2011 National Population and Housing Census DDI_IRN_2011_PHC_v01_M_v7.6_A_IPUMS IPUMS

Integrated Public Use Microdata Series (IPUMS) International

IPUMS April 1, 2025 IPUMS, 50 Willey Hall, 225 - 19th Avenue South, Minneapolis, MN 55455 Organization for Economic Co-operation and Development, Development Co-operation Directorate JADE#:60525;MEHLB(2010)12 IPUMS Version 7.6 October 2025 : NEW FEATURES. --NO "new features" listed in Revision History NEW SAMPLES. --Six new census samples for Honduras (2013), Kenya (2019), Malawi (2018), Mongolia (2010, 2020), and Mozambique (2017) were added to the data series. All census samples extend pre-existing series for those countries. --91 quarterly labor force surveys from the Philippines (1997 - 2019) were added to IPUMS. SUPPLEMENTAL DATA. --No "supplemental data" listed in revision history NEW VARIABLES. --New spatially harmonized birthplace and previous-residence variables are available for samples in this data release. More information is available here (https://international.ipums.org/international/geo_mig.shtml). --Users should note that many older migration and birthplace variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. For birthplace variables refer to this table (https://international.ipums.org/international/resources/misc_docs/migCrosswalk_names.pdf). EDITED SAMPLES. --For the Zambia 2000 sample, an error in the household breaks was corrected, resulting in the creation of 1,988 new households (1% increase) that were previously combined with other households. The person records included in the sample did not change. Due to an inconsistency in the original file, no household-level information other than geographic location is available for these newly identified households, necessitating the addition of "unknown" values for this sample to the following variables: BEDROOMS, ELECTRIC, FLOOR, FUELCOOK, FUELHEAT, OWNERSHIP, PHONE, RADIO, REFRIG, ROOMS, SEWAGE, TRASH, WATSRC, TV, TOILET, GQ, ROOF, WATSUP, BIKE, MOTORCYCLE, KITCHEN, GQTYPE, AUTOS, and WALL. EDITED VARIABLES. --For the 1998 and 2008 Malawi samples, the family interrelationship pointer variables MOMLOC and POPLOC were modified to allow a "Spouse/partner" of the household head to be linked as a parent to an "Other relative", because the enumeration instructions specify that adopted and stepchildren were categorized as "Other relative". These samples are now consistent with the links made in the newly released 2018 Malawi sample, which had the same enumeration instructions for adopted and stepchildren. --In the samples for Côte d'Ivoire 1988 and 1998, Rwanda 1991 and 2002, Togo 1960 and 2010, and South Africa 2001, for the harmonized variable POLYGAM, persons in consensual unions were previously coded as "No, in monogamous union". Because there was no response option in these samples for polygamous consensual unions, it is more appropriate to treat these cases as not-in-universe, so they have been recoded to "NIU (not in universe)". --MARST has been edited for Honduras 1974 to reclassify the source variable responses "married, wife lives separately" and "consensual union, companion lives separately" as separations. The documentation suggests that "separately" actually indicates a relationship separation and not an absent spouse or companion. Other minor edits were implemented for MARST for Mozambique 1997 and 2007. --In the Mozambique 1997 sample, an error was corrected that recoded persons with a relationship of "Unknown" in the source data to "Other relative or non-relative" (6000) in the harmonized variable RELATE. These persons are now coded as "Not Stated/Unknown" (9999). --In the Malawi 1987, 1998, and 2008 samples, for variable WATSUP, a programming error was corrected such that any households who reported having piped water in either the wet or the dry season are classified as having access to piped water. This programming was also applied to the newly released 2018 sample. --The NATIVITY variable has been edited in the Chile 2017 sample to correct a programming error that mistakenly classified as foreign-born about 20 thousand person records that were actually native-born. --The MIGRATE5 variable has been edited in the Chile 2017 sample, given a programming error that classified most migrants as having changed their major geographic unit. The MIGRATE5 variable for the Chile 1982 and 1992 samples has been edited to use spatially harmonized geographic units to calculate migration status. --In the 1989, 1999, and 2009 Kenya samples, households who indicated that their lighting type or fuel was "Solar" were recoded from "No" to "Yes" in ELECTRIC, based on secondary sources documenting the spread of home solar energy systems in Kenya beginning in the mid-1980s. In the 1989 and 1999 Kenya samples, programming was removed that previously recoded households that reported using electricity as their main cooking fuel to "Yes" in the access to electricity variable ELECTRIC, making it more consistent across samples. Other minor edits were implemented for ELECTRIC in Botswana 2011, Ethiopia 1984 and 1994, Mongolia 1989, Mozambique 2007. --Some samples in DISCARE classified responses indicating "some" difficulty into "yes". These cases were revised to consistently include in "yes" only responses indicating "a lot of difficulty" or "cannot do at all". --Some codes were improperly labeled for municipalities in Honduras 1961 and 1974, which affect variables on place of residence, birthplace, and previous residence. 2011 National Population and Housing Census - IPUMS Subset PHC ir2011a (IPUMS Harmonized Subset) IRN_2011_PHC_v01_M_v7.6_A_IPUMS Statistical Center of Iran IPUMS (c) Copyright 2011, Statistical Center of Iran and Minnesota Population Center Statistical Center of Iran 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 Fertility and Mortality Variables -- PERSON Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Geography: F-N Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Migration: F-N Variables -- PERSON Nativity and Birthplace Variables -- PERSON Technical Person Variables -- PERSON Demographic Variables -- PERSON Migration: Global Variables -- PERSON Other Person Variables -- PERSON Education Variables -- PERSON Work Variables -- PERSON Fertility and Mortality Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Nativity and Birthplace Variables -- PERSON Technical Person Variables -- PERSON Work: Industry Variables -- PERSON Work: Occupation Variables -- PERSON October 23, 2011 24 October to 13 November, 2011 Iran, Islamic Republic of Sub-province Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: Not applicable - Households: Individuals who live together in a dwelling, share expenses, and usesually eat togeher. - Group quarters: Comparised of indiviuals who have chosen to live together because of a characterisitc shared by majority or all of them. For example university dormatories. These households lack a distinct head of household, usually lack kinship, and their composition lacks permanency or stability. The members of all private settled, institutional, and colelctive families whose place of usual residence is located in Iran at the time of the enumeration and also the members of all private unsettled households of the country comprise the population under enumeration. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Iran 2011 MICRODATA SOURCE: Statistical Center of Iran SAMPLE SIZE (person records): 1481586. SAMPLE DESIGN: 2% stratified random sample of urban/rural areas at the county level. Face-to-face [f2f] Form 2- Household Questionnaire, Form 3 Instiutional household questionnaire. Form 4- Settlement characteristics form de jure, CENSUS DAY: October 23, 2011 Calculated as the inverse of the probability of the household's selection 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. Statistical Center of Iran 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: Iran, Islamic Republic of, Statistical Center of Iran. 2011 National Population and 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 ir2011a, 2025 IRN2011_PHC-H-H.dat Household records 425,007 ascii Minnesota Population Center Version 7.5, IPUMS sample IRN2011_PHC-P-H.dat Person records 1481586 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 Number of unrelated persons UNREL indicates the number of persons in the household who are unrelated to the head as defined in the variable RELATE. 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ Group Quarters Variables -- HOUSEHOLD Urban-rural status URBAN indicates whether the household was located in a place designated as urban or as rural. 1 Rural 2 Urban 9 Unknown Geography: Global Variables -- HOUSEHOLD Continent and region of country REGIONW identifies the continent and region of each country. 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia Geography: Global Variables -- HOUSEHOLD 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 2nd subnational geographic level, world [consistent boundaries over time] GEOLEV2 indicates the second major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. Second administrative units in GEOLEV2 have been spatio-temporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV2 is a 9-digit numeric variable. GEOLEV2 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO2_BR. 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 Population density of GEOLEV2 unit, in persons per square kilometer POPDENSGEO2 indicates the population density in persons per square kilometer of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO2 is a 12-digit 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 Area of GEOLEV2 unit in square kilometers AREAMOLLWGEO2 indicates the area in square kilometers of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO2 is a 10-digit numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Iran, Province 2006 - 2011 [Level 1; consistent boundaries, GIS] GEO1_IR identifies the household's province within Iran in all sample years. Provinces are the first level administrative units of the country. GEO1_IR 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_IR can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Iran 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. 364000 Markazi 364001 Gilan 364002 Mazandaran 364003 East Azarbayejan 364004 West Azarbayejan 364005 Kermanshah 364006 Khuzestan 364007 Fars 364008 Kerman 364009 Razavi Khorasan 364010 Esfahan 364011 Sistan and Baluchestan 364012 Kordestan 364013 Hamedan 364014 Chaharmahal and Bakhtiyari 364015 Lorestan 364016 Ilam 364017 Kohgiluyeh and Boyerahmad 364018 Bushehr 364019 Zanjan 364020 Semnan 364021 Yazd 364022 Hormozgan 364023 Tehran, Alborz 364024 Ardebil 364025 Qom 364026 Qazvin 364027 Golestan 364028 North Khorasan 364029 South Khorasan Geography: F-N Variables -- HOUSEHOLD Iran, Province 2011 [Level 1, GIS] GEO1_IR2011 identifies the household's province within Iran in 2011. Provinces are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_IR2011 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Iran 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. 000 Markazi 001 Gilan 002 Mazandaran 003 East Azarbayejan 004 West Azarbayejan 005 Kermanshah 006 Khuzestan 007 Fars 008 Kerman 009 Razavi Khorasan 010 Esfahan 011 Sistan and Baluchestan 012 Kordestan 013 Hamedan 014 Chaharmahal and Bakhtiyari 015 Lorestan 016 Ilam 017 Kohgiluyeh and Boyerahmad 018 Bushehr 019 Zanjan 020 Semnan 021 Yazd 022 Hormozgan 023 Tehran 024 Ardebil 025 Qom 026 Qazvin 027 Golestan 028 North Khorasan 029 South Khorasan 030 Alborz Geography: F-N Variables -- HOUSEHOLD Iran, Sub-province 2006 - 2011 [Level 2; consistent boundaries, GIS] GEO2_IR identifies the household's sub-province within Iran in all sample years. Sub-provinces are the second level administrative units of the country, after provinces. GEO2_IR 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 GEO2_IR can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Iran 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. 364000001 Arak, Khondab 364000003 Tafresh, Farahan, Ashtian 364000004 Khomein 364000005 Delijan 364000006 Saveh 364000007 Shazand 364000009 Mahallat 364000010 Zarandiyeh 364000011 Komeijan 364001001 Astara 364001002 Astane-ye-Ashrafiyeh 364001003 Bandar Anzali 364001004 Talesh 364001005 Rasht 364001006 Rudbar 364001007 Rudsar 364001008 Sumaehsara 364001009 Fuman 364001010 Langrud 364001011 Lahijan 364001012 Shaft 364001013 Amlash 364001014 Rezvanshahr 364001015 Siahkal 364001016 Masal 364002001 Amol 364002002 Babol 364002004 Behshahr 364002005 Tonkabon, Abbasabad 364002006 Ramsar 364002007 Sari, Miandorud 364002008 Savadkuh 364002010 Qaemshahr 364002014 Nur 364002015 Noshahr 364002016 Babolsar, Fereydunkenar 364002018 Mahmoudabad 364002019 Neka 364002020 Chalus 364002021 Juybar 364002022 Galugah 364003002 Ahar 364003003 Tabriz 364003005 Sarab 364003006 Maragheh 364003007 Marand 364003010 Miyaneh 364003011 Hashtrud 364003012 Bonab 364003013 Bostanabad 364003014 Shabestar 364003015 Kaleibar, Khoda Afarin 364003016 Haris 364003019 Jolfa 364003020 Malekan 364003021 Azarshahr 364003022 Osku 364003023 Charoimaq 364003024 Varzaqan 364003025 Ajabshir 364004001 Orumiyeh 364004002 Piranshahr 364004003 Khoy, Chaypareh 364004004 Sardasht 364004005 Salmas 364004006 Poldasht, Maku, Showt 364004007 Mahabad 364004008 Miandoab 364004009 Naqadeh 364004010 Bukan 364004011 Shahindezh 364004012 Takab 364004013 Oshnaviyeh 364004014 Chaldoran 364005001 Eslamabad-e-Gharb 364005002 Kermanshah 364005003 Paveh 364005004 Sar-e-pol-e-Zahab 364005005 Sonqor 364005006 Qasr-e-Shirin 364005007 Kangavar 364005008 Gilan-e-Gharb 364005009 Javanrud 364005010 Sahneh 364005011 Harsin 364005012 Salas-e-Babajani 364005013 Dalahu 364005014 Ravansar 364006001 Abadan 364006002 Andimeshk 364006003 Ahvaz, Bavi 364006004 Izeh 364006005 Bandar-e-Mahshahr 364006006 Behbahan 364006007 Khorramshahr 364006008 Dezful 364006009 Hoveizeh, Dasht-e-Azadegan 364006010 Ramhormoz, Haftgol 364006011 Shadegan 364006012 Shushtar 364006013 Andika, Masjed Soleyman 364006014 Shush 364006015 Baghmalek 364006016 Omidiyeh 364006017 Lali 364006018 Hendijan 364006019 Ramshir 364006020 Gotvand 364007001 Abadeh 364007002 Estahban 364007003 Eqlid 364007004 Jahrom 364007005 Darab 364007006 Sepidan 364007007 Shiraz, Sarvestan, Kavar, Kharameh 364007008 Fasa 364007009 Firuzabad 364007010 Kazerun 364007011 Larestan, Gerash 364007012 Marvdasht 364007013 Mamasani, Rostam 364007014 Neyriz 364007015 Lamerd 364007016 Bavanat 364007017 Arsanjan 364007018 Khorrambid 364007019 Zarrindasht 364007020 Qirokarzin 364007021 Mohr 364007022 Farashband 364007023 Pasargad 364007024 Khonj 364008001 Baft, Rabar, Arzuiyeh 364008002 Bam, Rigan, Narmashir, Fahraj 364008003 Jiroft, Anbarabad 364008004 Rafsanjan, Anar 364008005 Kohbonan, Zarand 364008006 Sirjan 364008007 Shahr-e-Babak 364008008 Kerman 364008009 Manujan, Kahnuj, Faryab 364008010 Bardsir 364008011 Ravar 364008015 Rudbar-e-Jonub 364008016 Ghaleh-Ganj 364009004 Taybad, Bakharz 364009005 Torbat-e-Heydariyeh, Zave 364009006 Torbat-e-Jam 364009007 Dargaz 364009008 Sabzevar, Joghatai, Jowayin, Khoshab 364009013 Quchan 364009014 Kashmar 364009015 Gonabad, Bajestan 364009016 Mashhad, Binalud 364009017 Nishapur, Taht-e-Jolegh 364009018 Chenaran 364009019 Khaf 364009020 Sarakhs 364009022 Fariman 364009023 Bardeskan 364009027 Rashtkhar 364009028 Kalat 364009029 Khalil Abad 364009030 Mah-Velat 364010001 Ardestan 364010002 Esfahan 364010003 Khomeinishahr 364010004 Khansar 364010005 Semirom 364010006 Faridan 364010007 Fereydunshahr 364010008 Falavarjan 364010009 Shahreza 364010010 Kashan 364010011 Golpayegan 364010012 Lenjan 364010013 Naeen, Khur o Biabanak 364010014 Najafabad 364010015 Natanz 364010016 Shahinshahr o Meymeh, Borkhar 364010017 Mobarakeh 364010018 Aran and Bidgol 364010019 Tiran and Karvan 364010020 Chadegan 364010021 Dehaqan 364011001 Iranshahr, Dalgan 364011002 Chabahar 364011003 Khash 364011004 Zabol, Hirmand 364011005 Zahedan 364011006 Sib o Soran, Saravan, Zaboli 364011007 Neekshahr 364011008 Sarbaz 364011009 Konarak 364011010 Zahak 364012001 Baneh 364012002 Bijar 364012003 Saqqez 364012004 Sanandaj 364012005 Qorveh, Dehgolan 364012006 Marivan 364012007 Divandarreh 364012008 Kamyaran 364012009 Sarvabad 364013001 Tuyserkan 364013002 Malayer 364013003 Nahavand 364013004 Hamedan, Famenin 364013005 Kabudarahang 364013006 Asadabad 364013007 Bahar 364013008 Razan 364014001 Borujen 364014002 Shahr-e-Kord, Kiaar 364014003 Farsan 364014004 Lordegan 364014005 Ardal 364014006 Kuhrang 364015001 Aligudarz 364015002 Borujerd 364015003 Khorramabad, Dowreh 364015004 Delfan 364015005 Dorud 364015006 Kuhdasht 364015007 Azna 364015008 Poldokhtar 364015009 Selseleh 364016001 Ilam 364016002 Darrehshahr 364016003 Dehloran 364016004 Shirvan and Chardavel 364016005 Mehran, Malekshahi 364016006 Abdanan 364016007 Ivan 364017001 Boyerahmad 364017002 Gachsaran, Basht 364017003 Kohgiluyeh, Charam 364017004 Dena 364017005 Bahmaee 364018001 Bushehr 364018002 Tangestan 364018003 Dashtestan 364018004 Dashti 364018005 Dayyer 364018006 Kangan 364018007 Genaveh 364018008 Deylam 364018009 Jam 364019001 Abhar 364019003 Khodabandeh 364019004 Zanjan 364019006 Ijerud 364019007 Khorramdarreh 364019008 Tarom 364019009 Mahneshan 364020001 Damghan 364020002 Semnan, Mehdishahr 364020003 Shahrud 364020004 Garmsar 364021001 Ardakan 364021002 Bafgh, Behabad 364021003 Taft 364021004 Mehriz 364021005 Yazd 364021006 Meybod 364021007 Abarkuh 364021008 Sadugh 364021009 Khatam 364021010 Tabas 364022002 Bandar Abbas 364022003 Bandar Lengeh 364022004 Qeshm, Abumusa 364022005 Minab, Sirik 364022006 Jask, Bashakerd 364022007 Rudan 364022008 Hajiabad 364022009 Bastak 364022010 Khamir 364022011 Parsian 364023001 Tehran 364023002 Damavand 364023003 Rey 364023004 Shemiranat 364023006 Varamin, Pishva 364023009 Malard, Qod, Shahriar 364023010 Eslamshahr 364023012 Robatkarim, Baharestan 364023013 Pakdasht 364023014 Firuzkuh 364023015 Karaj 364023016 Savojbolagh, Nazarabad, Taleghan 364024001 Ardebil, Sareyn 364024002 Bilehsavar 364024003 Khalkhal 364024004 Meshkinshahr 364024005 Garmi 364024006 Parsabad 364024007 Kowsar 364024008 Namin 364024009 Neer 364025001 Qom 364026001 Boyinzahra 364026002 Takestan 364026003 Qazvin 364026004 Abyek 364026005 Alborz 364027001 Bandar Gaz 364027002 Gomishan, Torkaman 364027003 Aliabad 364027004 Kordkuy 364027005 Gorgan 364027006 Gonbad-e-Kavus 364027007 Galikash, Minudasht 364027008 Aq Qala 364027009 Maravehtapeh, Kalaleh 364027010 Azadshahr 364027011 Ramyan 364028001 Esfarayen 364028002 Bojnurd 364028003 Jajrom, Garmeh 364028004 Shirvan 364028005 Faruj 364028006 Maneh and Samalqan 364029001 Birjand 364029002 Darmiyan 364029003 Sarbisheh 364029004 Qayenat 364029005 Nahbandan 364029006 Sarayan 364029007 Boshruyeh, Ferdows Geography: F-N Variables -- HOUSEHOLD Iran, Sub-province 2011 [Level 2, GIS] GEO2_IR2011 identifies the household's sub-province within Iran in 2011. Sub-provinces are the second level administrative units of the country, after divisions. A GIS map (in shapefile format), corresponding to GEO2_IR2011 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Iran 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. 000001 Arak 000003 Tafresh 000004 Khomein 000005 Delijan 000006 Saveh 000007 Shazand 000009 Mahallat 000010 Zarandiyeh 000011 Komeijan 000012 Khondab 000013 Farahan, Ashtian 001001 Astara 001002 Astane-ye-Ashrafiyeh 001003 Bandar Anzali 001004 Talesh 001005 Rasht 001006 Rudbar 001007 Rudsar 001008 Sumaehsara 001009 Fuman 001010 Langrud 001011 Lahijan 001012 Shaft 001013 Amlash 001014 Rezvanshahr 001015 Siahkal 001016 Masal 002001 Amol 002002 Babol 002004 Behshahr 002005 Tonkabon 002006 Ramsar 002007 Sari 002008 Savadkuh 002010 Qaemshahr 002014 Nur 002015 Noshahr 002016 Babolsar 002018 Mahmoudabad 002019 Neka 002020 Chalus 002021 Juybar 002022 Galugah 002023 Fereydunkenar 002024 Abbasabad 002025 Miandorud 003002 Ahar 003003 Tabriz 003005 Sarab 003006 Maragheh 003007 Marand 003010 Miyaneh 003011 Hashtrud 003012 Bonab 003013 Bostanabad 003014 Shabestar 003015 Kaleibar 003016 Haris 003019 Jolfa 003020 Malekan 003021 Azarshahr 003022 Osku 003023 Charoimaq 003024 Varzaqan 003025 Ajabshir 003026 Khoda Afarin 004001 Orumiyeh 004002 Piranshahr 004003 Khoy 004004 Sardasht 004005 Salmas 004006 Maku 004007 Mahabad 004008 Miandoab 004009 Naqadeh 004010 Bukan 004011 Shahindezh 004012 Takab 004013 Oshnaviyeh 004014 Chaldoran 004015 Poldasht 004016 Chaypareh 004017 Showt 005001 Eslamabad-e-Gharb 005002 Kermanshah 005003 Paveh 005004 Sar-e-pol-e-Zahab 005005 Sonqor 005006 Qasr-e-Shirin 005007 Kangavar 005008 Gilan-e-Gharb 005009 Javanrud 005010 Sahneh 005011 Harsin 005012 Salas-e-Babajani 005013 Dalahu 005014 Ravansar 006001 Abadan 006002 Andimeshk 006003 Ahvaz 006004 Izeh 006005 Bandar-e-Mahshahr 006006 Behbahan 006007 Khorramshahr 006008 Dezful 006009 Dasht-e-Azadegan 006010 Ramhormoz 006011 Shadegan 006012 Shushtar 006013 Masjed Soleyman 006014 Shush 006015 Baghmalek 006016 Omidiyeh 006017 Lali 006018 Hendijan 006019 Ramshir 006020 Gotvand 006021 Andika 006022 Haftgol 006023 Hoveizeh 006024 Bavi 007001 Abadeh 007002 Estahban 007003 Eqlid 007004 Jahrom 007005 Darab 007006 Sepidan 007007 Shiraz 007008 Fasa 007009 Firuzabad 007010 Kazerun 007011 Larestan 007012 Marvdasht 007013 Mamasani 007014 Neyriz 007015 Lamerd 007016 Bavanat 007017 Arsanjan 007018 Khorrambid 007019 Zarrindasht 007020 Qirokarzin 007021 Mohr 007022 Farashband 007023 Pasargad 007024 Khonj 007025 Sarvestan 007026 Rostam 007027 Gerash 007028 Kavar 007029 Kharameh 008001 Baft 008002 Bam 008003 Jiroft 008004 Rafsanjan 008005 Zarand 008006 Sirjan 008007 Shahr-e-Babak 008008 Kerman 008009 Kahnuj 008010 Bardsir 008011 Ravar 008012 Anbarabad 008013 Manujan 008014 Kohbonan 008015 Rudbar-e-Jonub 008016 Ghaleh-Ganj 008017 Rigan 008018 Rabar 008019 Fahraj 008020 Anar 008021 Narmashir 008022 Faryab 008023 Arzuiyeh 009004 Taybad 009005 Torbat-e-Heydariyeh 009006 Torbat-e-Jam 009007 Dargaz 009008 Sabzevar 009013 Quchan 009014 Kashmar 009015 Gonabad 009016 Mashhad 009017 Nishapur 009018 Chenaran 009019 Khaf 009020 Sarakhs 009022 Fariman 009023 Bardeskan 009027 Rashtkhar 009028 Kalat 009029 Khalil Abad 009030 Mah-Velat 009031 Bajestan 009032 Binalud 009033 Taht-e-Jolegh 009034 Joghatai 009035 Zave 009036 Jowayin 009037 Bakharz 009038 Khoshab 010001 Ardestan 010002 Esfahan 010003 Khomeinishahr 010004 Khansar 010005 Semirom 010006 Faridan 010007 Fereydunshahr 010008 Falavarjan 010009 Shahreza 010010 Kashan 010011 Golpayegan 010012 Lenjan 010013 Naeen, Khur o Biabanak 010014 Najafabad 010015 Natanz 010016 Shahinshahr o Meymeh 010017 Mobarakeh 010018 Aran, Bidgol 010019 Tiran, Karvan 010020 Chadegan 010021 Dehaqan 010022 Borkhar 011001 Iranshahr 011002 Chabahar 011003 Khash 011004 Zabol 011005 Zahedan 011006 Saravan 011007 Neekshahr 011008 Sarbaz 011009 Konarak 011010 Zahak 011011 Hirmand 011012 Dalgan 011013 Zaboli 011014 Sib o Soran 012001 Baneh 012002 Bijar 012003 Saqqez 012004 Sanandaj 012005 Qorveh 012006 Marivan 012007 Divandarreh 012008 Kamyaran 012009 Sarvabad 012010 Dehgolan 013001 Tuyserkan 013002 Malayer 013003 Nahavand 013004 Hamedan 013005 Kabudarahang 013006 Asadabad 013007 Bahar 013008 Razan 013009 Famenin 014001 Borujen 014002 Shahr-e-Kord 014003 Farsan 014004 Lordegan 014005 Ardal 014006 Kuhrang 014007 Kiaar 015001 Aligudarz 015002 Borujerd 015003 Khorramabad 015004 Delfan 015005 Dorud 015006 Kuhdasht 015007 Azna 015008 Poldokhtar 015009 Selseleh 015010 Dowreh 016001 Ilam 016002 Darrehshahr 016003 Dehloran 016004 Shirvan, Chardavel 016005 Mehran 016006 Abdanan 016007 Ivan 016008 Malekshahi 017001 Boyerahmad 017002 Gachsaran, Basht 017003 Kohgiluyeh 017004 Dena 017005 Bahmaee 017006 Charam 018001 Bushehr 018002 Tangestan 018003 Dashtestan 018004 Dashti 018005 Dayyer 018006 Kangan 018007 Genaveh 018008 Deylam 018009 Jam 019001 Abhar 019003 Khodabandeh 019004 Zanjan 019006 Ijerud 019007 Khorramdarreh 019008 Tarom 019009 Mahneshan 020001 Damghan 020002 Semnan 020003 Shahrud 020004 Garmsar 020005 Mehdishahr 021001 Ardakan 021002 Bafgh, Behabad 021003 Taft 021004 Mehriz 021005 Yazd 021006 Meybod 021007 Abarkuh 021008 Sadugh 021009 Khatam 021010 Tabas 022002 Bandar Abbas 022003 Bandar Lengeh 022004 Qeshm, Abumusa 022005 Minab 022006 Jask 022007 Rudan 022008 Hajiabad 022009 Bastak 022010 Khamir 022011 Parsian 022012 Sirik 022013 Bashakerd 023001 Tehran 023002 Damavand 023003 Rey 023004 Shemiranat 023006 Varamin 023009 Shahriar 023010 Eslamshahr 023012 Robatkarim 023013 Pakdasht 023014 Firuzkuh 023016 Qod 023017 Malard 023018 Pishva 023019 Baharestan 024001 Ardebil, Sareyn 024002 Bilehsavar 024003 Khalkhal 024004 Meshkinshahr 024005 Garmi 024006 Parsabad 024007 Kowsar 024008 Namin 024009 Neer 025001 Qom 026001 Boyinzahra 026002 Takestan 026003 Qazvin 026004 Abyek 026005 Alborz 027001 Bandar Gaz 027002 Torkaman 027003 Aliabad 027004 Kordkuy 027005 Gorgan 027006 Gonbad-e-Kavus 027007 Minudasht 027008 Aq Qala 027009 Kalaleh 027010 Azadshahr 027011 Ramyan 027012 Maravehtapeh 027013 Gomishan 027014 Galikash 028001 Esfarayen 028002 Bojnurd 028003 Jajrom 028004 Shirvan 028005 Faruj 028006 Maneh, Samalqan 028007 Garmeh 029001 Birjand 029002 Darmiyan 029003 Sarbisheh 029004 Qayenat 029005 Nahbandan 029006 Sarayan 029007 Ferdows 029008 Boshruyeh 030001 Karaj 030002 Savojbolagh 030003 Nazarabad 030004 Taleghan Geography: F-N Variables -- HOUSEHOLD Household classification HHTYPE is a constructed variable that describes the composition of households. HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ. 00 Vacant household 01 One-person household 02 Married/cohab couple, no children 03 Married/cohab couple with children 04 Single-parent family 05 Polygamous family 06 Extended family, relatives only 07 Composite household, family and non-relatives 08 Non-family household 09 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable Constructed Household Variables -- HOUSEHOLD Number of families in household NFAMS is a constructed variable that indicates the number of families within each household. Family membership is defined by FAMUNIT. A "family" is any group of persons related by blood, adoption, or marriage. An unrelated individual within the household is considered a separate family. Thus, a household consisting of a widow and a domestic employee contains two families; a household consisting of a large, multi-generation extended family with no persons unrelated to the head counts as a single family. NFAMS is constructed from information in RELATE (relationship to head) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). See those variable descriptions for more detail. 0 Vacant household 1 1 family 2 2 families 3 3 families 4 4 families 5 5 families 6 6 families 7 7 families 8 8 families 9 9 or more families Constructed Household Variables -- HOUSEHOLD Number of married couples in household NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household. NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household). 0 No married couples in household 1 1 couple 2 2 couples 3 3 couples 4 4 couples 5 5 couples 6 6 couples 7 7 couples 8 8 couples 9 9 or more couples Constructed Household Variables -- HOUSEHOLD Number of mothers in household NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household. NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household). 0 No mothers in household 1 1 mother 2 2 mothers 3 3 mothers 4 4 mothers 5 5 mothers 6 6 mothers 7 7 mothers 8 8 mothers 9 9 or more mothers in household Constructed Household Variables -- HOUSEHOLD Number of fathers in household NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household. NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household). 0 No fathers in household 1 1 father 2 2 fathers 3 3 fathers 4 4 fathers 5 5 fathers 6 6 fathers 7 7 fathers 8 8 fathers 9 9 or more fathers in household Constructed Household Variables -- HOUSEHOLD Head's location in household HEADLOC gives the person number (PERNUM) of the head of household in samples in which persons are organized into households. HEADLOC is a 3-digit numeric variable. Constructed Household Variables -- HOUSEHOLD Dwelling number Iran 2011: All records This variable indicates the dwelling number. This is a 7-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Number of persons in household Iran 2011: All records This variable indicates the number of persons in a household. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 21 21 22 22 23 23 24 24 25 25 27 27 30 30 Technical Household Variables -- HOUSEHOLD Rural or urban status ____ <span class="lang">Oastan</span> (Province) <br />____ <span class="lang">Shahrestan</span> (sub-province) <br />____ <span class="lang">Bakhsh</span> (county) <br />____ <span class="lang">Shahr </span>/ <span class="lang">Dehestan</span> (city / agglomeration) <br />____ Village <br />____ Block number/Village code <br />____ District number Iran 2011: All households This variable indicates the household's rural or urban status. 0 Rural 1 Urban Geography: F-N Variables -- HOUSEHOLD Household type Household type <br /> </p> <div class="i1">[] 1 Settled private<br />[] 2 Unsettled<br />[] 3 Collective</div> <span class="em">3- Type of household</span><div class="i1">On top of form 2, there is room to specify type of household. Put X in the box that corresponds with the type of household namely conventional settled, conventional unsettled, and collective.<br />[Picture omitted]</div> Iran 2011: All households This variable indicates the type of household. 1 Ordinary, settled 3 Collective Group Quarters Variables -- HOUSEHOLD Strata Iran 2011: 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: Global Variables -- HOUSEHOLD Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. Technical Person Variables -- PERSON Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Person Variables -- PERSON Mother's location in household MOMLOC is a constructed variable that indicates whether or not the person's mother lived in the same household and, if so, gives the person number of the mother (see PERNUM). MOMLOC makes it easy for researchers to link the characteristics of children and their (probable) mothers. The method by which probable child-mother links are identified is described in PARRULE. The general design of MOMLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of MOMLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: MOMLOC identifies social relationships (such as stepmother and adopted mother) as well as biological relationships. The variable STEPMOM is designed to identify some of these social relationships. To restrict MOMLOC to biological mothers, such as for own children fertility estimation, MOMLOC should be reset to zero when STEPMOM is greater than zero. MOMLOC is a 3-digit numeric variable. Codes0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother Constructed Family Interrelationship Variables -- PERSON Father's location in household POPLOC is a constructed variable that indicates whether or not the person's father lived in the same household and, if so, gives the person number of the father (see PERNUM). POPLOC makes it easy for researchers to link the characteristics of children and their (probable) fathers. The method by which probable child-father links are identified is described in PARRULE. The general design of POPLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of POPLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: POPLOC identifies social relationships (such as stepfather and adopted father) as well as biological relationships. The variable STEPPOP is designed to identify some of these social relationships. To restrict POPLOC to biological mothers, such as for own children fertility estimation, POPLOC should be reset to zero when STEPPOP is greater than zero. POPLOC is a 3-digit numeric variable. Codes0 = No father of this person present in the household. 1 or higher = The person number of this person's father Constructed Family Interrelationship Variables -- PERSON Spouse's location in household SPLOC is a constructed variable that indicates whether or not the person's spouse lived in the same household and, if so, gives the person number (PERNUM) of the spouse. SPLOC makes it easy for researchers to link the characteristics of (probable) spouses. The method by which probable spouse-spouse links are identified is described in SPRULE. The general design of SPLOC and other constructed variables is modeled on the methods developed for IPUMS-USA "Family Interrelationships", but the details vary significantly. For more details on the construction of SPLOC, see the Comparability section of SPRULE and this paper on IPUMSI family linking methodology. SPLOC is a 3-digit numeric variable. Codes0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse Constructed Family Interrelationship Variables -- PERSON Rule for linking parent PARRULE describes the criteria by which the IPUMS International variables MOMLOC and POPLOC linked the person to a probable mother and/or father. IPUMS International establishes child-parent links according to five basic rules, and PARRULE gives the number of the rule that applied to the link in question. A link to any parent automatically generates a second link to that parent's spouse or partner, so only one rule is needed to describe both MOMLOC and POPLOC. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. 00 No parent of person in household 11 Link to head or spouse, unambiguous 12 Link to head or spouse, ambiguous 21 Child-Grandchild, within empirical child cap 22 Child-Grandchild, within constructed child cap 23 Child-Grandchild, exceeds child cap 31 Specified Other Relatives, within empirical child cap 32 Specified Other Relatives, within constructed child cap 33 Specified Other Relatives, exceeds child cap 41 Other Relatives, within empirical child cap 42 Other Relatives, within constructed child cap 51 Non-Relatives, within empirical child cap 52 Non-Relatives, within constructed child cap Constructed Family Interrelationship Variables -- PERSON Rule for linking spouse SPRULE explains the criteria by which the IPUMS-International variable SPLOC linked the person to his/her probable spouse. IPUMS International establishes spouse-spouse links according to five basic rules, and SPRULE gives the number of the rule that applied to the link in question. A sixth rule identifies sample-specific linking procedures only imposed in selected instances. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. 00 No spouse present 01 Rule 1: strong relationship pairing, couple adjacent 02 Rule 2: strong relationship pairing, couple not adjacent 03 Rule 3: weak relationship pairing, couple adjacent 04 Rule 4: weak relationship pairing, couple not adjacent 05 Rule 5: weak consensual union pairings 06 Rule 6: sample-specific rules (usually child-to-child) Constructed Family Interrelationship Variables -- PERSON Probable stepmother STEPMOM indicates whether a person's mother, as identified by MOMLOC, was most probably not the person's biological mother. Non-zero values of STEPMOM explain why it is probable that the person's mother was a step- or adopted mother. A value of 0 indicates no likely stepmother because (1) the mother identified in MOMLOC was probably the biological mother or (2) there is no mother of this person present in the household. The codes for STEPMOM are as follows: 0 = Biological mother or no mother of this person present in household. 1 = Mother has no children born or surviving. 2 = Child reports mother is deceased. 3 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner, stepchild/child-in-law). 4 = Mother reports no children in the home. 5 = Age difference between mother and child was less than 12 or greater than 54 years. 6 = Child exceeds known fertility of mother. In cases where more than one criterion for a likely stepmother is met, STEPMOM will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. In cases where a mother is linked to more children than she reports in CHBORN or CHSURV, the determination of which children to flag as probable stepchildren is based first on the strength of the child-mother pairing (see PARRULE), and then on the order of children in the household roster. Since most links to a given mother will be made at the same strength level, order will often be the decisive factor in flagging probable stepmother relationships. Users should note that there are many stepmothers and adopted mothers in the population that cannot be identified with information available in the censuses. Therefore, STEPMOM will always under-represent their actual number in the population. 0 Biological mother or no mother present 1 Mother has no children born or surviving 2 Child reports mother is deceased 3 Explicitly identified step relationship 4 Mother reports no children in the home 5 Age difference implausible 6 Child exceeds known fertility of mother Constructed Family Interrelationship Variables -- PERSON Probable stepfather STEPPOP indicates whether a person's father, as identified by POPLOC, was most probably not the person's biological father. Non-zero values of STEPPOP explain why it is probable that the person's father was a step- or adopted father. A value of 0 indicates no likely stepfather because (1) the father identified in POPLOC was probably the biological father or (2) there is no father of this person present in the household. The codes for STEPPOP are as follows: 0 = Biological father or no father of this person present in household. 1 = Child reports father is deceased. 2 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner; stepchild/child-in-law). 3 = Age difference between father and child was less than 12 or greater than 54 years. In cases where more than one criterion for a likely stepfather is met, STEPPOP will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepfathers and adopted fathers in the population that cannot be identified with information available in the censuses. Therefore, STEPPOP will always under-represent their actual number in the population. 0 Biological father or no father present 1 Child reports father is deceased 2 Explicitly identified step relationship 3 Age difference implausible 4 Spouse of mother 5 Identified as adopted 6 Surname difference -- male child or never-married female Constructed Family Interrelationship Variables -- PERSON Man with more than one wife linked POLYMAL indicates if a man had more than one wife linked to him in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The point of POLYMAL is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. 0 No more than one wife linked via SPLOC 1 More than one wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON Woman is second or higher order wife POLY2ND indicates if a woman was the second or higher order wife linked to a husband in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The variable does not suggest the actual marital order of wives, only their relative positions in the person order of the household as it was enumerated. The point of POLY2ND is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. 0 Person is not the 2nd or higher order wife linked via SPLOC 1 Person is the 2nd or higher order wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON Family unit membership FAMUNIT is a constructed variable indicating to which family within the household a person belongs. All persons related to the household head receive a 1 (see RELATE). Each secondary family or secondary individual receives a higher code. For purposes of FAMUNIT, secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). FAMUNIT is a 4-digit numeric variable. CodesIf there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on. Constructed Family Interrelationship Variables -- PERSON Number of own family members in household FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them. FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membership). The primary family is defined as all persons related to the head in the RELATE variable. Secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). 0001 1 family member present 0002 2 family members present 0003 3 family members present 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 or more persons Constructed Family Interrelationship Variables -- PERSON Number of own children in household NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children in household Constructed Family Interrelationship Variables -- PERSON Number of own children under age 5 in household NCHLT5 provides a count of the person's own children under age five living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more own children under age 5 in household 98 One or more children have unknown age Constructed Family Interrelationship Variables -- PERSON Age of eldest own child in household ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. ELDCH is top-coded at age 50 or older. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Age of youngest own child in household YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. YNGCH is top-coded at age 50 or older. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Relationship to household head [general version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown Demographic Variables -- PERSON Relationship to household head [detailed version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling's sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder, or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown Demographic Variables -- PERSON 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 Year of birth BIRTHYR gives the person's year of birth. 0000 NIU (not in universe) 1628 1628 1629 1629 1630 1630 1631 1631 1634 1634 1635 1635 1636 1636 1637 1637 1638 1638 1639 1639 1640 1640 1641 1641 1642 1642 1643 1643 1644 1644 1645 1645 1646 1646 1647 1647 1648 1648 1649 1649 1650 1650 1651 1651 1652 1652 1653 1653 1654 1654 1655 1655 1656 1656 1657 1657 1658 1658 1659 1659 1660 1660 1661 1661 1662 1662 1663 1663 1664 1664 1665 1665 1666 1666 1667 1667 1668 1668 1669 1669 1670 1670 1671 1671 1672 1672 1673 1673 1674 1674 1675 1675 1676 1676 1677 1677 1678 1678 1679 1679 1680 1680 1681 1681 1682 1682 1683 1683 1684 1684 1685 1685 1686 1686 1687 1687 1688 1688 1689 1689 1690 1690 1691 1691 1692 1692 1693 1693 1694 1694 1695 1695 1696 1696 1697 1697 1698 1698 1699 1699 1700 1700 1701 1701 1702 1702 1703 1703 1704 1704 1705 1705 1706 1706 1707 1707 1708 1708 1709 1709 1710 1710 1711 1711 1712 1712 1713 1713 1714 1714 1715 1715 1716 1716 1717 1717 1718 1718 1719 1719 1720 1720 1721 1721 1722 1722 1723 1723 1724 1724 1725 1725 1726 1726 1727 1727 1728 1728 1729 1729 1730 1730 1731 1731 1732 1732 1733 1733 1734 1734 1735 1735 1736 1736 1737 1737 1738 1738 1739 1739 1740 1740 1741 1741 1742 1742 1743 1743 1744 1744 1745 1745 1746 1746 1747 1747 1748 1748 1749 1749 1750 1750 1751 1751 1752 1752 1753 1753 1754 1754 1755 1755 1756 1756 1757 1757 1758 1758 1759 1759 1760 1760 1761 1761 1762 1762 1763 1763 1764 1764 1765 1765 1766 1766 1767 1767 1768 1768 1769 1769 1770 1770 1771 1771 1772 1772 1773 1773 1774 1774 1775 1775 1776 1776 1777 1777 1778 1778 1779 1779 1780 1780 1781 1781 1782 1782 1783 1783 1784 1784 1785 1785 1786 1786 1787 1787 1788 1788 1789 1789 1790 1790 1791 1791 1792 1792 1793 1793 1794 1794 1795 1795 1796 1796 1797 1797 1798 1798 1799 1799 1800 1800 1801 1801 1802 1802 1803 1803 1804 1804 1805 1805 1806 1806 1807 1807 1808 1808 1809 1809 1810 1810 1811 1811 1812 1812 1813 1813 1814 1814 1815 1815 1816 1816 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2017 2017 2018 2018 2019 2019 2020 2020 9999 Unknown Demographic Variables -- PERSON Month of birth BIRTHMO indicates the person's month of birth. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Children ever born CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children surviving CHSURV reports the number of children born to a woman who were still living at the time of the census. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female children ever born CHBORNF indicates the number of female children ever born to a woman. Only live births are counted. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male children ever born CHBORNM indicates the number of male children ever born to a woman. Only live births are counted. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female children surviving CHSURVF indicates the number of female children ever born to a woman still living at the time of the census. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male children surviving CHSURVM indicates the number of male children ever born to a woman still living at the time of the census. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of births last year BIRTHSLYR indicates whether any -- and in most cases how many -- children were born to a woman in the past twelve months. 0 None 1 1 (1 or more) 2 2 3 3 4 4+ 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children surviving from births last year BIRTHSURV indicates the number of children born in the past twelve months who were still living at the time of the census. 0 0 1 1 (1 or more) 2 2 3 3 4 4+ 8 Unknown 9 NIU (not in universe) Fertility and Mortality 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 School attendance SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census. 0 NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing Education Variables -- PERSON 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 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 Occupation, ISCO-1988, 3-digit ISCO88A provides the 3-digit occupation code for the respondent using the ISCO-1988 occupation classification. 010 Armed forces 111 Legislators 112 Senior government officials 113 Traditional chiefs and heads of villages 114 Senior officials of special-interest organizations 121 Directors and chief executives 122 Production and operations department managers 123 Other department managers 131 General managers 199 Legislators, senior officials and managers not elsewhere classified 211 Physicists, chemists and related professionals 212 Mathematicians, statisticians and related professionals 213 Computing professionals 214 Architects, engineers and related professionals 221 Life science professionals 222 Health professionals (except nursing) 223 Nursing and midwifery professionals 231 College, university and higher education teaching professionals 232 Secondary education teaching professionals 233 Primary and pre-primary education teaching professionals 234 Special education teaching professionals 235 Other teaching professionals 241 Business professionals 242 Legal professionals 243 Archivists, librarians and related information professionals 244 Social science and related professionals 245 Writers and creative or performing artists 246 Religious professionals 299 Professionals no elsewhere classified 311 Physical and engineering science technicians 312 Computer associate professionals 313 Optical and electronic equipment operators 314 Ship and aircraft controllers and technicians 315 Safety and quality inspectors 321 Life science technicians and related associate professionals 322 Modern health associate professionals (except nursing) 323 Nursing and midwifery associate professionals 324 Traditional medicine practitioners and faith healers 331 Primary education teaching associate professionals 332 Pre-primary education teaching associate professionals 333 Special education teaching associate professionals 334 Other teaching associate professionals 341 Finance and sales associate professionals 342 Business services agents and trade brokers 343 Administrative associate professionals 344 Customs, tax and related government associate professionals 345 Police inspectors and detectives 346 Social work associate professionals 347 Artistic, entertainment and sports associate professionals 348 Religious associate professionals 399 Technicians and associate professionals not elsewhere classified 411 Secretaries and keyboard-operating clerks 412 Numerical clerks 413 Material-recording and transport clerks 414 Library, mail and related clerks 419 Other office clerks 421 Cashiers, tellers and related clerks 422 Client information clerks 499 Clerks not elsewhere classified 511 Travel attendants and related workers 512 Housekeeping and restaurant services workers 513 Personal care and related workers 514 Other personal services workers 515 Astrologers, fortune-tellers and related workers 516 Protective services workers 521 Fashion and other models 522 Shop salespersons and demonstrators 523 Stall and market salespersons 599 Service workers and shop and market sales workers not elsewhere classified 611 Market gardeners and crop growers 612 Market-oriented animal producers and related workers 613 Market-oriented crop and animal producers 614 Forestry and related workers 615 Fishery workers, hunters and trappers 621 Subsistence agricultural and fishery workers 699 Skilled agricultural and fishery workers not elsewhere classified 711 Miners, shotfirers, stone cutters and carvers 712 Building frame and related trades workers 713 Building finishers and related trades workers 714 Painters, building structure cleaners and related trades workers 721 Metal moulders, welders, sheet-metal workers, structural- metal preparers, and related trades workers 722 Blacksmiths, tool-makers and related trades workers 723 Machinery mechanics and fitters 724 Electrical and electronic equipment mechanics and fitters 731 Precision workers in metal and related materials 732 Potters, glass-makers and related trades workers 733 Handicraft workers in wood, textile, leather and related materials 734 Printing and related trades workers 741 Food processing and related trades workers 742 Wood treaters, cabinet-makers and related trades workers 743 Textile, garment and related trades workers 744 Pelt, leather and shoemaking trades workers 799 Craft and related trade workers not elsewhere classified 811 Mining- and mineral-processing-plant operators 812 Metal-processing-plant operators 813 Glass, ceramics and related plant operators 814 Wood-processing- and papermaking-plant operators 815 Chemical-processing-plant operators 816 Power-production and related plant operators 817 Automated-assembly-line and industrial-robot operators 821 Metal- and mineral-products machine operators 822 Chemical-products machine operators 823 Rubber- and plastic-products machine operators 824 Wood-products machine operators 825 Printing-, binding- and paper-products machine operators 826 Textile-, fur- and leather-products machine operators 827 Food and related products machine operators 828 Assemblers 829 Other machine operators and assemblers 831 Locomotive-engine drivers and related workers 832 Motor-vehicle drivers 833 Agricultural and other mobile-plant operators 834 Ships' deck crews and related workers 899 Other plant and machine operaters and assemblers not elsewhere classified 911 Street vendors and related workers 912 Shoe cleaning and other street services elementary occupations 913 Domestic and related helpers, cleaners and launderers 914 Building caretakers, window and related cleaners 915 Messengers, porters, doorkeepers and related workers 916 Garbage collectors and related labourers 921 Agricultural, fishery and related labourers 931 Mining and construction labourers 932 Manufacturing labourers 933 Transport labourers and freight handlers 989 Elementary occupations not elsewhere classified 990 Other workers, not elsewhere classified 998 Unknown 999 NIU (not in universe) 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 Sector of employment EMPSECT indicates the economic sector in which the person was employed. Economic sector is defined in terms of ownership or control of the enterprise in which the person worked. 00 NIU (not in universe) 10 Public 20 Private 21 Private, not elsewhere classified 22 Individual/family enterprise, and self-employed 23 Foreign 30 Mixed: public-private or parastatal 40 Collective or cooperative 50 Foreign government or non-governmental organization 60 Other, unspecified 61 Canal zone 62 Faith-based organization 63 Informal sector 99 Unknown Work Variables -- PERSON 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 Reason for migration MIGCAUSE indicates the reason why the person moved from their previous place of residence. 00 NIU (not in universe) 10 Work 11 Seeking work 12 Job relocation 13 Job assignment 14 Opportunity 15 Proximity to work 16 Job loss 19 Other work 20 Family move 21 Follow household head 22 Follow spouse 23 Follow relative 24 Marriage of a family member 25 Divorce or separation of a family member 26 Healthcare or age of a family member 27 Death or birth of a family member 29 Other family 30 Education 31 Studies 32 End of education 33 Proximity to education 34 Other education 40 Marriage, divorce, widowhood 41 Marriage or union 42 Divorce or widowhood 50 Insecurity, disaster, or violence 51 War, conflict 52 Violence or insecurity 53 Domestic violence 54 Social or political problems, including security 55 Natural disaster 56 Refugee, reason not specified 57 Asylum seeker, reason not specified 59 Other insecurity, disaster, or violence 60 Personal 61 Age related reasons 62 Quality of life 63 Become independent 69 Other personal 70 Other reason 71 Health 72 Repatriation 73 Retirement 74 House or flat acquisition 75 Housing problems 76 Visiting 77 Ordination 78 Military or institutional housing 79 Other reason, not elsewhere classified 99 Unknown Migration: Global Variables -- PERSON Province of previous residence, Iran; consistent boundaries, GIS MIG1_P_IR indicates the person's province of previous residence within Iran. 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. 364000 Markazi 364001 Gilan 364002 Mazandaran 364003 East Azarbayejan 364004 West Azarbayejan 364005 Kermanshah 364006 Khuzestan 364007 Fars 364008 Kerman 364009 Razavi Khorasan 364010 Esfahan 364011 Sistan and Baluchestan 364012 Kordestan 364013 Hamedan 364014 Chaharmahal and Bakhtiyari 364015 Lorestan 364016 Ilam 364017 Kohgiluyeh and Boyerahmad 364018 Bushehr 364019 Zanjan 364020 Semnan 364021 Yazd 364022 Hormozgan 364023 Tehran, Alborz 364024 Ardebil 364025 Qom 364026 Qazvin 364027 Golestan 364028 North Khorasan 364029 South Khorasan 364097 Abroad 364098 Unknown 364099 NIU (not in universe) Migration: F-N Variables -- PERSON Sub-Province of previous residence, Iran; consistent boundaries, GIS MIG2_P_IR indicates the person's sub-province of previous residence within Iran. Migration sub-province codes from MIG2_P_IR are compatible with codes from GEO2_IR. 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. 364000001 Arak, Khondab 364000003 Tafresh, Farahan, Ashtian 364000004 Khomein 364000005 Delijan 364000006 Saveh 364000007 Shazand 364000009 Mahallat 364000010 Zarandiyeh 364000011 Komeijan 364001001 Astara 364001002 Astane-ye-Ashrafiyeh 364001003 Bandar Anzali 364001004 Talesh 364001005 Rasht 364001006 Rudbar 364001007 Rudsar 364001008 Sumaehsara 364001009 Fuman 364001010 Langrud 364001011 Lahijan 364001012 Shaft 364001013 Amlash 364001014 Rezvanshahr 364001015 Siahkal 364001016 Masal 364002001 Amol 364002002 Babol 364002004 Behshahr 364002005 Tonkabon, Abbasabad 364002006 Ramsar 364002007 Sari, Miandorud 364002008 Savadkuh 364002010 Qaemshahr 364002014 Nur 364002015 Noshahr 364002016 Babolsar, Fereydunkenar 364002018 Mahmoudabad 364002019 Neka 364002020 Chalus 364002021 Juybar 364002022 Galugah 364003002 Ahar 364003003 Tabriz 364003005 Sarab 364003006 Maragheh 364003007 Marand 364003010 Miyaneh 364003011 Hashtrud 364003012 Bonab 364003013 Bostanabad 364003014 Shabestar 364003015 Kaleibar, Khoda Afarin 364003016 Haris 364003019 Jolfa 364003020 Malekan 364003021 Azarshahr 364003022 Osku 364003023 Charoimaq 364003024 Varzaqan 364003025 Ajabshir 364004001 Orumiyeh 364004002 Piranshahr 364004003 Khoy, Chaypareh 364004004 Sardasht 364004005 Salmas 364004006 Poldasht, Maku, Showt 364004007 Mahabad 364004008 Miandoab 364004009 Naqadeh 364004010 Bukan 364004011 Shahindezh 364004012 Takab 364004013 Oshnaviyeh 364004014 Chaldoran 364005001 Eslamabad-e-Gharb 364005002 Kermanshah 364005003 Paveh 364005004 Sar-e-pol-e-Zahab 364005005 Sonqor 364005006 Qasr-e-Shirin 364005007 Kangavar 364005008 Gilan-e-Gharb 364005009 Javanrud 364005010 Sahneh 364005011 Harsin 364005012 Salas-e-Babajani 364005013 Dalahu 364005014 Ravansar 364006001 Abadan 364006002 Andimeshk 364006003 Ahvaz, Bavi 364006004 Izeh 364006005 Bandar-e-Mahshahr 364006006 Behbahan 364006007 Khorramshahr 364006008 Dezful 364006009 Hoveizeh, Dasht-e-Azadegan 364006010 Ramhormoz, Haftgol 364006011 Shadegan 364006012 Shushtar 364006013 Andika, Masjed Soleyman 364006014 Shush 364006015 Baghmalek 364006016 Omidiyeh 364006017 Lali 364006018 Hendijan 364006019 Ramshir 364006020 Gotvand 364007001 Abadeh 364007002 Estahban 364007003 Eqlid 364007004 Jahrom 364007005 Darab 364007006 Sepidan 364007007 Shiraz, Sarvestan, Kavar, Kharameh 364007008 Fasa 364007009 Firuzabad 364007010 Kazerun 364007011 Larestan, Gerash 364007012 Marvdasht 364007013 Mamasani, Rostam 364007014 Neyriz 364007015 Lamerd 364007016 Bavanat 364007017 Arsanjan 364007018 Khorrambid 364007019 Zarrindasht 364007020 Qirokarzin 364007021 Mohr 364007022 Farashband 364007023 Pasargad 364007024 Khonj 364008001 Baft, Rabar, Arzuiyeh 364008002 Bam, Rigan, Narmashir, Fahraj 364008003 Jiroft, Anbarabad 364008004 Rafsanjan, Anar 364008005 Kohbonan, Zarand 364008006 Sirjan 364008007 Shahr-e-Babak 364008008 Kerman 364008009 Manujan, Kahnuj, Faryab 364008010 Bardsir 364008011 Ravar 364008015 Rudbar-e-Jonub 364008016 Ghaleh-Ganj 364009004 Taybad, Bakharz 364009005 Torbat-e-Heydariyeh, Zave 364009006 Torbat-e-Jam 364009007 Dargaz 364009008 Sabzevar, Joghatai, Jowayin, Khoshab 364009013 Quchan 364009014 Kashmar 364009015 Gonabad, Bajestan 364009016 Mashhad, Binalud 364009017 Nishapur, Taht-e-Jolegh 364009018 Chenaran 364009019 Khaf 364009020 Sarakhs 364009022 Fariman 364009023 Bardeskan 364009027 Rashtkhar 364009028 Kalat 364009029 Khalil Abad 364009030 Mah-Velat 364010001 Ardestan 364010002 Esfahan 364010003 Khomeinishahr 364010004 Khansar 364010005 Semirom 364010006 Faridan 364010007 Fereydunshahr 364010008 Falavarjan 364010009 Shahreza 364010010 Kashan 364010011 Golpayegan 364010012 Lenjan 364010013 Naeen, Khur o Biabanak 364010014 Najafabad 364010015 Natanz 364010016 Shahinshahr o Meymeh, Borkhar 364010017 Mobarakeh 364010018 Aran and Bidgol 364010019 Tiran and Karvan 364010020 Chadegan 364010021 Dehaqan 364011001 Iranshahr, Dalgan 364011002 Chabahar 364011003 Khash 364011004 Zabol, Hirmand 364011005 Zahedan 364011006 Sib o Soran, Saravan, Zaboli 364011007 Neekshahr 364011008 Sarbaz 364011009 Konarak 364011010 Zahak 364012001 Baneh 364012002 Bijar 364012003 Saqqez 364012004 Sanandaj 364012005 Qorveh, Dehgolan 364012006 Marivan 364012007 Divandarreh 364012008 Kamyaran 364012009 Sarvabad 364013001 Tuyserkan 364013002 Malayer 364013003 Nahavand 364013004 Hamedan, Famenin 364013005 Kabudarahang 364013006 Asadabad 364013007 Bahar 364013008 Razan 364014001 Borujen 364014002 Shahr-e-Kord, Kiaar 364014003 Farsan 364014004 Lordegan 364014005 Ardal 364014006 Kuhrang 364015001 Aligudarz 364015002 Borujerd 364015003 Khorramabad, Dowreh 364015004 Delfan 364015005 Dorud 364015006 Kuhdasht 364015007 Azna 364015008 Poldokhtar 364015009 Selseleh 364016001 Ilam 364016002 Darrehshahr 364016003 Dehloran 364016004 Shirvan and Chardavel 364016005 Mehran, Malekshahi 364016006 Abdanan 364016007 Ivan 364017001 Boyerahmad 364017002 Gachsaran, Basht 364017003 Kohgiluyeh, Charam 364017004 Dena 364017005 Bahmaee 364018001 Bushehr 364018002 Tangestan 364018003 Dashtestan 364018004 Dashti 364018005 Dayyer 364018006 Kangan 364018007 Genaveh 364018008 Deylam 364018009 Jam 364019001 Abhar 364019003 Khodabandeh 364019004 Zanjan 364019006 Ijerud 364019007 Khorramdarreh 364019008 Tarom 364019009 Mahneshan 364020001 Damghan 364020002 Semnan, Mehdishahr 364020003 Shahrud 364020004 Garmsar 364021001 Ardakan 364021002 Bafgh, Behabad 364021003 Taft 364021004 Mehriz 364021005 Yazd 364021006 Meybod 364021007 Abarkuh 364021008 Sadugh 364021009 Khatam 364021010 Tabas 364022002 Bandar Abbas 364022003 Bandar Lengeh 364022004 Qeshm, Abumusa 364022005 Minab, Sirik 364022006 Jask, Bashakerd 364022007 Rudan 364022008 Hajiabad 364022009 Bastak 364022010 Khamir 364022011 Parsian 364023001 Tehran 364023002 Damavand 364023003 Rey 364023004 Shemiranat 364023006 Varamin, Pishva 364023009 Malard, Qod, Shahriar 364023010 Eslamshahr 364023012 Robatkarim, Baharestan 364023013 Pakdasht 364023014 Firuzkuh 364023015 Karaj 364023016 Savojbolagh, Nazarabad, Taleghan 364023998 Tehran and Alborz provinces, unknown sub-province 364024001 Ardebil, Sareyn 364024002 Bilehsavar 364024003 Khalkhal 364024004 Meshkinshahr 364024005 Garmi 364024006 Parsabad 364024007 Kowsar 364024008 Namin 364024009 Neer 364025001 Qom 364026001 Boyinzahra 364026002 Takestan 364026003 Qazvin 364026004 Abyek 364026005 Alborz 364027001 Bandar Gaz 364027002 Gomishan, Torkaman 364027003 Aliabad 364027004 Kordkuy 364027005 Gorgan 364027006 Gonbad-e-Kavus 364027007 Galikash, Minudasht 364027008 Aq Qala 364027009 Maravehtapeh, Kalaleh 364027010 Azadshahr 364027011 Ramyan 364028001 Esfarayen 364028002 Bojnurd 364028003 Jajrom, Garmeh 364028004 Shirvan 364028005 Faruj 364028006 Maneh and Samalqan 364029001 Birjand 364029002 Darmiyan 364029003 Sarbisheh 364029004 Qayenat 364029005 Nahbandan 364029006 Sarayan 364029007 Boshruyeh, Ferdows 364097097 Abroad 364098098 Unknown 364099099 NIU (not in universe) Migration: F-N Variables -- PERSON Person number (within household) Iran 2011: All records This variable indicates the person number (within household). 00 Household record 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 Technical Person Variables -- PERSON Relationship to the head of household 3. Relationship to head of the household</p> <div class="i1">[] 1 Head of household<br />[] 2 Spouse<br />[] 3 Son/daughter<br />[] 4 Son/daughter in low<br />[] 5 Grandchild or great grandchild<br />[] 6 Father or mother<br />[] 7 Brother or sister<br />[] 8 Spouse's parents<br />[] 9 Spouse's brother or sister<br />[] 10 Other relatives<br />[] 11 Non-relatives</div> <span class="em">Column 3 - Relationship to the head of household</span><div class="i1">At this point you have document full name of the head of household on the first row of column 2. Code 1 designating the head of household is included in the design. Ask how every member of the household is related to the head, and document the corresponding code in the designated box located in column 3.<br />- For households with more than one sheet, use the pink box [box for correction] for the individual documented on the first row of the 2nd sheet.<br />- Leave this column blank for collective households.</div> Iran 2011: All persons This variable indicates a person's relationship to the head of household. 01 Head of household 02 Spouse 03 Child 04 Son or daughter-in-law 05 Grandchild or great-grandchild 06 Father or mother 07 Sister or brother 08 Parent-in-law 09 Brother or sister-in-law 10 Other relatives 11 Non-relatives 12 Collective household 98 Unknown Demographic Variables -- PERSON Gender 4. Sex</p> <div class="i1">[] Male<br />[] Female</div> <span class="em">Column 4 - Gender</span><div class="i1">Put X in the corresponding box. Do not guess gender of the individual based on their first names because both genders share some names.</div> Iran 2011: All persons This variable indicates a person's gender. 1 Male 2 Female Demographic Variables -- PERSON Birth month, Iranian Solar calendar Birth date</p> <div class="i1">_ _ 5. Month<br />_ _ 6. Year</div><p>7. Age at last birthday _ _</p> <div class="i1">[] Lunar calendar (check if date of birth is stated in the lunar calendar)<br />[] Under one year<br />[] Aged 100 or over</div> <span class="em">Columns 5and 6 - Date of birth</span> </p> <div class="i1">Ask the respondent to report day, month, and year of the birth of each individual according to their birth certificates or other official documents. If there is discrepancy between the actual date of birth and what is on the birth certificate, accept the latter. <br />- If the individual lacks birth certificate or other official document, accept the date that respondent gives. If the respondent is not informative, for individuals less than 100-year old [except the lunar <span class="lang">hidjri </span> calendar] enter MM in columns 5 and 6.<br />- For individuals 100-year or older, put X in the "100-year and older" box.</div><span class="em">Column 5 -Month</span><div class="i1">- For individuals 100-year or older, whether or not the month of birth is clear even in lunar<span class="lang"> hidjri </span> calendar, just put X in the "100-year and older" box and leave the rest blank.<br />- For individuals less than 100-year old:<br /> [] If age is expressed in calendars rather than the lunar <span class="lang"> hidjri </span> and month of birth is clear, document it as a two-digit number and leave the rest blank. See below.<br /> [] For calendars rather than the lunar <span class="lang">hidjri</span> if the month is no clear print MM in the boxes in column 5 and leave the rest blanks.<br /> [] When the date of birth is in lunar <span class="lang">hidjri</span> calendar, whether or not the month of birth is clear, write X in the lunar<span class="lang"> hidjri </span>calendar box and leave the rest blank.<br />Follow the table on page 84 to turn the non-Iranian months to the Iranian ones.</div> Iran 2011: All persons This variable indicates a person's month of birth. 01 21 March to 20 April 02 21 April to 21 May 03 22 May to 21 June 04 22 June to 22 July 05 23 July to 22 August 06 23 August to 22 September 07 23 September to 22 October 08 23 October to 21 November 09 22 November to 21 December 10 22 December to 20 January 11 21 January to 19 February 12 20 February to 20 March 99 Unknown Demographic Variables -- PERSON Birth year registered in the Islamic Lunar calendar Birth date</p> <div class="i1">_ _ 5. Month<br />_ _ 6. Year</div><p>7. Age at last birthday _ _</p> <div class="i1">[] Lunar calendar (check if date of birth is stated in the lunar calendar)<br />[] Under one year<br />[] Aged 100 or over</div> <span class="em">Columns 5and 6 - Date of birth</span> </p> <div class="i1">Ask the respondent to report day, month, and year of the birth of each individual according to their birth certificates or other official documents. If there is discrepancy between the actual date of birth and what is on the birth certificate, accept the latter. <br />- If the individual lacks birth certificate or other official document, accept the date that respondent gives. If the respondent is not informative, for individuals less than 100-year old [except the lunar <span class="lang">hidjri </span> calendar] enter MM in columns 5 and 6.<br />- For individuals 100-year or older, put X in the "100-year and older" box.</div><span class="em">Colum 6 -Year</span><div class="i1">Follow the instruction below to fill this column:<br />- For individuals 100-year or older, independent of the type of calendar, whether or not the year of birth is clear, write X in the box "100-year or older" and leave both boxes in column clear.<br />- For individual is less than 100-year old:<br />[] For individual whose year of birth is based on lunar/ solar <span class="lang">hidjri</span> [Islamic] calendar, write the last two digits of the year of birth in the boxes in column 6, e.g. write 09 for 1309 and 25 for 1325. <br />[] For individuals with unclear year of birth write MM in both boxes.<br />[] If the year of birth is in Gregorian calendar turned it to the solar <span class="lang">hidjri</span> calendar before writing the last two digits in the corresponding boxes.<br />- If an individual's date of birth is not in any of the above calendars, do research and turn it into solar <span class="lang">hidjri</span> calendar, then document it.</div> Iran 2011: All persons This variable indicates whether a person's birth year is registered in the Islamic lunar calendar. 0 No 1 Yes Demographic Variables -- PERSON Age is 100 years or older (according to birth month) Birth date</p> <div class="i1">_ _ 5. Month<br />_ _ 6. Year</div><p>7. Age at last birthday _ _</p> <div class="i1">[] Lunar calendar (check if date of birth is stated in the lunar calendar)<br />[] Under one year<br />[] Aged 100 or over</div> <span class="em">Column 7 -Age</span><div class="i1">This column is concerned about the number of full years an individual has lived e.g. all individuals older than 15 and less than 16 are considered 15 year-old.<br />- For infants less than one-year old put X in the "les than one-year old" box and leave the rest blank.<br />- For individuals 100-year or older put X in the "100-year and older" box and leave the rest blank.<br />- For the rest of individuals, write the age as a two-digit number in the corresponding boxes in column 7.<br />- For all individuals whose date of birth is based on lunar <span class="lang"> hidjri </span> calendar, subtract the year from 1432 and write the result in column 7.<br />- For individuals whose date of birth is unclear, accept the age that respondent reports. If the respondent is not sure, try to calculate the date of birth by comparing the individual's age with the ages of other members of the family.<br />To fill some of other columns in the questionnaire correctly, ages of individuals should be calculated accurately. Consider the summary table on page 86 when filling columns 5-7.</div> Iran 2011: All persons This variable indicates whether a person is 100 years or older, determined by their birth month. 0 No 1 Yes Demographic Variables -- PERSON Birth year, Islamic Lunar (Gregorian) calendar Birth date</p> <div class="i1">_ _ 5. Month<br />_ _ 6. Year</div><p>7. Age at last birthday _ _</p> <div class="i1">[] Lunar calendar (check if date of birth is stated in the lunar calendar)<br />[] Under one year<br />[] Aged 100 or over</div> <span class="em">Columns 5and 6 - Date of birth</span> </p> <div class="i1">Ask the respondent to report day, month, and year of the birth of each individual according to their birth certificates or other official documents. If there is discrepancy between the actual date of birth and what is on the birth certificate, accept the latter. <br />- If the individual lacks birth certificate or other official document, accept the date that respondent gives. If the respondent is not informative, for individuals less than 100-year old [except the lunar <span class="lang">hidjri </span> calendar] enter MM in columns 5 and 6.<br />- For individuals 100-year or older, put X in the "100-year and older" box.</div><span class="em">Colum 6 -Year</span><div class="i1">Follow the instruction below to fill this column:<br />- For individuals 100-year or older, independent of the type of calendar, whether or not the year of birth is clear, write X in the box "100-year or older" and leave both boxes in column clear.<br />- For individual is less than 100-year old:<br />[] For individual whose year of birth is based on lunar/ solar <span class="lang">hidjri</span> [Islamic] calendar, write the last two digits of the year of birth in the boxes in column 6, e.g. write 09 for 1309 and 25 for 1325. <br />[] For individuals with unclear year of birth write MM in both boxes.<br />[] If the year of birth is in Gregorian calendar turned it to the solar <span class="lang">hidjri</span> calendar before writing the last two digits in the corresponding boxes.<br />- If an individual's date of birth is not in any of the above calendars, do research and turn it into solar <span class="lang">hidjri</span> calendar, then document it.</div> Iran 2011: All persons This variable indicates a person's birth year according to the Islamic Lunar calendar. 1293 1291 to 1293 (1912-13 to 1914-15) 1294 1294 (1915-16) 1295 1295 (1916-17) 1296 1296 (1917-18) 1297 1297 (1918-19) 1298 1298 (1919-20) 1299 1299 (1920-21) 1300 1300 (1921-22) 1301 1301 (1922-23) 1302 1302 (1923-24) 1303 1303 (1924-25) 1304 1304 (1925-26) 1305 1305 (1926-27) 1306 1306 (1927-28) 1307 1307 (1928-29) 1308 1308 (1929-30) 1309 1309 (1930-31) 1310 1310 (1931-32) 1311 1311 (1932-33) 1312 1312 (1933-34) 1313 1313 (1934-35) 1314 1314 (1935-36) 1315 1315 (1936-37) 1316 1316 (1937-38) 1317 1317 (1938-39) 1318 1318 (1939-40) 1319 1319 (1940-41) 1320 1320 (1941-42) 1321 1321 (1942-43) 1322 1322 (1943-44) 1323 1323 (1944-45) 1324 1324 (1945-46) 1325 1325 (1946-47) 1326 1326 (1947-48) 1327 1327 (1948-49) 1328 1328 (1949-50) 1329 1329 (1950-51) 1330 1330 (1951-52) 1331 1331 (1952-53) 1332 1332 (1953-54) 1333 1333 (1954-55) 1334 1334 (1955-56) 1335 1335 (1956-57) 1336 1336 (1957-58) 1337 1337 (1958-59) 1338 1338 (1959-60) 1339 1339 (1960-61) 1340 1340 (1961-62) 1341 1341 (1962-63) 1342 1342 (1963-64) 1343 1343 (1964-65) 1344 1344 (1965-66) 1345 1345 (1966-67) 1346 1346 (1967-68) 1347 1347 (1968-69) 1348 1348 (1969-70) 1349 1349 (1970-71) 1350 1350 (1971-72) 1351 1351 (1972-73) 1352 1352 (1973-74) 1353 1353 (1974-75) 1354 1354 (1975-76) 1355 1355 (1976-77) 1356 1356 (1977-78) 1357 1357 (1978-79) 1358 1358 (1979-80) 1359 1359 (1980-81) 1360 1360 (1981-82) 1361 1361 (1982-83) 1362 1362 (1983-84) 1363 1363 (1984-85) 1364 1364 (1985-86) 1365 1365 (1986-87) 1366 1366 (1987-88) 1367 1367 (1988-89) 1368 1368 (1989-90) 1369 1369 (1990-91) 1370 1370 (1991-92) 1371 1371 (1992-93) 1372 1372 (1993-94) 1373 1373 (1994-95) 1374 1374 (1995-96) 1375 1375 (1996-97) 1376 1376 (1997-98) 1377 1377 (1998-99) 1378 1378 (1999-00) 1379 1379 (2000-01) 1380 1380 (2001-02) 1381 1381 (2002-03) 1382 1382 (2003-04) 1383 1383 (2004-05) 1384 1384 (2005-06) 1385 1385 (2006- 07) 1386 1386 (2007-08) 1387 1387 (2008-09) 1388 1388 (2009-10) 1389 1389 (2010-11) 1390 1390 (2011) 9998 Unknown Demographic Variables -- PERSON Age is 100 years or older (according to birth year) Birth date</p> <div class="i1">_ _ 5. Month<br />_ _ 6. Year</div><p>7. Age at last birthday _ _</p> <div class="i1">[] Lunar calendar (check if date of birth is stated in the lunar calendar)<br />[] Under one year<br />[] Aged 100 or over</div> <span class="em">Column 7 -Age</span><div class="i1">This column is concerned about the number of full years an individual has lived e.g. all individuals older than 15 and less than 16 are considered 15 year-old.<br />- For infants less than one-year old put X in the "les than one-year old" box and leave the rest blank.<br />- For individuals 100-year or older put X in the "100-year and older" box and leave the rest blank.<br />- For the rest of individuals, write the age as a two-digit number in the corresponding boxes in column 7.<br />- For all individuals whose date of birth is based on lunar <span class="lang"> hidjri </span> calendar, subtract the year from 1432 and write the result in column 7.<br />- For individuals whose date of birth is unclear, accept the age that respondent reports. If the respondent is not sure, try to calculate the date of birth by comparing the individual's age with the ages of other members of the family.<br />To fill some of other columns in the questionnaire correctly, ages of individuals should be calculated accurately. Consider the summary table on page 86 when filling columns 5-7.</div> Iran 2011: All persons This variable indicates whether a person is 100 years or older, determined by their birth year. 0 No 1 Yes Demographic Variables -- PERSON Age Birth date</p> <div class="i1">_ _ 5. Month<br />_ _ 6. Year</div><p>7. Age at last birthday _ _</p> <div class="i1">[] Lunar calendar (check if date of birth is stated in the lunar calendar)<br />[] Under one year<br />[] Aged 100 or over</div> <span class="em">Column 7 -Age</span><div class="i1">This column is concerned about the number of full years an individual has lived e.g. all individuals older than 15 and less than 16 are considered 15 year-old.<br />- For infants less than one-year old put X in the "les than one-year old" box and leave the rest blank.<br />- For individuals 100-year or older put X in the "100-year and older" box and leave the rest blank.<br />- For the rest of individuals, write the age as a two-digit number in the corresponding boxes in column 7.<br />- For all individuals whose date of birth is based on lunar <span class="lang"> hidjri </span> calendar, subtract the year from 1432 and write the result in column 7.<br />- For individuals whose date of birth is unclear, accept the age that respondent reports. If the respondent is not sure, try to calculate the date of birth by comparing the individual's age with the ages of other members of the family.<br />To fill some of other columns in the questionnaire correctly, ages of individuals should be calculated accurately. Consider the summary table on page 86 when filling columns 5-7.</div> Iran 2011: All persons This variable indicates a person's age. 000 Less than one year old 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100+ 998 Unknown Demographic Variables -- PERSON Less than one year old Birth date</p> <div class="i1">_ _ 5. Month<br />_ _ 6. Year</div><p>7. Age at last birthday _ _</p> <div class="i1">[] Lunar calendar (check if date of birth is stated in the lunar calendar)<br />[] Under one year<br />[] Aged 100 or over</div> <span class="em">Column 7 -Age</span><div class="i1">This column is concerned about the number of full years an individual has lived e.g. all individuals older than 15 and less than 16 are considered 15 year-old.<br />- For infants less than one-year old put X in the "les than one-year old" box and leave the rest blank.<br />- For individuals 100-year or older put X in the "100-year and older" box and leave the rest blank.<br />- For the rest of individuals, write the age as a two-digit number in the corresponding boxes in column 7.<br />- For all individuals whose date of birth is based on lunar <span class="lang"> hidjri </span> calendar, subtract the year from 1432 and write the result in column 7.<br />- For individuals whose date of birth is unclear, accept the age that respondent reports. If the respondent is not sure, try to calculate the date of birth by comparing the individual's age with the ages of other members of the family.<br />To fill some of other columns in the questionnaire correctly, ages of individuals should be calculated accurately. Consider the summary table on page 86 when filling columns 5-7.</div> Iran 2011: All persons This variable indicates whether a person is less than one year old. 0 No 1 Yes Demographic Variables -- PERSON Age is 100 years or older Birth date</p> <div class="i1">_ _ 5. Month<br />_ _ 6. Year</div><p>7. Age at last birthday _ _</p> <div class="i1">[] Lunar calendar (check if date of birth is stated in the lunar calendar)<br />[] Under one year<br />[] Aged 100 or over</div> <span class="em">Column 7 -Age</span><div class="i1">This column is concerned about the number of full years an individual has lived e.g. all individuals older than 15 and less than 16 are considered 15 year-old.<br />- For infants less than one-year old put X in the "les than one-year old" box and leave the rest blank.<br />- For individuals 100-year or older put X in the "100-year and older" box and leave the rest blank.<br />- For the rest of individuals, write the age as a two-digit number in the corresponding boxes in column 7.<br />- For all individuals whose date of birth is based on lunar <span class="lang"> hidjri </span> calendar, subtract the year from 1432 and write the result in column 7.<br />- For individuals whose date of birth is unclear, accept the age that respondent reports. If the respondent is not sure, try to calculate the date of birth by comparing the individual's age with the ages of other members of the family.<br />To fill some of other columns in the questionnaire correctly, ages of individuals should be calculated accurately. Consider the summary table on page 86 when filling columns 5-7.</div> Iran 2011: All persons This variable indicates that a person is 100 years old or older. 0 No 1 Yes Demographic Variables -- PERSON Residence status 8. Residence status <br /> </p> <div class="i1">[] 1 Present<br />[] 2 Temporarily absent<br />[] 3 Abroad for work or education<br />[] 4 Other</div> <span class="em">Column 8 -Domicile status</span><div class="i1">Enter the relevant code for each household member. <br />Code 1, Present- Indicates the individual resides at the usual residence of the household when such household is enumerated. If the individual is at workplace, school, etc. he will return to the residence at the end of workday or school day.<br />Code 2, temporarily absent-<br />- This code is applied to individuals who have left the household temporarily and are on trips for business, leisure, pilgrim, or hospitalization, etc. and are in another place [within the country or abroad].<br />- Newborn and their mother who are still in the hospital.<br />Code 3, abroad for education or work- This code is applied to individuals who are expected to return to the household under enumeration after finishing work or education.<br />Code 4, Other- Code 4 indicates household members who do not belong to any other category e.g. those in the company of individuals marked with code 3, e.g. spouses and children of individuals who live abroad for work or education.</div> Iran 2011: All persons This variable indicates a person's residence status within the household. 1 Present 2 Temporarily absent 3 Abroad for education or work 4 Other 8 Unknown Migration: Global Variables -- PERSON Live in another residence 9. Does he/she reside in another place?</p> <div class="i1">[] 1 Yes, in the same village or city<br />[] 2 Yes, in other city, cite it ____<br />[] 3 Yes, in other village ____<br />[] 4 No</div> <span class="em">Column 9 -Does the individual reside in another residence?</span><div class="i1">Complete this section for present and temporarily absent household members [those with code 1 or 2 in column 8], and leave it blank for the rest.<br />Code 1, in the same city or settlement<br />Code 2, in another city [include name]<br />Code 3, in another settlement<br />Code 4, no for those who do not have another placed of residence<br />If the individual resides in multiple residences, enter the code indicating the location that individual resides the longest duration throughout the year. <br />[Picture omitted]</div> Iran 2011: Persons who are present or temporarily absent [discrepancies: none] This variable indicates whether a person lives in another residence. 1 Yes, in the same city or settlement 2 Yes, in another city 3 Yes, in another settlement 4 No 8 Unknown 9 NIU (not in universe) Migration: Global Variables -- PERSON Fraction of the year spent in the second residence <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p><span class="em">For those who responded "yes, in the same village" or city or "yes, in other city" to question 9</span> <br />10. How long has the person lived in the second residence?</p> <div class="i1">[] 1 Less than three months<br />[] 2 Three to six months</div> <span class="em">Column 10 -What fraction of the year does the individual spend in the 2nd residence?</span> </p> <div class="i1">Fill this column for individuals with codes 2 or 3 in column 9 and leave it blank for the. If the individual resides in the 2nd residence less than 3 months check 1 and if between 3 -6 months check 2. If the individual stays more than 6 months per year in the 2nd residence, do not consider him a member of the household under enumeration, therefore do not assign him a row in this questionnaire.<br />[Picture omitted]</div> Iran 2011: Persons who live in another city or settlement [discrepancies: none] This variable indicates the fraction of the year that a person spent in the second residence. 1 Less than 3 months 2 3 to 6 months 8 Unknown 9 NIU (not in universe) Migration: Global Variables -- PERSON Changed city or settlement of residence since October 23, 2006 <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p>11. Has she/he changed his/her residences since 2006? <br /> </p> <div class="i1">[] Yes<br />[] No</div> <span class="em">Column 11 -16, moving status -General description</span> <br /> </p> <div class="i1">Fill this columns if code 1 or 2 is checked in column 8, and leave it blank for the. This column is left blank for conventional unsettled households.<br />[Picture omitted]</div><span class="em">Column 11 -Has the individual changed city or settlement of residence since October 23, 2006 [last census]?</span><div class="i1">This column documents whether or not individual has changed city or settlement of residence. Leave it blank for those who moved within the same city or settlement.</div> Iran 2011: Persons who are present or temporarily absent [discrepancies: none] This variable indicates whether a person changed city or settlement of residence since October 23, 2006. 1 Yes 2 No 9 NIU (not in universe) Migration: Global Variables -- PERSON Length of residence in the other city or settlement (in years) <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p>11. Has she/he changed his/her residences since 2006? <br /> </p> <div class="i1">[] Yes<br />[] No</div><span class="em">For persons who answered yes to question 11</span> <br />12. Length of residence in the same city or village in full years _ _ <span class="em">Column 11 -16, moving status -General description</span> <br /> </p> <div class="i1">Fill this columns if code 1 or 2 is checked in column 8, and leave it blank for the. This column is left blank for conventional unsettled households.<br />[Picture omitted]</div><span class="em">Column 11 -Has the individual changed city or settlement of residence since October 23, 2006 [last census]?</span><div class="i1">This column documents whether or not individual has changed city or settlement of residence. Leave it blank for those who moved within the same city or settlement.</div><span class="em">Column 12 -16, General description</span><div class="i1">If "yes" is checked in column 11, fill columns 12 -16 but leave them blank for the rest of members. If the individual has moved several times since the last census, fill these columns for the latest move.</div><span class="em">Column 12 -Length of residence in the very city or settlement in full years</span><div class="i1">[Picture omitted]<br />The very city or settlement refers to the geographical location where the individual has lived continuously till enumeration. Report the length of stay in full years e.g. write 3 in column 12 if the duration of stay is three years and 11 months. <br />- If the individual has not filled a full year write "0".<br />- It is obvious that the reported number cannot exceed 5 years.</div> Iran 2011: Persons who changed city or settlement of residence [discrepancies: none] This variable indicates a person's length of residence in the other city or settlement. 0 0 year 1 1 year 2 2 years 3 3 4 4 5 5 8 Unknown 9 NIU (not in universe) Migration: Global Variables -- PERSON Reason for change of previous residence <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p><span class="em">For persons who answered yes to question 11</span> <br />12. Length of residence in the same city or village in full years _ _</p> <p>13. Reason for change of previous residence <br /> </p> <div class="i1">[] 1 Seeking job<br />[] 2 Looking for a better job<br />[] 3 Job transfer<br />[] 4 Education<br />[] 5 Being graduate<br />[] 6 Military service<br />[] 7 End of military service<br />[] 8 Following the household<br />[] 9 Other</div> <span class="em">Column 11 -16, moving status -General description</span> <br /> </p> <div class="i1">Fill this columns if code 1 or 2 is checked in column 8, and leave it blank for the. This column is left blank for conventional unsettled households.<br />[Picture omitted]</div><span class="em">Column 11 -Has the individual changed city or settlement of residence since October 23, 2006 [last census]?</span><div class="i1">This column documents whether or not individual has changed city or settlement of residence. Leave it blank for those who moved within the same city or settlement.</div><span class="em">Column 12 -16, General description</span><div class="i1">If "yes" is checked in column 11, fill columns 12 -16 but leave them blank for the rest of members. If the individual has moved several times since the last census, fill these columns for the latest move.</div><span class="em">Column 13 -reason for change of previous residence</span><div class="i1">[Picture omitted]<br />Fill this column only if "yes" is checked in column 11. Check only one out of the nine codes in column 13.<br />- When there are several reasons for moving, document the most important move according to the respondent's report.<br />- For individuals who have moved several times since the last census, document the reason for the latest move. <br />Code 1, seeking employment<br />Enter code 1 for an individual who had been unemployed before leaving the previous residence, and had moved to another city to start an actual job or seek employment. <br />Code 2, seeking better employment <br />Enter code 2 for an individual who had been employed before leaving the previous residence, and moved to another city to start a better job or seek a better employment. <br />Code 3, job transfer <br />Enter code 3 if individual moved from the previous residence and moved to the city under enumeration due to job transfer. <br />Code 4, education<br />Enter code 4 if the individual changed the previous residence in order to start school in the city or settlement under enumeration.<br />Code 5, graduation<br />Enter code 5 if the individual changed previous residence because he graduated and moved to the city or settlement under enumeration.<br />Code 6, mandatory service or discharge<br />Enter code 6 if the individual moved to the city or settlement under enumeration to start conscription or moved to the very city upon discharge.<br />Code 7, seeking better housing<br />Enter 7 if the individual changed the previous residence to find better housing, whether cheaper, with improved facilities, etc.<br />Code 8, following the household<br />Enter code 8 for dependents who follow the household or those who changed their residence after getting married.<br />Code 9, other<br />Enter code 9 if none of the other codes apply to the individual, e.g. move due to climate, access to advanced facilities, imprisonment, etc.</div> Iran 2011: Persons who changed city or settlement of residence [discrepancies: none] This variable indicates the reason that a person moved from the previous residence. 01 Seeking job 02 Looking for a better job 03 Job transfer 04 Education 05 Graduation 06 Military service 07 End of military service 08 Following the household 09 Other 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Previous residence <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p><span class="em">For persons who answered yes to question 11</span> <br />12. Length of residence in the same city or village in full years _ _</p> <p>14. Previous residence</p> <div class="i1">Elsewhere in the same <span class="lang">Shahrestan</span> (sub-province)</div><div class="i2">[] 1 City<br />[] 2 Village</div><div class="i1">Another <span class="lang">Shahrestan</span> (sub-province)</div><div class="i2">[] 3 City<br />[] 4 Village<br />[] 5 Abroad</div> <span class="em">Column 11 -16, moving status -General description</span> <br /> </p> <div class="i1">Fill this columns if code 1 or 2 is checked in column 8, and leave it blank for the. This column is left blank for conventional unsettled households.<br />[Picture omitted]</div><span class="em">Column 11 -Has the individual changed city or settlement of residence since October 23, 2006 [last census]?</span><div class="i1">This column documents whether or not individual has changed city or settlement of residence. Leave it blank for those who moved within the same city or settlement.</div><span class="em">Column 12 -16, General description</span><div class="i1">If "yes" is checked in column 11, fill columns 12 -16 but leave them blank for the rest of members. If the individual has moved several times since the last census, fill these columns for the latest move.</div><span class="em">Column 14 -previous residence</span><div class="i1">[Picture omitted]<br />If "yes" is checked in column 11, fill column 14 with one of the 5 codes explained below:<br />Codes 1 and 2, another residence in the same county<br />Enter code one for city and 2 for settlement<br />Codes 3 and 4, another county<br />Enter code one for city and 2 for settlement<br />Code 5, abroad<br />Enter code 5 for all individuals whose previous residences were abroad.<br />If the individual has moved several times since the last census, fill these columns for the latest move.</div> Iran 2011: Persons who changed city or settlement of residence [discrepancies: none] This variable indicates the location of a person's previous residence. 1 Different city within the same sub-province 2 Different village within the same sub-province 3 Different city in a different sub-province 4 Different village in a different sub-province 5 Abroad 6 Different sub-province, unknown if city or village 7 Changed settlement or residence, from unknown location in Iran 8 Unknown 9 NIU (not in universe) Migration: Global Variables -- PERSON Province of previous residence <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p><span class="em">For persons who answered yes to question 11</span> <br />12. Length of residence in the same city or village in full years _ _</p> <p><span class="em">For those living in another <span class="lang">Shahrestan</span> sub-province from question 14</span> <br />15. Name of the <span class="lang">Shahrestan</span> (sub-province) of the previous residence, for abroad name of country ____ <span class="em">Column 11 -16, moving status -General description</span> <br /> </p> <div class="i1">Fill this columns if code 1 or 2 is checked in column 8, and leave it blank for the. This column is left blank for conventional unsettled households.<br />[Picture omitted]</div><span class="em">Column 11 -Has the individual changed city or settlement of residence since October 23, 2006 [last census]?</span><div class="i1">This column documents whether or not individual has changed city or settlement of residence. Leave it blank for those who moved within the same city or settlement.</div><span class="em">Column 12 -16, General description</span><div class="i1">If "yes" is checked in column 11, fill columns 12 -16 but leave them blank for the rest of members. If the individual has moved several times since the last census, fill these columns for the latest move.</div><span class="em">Column 15 -name of the county of previous residence [if abroad, write the country]</span><div class="i1">[Picture omitted] <br />Fill this column for individuals with codes 3, 4, or 5 in column 14, and leave it blank for the rest. If codes 3 or 4 is in column 14, write the name of the previous county of residence [based on the latest administrative divisions of Iran], and if code 5 is in column 14, write the name of the foreign country. If the respondent does not know name of the county but those of district and/or city, use tables in the addendum to find it.</div> Iran 2011: Persons who changed sub-province of residence [discrepancies: none] This variable indicates the province of a person's previous residence. 00 Markazi 01 Gilan 02 Mazandaran 03 East Azarbayejan 04 West Azarbayejan 05 Kermanshah 06 Khuzestan 07 Fars 08 Kerman 09 Razavi Khorasan 10 Esfahan 11 Sistan and Baluchestan 12 Kordestan 13 Hamedan 14 Chaharmahal and Bakhtiyari 15 Lorestan 16 Ilam 17 Kohgiluyeh and Boyerahmad 18 Bushehr 19 Zanjan 20 Semnan 21 Yazd 22 Hormozgan 23 Tehran 24 Ardebil 25 Qom 26 Qazvin 27 Golestan 28 North Khorasan 29 South Khorasan 30 Alborz 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Sub-province of previous residence <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p><span class="em">For persons who answered yes to question 11</span> <br />12. Length of residence in the same city or village in full years _ _</p> <p><span class="em">For those living in another <span class="lang">Shahrestan</span> sub-province from question 14</span> <br />15. Name of the <span class="lang">Shahrestan</span> (sub-province) of the previous residence, for abroad name of country ____ <span class="em">Column 11 -16, moving status -General description</span> <br /> </p> <div class="i1">Fill this columns if code 1 or 2 is checked in column 8, and leave it blank for the. This column is left blank for conventional unsettled households.<br />[Picture omitted]</div><span class="em">Column 11 -Has the individual changed city or settlement of residence since October 23, 2006 [last census]?</span><div class="i1">This column documents whether or not individual has changed city or settlement of residence. Leave it blank for those who moved within the same city or settlement.</div><span class="em">Column 12 -16, General description</span><div class="i1">If "yes" is checked in column 11, fill columns 12 -16 but leave them blank for the rest of members. If the individual has moved several times since the last census, fill these columns for the latest move.</div><span class="em">Column 15 -name of the county of previous residence [if abroad, write the country]</span><div class="i1">[Picture omitted] <br />Fill this column for individuals with codes 3, 4, or 5 in column 14, and leave it blank for the rest. If codes 3 or 4 is in column 14, write the name of the previous county of residence [based on the latest administrative divisions of Iran], and if code 5 is in column 14, write the name of the foreign country. If the respondent does not know name of the county but those of district and/or city, use tables in the addendum to find it.</div> Iran 2011: Persons who changed sub-province of residence [discrepancies: none] This variable indicates the sub-province of a person's previous residence. 0001 Arak 0003 Tafresh 0004 Khomein 0005 Delijan 0006 Saveh 0007 Shazand 0009 Mahallat 0014 Province of Markazi, other sub-provinces 0101 Astara 0102 Astane-ye-Ashrafiyeh 0103 Bandar Anzali 0104 Talesh 0105 Rasht 0106 Rudbar 0107 Rudsar 0108 Sumaehsara 0109 Fuman 0110 Langrud 0111 Lahijan 0112 Shaft 0113 Amlash 0115 Siahkal 0117 Province of Gilan, other sub-provinces 0201 Amol 0202 Babol 0204 Behshahr 0205 Tonkabon 0206 Ramsar 0207 Sari 0208 Savadkuh 0210 Qaemshahr 0214 Nur 0215 Noshahr 0216 Babolsar 0218 Mahmoudabad 0219 Neka 0220 Chalus 0221 Juybar 0226 Province of Mazandaran, other sub-provinces 0302 Ahar 0303 Tabriz 0305 Sarab 0306 Maragheh 0307 Marand 0310 Miyaneh 0311 Hashtrud 0312 Bonab 0313 Bostanabad 0314 Shabestar 0315 Kaleibar 0316 Haris 0319 Jolfa 0320 Malekan 0322 Osku 0324 Varzaqan 0325 Ajabshir 0327 Province of East Azarbayejan, other sub-provinces 0401 Orumiyeh 0402 Piranshahr 0403 Khoy 0404 Sardasht 0405 Salmas 0406 Maku 0407 Mahabad 0408 Miandoab 0409 Naqadeh 0410 Bukan 0411 Shahindezh 0412 Takab 0418 Province of West Azarbayejan, other sub-provinces 0501 Eslamabad-e-Gharb 0502 Kermanshah 0503 Paveh 0504 Sar-e-pol-e-Zahab 0505 Sonqor 0506 Qasr-e-Shirin 0507 Kangavar 0509 Javanrud 0510 Sahneh 0511 Harsin 0513 Dalahu 0515 Province of Kermanshah, other sub-provinces 0601 Abadan 0602 Andimeshk 0603 Ahvaz 0604 Izeh 0605 Bandar-e-Mahshahr 0606 Behbahan 0607 Khorramshahr 0608 Dezful 0610 Ramhormoz 0611 Shadegan 0612 Shushtar 0613 Masjed Soleyman 0614 Shush 0615 Baghmalek 0616 Omidiyeh 0619 Ramshir 0624 Province of Khuzestan, other sub-provinces 0701 Abadeh 0702 Estahban 0703 Eqlid 0704 Jahrom 0705 Darab 0706 Sepidan 0707 Shiraz 0708 Fasa 0709 Firuzabad 0710 Kazerun 0711 Larestan 0712 Marvdasht 0713 Mamasani 0714 Neyriz 0715 Lamerd 0716 Bavanat 0717 Arsanjan 0720 Qirokarzin 0721 Mohr 0722 Farashband 0728 Kavar 0729 Kharameh 0730 Province of Fars, other sub-provinces 0801 Baft 0802 Bam 0803 Jiroft 0804 Rafsanjan 0805 Zarand 0806 Sirjan 0808 Kerman 0809 Kahnuj 0810 Bardsir 0812 Anbarabad 0824 Province of Kerman, other sub-provinces 0904 Taybad 0905 Torbat-e-Heydariyeh 0906 Torbat-e-Jam 0907 Dargaz 0908 Sabzevar 0913 Quchan 0914 Kashmar 0915 Gonabad 0916 Mashhad 0917 Nishapur 0918 Chenaran 0919 Khaf 0920 Sarakhs 0922 Fariman 0923 Bardeskan 0927 Rashtkhar 0928 Kalat 0939 Province of Razavi Khorasan, other sub-provinces 1001 Ardestan 1002 Esfahan 1003 Khomeinishahr 1005 Semirom 1006 Faridan 1007 Fereydunshahr 1008 Falavarjan 1009 Shahreza 1010 Kashan 1011 Golpayegan 1012 Lenjan 1013 Naeen 1014 Najafabad 1015 Natanz 1016 Shahinshahr o Meymeh 1017 Mobarakeh 1019 Tiran and Karvan 1024 Province of Esfahan, other sub-provinces 1101 Iranshahr 1102 Chabahar 1103 Khash 1104 Zabol 1105 Zahedan 1106 Saravan 1107 Neekshahr 1115 Province of Sistan and Baluchestan, other sub-provinces 1201 Baneh 1202 Bijar 1203 Saqqez 1204 Sanandaj 1205 Qorveh 1206 Marivan 1207 Divandarreh 1208 Kamyaran 1209 Sarvabad 1210 Dehgolan 1301 Tuyserkan 1302 Malayer 1303 Nahavand 1304 Hamedan 1305 Kabudarahang 1306 Asadabad 1308 Razan 1310 Province of Hamedan, other sub-provinces 1401 Borujen 1402 Shahr-e-Kord 1403 Farsan 1404 Lordegan 1405 Ardal 1408 Province of Chaharmahal and Bakhtiyari, other sub-provinces 1501 Aligudarz 1502 Borujerd 1503 Khorramabad 1505 Dorud 1506 Kuhdasht 1507 Azna 1508 Poldokhtar 1510 Province of Lorestan, other sub-provinces 1601 Ilam 1602 Darrehshahr 1603 Dehloran 1604 Shirvan and Chardavel 1605 Mehran 1609 Province of Ilam, other sub-provinces 1701 Boyerahmad 1702 Gachsaran 1703 Kohgiluyeh 1708 Province of Kohgiluyeh and Boyerahmad, other sub-provinces 1801 Bushehr 1802 Tangestan 1803 Dashtestan 1804 Dashti 1806 Kangan 1807 Genaveh 1809 Jam 1810 Province of Bushehr, other sub-provinces 1901 Abhar 1903 Khodabandeh 1904 Zanjan 1907 Khorramdarreh 1909 Mahneshan 1910 Province of Zanjan, other sub-provinces 2001 Damghan 2002 Semnan 2003 Shahrud 2006 Province of Semnan, other sub-provinces 2102 Bafgh 2105 Yazd 2110 Tabas 2112 Province of Yazd, other sub-provinces 2202 Bandar Abbas 2203 Bandar Lengeh 2204 Qeshm 2205 Minab 2207 Rudan 2208 Hajiabad 2214 Province of Hormozgan, other sub-provinces 2301 Tehran 2302 Damavand 2303 Rey 2306 Varamin 2309 Shahriar 2310 Eslamshahr 2312 Robatkarim 2313 Pakdasht 2316 Qod 2317 Malard 2319 Baharestan 2320 Province of Tehran, other sub-provinces 2401 Ardebil 2403 Khalkhal 2404 Meshkinshahr 2405 Garmi 2406 Parsabad 2411 Province of Ardebil, other sub-provinces 2501 Qom 2601 Boyinzahra 2602 Takestan 2603 Qazvin 2604 Abyek 2605 Alborz 2701 Bandar Gaz 2702 Torkaman 2703 Aliabad 2705 Gorgan 2706 Gonbad-e-Kavus 2707 Minudasht 2708 Aq Qala 2709 Kalaleh 2710 Azadshahr 2714 Galikash 2715 Province of Golestan, other sub-provinces 2801 Esfarayen 2802 Bojnurd 2803 Jajrom 2804 Shirvan 2805 Faruj 2808 Province of North Khorasan, other sub-provinces 2901 Birjand 2902 Darmiyan 2904 Qayenat 2905 Nahbandan 2907 Ferdows 2909 Province of South Khorasan, other sub-provinces 3001 Karaj 3002 Savojbolagh 3005 Province of Alborz, other sub-provinces 9998 Unknown 9999 NIU (not in universe) 9997 Abroad Migration: Global Variables -- PERSON Country of previous residence <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p><span class="em">For persons who answered yes to question 11</span> <br />12. Length of residence in the same city or village in full years _ _</p> <p><span class="em">For those living in another <span class="lang">Shahrestan</span> sub-province from question 14</span> <br />15. Name of the <span class="lang">Shahrestan</span> (sub-province) of the previous residence, for abroad name of country ____ <span class="em">Column 11 -16, moving status -General description</span> <br /> </p> <div class="i1">Fill this columns if code 1 or 2 is checked in column 8, and leave it blank for the. This column is left blank for conventional unsettled households.<br />[Picture omitted]</div><span class="em">Column 11 -Has the individual changed city or settlement of residence since October 23, 2006 [last census]?</span><div class="i1">This column documents whether or not individual has changed city or settlement of residence. Leave it blank for those who moved within the same city or settlement.</div><span class="em">Column 12 -16, General description</span><div class="i1">If "yes" is checked in column 11, fill columns 12 -16 but leave them blank for the rest of members. If the individual has moved several times since the last census, fill these columns for the latest move.</div><span class="em">Column 15 -name of the county of previous residence [if abroad, write the country]</span><div class="i1">[Picture omitted] <br />Fill this column for individuals with codes 3, 4, or 5 in column 14, and leave it blank for the rest. If codes 3 or 4 is in column 14, write the name of the previous county of residence [based on the latest administrative divisions of Iran], and if code 5 is in column 14, write the name of the foreign country. If the respondent does not know name of the county but those of district and/or city, use tables in the addendum to find it.</div> Iran 2011: Persons who changed their place of residence from abroad [discrepancies: none] This variable indicates the country of a person's previous residence. 004 Afghanistan 368 Iraq 414 Kuwait 586 Pakistan 784 United Arab Emirates 990 Asia, other 991 Europe 992 Other 998 Unknown 999 NIU (not in universe) Migration: Global Variables -- PERSON Changed foreign country of residence to Iran <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p><span class="em">For all answers except abroad in question 14</span> <br />16. Has she/he changed her/his residence from abroad to the inside country since Nov. 2006 ____ <span class="em">Column 11 -16, moving status -General description</span> <br /> </p> <div class="i1">Fill this columns if code 1 or 2 is checked in column 8, and leave it blank for the. This column is left blank for conventional unsettled households.<br />[Picture omitted]</div><span class="em">Column 11 -Has the individual changed city or settlement of residence since October 23, 2006 [last census]?</span><div class="i1">This column documents whether or not individual has changed city or settlement of residence. Leave it blank for those who moved within the same city or settlement.</div><span class="em">Column 12 -16, General description</span><div class="i1">If "yes" is checked in column 11, fill columns 12 -16 but leave them blank for the rest of members. If the individual has moved several times since the last census, fill these columns for the latest move.</div><span class="em">Column 16 -has the individual changed foreign country of residence to Iran? [write the name]</span><div class="i1">[Picture omitted]<br />Fill this column for individuals with codes 1, 2, 3, and 4 in column 14, namely those who had at least one move within the country. Leave this part blank if the individual did not move. <br />Find out whether or not the individual moved from abroad to Iran since the last census. Check yes or no according to the response.</div> Iran 2011: Persons who changed city or settlement of residence, excluding those who lived abroad [discrepancies: none] This variable indicates whether a person changed their country of residence from a foreign country to Iran. 1 Yes 2 No 9 NIU (not in universe) Migration: Global Variables -- PERSON Country of previous residence <span class="h3">Questions 10-16 for those whose residence status is present or temporarily absent</span></p> <p><span class="em">For all answers except abroad in question 14</span> <br />16. Has she/he changed her/his residence from abroad to the inside country since Nov. 2006 ____ <span class="em">Column 11 -16, moving status -General description</span> <br /> </p> <div class="i1">Fill this columns if code 1 or 2 is checked in column 8, and leave it blank for the. This column is left blank for conventional unsettled households.<br />[Picture omitted]</div><span class="em">Column 11 -Has the individual changed city or settlement of residence since October 23, 2006 [last census]?</span><div class="i1">This column documents whether or not individual has changed city or settlement of residence. Leave it blank for those who moved within the same city or settlement.</div><span class="em">Column 12 -16, General description</span><div class="i1">If "yes" is checked in column 11, fill columns 12 -16 but leave them blank for the rest of members. If the individual has moved several times since the last census, fill these columns for the latest move.</div><span class="em">Column 16 -has the individual changed foreign country of residence to Iran? [write the name]</span><div class="i1">[Picture omitted]<br />Fill this column for individuals with codes 1, 2, 3, and 4 in column 14, namely those who had at least one move within the country. Leave this part blank if the individual did not move. <br />Find out whether or not the individual moved from abroad to Iran since the last census. Check yes or no according to the response.</div> Iran 2011: Persons who changed city or settlement of residence and previously lived abroad [discrepancies: none] This variable indicates the country of previous residence for the respondent. 004 Afghanistan 784 United Arab Emirates 990 Asia, other 991 Europe 992 Other 998 Unknown 999 NIU (not in universe) Migration: Global Variables -- PERSON Used internet in the residence at least once in the past 12 months <span class="h3">For persons aged 6 and over</span></p> <p>17. Has she/he used the internet at least once during the last 12 months?</p> <div class="i1">[] 1 Yes, at home<br />[] 2 Yes, at work<br />[] 3 Yes, at educational institutes<br />[] 4 Yes, at coffee net<br />[] 5 Yes, at other<br />[] 6 No</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 17 -Has the individual used internet in his/her residence at least once in the last 12 months?</span><div class="i1">If the individual has personally used the internet, ask where the individual accessed internet, and enter the corresponding code in column 17. If the answer is no write X in box number 6.<br />Code 1, at own residence<br />Code 2, at work<br />Code 3, at school<br />Code 4, coffee net<br />Code 5, other<br />Code 6, not used internet in the last 12 months.<br />- If the individual had access to internet at multiple location, check each relevant box.</div> Iran 2011: Persons age 6+ [discrepancies: type I none; type II 1.1%] This variable indicates whether a person has used internet in the residence at least once in the past 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Used internet at work at least once in the past 12 months <span class="h3">For persons aged 6 and over</span></p> <p>17. Has she/he used the internet at least once during the last 12 months?</p> <div class="i1">[] 1 Yes, at home<br />[] 2 Yes, at work<br />[] 3 Yes, at educational institutes<br />[] 4 Yes, at coffee net<br />[] 5 Yes, at other<br />[] 6 No</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 17 -Has the individual used internet in his/her residence at least once in the last 12 months?</span><div class="i1">If the individual has personally used the internet, ask where the individual accessed internet, and enter the corresponding code in column 17. If the answer is no write X in box number 6.<br />Code 1, at own residence<br />Code 2, at work<br />Code 3, at school<br />Code 4, coffee net<br />Code 5, other<br />Code 6, not used internet in the last 12 months.<br />- If the individual had access to internet at multiple location, check each relevant box.</div> Iran 2011: Persons age 6+ [discrepancies: type I none; type II 1.1%] This variable indicates whether a person used internet at work at least once in the past 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Used internet at school at least once in the past 12 months <span class="h3">For persons aged 6 and over</span></p> <p>17. Has she/he used the internet at least once during the last 12 months?</p> <div class="i1">[] 1 Yes, at home<br />[] 2 Yes, at work<br />[] 3 Yes, at educational institutes<br />[] 4 Yes, at coffee net<br />[] 5 Yes, at other<br />[] 6 No</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 17 -Has the individual used internet in his/her residence at least once in the last 12 months?</span><div class="i1">If the individual has personally used the internet, ask where the individual accessed internet, and enter the corresponding code in column 17. If the answer is no write X in box number 6.<br />Code 1, at own residence<br />Code 2, at work<br />Code 3, at school<br />Code 4, coffee net<br />Code 5, other<br />Code 6, not used internet in the last 12 months.<br />- If the individual had access to internet at multiple location, check each relevant box.</div> Iran 2011: Persons age 6+ [discrepancies: type I none; type II 1.1%] This variable indicates whether a person has used internet at school at least once in the past 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Used internet at coffee shop at least once in the past 12 months <span class="h3">For persons aged 6 and over</span></p> <p>17. Has she/he used the internet at least once during the last 12 months?</p> <div class="i1">[] 1 Yes, at home<br />[] 2 Yes, at work<br />[] 3 Yes, at educational institutes<br />[] 4 Yes, at coffee net<br />[] 5 Yes, at other<br />[] 6 No</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 17 -Has the individual used internet in his/her residence at least once in the last 12 months?</span><div class="i1">If the individual has personally used the internet, ask where the individual accessed internet, and enter the corresponding code in column 17. If the answer is no write X in box number 6.<br />Code 1, at own residence<br />Code 2, at work<br />Code 3, at school<br />Code 4, coffee net<br />Code 5, other<br />Code 6, not used internet in the last 12 months.<br />- If the individual had access to internet at multiple location, check each relevant box.</div> Iran 2011: Persons age 6+ [discrepancies: type I none; type II 1.1%] This variable indicates whether a person has used internet at coffee shop at least once in the past 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Used internet in other places at least once in the past 12 months <span class="h3">For persons aged 6 and over</span></p> <p>17. Has she/he used the internet at least once during the last 12 months?</p> <div class="i1">[] 1 Yes, at home<br />[] 2 Yes, at work<br />[] 3 Yes, at educational institutes<br />[] 4 Yes, at coffee net<br />[] 5 Yes, at other<br />[] 6 No</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 17 -Has the individual used internet in his/her residence at least once in the last 12 months?</span><div class="i1">If the individual has personally used the internet, ask where the individual accessed internet, and enter the corresponding code in column 17. If the answer is no write X in box number 6.<br />Code 1, at own residence<br />Code 2, at work<br />Code 3, at school<br />Code 4, coffee net<br />Code 5, other<br />Code 6, not used internet in the last 12 months.<br />- If the individual had access to internet at multiple location, check each relevant box.</div> Iran 2011: Persons age 6+ [discrepancies: type I none; type II 1.1%] This variable indicates whether a person has used internet in another places at least once in the past 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Internet not used in the past 12 monts <span class="h3">For persons aged 6 and over</span></p> <p>17. Has she/he used the internet at least once during the last 12 months?</p> <div class="i1">[] 1 Yes, at home<br />[] 2 Yes, at work<br />[] 3 Yes, at educational institutes<br />[] 4 Yes, at coffee net<br />[] 5 Yes, at other<br />[] 6 No</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 17 -Has the individual used internet in his/her residence at least once in the last 12 months?</span><div class="i1">If the individual has personally used the internet, ask where the individual accessed internet, and enter the corresponding code in column 17. If the answer is no write X in box number 6.<br />Code 1, at own residence<br />Code 2, at work<br />Code 3, at school<br />Code 4, coffee net<br />Code 5, other<br />Code 6, not used internet in the last 12 months.<br />- If the individual had access to internet at multiple location, check each relevant box.</div> Iran 2011: Persons age 6+ [discrepancies: type I none; type II 1.1%] This variable indicates whether a person has not used the internet in the past 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Currently attending school <span class="h3">For persons aged 6 and over</span></p> <p>18. Is he/she attending school / university? <br /> </p> <div class="i1">[] 1 Yes, in Iran<br />[] 2 Yes, abroad<br />[] 3 No</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 18 -Is the individual attending school currently?</span><div class="i1">[Picture omitted]<br />Check box 1 for students in compulsory or higher education in the country, seminary students, students in adult education program, and those abroad. If the individual is attending school in Iran check box 1, and if abroad check 2. Check box 3 if the individual is not attending any school.<br />- Students on leave are still attending school.<br />- If an individual is accepted in a higher education program and is registered with the institution, he is attending school.<br />- Individuals taking up courses at Iran Technical and Vocational Training Organization, and those taking unofficial courses in computer science, language, painting, sowing, college entrance prep, etc., are not attending school.<br />- Individuals taking comprehensive courses offered by higher education but are not accepted in any official higher education program are not attending school.</div> Iran 2011: Persons age 6+ [discrepancies: none] This variable indicates whether a person is currently attending school. 1 Yes, in Iran 2 Yes, abroad 3 No 8 Unknown 9 NIU (not in universe) Education Variables -- PERSON Literacy status <span class="h3">For persons aged 6 and over</span></p> <p>19. Literacy status</p> <div class="i1">[] 1 Literate<br />[] 2 Illiterate</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 19 -Literacy status</span><div class="i1">[Picture omitted]<br />Fill this column for individual 6-year or older. <br />Code 1, Literate is an individual who can read and write simple Farsi text whether or not he has an official certificate of education. <br />Code 2, Illiterate is an individual who is not literate. An individual who can read but is not able to write is considered illiterate.<br />- Beware not to automatically consider the blind, the deaf, or individuals with impaired speech illiterate.</div> Iran 2011: Persons age 6+ [discrepancies: none] This variable indicates a person's literacy status. 1 Literate 2 Illiterate 8 Unknown 9 NIU (not in universe) Education Variables -- PERSON Field of study (3-digit) <span class="h3">For persons aged 6 and over</span></p> <p>21. Field of Study</p> <div class="i1">For grade, course or educational attainment in question 20 ____</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 20 and 21 -Grade, level, degree, and field of study -General description</span><div class="i1">Fill these two columns if code 1 is checked in column 19, and leave them blank for the rest of individuals.<br />Answers to these questions are based on the International Standard Classification of Education.<br />[Picture omitted]</div><span class="em">Column 21 -Field of study</span> </p> <div class="i1">Field of study is related to the grade, level, or certificate written in column 20:<br />- Write "general" in this column if the level is not divided to tracks e.g. for elementary education.<br />- Write the name of related track/field of study for high school, college-prep, and higher education.<br />- Leave it blank if there is no transcript or certificate available.<br />- Write track/field for theology students if any, otherwise "theology" is enough.<br />[Tables showing how to fill 20 and 21 omitted]<br />Answers in column 20 and 21 are read by software. Make sure to write in legible hand writing, avoid script, leave space between words, write in one row, and avoid punctuation.</div> Iran 2011: Literate persons age 6+ [discrepancies: type I none; type II 0.2%] This variable indicates a person's field of study. 010 General program, basic/extended 140 Teacher education and educational science 142 Education science 143 Training for pre-school teachers 144 Training for teachers at basic levels 145 Training for teachers with subject specialization 146 Training for teachers of vocational subjects 211 Fine arts 212 Music and performing arts 213 Audio-visual techniques and media production 214 Design 215 Craft skills 220 Humanities 221 Religion 222 Foreign languages 223 Mother tongue 225 History and archaeology 226 Philosophy and ethics 311 Psychology 312 Sociology and cultural studies 313 Political science and civics 314 Economics 321 Journalism and reporting 322 Library, information, archive 341 Wholesale and retail sales 342 Marketing and advertising 343 Finance, banking, insurance 344 Accounting and taxation 345 Management and administration 346 Secretarial and office work 380 Law 420 Life Science 421 Biology, biochemistry, and environmental science 441 Physics 442 Chemistry 443 Earth Science 461 Mathematics 462 Statistics 482 Computer use 520 Engineering and engineering trades 521 Mechanics and metal work 522 Electricity and energy 523 Electronics and automation 524 Chemical and process engineering 525 Motor vehicles, ships and aircraft 541 Food processing 542 Textiles, clothes, footwear, leather processing 543 Materials (wood, paper, plastic, glass) processing 544 Mining and extraction 581 Architecture and town planning 582 Building and civil engineering 621 Crop and livestock production 622 Horticulture 623 Forestry 624 Fisheries 640 Veterinary 721 Medicine 723 Nursing and caring 724 Dental studies 725 Medical diagnostic and treatment technology 726 Therapy and rehabilitation 727 Pharmacy 761 Child care and youth services 762 Social work and counseling 811 Hotel, restaurant and catering services 812 Travel, tourism and leisure services 813 Sports 814 Domestic services 815 Hair and beauty services 840 Transport services 851 Environmental protection technology, natural environments and wildlife protection 853 Community sanitation services 861 Protection of persons and property 862 Occupational health and safety 863 Military and defence 998 Unknown 999 NIU (not in universe) Education Variables -- PERSON Place of education <span class="h3">For persons aged 6 and over</span></p> <p><span class="em">For present and temporarily absent from question 8 and those who are presently attending school / university in Iran </span></p> <p>22. Place of education</p> <div class="i1">[] 1 In the same city or village<br />[] 2 In over city, mention the name ____<br />[] 3 In other village</div> <span class="em">Columns 17 -22, Internet access, literacy, educational attainment - General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this section for individuals 6-year or older.</div><span class="em">Column 22 -Place of education</span><div class="i1">[Picture omitted]<br />Fill this column if codes 1 or 2 in column 8 and cod 1 in column 18 are checked, otherwise leave it blank.<br />Code 1, in the same city/settlement<br />Code 2, in another city and mention the name<br />Code 3, in another settlement<br />To fill the columns at the back of the form, bend the sheet on the fold line to make sure information is entered on the correct row for each individual.</div> Iran 2011: Literate residents age 6+ who currently attend school [discrepancies: none] This variable indicates a person's place of education within Iran. 1 In the same city or village 2 In other city 3 In other village 8 Unknown 9 NIU (not in universe) Education Variables -- PERSON Employment in the past 7 days <span class="h3">Activity and marital status - For people aged 10 and over</span></p> <p>23. Activity status during the last 7 days</p> <div class="i1">[] 1 Worked during the last 7 days<br />[] 2 Unpaid work in the household business<br />[] 3 Temporarily absent from work<br />[] 4 Did not work during the last 7 days</div> <span class="em">Column 23 -30, Employment and marital status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for individual 10-year or older.</div><span class="em">Column 23 -Employment status in the past 7 days</span> </p> <div class="i1">[Picture omitted]<br />Employment includes business activities performed either physically or mentally to manufacture merchandise or provide service in return for cash or in-kind income. Employees are divided into paid-employees and own- account workers.<br />Activities of the following individuals are considered employment:<br />- Conscription<br />- Individuals paid to serve in <span class="lang">Basij</span> militia [Organization for Mobilization of Oppressed]<br />- Individuals manufacturing goods or providing services e.g. carpet weaving, sewing, hair-dressing, private tutoring, typing, electronics repair, elderly/baby-sitting, etc. in places of residence to generate income.<br />- Individuals manufacturing durable goods for own or their households use e.g. carpet weaving, Kilim tapestry, sewing, etc.<br />- Individuals who are building or remodeling their own place of residence.<br />- Interns who are directly involved with manufacturing goods or providing services at workplaces whether or not they are paid. <br />? Individuals involved with farming, horticulture, livestock, animal husbandry, fishing, etc. <br />Ask specific questions about the status of employment for each household member over 10-year old. Do not automatically consider housewives and students unemployed.<br />Code 1, worked 7 out of 7 days<br />- Whether or not this period of individual's work activity involved usual employment.<br />Code 2, worked unpaid for family business <br />These individuals are commonly women and adolescents who work in family businesses such as animal farming, carpet weaving, etc. Check code 2 if the individual worked this type of job at least one hour in the past 7 days. <br />In rural area adolescents and women are involved with activities such as farming. If a household member helped with such activities at least one hour in the past 7 days, consider that person employed. <br />Code 3, employed but temporarily absent from work in the past 7 days<br />Code 3 is applied if the absence from work is due to vacation, travel, seasonal nature of the job, shift-work, etc. but the worker is definitely returns to the same job.<br />[] If individuals are paid workers then should have contract to guarantee their return to work. The absences is authorized based on the conditions and regulations of employment and they are usually paid partially or in full during their absence. <br />[] If individuals are own- account workers, the business should have continuity in order for the individual to return to activity again. <br />Examples: <br />- Own-account farmers who have not worked in the past 7 days due to seasonal nature of the job.<br />- Individuals who have not gone to work in the past 7 days due to shift-work or alternate work schedule.<br />- Individuals who were absent from work in the past 7 days due to sickness, travel, vacation, holidays, etc.<br />- Individuals who have not gone to work due to temporary organizational changes, failure of equipment, lack of customer or work order. <br />- Individuals on administrative leave or suspension but still have valid contracts.<br />Check code 2 for unpaid family workers if have worked at least one hour in the past 7 days. Do not consider the individual temporarily absent if he has not worked at all in the past 7 days, therefore do not check 3 but check code 4.<br />Code 4, has not worked in the past 7 days<br />For individuals who have not worked in the past 7 days, and are not unpaid family worker neither temporarily absent, check code 4. The following activities are not considered employment:<br />- Unpaid activities at home done for the household, e.g. cooking, housekeeping, raising children, etc., namely activities commonly done by women. <br />? Volunteer work in charities and <span class="lang">Basij</span>.<br />- Minor repairs of residences such changing faucet, window frame and glass, and repair of appliances.<br />-Investment in stock market or businesses without participation in operation or management.<br />If codes 1 - 3 are checked columns 24 - 25 should be left blank and columns 26 - 29 should be completed.</div> Iran 2011: Persons age 10+ [discrepancies: none] This variable indicates a person's employment status in the past 7 days. 1 Worked 2 Unpaid workers in household business 3 Temporarily absent from work 4 Did not work 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Job search in the past 30 days <span class="h3">Activity and marital status - For people aged 10 and over</span></p> <p><span class="em"> For those who did not work during the last 7 days </span> <br />24. Status of seeking work during the last 30 days</p> <div class="i1">[] 1 Seeking work<br />Not seeking work due to:</div><div class="i2">[] 2 Starting work in future<br />[] 3 Has not been working, waiting to return to previous work<br />[] 4 Education<br />[] 5 Homemaker<br />[] 6 Income recipient<br />[] 7 Other</div> <span class="em">Column 23 -30, Employment and marital status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for individual 10-year or older.</div><span class="em">Column 24-Status of job search in the past 30 days </span><div class="i1">[Picture omitted]<br />Fill column 24 as below if code 4 is checked in column 23:<br />Code 1, has been seeking employment in the past 30 days<br />Seeking employment includes registering with or seeking job from recruitment agencies, asking friends, contacting employer, reading employment column in paper, etc. Check code 1 for these individuals.<br />If the individual has not sought employment, ask about the main reason and check one of the codes 2 - 7.<br />Code 2, set date of employment in the future<br />Code 3, awaiting return to the previous job<br />Code 4, education<br />For individuals who are currently enrolled in school either in Iran or abroad.<br />Code 5, homemaking<br />Code 6, relying on assets and revenues<br />For individuals who have incomes from retirement, real estate, stock market, term deposit, etc. without being participation with actual work.<br />Code 7, Others<br />For individuals preparing for college-entrance exam, elderly, etc.</div> Iran 2011: Persons age 10+ who did not work in the past 7 days [discrepancies: none] This variable indicates whether a person searched for work in the past 30 days, and the reason for not seeking work during this time (if applicable). 1 Seeking work 2 Not seeking work due to employment start date in future 3 Awaiting return to previous job 4 Not seeking work due to education 5 Not seeking work due to homemaking 6 Relying on assets and revenue (not seeking work) 7 Others 9 NIU (not in universe) Work Variables -- PERSON Employment readiness <span class="h3">Activity and marital status - For people aged 10 and over</span></p> <p><span class="em"> For those who are seeking work or has not been seeking </span> <br />25. Status of availability to work</p> <div class="i1">[] 1 Available to work<br />[] 2 Not available to work due to education<br />[] 3 Homemaker<br />[] 4 Income recipient<br />[] 5 Other</div> <span class="em">Column 23 -30, Employment and marital status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for individual 10-year or older.</div><span class="em">Column 25, employment readiness</span><div class="i1">Fill column 25 as below if code 1, 2, or 3 is checked in column 24:<br />[Picture omitted] <br />Code 1, available for employment<br />Check code 1 for an individual who is ready for work for a period of 15 days spanning the past 7 days and the next 7 days. In other words if the individual had found job in the past 7 days he would have remained employment ready for the coming 7 days.<br />Not ready for employment due to:<br />Code 2, education<br />Code 3, homemaking<br />Code 4, relying on assets and revenues<br />Code 5, other</div> Iran 2011: Persons age 10+ who are seeking work, not seeking work due to future employment or awaiting return to previous job [discrepancies: none] This variable indicates whether a person is available for employment. 1 Available for employment 2 Not avilable for employment due to education 3 Not avilable for employment due to homemaking 4 Not avilable for employment due to relying on assets and revenue 5 Not avilable for employment due to other 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Industry (3-digit) <span class="h3">Activity and marital status - For people aged 10 and over</span></p> <p><span class="em">Questions 26-28 for those who are working, doing unpaid work in the household business, or are temporarily absent from work </span></p> <p>26. Main activity of the work place (It should be avoided to write general titles such as office, company, factory, supermarket, shop ...) _____ <span class="em">Column 23 -30, Employment and marital status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for individual 10-year or older.</div><span class="em">Columns 26 -29, main activity of the workplace, job, job status, workplace</span><div class="i1">[Picture omitted]<br />Fill these columns if codes 1, 2, or 3 are checked in column 23, and leave it blank for the rest.<br />- For individuals who were temporarily absent from work (column 23 code 3) fill this column according to their usual job.<br />- When filling these columns for an individual who worked a job other than his usual one in the past 7 days [column 23 code 1] consider the most recent job carried.<br />- When filling these columns for individuals who work multiple jobs, consider the main job carried. If the respondent cannot specify the answer, the job that individual worked the highest number of hours carrying in the past 7 days is the main job. If the individual spends equal number of hours at each job, then the main job is the one that the individual has stayed with the longest.</div><span class="em">Column 26, main activity of the workplace</span><div class="i1">[Picture omitted]<br />All business activities are coded based on the International Standard Industrial Classification of All Economic activities (ISIC), therefore it is necessary to follow the tables in pages 113 - 115 of this manual and the remarks below:<br />- Write the main activity of the workplace to accurately convey the activity. Avoid just writing non-specific titles such as store, shop, office, company, factory, etc. <br />- If the individual does not have a fixed workplace in case of construction workers, cab drivers, peddlers, etc. write the main activity instead. <br />- Writing titles such as wholesale, import, and export are necessary.<br />- For individuals who work for ministries, government organizations and agencies, and Islamic revolution organizations, if the name of workplace does not convey the type of activity, add the type of activity as well.<br />[Picture omitted]<br />- Write the specific activity of banks and financial institution, rather than just bank.<br />[Picture omitted]<br />- Make sure to write either manufacturing or repair, whichever applies, in addition to the main activity of the workplace. If these activities are combined at a workplace write both. <br />[Picture omitted]<br />- For mining and also manufacturing goods, specify the type of mineral or goods.<br />[Picture omitted]<br />- Specify the type of vehicle for drivers and auto service shops.<br />- Specify passenger vs freight transportation and intercity service vs. intracity transit in addition to the route such as ground, air, sea, and rail.<br />[Picture omitted]<br />- If telecommunication is the main activity of workplace specify wired, wireless, or via satellite.<br />[Picture omitted]<br />For natural or legal person who is hired by private sector but works in a government office, e.g. a janitor, the main activity of workplace is the one that individual has contract with.</div> Iran 2011: Persons age 10+ who worked, were unpaid workers, or temporarily absent from work in the past 7 days [discrepancies: none] This variable indicates the industry (3-digit) where the person works. 011 Growing of non-perennial crops 012 Growing of perennial crops 013 Plant propagation 014 Animal production 016 Support activities to agriculture and post-harvest crop activities 021 Silviculture and other forestry activities 022 Logging and gathering of non-wood products 024 Support service to forestry 031 Fishing 032 Aquaculture 051 Mining of hard coal or lignite 061 Extraction of crude petroleum 062 Extraction of natural gas 071 Mining of iron ores 072 Mining of non-ferrous metal ores 081 Quarrying of stone, sand and clay 089 Other mining and quarrying 091 Support activities for petroleum, natural gas extraction, and other mining and quarrying 101 Processing and preserving of meat, fish, crustaceans, and molluscs 103 Processing and preserving of fruit and vegetables 104 Manufacture of vegetable and animal oils and fats 105 Manufacture of dairy products 106 Manufacture of grain mill products, starches and starch products 107 Manufacture of other food products 108 Manufacture of prepared animal feeds 110 Manufacture of beverages 120 Manufacture of tobacco products 131 Spinning, weaving and finishing of textiles 139 Manufacture of other textiles 141 Manufacture of wearing apparel, except fur apparel 143 Manufacture of knitted and crocheted apparel 151 Tanning and dressing of leather; manufacture of luggage, handbags, saddlery and harness; dressing and dyeing of fur 152 Manufacture of footwear 161 Sawmilling and planing of wood 162 Manufacture of products of wood, cork, straw and plaiting materials 170 Manufacture of paper and paper products 181 Printing and service activities related to printing 191 Manufacture of coke oven products 192 Manufacture of refined petroleum products 201 Manufacture of basic chemicals, fertilizers and nitrogen compounds, plastics and synthetic rubber in primary forms 202 Manufacture of other chemical products 203 Manufacture of man-made fibres 210 Manufacture of pharmaceuticals, medicinal chemical and botanical products 221 Manufacture of rubber products 222 Manufacture of plastics products 231 Manufacture of glass and glass products 239 Manufacture of non-metallic mineral products n.e.c. 241 Manufacture of basic iron and steel 242 Manufacture of basic precious and other non-ferrous metals 243 Casting of metals 251 Manufacture of structural metal products, tanks, reservoirs and steam generators 252 Manufacture of weapons and ammunition 259 Manufacture of other fabricated metal products; metalworking service activities 261 Manufacture of electronic components and boards 262 Manufacture of computers and peripheral equipment 263 Manufacture of communication equipment 264 Manufacture of consumer electronics 265 Manufacture of measuring, testing, navigating and control equipment; watches and clocks 266 Manufacture of irradiation, electromedical and electrotherapeutic equipment 271 Manufacture of electric motors, generators, transformers and electricity distribution and control apparatus 272 Manufacture of batteries and accumulators 273 Manufacture of wiring and wiring devices 274 Manufacture of electric lighting equipment 275 Manufacture of domestic appliances 279 Manufacture of other electrical equipment 281 Manufacture of general-purpose machinery 282 Manufacture of special-purpose machinery 291 Manufacture of motor vehicles 292 Manufacture of bodies (coachwork) for motor vehicles; manufacture of trailers and semi-trailers 293 Manufacture of parts and accessories for motor vehicles 301 Building of ships and boats 302 Manufacture of railway locomotives and rolling stock 303 Manufacture of air and spacecraft and related machinery 309 Other manufacture of transport equipment 310 Manufacture of furniture 321 Manufacture of jewellery, bijouterie and related articles 324 Manufacture of games and toys 325 Manufacture of medical and dental instruments and supplies 329 Other manufacturing 331 Repair of fabricated metal products, machinery and equipment 339 Manufacturing, not elsewhere classified 340 Manufacturing, category not specified 351 Electric power generation, transmission and distribution 352 Manufacture of gas; distribution of gaseous fuels through mains 353 Steam and air conditioning supply 360 Water collection, treatment and supply 370 Sewerage 381 Waste collection, waste treatment and disposal 383 Materials recovery 410 Construction of buildings 421 Construction of roads and railways 422 Construction of utility projects 429 Construction of other civil engineering projects 431 Demolition and site preparation 432 Electrical, plumbing and other construction installation activities 433 Building completion and finishing 439 Other specialized construction activities 451 Sale of motor vehicles 452 Maintenance and repair of motor vehicles 453 Sale of motor vehicle parts and accessories 454 Sale, maintenance and repair of motorcycles and related parts and accessories 461 Wholesale on a fee or contract basis 462 Wholesale of agricultural raw materials and live animals 463 Wholesale of food, beverages and tobacco 464 Wholesale of household goods 465 Wholesale of machinery, equipment and supplies 466 Other specialized wholesale 469 Non-specialized wholesale trade 471 Retail sale in non-specialized stores 472 Retail sale of food, beverages and tobacco in specialized stores 473 Retail sale of automotive fuel in specialized stores 474 Retail sale of information and communications equipment in specialized stores 475 Retail sale of other household equipment in specialized stores 476 Retail sale of cultural and recreation goods in specialized stores 477 Retail sale of other goods in specialized stores 478 Retail sale via stalls and markets 479 Retail trade not in stores, stalls or markets 491 Transport via railways 492 Other land transport 493 Transport via pipeline 501 Sea and coastal water transport 502 Inland water transport 511 Passenger and freight air transport 521 Warehousing and storage 522 Support activities for transportation 531 Postal activities 532 Courier activities 551 Short term accommodation activities 552 Other accommodation 561 Restaurants and mobile food service activities 562 Event catering and other food service activities 563 Beverage serving activities 581 Publishing of books, periodicals and other publishing activities 591 Motion picture, video and television programme activities 602 Television programming and broadcasting activities 610 Telecommunications 620 Computer programming, consultancy and related activities 639 Information and communication, not elsewhere classified 641 Monetary intermediation 643 Trusts, funds and similar financial entities 649 Other financial service activities, except insurance and pension funding activities 651 Insurance 661 Activities auxiliary to financial service activities, except insurance and pension funding 662 Activities auxiliary to insurance and pension funding 681 Real estate activities 691 Legal activities 692 Accounting, bookkeeping and auditing activities; tax consultancy 701 Activities of head offices 702 Management consultancy activities 711 Architectural and engineering activities and related technical consultancy 712 Technical testing and analysis 721 Research and experimental development on natural sciences and engineering 722 Research and experimental development on social sciences and humanities 731 Advertising 741 Specialized design activities 742 Photographic activities 749 Other professional, scientific and technical activities 750 Veterinary activities 771 Renting and leasing of motor vehicles, personal and household goods, or other machinery, equipment, and tangible goods 780 Employment and human resources activities 791 Travel agency and tour operator activities, other reservation service and related activities 800 Private security, security systems, and investigation activities 812 Cleaning activities 813 Landscape care and maintenance service activities 821 Office administrative and support activities 822 Activities of call centres 823 Organization of conventions and trade shows 829 Other business support service activities 841 Administration of the State and the economic and social policy of the community 842 Provision of services to the community as a whole 843 Compulsory social security activities 851 Pre-primary and primary education 852 Secondary education 853 Higher education 854 Other education and educational support activities 861 Hospital activities 862 Medical and dental practice activities 869 Other human health activities 871 Residential nursing care facilities 872 Residential care activities for mental retardation, mental health, substance abuse, elderly, and disabled 879 Other residential care activities 889 Other social work activities without accommodation 900 Creative, arts and entertainment activities 910 Libraries, archives, museums and other cultural activities 931 Sports activities 932 Other amusement and recreation activities 941 Activities of business, employers and professional membership organizations 942 Activities of trade unions 949 Activities of other membership organizations 951 Repair of computers and communication equipment 952 Repair of personal and household goods 960 Other personal service activities 970 Activities of households as employers of domestic personnel 990 Activities of extraterritorial organizations and bodies 998 Unknown 999 NIU (not in universe) Work: Industry Variables -- PERSON Occupation (3-digit) <span class="h3">Activity and marital status - For people aged 10 and over</span></p> <p><span class="em">Questions 26-28 for those who are working, doing unpaid work in the household business, or are temporarily absent from work </span></p> <p>27. Job (It should be avoided to write general titles such as clerk, farmer, and self-employment) ____ <span class="em">Column 23 -30, Employment and marital status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for individual 10-year or older.</div><span class="em">Columns 26 -29, main activity of the workplace, job, job status, workplace</span><div class="i1">[Picture omitted]<br />Fill these columns if codes 1, 2, or 3 are checked in column 23, and leave it blank for the rest.<br />- For individuals who were temporarily absent from work (column 23 code 3) fill this column according to their usual job.<br />- When filling these columns for an individual who worked a job other than his usual one in the past 7 days [column 23 code 1] consider the most recent job carried.<br />- When filling these columns for individuals who work multiple jobs, consider the main job carried. If the respondent cannot specify the answer, the job that individual worked the highest number of hours carrying in the past 7 days is the main job. If the individual spends equal number of hours at each job, then the main job is the one that the individual has stayed with the longest.</div><span class="em">Column 27, occupation</span><div class="i1">Occupation, is an activity, based on definitions and examples, which is carried by the individual in the past 7 days. Occupation of temporarily absent individuals is the one conducted by such individual when is employed.<br />[Picture omitted]<br />All occupations are named based on the International Standard Classification of Occupations [ISCO].<br />- In most workplaces there are different types of occupation e.g. in an elementary school occupation titles include director, principal, teacher, janitor, etc. Make sure to ask specific question about the type of occupation an individual carries in a workplace.<br />- Make a distinction between the field of study and occupation e.g. an agriculture engineer may work in the position of manager of accounting. In this case the latter is the occupation. <br />- Make sure to find out the main occupation if the individual is a farming because some farmers work in more than one area of agriculture. <br />- Have the following definitions in mind when documenting farming occupations:<br />[1] Field crop and vegetable growers are farmers who plant, grow, and harvest one or more annual plants such as wheat, oat, rice, sugar beet, vegetable, etc. <br />[2] Tree and shrub crop growers are perennial plant farmers who grow apples, pears, grapes, oranges, tea, etc.<br />[3] Gardeners, horticultural and nursery growers.<br />- Specify whether or not the industry is mechanized and write the term "operator" when necessary.<br />- If the occupation requires different skills, document the highest level of responsibility the individual carries e.g. for a typist who does archiving in the same workplace, document the latter.<br />- If the individual carries responsibilities from manufacturing to distribution of goods and does not single out one as the main job, document the job related to manufacturing. For example if the pastry chef sells the confectionary at the counter write pastry chef.<br />- Document the rank for serviceperson and police officers, except for privates doing conscription.<br />- For privates who are spending their conscription in military or police force write conscription, otherwise write the job they are performing in the agency.<br />- For paid individual who is serving in<span class="lang"> Basij </span>militia write serviceman.<br />[Picture omitted]<br />- Avoid general titles such as employee, technician, laborer, physician, engineer, farmer, teacher, specialist, own- account worker, repairman, and goldsmith because each comprise several titles with its individual code. See tables on pages 118 - 122.<br />[Table omitted]<br />Quite often there is a relation between the occupation and main activity of the workplace. See examples in table on Page 120.<br />- Avoid general titles for agricultural and livestock farmers. There is almost always a relation between the occupation and the main activity of workplace, therefore, when documenting the latter, write the type of economic activity and the product. Document the traditional vs. industrial for farming activities. See table on page 121.<br />- See examples of occupations which are not related to the main activity of the workplace in table on 122.<br />Answers in column 26 and 27 are read by software.</div> Iran 2011: Persons age 10+ who worked, were unpaid workers or temporarily absent from work in the past 7 days [discrepancies: none] This variable indicates the person's occupation (3-digit). 011 Armed forces and police officers 110 Legislators and senior officials 114 Managers and administrators of specialized organizations 141 School supervisors and principals 142 Transport and communications service supervisors 211 Physicists, chemists and related professionals 212 Mathematicians, statisticians and related professionals 213 Computing professionals 214 Architects, engineers and related professionals 221 Life science professionals 222 Health professionals (except nursing) 223 Nursing and midwifery professionals 231 College, university and higher education teaching professionals 232 Secondary vocational, lower and upper secondary education teaching 233 Primary and Pre-primary education teaching professionals 234 Special education teaching professionals (teach physically or me 235 Other teaching professionals 241 Business professionals 242 Legal professionals 243 Archivists, librarians and related information professionals 244 Social science and related professionals 245 Writers and creative or performing artists 246 Religious professionals 249 Other professionals, not elsewhere classified 311 Physical and engineering science technicians 312 Computer associate professionals 313 Optical and electronic equipment operators 314 Ship and aircraft controllers and technicians 315 Safety and quality inspectors 321 Life science technicians and related associate professionals 322 Modern health associate professionals (except nursing) 323 Nursing and midwifery associate professionals 331 Primary, pre-primary, and special education teaching associate professionals 334 Other teaching associate professionals 341 Finance and sales associate professionals 342 Business services agents and trade brokers 343 Administrative associate professionals 344 Customs, tax and related government associate professionals 346 Social work associate professionals 347 Artistic, entertainment and sports associate professionals 348 Religious associate professionals 411 Secretaries and keyboard-operating clerks 412 Numerical clerks 413 Material-recording and transport clerks 414 Library, mail and related clerks 419 Other office clerks 421 Cashiers, tellers and related clerks 422 Client information clerks 511 Travel attendants and related workers 512 Housekeeping and restaurant services workers 513 Personal care and related workers 514 Other personal services workers 516 Protective services workers 522 Shop salespersons and demonstrators 523 Stall and market salespersons 611 Market gardeners and crop growers 612 Market-oriented animal producers and related workers 614 Forestry and related workers 615 Fishery workers, hunters and trappers 711 Miners, shotfirers, stone cutters and carvers 712 Building frame and related trades workers 713 Building finishers and related trades workers 714 Painters, building structure cleaners and related trades workers 721 Metal moulders, welders, sheet-metal workers, structural-metal preparers and realted trades workers 722 Blacksmiths, tool-makers and related trades workers 723 Machinery mechanics and fitters 724 Electrical and electronic equipment mechanics and fitters 731 Precision workers in metal and related materials 732 Potters, glass-makers and related trades workers 733 Handicraft workers in wood, textile, leather and related materials 734 Printing and related trades workers 741 Food processing and related trades workers 742 Wood treaters, cabinet-makers and related trades workers 743 Textile, garment and related trades workers 744 Pelt, leather and shoemaking trades workers 745 Electronics mechanics, fitters and servicers 750 Supervisors of jewelry, glass blowing, ceramics and the like 811 Mining and mineral-processing-plant operators 812 Metal-processing-plant operators 813 Glass, ceramics and related plant operators 814 Wood-processing and papermaking-plant operators 815 Chemical-processing-plant operators 816 Power-production and related plant operators 821 Metal- and mineral-products machine operators 822 Chemical-products machine operators 823 Rubber- and plastic-products machine operators 825 Printing-, binding- and paper-products machine operators 826 Textile-, fur- and leather-products machine operators 827 Food and related products machine operators 828 Assemblers 829 Other machine operators and assemblers 831 Locomotive-engine drivers and related workers 832 Motor-vehicle drivers 833 Agricultural and other mobile-plant operators 834 Ship deck crews and related workers 899 Plant and machine operators and assemblers, not elsewhere classified 911 Street vendors and related workers 913 Domestic and related helpers, cleaners and launderers 914 Building caretakers, window and related cleaners 915 Messengers, porters, doorkeepers and related workers 916 Garbage collectors and related labourers 921 Agricultural, fishery and related labourers 931 Mining and construction labourers 932 Manufacturing labourers 933 Transport labourers and freight handlers 998 Unknown 999 NIU (not in universe) Work: Occupation Variables -- PERSON Class of worker <span class="h3">Activity and marital status - For people aged 10 and over</span></p> <p><span class="em">Questions 26-28 for those who are working, doing unpaid work in the household business, or are temporarily absent from work </span></p> <p>28. Job status</p> <div class="i1">[] 1 Employer<br />[] 2 Own-account, wage, and salaried worker<br />[] 3 Public sector<br />[] 4 Private sector<br />[] 5 Cooperative sector<br />[] 6 Unpaid family worker</div> <span class="em">Column 23 -30, Employment and marital status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for individual 10-year or older.</div><span class="em">Columns 26 -29, main activity of the workplace, job, job status, workplace</span><div class="i1">[Picture omitted]<br />Fill these columns if codes 1, 2, or 3 are checked in column 23, and leave it blank for the rest.<br />- For individuals who were temporarily absent from work (column 23 code 3) fill this column according to their usual job.<br />- When filling these columns for an individual who worked a job other than his usual one in the past 7 days [column 23 code 1] consider the most recent job carried.<br />- When filling these columns for individuals who work multiple jobs, consider the main job carried. If the respondent cannot specify the answer, the job that individual worked the highest number of hours carrying in the past 7 days is the main job. If the individual spends equal number of hours at each job, then the main job is the one that the individual has stayed with the longest.</div><span class="em">Column 28, status in employment</span><div class="i1">[Picture omitted]<br />Code 1, employer<br />An individual who hires at least one employee e.g.:<br />- Owner of a sawmill who has hired a few laborers to run the mill.<br />- Owner of grocery with one hired laborer working for him<br />- A mason who has hired a few construction workers to carry the job he has contracted.<br />Note:<br />- Individuals who run their occupational activities using only unpaid family workers are not employers.<br />Code 2, own- account worker<br />An individual who hires no employee, and himself is not a paid worker either:<br />- A grocer who runs his own grocery store individually or with a partner.<br />- Individuals who run their occupational activities using only unpaid family workers.<br />- Farmers who cooperate with each other during harvest are considered own- account worker if they do not hire any laborer.<br />Code 3, public sector employee<br />Individuals who work for ministries, institutions, agencies, government offices and agencies and Islamic revolution organizations, public banks, or city, and are paid in cash or in-kind e.g. employees of Ministry of Education or National Bank of Iran or police officers.<br />- Public sector employees are hired, on contract, temp, or day laborer.<br />- Employees of manufacturing and business activities under public sector management. <br />- Privates in conscription.<br />- Individuals hired to work under private sector contractors are not public sector employees even if the contractor works for public sector.<br />Code 4, private sector employee <br />An individual who works in private sector in return for cash or in kind, whether the employee is an individual or institution, e.g. the CEO of a private sector construction company, private nursery teacher, private hospital accountant, cashier of private sector bank, etc. <br />Note: <br />- An individual hired and paid by private sector whose workplace is in public sector is private sector employee.<br />- Unpaid internes who work in public or private sector get codes 3 or 4 respectively.<br />Code 5, co- operative sector employee <br />Co- operative companies are created and registered according to co- operative law of trade and comprise different types such as consumer co- ops, housing co- ops, etc. <br />Code 6, unpaid family worker <br />An individual who works unpaid for another member of the same household with whom he has family ties e.g. a son who helps his father in livestock farm without pay.</div> Iran 2011: Persons age 10+ who worked, were unpaid workers or temporarily absent from work in the past 7 days [discrepancies: none] This variable indicates the class of worker for an employed person. 1 Employer 2 Own-account worker 3 Paid employee in the public sector 4 Paid employee in the private sector 5 Paid employee in the cooperative sector 6 Unpaid family worker 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Place of work <span class="h3">Activity and marital status - For people aged 10 and over</span></p> <p>29. (For those present or temporarily absent from question 8) <br />Work Place</p> <div class="i1">[] 1 In the same city or village<br />[] 2 In other city, mention the name _____<br />[] 3 In other village</div> <span class="em">Column 23 -30, Employment and marital status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for individual 10-year or older.</div><span class="em">Columns 26 -29, main activity of the workplace, job, job status, workplace</span><div class="i1">[Picture omitted]<br />Fill these columns if codes 1, 2, or 3 are checked in column 23, and leave it blank for the rest.<br />- For individuals who were temporarily absent from work (column 23 code 3) fill this column according to their usual job.<br />- When filling these columns for an individual who worked a job other than his usual one in the past 7 days [column 23 code 1] consider the most recent job carried.<br />- When filling these columns for individuals who work multiple jobs, consider the main job carried. If the respondent cannot specify the answer, the job that individual worked the highest number of hours carrying in the past 7 days is the main job. If the individual spends equal number of hours at each job, then the main job is the one that the individual has stayed with the longest.</div><span class="em">Column 29, place of work </span> </p> <div class="i1">Fill this column if code 1 or 2 is checked in column 8 and one of the boxes (1 - 3) in column 23 is checked as well, but leave it blank for the rest. <br />[Picture omitted]<br />Code 1, in the same city or settlement<br />Check code 1 if the individual works in the city or settlement under enumeration. <br />- Check code 1 for individuals who do not have a specific workplace due to the nature of their job e.g. intercity bus drivers, peddlers, etc.<br />Code 2, in another city [include name]<br />Code 3, in another settlement [include name]</div> Iran 2011: Residents age 10+ who worked, were unpaid workers or temporarily absent from work in the past 7 days [discrepancies: none] This variable indicates the place of a person's work in Iran. 1 Same city or settlement 2 Another city 3 Another settlement 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Marital status <span class="h3">Activity and marital status - For people aged 10 and over</span></p> <p>30. Marital status</p> <div class="i1">[] 1 Married<br />[] 2 Widowed<br />[] 3 Divorced<br />[] 4 Never married</div> <span class="em">Column 23 -30, Employment and marital status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for individual 10-year or older.</div><span class="em">Column 30, marital status</span><div class="i1">[Picture omitted]<br />Fill this column for household members 10-year or older and leave it blank for the rest.<br />Code 1, married<br />Check code 1 for married individuals, whether permanent or temporary in intention, even if the couple have not started living together yet. Engaged individuals are not considered married. <br />Code 2, widowed <br />If the individual was widowed before but remarried by the time of enumeration do not consider him widowed. <br />Code 3, divorced<br />If the individual was divorced before but remarried by the time of enumeration do not consider him divorced.<br />Code 4, never married<br />- Document marital status of individuals who married more than once based on their status at the time of enumeration e.g. if an individual got divorced after the first marriage and became widowed in the 2nd marriage and has not remarried by the time of enumeration, check code 2.<br />- If a man is polygamist, he and all of his wives are considered married. Check box 1 for each.</div> Iran 2011: Persons age 10+ [discrepancies: none] This variable indicates a person's marital status. 1 Married 2 Widowed 3 Divorced 4 Never married 8 Unknown 9 NIU (not in universe) Demographic Variables -- PERSON Ever had a live birth <span class="h3">Fertility status - for women aged 10 and over who have been married, widowed, or divorced from question 30</span></p> <p>31. Has she ever given a live birth?</p> <div class="i1">[] Yes<br />[] No</div> <span class="em">Columns 31 -36, reproductive status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this columns if codes 1, 2, or 3 is checked in column 30 and leave them blank for the rest.<br />- Fill these column for females only.</div><span class="em">Column 31, has the individual ever given birth to a live newborn?</span> </p> <div class="i1">A live newborn shows at least one sign of life after birth [crying, moving limbs, breathing, etc.] even if dies immediately. Ask this question for every female who married at least once to make sure if she had a live birth by the time of enumeration.</div> Iran 2011: Ever-married females age 10+ [discrepancies: type I trace; type II none] This variable indicates whether a woman has ever had a live birth. 1 Yes 2 No 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of live female births <span class="h3">Fertility status - for women aged 10 and over who have been married, widowed, or divorced from question 30</span></p> <p>[Questions 32-36 for those who answered yes to question 31]</p> <p>32. Number of children ever born (in total)</p> <div class="i1">_ _ Boys<br />_ _ Girls</div> <span class="em">Columns 31 -36, reproductive status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this columns if codes 1, 2, or 3 is checked in column 30 and leave them blank for the rest.<br />- Fill these column for females only.</div><span class="em">Columns 32 and 33, number of live newborns</span> </p> <div class="i1">Fill these columns if "yes" is checked in column 31 and leave blank for the rest.</div><span class="em">Column 32, total number of live newborns</span> </p> <div class="i1">[Picture omitted]<br />Enter the total number of live newborns delivered till the time of enumeration for each female married at least once.<br />These children may<br />- not be alive at the time of enumeration<br />- live with the household under enumeration or another.<br />- from one or more marriages<br />Specify the number of live newborns based on gender as two-digit number e.g. if a woman has one son from previous marriage and two daughters from current marriage write "01" and "02" in respective rows. If all of the live newborns are the same gender, fill the row of other gender with "00".</div> Iran 2011: Ever-married females age 10+ who have given birth [discrepancies: none] This variable indicates the number of live female births the woman ever had. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of live male births <span class="h3">Fertility status - for women aged 10 and over who have been married, widowed, or divorced from question 30</span></p> <p>[Questions 32-36 for those who answered yes to question 31]</p> <p>32. Number of children ever born (in total)</p> <div class="i1">_ _ Boys<br />_ _ Girls</div> <span class="em">Columns 31 -36, reproductive status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this columns if codes 1, 2, or 3 is checked in column 30 and leave them blank for the rest.<br />- Fill these column for females only.</div><span class="em">Columns 32 and 33, number of live newborns</span> </p> <div class="i1">Fill these columns if "yes" is checked in column 31 and leave blank for the rest.</div><span class="em">Column 32, total number of live newborns</span> </p> <div class="i1">[Picture omitted]<br />Enter the total number of live newborns delivered till the time of enumeration for each female married at least once.<br />These children may<br />- not be alive at the time of enumeration<br />- live with the household under enumeration or another.<br />- from one or more marriages<br />Specify the number of live newborns based on gender as two-digit number e.g. if a woman has one son from previous marriage and two daughters from current marriage write "01" and "02" in respective rows. If all of the live newborns are the same gender, fill the row of other gender with "00".</div> Iran 2011: Ever-married females age 10+ who have given birth [discrepancies: none] This variable indicates the number of live male births the woman ever had. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female children surviving <span class="h3">Fertility status - for women aged 10 and over who have been married, widowed, or divorced from question 30</span></p> <p>[Questions 32-36 for those who answered yes to question 31]</p> <p>33. Number of children born, still living</p> <div class="i1">_ _ Boys<br />_ _ Girls</div> <span class="em">Columns 31 -36, reproductive status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this columns if codes 1, 2, or 3 is checked in column 30 and leave them blank for the rest.<br />- Fill these column for females only.</div><span class="em">Columns 32 and 33, number of live newborns</span> </p> <div class="i1">Fill these columns if "yes" is checked in column 31 and leave blank for the rest.</div><span class="em">Column 33, living offspring</span> </p> <div class="i1">Living offspring of a woman married at least once are, by definition, children who are alive by the time of enumeration. <br />These children may<br />- live with the household under enumeration or another.<br />- from one or more marriages<br />Specify the number of living offspring based on gender as a two-digit number. <br />- for example if no male offspring is living write "00"<br />- for women who have given birth to only girls ("00" is in column 32), leave column 33 blank where is says "boys".<br />- The number in column 33 should be equal or less than the corresponding number in column 32.</div> Iran 2011: Ever-married females age 10+ who have given birth to female children [disrepancies: none] This variable indicates the number of female children the woman ever had that are still living. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male children surviving <span class="h3">Fertility status - for women aged 10 and over who have been married, widowed, or divorced from question 30</span></p> <p>[Questions 32-36 for those who answered yes to question 31]</p> <p>33. Number of children born, still living</p> <div class="i1">_ _ Boys<br />_ _ Girls</div> <span class="em">Columns 31 -36, reproductive status -General description</span> </p> <div class="i1">[Picture omitted]<br />Fill this columns if codes 1, 2, or 3 is checked in column 30 and leave them blank for the rest.<br />- Fill these column for females only.</div><span class="em">Columns 32 and 33, number of live newborns</span> </p> <div class="i1">Fill these columns if "yes" is checked in column 31 and leave blank for the rest.</div><span class="em">Column 33, living offspring</span> </p> <div class="i1">Living offspring of a woman married at least once are, by definition, children who are alive by the time of enumeration. <br />These children may<br />- live with the household under enumeration or another.<br />- from one or more marriages<br />Specify the number of living offspring based on gender as a two-digit number. <br />- for example if no male offspring is living write "00"<br />- for women who have given birth to only girls ("00" is in column 32), leave column 33 blank where is says "boys".<br />- The number in column 33 should be equal or less than the corresponding number in column 32.</div> Iran 2011: Ever-married females age 10+ who have given birth to male children [disrepancies: none] This variable indicates the number of male children the woman ever had that are still living. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Live births in the past 365 days <span class="em">Questions 34-36 for women aged 10 to 54</span></p> <p>34. Has she given a live birth during the last 365 days?</p> <div class="i1">[] Yes<br />[] No</div> <span class="em">Columns 32 and 33, number of live newborns</span> </p> <div class="i1">Fill these columns if "yes" is checked in column 31 and leave blank for the rest.</div><span class="em">Column 34 -36, General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for females 10 - 54 year-old married at least once [codes 1, 2, 3 in column 30] and gave birth to at least one live newborn ["yes" in column 31], and leave it blank for the rest.</div><span class="em">Column 34, has the individual given birth to a live newborn in the past 365 days?</span> </p> <div class="i1">Check yes or no in this column. <br />" If a woman gave birth to a live newborn during the month of October 2005, make sure to check "yes" in this column only if the child has not filled a full year of life by the time of enumeration. In other words the child should not have passed his first birthday.</div> Iran 2011: Ever-married females age 10-54 who have given birth [discrepancies: none] This variable indicates whether the woman had any live births in the past 365 days. 1 Yes 2 No 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female live births in the past 365 days <span class="em">Questions 34-36 for women aged 10 to 54</span></p> <p><span class="em">Questions 35-36 for yes to question 34</span></p> <p>35. Number of children born alive during the last 365 days (in total)</p> <div class="i1">_ _ Boys<br />_ _ Girls</div> <span class="em">Columns 32 and 33, number of live newborns</span> </p> <div class="i1">Fill these columns if "yes" is checked in column 31 and leave blank for the rest.</div><span class="em">Column 34 -36, General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for females 10 - 54 year-old married at least once [codes 1, 2, 3 in column 30] and gave birth to at least one live newborn ["yes" in column 31], and leave it blank for the rest.</div><span class="em">Column 34, has the individual given birth to a live newborn in the past 365 days?</span> </p> <div class="i1">Check yes or no in this column. <br />" If a woman gave birth to a live newborn during the month of October 2005, make sure to check "yes" in this column only if the child has not filled a full year of life by the time of enumeration. In other words the child should not have passed his first birthday.</div> Iran 2011: Ever-married females age 10-54 who gave birth in the past year [discrepancies: none] This variable indicates the number of female live births that a woman has had in the past 365 days. 0 0 1 1 2 2+ 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male live births in the past 365 days <span class="em">Questions 34-36 for women aged 10 to 54</span></p> <p><span class="em">Questions 35-36 for yes to question 34</span></p> <p>35. Number of children born alive during the last 365 days (in total)</p> <div class="i1">_ _ Boys<br />_ _ Girls</div> <span class="em">Columns 32 and 33, number of live newborns</span> </p> <div class="i1">Fill these columns if "yes" is checked in column 31 and leave blank for the rest.</div><span class="em">Column 34 -36, General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for females 10 - 54 year-old married at least once [codes 1, 2, 3 in column 30] and gave birth to at least one live newborn ["yes" in column 31], and leave it blank for the rest.</div><span class="em">Column 34, has the individual given birth to a live newborn in the past 365 days?</span> </p> <div class="i1">Check yes or no in this column. <br />" If a woman gave birth to a live newborn during the month of October 2005, make sure to check "yes" in this column only if the child has not filled a full year of life by the time of enumeration. In other words the child should not have passed his first birthday.</div> Iran 2011: Ever-married females age 10-54 who gave birth in the past year [discrepancies: none] This variable indicates the number of male live births that a woman has had in the past 365 days. 0 0 1 1 2 2+ 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female children surviving who were born in the past 365 days <span class="em">Questions 34-36 for women aged 10 to 54</span></p> <p><span class="em">Questions 35-36 for yes to question 34</span></p> <p>36. Number of children born alive during the last 365 days, still living</p> <div class="i1">_ _ Boys<br />_ _ Girls</div> <span class="em">Columns 32 and 33, number of live newborns</span> </p> <div class="i1">Fill these columns if "yes" is checked in column 31 and leave blank for the rest.</div><span class="em">Column 34 -36, General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for females 10 - 54 year-old married at least once [codes 1, 2, 3 in column 30] and gave birth to at least one live newborn ["yes" in column 31], and leave it blank for the rest.</div><span class="em">Columns 35 -36, General description</span> </p> <div class="i1">Fill these columns for females 10 - 54 year-old married at least once [codes 1, 2, 3 in column 30], with "yes" checked in column 34; and leave it blank for the rest. Enter the number of boys and girls as a one-digit number separately in the corresponding rows. <br />[Picture omitted]<br />Total number of live birth in the past 365 days <br />Fill this column if "yes" is checked in column 34 and leave it blank for the rest.<br />Ask the number of live births in the past 365 days, whether or not the offspring is still living by the time of enumeration, and document the number based on the gender, boys/girls, in the corresponding rows.</div><span class="em">Column 36, number of living offspring born in the past 365 days</span> </p> <div class="i1">Document the number based on the gender in the corresponding row.<br />? the number in column 36 should be equal or less than the corresponding numbers in column 35 and/or 33.<br />Consider the following when filling columns 35 -36<br />If yes is checked in column 34 follow the instruction below when filling columns 35 -36:<br />- If the individual gave birth to both live boys and girls, document them in each row in column 35. If those offspring are still alive, enter the number in column 36 and if e.g. the female newborn is not living anymore, write zero in column 36 in the corresponding row.<br />- If the individual only gave birth to female live newborns, document the number of girls in the corresponding row in column 35 and follow the instructions below in rows for boys:<br />[] If the individual gave birth boy[s] and the number is documented in column 32, write zero in column 35 and leave column 36 blank.<br />[] If the individual did not give birth to any live boy(s), and zero is documented in column 32, leave columns 35 and 36 blank.</div> Iran 2011: Ever-married females age 10-54 who gave birth to a female child in the past year [discrepancies: none] This variable indicates the number of female children born in the past 365 days that are still alive. 0 0 1 1 2 2+ 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male children surviving who were born in the past 365 days <span class="em">Questions 34-36 for women aged 10 to 54</span></p> <p><span class="em">Questions 35-36 for yes to question 34</span></p> <p>36. Number of children born alive during the last 365 days, still living</p> <div class="i1">_ _ Boys<br />_ _ Girls</div> <span class="em">Columns 32 and 33, number of live newborns</span> </p> <div class="i1">Fill these columns if "yes" is checked in column 31 and leave blank for the rest.</div><span class="em">Column 34 -36, General description</span> </p> <div class="i1">[Picture omitted]<br />Fill these columns for females 10 - 54 year-old married at least once [codes 1, 2, 3 in column 30] and gave birth to at least one live newborn ["yes" in column 31], and leave it blank for the rest.</div><span class="em">Columns 35 -36, General description</span> </p> <div class="i1">Fill these columns for females 10 - 54 year-old married at least once [codes 1, 2, 3 in column 30], with "yes" checked in column 34; and leave it blank for the rest. Enter the number of boys and girls as a one-digit number separately in the corresponding rows. <br />[Picture omitted]<br />Total number of live birth in the past 365 days <br />Fill this column if "yes" is checked in column 34 and leave it blank for the rest.<br />Ask the number of live births in the past 365 days, whether or not the offspring is still living by the time of enumeration, and document the number based on the gender, boys/girls, in the corresponding rows.</div><span class="em">Column 36, number of living offspring born in the past 365 days</span> </p> <div class="i1">Document the number based on the gender in the corresponding row.<br />? the number in column 36 should be equal or less than the corresponding numbers in column 35 and/or 33.<br />Consider the following when filling columns 35 -36<br />If yes is checked in column 34 follow the instruction below when filling columns 35 -36:<br />- If the individual gave birth to both live boys and girls, document them in each row in column 35. If those offspring are still alive, enter the number in column 36 and if e.g. the female newborn is not living anymore, write zero in column 36 in the corresponding row.<br />- If the individual only gave birth to female live newborns, document the number of girls in the corresponding row in column 35 and follow the instructions below in rows for boys:<br />[] If the individual gave birth boy[s] and the number is documented in column 32, write zero in column 35 and leave column 36 blank.<br />[] If the individual did not give birth to any live boy(s), and zero is documented in column 32, leave columns 35 and 36 blank.</div> Iran 2011: Ever-married females age 10-54 who gave birth to a male child in the past year [discrepancies: none] This variable indicates the number of male children born in the past 365 days that are still alive. 0 0 1 1 2 2+ 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Mother is a member of this household <span class="h3">For all household members</span></p> <p>37. Is the mother a member of this household?</p> <div class="i1">[] Yes<br />[] No</div> <span class="em">Column 37 -42, General description</span> </p> <div class="i1">Fill these columns for all household members regardless of age and gender.<br />[Picture omitted]</div><span class="em">Column 37, is the mother of individual a member of the very household?</span> </p> <div class="i1">Mother is the one who has given birth to the very child not his step mother or wet nurse. Ask this question for each household member. If the mother passed away or is a member of another household check "no" in column 37.<br />[Picture omitted]</div> Iran 2011: All persons This variable indicates whether a person's mother is a member of this very household. 1 Yes 2 No 8 Unknown Constructed Family Interrelationship Variables -- PERSON Mother's row number <span class="h3">For all household members</span></p> <p>37. Is the mother a member of this household?</p> <div class="i1">[] Yes<br />[] No</div><span class="em">Question 38 is for those whose mothers are a member of this household</span></p> <p>38. Line number of mother in column 1 _ _ <span class="em">Column 37 -42, General description</span> </p> <div class="i1">Fill these columns for all household members regardless of age and gender.<br />[Picture omitted]</div><span class="em">Column 38, mother's row number in column 1</span> </p> <div class="i1">Fill this column only if yes is checked in column 37 meaning the mother of individual is the member of the household under enumeration. <br />- Column 37 and 38 are not filled for collective households.<br />[Picture omitted]</div> Iran 2011: Persons who's mother is a member of the household [discrepancies: none] This variable indicates the row number of a person's mother who lives in the household. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 19 19 98 Unknown 99 NIU (not in universe) Constructed Family Interrelationship Variables -- PERSON Birth place <span class="h3">For all household members</span></p> <p>39. Place of birth (mother's place of residence at the time of delivery):</p> <div class="i1">[] 1 The same city / village<br />[] 2 Another city<br />[] 3 Another village<br />[] 4 Abroad</div> <span class="em">Column 37 -42, General description</span> </p> <div class="i1">Fill these columns for all household members regardless of age and gender.<br />[Picture omitted]</div><span class="em">Column 39, place of birth [mother's place of residence at the time of individual's birth]</span> </p> <div class="i1">[Picture omitted]<br />Birthplace of an individual is his mother's residence at the time of his birth. Birthplace is not necessarily the same as the individual's current residence and is not always the place documented in his birth certificate. Document birthplace of each individual by comparing it with his current residence in one of the four possibilities mentioned below: <br />Code 1, the same city or settlement <br />Code 2, another city <br />Code 3, another settlement<br />Code 4, abroad<br />Answer column 39 by considering the administrative divisions of the country at the time of individual's birth, therefore, if the birthplace was a settlement then and a city now, check code 3.<br />- Leave this column blank for the unsettled conventional households.</div> Iran 2011: All persons This variable indicates a person's place of birth, and whether the person was native- or foreign-born. 1 This city or settlement 2 Another city 3 Another settlement 4 Abroad 8 Unknown Nativity and Birthplace Variables -- PERSON Person weight Iran 2011: All persons This variable indicates the person weight. This is a 6-digit numeric variable with 4 implied decimal places Technical Person Variables -- PERSON