014A_IND - Industry Finland 2010 - see Variable: FI2010A_IND - Industry France 1962 - see Variable: FR1962A_IND - Industry France 1968 - see Variable: FR1968A_IND41 - Industry, 41 categories France 1975 - see Variable: FR1975A_INDUN - Industry, UNO France 1982 - see Variable: FR1982A_INDUN - Industry, United Nations nomenclature France 1990 - see Variable: FR1990A_IND15 - Industry, 15 categories France 1999 - see Variable: FR1999A_INDCITI - Industry, ISIC France 2006 - see Variable: FR2006A_IND700N - Economic activity in 700 categories (2003 classification) numeric recode France 2011 - see Variable: FR2011A_IND - Industry, 732 categories Germany 1970 - see Variable: DE1970A_IND - Industry Germany 1971 - see Variable: DE1971A_IND - Industry Germany 1981 - see Variable: DE1981A_IND - Industry Germany 1987 - see Variable: DE1987A_IND - Industry Ghana 2000 - see Variable: GH2000A_IND - Industry Ghana 2010 - see Variable: GH2010A_IND - Industry (major groups) Greece 1971 - see Variable: GR1971A_IND - Industry Greece 1981 - see Variable: GR1981A_IND - Industry Greece 1991 - see Variable: GR1991A_IND - Industry Greece 2001 - see Variable: GR2001A_IND - Industry Greece 2011 - see Variable: GR2011A_IND - Industry Guatemala 1964 - see Variable: GT1964A_IND3 - Field of economic activity (3-digits) Guatemala 1973 - see Variable: GT1973A_IND3 - Industry (3-digits) Guatemala 1981 - see Variable: GT1981A_IND3 - Industry (3-digits) Guatemala 1994 - see Variable: GT1994A_IND2 - Field of economic activity (2-digits) Guatemala 2002 - see Variable: GT2002A_IND1 - Field of economic activity (1-digit) Guinea 1983 - see Variable: GN1983A_IND2 - Branch of economic activity, 2 digits Guinea 2014 - see Variable: GN2014A_IND - Industry (3-digit) Haiti 1982 - see Variable: HT1982A_IND - Branch of work Haiti 2003 - see Variable: HT2003A_IND2 - Industry, 3 digits Honduras 1961 - see Variable: HN1961A_IND - Industry (2-digits) Honduras 1974 - see Variable: HN1974A_IND - Industry (3-digits) Honduras 2001 - see Variable: HN2001A_IND - Industry (4-digit) Honduras 2013 - see Variable: HN2013A_IND3 - Economic activity (3-digit) Hungary 2001 - see Variable: HU2001A_IND - Industry, branch of economy Hungary 2011 - see Variable: HU2011A_IND - Industry Indonesia 1971 - see Variable: ID1971A_IND - Industry Indonesia 1976 - see Variable: ID1976A_IND - Industry Indonesia 1980 - see Variable: ID1980A_IND - Industry Indonesia 1985 - see Variable: ID1985A_IND - Industry of primary occupation Indonesia 1990 - see Variable: ID1990A_IND - Industry of main occupation last week Indonesia 1995 - see Variable: ID1995A_IND - Industry Indonesia 2000 - see Variable: ID2000A_IND - Industry of primary occupation Indonesia 2005 - see Variable: ID2005A_IND - Industry Indonesia 2010 - see Variable: ID2010A_IND - Industry Iran 2006 - see Variable: IR2006A_IND4 - Industry Iran 2011 - see Variable: IR2011A_IND - Industry (3-digit) Iraq 1997 - see Variable: IQ1997A_IND - Industry Ireland 1971 - see Variable: IE1971A_IND - Industry Ireland 1981 - see Variable: IE1981A_IND - Industry class Ireland 1986 - see Variable: IE1986A_IND - Industry class Ireland 1991 - see Variable: IE1991A_IND - Industry class Ireland 1996 - see Variable: IE1996A_IND - Industry class Ireland 2002 - see Variable: IE2002A_IND - Industry class Ireland 2006 - see Variable: IE2006A_IND - Industry class Ireland 2011 - see Variable: IE2011A_IND - Industry Ireland 2016 - see Variable: IE2016A_IND - Industry Israel 1972 - see Variable: IL1972A_IND - Industry Israel 1983 - see Variable: IL1983A_IND - Industry Israel 1995 - see Variable: IL1995A_IND - Industry Israel 2008 - see Variable: IL2008A_IND - Branch of economy Italy 2001 - see Variable: IT2001A_IND - Industry Italy 2011 - see Variable: IT2011A_IND - Sector of economic activity Jamaica 1982 - see Variable: JM1982A_IND - Industry or type of business during past week / in last job Jamaica 1991 - see Variable: JM1991A_IND3 - Industry during past week or in last job, 3 digits Jamaica 2001 - see Variable: JM2001A_IND3 - Industry 3-digit Jordan 2004 - see Variable: JO2004A_IND - Major current economic activity of the establishment Kenya 2019 - see Variable: KE2019A_IND1 - Industry, ISIC section Kyrgyzstan 1999 - see Variable: KG1999A_IND - Activity type of an enterprise you are working in Kyrgyzstan 2009 - see Variable: KG2009A_IND - Type of industry, enterprise or organization Laos 1995 - see Variable: LA1995A_IND2 - Main industry in the last 12 months (2-digit) Laos 2005 - see Variable: LA2005A_IND3 - Industry (ISIC 3-digit) Laos 2015 - see Variable: LA2015A_IND2 - Industry (2-digit ISIC Rev. 4) Lesotho 2006 - see Variable: LS2006A_IND - Industry (2-digits) Liberia 1974 - see Variable: LR1974A_IND - Industry (3-digit) Liberia 2008 - see Variable: LR2008A_IND - Industry Malawi 1987 - see Variable: MW1987A_IND2 - Industry, 2 digit Malawi 1998 - see Variable: MW1998A_IND4 - Industry, 4-digit Malawi 2008 - see Variable: MW2008A_IND2 - Main industry Malawi 2018 - see Variable: MW2018A_IND3 - Main industry (ISIC 2008 3-digit) Malaysia 1970 - see Variable: MY1970A_IND3 - Industry last week Malaysia 1980 - see Variable: MY1980A_IND3 - Industry last week (3 digits) Malaysia 1991 - see Variable: MY1991A_IND3 - Main industry (3 digits) Malaysia 2000 - see Variable: MY2000A_IND3 - Main industry - 3 digits Mali 1987 - see Variable: ML1987A_IND - Principal branch of employment last month Mali 1998 - see Variable: ML1998A_IND - Branch of economic activity Mali 2009 - see Variable: ML2009A_IND - Industry Mauritius 1990 - see Variable: MU1990A_IND - Industry (1-digit) Mauritius 2000 - see Variable: MU2000A_IND1 - Industry (1 digit) Mauritius 2011 - see Variable: MU2011A_IND2 - Industry (2-digit) Mexico 1960 - see Variable: MX1960A_IND - Industry Mexico 1970 - see Variable: MX1970A_IND - Industry Mexico 1990 - see Variable: MX1990A_IND5 - Industry, 5 digits Mexico 1995 - see Variable: MX1995A_IND - Industry Mexico 2000 - see Variable: MX2000A_IND3 - Industry, 3 digits Mexico 2010 - see Variable: MX2010A_IND - Industry Mexico 2015 - see Variable: MX2015A_IND - Industry Mexico 2020 - see Variable: MX2020A_IND - Industry (4-digits) Mongolia 2000 - see Variable: MN2000A_IND - Industry Mongolia 2010 - see Variable: MN2010A_IND2 - Industry, division (ISIC Revision 4) Mongolia 2020 - see Variable: MN2020A_IND3 - Main industry (3-digit) Morocco 1982 - see Variable: MA1982A_IND3 - Industry (3-digit) Morocco 1994 - see Variable: MA1994A_IND2 - Industry (2 digits) Morocco 2004 - see Variable: MA2004A_IND2 - Sector of economic activity (2-digit) Morocco 2014 - see Variable: MA2014A_IND2 - Industry (2-digit) Mozambique 1997 - see Variable: MZ1997A_IND1 - Industry Mozambique 2007 - see Variable: MZ2007A_IND - Industry Mozambique 2017 - see Variable: MZ2017A_IND2 - Main economic activity (2-digits CAE Rev.2) Myanmar 2014 - see Variable: MM2014A_IND - Industry Nepal 2001 - see Variable: NP2001A_IND - Usual industry Nepal 2011 - see Variable: NP2011A_IND - Industry (2-digit) Netherlands 1960 - see Variable: NL1960A_IND - Industry Netherlands 1971 - see Variable: NL1971A_IND - Industry Netherlands 2001 - see Variable: NL2001A_IND - Industry Netherlands 2011 - see Variable: NL2011A_IND - Industry (1-digit) Nicaragua 1971 - see Variable: NI1971A_IND3 - Industry (ISIC2), 3 digits Nicaragua 1995 - see Variable: NI1995A_IND - Industry (ISIC 3.1, 3 digits) Nicaragua 2005 - see Variable: NI2005A_IND3 - Industry (ISIC 3.1, 3 digits)) Pakistan 1973 - see Variable: PK1973A_IND2 - Industry, 2 digit Palestine 1997 - see Variable: PS1997A_IND - Industry Palestine 2007 - see Variable: PS2007A_IND - Industry Palestine 2017 - see Variable: PS2017A_IND - Industry Panama 1960 - see Variable: PA1960A_IND3 - Industry (3 digit) Panama 1970 - see Variable: PA1970A_IND3 - Industry [3 digit] Panama 1980 - see Variable: PA1980A_IND - Industry, 3-digit Panama 1990 - see Variable: PA1990A_IND3 - Industry - 3 Digits Panama 2000 - see Variable: PA2000A_IND - Economic activity, 3 digits Panama 2010 - see Variable: PA2010A_IND - Economic activity, 4 digits Papua New Guinea 1980 - see Variable: PG1980A_IND - Industry, 3 digits Papua New Guinea 2000 - see Variable: PG2000A_IND3 - Industry (3-digit) Paraguay 1962 - see Variable: PY1962A_IND3 - Industry (3 digits) Paraguay 1972 - see Variable: PY1972A_IND3 - Industry (3 digits) Paraguay 1982 - see Variable: PY1982A_IND3 - Industry, 3-digits Paraguay 1992 - see Variable: PY1992A_IND3 - Industry, 3 digits Paraguay 2002 - see Variable: PY2002A_IND - Industry (4 digits) Peru 1993 - see Variable: PE1993A_IND - Economic activity (4 digits) Peru 2007 - see Variable: PE2007A_IND - Economic activity (4-digits) Peru 2017 - see Variable: PE2017A_IND4 - Economic activity (4-digits, in primary job last week) Philippines 1990 - see Variable: PH1990A_IND - Industry Philippines 1995 - see Variable: PH1995A_IND - Industry Philippines 2000 - see Variable: PH2000A_IND - Industry Philippines 2010 - see Variable: PH2010A_IND3 - Kind of business or industry (3-digit) Poland 1978 - see Variable: PL1978A_IND - Industry (of person providing support) Poland 2002 - see Variable: PL2002A_IND - Industry (main employer) Portugal 1981 - see Variable: PT1981A_IND - Industry Portugal 1991 - see Variable: PT1991A_IND - Industry Portugal 2001 - see Variable: PT2001A_IND - Industry Portugal 2011 - see Variable: PT2011A_IND - Industry Puerto Rico 1970 - see Variable: PR1970A_IND1990 - Industry, 1990 basis Puerto Rico 1980 - see Variable: PR1980A_IND1990 - Industry, 1990 basis Puerto Rico 1990 - see Variable: PR1990A_IND - Industry Puerto Rico 2000 - see Variable: PR2000A_IND1990 - Industry, 1990 basis Puerto Rico 2005 - see Variable: PR2005A_IND1990 - Industry, 1990 basis Puerto Rico 2010 - see Variable: PR2010A_IND - Industry Puerto Rico 2015 - see Variable: PR2015A_IND - Industry Puerto Rico 2020 - see Variable: PR2020A_IND - Industry Romania 1977 - see Variable: RO1977A_IND - Industry of supporter Romania 1977 - see Variable: RO1977A_WKACT - Activity category Romania 1992 - see Variable: RO1992A_IND - Industry Romania 2002 - see Variable: RO2002A_IND - Industry Romania 2011 - see Variable: RO2011A_INDGEN - Industry (general categories) Rwanda 2002 - see Variable: RW2002A_IND - Industry Rwanda 2012 - see Variable: RW2012A_IND2 - Industry (3-digit) Saint Lucia 1991 - see Variable: LC1991A_IND3 - Industry, 2 digit Senegal 1988 - see Variable: SN1988A_IND - Industry Senegal 2013 - see Variable: SN2013A_IND3 - Industry (3-digit) Sierra Leone 2004 - see Variable: SL2004A_IND - Industry Slovenia 2002 - see Variable: SI2002A_IND - Industry South Africa 1996 - see Variable: ZA1996A_IND2 - Industry, 2 digits South Africa 2001 - see Variable: ZA2001A_IND3 - Industry, 3 digit South Africa 2007 - see Variable: ZA2007A_IND3 - Industry, 3 digit South Sudan 2008 - see Variable: SS2008A_IND - Industry Spain 1981 - see Variable: ES1981A_IND - Industry Spain 1991 - see Variable: ES1991A_IND - Activity of the establishment Spain 2001 - see Variable: ES2001A_IND - Industry Spain 2011 - see Variable: ES2011A_IND - Industry, 2-digits Sudan 2008 - see Variable: SD2008A_IND - Industry Suriname 2004 - see Variable: SR2004A_IND - Industry Suriname 2012 - see Variable: SR2012A_IND - Industry (groups) Switzerland 1970 - see Variable: CH1970A_IND - Branch of economic activity (industry) Switzerland 1980 - see Variable: CH1980A_IND - Branch of economic activity (industry) Switzerland 1990 - see Variable: CH1990A_IND - Branch of economic activity (industry) Switzerland 2000 - see Variable: CH2000A_IND - Branch of economic activity (industry) Switzerland 2011 - see Variable: CH2011A_IND2 - Industry of local unit, workplace (NOGA 2-digit) Tanzania 2002 - see Variable: TZ2002A_IND - Industry last week Tanzania 2012 - see Variable: TZ2012A_IND - Industry Thailand 1970 - see Variable: TH1970A_IND - Principal industry last year Thailand 1980 - see Variable: TH1980A_IND - Principal industry last year Thailand 1990 - see Variable: TH1990A_IND3 - Principal industry last year, 3 digits Thailand 2000 - see Variable: TH2000A_IND3 - Industry last year, 3 digits Togo 1970 - see Variable: TG1970A_IND - Industry (1-digit) Togo 2010 - see Variable: TG2010A_IND3 - Industry (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_IND - Industry (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_IND - Industry Trinidad and Tobago 2000 - see Variable: TT2000A_IND - Industry (2 digits) Turkey 1985 - see Variable: TR1985A_INDALT - Industry (2-digit) Turkey 1990 - see Variable: TR1990A_IND2 - Industry (2 digits) Turkey 2000 - see Variable: TR2000A_IND2 - Industry, 2 digit Uganda 2002 - see Variable: UG2002A_IND - Industry United Kingdom 1961 - see Variable: UK1961A_IND - Industry United Kingdom 1971 - see Variable: UK1971A_IND - Industry United Kingdom 1991 - see Variable: UK1991A_IND - Industrial classification United Kingdom 2001 - see Variable: UK2001A_IND - Industry classification United States 1960 - see Variable: US1960A_IND - Industry United States 1970 - see Variable: US1970A_IND - Industry United States 1980 - see Variable: US1980A_IND - Industry United States 1990 - see Variable: US1990A_IND - Industry United States 2000 - see Variable: US2000A_IND - Industry United States 2005 - see Variable: US2005A_IND - Industry United States 2010 - see Variable: US2010A_IND - Industry United States 2015 - see Variable: US2015A_IND - Industry United States 2020 - see Variable: US2020A_IND - Industry Uruguay 1963 - see Variable: UY1963A_IND2 - Primary industry [2-digit] Uruguay 1985 - see Variable: UY1985A_IND - Industry during the past week Uruguay 1996 - see Variable: UY1996A_IND2 - Industry (ISIC 3, 2 digits) Uruguay 2006 - see Variable: UY2006A_IND3 - Industry (ISIC rev 3, 3 digits) Venezuela 1981 - see Variable: VE1981A_IND - Industry Venezuela 1990 - see Variable: VE1990A_IND - Industry Venezuela 2001 - see Variable: VE2001A_IND - Industry Vietnam 1989 - see Variable: VN1989A_IND2 - Industry, 2 digits Vietnam 1999 - see Variable: VN1999A_IND3 - Industry, 3 digit Vietnam 2009 - see Variable: VN2009A_IND - Industry Vietnam 2019 - see Variable: VN2019A_IND3 - Industry, 3 digit Zambia 1990 - see Variable: ZM1990A_IND - Industry Zambia 2000 - see Variable: ZM2000A_IND - Type of industry, 3 digits Zambia 2010 - see Variable: ZM2010A_IND2 - Industry, 3 digits Work Variables -- PERSON Status in employment (class of worker) [general version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 0 NIU (not in universe) 1 Self-employed 2 Wage/salary worker 3 Unpaid worker 4 Other 9 Unknown/missing Work Variables -- PERSON Status in employment (class of worker) [detailed version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 000 NIU (not in universe) 100 Self-employed 101 Self-employed, unincorporated 102 Self-employed, incorporated 110 Employer 111 Sharecropper, employer 120 Working on own account 121 Own account, agriculture 122 Domestic worker, self-employed 123 Subsistence worker, own consumption 124 Own account, other 125 Own account, without temporary/unpaid help 126 Own account, with temporary/unpaid help 130 Member of cooperative 140 Sharecropper 141 Sharecropper, self-employed 142 Sharecropper, employee 150 Kibbutz member 199 Self-employed, not specified 200 Wage/salary worker 201 Management 202 Non-management 203 White collar (non-manual) 204 Blue collar (manual) 205 White or blue collar 206 Day laborer 207 Employee, with a permanent job 208 Employee, occasional, temporary, contract 209 Employee without legal contract 210 Wage/salary worker, private employer 211 Apprentice 212 Religious worker 213 Wage/salary worker, non-profit, NGO 214 White collar, private 215 Blue collar, private 216 Paid family worker 217 Cooperative employee 220 Wage/salary worker, government or public sector 221 Federal, government employee 222 State government employee 223 Local government employee 224 White collar, public 225 Blue collar, public 226 Public companies 227 Civil servants, local collectives 230 Domestic worker (work for private household) 240 Seasonal migrant 241 Seasonal migrant, no broker 242 Seasonal migrant, uses broker 250 Other wage and salary 251 Canal zone/commission employee 252 Government employment/training program 253 Mixed state/private enterprise/parastatal 254 Government public work program 255 State enterprise employee 256 Coordinated and continuous collaboration job 300 Unpaid worker 310 Unpaid family worker 320 Apprentice, unpaid or unspecified 330 Trainee 340 Apprentice or trainee 350 Works for others without wage 400 Other 999 Unknown/missing Work Variables -- PERSON Months worked last year WRKMTHS gives the number of months that the respondent worked for profit, pay, or as an unpaid family worker during the previous year. 00 Less than one month 01 1 month 02 2 months 03 3 months 04 4 months 05 5 months 06 6 months 07 7 months 08 8 months 09 9 months 10 10 months 11 11 months 12 12 months 98 Not reported/unknown 99 NIU (not in universe) Work Variables -- PERSON Migration status, previous residence MIGRATEP indicates whether the person's most recent move (if any) was between minor administrative units, major units, or countries. 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 Migration: Global Variables -- PERSON Country of previous residence MIGCTRYP indicates the country of previous residence of international migrants. Persons who never lived abroad are coded to the "non-migrant" category. 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 Migration: Global Variables -- PERSON 1st subnational geographic level of previous residence, world [consistent boundaries over time] 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. 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] 454306 Mwanza, Neno [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] 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] 496011 Ulaanbaatar [Province: Mongolia] 496021 Dornod [Province: Mongolia] 496022 Sukhbaatar [Province: Mongolia] 496023 Khentii [Province: Mongolia] 496041 Tuv [Province: Mongolia] 496043 Selenge [Province: Mongolia] 496044 Dornogobi [Province: Mongolia] 496045 Darkhan-Uul [Province: Mongolia] 496046 Umnugobi [Province: Mongolia] 496048 Dundgobi, Gobisumber [Province: Mongolia] 496061 Orkhon [Province: Mongolia] 496062 Uvurkhangai [Province: Mongolia] 496063 Bulgan [Province: Mongolia] 496064 Bayankhongor [Province: Mongolia] 496065 Arkhangai [Province: Mongolia] 496067 Khuvsgul [Province: Mongolia] 496081 Zavkhan [Province: Mongolia] 496082 Gobi-Altai [Province: Mongolia] 496083 Bayan-Ulgii [Province: Mongolia] 496084 Khovd [Province: Mongolia] 496085 Uvs [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] 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] Migration: Global Variables -- PERSON Years residing in current locality MIGYRS1 indicates how many years the person has resided in their current locality of residence. 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) Migration: Global Variables -- PERSON Department of previous residence, Colombia; consistent boundaries, GIS MIG1_P_CO indicates the person's department of previous residence within Colombia. Persons who never migrated across departments are coded to their department of current residence. 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. 170005 Antioquia 170008 Atlántico 170011 Bogotá D.C., Cundinamarca 170013 Bolívar, Sucre 170015 Boyacá, Casanare 170018 Caquetá 170019 Cauca 170023 Cordoba 170027 Chocó 170041 Huila 170044 La Guajira 170050 Meta 170052 Nariño 170054 Cesar, Norte De Santander, Magdalena 170066 Caldas, Quindío, Risaralda 170068 Santander 170073 Tolima 170076 Valle Del Cauca 170081 Arauca 170086 Putumayo 170088 Archipiélago De San Andrés Y Providencia 170095 Amazonas, Guaviare, Vaupés, Vichada, Guainía 170097 Abroad 170098 Unknown Migration: A-E Variables -- PERSON Relationship to head of household <svar v="CO64A400" a="all"><span class="em">3. Code relationship with the head of household</span> ____ _<br /><div class="i1">Write the head of household first, then, according to the case, wife, child, grandchild, uncle, guest, renter, servant, child of the servant, etc.</div><br /></svar> <svar v="CO64A400" a="all"><span class="h3">Relationship with the head of the household</span><br /><br /><span class="em">Column No. 3 - What is your relationship with the head of the family?</span> A person who supplies information should respond to this question in the following manner:<br /><br />Before the name of the head of family the word "head" will be written down and, next, according to the case, the corresponding familial relationship, like: spouse, child, etc. Persons who without having familial relationships with the Head make part of the family unit, should be registered with the names that correspond to them, such as: guests, tenants or servants. If children of servants are older than 14 years they should be registered as servants and if they have not reached this age, as "children of servant".<br /><br />For cases of <span class="em">non-family groups</span> the head will be written down in the first place, according to the hierarchy and immediately the rest of the persons specifying if it concerns a prisoner, soldier, guard, elderly person, student, religious person, passenger, etc. A person who does not share meals with the census family should be registered as Head for being by themselves a <span class="em">census family</span> of one person and in the contrary case they will be registered as a tenant. In family residences where bakeries and other domestic industries are run, whose workers live together with the family of the owners, persons of the census family, should be registered first pointing out their corresponding relationship and afterwards workers of the industry, with the name "lodger".<br /></svar> Colombia 1964: This variable indicates the relationship to the head of the household. 1 Head of household 2 Wife 3 Children 4 Other relatives 5 Guests 6 Tenants 7 Servants 8 People in non-family groups Demographic Variables -- PERSON Sex <svar v="CO64A401" a="all"><span class="em">4. Sex</span> _<br /><div class="i1">Write accordingly, man or woman</div><br /></svar> <svar v="CO64A401" a="all"><span class="h3">Sex</span><br /><br /><span class="em">Column No. 4 - In this column the word "man" or "woman" should be written down, according to what the case is</span>. For no reason should the sex of persons not be indicated.<br /></svar> Colombia 1964: All persons This variable indicates gender. 1 Male 2 Female Demographic Variables -- PERSON Age <svar v="CO64A402" a="all"><span class="em">5. Age</span> ____<br /><div class="i1">Write the age in full years. For children younger than one year, write the months as 0/12, 1/12, 2/12, 11/12, etc.</div><br /></svar> <svar v="CO64A402" a="all"><span class="h3">Age</span><br /><br /><span class="em">Column No. 5 - How old did you become on your last birthday?</span> In this column the exact age of a person in completed years at the last birthday should be registered. The age of children less than one year should be written down in twelve parts of the year, so: A child two months old will be written down 2/12; one of four months 4/12 and one of fifteen days that is less than a month 0/12.<br /><br />Fractions of years or months in the age of persons should not be written down when they are older than one year. If they are five years a half years old they will be written down only as 5. Fractions and months are used only for those younger than one year (zero years).<br /><br />If a person says that they do not know their age, they should find out by the approximate date of their birth with the help of known facts.<br /><br /><span class="pg">[p. 17]</span><br /><br />If this is not possible, the age that they think they are should be written down. In no case should this information be left blank.<br /><br />If the age that a person says to be ends in zero (0) or in five (5), it should be asked if this age is exact, with the purpose of eliminating the tendency to give round numbers.<br /></svar> Colombia 1964: All persons This variable indicates age in years, and in some cases, in months. 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99+ 100 0 months 101 1 month 102 2 months 103 3 months 104 4 months 105 5 months 106 6 months 107 7 months 108 8 months 109 9 months 110 10 months 111 11 months 999 Unknown Demographic Variables -- PERSON Marital status <svar v="CO64A403" a="all"><span class="em">6. Marital status code</span> ____ _<br /><div class="i1">Write accordingly, single, married, consensual union, separated, widow.</div><br /></svar> <svar v="CO64A403" a="all"><span class="h3">Marital status</span><br /><br /><span class="em">Column No. 6 - What is your current civil state?</span> The civil state that a person has on the census date should be registered, writing down according to the case the determination of single, married, consensual union, widowed, or separated.<br /><br />It is necessary to establish clearly the current civil state of each enumerated person. This should be only one response that is registered in column 6. The corresponding civil state should be written down of all persons, even the youngest of age.<br /><br />The definitions of civil state are as follows:<br /><br /><div class="i1"><span class="em">Single</span>: A person is single when they have never married, and on the census date they do not live in a consensual union or as married without being so.<br /><br /><span class="em">Married</span>: When a person says they are married and having legalized their union with legal ties.<br /><br /><span class="em">Consensual Union</span>: If a person lives as married without being so, or one who lives as husband or wife without having legalized the union, they are not considered as a single person but rather as in "Consensual Union".<br /><br /><span class="em">Separated</span>: When a person is legally married and does not live with their spouse due to reasons other than temporary absence for work, vacation, on leave, business, etc.<br /><br /><span class="em">Widowed</span>: When a person declared to be widowed, has not married again and does not live in consensual union or as married without being so.</div><br /></svar> Colombia 1964: All persons This variable indicates marital status. 1 Single 2 Married 3 Widowed 4 Consensual union 5 Separated Demographic Variables -- PERSON Department of birth <svar v="CO64A404 CO64A405" a="all"><span class="em">7. Place of birth code</span> ____ _<br /><div class="i1">For those born in Colombia, write the name of the municipality and the first three letters of the Department or Territory. For those born outside of Colombia, write the country of birth.</div><br /></svar> <svar v="CO64A404 CO64A405" a="all"><span class="h3">Place of birth</span><br /><br /><span class="em">Column No. 7 - What is the name of the municipality where you were born?</span> The name of the municipality where Colombians were born will be written down and also the first three letters of the name of the department, administration or precinct.<br /><br />For Colombians born abroad (that is, children of Colombian father and mother who had been born abroad and are found in Colombia, and for foreigners, the name of the country where they were born should be registered, in accordance with the current international division of countries, for example: United States, France, West Germany etc.<br /></svar> Colombia 1964: All persons This variable indicates place (department) of birth. 01 Antioquia 02 Atlantico 03 Bolivar 04 Boyaca 05 Caldas 06 Cauca 07 Cordoba 08 Distrito Especial 09 Cundinamarca 10 Choco 11 Huila 12 Guajira 13 Magdalena 14 Meta 15 Nariño 16 Norte de Santander 17 Santander 18 Tolima 19 Valle 21 Arauca 22 San Andres y Providencia 23 Caqueta 31 Amazonas 32 Guania 33 Putumayo 34 Vaupes 35 Vichada 40 Canada 41 United States 42 Mexico 43 Costa Rica 44 Cuba 45 Guatemala 46 Nicaragua 47 Panama 48 El Salvador 49 Other Central American countries 50 Argentina 51 Brazil 52 Chile 53 Ecuador 54 Peru 55 Venezuela 56 Other South American countries 60 China 61 Japan 62 Lebanon 63 Palestine 64 Syria 65 Other Asian countries 70 Germany 71 Austria 72 Belgium 73 Czechoslovakia 74 Denmark 75 Spain 76 Greece 77 Netherlands 78 Hungary 79 Italy 80 Poland 81 United Kingdom 82 Romania 83 Sweden 84 Switzerland 85 Soviet Union 86 Yugoslavia 87 Other European countries 90 Africa 91 Oceania Nativity and Birthplace Variables -- PERSON Birth municipality compared to that of enumeration <svar v="CO64A404 CO64A405" a="all"><span class="em">7. Place of birth code</span> ____ _<br /><div class="i1">For those born in Colombia, write the name of the municipality and the first three letters of the Department or Territory. For those born outside of Colombia, write the country of birth.</div><br /></svar> <svar v="CO64A404 CO64A405" a="all"><span class="h3">Place of birth</span><br /><br /><span class="em">Column No. 7 - What is the name of the municipality where you were born?</span> The name of the municipality where Colombians were born will be written down and also the first three letters of the name of the department, administration or precinct.<br /><br />For Colombians born abroad (that is, children of Colombian father and mother who had been born abroad and are found in Colombia, and for foreigners, the name of the country where they were born should be registered, in accordance with the current international division of countries, for example: United States, France, West Germany etc.<br /></svar> Colombia 1964: All persons This variable indicates the relationship between birth place and place of enumeration. 1 Same municipality as that of enumeration 2 Different municipality from that of enumeration, but same department 3 Municipality belonging to a department different from that of enumeration 4 Code for foreigners (different country) Nativity and Birthplace Variables -- PERSON Period of time in current residence <svar v="CO64A406" a="all"><span class="em">8. Time</span> ____<br /><div class="i1">For those born in other municipalities, write the length of time spent in the current place. If it is less than one year, write the months. Examples, 0/12, 3/12, 7/12, 11/12, etc. For those who were born in the municipality where they are registered, write the word 'always'.</div><br /></svar> <svar v="CO64A406" a="all"><span class="em">Time</span><br /><br /><span class="em">Column No. 8 - How long have you lived in this municipality?</span><br /><br />In this column the <span class="em">number of continuous years</span> that a person has lived recently within the limits of the municipality where the enumeration is done will be written down.<br /><br /><span class="pg">[p. 18]</span><br /><br />The continuous years will be counted backwards from the census date. When one has not stayed a complete year in the municipality of enumeration the number of months in fractions of twelve will be written down.<br /><br />For those <span class="em">born in the municipality</span> in which they are being enumerated and who are present on the census date, the word <span class="em">always</span> will be registered.<br /></svar> Colombia 1964: All persons This variable indicates the length of time (in years and, in some cases, months) spent in the current residence, and if always lived in current residence, length of time is the same as age. 001 1 year 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 0 months 101 1 month 102 2 months 103 3 months 104 4 months 105 5 months 106 6 months 107 7 months 108 8 months 109 9 months 110 10 months 111 11 months 998 Unknown Migration: Global Variables -- PERSON Previous residence (department) or current for those born where enumerated <svar v="CO64A407 CO64A408" a="all"><span class="em">9. Origin</span> ____ _<br /><div class="i1">Write the name of the municipality of residency immediately prior and the first three letters of the department or territory for those who were born in other municipalities. For example: --Anori--Ant.; Cali--Val. If they were born in the municipality where they are enumerated, make a horizontal line.</div><br /></svar> <svar v="CO64A407 CO64A408" a="all"><span class="em">Origin</span><br /><br /><span class="em">Column No. 9 - What was your municipality previous to arriving at this municipality?</span><br /><br />For <span class="em">persons born outside of the municipality</span> in which they are being enumerated the name of the municipality where they had their residence immediately before should be written down. After the name of the municipality the first three letters of the Department, Administration or Precinct should be written.<br /><br />Living or staying as <span class="em">resident</span> is understood to be settled down in the Municipality for reasons of work, business, family life or any other reason of economic or social character. A person can be <span class="em">resident</span> for a very short or very long time.<br /><br />Example 1: Mr. Juan Ríos Ramos, of Boyacá, settled down in the Municipality of Rionegro in the Department of Antioquia, and from this Municipality he moved to the city of Cali. The enumerator should register in column 9 as municipality of residence immediately before, the following annotation "Rionegro - Ant."<br /><br />Example 2: Mr. Roberto Martínez was born in Cali and was enumerated in this city. In column 9 the expression "Always" should appear.<br /></svar> Colombia 1964: All persons This variable indicates the department of previous residence or current residence if always lived in residence of enumeration. 01 Antioquia 02 Atlantico 03 Bolivar 04 Boyaca 05 Caldas 06 Cauca 07 Cordoba 08 Distrito Especial 09 Cundinamarca 10 Choco 11 Huila 12 Guajira 13 Magdalena 14 Meta 15 Nariño 16 Norte de Santander 17 Santander 18 Tolima 19 Valle 21 Arauca 22 San Andres y Providencia 23 Caqueta 31 Amazonas 32 Guania 33 Putumayo 34 Vaupes 35 Vichada 40 Canada 41 United States 42 Mexico 43 Costa Rica 44 Cuba 45 Guatemala 46 Nicaragua 47 Panama 48 El Salvador 49 Other Central American countries 50 Argentina 51 Brazil 52 Chile 53 Ecuador 54 Peru 55 Venezuela 56 Other South American countries 60 China 61 Japan 62 Lebanon 63 Palestine 64 Syria 65 Other Asian countries 70 Germany 71 Austria 72 Belgium 73 Czechoslovakia 74 Denmark 75 Spain 76 Greece 77 Netherlands 78 Hungary 79 Italy 80 Poland 81 United Kingdom 82 Romania 83 Sweden 84 Switzerland 85 Soviet Union 86 Yugoslavia 87 Other European countries 90 Africa 91 Oceania Migration: Global Variables -- PERSON Migrant from department capital <svar v="CO64A409" a="all"><span class="em">10. Zone</span> ____<br /><div class="i1">If the person is originally from the Department capital, write "yes". If not, write "no".</div><br /></svar> <svar v="CO64A409" a="all"><span class="em">Urban or rural area</span><br /><br />Column No. 10 - In the municipality where you have your previous residence did you live in the capital of the municipality or in the rural part? In this column yes should be written for persons who lived in the capital of the municipality of previous residence, and no for those who lived in the places far from the municipal capital.<br /></svar> Colombia 1964: All persons This variable indicates whether originally from the department capital. 1 Yes 2 No 3 Foreign place Migration: Global Variables -- PERSON Literacy <svar v="CO64A410" a="all"><span class="em">11. Literacy</span> ____<br /><div class="i1">Write "yes" for those who know how to read and write. If not, write "no".</div><br /></svar> <svar v="CO64A410" a="all"><span class="h3">Literacy</span><br /><br /><span class="em">Column No. 11 - Do you know how to read and write?</span> If a person knows how to read and write a simple paragraph, yes should be written down in this column. In the contrary case no should be written down.<br /><br />When a person knows how to read but not write or the opposite, and in the case of one who writes only numbers or barely draws their name, no should be written down. One should proceed equally in cases of persons who forgot how to read and write.<br /><br />This column cannot remain without information and therefore special care is recommended to the enumerator in the registering of this information.<br /></svar> Colombia 1964: Persons age 5+ [discrepancies: none] This variable indicates literacy status. 1 Literate 2 Illiterate 9 NIU (not in universe) Education Variables -- PERSON Educational level, 1 digit <svar v="CO64A411 CO64A412" a="all"><span class="em">12. Schooling</span> ____<br /><div class="i1">Write as applicable: Elementary, Secondary, Commercial Technical Schooling, Artistic Technical Schooling, Nursing, Industrial Technical Schooling, Agricultural Technical Schooling, University, Schooling for the <span class="lang">Magisterio</span> [elementary and secondary teaching]</div><br /></svar> <svar v="CO64A411 CO64A412" a="all"><span class="h3">Level of education</span><br /><br /><span class="em">Column No. 12 - What education have you received in education centers?</span> The enumerator should ask this question with reference to all persons 5 years old or older. The response should be written down in this column.<br /><br />The annotation in the census form should indicate clearly and exactly the class of education received, for example: Primary, Secondary, Technical Industrial, Arts and Crafts, Complementary, Home for Farmers, Agricultural or Livestock, Elemental Nursing, Higher Nursing, Artistic Schooling, Elemental Religious, Higher Religious, Primary School Teacher, University, Military, Radio-technical, etc.<br /><br />The generic name of <span class="em">secondary</span> education should not be used since it means many types of teaching and obtaining the exact name of each one of them is what is important to the Censuses. For persons who did not receive any class of instruction in educational centers the expression <span class="em">none</span> should be written down.<br /><br />In no case should this important aspect be left without annotation.<br /><br /><span class="em">Column No. 13 - What was the highest year that you passed in the education that you just indicated?</span> The enumerator should write down the number that corresponds to the last year of study <span class="em">passed</span>, for example: If a person is said to have passed as the last studied, the third year of Secondary school, the enumerator should write the number 3 in this column, in front of the word Secondary school that was written down in the immediately previous column (12).<br /><br />Another example: If a person passed the first year of primary school, they should be registered in column 12 with the word Primary and in column 13 with the number 1 which corresponds to the year of education passed.<br /><br />For persons who have not received any class of education in educational centers, they will be written down as zero (0).<br /></svar> Colombia 1964: Persons age 5+ [discrepancies: none] This variable indicates the person's education level in 1-digit. 0 No completed years 1 Primary 2 Secondary degree 3 Technical education 4 Teaching school (magisterio) 5 University 6 Special education 7 Fundamental education (basic literacy) 9 NIU (not in universe) Education Variables -- PERSON Educational level, 2 digits <svar v="CO64A411 CO64A412" a="all"><span class="em">12. Schooling</span> ____<br /><div class="i1">Write as applicable: Elementary, Secondary, Commercial Technical Schooling, Artistic Technical Schooling, Nursing, Industrial Technical Schooling, Agricultural Technical Schooling, University, Schooling for the <span class="lang">Magisterio</span> [elementary and secondary teaching]</div><br /></svar></p> <p><svar v="CO64A412"><span class="em">13. Year</span> _<br /><div class="i1">Write the highest educational year completed in column 12.</div><br /></svar> <svar v="CO64A411 CO64A412" a="all"><span class="h3">Level of education</span><br /><br /><span class="em">Column No. 12 - What education have you received in education centers?</span> The enumerator should ask this question with reference to all persons 5 years old or older. The response should be written down in this column.<br /><br />The annotation in the census form should indicate clearly and exactly the class of education received, for example: Primary, Secondary, Technical Industrial, Arts and Crafts, Complementary, Home for Farmers, Agricultural or Livestock, Elemental Nursing, Higher Nursing, Artistic Schooling, Elemental Religious, Higher Religious, Primary School Teacher, University, Military, Radio-technical, etc.<br /><br />The generic name of <span class="em">secondary</span> education should not be used since it means many types of teaching and obtaining the exact name of each one of them is what is important to the Censuses. For persons who did not receive any class of instruction in educational centers the expression <span class="em">none</span> should be written down.<br /><br />In no case should this important aspect be left without annotation.<br /><br /><span class="em">Column No. 13 - What was the highest year that you passed in the education that you just indicated?</span> The enumerator should write down the number that corresponds to the last year of study <span class="em">passed</span>, for example: If a person is said to have passed as the last studied, the third year of Secondary school, the enumerator should write the number 3 in this column, in front of the word Secondary school that was written down in the immediately previous column (12).<br /><br />Another example: If a person passed the first year of primary school, they should be registered in column 12 with the word Primary and in column 13 with the number 1 which corresponds to the year of education passed.<br /><br />For persons who have not received any class of education in educational centers, they will be written down as zero (0).<br /></svar> Colombia 1964: Persons age 5+ [discrepancies: type I trace; type II none] This variable indicates the person's education level in 2-digits. 00 Years completed unspecified 01 Preschool education (kindergarten) 10 Primary, years completed unspecified 11 First year of primary 12 Second year of primary 13 Third year of primary 14 Fourth year of primary 15 Fifth year of primary 20 Secondary, years completed unspecified 21 First year of secondary 22 Second year of secondary 23 Third year of secondary 24 Fourth year of secondary 25 Fifth year of secondary 26 Sixth year of secondary 31 Industrial technical schooling 32 Agricultural technical schooling 33 Commercial technical schooling 34 Nursing technical schooling 35 Artistic technical schooling 36 Religious technical schooling 37 Unspecified technical schooling 40 Teaching school (magisterio) 50 University education, years completed unspecified 51 First year of university 52 Second year of university 53 Third year of university 54 Fourth year of university 55 Fifth year of university 56 Sixth year of university 60 Special education (physical or mental disability) 70 Fundamental education (in night schools and via radio) (basic literacy) 99 NIU (not in universe) Education Variables -- PERSON Employment status <svar v="CO64A414" a="all"><span class="em">15. Do you currently have paid employment?</span> ____<br /><div class="i1">Write "yes" or "no".</div><br /></svar></p> <p><svar v=" CO64A417 CO64A414" a=" CO64A417"><span class="em">19. Occupation or condition of unemployment</span> ____ _<br /><div class="i1">Write the occupation or usual employment of the person. Examples: Farmer, doctor, carpenter, accountant, manual laborer, servant, etc. If the person does not work, write the unemployment condition: renter, pensioner, disabled, elderly, household domestic duties, student, etc. For those who are unemployed, write their last paid occupation.</div><br /></svar> <svar v="CO64A414" a="all"><span class="em">Column No. 15 - Remunerated activity on the census date</span><br /><br />Are you working a remunerated occupation on the census date? The enumerator should ask this question to all persons 10 years old or older.<br /><br /><span class="pg">[p. 20]</span><br /><br />For persons who have a remunerated occupation <span class="em">on the census date</span>, the word yes should be written down. For persons who did not have a remunerated occupation on this date, the word <span class="em">no</span> should be written down.<br /><br />A remunerated occupation refers to a craft a person does by which they obtain a retribution in money or in kind.<br /></svar></p> <p><svar v="CO64A414 CO64A417" a=" CO64A417"><span class="h3">Occupation and condition of unemployment</span><br /><br /><span class="em">Column No. 19 - What is your habitual occupation or craft?</span> Occupation is understood as profession, craft or class of job that a person who is working does habitually or what a person who is unemployed did on the census date.<br /><br />One should write down in this column of the form:<br /><br /><div class="i1">a) The habitual occupation of persons who are working on the census date.<br /><br />b) The habitual occupation of persons who are found without work on the census date.</div><br /><br /><span class="pg">[p. 21]</span><br /><br /><div class="i1">c) The condition of persons who do not work because of being of being under age, elderly or invalids, rentiers, pensioned, or who do domestic duties without remuneration, etc.</div><br /><br /><span class="em">Habitual occupation</span>. - The habitual occupation of a person, that is, the occupation to which the most time is dedicated should be written down. When a person has many occupations and it is hard for them to know in which the most time is spent, the occupation that produces the greatest incomes should be written down.<br /><br />In this column, the complete name of the occupation should be written down in a manner that clearly indicates the class or craft or task that is done. In many occupations it is necessary to employ more than one word to be able to describe them correctly, like "wholesale storekeeper", "engineer of mines", "automobile greaser", "retail storekeeper", "upholsterer of furniture", etc., single names like "storekeeper", "engineer", "greaser", "upholsterer", etc indicate nothing respective of the specific occupation. Equally, generic names <span class="em">should not be employed</span> like "manual laborer", "white collar worker", "industrial", etc., since they also do not correctly define the occupation correctly. In some occupations like those of accountant, typist, superintendent, etc., this single name describes the craft or task correctly and therefore can be written down without other specification.<br /><br />The habitual occupation also should be registered for persons interned temporarily in hospitals, clinics, as also those who are found detained for police reasons.<br /><br /><span class="em">Occupation of family helpers</span>. - For members of a family (spouse, children relatives) who collaborate in the economic company of the Head of the family or other relative during a time less than two days a week, 10 days a month or 4 months a year, without pay or fixed daily wages, they should be written down as the same occupation as the Head of family or the relative who they help.<br /><br />Food, in these cases, should not be considered remuneration.<br /><br /><span class="em">Secondary remunerated occupations: </span>For students, housewives and the rest of persons whose principal activity is not remunerated but who at the same time has a secondary occupation that permits them some monetary income, this last occupation should be registered even though they only do it on some days or some hours a day.<br /><br /><span class="em">Agricultural occupations</span>. - The following occupations should be distinguished as agricultural occupations:<br /><br /><span class="em">Farmer</span>: The person who directs the planting and collection of crops, either on private property or for a third party company without depending on other persons.<br /><br />Also family helpers who work on the farm of the Head of family or relative are farmers, without pay or fixed daily wage and during a time not shorter than two days a week, 10 days a month or 4 months a year.<br /><br /><span class="em">Administrator of a farm</span>: A person who directs jobs of an agricultural or livestock farm, and for it receives remuneration from the corresponding owner or from the manager of the farm.<br /><br /><span class="pg">[p. 22]</span><br /><br /><span class="em">Foreman of the farm</span>: A person who directs a group of agricultural manual laborers, controls their jobs and for this receives remuneration.<br /><br /><span class="em">Agricultural manual laborer</span>: A person who works as a worker in a farm for a daily wages in money, products or both.<br /><br />The rest of the occupations of persons who work in farms as helpers in the agricultural labors should be registered as their specific names, such as: Agronomist Engineer, Farm Pilot, Tractor driver, and the same with the personnel of administration and services: Mechanic, Accountant, Inspector, Typist, Servant, etc.<br /><br /><span class="em">Are you looking for work for the first time?</span><br /><br />The cases of persons who on the census date because of not having worked before are found looking for work for the first time should be written down. The annotation will be made in the same column 19, as: "<span class="em">B. T. X. 1a vez</span>"<br /><br /><span class="em">Condition of inactivity</span>. - For a persons who do not work due to conditions of age, health or are dedicating their time to study in education centers, domestic duties, or those who live on investments or pensions and do not have a remunerated occupation, the condition of inactivity that corresponds to them, in accordance with the following names should be registered:<br /><br /><div class="i1"><span class="em">Home</span>: Women who without having a remunerated occupation do domestic duties.<br /><br /><span class="em">Minor</span>: A person younger than 14 years who does not study and does not have an occupation.<br /><br /><span class="em">Student</span>: A person who studies in an education establishment and does not have a remunerated occupation.<br /><br /><span class="em">Elderly person</span>: A person who cannot work because of age.<br /><br /><span class="em">Invalid</span>: A person who cannot carry out a job because of a physical incapacity.<br /><br /><span class="em">Rentier</span>: A person without remunerated occupation who lives from the product of investments or stocks.<br /><br /><span class="em">Pensioned</span>: A person without remunerated occupation who lives on a pension supplied by official and private entities.<br /><br /><span class="em">Interned</span>: A person who resides and is attended in a social institution of health, like mental hospitals, sanitariums, old peoples home, hospices, etc.<br /><br /><span class="em">Imprisoned</span>: A resident in jails where they complete a sentence. They should not be confused with a simple detainee.<br /><br /><span class="em">Religious person</span>: Persons of both sexes who live in convents.</div><br /><br />For persons who are found in collective residences (barracks, convents, hospitals, boarding schools, etc.) the habitual occupation, grade, title or condition should be registered, for example: administrator, superintendent, servant, lieutenant, sergeant, corporal, soldier, student, priest, etc.<br /><br />Persons who do not work should not be confused with those who having worked in some part of the census year, are found without a job or employment on the official day of the census. Equally, these last persons also should not be confused with those looking for a job for the first time, such as persons who finished their studies and are looking for work.<br /></svar> Colombia 1964: All persons This variable indicates activity status. This variable was constructed based on a yes/no question about whether the person was working along with additional information gathered about activity status for those who were not working. This variable is used to define the universe for subsequent employment questions. In the labor force is defined as those who answered yes they were working or those who answered no they were not working and do not have any other activity status. Those not in the labor force are those who answered no they were not working and had another activity status (i.e. household domestic duties, students, minors, elderly, disabled and institutionalized, pensioners and rentiers, or others in similar conditions). 1 Has paid work 2 Does not have paid work (unemployed) 3 Household domestic duties 4 Students 5 Elderly 6 Disabled and institutionalized 7 Pensioners and rentiers 8 Others in similar conditions 9 Persons under age 5 and non-students age 5-11 Work Variables -- PERSON Looked for work <svar v="CO64A415" a="all"><span class="em">16. If you do not currently have paid employment, have you looked for work in the previous month?</span> ____<br /><div class="i1">Write "yes" or "no".</div><br /></svar> <svar v="CO64A415" a="all"><span class="em">Column No. 16</span> - This column will be employed only for persons who do not have an occupation <span class="em">on the census date</span>, that is, for those for whom <span class="em">no</span> was written in column 15.<br /><br />If an unemployed person looked for work during the month that ended with the census date, the word yes will be written down. In the case of not having looked for work during this month, the word no will be written down.<br /></svar> Colombia 1964: Persons age 12+ who were working [discrepancies: none] This variable indicates if the person is currently looking for work. 1 Yes 2 No 9 NIU (not in universe) Work Variables -- PERSON Months worked <svar v="CO64A416" a="all"><span class="em">17. Write the number of months that you have had paid employment in the year preceding the census.</span> ____<br /></svar> <svar v="CO64A416" a="all"><span class="em">Column No. 17 - Time worked</span>. - How many months did you work during the year that ended June 2? This question will be asked to all employed and unemployed persons. The number of complete months that a person worked during the year before the census date should be written down, whether full time or part time.<br /><br />Special care is recommended in registering the time worked by persons whose job has not been full time. If a person supplies information about the number of days worked habitually during the week, the result of the months worked will be obtained in the following table:<br /><br />Days worked in the week / Months worked<br />1 day = 2 months<br />2 day = 4 months<br />3 day = 6 months<br />4 day = 8 months<br />5 day = 10 months<br />6 day = 12 months<br /><br />Vacations, sickness-related absences, or other causes; during which one receives remuneration in money or in kind, should be considered as time worked.<br /></svar> Colombia 1964: Persons age 12+ who were working [discrepancies: none] This variable indicates the number of months worked during the year that ended June 2. 00 No months worked 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) Work Variables -- PERSON Occupation (COTA, 4 digits) <svar v=" CO64A417 CO64A414" a=" CO64A417"><span class="em">19. Occupation or condition of unemployment</span> ____ _<br /><div class="i1">Write the occupation or usual employment of the person. Examples: Farmer, doctor, carpenter, accountant, manual laborer, servant, etc. If the person does not work, write the unemployment condition: renter, pensioner, disabled, elderly, household domestic duties, student, etc. For those who are unemployed, write their last paid occupation.</div><br /></svar> <svar v="CO64A414 CO64A417" a=" CO64A417"><span class="h3">Occupation and condition of unemployment</span><br /><br /><span class="em">Column No. 19 - What is your habitual occupation or craft?</span> Occupation is understood as profession, craft or class of job that a person who is working does habitually or what a person who is unemployed did on the census date.<br /><br />One should write down in this column of the form:<br /><br /><div class="i1">a) The habitual occupation of persons who are working on the census date.<br /><br />b) The habitual occupation of persons who are found without work on the census date.</div><br /><br /><span class="pg">[p. 21]</span><br /><br /><div class="i1">c) The condition of persons who do not work because of being of being under age, elderly or invalids, rentiers, pensioned, or who do domestic duties without remuneration, etc.</div><br /><br /><span class="em">Habitual occupation</span>. - The habitual occupation of a person, that is, the occupation to which the most time is dedicated should be written down. When a person has many occupations and it is hard for them to know in which the most time is spent, the occupation that produces the greatest incomes should be written down.<br /><br />In this column, the complete name of the occupation should be written down in a manner that clearly indicates the class or craft or task that is done. In many occupations it is necessary to employ more than one word to be able to describe them correctly, like "wholesale storekeeper", "engineer of mines", "automobile greaser", "retail storekeeper", "upholsterer of furniture", etc., single names like "storekeeper", "engineer", "greaser", "upholsterer", etc indicate nothing respective of the specific occupation. Equally, generic names <span class="em">should not be employed</span> like "manual laborer", "white collar worker", "industrial", etc., since they also do not correctly define the occupation correctly. In some occupations like those of accountant, typist, superintendent, etc., this single name describes the craft or task correctly and therefore can be written down without other specification.<br /><br />The habitual occupation also should be registered for persons interned temporarily in hospitals, clinics, as also those who are found detained for police reasons.<br /><br /><span class="em">Occupation of family helpers</span>. - For members of a family (spouse, children relatives) who collaborate in the economic company of the Head of the family or other relative during a time less than two days a week, 10 days a month or 4 months a year, without pay or fixed daily wages, they should be written down as the same occupation as the Head of family or the relative who they help.<br /><br />Food, in these cases, should not be considered remuneration.<br /><br /><span class="em">Secondary remunerated occupations: </span>For students, housewives and the rest of persons whose principal activity is not remunerated but who at the same time has a secondary occupation that permits them some monetary income, this last occupation should be registered even though they only do it on some days or some hours a day.<br /><br /><span class="em">Agricultural occupations</span>. - The following occupations should be distinguished as agricultural occupations:<br /><br /><span class="em">Farmer</span>: The person who directs the planting and collection of crops, either on private property or for a third party company without depending on other persons.<br /><br />Also family helpers who work on the farm of the Head of family or relative are farmers, without pay or fixed daily wage and during a time not shorter than two days a week, 10 days a month or 4 months a year.<br /><br /><span class="em">Administrator of a farm</span>: A person who directs jobs of an agricultural or livestock farm, and for it receives remuneration from the corresponding owner or from the manager of the farm.<br /><br /><span class="pg">[p. 22]</span><br /><br /><span class="em">Foreman of the farm</span>: A person who directs a group of agricultural manual laborers, controls their jobs and for this receives remuneration.<br /><br /><span class="em">Agricultural manual laborer</span>: A person who works as a worker in a farm for a daily wages in money, products or both.<br /><br />The rest of the occupations of persons who work in farms as helpers in the agricultural labors should be registered as their specific names, such as: Agronomist Engineer, Farm Pilot, Tractor driver, and the same with the personnel of administration and services: Mechanic, Accountant, Inspector, Typist, Servant, etc.<br /><br /><span class="em">Are you looking for work for the first time?</span><br /><br />The cases of persons who on the census date because of not having worked before are found looking for work for the first time should be written down. The annotation will be made in the same column 19, as: "<span class="em">B. T. X. 1a vez</span>"<br /><br /><span class="em">Condition of inactivity</span>. - For a persons who do not work due to conditions of age, health or are dedicating their time to study in education centers, domestic duties, or those who live on investments or pensions and do not have a remunerated occupation, the condition of inactivity that corresponds to them, in accordance with the following names should be registered:<br /><br /><div class="i1"><span class="em">Home</span>: Women who without having a remunerated occupation do domestic duties.<br /><br /><span class="em">Minor</span>: A person younger than 14 years who does not study and does not have an occupation.<br /><br /><span class="em">Student</span>: A person who studies in an education establishment and does not have a remunerated occupation.<br /><br /><span class="em">Elderly person</span>: A person who cannot work because of age.<br /><br /><span class="em">Invalid</span>: A person who cannot carry out a job because of a physical incapacity.<br /><br /><span class="em">Rentier</span>: A person without remunerated occupation who lives from the product of investments or stocks.<br /><br /><span class="em">Pensioned</span>: A person without remunerated occupation who lives on a pension supplied by official and private entities.<br /><br /><span class="em">Interned</span>: A person who resides and is attended in a social institution of health, like mental hospitals, sanitariums, old peoples home, hospices, etc.<br /><br /><span class="em">Imprisoned</span>: A resident in jails where they complete a sentence. They should not be confused with a simple detainee.<br /><br /><span class="em">Religious person</span>: Persons of both sexes who live in convents.</div><br /><br />For persons who are found in collective residences (barracks, convents, hospitals, boarding schools, etc.) the habitual occupation, grade, title or condition should be registered, for example: administrator, superintendent, servant, lieutenant, sergeant, corporal, soldier, student, priest, etc.<br /><br />Persons who do not work should not be confused with those who having worked in some part of the census year, are found without a job or employment on the official day of the census. Equally, these last persons also should not be confused with those looking for a job for the first time, such as persons who finished their studies and are looking for work.<br /></svar> Colombia 1964: Persons age 12+ who were working or are unemployed but worked before [discrepancies: none] This variable indicates the occupation of worker, using the occupational classification for the Census of the Americas (COTA-1960). 0000 Architect, engineer, and persons in related occupations 0001 Chemist, pharmacist, and persons in related occupations 0002 Agronomist, veterinarian, and persons in related occupations 0003 Doctor, surgeon, and dentist 0004 Paramedic and persons in related occupations 0005 Nurse and midwife 0006 Professor and teacher 0007 Specialist in Mathematics, Social Sciences, and related fields 0008 Lawyer, judge, and persons in related occupations 0009 Artist, writer, entertainer, and persons in related occupations 0010 Cleric and persons related to social welfare 0011 Persons in other occupations related to professionals and technicians 0100 Public administration manager 0101 Executive officer and manager, wholesale and retail trade 0102 Other executive officer, manager, and managing proprietor 0200 Accountant and accounting specialist 0201 Book-keeper, cashier, debt collector, and persons in related occupations 0202 Typist and stenographer 0203 Other office equipment operators 0204 Inspector, dispatcher, and transportation services controller 0205 Postman and messenger 0206 Telephone switchboard operator, telegraph and other telecommunication services operators 0207 Other office clerks and persons in occupations related to transport and communications 0208 Other office clerks and persons in related occupations 0300 Salesman proprietor, wholesale and retail trade 0301 Salesclerk and street vendor 0302 Commercial traveller, manufacturer's agent, and salesman working on commisions, wholesale trade 0303 Other salesmen and persons in related occupations 0400 Farmers, livestock producers, and farm managers 0401 Agricultural and livestock workers, and gardener 0402 Fishermen and persons in related occupations 0403 Hunter, trapper, and persons in related occupations 0404 Forestry and rubber workers, and persons in related occupations 0500 Miners in coal and metal mineral deposits 0501 Mineral treaters and other workers in coal and metal mineral deposits 0502 Quarrymen and persons in related occupations in non-metal mineral solid deposits 0503 Mineral treaters and laborers in quarries and other non-solid mineral deposits 0504 Oil well drillers, other well drillers, laborers in oil wells, and persons in related occupations 0600 Driver 0601 Driver and fireman, railway engine 0602 Deck officer, engineer officer, and pilots, sea and river transport 0603 Deck and engine-room ratings, barge crews and boatmen, sea and river transport 0604 Aircraft pilot, navigator, and flight engineer 0605 Railway brakeman and shunter and persons in other occupations related to transportation 0700 Spinner, weaver, dyer, and persons in related occupations 0701 Tailor, dressmaker, furrier, skinner, and persons in occupations related to production of fabric and leather clothing 0702 Shoemaker, shoe repairers, and persons in occupations related to leather articles production 0703 Carpenter, cabinetmaker, cooper, and persons in related occupations 0704 Bricklayer, glazier, and persons in related occupations 0705 Painter and paperhangers 0706 Plumber, pipe fitter, riveter, and assemblers of iron structures 0707 Electrician, electric cable installer, radio and television repairmen, and persons in related occupations 0708 Mechanic-repairman, machinery and vehicles, machine-tool operator, and persons in related occupations 0709 Mechanic, precision instruments, clocks, jewelry, and persons in related occupations 0710 Stationary-engine and excavating and lifting equipment operators, and persns in related occupations 0711 Compositor, pressman, litographer, engraver, bookbinder, and persons in related occupations 0800 Furnaceman, roller, blacksmith, forgeman, and persons in related occupations 0801 Potter, glass former, glass blower, and other workers in the pottery, glass, and stone industries 0802 Cooker, roaster, miller, batch- and continuous-still operator, and other operators in the chemical industry 0803 Butcher, meat cutter, baker, pastrycook, brewer, and persons in related occupations 0804 Cigar makers and other operators in the tobacco industry 0805 Tanner, fellmonger, pelt dresser, and other operators en in storing and preparing pelts and leather 0806 Operators in the paper making industry 0807 Operators in the production of machinery, electrical, and transportation equipment 0809 Operators in production processes and related occupations, not elsewhere classified 0810 Packer, labeller, and related occupations 0811 Factory operators and persons in related occupations, not elsewhere classified 0900 Construction laborers 0901 Longshoreman, loader, and other transportation laborers 0902 Launderer, presser, dry cleaner, and laborers in related businesses 0903 Other operators, not elsewhere classified 1000 Workers in protection services 1001 Cook and other personnel in private house service 1002 Launderer and presser 1003 Waiter in restaurants and coffee shops, bartender, and workers in related occupations 1004 Cook, valet, persons working in pension services, and workers in related occupations, not in private service 1005 Barber, hairdresser, beautician, and workers in related occupations 1006 Doorman, janitor, elevator operator, and workers in related occupations 1007 Athlete, sportsman, and workers in related occupations 1008 Photographer and workers in related occupations 1009 Embalmer and undertaker 1010 Other service workers 1100 Armed forces 1101 New workers seeking employment 1102 Workers not reporting any occupation 1103 Workers reporting unindetifiable occupations 1104 Diplomatic and consular personnel, not elsewhere classified 1105 Persons out of the workforce 9998 Unknown 9999 NIU (not in universe) Work: Occupation Variables -- PERSON Industry, 1 digit <svar v="CO64A418 CO64A419 CO64A420 CO64A421" a="all"><span class="em">20. Place of employment</span> ____ _<br /><div class="i1">Write the principal activity of the industry where the person works. Examples: shoe factory, carpentry shop, clothing shop, agricultural farm, store, road construction, transportation, etc. For those who are unemployed, write the activity of their last employment.</div><br /></svar> <svar v="CO64A418 CO64A419 CO64A420 CO64A421" a="all"><span class="em">Place of employment</span><br /><br /><span class="em">Column No. 20: Principal activity of the office, factory or workshop for which it is worked</span>. - What is the principal activity of the factory, store, office, entity, etc. where you worked? In this column the principal activity of the establishment where a person works should be written down, indicating what is produced if it concerns a factory; what is sold it if is a store, what is extracted if it is for example an exploiting company of mines or wood, or also the class of service that is offered if that is the specialty of the establishment.<br /><br />The activity of an establishment should be registered clearly such as: Beer brewery, tile factory, automobile repair workshop, provisions store, cloth store, company of electric energy, transportation of cargo, transportation of passengers, government position, mayoralty, barracks of the army, hotel, convent, shoe store, carpenter's shop, etc.<br /><br /><span class="em">One should not write down</span>: the name or social purpose of an establishment, since the largest part of them do not indicate the corresponding activity, which would be the same as leaving this question without an answer. For example: Store "Fénix" or Workshop "La Esmeralda"; etc.<br /><br />For persons who work in their homes on dresses, sewing, repairing shoes etc., for an establishment, the class of activity of the establishment should be written down, example: Clothing store, shoe store, embroidery factory, etc. If on the other hand, they themselves sell their product; "their domicile" will be written down.<br /><br />For storekeepers, sellers and craftsmen who do not have a fixed establishment, they should be written down as "street vendor".<br /><br />For masons, who do not depend on a determined company, "construction jobs" should be written down.<br /><br />Inasmuch as cooks, butlers, and servants in general, they should be written down where they work: Family house, hotel, restaurant, etc.<br /><br />For persons who are absent from their job because of vacations, sickness, on leave, etc., the activity of the establishment where they work should be written down. For persons who are without work, the activity of the establishment where they worked last will be written down.<br /><br />In this column one should not write down any persons who in column 19 were categorized as minors, looking for work, students, invalids, rentiers, pensioned, interned, imprisoned, and the rest of the conditions. Neither should commas be used for repeating information nor forgetting that this column refers to the place of work and not the occupation.<br /></svar> Colombia 1964: Persons age 12+ who were working [discrepancies: none] This variable indicates the industry (1-digit) of employment. 00 Agriculture, forestry, hunting, fishing, and unknown 01 Mine and quarry exploitation 02 Manufacturing industries 03 Manufacturing industries 04 Construction 05 Electricity, gas, water and sanitary services 06 Business 07 Transportation, storage and communications 08 Services 09 Unspecified activities 99 NIU (not in universe) Work: Industry Variables -- PERSON Industry, 2 digits <svar v="CO64A418 CO64A419 CO64A420 CO64A421" a="all"><span class="em">20. Place of employment</span> ____ _<br /><div class="i1">Write the principal activity of the industry where the person works. Examples: shoe factory, carpentry shop, clothing shop, agricultural farm, store, road construction, transportation, etc. For those who are unemployed, write the activity of their last employment.</div><br /></svar> <svar v="CO64A418 CO64A419 CO64A420 CO64A421" a="all"><span class="em">Place of employment</span><br /><br /><span class="em">Column No. 20: Principal activity of the office, factory or workshop for which it is worked</span>. - What is the principal activity of the factory, store, office, entity, etc. where you worked? In this column the principal activity of the establishment where a person works should be written down, indicating what is produced if it concerns a factory; what is sold it if is a store, what is extracted if it is for example an exploiting company of mines or wood, or also the class of service that is offered if that is the specialty of the establishment.<br /><br />The activity of an establishment should be registered clearly such as: Beer brewery, tile factory, automobile repair workshop, provisions store, cloth store, company of electric energy, transportation of cargo, transportation of passengers, government position, mayoralty, barracks of the army, hotel, convent, shoe store, carpenter's shop, etc.<br /><br /><span class="em">One should not write down</span>: the name or social purpose of an establishment, since the largest part of them do not indicate the corresponding activity, which would be the same as leaving this question without an answer. For example: Store "Fénix" or Workshop "La Esmeralda"; etc.<br /><br />For persons who work in their homes on dresses, sewing, repairing shoes etc., for an establishment, the class of activity of the establishment should be written down, example: Clothing store, shoe store, embroidery factory, etc. If on the other hand, they themselves sell their product; "their domicile" will be written down.<br /><br />For storekeepers, sellers and craftsmen who do not have a fixed establishment, they should be written down as "street vendor".<br /><br />For masons, who do not depend on a determined company, "construction jobs" should be written down.<br /><br />Inasmuch as cooks, butlers, and servants in general, they should be written down where they work: Family house, hotel, restaurant, etc.<br /><br />For persons who are absent from their job because of vacations, sickness, on leave, etc., the activity of the establishment where they work should be written down. For persons who are without work, the activity of the establishment where they worked last will be written down.<br /><br />In this column one should not write down any persons who in column 19 were categorized as minors, looking for work, students, invalids, rentiers, pensioned, interned, imprisoned, and the rest of the conditions. Neither should commas be used for repeating information nor forgetting that this column refers to the place of work and not the occupation.<br /></svar> Colombia 1964: Persons age 12+ who were working [discrepancies: none] This variable indicates the industry (2-digit) of employment. 00 NIU (not in universe) 01 Agriculture 02 Forestry and wood extraction 03 Ordinary hunting, trap hunting and animal repopulation 04 Fishing 11 Coal mine exploitation 12 Metal mineral extraction 13 Crude petroleum and natural gas 14 Rock, clay and sand extraction 19 Extraction of nonmetallic minerals not classified elsewhere 20 Manufacturing industries for food products, except for drinks 21 Beverage industries 22 Tobacco industries 23 Textile industries 24 Manufacture of shoes, clothes, and other items made of textiles 25 Wood and cork industries, except for furniture manufacturing 26 Manufacture of furniture and accessories 27 Paper and paper product manufacturing 28 Undocumented 29 Leather and leather and skins products industries, except for shoes and clothing 30 Manufacture of rubber products 31 Manufacture of chemical substances and products 32 Manufacture of products derived from petroleum and coal 33 Manufacture of nonmetallic mineral products except for those derived from petroleum and coal 34 Basic metal industries 35 Manufacture of metal products except for machinery and transportation equipment 36 Construction of machinery, except for electrical machinery 37 Construction and repair of electrical machinery, apparatuses and other accessories 38 Construction of transportation material 39 Diverse manufacturing industries 40 Building Construction 51 Electricity and natural gas 52 Water supply and sanitation services 61 Wholesale and retail commerce 62 Banks and other financial establishments 63 Insurance companies 64 Real estate 71 Transportation 72 Storage and warehouses 73 Communications 81 Governmental services 82 Public services 83 Business services 84 Recreational services 85 Domestic services 86 Diplomatic and consular services of foreign countries 91 Unspecified and undeclared activities 99 Unknown Work: Industry Variables -- PERSON Industry, 3 digits <svar v="CO64A418 CO64A419 CO64A420 CO64A421" a="all"><span class="em">20. Place of employment</span> ____ _<br /><div class="i1">Write the principal activity of the industry where the person works. Examples: shoe factory, carpentry shop, clothing shop, agricultural farm, store, road construction, transportation, etc. For those who are unemployed, write the activity of their last employment.</div><br /></svar> <svar v="CO64A418 CO64A419 CO64A420 CO64A421" a="all"><span class="em">Place of employment</span><br /><br /><span class="em">Column No. 20: Principal activity of the office, factory or workshop for which it is worked</span>. - What is the principal activity of the factory, store, office, entity, etc. where you worked? In this column the principal activity of the establishment where a person works should be written down, indicating what is produced if it concerns a factory; what is sold it if is a store, what is extracted if it is for example an exploiting company of mines or wood, or also the class of service that is offered if that is the specialty of the establishment.<br /><br />The activity of an establishment should be registered clearly such as: Beer brewery, tile factory, automobile repair workshop, provisions store, cloth store, company of electric energy, transportation of cargo, transportation of passengers, government position, mayoralty, barracks of the army, hotel, convent, shoe store, carpenter's shop, etc.<br /><br /><span class="em">One should not write down</span>: the name or social purpose of an establishment, since the largest part of them do not indicate the corresponding activity, which would be the same as leaving this question without an answer. For example: Store "Fénix" or Workshop "La Esmeralda"; etc.<br /><br />For persons who work in their homes on dresses, sewing, repairing shoes etc., for an establishment, the class of activity of the establishment should be written down, example: Clothing store, shoe store, embroidery factory, etc. If on the other hand, they themselves sell their product; "their domicile" will be written down.<br /><br />For storekeepers, sellers and craftsmen who do not have a fixed establishment, they should be written down as "street vendor".<br /><br />For masons, who do not depend on a determined company, "construction jobs" should be written down.<br /><br />Inasmuch as cooks, butlers, and servants in general, they should be written down where they work: Family house, hotel, restaurant, etc.<br /><br />For persons who are absent from their job because of vacations, sickness, on leave, etc., the activity of the establishment where they work should be written down. For persons who are without work, the activity of the establishment where they worked last will be written down.<br /><br />In this column one should not write down any persons who in column 19 were categorized as minors, looking for work, students, invalids, rentiers, pensioned, interned, imprisoned, and the rest of the conditions. Neither should commas be used for repeating information nor forgetting that this column refers to the place of work and not the occupation.<br /></svar> Colombia 1964: Persons age 12+ who were working [discrepancies: none] This variable indicates the industry (3-digit) of employment. 000 NIU (not in universe) 011 Agriculture and livestock 012 Agricultural services 021 Forestry 022 Wood extraction 030 Animal hunting 041 Sea fishing 043 Interior waterways fishing 110 Coal mine exploitation 121 Iron mine exploitation 122 Extraction of metallic minerals except for iron 130 Crude petroleum and natural gas 140 Extraction of rock, clay and sand 191 Salt mine exploitation 199 Extraction of nonmetallic minerals not classified elsewhere 201 Livestock slaughter, meat preparation and conservation 202 Manufacture of dairy products 203 Fruit and vegetable canning and conservation 204 Canning and conservation of fish and other marine products 205 Mills and threshers 206 Manufacture of bakery products 207 Sugar refineries and sugar mills 208 Chocolate factory and candy factory 209 Diverse food industries 211 Distillation, rectification and mixing of alcoholic drinks 212 Wine industries 213 Manufacture of beer and malt 214 Manufacture of nonalcoholic drinks and carbonated drinks 220 Tobacco industries 231 Bobbin winding, knit, and finished textiles 232 Manufacture of knit products 233 Manufacture of ropes and cords 239 Manufacture of textiles and cords 241 Manufacture of shoes 242 Shoe repair 243 Manufacture of clothing, except shoes 251 Wood shops, wood finishers and others 252 Wood, cane, and similar packaging 259 Manufacture of wood and cork items not classified elsewhere 260 Manufacture of furniture and accessories 271 Manufacture of paper and cardboard 272 Manufacture of paper and cardboard items 280 Printers, editorials and similar industries 291 Leather tanning and finishing 292 Manufacture of articles of skins except for clothing 293 Manufacture of articles of leather except for shoes and other clothing 300 Manufacture of rubber products 301 Manufacture of rubber products 311 Manufacture of industrial chemical products 312 Manufacture of inedible vegetable and animal oils and fats 313 Manufacture of paint, varnishes and lacquers 319 Manufacture of chemical products 321 Petroleum refineries 329 Manufacture of diverse petroleum and coal products 331 Manufacture of clay products for construction 332 Manufacture of glass and glass products 333 Manufacture of ceramics and pottery 334 Manufacture of cement 339 Manufacture of mineral products not classified elsewhere 341 Basic iron and steel industries 342 Non-iron metal industries 350 Manufacture of metallic products, except for machinery and transportation equipment 360 Construction of machinery, except for electrical machinery 370 Construction of electrical machinery, appliances and other accessories 381 Naval constructions and boat repair 382 Train equipment construction and repair 383 Automobile vehile assembly 384 Auto-motor vehicle repair 385 Bicycle construction 386 Airplane repair and maintenance shops 389 Manufacture of other transportation vehicles not classified previously 394 Manufacture of jewelery and silver items 395 Manufacture of musical instruments 399 Other manufacturing industries not classified elsewhere 400 Construction of buildings 401 Communication channel construction 402 Other construction 511 Electricity and electrical energy 512 Natural gas production and distribution 521 Water supply 522 Sanitary services 611 Wholesale commerce 612 Retail commerce of edible products 613 Retail commerce of clothing 614 Retail commerce of other products not classified elsewhere 620 Banks and other financial establishments 630 Insurance companies 640 Real estate 711 Railroad transportation 712 Urban transportation 713 Freeway passenger transportation 714 Freeway transportation not classified elsewhere 715 Sea transportation 716 Costal and fluvial transportation 717 Air transportation 718 Transportation auxiliary services 719 Transportation not classified elsewhere 720 Storage and warehouses 730 Communications 810 Governmental services 811 Legislative entities 812 Armed forces 821 Official public instruction and private instruction 822 Official and private medical and sanitary services 823 Scientific research institutes 824 Religious organizations 825 Social assistance institutes 826 Commercial and professional associations 827 Libraries, museums, botanical gardens and zoos 829 Other service institutes not classified previously 831 Law offices 832 Accounting, auditing and bookkeeping services 833 Technical services 839 Commercial services not classified elsewhere 841 Cinematographic movie production, distribution and exhibition 842 Theaters and related services 843 Recreation services, except for theaters and movie theaters 851 Domestic services 852 Restaurants, cafes, bars and similar 853 Hotels, pensions and guest homes 854 Laundromats and dry cleaning 855 Barbers and beauty salons 856 Photographic studios 859 Personal services not classified elsewhere 861 Diplomatic and consular services of foreign countries 910 Unspecified and undeclared activities 999 Undocumented Work: Industry Variables -- PERSON Industry, 4 digits <svar v="CO64A418 CO64A419 CO64A420 CO64A421" a="all"><span class="em">20. Place of employment</span> ____ _<br /><div class="i1">Write the principal activity of the industry where the person works. Examples: shoe factory, carpentry shop, clothing shop, agricultural farm, store, road construction, transportation, etc. For those who are unemployed, write the activity of their last employment.</div><br /></svar> <svar v="CO64A418 CO64A419 CO64A420 CO64A421" a="all"><span class="em">Place of employment</span><br /><br /><span class="em">Column No. 20: Principal activity of the office, factory or workshop for which it is worked</span>. - What is the principal activity of the factory, store, office, entity, etc. where you worked? In this column the principal activity of the establishment where a person works should be written down, indicating what is produced if it concerns a factory; what is sold it if is a store, what is extracted if it is for example an exploiting company of mines or wood, or also the class of service that is offered if that is the specialty of the establishment.<br /><br />The activity of an establishment should be registered clearly such as: Beer brewery, tile factory, automobile repair workshop, provisions store, cloth store, company of electric energy, transportation of cargo, transportation of passengers, government position, mayoralty, barracks of the army, hotel, convent, shoe store, carpenter's shop, etc.<br /><br /><span class="em">One should not write down</span>: the name or social purpose of an establishment, since the largest part of them do not indicate the corresponding activity, which would be the same as leaving this question without an answer. For example: Store "Fénix" or Workshop "La Esmeralda"; etc.<br /><br />For persons who work in their homes on dresses, sewing, repairing shoes etc., for an establishment, the class of activity of the establishment should be written down, example: Clothing store, shoe store, embroidery factory, etc. If on the other hand, they themselves sell their product; "their domicile" will be written down.<br /><br />For storekeepers, sellers and craftsmen who do not have a fixed establishment, they should be written down as "street vendor".<br /><br />For masons, who do not depend on a determined company, "construction jobs" should be written down.<br /><br />Inasmuch as cooks, butlers, and servants in general, they should be written down where they work: Family house, hotel, restaurant, etc.<br /><br />For persons who are absent from their job because of vacations, sickness, on leave, etc., the activity of the establishment where they work should be written down. For persons who are without work, the activity of the establishment where they worked last will be written down.<br /><br />In this column one should not write down any persons who in column 19 were categorized as minors, looking for work, students, invalids, rentiers, pensioned, interned, imprisoned, and the rest of the conditions. Neither should commas be used for repeating information nor forgetting that this column refers to the place of work and not the occupation.<br /></svar> Colombia 1964: Persons age 12+ who were working [discrepancies: none] This variable indicates the person's industry of employment with 4-digits. 0000 NIU (not in universe) 0111 Open air and green house cultivations 0112 Large and small livestock raising, fattening and care 0113 Domestic poultry raising 0114 Bee-Honey production 0115 Milk production 0121 Planting and harvesting services 0122 Veterinary services 0123 Fumigation services 0124 Agricultural machinery renting 0125 Other agricultural services 0211 Forest repopulation and conservation 0212 Resin, rubber and bark collection 0213 Charcoal production 0221 Tree cutting 0222 Stripping and carving pieces of wood 0301 Animal hunting with traps or guns 0411 Coastal and high-sea fishing 0431 Lake, river and gully fishing 1101 Coal extraction 1211 Extraction of iron minerals 1221 Gold extraction 1222 Platinum extraction 1223 Silver extraction 1224 Extraction of other non-iron metallic minerals 1301 Crude petroleum extraction 1302 Natural gas 1401 Rock, slate and gravel extraction 1402 Clay extraction 1403 Sand extraction 1911 Rock salt extraction 1912 Marine salt extraction 1913 Manufacture of salt 1991 Emerald extraction 1992 Limestone extraction 1993 Lime extraction 1994 Marble extraction 1995 Natural asphalt extraction 1996 Extraction of other non-metallic minerals 2011 Butchers and refrigerators 2012 Meat packing and conservation 2013 Manufacture of lard and combustible animal fats 2021 Manufacture of cheeses and butter 2022 Manufacture of powdered milk and condensed milk 2023 Pasteurizers 2024 Ice cream manufacture 2025 Other food products derived from milk 2031 Canning and conservation of fruit, vegetables and fruit or vegetable juice 2032 Canning and conservation of marmalades, jams and similar 2041 Preparation, conservation, and canning of fish and other marine products 2051 Flour production mills 2052 Cereal sifters and threshers 2053 Coffee sifters 2054 Manufacture of products made of oats, barley and similar 2061 Bakeries 2062 Cake shop, cookie shop and similar 2071 Sugar refinery and elaboration 2072 Honey and brown sugar manufacture 2081 Chocolate factory 2082 Confectioner and candy maker 2091 Edible vegetable fat and oil factories 2092 Manufacture of condiments, salsas and similar 2093 Manufacture of edible pastas (noodles) 2094 Manufacture of yeast 2095 Ice making 2096 Coffee toasting 2097 Other food industries not classified elsewhere 2111 Alcohol distillers 2112 Liquor factories 2121 Factories of wine, cider and similar 2131 Beer and malt factories 2141 Non-alcoholic, carbonated drink factories 2142 Juice and other non-carbonated drinks factory 2201 Manufacture of cigars and smoking tobacco 2202 Manufacture of cigarettes 2310 Manufacture of synthetic threads (rayon, nylon, and other synthetic fabrics) 2311 Manufacture of wool thread 2312 Manufacture of cotton thread (includes cotton gins) 2313 Manufacture of other natural fibers (pita fiber, hemp and similar) 2314 Cotton fabric (not including knit cloth) factories 2315 Woolen cloth factories 2316 Synthetic fiber cloth factories 2317 Ribbon, lace and other braiding articles factories 2318 Manufacture of ponchos, blankets, shawls and similar 2319 Manufacture of other similar products not classified previously 2321 Sock (nylon stocking) factories 2322 Manufacture in factories of underwear made of knit cloth, cotton and other fibers 2331 Manufacture of ropes, cables, cords and nets of vegetable fibres 2332 Manufacture of wrapping made of pita fiber and other similar fibers 2391 Manufacture of imbedded or waterproofed fabrics 2392 Manufacture of mats, straw rugs and similar 2393 Manufacture of other textile products not specified previously 2411 Leather shoe factories 2412 Manufacture of leather sandals and thongs 2413 Manufacture of shoes made of pita fiber and other materials, except rubber 2421 Shoe repair 2431 Tailors 2432 Fashion designers 2433 Shirt makers 2434 Underwear making, except for knit cloth 2435 Manufacture of felt hats 2436 Manufacture of hats made of straw and other fibers 2437 Manufacture of leather and skin clothing 2438 Dress factories 2439 Manufacture of embroidery, pleated products and similar 2511 Saw mills 2512 Wood finishing shops 2513 Manufacture of wood products for construction 2514 Manufacture of sheets of chip board, plywood, and similar 2521 Manufacture of wooden containers 2522 Manufacture of baskets, wicker articles and similar 2591 Construction of wood work for building finishing (doors, windows, stairways, etc.) 2592 Manufacture of small wooden items (toys, toothpicks, etc.) 2593 Manufacture of cork products 2601 Manufacture of furniture for habitations, offices and establishments 2602 Manufacture of blinds, furniture for radios, televisions and similar 2603 Manufacture of other unspecified furniture and accessories 2711 Manufacture of paper and cardboard 2721 Manufacture of paper and cardboard bags and wrappers 2722 Manufacture of paper and office items 2723 Manufacture of other paper and cardboard items 2801 Printing and lithography shops 2802 Printing of books, newspapers and magazines 2803 Photogravures and zincogravures 2804 Electro-chemical printing and reproduction 2805 Binding 2911 Companies dedicated to leather tanning and finishing 2921 Preparation and finishing of skins for the use of the hides 2931 Manufacture of leather luggage, bags and similar 2932 Manufacture of harnesses and tack (saddle shops) 2933 Manufacture of other leather items other than shoes and clothing 3011 Manufacture of tires and inner tubes 3012 Retreading and vulcanization of tires 3013 Manufacture of rubber shoes 3014 Manufacture of rubber soles and heels 3015 Manufacture of other rubber items not classified elsewhere 3111 Manufacture of chemical products 3112 Manufacture of plastic materials 3113 Assembly of products 3114 Manufacture of chemical fertilizers and fungicides 3121 Manufacture of inedible vegetable and animal oils and fats 3131 Manufacture of paint and varnish 3132 Manufacture of lacquers and glues (animal-based glues) 3191 Manufacture of drugs 3192 Perfume and cosmetics preparation 3193 Manufacture of soap and detergents 3194 Manufacture of candle wax and candles 3195 Manufacture of matches 3196 Manufacture of insecticides 3197 Manufacture of waxes and polishes 3198 Manufacture of other chemical products non specified 3211 Manufacture of combustibles, lubricants and other products derived from petroleum 3291 Manufacture of asphalt 3292 Manufacture of products derived from petroleum and coal, not previously classified 3311 Manufacture of brick, tiles, adobes and tubes made of clay 3312 Manufacture of heat-resistant clay products 3321 Manufacture of glass and glass products 3331 Manufacture of porcelain and flint products 3332 Manufacture of dishware made of clay and other pottery products 3341 Cement factories 3391 Manufacture of cement, plaster and asbestos-cement products 3392 Manufacture of marble and stone 3393 Manufacture of cement tiles 3394 Manufacture of other non-metallic mineral products 3411 Production of bars, tubes, railing, rods and wires of iron and steel 3412 Manufacture of coke 3421 Manufacture of non-iron tubes, rods, wires and other non-ferrous products 3501 Manufacture of tin products 3502 Manufacture of metallic kitchen equipment and utensils 3503 Manufacture of electronic artifacts 3504 Manufacture of nails, nuts, and screws 3505 Smelting, galvanizing, nickeling and gold-plating of metal products 3506 Minting of coins, medals and similar 3507 Blacksmith shops, plumber shops and solder shops 3508 Manufacture of other metallic products not classified previously 3601 Manufacture of agriculture machinery and implements 3602 Manufacture of sugar mills, mills, machines for mills and mining 3603 Assemblers of machinery for homes (washers, refrigerators, polishers) 3604 Assemblers of office machinery 3605 Mechanical repair shops 3606 Manufacture of other non-electric machinery not classified previously 3701 Manufacture and assembly of electrical apparatuses (motors, transformers, etc.) 3702 Assemblers of radio-reception and radio-diffusion apparatuses 3703 Manufacture of stoves, ovens and other household items 3704 Manufacture of pumps, electric signs and similar 3705 Electrical items repair shops 3706 Construction of other electronic apparatuses not specified previously 3811 Shipyards for the construction and repair of sailing vessels 3821 Assembly shops for locomotives and railroad equipment 3822 Railroad equipment repair shops 3831 Automobile assembly 3832 Manufacture of chassis for busses and trucks 3841 Vehicle mechanic repair shops 3842 Automobile painting and upholstery shops 3843 Automobile vehicle repair shops not classified elsewhere 3851 Manufacture and repair of bicycles, tricycles and pedaled vehicles 3861 Airplane repair and maintenance shops 3891 Manufacture of animal traction vehicles 3892 Manufacture of manually propelled vehicles 3941 Manufacture of jewelry made from precious metals 3942 Manufacture of silver items 3951 Manufacture of musical instruments 3991 Manufacture of toys, except those of wood 3992 Manufacture of pencils and office articles 3993 Manufacture of advertisements 3994 Manufacture of brushes, brooms and similar 3995 Manufacture of products of plastic materials 3996 Manufacture of identification plates, rosettes, emblems and signs 3997 Dental prosthetics laboratories 3998 Other manufacturing industries not classified previously 4001 Building construction, repair and demolition 4011 Construction and conservation of highways, roads, streets and bridges 4012 Construction and conservation of railroad lines 4013 Construction and conservation of piers and ports 4014 Construction and conservation of airfields 4015 Construction and maintenance of telephone and telegraph lines 4016 Artesian well digging 4021 Irrigation and water supply works 4022 Construction of sewage system and plumbing 4023 Other constructions not classified previously 5111 Production, transmission and distribution of electrical energy 5121 Natural gas production in factory and distribution for domestic consumption 5211 Water supply, purification and distribution 5221 Water elimination and drainage work 6111 Import businesses and wholesale distributors of foreign items 6112 Whole distributors of national products 6113 National products export businesses 6114 Other establishment of wholesale distribution of national and foreign products 6121 Grain and vegetable stores 6122 Cigarette stores, pastry stores and similar 6123 Butcher shops 6124 Milk stores 6125 Undocumented 6131 Stores for shoes, leather items and similar 6132 Stores for cloths, fabrics and general clothing 6141 Hardware stores 6142 Drug stores 6143 Jewelers and watch smiths 6144 Bookstores and paper stores 6145 Vehicle sales, accessories and spare parts 6146 Stores for gasoline, lubricants and similar 6147 Home furniture and accessories 6148 Sales of coal and other combustibles 6149 Other commercial retail establishments not classified 6201 Banks in general 6202 Agriculture, industrial and mining development and credit institutions 6203 Credit cooperatives and investment companies 6204 Stock exchanges 6205 Other financial establishments not classified 6301 National and foreign insurance companies 6401 Agencies for real estate administration and purchase/sale 6402 Urbanization companies 7111 Railroad passenger and cargo transportation 7121 Urban passenger transportation 7131 Highway passenger transportation 7141 Highway cargo transportation 7151 Transportation of passengers and cargo by sea 7161 Transportation of passengers and cargo in coastal areas and inland waterways 7171 Transportation of passengers and cargo by air 7181 Tourism agencies 7182 Transportation agencies 7183 Garage services 7191 Transportation of gasoline and petroleum by pipeline 7192 Other types of transportation not classified previously 7201 Deposit and storage stores 7301 Post offices and telegraph offices 7302 Radio telecommunication offices 8101 Offices of the national government 8102 Offices of the departmental (state) government 8103 Offices of the municipal government 8111 Legislative bodies 8112 Departmental (state) assemblies 8113 Municipal councils 8121 National army 8122 Militarized police 8211 University teaching 8212 High school and technical teaching 8213 Primary teaching 8214 Centers for the teaching of infants 8215 Other educational establishments 8221 Clinics, hospitals and places of public health 8222 Medical and dental offices 8223 Hygiene centers and dispensaries 8224 Clinical laboratories 8225 Other public medical services 8231 Institutes of scientific investigation 8241 Seminaries, convents and missionary institutions 8251 Orphanages and homes for the elderly, invalids and indigents 8252 Charitable organizations 8253 Other welfare institutions 8261 Chambers of commerce 8262 Professional associations 8271 Libraries, museums, and other similar establishments 8291 Other service institutions not classified previously 8311 Law offices 8321 Accounting, auditing and bookkeeping offices 8331 Technical consulting offices 8332 Building plans drafting offices 8391 Publicity and advertising offices 8392 Employment agencies 8393 Information and news agencies 8394 Other commercial services not classified elsewhere 8411 Production and distribution of cinematographic films 8412 Cinematographic film exhibition theaters 8421 Theaters 8422 Theater companies 8423 Orchestras in general 8424 Radio television studios 8425 Recording and manufacture of phonograph records 8431 Sports clubs 8432 Recreation establishments 8511 Domestic services (servants, tutors, housekeepers, etc.) en private homes 8521 Cafés 8522 Restaurants and bars 8523 Ice cream shops and pastry shops (sales) 8531 Hotels and pensions 8532 Other lodging establishments 8541 Laundromats 8542 Dry cleaning 8551 Barbers and hair stylists 8561 Photographic film revealing and imprints 8591 Funeral agencies 8592 Shoe cleaning 8593 Establishments for building cleaning 8594 Other personal services besides the aforementioned 8611 Diplomatic services 8612 Consulate services 9101 Unspecified activities 9102 Undeclared activities 9999 Unknown Work: Industry Variables -- PERSON Class of worker <svar v="CO64A422" a="all"><span class="em">21. Work category.</span> ____ _<br /><div class="i1">Write according as applicable:</div><br /><div class="i2">Owner: When the person pays employees or workers out of his own funds.<br />Own-Account worker: When the person works for himself/herself without employees or workers.<br />Family helper: When he/she helps the head of family or a relative [with] payment.<br />Professional/white collar worker: When the work involves office work, control, or security.<br />Manual laborer/blue collar worker: When the work is manual.</div><br /></svar> <svar v="CO64A422" a="all"><span class="em">Occupation category</span><br /><br /><span class="em">Column No. 21</span>. - In this column the occupation category that a person has in the establishment or place where they work or when they worked if they are unemployed will be indicated. The corresponding questions to each category are given below:<br /><br /><span class="pg">[p. 24]</span><br /><br /><div class="i1"><span class="em">Employer or owner</span>: Do you pay your own account or one or more workers or employees in your business? If the question is affirmative the word "employer" should be written down.<br /><br />Examples of employers are: An owner of a factory, farm or store or any other company of business, who occupies and pays by their own account workers and employees. In the registering of this column, managers, administrators, butlers, subordinate office heads are not taken into account, since these persons depend on others and therefore are not employers but rather employees.<br /><br /><span class="em">Independent worker</span>: Do you work for you own account without paying workers or employees in your business?<br /><br />An Independent Worker can work alone or with the free aid of relatives, but not with remunerated persons. In these conditions the word "Independent Worker" will be written down.<br /><br />Examples of Independent Workers are, a craftsperson who has their own workshop, a farmer who works a parcel of land, a salesclerk who attends their store, a mason who does small jobs by contract, an owner of a truck or automobile who drives it and takes for themselves the product of the work, a shoeshine person, a newspaper seller, always persons who do not work with remunerated workers.<br /><br />It can be observed that the difference between an independent worker and an employer, is that the employer has remunerated workers and the independent worker has none.<br /><br /><span class="em">Family helpers</span>: Do you help without fixed remuneration, in the job of the Head of family or any relative? A person from the family (spouse, children, relatives) who with their job helps the Head of family or relative in their business for a time equivalent to two days a week, or 10 days a month to four months a year, without receiving fixed remuneration, should be written down in this column with the name "Family Helper".<br /><br />Example of family helpers can be the following persons always who meet the following pointed out conditions: A child or relative who works in the farm of their father; a wife who works in the store of her husband, a child who helps their mother in a dressmaker's studio, etc.<br /><br />One should keep in mind when registering this column that a family helper meets the following conditions:</div><br /><br /><div class="i2">a) Being relative of the Head of family or person who collaborates with him.<br /><br />b) Working without fixed remuneration (food should not be considered remuneration).<br /><br />c) Working with the Head or parent for more than two days a week, or 10 days a month to four months a year.</div><br /><br /><div class="i1"><span class="em">Employee</span>: Are you an employee? An employee is considered a person who carries out, under the dependence of another, administrative functions, direction, organization, or vigilance in exchange for remuneration. Examples: a manager of a bank, an administrator of a company, workers in an office of institutional officials or of private companies.</div><br /><br /><span class="pg">[p. 25]</span><br /><br /><div class="i1"><span class="em">Exceptions</span>: In this column chauffeurs of companies and persons of domestic service (servants) will be indicated, such as the Law stipulates.<br /><br /><span class="em">Laborer</span>: A laborer is considered to be a worker who is employed with a predominately manual activity, connected directly to a production of goods and services, always depending on an employer and receives a periodic remuneration. Laborers are workers of the production in factories or workshops, those employed in manual jobs in public works and agricultural day laborers. They are also those who work in a house for a determined employer, whether for a fixed daily wage or by the job, as in the very frequent case of laborers in a tailor's shop, shoe store, and couturier shop, who does work in their house and who earns according to what was done.</div><br /></svar> Colombia 1964: Persons age 12+ who were working [discrepancies: none] This variable indicates the class of worker. 1 Owner 2 Own-account worker 3 Family helper 4 Professional/white collar worker 5 Manual laborer/blue collar worker 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON