Housing, Economic, Demographic Characteristics survey (H.E.D), 1973 DDI_PAK_1973_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. Housing, Economic, Demographic Characteristics survey (H.E.D), 1973 - IPUMS Subset PHC pk1973a (IPUMS Harmonized Subset) PAK_1973_PHC_v01_M_v7.6_A_IPUMS Population Census Organization IPUMS (c) Copyright 1973, Population Census Organization and Minnesota Population Center Population Census Organization Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.6 Version 7.6. The datasets contain selected variables from the original microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Nativity and Birthplace Variables -- PERSON Fertility and Mortality Variables -- PERSON Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Disability Variables -- PERSON Geography: O-Z Variables -- HOUSEHOLD Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Migration: O-Z Variables -- PERSON Migration: Global Variables -- PERSON Technical Person Variables -- PERSON Other Person Variables -- PERSON Demographic Variables -- PERSON Disability Variables -- PERSON Nativity and Birthplace Variables -- PERSON Migration: Global Variables -- PERSON Education Variables -- PERSON Work Variables -- PERSON Work: Occupation Variables -- PERSON Work: Industry Variables -- PERSON Fertility and Mortality Variables -- PERSON Technical Person Variables -- PERSON Not specified (January 1973) Pakistan District Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: no UNIT DESCRIPTIONS: - Dwellings: Housing unit refers to those vacant places or residential places where a household can reside. A housing unit may consist of one room or there may be a few rooms which can be used for residential purpose or are being used for residential purpose. Places under bridges, empty cars of a train or boat can be these types of residences. - Households: A household may be a person living above and also comprise a few such persons who live and eat together. They may include members of household relatives, friends, servants and other non-relatives. Eating together means having common cooking arrangements at a place. - Group quarters: A group of persons living together who have collective arrangement for taking meal, such as boarding house, restaurant/hotel, or other institutional places) . The non-institutional population. Sample survey data [ssd] Additional notes on a sample that is part of this study: Pakistan 1973 Note: Excludes 4 districts in NWFP; many headless households (fragments) MICRODATA SOURCE: Population Census Organization SAMPLE SIZE (person records): 1453332. SAMPLE DESIGN: Approximately 24 thousand blocks were selected out of 75 thousand in the country. A sample of households would be taken from each block to yield 300,000 households. Urban households were oversampled relative to rural. Roughly 15% of households do not have a head and appear to be fragments. *NOTE: The sample excludes 4 districts in the North-West Frontier Province: Chitral, Dir, Swat, and Malakand Agency. Face-to-face [f2f] The HED sample survey was a second phase of the 1972 Census administered to 300,000 households. The first phase was a full-count census in September 1972 that used a seven-question short form. The HED questionnaire contains two parts. Part I asks questions on housing characteristics and household facilities for both urban and rural areas. Part II asks questions particulars of household member. de jure, CENSUS DAY: Not specified (January 1973) Calculated by the census office 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. Population Census Organization 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: Pakistan, Population Census Organization. Housing, Economic, Demographic Characteristics survey (H.E.D), 1973 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 pk1973a, 2025 PAK1973_PHC-H-H.dat Household records 322,131 ascii Minnesota Population Center Version 7.5, IPUMS sample PAK1973_PHC-P-H.dat Person records 1453332 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 Pakistan, Province 1973 - 1998 [Level 1; consistent boundaries, GIS] GEO1_PK identifies the household's province within Pakistan in all sample years. Provinces are the first level administrative units of the country. GEO1_PK 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_PK can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Pakistan 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. 586001 North-West Frontier Province 586002 Fata 586003 Punjab, Islamabad 586004 Sind 586005 Baluchistan 586007 Northern areas 586008 Kashmir Geography: O-Z Variables -- HOUSEHOLD Pakistan, Province 1973 [Level 1, GIS] GEO1_PK1973 identifies the household's province within Pakistan in 1973. Provinces are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_PK1973 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Pakistan can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 001 North-West Frontier Province 002 Punjab 003 Sind 004 Baluchistan Geography: O-Z Variables -- HOUSEHOLD Pakistan, Administrative division 1973 - 1998 [Level 2; consistent boundaries, GIS] GEO2_PK identifies the household's administrative division within Parkistan in all sample years. Administrative divisions are the second level administrative units of the country, after provinces. GEO2_PK 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_PK can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Pakistan 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. 586001001 Bannu, D.I.Khan 586001002 Hazara, Kohat, Malakand, Mardan, Peshawar 586002001 Federally Administered Tribal Areas (FATA) 586003001 Bahawalpur 586003002 D.G.Khan, Gujranwala, Lahore, Multan 586003003 Faisalabad, Sargodha 586003004 Rawalpindi, Islamabad 586004001 Hyderabad, Mirpur Khas 586004002 Karachi 586004003 Larkana, Sukkur 586005001 Kalat, Mekran 586005002 Nasirabad, Sibi 586005003 Quetta, Zhob 586007001 Northern Areas 586008001 Kashmir Geography: O-Z Variables -- HOUSEHOLD Pakistan, Administrative division 1973 [Level 2, GIS] GEO2_PK1973 indicates the householdâs administrative division within Pakistan in 1973. Administrative divisions are the second level administrative units of the country, after provinces. A GIS map (in shapefile format), corresponding to GEO2_PK1973 can be downloaded from the GIS Boundary files page in the IPUMS International web site The full set of geography variables for Pakistan 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. 001001 Chitral 001002 Dir 001003 Swat 001004 Malakand Agency 001005 Hazara 001006 Mardan 001007 Peshawar 001010 Kohat 001014 D.I. Khan 001015 Bannu 002018 Campbellpur 002019 Federal Capital Islamabad and Rawalpindi 002023 Jhelum 002024 Gujrat 002026 Sargodha 002028 Mianwalai 002029 Lyallpur 002031 Jhang 002032 Lahore 002035 Gujranwala 002037 Sheikhupura 002038 Sialkot 002041 D.G. Khan 002042 Muzaffargarh 002043 Multan 002046 Sahiwal 002047 Bahalpur 002048 Bahawalnagar 002049 Rahimyar Khan 003050 Jacobabad 003051 Sukkur 003053 Larkana 003054 Nawabshah 003055 Khairpur 003056 Hyderabad 003058 Dadu 003059 Tharparkar 003060 Sanghar 003061 Thatta 003062 Karachi 004067 Quetta 004070 Sibi 004072 Loralai 004073 Zhob 004074 Chagai 004075 Kalat 004076 Kachhi 004077 Kharan 004078 Mekran 004081 Lasbella 096096 Northern Areas 097097 Federally Administered Tribal Areas (FATA) 098098 Kashmir Geography: O-Z Variables -- HOUSEHOLD Pakistan, District 1973 - 1998 [Level 3; inconsistent boundaries, harmonized by name] DISTPK identifies the household's district within Pakistan in all sample years. Districts are the third level administrative units of the country, after administrative division. DISTPK is harmonized by name and does not account for boundary changes over time. The full set of geography variables for Pakistan 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. 111 Bannu 112 Lakki Marwat 121 D.I.Khan 122 Tank 131 Abbottabad 132 Batagram 133 Haripur 134 Kohistan 135 Mansehra 139 Hazara district 141 Hangu 142 Karak 143 Kohat 151 Buner 152 Chitral 154 Malakand Prote 155 Shangla 156 Swat 157 Upper Dir 158 Lower Dir 161 Mardan 162 Swabi 171 Charsadda 172 Nowshera 173 Peshawar 311 Bahawalnagar 312 Bahawalpur 313 Rahim Yar Khan 321 Dera Ghazi Khan 322 Layyah 323 Muzaffargarh 324 Rajanpur 331 Faisalabad 332 Jhang 333 Toba Tek Singh 341 Gujranwala 342 Gujrat 343 Hafizabad 344 Mandi Bahauddin 345 Narowal 346 Sialkot 351 Kasur 352 Lahore 353 Okara 354 Sheikhupura 361 Khanewal 362 Lodhran 363 Multan 364 Pakpattan 365 Sahiwal 366 Vehari 371 Attock 372 Chakwal 373 Jhelum 374 Rawalpindi 381 Bhakkar 382 Khushab 383 Mianwali 384 Sargodha 411 Badin 412 Dadu 413 Hyderabad 414 Thatta 421 Karachi Central 422 Karachi East 423 Karachi South 424 Karachi West 425 Malir 429 Karachi district 431 Jacobabad 432 Larkana 433 Shikarpur 441 Mirpur Khas 442 Sanghar 443 Tharparkar 444 Umer Kot 451 Ghotki 452 Khairpur 453 Naushahro Feroze 454 Nawabshah 455 Sukkur 511 Awaran 512 Kalat 513 Kharan 514 Khuzdar 515 Lasbela 516 Mastung 521 Gwadar 522 Kech 523 Panjgur 529 Mekran district 531 Bolan 532 Jaffarabad 533 Jhal Magsi 534 Nasirabad 541 Chagai 542 Killa Abdullah 543 Pishin 544 Quetta 551 Dera Bugti 552 Kohlu 553 Sibi 554 Ziarat 559 Kachhi 561 Barkhan 562 Killa Saifullah 563 Loralai 564 Musakhel 565 Zhob 611 Islamabad Geography: O-Z Variables -- HOUSEHOLD DHS-IPUMS-I Pakistan regions, 1973-2012 [consistent boundaries, GIS] DHS_IPUMSI_PK provides geographic codes for Pakistan that match those in the DHS and IPUMS-International databases. This variable can be used to link contextual area data from IPUMS-DHS to IPUMS-International or vice versa. The codes in DHS_IPUMSI_PK indicate the major administrative unit in which the household was enumerated or surveyed. GIS shapefiles for Pakistan can be downloaded here. 1 Punjab (includes Islamabad Capital Territory) 2 Sindh 3 Khyber Pakhtunkhwa (North West Frontier Province) 4 Balochistan 5 Gilgit Baltistan (Federally Administered Northern Areas) 6 Federally Administered Tribal Areas (FATA) 7 Azad, Jammu and Kashmir Geography: IPUMS-I, IPUMS-DHS 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 Pakistan 1973: All households This variable indicates the dwelling number. This is a 6-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Number of persons in household Pakistan 1973: All households This variable indicates the number of persons 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 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 40 40 Technical Household Variables -- HOUSEHOLD Urban Pakistan 1973: All households This variable indicates whether the dwelling is in an urban or rural area. 1 Rural 2 Urban population less than 10000 3 Urban population 10000-25000 4 Urban population 25000-50000 5 Urban population 50000-100000 6 Urban population 100000 and above Geography: O-Z Variables -- HOUSEHOLD Household weight Pakistan 1973: All households This variable indicates the household weight. This is a 2-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Strata Pakistan 1973: 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: O-Z 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 Age at first marriage or union AGEMARR indicates the person's age at first marriage or consensual union. 00 NIU (not in universe) 10 10 or younger 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98 99 Unknown 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 Nativity status NATIVITY indicates whether the person was native-born or foreign-born. 0 NIU (not in universe) 1 Native-born 2 Foreign-born 9 Unknown/missing Nativity and Birthplace Variables -- PERSON Country of birth BPLCOUNTRY indicates the person's country of birth. 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11005 British Indian Ocean Territory 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11051 Ethiopia (including Eritrea) 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, other or n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15021 Upper Volta 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15081 Guinea-Bissau and Cape Verde 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15180 Canary Islands 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21200 St. Croix 21210 St. John 21220 St. Lucia 21230 St Thomas 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21991 Caribbean commonwealth, n.s. 21999 Caribbean, other or n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, other or n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, other or n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32042 India/Pakistan/Bangladesh/Sri Lanka 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32101 Pakistan/Bangladesh 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32999 South-Central Asia, other or n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33999 South-Eastern Asia, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34071 Israel/Palestine 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34111 West Bank 34112 Gaza Strip 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41991 Albania, Bulgaria, Czech, Hungary, Romania, Yugoslavia 41992 Central-Eastern Europe 41999 Eastern Europe, other or n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43121 Spain/Portugal 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43991 Gibraltar/Malta 43992 Portugal/Greece 43993 Italy, Holy See, San Marino 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44021 Belgium/Luxemburg 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44042 West Germany 44043 Germany/Austria 44044 Mecklenburg-Schwerin 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44991 Belgium, Denmark, Luxembourg, Netherlands 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (original 15) 49994 Other European Union (not original 15) 49999 Europe, other or n.s. 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53060 Federated States of Micronesia 53999 Micronesia, other or n.s. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 80000 AT SEA 90000 Other countries n.s. 99999 Unknown Nativity and Birthplace Variables -- PERSON District of birth, Pakistan BPLPK indicates the person's district of birth within Pakistan. East Pakistan is coded as a foreign country. NOTE: The Pakistan 1973 sample includes respondents whose districts of birth are in the Federally Administered Tribal Areas and the two autonomous states, Northern areas (Gilgit-Baltistan) and Kashmir. The actual residents of those areas are not included in the sample. 111 Bannu 121 D.I. Khan 139 Hazara 143 Kohat 152 Chitral 154 Malakand Agency 156 Swat 158 Dir 161 Mardan 173 Peshawar 311 Bahawalnagar 312 Bahalpur 313 Rahimyar Khan 321 D.G. Khan 323 Muzaffargarh 331 Lyallpur 332 Jhang 341 Gujranwala 342 Gujrat 346 Sialkot 352 Lahore 354 Sheikhupura 363 Multan 365 Sahiwal 371 Campbellpur 373 Jhelum 383 Mianwalai 384 Sargodha 412 Dadu 413 Hyderabad 414 Thatta 429 Karachi 431 Jacobabad 432 Larkana 442 Sanghar 443 Tharparkar 452 Khairpur 454 Nawabshah 455 Sukkur 512 Kalat 513 Kharan 515 Lasbella 529 Mekran 541 Chagai 544 Quetta 553 Sibi 559 Kachhi 563 Loralai 565 Zhob 611 Islamabad and Rawalpindi 901 Fata Tribal area under DC (Peshawar, Kohat, D.I. Khan, Bannu), Mohammad agency, Khyber agency, Kurram agency, North Wazirsitan, South Waziristan 902 Muzaffarabad, Poonch, Mirpur, Gilgit agency, Baltistan agency 903 Occupied Kashmir 990 Foreign country 999 Unknown 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 Educational attainment, Pakistan EDUCPK indicates the person's educational attainment in Pakistan in terms of the level of schooling completed. 000 NIU (not in universe) 100 None 200 Primary 210 Less than primary 220 Primary 230 Middle 300 Secondary 310 Matric 320 Intermediate 400 Tertiary 410 Bachelors degree 420 Post-graduate 421 MA / MSCc and above 422 Bsc and above (engineering) 423 MBBS / BDS and above 424 LLB and above 430 Diploma or certificate 431 Diploma 432 Certificate 500 Others 999 Unknown 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-1968, 3-digit ISCO68A provides the 3-digit occupation code for the respondent using the ISCO-1968 occupation classification. 011 Chemists 012 Physicists 013 Physical scientists not elsewhere classified 014 Physical science technicians 021 Architects and town planners 022 Civil engineers 023 Electrical and electronics engineers 024 Mechanical engineers 025 Chemical engineers 026 Metallurgists 027 Mining engineers 028 Industrial engineers 029 Engineers not elsewhere classified 031 Surveyors 032 Draughtsmen 033 Civil engineering technicians 034 Electrical and electronics engineering technicians 035 Mechanical engineering technicians 036 Chemical engineering technicians 037 Metallurgical technicians 038 Mining technicians 039 Engineering technicians not elsewhere classified 041 Aircraft pilots, navigators and flight engineers 042 Ships' deck officers and pilots 043 Ships' engineers 049 Aircraft and ships officers, n.e.c. 051 Biologists, zoologists and related scientists 052 Bacteriologists, pharmacologists and related scientists 053 Agronomists and related scientists 054 Life sciences technicians 059 Life sciences technicians and related technicians, n.e.c. 061 Medical doctors 062 Medical assistants 063 Dentists 064 Dental assistants 065 Veterinarians 066 Veterinary assistants 067 Pharmacists 068 Pharmaceutical assistants 069 Dietitians and public health nutritionists 071 Professional nurses 072 Nursing personnel not elsewhere classified 073 Professional midwives 074 Midwifery personnel not elsewhere classified 075 Optometrists and opticians 076 Physiotherapists and occupational therapists 077 Medical Xray technicians 079 Medical, dental, veterinary and related workers not elsewhere classified 081 Statisticians 082 Mathematicians and actuaries 083 Systems Analysts 084 Statistical and mathematical technicians 089 Statisticians, mathematicians, systems analysts and related technicians, n.e.c. 090 Economists 099 Other social scientists, n.e.c. 110 Accountants 121 Lawyers 122 Judges 129 Jurists not elsewhere classified 131 University and higher education teachers 132 Secondary education teachers 133 Primary education teachers 134 Preprimary education teachers 135 Special education teachers 139 Teachers not elsewhere classified 141 Ministers of religion and related members of religious orders 149 Workers in religion not elsewhere classified 151 Authors and critics 159 Authors, journalists and related writers not elsewhere classified 161 Sculptors, painters and related artists 162 Commercial artists and designers 163 Photographers and cameramen 169 Sculptors, painters and related artists, n.e.c. 171 Composers, musicians and singers 172 Choreographers and dancers 173 Actors and stage directors 174 Producers, performing arts 175 Circus performers 179 Performing artists not elsewhere classified 180 Athletes, sportsmen and related workers 191 Librarians, archivists and curators 192 Sociologists, anthropologists and related scientists 193 Social workers 194 Personnel and occupational specialists 195 Philologists, translators and interpreters 199 Other professional, technical and related workers 201 Legislative officials 202 Government administrators 211 General managers 212 Production managers (except farm) 219 Managers not elsewhere classified 299 Administrative and managerial, n.e.c. 300 Clerical supervisors 310 Government executive officials 321 Stenographers, typists and teletypists 322 Card and tapepunching machine operators 323 Telex operators 329 Stenegraphers, typists and teletypists, n.e.d. 331 Bookkeepers and cashiers 339 Bookkeepers, cashiers and related workers not elsewhere classified 341 Bookkeeping and calculating machine operators 342 Automatic dataprocessing machine operators 349 Computing machine operators, n.e.c. 351 Railway station masters 352 Postmasters 359 Transport and communications supervisors not elsewhere classified 360 Transport conductors 370 Mail distribution clerks 380 Telephone and telegraph operators 391 Stock clerks 392 Material and production planning clerks 393 Correspondence and reporting clerks 394 Receptionists and travel agency clerks 395 Library and filing clerks 399 Clerks not elsewhere classified 400 Managers (wholesale and retail trade) 410 Working proprietors (wholesale and retail trade) 421 Sales supervisors 422 Buyers 431 Technical salesmen and service advisers 432 Commercial travellers and Manufacturers' agents 439 Technical salesmen, commercial travellers and manufacturers' agents, n.e.c. 441 Insurance, real estate and securities salesmen 442 Business services salesmen 443 Auctioneers 451 Salesmen, shop assistants and demonstrators 452 Street vendors, canvassers and newsvendors 454 Itinerant traders 459 Salesmen, shop assistants and demonstrators, n.e.c. 490 Sales workers not elsewhere classified 500 Managers (catering and lodging services) 510 Working proprietors (catering and lodging services) 520 Housekeeping and related service supervisors 531 Cooks 532 Waiters, bartenders and related workers 540 Maids and related housekeeping service workers not elsewhere classified 551 Building caretakers 552 Charworkers, cleaners and related workers 560 Launderers, drycleaners and pressers 570 Hairdressers, barbers, beauticians and related workers 581 Firefighters 582 Policemen and detectives 589 Protective service workers not elsewhere classified 591 Guides 592 Undertakers and embalmers 599 Other service workers 600 Farm managers and supervisors 611 General farmers 612 Specialised farmers 621 General farm workers 622 Field crop and vegetable farm workers 623 Orchard, vineyard and related tree and shrub crop workers 624 Livestock workers 625 Dairy farm workers 626 Poultry farm workers 627 Nursery workers and gardeners 628 Farm machinery operators 629 Agricultural and animal husbandry workers not elsewhere classified 631 Loggers 632 Forestry workers (except logging) 639 Forestry and loggers, n.e.c. 641 Fishermen 649 Fishermen, hunters and related workers not elsewhere classified 700 Production supervisors and general foremen 711 Miners and quarrymen 712 Mineral and stone treaters 713 Well drillers, borers and related workers 721 Metal smelting, converting and refining furnacemen 722 Metal rollingmill workers 723 Metal melters and reheaters 724 Metal casters 725 Metal moulders and coremakers 726 Metal annealers, temperers and casehardeners 727 Metal drawers and extruders 728 Metal platers and coaters 729 Metal processers not elsewhere classified 731 Wood treaters 732 Sawyers, plywood makers and related woodprocessing workers 733 Paper pulp preparers 734 Paper makers 739 Wood preparation workers and paper makers, n.e.c. 741 Crushers, grinders and mixers 742 Cookers, roasters and related heattreaters 743 Filter and separator operators 744 Still and reactor operators 745 Petroleum refining workers 749 Chemical processers and related workers not elsewhere classified 751 Fibre preparers 752 Spinners and winders 753 Weaving and knittingmachine setters and patterncard preparers 754 Weavers and related workers 755 Knitters 756 Bleachers, dyers and textile product finishers 759 Spinners, weavers, knitters, dyers and related workers not elsewhere classified 761 Tanners and fellmongers 762 Pelt dressers 769 Tanners, fellmongers and pelt dressers, n.e.c. 771 Grain millers and related workers 772 Sugar processers and refiners 773 Butchers and meat preparers 774 Food preservers 775 Dairy product processers 776 Bakers, pastrycooks and confectionery makers 777 Tea, coffee and cocoa preparers 778 Brewers, wine and beverage makers 779 Food and beverage processers not elsewhere classified 781 Tobacco preparers 782 Cigar makers 783 Cigarette makers 789 Tobacco preparers and tobacco product makers not elsewhere classified 791 Tailors and dressmakers 792 Fur tailors and related workers 793 Milliners and hatmakers 794 Patternmakers and cutters 795 Sewers and embroiderers 796 Upholsterers and related workers 799 Tailors, dressmakers, sewers, upholsterers and related workers not elsewhere classified 801 Shoemakers and shoe repairers 802 Shoe cutters, lasters, sewers and related workers 803 Leather goods makers 811 Cabinetmakers 812 Woodworking machine operators 819 Cabinetmakers and related woodworkers not elsewhere classified 820 Stone cutters and carvers 831 Blacksmiths, hammersmiths and forgingpress operators 832 Toolmakers, metal patternmakers and metal markers 833 Machinetool setteroperators 834 Machinetool operators 835 Metal grinders, polishers and tool sharpeners 839 Blacksmiths, toolmakers and machinetool operators not elsewhere classified 841 Machinery fitters and machine assemblers 842 Watch, clock and precision instrument makers 843 Motor vehicle mechanics 844 Aircraft engine mechanics 849 Machinery fitters, machine assemblers and precision instrument makers (except electrical) not elsewhere classified 851 Electrical fitters 852 Electronics fitters 853 Electrical and electronics equipment assemblers 854 Radio and television repairmen 855 Electrical wiremen 856 Telephone and telegraph installers 857 Electric linemen and cable jointers 859 Electrical fitters and related electrical and electronics workers not elsewhere classified 861 Broadcasting station operators 862 Sound equipment operators and cinema projectionists 871 Plumbers and pipe fitters 872 Welders and flamecutters 873 Sheetmetal workers 874 Structural metal preparers and erectors 879 Other plumbers, welders, sheet metal and structural metal preparers and erectors 880 Jewellery and precious metal workers 891 Glass formers, cutters, grinders and finishers 892 Potters and related clay and abrasive formers 893 Glass and ceramics kilnmen 894 Glass engravers and etchers 895 Glass and ceramics painters and decorators 899 Glass formers, potters and related workers not elsewhere classified 901 Rubber and plastics product makers (except tire makers and tire vulcanisers) 902 Tire makers and vulcanisers 910 Paper and paperboard products makers 921 Compositors and typesetters 922 Printing pressmen 923 Stereotypers and electrotypers 924 Printing engravers (except photoengravers) 925 Photoengravers 926 Bookbinders and related workers 927 Photographic darkroom workers 929 Printers and related workers not elsewhere classified 931 Painters, construction 939 Painters not elsewhere classified 941 Musical instrument makers and tuners 942 Basketry weavers and brush makers 943 Nonmetallic mineral product makers 949 Other production and related workers 951 Bricklayers, stonemasons and tile setters 952 Reinforced concreters, cement finishers and terrazzo workers 953 Roofers 954 Carpenters, joiners and parquetry workers 955 Plasterers 956 Insulators 957 Glaziers 959 Construction workers not elsewhere classified 961 Power generating machinery operators 969 Stationary engine and related equipment operators not elsewhere classified 971 Dockers and freight handlers 972 Riggers and cable splicers 973 Crane and hoist operators 974 Earthmoving and related machinery operators 979 Material handling equipment operators not elsewhere classified 981 Ships' deck ratings, barge crews and boatmen 982 Ships' engineroom ratings 983 Railway engine drivers and firemen 984 Railway brakemen, signalmen and shunters 985 Motor vehicle drivers 986 Animal and animaldrawn vehicle drivers 989 Transport equipment operators not elsewhere classified 990 Labourers not elsewhere classified 995 Armed forces 997 Response suppressed 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 Hours worked per week HRSWORK1 indicates the number of hours the respondent worked per week at all jobs. 000 0 hours 001 1 hour 002 2 hours 003 3 hours 004 4 hours 005 5 hours 006 6 hours 007 7 hours 008 8 hours 009 9 hours 010 10 hours 011 11 hours 012 12 hours 013 13 hours 014 14 hours 015 15 hours 016 16 hours 017 17 hours 018 18 hours 019 19 hours 020 20 hours 021 21 hours 022 22 hours 023 23 hours 024 24 hours 025 25 hours 026 26 hours 027 27 hours 028 28 hours 029 29 hours 030 30 hours 031 31 hours 032 32 hours 033 33 hours 034 34 hours 035 35 hours 036 36 hours 037 37 hours 038 38 hours 039 39 hours 040 40 hours 041 41 hours 042 42 hours 043 43 hours 044 44 hours 045 45 hours 046 46 hours 047 47 hours 048 48 hours 049 49 hours 050 50 hours 051 51 hours 052 52 hours 053 53 hours 054 54 hours 055 55 hours 056 56 hours 057 57 hours 058 58 hours 059 59 hours 060 60 hours 061 61 hours 062 62 hours 063 63 hours 064 64 hours 065 65 hours 066 66 hours 067 67 hours 068 68 hours 069 69 hours 070 70 hours 071 71 hours 072 72 hours 073 73 hours 074 74 hours 075 75 hours 076 76 hours 077 77 hours 078 78 hours 079 79 hours 080 80 hours 081 81 hours 082 82 hours 083 83 hours 084 84 hours 085 85 hours 086 86 hours 087 87 hours 088 88 hours 089 89 hours 090 90 hours 091 91 hours 092 92 hours 093 93 hours 094 94 hours 095 95 hours 096 96 hours 097 97 hours 098 98 hours 099 99 hours 100 100 hours 101 101 hours 102 102 hours 103 103 hours 104 104 hours 105 105 hours 106 106 hours 107 107 hours 108 108 hours 109 109 hours 110 110 hours 111 111 hours 112 112 hours 113 113 hours 114 114 hours 115 115 hours 116 116 hours 117 117 hours 118 118 hours 119 119 hours 120 120 hours 121 121 hours 122 122 hours 123 123 hours 124 124 hours 125 125 hours 126 126 hours 127 127 hours 128 128 hours 129 129 hours 130 130 hours 131 131 hours 132 132 hours 133 133 hours 134 134 hours 135 135 hours 136 136 hours 137 137 hours 138 138 hours 139 139 hours 140 140+ hours 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Hours worked per week, categorized HRSWORK2 indicates the number of hours the respondent worked per week at all jobs, categorized into intervals. 0 None 1 1 to 14 hours (except tt1980, tt1990 and tt2000) 2 15 to 29 hours (except de1970, ps2017, tt1980, tt1990, tt2000, and ve1971) 3 30 to 39 hours (except de1970, ps2017, tt1980, tt1990, tt2000, and ve1971) 4 40-48 hours (except il1972, tt1980, tt1990, and tt2000) 5 49 hours or more (except il1972 and tt2000) 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Actual hours worked per week HRSACTUAL1 indicates the actual number of hours the respondent worked per week at all jobs. 000 0 hours 001 1 hour 002 2 hours 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100 101 101 102 102 103 103 104 104 105 105 106 106 107 107 108 108 109 109 110 110 111 111 112 112 113 113 114 114 115 115 116 116 117 117 118 118 119 119 120 120 121 121 122 122 123 123 124 124 125 125 126 126 127 127 128 128 129 129 130 130 131 131 132 132 133 133 134 134 135 135 136 136 137 137 138 138 139 139 140 140+ hours 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Actual hours worked per week, categorized HRSACTUAL2 indicates the actual number of hours the respondent worked per week at all jobs, categorized into intervals. 0 None 1 1 to 14 hours (except tt1980, tt1990, and tt2000) 2 15 to 29 hours (except ps2017, tt1980, tt1990, tt2000, and ve1971) 3 30 to 39 hours (except ps2017, tt1980, tt1990, tt2000, and ve1971) 4 40 to 48 hours (except tt1980, tt1990, and tt2000) 5 49 hours or more (except tt2000) 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Period seeking work LOOKJOB indicates the continuous period of time that an unemployed person has been seeking work. 00 NIU (not in universe) 10 Seeking work less than one year 11 Seeking work less than 1 month 12 Seeking work less than 3 months 13 Seeking work 1 to less than 3 months 14 Seeking work 1 to 6 months 15 Seeking work 3 to 12 months 16 Seeking work 3 to less than 6 months 17 Seeking work 6 to 12 months 20 Seeking work more than 1 year 21 Seeking work more than 1 and up to 2 years 22 Seeking work more than 2 years 90 Seeking work, unspecified period 99 Unknown Work Variables -- PERSON Years residing in current locality MIGYRS1 indicates how many years the person has resided in their current locality of residence. 00 Less than 1 year 01 1 year (or 1 year or less) 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95+ years 96 Less than 5 years 97 More than 5 years 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Province of residence 8 years ago, Pakistan; consistent boundaries, GIS MIG1_8_PK indicates the person's province of residence within Pakistan in September 1965 (eight calendar years before the census). NOTE: The variable includes categories for disputed regions. East Pakistan, which was part of Pakistan at the time of migration, but was the independent country of Bangladesh at the time of the census is coded as "Abroad" in this integrated version of the variable. Consult the source variable (PK1973A_0429) for further detail. 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. 000000 NIU (not in universe) 586001 North-West Frontier Province 586002 Fata 586003 Punjab, Islamabad 586004 Sind 586005 Baluchistan 586007 Northern areas 586008 Kashmir 586097 Abroad 586098 Unknown Migration: O-Z Variables -- PERSON District of residence 8 years ago, Pakistan; consistent boundaries, GIS MIG2_8_PK indicates the person's administrative division of residence, 8 years ago within Pakistan. Migration administrative division codes from MIG2_8_PK are compatible with codes from GEO2_PK. 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. 586001001 Bannu, D.I.Khan 586001002 Hazara, Kohat, Malakand, Mardan, Peshawar 586002001 Federally Administered Tribal Areas (FATA) 586003001 Bahawalpur 586003002 D.G.Khan, Gujranwala, Lahore, Multan 586003003 Faisalabad, Sargodha 586003004 Rawalpindi, Islamabad 586004001 Hyderabad, Mirpur Khas 586004002 Karachi 586004003 Larkana, Sukkur 586005001 Kalat, Mekran 586005002 Nasirabad, Sibi 586005003 Quetta, Zhob 586007001 Northern Areas 586008001 Kashmir 586097097 Abroad 586098098 Unknown 586099099 NIU (not in universe) Migration: O-Z Variables -- PERSON Disability status DISABLED indicates whether the person reported a disability of any kind. 0 NIU (not in universe) 1 Yes, disabled 2 No, not disabled 9 Unknown Disability Variables -- PERSON Blind or vision-impaired DISBLND indicates whether the person was blind or had limited vision. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Deaf or hearing-impaired DISDEAF indicates whether the person was deaf or had limited hearing. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Mute or speech impaired DISMUTE indicates if the person could not speak or had a significant speech impediment. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Person number (within household) Pakistan 1973: All persons This variable indicates the person number (within the 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 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 Technical Person Variables -- PERSON Mother/child code Pakistan 1973: All persons This variable indicates the mother/child code. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 99 Unknown Other Person Variables -- PERSON Relationship <svar v="PK73A401" a="all">3. Relationship to the head of household Write relationship of each person listed to the head of household ____ </svar> <svar v="PK73A401" a="all">4.5 Relationship to the head of household (Column-3) Actually it is also the part of recognition of that person whose name is written in second column. The definition of head of household has been written in Para 2.7. A person lives alone will be considered head of household. If some persons live together the person declared head by them would be considered the head of the household. The word head of household has already been entered on first line of the third column. It means the name of the person entered first will be head of the household as explained in para-4.4. Besides head, other members of the household will be entered in subsequent lines. The purpose of third column is to show that what relation they have with the head of household and this information will be inquired about every person. It will be asked to the respondent that what relation (Mr./Ms./Mrs. written in column-2) has with the (Mr./Mrs. by name head of household). After inquiring the question of relation about other members besides the head of household, whatever answer is given, the response will be entered in column-3 in front of each name (which is entered in column-2). For example wife, husband, son, daughter, daughter in-law, sister/brother in law, nieces, grandson, friends, servant, guests and other residents, etc.) </svar> The relationship with head of household should not be written in the shaded place of that column. Pakistan 1973: All persons This variable indicates the person's relationship to the household head. 01 Head 02 Spouse 03 Child 04 Child-in-law 05 Parent or parent-in-law 06 Sibling, sibling-in-law, and their spouses 07 Grandchild 08 Other relatives 09 Servants 10 Other 99 Unknown Demographic Variables -- PERSON Sex <svar v="PK73A402" a="all">4. Sex <div class="i1">[] 1 Male [] 2 Female</div> </svar> <svar v="PK73A402" a="all">4.6 Sex (Column-4) Write the relevant code number. Code "1" for Male and "2" for Female. This code will be written for each person of household and every person of household will be either a male or female, the sex of effeminate will be treated as male and code-1 to will be written for him in column-4. </svar> Pakistan 1973: All persons This variable indicates the person's gender. 1 Male 2 Female Demographic Variables -- PERSON Age <svar v="PK73A403" a="all">5. Age (in completed years) _ _ </svar> <svar v="PK73A403" a="all">4.7 Age (Column-5) The age of every person will be written in this column. It may be inquired, "what is the age of that person?" (by asking his name.) Age is the interval, which is estimated or calculated in completed years between the period of birth of person and the time of survey. For children who are less than one year, 0 (zero) will be entered for their age. The age of every person will be counted from the starting date of survey. The child who has not attained the age of one year, his age will be written [Pg. 29] zero (0) in that column. For the person whose age cannot be known, the enumerator should try to estimate correct age of the member while reminding him memorable past historical events, these can be both local and national. For example, the date of creation of Pakistan in 14th August, 1947, Indian attack on Pakistan in September 1965, a starvation in Bengal in 1943, and an earthquake in Quetta in 1934, etc. In most of cases the correct estimate of age can be guessed with reference to the age of the different members of the household. Estimation of age is a very important task, so the enumerators will have to do hard work and use their wisdom in this connection. Sometimes it is better to guess the age of the members of household. The relation between them should be kept in view for it. It has to start from the youngest child and finish on the oldest person of the household. The age of wife/husband can be estimated from age at which they got married. The age of first child can be calculated/known by the difference of age between his parents at the time of marriage and the time of birth of first baby. The age of other children can be guessed by the intermediate interval of their birth. </svar> Pakistan 1973: All persons This variable indicates the person's age in completed years. 00 Less than one year 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98 99 99 or older Demographic Variables -- PERSON Marital status <svar v="PK73A404" a="all">6. Marital status <div class="i1">[] 1 Never married [] 2 Married [] 3 Widowed [] 4 Divorced</div> </svar> <svar v="PK73A404" a="all">4.8 Marital status (Col-No.6) (Persons of ten years age or above) The question should be asked about them (by entered name) whether he/she is married, unmarried, widowed or divorced. The answer of this question will be written in column-6. If a person is unmarried, code "1" will [Pg. 30] be entered for him/her, for married person code "2", for widowed code "3", and for divorced code"4" will be written in column-6. This question should not be asked of people below ten years old, and code "1" will be entered for them. "Un-married person means those who have never been married," "married are those persons who are married at that time and living like wife/husband." This includes separated persons if their wife/husband is alive and they are not divorced. The widowed are those whose wife/husband is dead and still they have not married second time. Divorced means both individuals, which have been divorced or who gave divorce and have not again married. The entry of marital status will be done in regard of present status. </svar> Pakistan 1973: All persons This variable indicates the person's marital status. 1 Never married 2 Married 3 Widowed 4 Divorced Demographic Variables -- PERSON Disability <svar v="PK73A405" a="all">7. Disability <div class="i1">[] 1 Blind [] 2 Deaf and dumb [] 3 Crippled [] 4 Other handicapped</div> </svar> <svar v="PK73A405" a="all">4.9 Disability (Column-7) The following questions of column-7 related to every person of household will be asked. <div class="i1">a. Does any person in the household (By entered names) suffer from any type of disability? If the answer is 'Yes' then ask b. Which type of disability? Enter the relevant code of disability. Codes of disabilities are given below.</div> <div class="i2">1 - Blind 2 - Deaf and dumb 3 - Crippled 4 - Others, the disability other than above mentioned disabilities 5 - None (If not find in above category</div> [Pg. 31] Different types of disabilities are explained as below. If the first question of disability is NO there is a need to ask other questions about that person and code '"5" (None) will be entered in the line in which his/her name is written. Disability means a person who has physical or organ impairment whether it is natural or due to any accident, illness, a part of his/her body became non-functional or become weaker. According to the report of H.E.D., the disability has been divided into four categories. <div class="i1">1. Blindness A person will be considered blind if he/she could not count the fingers of enumerator before him/her with or without spectacles at the distance of one foot. 2. Deaf and dumb A person who could not speak and hear will be deaf and dumb. A man who is deaf but can speak or is dumb but can hear will also be included in this category. 3. Crippled A person who is not able to use/move one or both hands, one or both legs permanently will be known as Crippled/lame 4. Other handicapped First type is hindrance, Second type means that a person is not a blind, deaf and dumb but he is suffering from another type of disability for example mentally retarded, physically impaired etc. through which his normal life is disturbed</div> </svar> Pakistan 1973: All persons This variable indicates the person's disability status. 1 Blind 2 Deaf and/or mute 3 Crippled 4 Other 5 None Disability Variables -- PERSON Place of birth (district) <svar v="PK73A406 PK73A407 PK73A408 PK73A429 PK73A430">Internal migration [Questions 8-10.] </svar> <svar v="PK73A406" a="all">8. Birth place (district/country) Write the name of district in which the person was born. Give name of the country, if born outside Pakistan. ____ </svar> <svar v="PK73A406" a="all">5.2 Place of birth. (District, Country) (Col 8) This question may be asked (by entered name of respondent) in which district or country the person was born. If a person is born in any area of Pakistan then enter the name of district or agency where he was born. If he is born out of Pakistan then write only the name of the country. Place of birth means that place where a person was born. For the purpose of this survey it can be a country or some geographic unit. If a person was born in Pakistan then the name of its administrative district or agency will be written. If a person was born in Azad Jammu and Kashmir then the name of district along with Azad Jammu and Kashmir Mirpur will also be written. Similarly the person who was born in occupied Kashmir, write name of district along with occupied Kashmir. If a person was born out of Pakistan in some other country then in such a case write only the name of the country (e.g., Iran, Turkey, U.S.A., etc.). </svar> Pakistan 1973: All persons This variable indicates the person's district of birth. 01 Chitral 02 Dir 03 Swat 04 Malakand Agency 05 Hazara 06 Mardan 07 Peshawar 10 Kohat 14 D.I. Khan 15 Bannu 18 Campbellpur 19 Federal Capital Islamabad and Rawalpindi 23 Jhelum 24 Gujrat 26 Sargodha 28 Mianwalai 29 Lyallpur 31 Jhang 32 Lahore 35 Gujranwala 37 Sheikhupura 38 Sialkot 41 D.G. Khan 42 Muzaffargarh 43 Multan 46 Sahiwal 47 Bahalpur 48 Bahawalnagar 49 Rahimyar Khan 50 Jacobabad 51 Sukkur 53 Larkana 54 Nawabshah 55 Khairpur 56 Hyderabad 58 Dadu 59 Tharparkar 60 Sanghar 61 Thatta 62 Karachi 67 Quetta 70 Sibi 72 Loralai 73 Zhob 74 Chagai 75 Kalat 76 Kachhi 77 Kharan 78 Mekran 81 Lasbella 91 Fata Tribal area under DC (Peshawar, Kohat, D.I. Khan, Bannu), Malakand agency, Mohammad agency, Khyber agency, Kurram agency, North Wazirsitan, South Waziristan 92 Muzaffarabad, Poonch, Mirpur, Gilgit agency, Baltistan agency 93 Occupied Kashmir 94 East Pakistan 95 India 96 Afghanistan 97 Rest of the world 99 Unknown Nativity and Birthplace Variables -- PERSON Duration of continuous residence <svar v="PK73A406 PK73A407 PK73A408 PK73A429 PK73A430">Internal migration [Questions 8-10.] </svar> <svar v="PK73A407" a="all">9. Duration of continuous residence in this locality (write duration in completed years) ____ </svar> <svar v="PK73A407" a="all">5.3 Duration of continuous residence in this locality. (Sample area Col. 9) The question will be asked of how long this member of household (by entered name) has been residing in this area (sample area). This period will be counted since that person used to live in this locality regularly and period spent till this survey. By area means present in that village, town or city in which his housing unit is situated. If he has gone out from this area on leave, business tour, for medical treatment, to see someone, etc for a few days, even then it will be considered that his stay in this area is continuous. The enumerators will write duration of residence of every member of the household in completed years. If the duration of residence is less than one year then write less than one year. </svar> Pakistan 1973: All persons This variable indicates the person's duration of continuous residence in the present locality (village, town or city). 00 Less than one year 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98 99 99 years and more Migration: Global Variables -- PERSON Residence in 1965 (district) <svar v="PK73A408 PK73A429 PK73A430" a="all">10. Where were you living (place of usual residence) when India attacked Pakistan in September 1965? (Write name of district with urban/rural indication, e.g. Multan (U) Sukkur (R), etc. ____ </svar> <svar v="PK73A408 PK73A429 PK73A430" a="all">5.4 Place of residence at the time of Indian attack on Pakistan in September, 1965 Ask the question (by entered name) of where was his usual residence when India attacked Pakistan in September, 1965? Usual residence means that geographic unit (village, town, or city) where the members of this household usually reside. By residence means living and eating together like family and usual residence means that place which is occupied by them where they can come and go at their free will without any check. If an owner of the house rents out his house or housing unit to someone on rent or without rent and as long as it is occupied by the other person that will not be treated as owner housing unit. This question will be asked about the residential status of every member of the household when India attacked Pakistan in first week of Sept, 1965. The present residence could be same as that at the time of survey and also be different. If this area is situated within the boundary of Pakistan, then enumerators will write the name of administrative district or agency where that person resided. The same will be the case for area of Azad Kashmir, Northern areas, and occupied Kashmir. The enumerator will have to indicate whether it is situated in an urban area or rural area. For urban area 'U' and for rural area 'R' will be written. If [Pg. 35] Multan before the Sept 1965 attack, then 'U' will be written along with Multan. Similarly, if some body was residing in rural area of Sukkur, then 'R' will be written with Sukkur. If some person has gone out from his usual residence temporarily to see someone or for business even then this house will be considered as his place of residence and place of travel or place of business will not be entered as his usual residence. </svar> Pakistan 1973: Persons age 8+ [discrepancies: type I none; type II trace] This variable indicates the person's district of residence in September 1965, when the Indo-Pakistani War of 1965 started. 01 Chitral 02 Dir 03 Swat 04 Malakand Agency 05 Hazara 06 Mardan 07 Peshawar 10 Kohat 14 D.I. Khan 15 Bannu 18 Campbellpur 19 Federal Capital Islamabad and Rawalpindi 23 Jhelum 24 Gujrat 26 Sargodha 28 Mianwalai 29 Lyallpur 31 Jhang 32 Lahore 35 Gujranwala 37 Sheikhupura 38 Sialkot 41 D.G. Khan 42 Muzaffargarh 43 Multan 46 Sahiwal 47 Bahalpur 48 Bahawalnagar 49 Rahimyar Khan 50 Jacobabad 51 Sukkur 53 Larkana 54 Nawabshah 55 Khairpur 56 Hyderabad 58 Dadu 59 Tharparkar 60 Sanghar 61 Thatta 62 Karachi 67 Quetta 70 Sibi 72 Loralai 73 Zhob 74 Chagai 75 Kalat 76 Kachhi 77 Kharan 78 Mekran 81 Lasbella 91 Fata Tribal area under DC (Peshawar, Kohat, D.I. Khan, Bannu), Malakand agency, Mohammad agency, Khyber agency, Kurram agency, North Wazirsitan, South Waziristan 92 Muzaffarabad, Poonch, Mirpur, Gilgit agency, Baltistan agency 93 Occupied Kashmir 94 East Pakistan 95 India 96 Afghanistan 97 Rest of the world 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Residence in urban or rural area in 1965 <svar v="PK73A408 PK73A429 PK73A430" a="all">10. Where were you living (place of usual residence) when India attacked Pakistan in September 1965? (Write name of district with urban/rural indication, e.g. Multan (U) Sukkur (R), etc. ____ </svar> <svar v="PK73A408 PK73A429 PK73A430" a="all">5.4 Place of residence at the time of Indian attack on Pakistan in September, 1965 Ask the question (by entered name) of where was his usual residence when India attacked Pakistan in September, 1965? Usual residence means that geographic unit (village, town, or city) where the members of this household usually reside. By residence means living and eating together like family and usual residence means that place which is occupied by them where they can come and go at their free will without any check. If an owner of the house rents out his house or housing unit to someone on rent or without rent and as long as it is occupied by the other person that will not be treated as owner housing unit. This question will be asked about the residential status of every member of the household when India attacked Pakistan in first week of Sept, 1965. The present residence could be same as that at the time of survey and also be different. If this area is situated within the boundary of Pakistan, then enumerators will write the name of administrative district or agency where that person resided. The same will be the case for area of Azad Kashmir, Northern areas, and occupied Kashmir. The enumerator will have to indicate whether it is situated in an urban area or rural area. For urban area 'U' and for rural area 'R' will be written. If [Pg. 35] Multan before the Sept 1965 attack, then 'U' will be written along with Multan. Similarly, if some body was residing in rural area of Sukkur, then 'R' will be written with Sukkur. If some person has gone out from his usual residence temporarily to see someone or for business even then this house will be considered as his place of residence and place of travel or place of business will not be entered as his usual residence. </svar> Pakistan 1973: Persons age 8+ [discrepancies: type I none; type II trace] This variable indicates whether the person's residence was in an urban or rural area in September 1965, when the Indo-Pakistani War of 1965 started. 1 Urban 2 Rural 8 Unknown 9 NIU (not in universe) Migration: Global Variables -- PERSON Literacy <svar v="PK73A409 PK73A410 PK73A411 PK73A412">Educational characteristics (For persons 5 years of age and above) [Questions 11-14.] </svar> <svar v="PK73A409" a="all">11. Literacy <div class="i1">[] 1 Literate with formal education [] 2 Literate without formal education [] 3 Illiterate</div> </svar> <svar v="PK73A409" a="all">6.2 Literacy. Those persons who are able to read and write with understanding in any language will be considered literate. Some people learn reading/writing through education in school, code number 1 will be given to such person. However, in Pakistan quite a big number of people, without going to school or Madarsah, with their efforts, can read and write, code No. 2 will be given to such persons. Such people who can not read or write at all or can read but not write will be considered illiterate in this survey and code No. 3 will be given to such people. </svar> Pakistan 1973: Persons age 5+ [discrepancies: type I none; type II 60.3%] This variable indicates whether the person is literate. Although the question was asked of persons age 5 and older, all age 6 students are listed under illiterate. 1 Literate, with education 2 Literate, no education 3 Illiterate 9 NIU (not in universe) Education Variables -- PERSON School attendance <svar v="PK73A409 PK73A410 PK73A411 PK73A412">Educational characteristics (For persons 5 years of age and above) [Questions 11-14.] </svar> <svar v="PK73A410" a="all">12. School attendance <div class="i1">[] 1 Attending general [] 2 Attending specialized [] 3 Attending Madrassah [] 4 Left school [] 5 Not attended any school</div> </svar> <svar v="PK73A410" a="all">6.3 School or college attendance (Code 12) To get answer for column 12, the following questions in seriatim will have to be asked from every member of the household of ages five and above. <div class="i1">1. Ask (by entered name) whether the person is going to school or college.</div> If the answer to Question number 1 [whether attending school or college] is yes then enquire, <div class="i1">2. Which type of the school or college (ask by entered name) is the person attending?</div> <div class="i2">a) General b) Specialized c) Eastern type Madarsah</div> [Pg. 37] <div class="i1">The answer to this question will be any one of the above three categories and relevant code No. 1, 2, or 3 will be entered against this person.</div> If the answer to Question Number 1 [whether attending school or college] is 'No' then ask the following questions. <div class="i1">3. Whether (ask by enter name) has left the school or college.</div> If the answer is 'yes' then code No. 4 will be written against the name of this person. If the answer of this question [whether the person has left school or college] is also 'No' then ask next question. <div class="i1">4. Did (ask by entered name) never go to school or college for education?</div> If the respondent rightly gave answers to the three questions as 'No' then answer to the question should be 'yes' and in Column 12 code No. 5 should be written. If someone gives an answer as "No" then ask the initial three questions again to get correct information. </svar> Pakistan 1973: Persons age 5+ [discrepancies: type I 0.4%; type II trace] This variable indicates whether the person attends school. 1 Attending general 2 Attending specialized 3 Attending Madrassah 4 Left school 5 Did not attend any school 8 Unknown 9 NIU (not in universe) Education Variables -- PERSON Level of education <svar v="PK73A409 PK73A410 PK73A411 PK73A412">Educational characteristics (For persons 5 years of age and above) [Questions 11-14.] </svar> <svar v="PK73A411" a="all">13. Highest grade/level passed in general or specialized or Madrassah education Write highest grade/level passed in general, specialized, Madrassah education, viz. Matric M.Sc., B.Edl, Allm, Fazil, etc. ____ </svar> <svar v="PK73A411" a="all">Educational characteristics (for persons of five years and above) School or college attendance means that a person has been going to an educational institution, Government or private, for attaining regular education. A private school or college, registered or not, where education is given under educational system and students are prepared for examination as private candidates for any level of education of educational board or university. The attendance in these schools or college will also be considered similar, provided the persons who are studying in such institutions are full time students. The attendance in any class of such schools and Madarsah will be treated as attendance of the schools where regular classes or levels under educational system are taken. Attendance at such institutions which provide training before employment (e.g., technical training centre, P. T. (physical training teachers), C.T. (teaching certificate), J.V. (junior vernacular), S.V. (senior vernacular), B.T., B.Ed, etc.) will be treated as attendance in [Pg. 38] special educational institutions provided the duration of the full time course. The people who are attending such intuitions is six months or equivalent to it a part time course, all such persons will be considered as admitted in the institutions. Different professional education which is not the part of any authentic educational system of the country (e.g., education given during job in-staff, college, or training centers) will not be considered equivalent to attendance in school or college for this survey. Similarly, attending a short time class, evening coaching centre, business examinations, languages and class of hobbies will also not be treated as attendance in school or college. The following institutions where there is no arrangement of education according to classes or levels will not come under the definitions of school or college. <div class="i1">1. Below primary, Kindergarten, Montessori, etc. 2. Adult education 3. Institution of laborers education 4. Schools of physical, mental or social education for disabled</div> The institutions which give on the job training will also be considered as school or college (e.g., training centre of nurses, railways training centre, training centre of post offices, National Institute of Public Administration (NIPA), government sector training institute, staff college, etc. and similar armed or semi armed intuitions). Apprenticeships will also not be treated as attendance in a school or college. Infect attendance means that some body attending an institution with a purpose that he will attain regular education of a course under a syllabus of educational system. Although there may be some temporary break in attendance due to illness or leave. The school or college attendance has been divided into three types. <div class="i1">1. General 2. Specialized education 3. Madrasah education</div> [Pg. 39] 1. General Education. General education means primary (first to fifth class), middle (Sixth to eight class), secondary school (ninth and tenth class) and arts course and science degree, including eleventh to fourteenth class. If such students are studying in intermediate or degree colleges they will be considered as studying general education. Those students who have passed B.A. or B.S. courses (i.e., studying in thirteen and fourteen classes) of the universities, they will be considered as attaining general education. 2. Specialized education. The definition of general education given above, education besides arts, commerce ,and science given in universities will be considered as specialized education. Professional arts (technical) and Masters of every type and every level are included in it such as B.Sc. engineering, B.com. (pass honors), MBBS, or B.Ed., etc.). Moreover, higher education of arts, commerce and science in B.A. honors and B.Sc. (honor) and Masters of every subject will be treated as specialized education. Apprenticeship before employment: Technical or professional education will also be treated as specialized education, but on job training (e.g., technical training or some other training obtained during employment) will not included in it. Degree or higher professional education (e.g., education in agricultural, veterinary, engineering, law, etc.) will also be considered specialized education. 3. Education in Madarsah. Madarsah is that place where "Imam," "Molvi," or some other teacher of the Holy Quran, and at some other places in urban or local languages give education. Madarsah is such an institution where regular education according to the Eastern system or religious education is given. Although Madarsahs and schools are considered as educational institutions in Pakistan, they are not treated equivalent to general education special education as primary or middle or high school. Due to this reason, it is not a part of special education, but this fact cannot be ignored that education of Madarsah is also a step [Pg. 40] towards different grades of education. It requires four years initial class admission 4 to 6 years. Alam 4 or 3 complete 2 years total (16 years in total). Therefore, it is considered a different type. All students who got education in Madarsahs or school they will be kept under education in Madarsah. The people who are not getting education in any institution are of two types. <div class="i1">1. The people who got admission in a school or college some time earlier and studied but now has before the school or college. They will be kept under category "Left the school." 2. The people who have never attended any educational institutions for education they will be included in the category "Not attended any school."</div> General, specialized or the highest class/level completed through education in Madarsah Col. 13. Information about every person of five years or above in Col. 13 will be asked. The following questions will be asked in this connection which highest grade level (ask by name of entered household member) in general, specialized or education of madarsah has completed. The people who never attended any educational institution for studies and code No. 5 has been entered in column 12 a dash may be put for such people in this box. The highest grade/class passed will be entered for them in the following way. The highest grade/level will be entered under general education like primary, middle, metric Inter and B.A. the student who are studying in ninth or tenth class. Middle will be entered for them. The students who are studying in intermediate have passed metric, therefore metric will be entered against their names. Similarly other classes will be entered. However no name of class before completion of primary will be entered such as class II, class III or class IV (the one who has passed class V, primary will be entered for him) [Pg. 41] As far as specialized education is concerned, for the education level below M. A the highest grades/level will be entered along with general education provided the level of general education is highest than that is necessary for admission in specialized education (e.g., Metric, PT, Metric, J.V, Inter arts, CT, BA, S.V., Inter Science, Diploma in Engineering, MA LLB, etc.). As regards the level of general education compulsory for specialized education, there is no need for its explanation (e.g., (BA Hon) BSc (Hon) B.E, BSc (Agriculture), MBBS, etc.). As regards the Madarssah education the completed level/grade will also be entered under it (e.g., initial, entry, Alam, Fazal, Kamal). If these levels are different in different areas than these, they may be entered as equivalent to the above mentioned level/grades. The duration of the level may be kept in view which is necessary for completion of the grade. </svar> Pakistan 1973: Persons age 5+ who ever attended school [discrepancies: type I trace; type II none] This variable indicates the person's level of education completed. 00 Oriental 01 Less than primary 02 Primary passed, but less than middle 03 Middle passed, but less than matric (high school) 04 Matric passed, but less than intermediate (junior college) 05 Intermediate passed, but less than degree 06 Degree passed, but less than higher degree 07 Post-graduate 08 Certificate 09 Diploma 99 NIU (not in universe) Education Variables -- PERSON Technical education <svar v="PK73A409 PK73A410 PK73A411 PK73A412">Educational characteristics (For persons 5 years of age and above) [Questions 11-14.] </svar> <svar v="PK73A412" a="all">14. Area of specialized education Write area for entries of specialized education in col. 13, e.g. Teaching, Engineering, Agriculture, etc. ____ </svar> <svar v="PK73A412" a="all">6.4 Field of Specialized Education (Col. 14) The question that will be asked to be entered in col. 14 (ask by name of household member entered) is which field of specialized education the person has completed. This question will be asked from only those persons against whose name the highest level or grade of specialized education has been entered. This question will not be asked highest level or grade in "general education." A dash will be put against the names of such persons. The details of different fields of education as these will be entered in Col. 14 are given as described below: The enumerators will have to ask more details from the persons against whose names specialized education has been entered in Col 13 (i.e., in which specialized field or sub field of specialized education they have completed). The details of specialized fields or subfields are explained as below. [Pg. 42] <div class="i1">1. Arts and Social Science. Refers to B.A. ( Hon) or M.A. or archeology, economics, humanities, history, international relation, political science, journalism, library science, philosophy, sociology, statistics, Islamite and all other subjects which are offered under arts by the universities, the highest degrees including population, journalism, international affairs, diploma and certificate are included which are offered by the universities under fields of arts. 2. Natural Science. Refers to B.Sc ( Hon), M.Sc, the higher degree in astrology, chemistry, biology, botany, physics, geography, gerontology, biochemistry, entomologies, geology, physics and all such other subjects which are offered under natural science by the universities. 3. Teaching and education. Refers to B.Ed, Diploma in Physical Training, Certificate of Junior Vernacular (J.V.), Certificate in Senior Vernacular (S.V.), Certificate in teaching such courses which are offered by the teacher training colleges, universities, institutions of education and research and teacher training normal schools. 4. Law. Refers to LLB, of that this education is attained from a Law College or some arts college. 5. Commerce and Administration. Refers to B.Com (Hon) irrespective of that it is done from special commerce college or degree colleges of arts, commerce colleges or institutes of business administration where other degree courses are offered or such diploma or certificates in public administration, labor administration are offered which are taught in other commerce training institutes, government, or private. Besides, such subjects as accounting, banking, commerce, management and secretariat assistance and secretariats science, etc. 6. Craft Technology and Engineering. Refers to such degree courses of engineering which are offered in engineering universities and engineering colleges. Different technique fields, technical subjects and [Pg. 43] all diploma and certificates of various handicrafts which are offered in technical training institutes for different levels. 7. Medical Refers to MBBS or Dentist. Bachelor of dentists science ( B.D.S) and all such higher degrees or diplomas which are offered in medical colleges, pharmacy, midwifery nursing and different subjects of allopathic medicine are included, the training of which is given in the lower level training institutes. Unum Tib, I Vedic homeopathic course which are offered at related colleges come under this. 8. Agriculture, forestry and fishery. Refers to such degree courses which are offered at agricultural universities or colleges, veterinary colleges. Institutions which give education related to forestry, including the agricultural training institute and agricultural extension institutes, schools of fisheries, forestry, or related training institutes. 9. Other special education: Refers to other degrees, diploma, certificates of special education e.g., construction, drawing, music, calligraphy, sculpture and other arts the education of which is given arts colleges and schools colleges of social welfare education/social work. The courses of Home economics or defense science (i.e., the courses which are offered at staff college or education given in other defense colleges) are included in this category.</div> The enumerator will have to write the special subject of specialized education and its other rule types wherever applicable (e.g., engineering, mechanical, engineering, civil engineering, chemical engineering, meteorology, mining, schools of georgic agriculture and forestry, etc.). Where there is no subtype enter in col. 13 the name of subject (e.g., philosophy, history economics, political science). </svar> Pakistan 1973: Persons age 5+ who ever attended school [discrepancies: type I trace; type II 25.9%] This variable indicates the person's technical area of education. 01 Humanities 02 Education 03 Fine Arts 04 Law 05 Social science 06 Natural sciences 07 Engineering 08 Medical Science 09 Agriculture 10 Veterinary medicine 11 Other specialized education 12 No specialized education 99 NIU (not in universe) Education Variables -- PERSON Worked last week <svar v="PK73A413 PK73A414 PK73A415 PK73A416 PK73A417 PK73A418 PK73A419 PK73A420 PK73A421">Economic characteristics (For persons 10 years of age and above) </svar> <svar v="PK73A413" a="all">15. Did he/she do any work at all last week for pay or profit (for a minimum of 15 hours, if worked as unpaid family helper) or there was a job but did not work). <div class="i1">[] 1 Yes [] 2 No</div> </svar> <svar v="PK73A413" a="all">7.25 For every person (10 years of age and above) of the household whose name has been entered in column-2, it may be asked, did he work during the last week for pay or wages or did he have work, but did not work during last week, or did he work for 15 or more hours as an unpaid family helper, or did he work as an unpaid family helper. Working and had a job but did not work has been defined in Para No.7.6 and 7.7. If responses to these questions are affirmative, then write code-1 in column-15 and get the information about the columns 16-18. If the response is negative, write code-2 and then make an entry in column-17. [Pg. 52] 7.26 The economic status of household members who are temporarily absent may be determined through responses of respondents and examples are given below. <div class="i1">1) If a person of the household has gone out on official tour or business, then it will be considered that he had been working since last week and code-1 will be written in that column. His common profession, industry, business level and weekly working timing will be entered in column 16, 17, 18 and 19. 2) If a person of the household has gone to see his relatives, or on trip or participating in the marriage ceremony and before going there he was working, then he will be considered on work even he did not work last week, the code-1 will be written in that column. His general profession, industry, occupational status will be entered in column 16, 17, 18 but the working hours will be written "NIL" in column 19. 3) If an outgoing person was in search of work before going out then he will not be considered as worker, rather treated as looking for work and code-2 will be entered in that column and code-1 will be entered in column 20. 4) If a person of the household went out for other purpose besides looking for work and before going out he was not working and not in search of work, either he was family helper or under studying then he will neither be considered as worker and nor as looking for work. Code-2 will be entered in that column and in front of him code-5 will be entered in column-20.</div> </svar> Pakistan 1973: Persons age 10+ [discrepancies: type I none; type II 0.1%] This variable indicates whether the person worked last week. Unpaid family helpers who worked at least 15 hours and those who had a job but did not work last week are also listed under having worked last week. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Occupation, 1 digit <svar v="PK73A414 PK73A415 PK73A416 PK73A417 PK73A418 PK73A419">For those who answered yes in Col. 15 </svar> <svar v="PK73A414 PK73A415" a="all">16. What kind of work did he/she do most of the last week? <div class="i1">[Question 16 was asked of persons who had a job last week, per question 15.] (Write title of occupation, e.g. Motor Mechanic, Carpenter, Taxi Driver, Cultivator, etc. ____</div> </svar> <svar v="PK73A414 PK73A415" a="all">7.27 Question No.16 This question will be asked from those persons of the household who are working or had the job but did not work and from those respondents against whom code-1 has been entered in column 15. The respondent may be asked that what type of work he had been doing last week. If he had work but he did not work last week then it will be enquired that what type of work he had but did not work. If the respondent tells that more than one type of work is done and inform his actual [Pg. 53] profession, the work will be written on which most of time was spent. The answer to this question may acquire in such a way that his profession/job may be explained fully. The doubtful and common answers may not be entered. Sometime a worker does not know about name of his job but he can explain that what type of work he is doing. The enumerator has to enter correct nature of job or profession. By writing generally some words (for work) or the name of instruments he is using in job. This goal can be achieved. The ambiguous entries (e.g., employment, labour, driver, conductor, etc.) will not be entered. The following examples will explain how the entries should be made: <div class="i1">"Agent" Tell whether he is a premium agent, commission agent, customer agent or agent of advertisements. "Engineer" Tell whether he is Civil engineer, Mining engineer, Electrical engineer, Chemical engineer, Mechanical engineer, Ship engineer, aeronautical engineer, etc. "Clerk" It may be written whether he is stenographer, typist, cashier, bookkeeper, postman, calculating machine operator, electronic computer operator, train dispatcher, radio, telephone operator, correspondent clerk, insurance clerk, store room clerk, statistical clerk, travel agency clerk, library clerk, proof reader, card and tap punching machine operator, etc. "Manager" It may be written whether he is a restaurant manager, hotel manager, cinema manager, wholesale manager, munshi of lawyer, retailer manager, farm manager, sales manager, and transport manager, etc. "Salesman" Tell whether he is an insurance salesperson, advertising salesperson, wholesale salesperson, retailer salesperson, hawker, or newspaper seller, etc. and also ask whether the laborer of factory is related to spinner, dying worker, cigar /cigarette maker, electro platter or machine maker etc. "Driver" Tell whether he is railway driver, tram driver, taxi driver, bus driver, tonga driver, sailor, driver of unmoved engine, crane operator, lifter, etc. [Pg. 54] "Mechanic" Tell whether he is motor truck driver or cycle motorcycle mechanic; textile mechanic; watch maker; or radio, television, telephone, and telegraph mechanic, etc. "Laborer" Tell whether he is the laborer of train, seaport, sweeper or dry port. "Inspector" Tell whether he is the inspector of health, excise, income tax, police, food or electricity, etc.</div> </svar> Pakistan 1973: Persons age 10+ who worked last week [discrepancies: type I 0.2%; type II 0.3%] This variable indicates the person's occupation (1-digit) last week. 0 NIU (not in universe) 1 Professional, technical and related workers 2 Administrative and managerial workers 3 Clerical and related workers 4 Sales workers 5 Service workers 6 Agricultural, animal husbandry and forestry workers, fishermen and hunters 7 Production and related workers, transport equipment operators and laborers 9 Unknown Work: Occupation Variables -- PERSON Occupation <svar v="PK73A414 PK73A415 PK73A416 PK73A417 PK73A418 PK73A419">For those who answered yes in Col. 15 </svar> <svar v="PK73A414 PK73A415" a="all">16. What kind of work did he/she do most of the last week? <div class="i1">[Question 16 was asked of persons who had a job last week, per question 15.] (Write title of occupation, e.g. Motor Mechanic, Carpenter, Taxi Driver, Cultivator, etc. ____</div> </svar> <svar v="PK73A414 PK73A415" a="all">7.27 Question No.16 This question will be asked from those persons of the household who are working or had the job but did not work and from those respondents against whom code-1 has been entered in column 15. The respondent may be asked that what type of work he had been doing last week. If he had work but he did not work last week then it will be enquired that what type of work he had but did not work. If the respondent tells that more than one type of work is done and inform his actual [Pg. 53] profession, the work will be written on which most of time was spent. The answer to this question may acquire in such a way that his profession/job may be explained fully. The doubtful and common answers may not be entered. Sometime a worker does not know about name of his job but he can explain that what type of work he is doing. The enumerator has to enter correct nature of job or profession. By writing generally some words (for work) or the name of instruments he is using in job. This goal can be achieved. The ambiguous entries (e.g., employment, labour, driver, conductor, etc.) will not be entered. The following examples will explain how the entries should be made: <div class="i1">"Agent" Tell whether he is a premium agent, commission agent, customer agent or agent of advertisements. "Engineer" Tell whether he is Civil engineer, Mining engineer, Electrical engineer, Chemical engineer, Mechanical engineer, Ship engineer, aeronautical engineer, etc. "Clerk" It may be written whether he is stenographer, typist, cashier, bookkeeper, postman, calculating machine operator, electronic computer operator, train dispatcher, radio, telephone operator, correspondent clerk, insurance clerk, store room clerk, statistical clerk, travel agency clerk, library clerk, proof reader, card and tap punching machine operator, etc. "Manager" It may be written whether he is a restaurant manager, hotel manager, cinema manager, wholesale manager, munshi of lawyer, retailer manager, farm manager, sales manager, and transport manager, etc. "Salesman" Tell whether he is an insurance salesperson, advertising salesperson, wholesale salesperson, retailer salesperson, hawker, or newspaper seller, etc. and also ask whether the laborer of factory is related to spinner, dying worker, cigar /cigarette maker, electro platter or machine maker etc. "Driver" Tell whether he is railway driver, tram driver, taxi driver, bus driver, tonga driver, sailor, driver of unmoved engine, crane operator, lifter, etc. [Pg. 54] "Mechanic" Tell whether he is motor truck driver or cycle motorcycle mechanic; textile mechanic; watch maker; or radio, television, telephone, and telegraph mechanic, etc. "Laborer" Tell whether he is the laborer of train, seaport, sweeper or dry port. "Inspector" Tell whether he is the inspector of health, excise, income tax, police, food or electricity, etc.</div> </svar> Pakistan 1973: Persons age 10+ who worked last week [discrepancies: type I 0.2%; type II trace] This variable indicates the person's occupation (3-digit) last week. 011 Chemist 012 Physicists 013 Physical scientists not elsewhere classified 014 Physical science technicians 021 Architects and town planners 022 Civil engineers 023 Electrical and electronics engineers 024 Mechanical engineers including marine and aeronautical engineers 025 Chemical engineers 026 Metallurgists 027 Mining engineers and metallurgical engineers 028 Industrial engineers 029 Engineers not elsewhere classified 030 Surveyors 032 Draughtsman and cartographers including lithographic artists 033 Civil engineering technicians 034 Electrical and electronics engineering technicians 035 Mechanical engineering technicians 036 Chemical engineering technicians 037 Metallurgical technicians 038 Mining technicians 039 Engineering and related technicians not elsewhere classified 041 Aircraft pilots, navigators and flight engineers 042 Ships' deck officers and pilots 043 Ships' engineers 049 Aircraft and ships' officers not elsewhere classified 051 Biologists, zoologists and related scientists 052 Bacteriologists, pharmacologists and related scientists 053 Agronomists and related scientists 054 Life sciences technicians 061 Medical doctors and surgeons 062 Medical assistants 063 Dentists 064 Dental assistants 065 Veterinarians 066 Veterinary assistants 067 Pharmacists 068 Pharmaceutical assistants 069 Dieticians and public health nutritionists 071 Professional nurses 072 Nursing personnel not elsewhere classified 073 Professional midwives 074 Midwifery personnel not elsewhere classified 075 Optometrists and opticians 076 Physiotherapists and occupational therapists 077 Medical X-ray technicians 078 Hakims/veids and homeopathic doctors 079 Medical, dental, veterinary and related workers not elsewhere classified including unregistered medical practitioners 081 Statisticians 082 Mathematicians and actuaries 083 Systems analysts and programmers 084 Statistical and mathematical technicians 090 Economists 110 Accountants and auditors 121 Lawyers 122 Judges 129 Jurists and other related legal occupations not elsewhere classified 131 University and college teachers 132 Secondary education teachers (including technical high school teachers) 133 Primary education teachers 134 Pre-primary education teachers 135 Teachers for education of handicapped 136 Teachers of religious education at all levels 137 Teachers of polytechnics, technical institutes 139 Teachers not elsewhere classified 140 Workers in religion 151 Authors and critics 159 Authors, journalists and related writers not elsewhere 161 Sculptors, painters and related artists 162 Commercial artists and designers 163 Photographers and cameramen 171 Composers, musicians and singers 172 Choreographers and dancers 173 Actors and stage directors 174 Producers (performing arts) 175 Circus performers 179 Performing artists not elsewhere classified 180 Athletes, sportsmen and related workers 191 Librarians, archivists and curators 192 Sociologists, anthropologists and related scientists 193 Social workers (full-time) 194 Personal and occupational specialists 195 Philologists, translators and interpreters 199 Other professional, technical and related workers 201 Governors, ministers and legislators not otherwise occupied (employed) 202 Government administrators and executives 211 Managers, directors and working proprietors mining and quarrying, manufacturing, construction communications, transport utility and sanitary services, excluding wholesale and retail trade and production managers 212 Production managers, except farms 213 Managers, directors and working proprietors of wholesale and retail trade including banks, insurance, real estate and other financial and business services institutions 219 Managers, directors and working proprietors not elsewhere classified 300 General Office supervisors 310 Non-gazette officers in local administration and government 321 Stenographers, typists and teletypists 322 Card and tape punching machine operators 331 Book-keepers, cashiers and related workers 339 Book-keepers, cashiers and related workers not elsewhere classified 341 Office machine operators 342 Automatic data processing machine operators 351 Railway station masters 352 Postmasters 359 Transport and communication supervisors not elsewhere classified 361 Railway passenger and goods train guards 362 Bus and train conductors 363 Inland water transport conductors 371 Postmen and sorters 372 Messengers and mail distribution workers (runners) 380 Tele-communication operators 391 Stock clerks 392 Material and production planning clerks 393 Correspondence and reporting clerks 394 Receptionists and travel agency clerks 395 Library and filing assistants/clerks 396 General clerks including government clerks 399 Clerks and other office workers not elsewhere classified 401 Managers (whole-sale trade) 402 Managers (retail trade) 410 Working proprietors (whole-sale and retail trade) 421 Sales supervisors/representatives 422 Purchasing agents and buyers 431 Technical salesmen and service advisors 432 Commercial travelers and manufacturer's agents/representatives 441 Insurance, real estate and securities salesmen 442 Business and advertising services agents 443 Auctioneers 451 Salesmen, shop assistants and demonstrators 452 Street vendors/canvassers 491 Money lenders and pawn brokers 499 Selling occupation not elsewhere classified 500 Managers (catering and lodging services) 510 Working proprietors (catering and lodging services) 520 Housekeeping and related service supervisors 531 Cooks and chefs 539 Other occupations in cooking, waiting, not elsewhere classified 540 Maids and related housekeeping service workers not elsewhere classified 551 Building caretakers 552 Charworkers, cleaners and related workers 560 Launderers, dry cleaners and pressers (including Dhobies) 570 Hairdressers, barbers, beauticians and related workers 581 Fire fighters 582 Policemen and detectives 589 Prison wardens, security staff, guards and related occupations not elsewhere classified 591 Guides 592 Undertakers and embalmers 599 Other service workers 600 Farm managers and supervisors 611 General farmers 612 Specialized farmers, excluding tea plantation workers 621 General farm workers 622 Field crop and vegetable growing workers 623 Orchard, vine yard and related tree and shrub crop workers except tea plantation workers 624 Live-stock and poultry farm workers 625 Dairy farm workers 626 Tea plantation workers 627 Nursery workers and gardeners including labha workers 628 Farm machinery operators 629 Agricultural and animal husbandry workers not elsewhere classified including bee keeping workers 631 Loggers 632 Forestry workers except loggers 641 Fishermen 642 Hunters, trappers and game wardens 649 Fishermen, hunters and related workers not elsewhere classified 700 Production supervisors and general foremen 711 Miners and quarrymen 712 Mineral and stone treaters 713 Well drillers, borers and related workers 719 Miners, quarrymen, well drillers and related workers including workers extracting gold from river sand 721 Metal smelting, converting and refining workers 722 Metal re-rolling mill workers 723 Metal melters and reheaters 724 Metal casters 725 Metal molders and core makers 726 Metal annealers, temperers and case hardeners 727 Metal drawers and extruders 728 Metal platers and coaters 729 Metal processers not elsewhere classified 731 Wood treaters 732 Sawyers, plywood makers and related wood processing workers 733 Pulp preparers 734 Paper makers 739 Wood preparation occupations not elsewhere classified 741 Crushers, grinders and mixers operators 742 Cookers, roasters and related heat treating machine operators 743 Filter and separator operators 744 Still and reactor operators 745 Petroleum refining workers 749 Chemical processors and related workers not elsewhere classified 751 Fiber preparers 752 Spinners, winders and twisters 753 Weaving and knitting machine setters and pattern-card preparers 754 Weavers and related workers (textile) 755 Knitters 756 Bleachers, dyers and textile product finishers 759 Spinners, weavers, mitters, dyers and related workers not elsewhere classified 761 Tanners and fellmongers 762 Pelt dressers 771 Grain millers, rice huskers and related workers 772 Sugar processors and refiners 773 Butchers and meat preparers 774 Food preservers 775 Dairy product processers 776 Bakers, confectionery and sweetmeat makers 777 Tea, coffee and cocoa preparers 778 Brewers, wine and beverage makers 779 Food and beverage processors not elsewhere classified 781 Tobacco preparers 782 Cigar makers 783 Cigarette makers 784 Bidi makers 789 Tobacco preparers and tobacco product makers not elsewhere classified 791 Tailors and dressmakers 792 Fur tailors and related workers 793 Milliners and hatmakers 794 Patternmakers and cutters 795 Sewers and embroiderers 796 Upholsterers and related workers 799 Tailors, dressmakers, sewers, upholsterers and related workers not elsewhere classified 801 Footwear makers, repairers and cutters not in factory 802 Footwear makers, repairers and cutters in factory 803 Leather goods makers 809 Other manufacturing and repairing occupations in leather products 811 Coopers and cabinet and furniture makers 812 Wood machinists 813 Finishers and polishers (wood) 819 Cabinet makers and related wood workers not elsewhere classified 820 Stone cutters and carvers 831 Blacksmiths, hammersmiths and forging press operators 832 Tool makers, metal pattern makers and metal makers 833 Machine tool setters/operators 834 Metal tool operators 835 Metal grinders, polishers and tool sharpeners 839 Blacksmiths, toolmakers and machine tool operators not elsewhere classified 841 Machinery fitters and machine assemblers 842 Watch, clock and precision instrument makers 843 Motor vehicle mechanics 844 Aircraft engine mechanics 849 Fitters, assemblers and precision instrument makers (except electrical) not elsewhere classified 851 Electrical fitters 852 Electronics fitters 853 Electrical and electronic equipment assemblers 854 Radio and television repairmen 855 Electricians/wiremen 856 Telecommunication (telephone and telegraph) installers 857 Electric linemen and cable jointers 859 Electrical fitters and related electrical and electronics workers not elsewhere classified 861 Broadcasting station operators 862 Sound equipment operators and cinema projectionists 871 Plumbers and pipe fitters 872 Welders and flame cutters 873 Sheet metal workers 874 Structural metal preparers and erectors 880 Jeweler and precious metal workers and engravers 891 Glass formers, cutters, grinders and finishers 892 Potters and related clay abrasive formers 893 Glass and ceramics kilnmen 894 Glass engravers and etchers 895 Glass and ceramics painters and decorators 899 Glass formers, potters and related workers not elsewhere classified 901 Rubber and plastics product makers (except tire makers and tire vulcanisers) 902 Tyre makers and vulcanisers 910 Paper and paperboard product makers 921 Compositors, typesetters and phototypesetters 922 Printing pressmen 923 Stereo-typers and electrotypers 924 Printing engravers (except photo-engravers) 925 Photo-engravers 926 Book binders and related workers 927 Photographic darkroom workers 929 Printers and related workers not elsewhere classified 931 Painters, construction 939 Painters not elsewhere classified 941 Musical instrument makers and tuners 942 Basketry weavers and brush makers 943 Non-metallic mineral product makers 949 Other production and related workers 951 Bricklayers, stonemasons and tile setters 952 Reinforced concreters, cement finishers and terrazzo workers 953 Roofers 954 Carpenters, joiners and parquetry workers 955 Plasterers 956 Insulators 957 Glaziers 959 Construction workers not elsewhere classified 961 Power generating machinery operators 969 Stationary engine and related equipment operators n.e.c. 971 Dokers and fright handlers 972 Riggers and cable splicers 973 Crane and hoist operators 974 Earth-moving and related machinery operators 979 Material handling equipment operators not elsewhere classified 981 Ships deck ratings, barge crews and boatman 982 Ships engine room ratings 983 Railway engine drivers and firemen 984 Railway brakemen, signalmen and shunters 985 Motor vehicle drivers 986 Animal and animal-drawn vehicle drivers 987 Cycle rickshaw drivers and pullers (manual) 989 Transport equipment operators not elsewhere classified 990 Laborers not elsewhere classified 998 Unknown 999 NIU (not in universe) Work: Occupation Variables -- PERSON Industry, 2 digit <svar v="PK73A414 PK73A415 PK73A416 PK73A417 PK73A418 PK73A419">For those who answered yes in Col. 15 </svar> <svar v="PK73A416 PK73A417" a="all">17. What kind of industry or business or service was he/she working in? ____ </svar> <svar v="PK73A416 PK73A417" a="all">7.28 Industry The nature of industry or business is determined by the manufacturing or making of products, which are made in any establishment (i.e., firm, mining, and field) where a man worked, or if he did not work during last week, but he did earlier. If a firm or establishment has more than [Pg. 55] one composition, the nature of industry will be determined by its major produce of its mostly working level. The difference between industry and occupation will be clarified in the following examples. <div class="i1">Example 1 Occupation (Column 16): Agriculture Farmer or Cultivator Nature of Job: Sugar-cane crop, grain crop, fruits and vegetables crop and wheat, rice maize sugar cane, edible/oil seeds etc., also cultivation of fruit and vegetables are included in it. Industry (entry to be made in Col. 17): Agriculture Example 2 Occupation (Column 16): Rearing the Live-stock Nature of Job: The breeding and progeny of cattle whether it is for meet or for wool, fur, etc., and milk and its product will also be included in it. Industry (entry to be made in Col. 17): Breeding and look after of cattle Example 3 Occupation (Column 16): Carpenter Nature of Job: Wooden Furniture Industry (entry to be made in Col. 17): Furniture and artificer in wood work Example 4 Occupation (Column 16): Carpenter Nature of Job: Artifice /making of railway carriage Industry (entry to be made in Col. 17): Railway Transportation Example 5 Occupation (Column 16): Truck Driver Nature of Job: Goods carrier Industry (entry to be made in Col. 17): Transportation, Truck Example 6 Occupation (Column 16): Porter(Coli) (Unskilled laborer who works in food market) Nature of Job: Carrier of goods in wholesale trade of food Industry (entry to be made in Col. 17): Whole sale and retail trade Example 7 Occupation (Column 16): Porter(Coli) (Unskilled laborer who works at a bus stop) Nature of Job: Road Transportation Industry (entry to be made in Col. 17): Transportation Example 8 Occupation (Column 16): Laborer (Mason) (Unskilled laborer who works in construction) Nature of Job: Construction of building Industry (entry to be made in Col. 17): Construction Example 9 Occupation (Column 16): Carpenter (power loomed) Nature of Job: Carpet/machine manufacturing Industry (entry to be made in Col. 17): Carpet/machine manufacturing Example 10 Occupation (Column 16): Carpenter (Maker of agricultural tools) Nature of Job: Manufacturer of agricultural tools Industry (entry to be made in Col. 17): Manufacturing of agricultural tools Example 11 Occupation (Column 16): Salesman Nature of Job: Cloth market, shoes market sweet, departmental store Industry (entry to be made in Col. 17): Wholesale and retail business</div> </svar> Pakistan 1973: Persons age 10+ who worked last week [discrepancies: type I 0.2%; type II 0.3%] This variable indicates the industry (2-digit) the person worked last week. 11 Agriculture, livestock and hunting 12 Forestry and logging 13 Fishing 21 Coal Mining 22 Crude petroleum and natural gas production 23 Metal ore mining 29 Other mining 31 Manufacture of food, beverages and tobacco 32 Textile, wearing apparel and leather industries 33 Manufacture of wood and wood products including furniture 34 Manufacture of paper and paper products, printing and publishing 35 Manufacture of chemicals, chemical products, and products of petroleum, coal, rubber and plastics 36 Manufacture of non-metallic mineral products except petroleum and coal 37 Basic metal industries 38 Manufacture of fabricated metal products, machinery and equipment 39 Other manufacturing and handicrafts 41 Electricity, gas and steam 42 Water works and supply 51 Building construction and related activities 52 Construction of streets, roads, highways and bridges 53 Construction of irrigation and hydroelectric projects 54 Construction of docks and communications projects 59 Construction projects, n.e.c. 61 Wholesale trade 62 Retail trade 63 Restaurants and hotels 71 Transport and storage 72 Communication 81 Financial institutions 82 Insurance 83 Real estate and business services 91 Public administration 92 Sanitary and similar services 93 Social and related community services 94 Recreation and cultural services 95 Personal and household services 96 International and other extra territorial bodies 98 Unknown 99 NIU (not in universe) Work: Industry Variables -- PERSON Work status <svar v="PK73A414 PK73A415 PK73A416 PK73A417 PK73A418 PK73A419">For those who answered yes in Col. 15 </svar> <svar v="PK73A418" a="all">18. Did he/she work as <div class="i1">[] 1 Employer [] 2 Employee [] 3 Self employed [] 4 Unpaid family helper</div> </svar> <svar v="PK73A418" a="all">7.29 Enquire from respondent the status of his employment. The definition of employment is given in sections 7.11 to 7.15. Write code 1 in this column in case of employer, if he/she is employee the code 2, and for self employed code 3 will be entered. If he/she is an unpaid family helper, then code 4 may be written. If a person had work but he did not work last week then enquire from him what was the status of employment when he had work and write the code according to that status. Column 18 Did he/she work as : <div class="i1">1. Employer 2. Employee 3. Self employed 4. Unpaid family helper?</div> 7.30 For instance if a man keeps/hires employees A and B for wages/pay or for their aid farming a cash crop in his own land and his sons C and D worked unpaid in his land and [the man] himself worked then his status will be as employer. The position of A and B will be as employee and C and D will be as unpaid family helper provided both worked more than fifteen hours in last week. If a man works in his own land and he has not hired any employee then his employment status will be self-employed as though his family members are unpaid family helpers for him without any reward. Sometime the enumerator can face difficulty determining [Pg. 57] the level of employment of the people who are working under different employers. However, it should be kept in mind that [if] the employers determine the timing of work of employees then their [the employees] position will be as employee otherwise they will be considered as self-employed. It has been further elaborated in below. <div class="i1">Occupation: Unskilled laborer who works in food market Industry: Trade Nature of job: He works in food market for fixed hours and timing of work is determined by employer Status of Employment: Employee Occupation: Unskilled laborer who works in food market Industry: Transportation Nature of job: The people give him wages for the service of carrying the goods from one place to other or he loads and unloads the goods and his timing has not be determined by anyone he works own his way Status of Employment: Self-employed Occupation: Laborer (Mason) (Unskilled laborer who work in construction) Industry: Construction Nature of job: He works on contract basis and gets wages proportion to work without fixed time Status of Employment: Self-employed Occupation: Laborer (Mason) (Unskilled laborer who work in construction) Industry: Construction Nature of job: His timing of work is fixed by the employer and he has to work within fixed time Status of Employment: Employee Occupation: Porter (Coli) (Unskilled laborer who work in Bus stop) Industry: Transportation Nature of job: He loads/unloads and looks after the luggage of passengers and his timing of laboring is not fixed Status of Employment: Self-employed Occupation: A water carrier (Unskilled laborer who provide water in the houses and shops) Industry: Self-service Nature of job: He provides the water at different houses and shops and he gets laboring according to quantity of water his timing of laboring is not fixed Status of Employment: Self-employed Occupation: A Water carrier (Unskilled laborer who works in construction) Industry: Construction Nature of job: He is employed for providing water in a construction company and his timing of laboring is fixed and he works daily and his work time is compulsory. Status of Employment: Employee </div> </svar> Pakistan 1973: Persons age 10+ who worked last week [discrepancies: type I 0.2%; type II 0.4%] This variable indicates the person's work status (class of worker). 1 Employer 2 Employee 3 Self employed 4 Unpaid family worker 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Hours of work <svar v="PK73A414 PK73A415 PK73A416 PK73A417 PK73A418 PK73A419">For those who answered yes in Col. 15 </svar> <svar v="PK73A419" a="all">19. How many hours did he/she work during the last week? ____ </svar> <svar v="PK73A419" a="all">7.31 Enter the hours here as the respondent worked last week. If a man spent time on more than one jobs, the spending hours as whole on profession/sub-profession will be written here. If a man had job but he did not work last week, the enumerator will has to enter 'NIL' in that case. 7.32 Generally, exaggeration is made in telling the timing of work during the last week while the respondent is working in agriculture or doing his own business, in this case, general response is that he/she has been working from morning to evening. In such case the enumerator should judge the correct time spent by the respondent on his job. The time spent on eating, rest and others matters should not be included in this case (in working time). </svar> Pakistan 1973: Persons age 10+ who worked last week [discrepancies: type I 0.8%; type II 0.4%] This variable indicates the total number of hours the person worked last week. 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 99 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Reason for unemployment <svar v="PK73A420 PK73A421">For those who did not work for pay or profit last week [Questions 20-21.] </svar> <svar v="PK73A420" a="all">20. Was he/she <div class="i1">[] 1 Able to work and looking for work (unemployed) [] 2 Temporarily suspended for 30 days [] 3 Job assured but not started [] 4 Unable to work [] 5 Others</div> </svar> <svar v="PK73A420" a="all">7.33 This question will be asked to those persons for whom code-2 is entered in col-15, it mean that they were neither working nor had the job during last week. <div class="i1">1 Able to work and looking for work If he/she was able to work and looking for work/job 2 Temporarily suspended for 30 days If he/she was suspended for less than 30 days on temporary basis 3 Job assured but work not started If he/she has been assured the job but he did not start the work as yet, provided the interval between assurance and starting work should not be more than 30 days. 4 Unable to work If he/she is unable to work</div> [Pg. 59] <div class="i1">5 Others If he/she is not included in above four categories, rather he/she is house wife/husband, under education, aged, disable, pensioner, property owner, proprietor of agricultural land and doesn't work him/herself. Unpaid family helper who did work for less than 15 hours and assured to get job or performing the duty honorary basis besides his family business elsewhere. Here such people will be entered who are involved in unethical or illegal occupation for instance thief, prostitute, etc.</div> The different terminologies that are used here, have been interpreted/elaborated in sections 7.15 to 7.23 . </svar> Pakistan 1973: Persons age 10+ who did not work last week [discrepancies: type I 0.2%; type II 3.1%] This variable indicates the person's reason for unemployment. 1 Able to work and looking for work (unemployed) 2 Temporarily suspended for 30 days 3 Job assured but work not started 4 Unable to work (age or disability) 5 Others 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Time looking for work (months) <svar v="PK73A420 PK73A421">For those who did not work for pay or profit last week [Questions 20-21.] </svar> <svar v="PK73A421" a="all">(For those who answered yes to number 1 [able to work and looking for work] in column 20 only) 21. How long has he/she been looking for work? Months _ _ </svar> <svar v="PK73A421" a="all">7.34 This question will be enquired to those people who told that they were able to work and looking for job and code 1 was entered in column 20. The man who is unemployed for days and looking for job, his total unemployment tenure will be written in months and years in column 21. This period (of unemployment) will be counted from that time when he was actually in search of a job until the date of survey. If an interval arises during the job searching period, then the latest tenure in which he has been searching for a job should be entered. For instance, [if] a man had a job for more than 14 days or stopped searching for a job and an interval is created between total periods [of unemployment], then in such case the period after the interval until the survey will be entered. It can be explained with an example that A and B are two persons who were employed in same factory and discharged themselves from the job since August 31, 1966. Thereafter they got a job on September 16, 1966 but again their jobs ended/expired on September 26 and September 30, 1966 respectively. In such condition, the period of unemployment of B since October 1, 1966 and of A since September 1, 1966 will be counted. Because A had got the job for less than 29 days this period is not considered unemployment interval. Therefore, counting of his [A's] unemployment period will be considered since September 1, 1966 instead of September 27, 1966 (although he was unemployed on September 27, 1966). </svar> Pakistan 1973: Persons age 10+ who did not work last week [discrepancies: type I 0.2%; type II 41.3%] This variable indicates the time (in months) when the person looked for work. 000 Less than one month 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 58 060 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 78 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 More than 99 months 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Age at first marriage <svar v="PK73A422 PK73A423 PK73A424 PK73A425 PK73A426 PK73A427">Children born (For ever married women only) </svar> <svar v="PK73A422" a="all">22. Age at first marriage Write the age in completed years. <div class="i1">Give actual number, if none put a cross in the relevant column. _ _</div> </svar> <svar v="PK73A422" a="all">8.2 Age at first marriage (Col 22) For a woman who has been entered as married in Col. 6, it will generally be her first marriage, but such a situation may also come up that this marriage is the second, third or more. Similarly the women for whom "widow" or "divorced" has been entered in Col. 6, it could be after her first marriage or she might have married many times before being divorced and now she is "widow" or "divorced" but in Col. 4 the age at which she married the first time will be entered. If some woman had married more than once the ages at other marriages will not be entered. Since it is a touchy and sensitive question, in order to get an accurate answer the enumerators should be polite and humble in asking the question and be careful that the respondent may not get offended due to his minor mistake. The enumerator should adopt the following ways for obtaining this information. If the marital status of a women has been shown, in Col 6, as married then the enumerator (in a proper way) should determine whether this is her only marriage and after it ask this question <div class="i1">1) What was age of Mrs. X/Y when she got married?</div> If the enumerator observes that the present marriage is not her first marriage then the question may be asked, <div class="i1">2) What was the age of Mrs. X/Y when she got married first? (which occurred somewhere else).</div> Similarly if the women is presently entered as widow or divorced then enumerator should try to know that whether it was her only marriage before being widowed or divorced. If it is not the case then the above mentioned question 2 may be asked. The enumerator should try to assess the accurate age which is given by the respondent. According to the existing law since 1960, a woman of less than 14 years age can not be married but sometimes the women get married at age less than fourteen years. Therefore if a [Pg. 63] woman says that she got married at age less than fourteen years then the enumerator should assess the accurate age by asking the related questions. </svar> Pakistan 1973: Ever-married females [discrepancies: type I 0.4%; type II 0.6%] This variable indicates the person's age at first marriage. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 79 79 80 80 82 82 83 83 84 84 85 85 90 90 91 91 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Total male births <svar v="PK73A422 PK73A423 PK73A424 PK73A425 PK73A426 PK73A427">Children born (For ever married women only) </svar> <svar v="PK73A423 PK73A424" a="all">How many sons? <div class="i1">23. Were ever born to you? _ _ 24. Are still alive? _ _</div> </svar> <svar v="PK73A423" a="all">8.3 Children ever born Col 23. The following questions must be asked, the answer of which shall be entered in this column. "How many (total) boys were born to Mr. X/Y?" Total boys means the boys which were born to a women during reproductive age (until the time of enumeration) the still births are not included in this question. The number which is written is this Col. will be only boys born alive irrespective of whether the boys were born during the current marriage or earlier marriages, whether they are alive at present or dead, and whether they were somewhere else at the time the entries were made. </svar> Pakistan 1973: Ever-married females [discrepancies: type I 0.4%; type II 0.6%] This variable indicates the total male children born to the person. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Living male children <svar v="PK73A422 PK73A423 PK73A424 PK73A425 PK73A426 PK73A427">Children born (For ever married women only) </svar> <svar v="PK73A423 PK73A424" a="all">How many sons? <div class="i1">23. Were ever born to you? _ _ 24. Are still alive? _ _</div> </svar> <svar v="PK73A424" a="all">8.4 Number of children who are still living (Col 24) The following questions will be asked in order to know the number of children still living. How many children, out of those born alive, are still living? The boys still living, this will include all laps, who are either member of this household or live far away or nearby this household. The boys from the earlier marriages of women will also be included. </svar> Pakistan 1973: Ever-married females [discrepancies: type I 0.2%; type II 5.3%] This variable indicates the total male children still alive that were born to the person. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Total female births <svar v="PK73A422 PK73A423 PK73A424 PK73A425 PK73A426 PK73A427">Children born (For ever married women only) </svar> <svar v="PK73A425 PK73A426" a="all">How many daughters <div class="i1">25. Were ever born to you? _ _ 26. Are still alive? _ _</div> </svar> <svar v="PK73A425" a="all">8.5 How many girls were born (Col 25) The following questions will be asked to get information in this connection. How many girl born means, all those girls which were born to the woman concerned during her reproductive age until the date of enumeration. Tthis does not include still born girls. The number written in this column will be of girls born alive. They may be from present marriage or from earlier marriages, alive or dead and they might be present or somewhere else on the date entries were made on the questionnaire. </svar> Pakistan 1973: Ever-married females [discrepancies: type I 0.2%; type II 5.5%] This variable indicates the total number of female children born to the person. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Living female children <svar v="PK73A422 PK73A423 PK73A424 PK73A425 PK73A426 PK73A427">Children born (For ever married women only) </svar> <svar v="PK73A425 PK73A426" a="all">How many daughters <div class="i1">25. Were ever born to you? _ _ 26. Are still alive? _ _</div> </svar> <svar v="PK73A426" a="all">8.6 Number of girls still living (Col 26) The following questions will be asked to get this number. How many girls out of total girls born to Mrs. X/Y are still living? The girls still living will include all the girls who are members of this household or who have married and they live with their husbands somewhere else. The girls born from the earlier marriages of the women will also be included. The entries in columns 23 to 26 will be made in digits. If there is no entry in any column put dash for it in the relevant column. </svar> Pakistan 1973: Ever-married females [discrepancies: type I 0.2%; type II 6.3%] This variable indicates the total number of female children still alive that were born to the person. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Period since last baby born alive <svar v="PK73A422 PK73A423 PK73A424 PK73A425 PK73A426 PK73A427">Children born (For ever married women only) </svar> <svar v="PK73A427" a="all">Period since last baby born alive? <div class="i1">Write (in years and months) the period from the date the last live baby was born to the date of enquiry. 27. Years _ _ 28. Months _ _</div> </svar> <svar v="PK73A427" a="all">8.7 Duration since last live birth (Col 27-28) The reason for asking the duration since occurrence of last live birth is to determine the duration spent by a married women after last live birth. This question will be asked from all the women who are married at the moment or widowed or divorced. This question will be asked in such a way. "What is the duration since last live birth of Mrs. X/Y?" This duration actually consists of the period when a last live birth boy or girl occurred to a married women and period will be counted up to the date of enumeration, irrespective of whether he [the child] is alive at the time of enumeration or not and he [the child] is living as a member of the household or living somewhere else. If after the last live birth the women became pregnant and miscarried then this period will not be counted and the duration will be counted from occurrence of last live birth. Intervening duration will be written in completed years or months. If, at the date of enumeration, the age of last live born baby was 5 years and 6 months then this duration will be 5 years seven months. Five will be written in the years box and 7 will be written in the months box. If the age of the baby is less than one year (e.g., 8 months and 10 days), then his age will be considered as 8 months. A dash will be filled in Col. 27 and the digit 8 will be entered in Col. 28. If no baby has ever been born to that woman then a dash will be put in Col. 23-28. </svar> Pakistan 1973: Ever-married females [discrepancies: type I 0.2%; type II 3.2%] This variable indicates the period (in months) since the last live baby was born. 000 Less than one month 001 1 month 002 2 months 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 months or more 999 NIU (not in universe) Fertility and Mortality Variables -- PERSON Person weight Pakistan 1973: All persons This variable indicates the person weight. This is a 2-digit numeric variable with 0 implied decimal places Technical Person Variables -- PERSON