DDI_NGA_2006_GHS_v01_M_v02_A_IPUMS
Minnesota Population Center
2016-04-25
NADA
- Version 02 (May 2018). This version is identical to version 6.4 (April 2016), except for the DDI Document ID and ID Number which were updated.
Documentation of census data and harmonized variables as found in IPUMS-International. The International Household Survey Network (IHSN) contracted IPUMS International for generating DDI and Dublin Core-compliant metadata related to population and housing census datasets from developing countries. The objective was to provide countries with detailed metadata in a format compatible with the DDI standard used by most of these countries, with a view to guarantee the preservation of the data and metadata, and the publishing of metadata.
The intellectual rights (including copyright) for the data and metadata in IPUMS are retained by the countries under a Memorandum of Understanding with the contributing countries. IPUMS-International has distribution rights to the metadata and data. The XML documents generated by this process are viewed as a distribution of the metadata.
Fields edited by the World Bank are: DDI ID and study ID to match World Bank study naming convention, as well as DDI Document Version and Version Description to reflect changes included in version 6.4.
Previous version documented in the World Bank Microdata Library:
- v6.3 (August 2014)
General Household Survey 2006 - IPUMS Subset
GHS 2006 (IPUMS Harmonized Subset)
NGA_2006_GHS_v01_M_v02_A_IPUMS
National Bureau of Statistics
Minnesota Population Center
Minnesota Population Center
(c) Copyright 2006, National Bureau of Statistics and Minnesota Population Center
NADA
National Bureau of Statistics
Population and Housing Census [hh/popcen]
Version 6.4. The datasets contain selected variables from the original census microdata plus harmonized variables from the IPUMS-International database.
In v6.4, the research team continued to carry out improvements to geography, providing harmonized geographic units for the second administrative level for roughly half the countries. More information about IPUMS geography variables is available <a href='https://international.ipums.org/international/geography_variables.shtml'>here</a>. Also, approximately 100 integrated variables were renamed. Affected variables with their current and previous names are listed <a href='https://international.ipums.org/international/resources/misc_docs/renamed_variables_sept2015.pdf'>here</a>. Geography variable also underwent wholesale renaming.
In this update, IPUMS added 19 new samples for Armenia, Austria, Costa Rica, Ethiopia, France, Ghana, Mozambique, Paraguay, Portugal, Puerto Rico, South Africa, and Spain. Ethiopia, Mozambique, and Paraguay were newly added countries to IPUMS. Samples for other countries extend pre-existing series for those countries.
In this version, geographic variables are significantly revised. IPUMS has developed subnational geographies for each country that are consistent over time and have associated GIS shape files. To distinguish the harmonized and unharmonized geographic variables, which will ultimately be available at the first and second administrative levels for most countries, a new, more systematic variable-naming convention have been imposed. The available geographic variables and their old and new names are described <a href='https://international.ipums.org/international/geography_variables.shtml'>here</a>. Further explanation of the new geographic variables and the GIS boundary files is available <a href='https://international.ipums.org/international/geography_gis.shtml'>here</a>.
Technical Household Variables -- HOUSEHOLD
Technical Person Variables -- PERSON
Geography: Global Variables -- HOUSEHOLD
Utilities Variables -- HOUSEHOLD
Dwelling Characteristics Variables -- HOUSEHOLD
Other Household Variables -- HOUSEHOLD
Demographic Variables -- PERSON
Fertility and Mortality Variables -- PERSON
Education Variables -- PERSON
Work Variables -- PERSON
Disability Variables -- PERSON
Geography: M-Z Variables -- HOUSEHOLD
Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD
Constructed Household Variables -- HOUSEHOLD
Constructed Family Interrelationship Variables -- PERSON
Group Quarters Variables -- HOUSEHOLD
Household Economic Variables -- HOUSEHOLD
Other Person Variables -- PERSON
IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.
The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.
Nigeria
National coverage
State
Households and persons
UNITS IDENTIFIED:
- Dwellings: No
- Vacant units: No
- Households: Yes
- Individuals: Yes
- Group quarters: No
- Special populations: No
UNIT DESCRIPTIONS:
- Households: A household consists of a person or a group of persons living together under the same roof or in the same building/compound, who eat from the same pot and recognize themselves as a unit.
- Group quarters: A housing unit occupied largely by persons not related by blood. Examples include school hostels where children from different parents live during the school session, hotels where travelers and holidaymakers or people on business stay for a short period of time. Institutional housing units usually contain more rooms than residential buildings.
Census/enumeration data [cen]
UNITS IDENTIFIED:
- Dwellings: No
- Vacant units: No
- Households: Yes
- Individuals: Yes
- Group quarters: No
- Special populations: No
UNIT DESCRIPTIONS:
- Households: A household consists of a person or a group of persons living together under the same roof or in the same building/compound, who eat from the same pot and recognize themselves as a unit.
- Group quarters: A housing unit occupied largely by persons not related by blood. Examples include school hostels where children from different parents live during the school session, hotels where travelers and holidaymakers or people on business stay for a short period of time. Institutional housing units usually contain more rooms than residential buildings.
MICRODATA SOURCE: National Bureau of Statistics
SAMPLE DESIGN: The sample followed a two-stage, replicated and rotable design in which enumeration areas (EAs) demarcated for the 1991 Population Census served as the primary sampling units and housing units (HUs) as the secondary sampling units. Sixty EAs per state and 30 EAs in the Federal Capital Territory, Abuja were randomly selected. In each EA, 10 households were selected randomly from a list of all households in the EA. In total, 21,900 housing units from 2,190 enumeration areas were included in the sample. The selected EAs were distributed across urban and rural areas.
SAMPLE UNIT: Enumeration area and housing unit
SAMPLE FRACTION: 0.1%
SAMPLE SIZE (person records): 83,700
Face-to-face [f2f]
A single form with eleven sections: A) Housing unit identification and conditions, B)Persons present in the household, C) Usual resident absent, D) Contraceptive prevalence, E) Births in the last 12 months, F) National programme on immunization, G) Child nutrition, H) Deaths in the last 12 months, I) Health, J) Householkd enterprises, and K) Household expenditure.
FIELD WORK PERIOD: March 3, 2007 to March 26, 2007
Weights computed by statistical agency should be used for most types of analysis.
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.
IPUMS International
Minnesota Population Center. Integrated Public Use Microdata Series, International: Version 6.4 [dataset]. Minneapolis: University of Minnesota, 2015. http://doi.org/10.18128/D020.V6.4.
Researchers should also acknowledge the statistical agency that originally produced the data:
Nigeria, National Bureau of Statistics, General Household Survey
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.
NGA2006-H-H
Household records
0
75
NGA2006-P-H
Person records
0
117
Record type
Record type
Record type
Record type
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.
Technical Household Variables -- HOUSEHOLD
IPUMS
Year
Year
Year
Year
Year
1960
1960
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
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
YEAR gives the year in which the census was taken.
Technical Household Variables -- HOUSEHOLD
IPUMS
IPUMS sample identifier
IPUMS sample identifier
IPUMS sample identifier
IPUMS sample identifier
IPUMS sample identifier
32197001
Argentina 1970
32199101
Argentina 1991
32200101
Argentina 2001
32201001
Argentina 2010
32219801
Argentina 1980
40197101
Austria 1971
40198101
Austria 1981
40199101
Austria 1991
40200101
Austria 2001
40201101
Austria 2011
50199101
Bangladesh 1991
50200101
Bangladesh 2001
50201101
Bangladesh 2011
51200101
Armenia 2001
51201101
Armenia 2011
68197601
Bolivia 1976
68199201
Bolivia 1992
68200101
Bolivia 2001
76196001
Brazil 1960
76197001
Brazil 1970
76198001
Brazil 1980
76199101
Brazil 1991
76200001
Brazil 2000
76201001
Brazil 2010
112199901
Belarus 1999
116199801
Cambodia 1998
116200801
Cambodia 2008
120197601
Cameroon 1976
120198701
Cameroon 1987
120200501
Cameroon 2005
124197101
Canada 1971
124198101
Canada 1981
124199101
Canada 1991
124200101
Canada 2001
152196001
Chile 1960
152197001
Chile 1970
152198201
Chile 1982
152199201
Chile 1992
152200201
Chile 2002
156198201
China 1982
156199001
China 1990
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
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
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
250196201
France 1962
250196801
France 1968
250197501
France 1975
250198201
France 1982
250199001
France 1990
250199901
France 1999
250200601
France 2006
250201101
France 2011
275199701
Palestine 1997
275200701
Palestine 2007
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
324198301
Guinea 1983
324199601
Guinea 1996
332197101
Haiti 1971
332198201
Haiti 1982
332200301
Haiti 2003
348197001
Hungary 1970
348198001
Hungary 1980
348199001
Hungary 1990
348200101
Hungary 2001
356198341
India 1983
356198741
India 1987
356199341
India 1993
356199941
India 1999
356200441
India 2004
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
368199701
Iraq 1997
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
376197201
Israel 1972
376198301
Israel 1983
376199501
Israel 1995
380200101
Italy 2001
388198201
Jamaica 1982
388199101
Jamaica 1991
388200101
Jamaica 2001
400200401
Jordan 2004
404196901
Kenya 1969
404197901
Kenya 1979
404198901
Kenya 1989
404199901
Kenya 1999
404200901
Kenya 2009
417199901
Kyrgyz Republic 1999
417200901
Kyrgyz Republic 2009
430197401
Liberia 1974
430200801
Liberia 2008
454198701
Malawi 1987
454199801
Malawi 1998
454200801
Malawi 2008
458197001
Malaysia 1970
458198001
Malaysia 1980
458199101
Malaysia 1991
458200001
Malaysia 2000
466198701
Mali 1987
466199801
Mali 1998
466200901
Mali 2009
484196001
Mexico 1960
484197001
Mexico 1970
484199001
Mexico 1990
484199501
Mexico 1995
484200001
Mexico 2000
484200501
Mexico 2005
484201001
Mexico 2010
496198901
Mongolia 1989
496200001
Mongolia 2000
504198201
Morocco 1982
504199401
Morocco 1994
504200401
Morocco 2004
508199701
Mozambique 1997
508200701
Mozambique 2007
524200101
Nepal 2001
528196001
Netherlands 1960
528197101
Netherlands 1971
528200101
Netherlands 2001
558197101
Nicaragua 1971
558199501
Nicaragua 1995
558200501
Nicaragua 2005
566200621
Nigeria 2006
566200721
Nigeria 2007
566200821
Nigeria 2008
566200921
Nigeria 2009
566201021
Nigeria 2010
586197301
Pakistan 1973
586198101
Pakistan 1981
586199801
Pakistan 1998
591196001
Panama 1960
591197001
Panama 1970
591198001
Panama 1980
591199001
Panama 1990
591200001
Panama 2000
591201001
Panama 2010
600196201
Paraguay 1962
600197201
Paraguay 1972
600198201
Paraguay 1982
600199201
Paraguay 1992
600200201
Paraguay 2002
604199301
Peru 1993
604200701
Peru 2007
608199001
Philippines 1990
608199501
Philippines 1995
608200001
Philippines 2000
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
642197701
Romania 1977
642199201
Romania 1992
642200201
Romania 2002
646199101
Rwanda 1991
646200201
Rwanda 2002
662198001
Saint Lucia 1980
662199101
Saint Lucia 1991
686198801
Senegal 1988
686200201
Senegal 2002
694200401
Sierra Leone 2004
704198901
Vietnam 1989
704199901
Vietnam 1999
704200901
Vietnam 2009
705200201
Slovenia 2002
710199601
South Africa 1996
710200101
South Africa 2001
710200701
South Africa 2007
710201101
South Africa 2011
724198101
Spain 1981
724199101
Spain 1991
724200101
Spain 2001
724201101
Spain 2011
728200801
South Sudan 2008
729200801
Sudan 2008
756197001
Switzerland 1970
756198001
Switzerland 1980
756199001
Switzerland 1990
756200001
Switzerland 2000
764197001
Thailand 1970
764198001
Thailand 1980
764199001
Thailand 1990
764200001
Thailand 2000
792198501
Turkey 1985
792199001
Turkey 1990
792200001
Turkey 2000
800199101
Uganda 1991
800200201
Uganda 2002
804200101
Ukraine 2001
818199601
Egypt 1996
818200601
Egypt 2006
826199101
United Kingdom 1991
826200101
United Kingdom 2001
834198801
Tanzania 1988
834200201
Tanzania 2002
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
854198501
Burkina Faso 1985
854199601
Burkina Faso 1996
854200601
Burkina Faso 2006
858196301
Uruguay 1963
858197501
Uruguay 1975
858198501
Uruguay 1985
858199601
Uruguay 1996
858200621
Uruguay 2006
858201101
Uruguay 2011
862197101
Venezuela 1971
862198101
Venezuela 1981
862199001
Venezuela 1990
862200101
Venezuela 2001
894199001
Zambia 1990
894200001
Zambia 2000
894201001
Zambia 2010
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).
Technical Household Variables -- HOUSEHOLD
IPUMS
Household serial number
Household serial number
Household serial number
Household serial number
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, 2002
Colombia 1993, 2005
Costa Rica 1984, 2000
Cuba 2002
Dominican Republic 1981, 2002, 2010
Ecuador 1990, 2001
Germany 1971
Hungary 1980, 1990, 2001
Jamaica 1982, 1991, 2001
Malaysia 1970, 1991, 2000
Mexico 1995, 1990, 2000, 2005
Nigeria 2006
Panama 2000
Peru 1993, 2007
Portugal 1981, 1991, 2001
Spain 1991
Uruguay 2011
Venezuela 1990, 2001
Vietnam 1989
In 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.
Technical Household Variables -- HOUSEHOLD
IPUMS
Number of person records in the household
Number of person records in the household
Number of person records in the household
Number of person records in the 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.
Technical Household Variables -- HOUSEHOLD
IPUMS
1st subnational geographic level, world [consistent boundaries over time]
1st subnational geographic level, world [consistent boundaries over time]
1st subnational geographic level, world [consistent boundaries over time]
1st subnational geographic level, world [consistent boundaries over time]
1st subnational geographic level, world [consistent boundaries over time]
32002
City of Buenos Aires [Province: Argentina]
32006
Buenos Aires province [Province: Argentina]
32010
Catamarca [Province: Argentina]
32014
Córdoba [Province: Argentina]
32018
Corrientes [Province: Argentina]
32022
Chaco [Province: Argentina]
32026
Chubut [Province: Argentina]
32030
Entre Ríos [Province: Argentina]
32034
Formosa [Province: Argentina]
32038
Jujuy [Province: Argentina]
32042
La Pampa [Province: Argentina]
32046
La Rioja [Province: Argentina]
32050
Mendoza [Province: Argentina]
32054
Misiones [Province: Argentina]
32058
Neuquén [Province: Argentina]
32062
Río Negro [Province: Argentina]
32066
Salta [Province: Argentina]
32070
San Juan [Province: Argentina]
32074
San Luis [Province: Argentina]
32078
Santa Cruz [Province: Argentina]
32082
Santa Fe [Province: Argentina]
32086
Santiago del Estero [Province: Argentina]
32090
Tucumán [Province: Argentina]
32094
Tierra del Fuego [Province: Argentina]
32099
Unknown [Province: Argentina]
40011
Burgenland [State: Austria]
40012
Niederösterreich [State: Austria]
40013
Wien [State: Austria]
40021
Kärnten [State: Austria]
40022
Steiermark [State: Austria]
40031
Oberösterreich [State: Austria]
40032
Salzburg [State: Austria]
40033
Tirol [State: Austria]
40034
Vorarlberg [State: Austria]
50010
Barisal [Division, Bangladesh]
50020
Chittagong [Division, Bangladesh]
50030
Dhaka [Division, Bangladesh]
50040
Khulna [Division, Bangladesh]
50050
Rajshahi, Rangpur [Division, Bangladesh]
50060
Sylhet [Division, Bangladesh]
51901
Yerevan [Province: Armenia]
51902
Aragatsotn [Province: Armenia]
51903
Ararat [Province: Armenia]
51904
Armavir [Province: Armenia]
51905
Gegharkunik [Province: Armenia]
51906
Lori [Province: Armenia]
51907
Kotayk [Province: Armenia]
51908
Shirak [Province: Armenia]
51909
Syunik [Province: Armenia]
51910
Vayots Dzor [Province: Armenia]
51911
Tavush [Province: Armenia]
68001
Chuquisaca [Department: Bolivia]
68002
La Paz [Department: Bolivia]
68003
Cochabamba [Department: Bolivia]
68004
Oruro [Department: Bolivia]
68005
Potosí [Department: Bolivia]
68006
Tarija [Department: Bolivia]
68007
Santa Cruz [Department: Bolivia]
68008
Beni [Department: Bolivia]
68009
Pando [Department: Bolivia]
76011
Rondonia [State: Brazil]
76012
Acre [State: Brazil]
76013
Amazonas [State: Brazil]
76014
Roraima [State: Brazil]
76015
Pará [State: Brazil]
76016
Amapa [State: Brazil]
76021
Maranhao [State: Brazil]
76022
Piauí [State: Brazil]
76023
Ceará [State: Brazil]
76024
Rio Grande do Norte [State: Brazil]
76025
Paraiba [State: Brazil]
76026
Pernambuco [State: Brazil]
76027
Alagoas [State: Brazil]
76028
Sergipe [State: Brazil]
76029
Bahia [State: Brazil]
76031
Minas Gerais [State: Brazil]
76032
Espírito Santo [State: Brazil]
76033
Rio de Janeiro [State: Brazil]
76035
São Paulo [State: Brazil]
76041
Parana [State: Brazil]
76042
Santa Catarina [State: Brazil]
76043
Rio Grande do Sul [State: Brazil]
76051
Mato Grosso, Mato Grosso do Sul [State: Brazil]
76052
Goiás and Tocantins [State: Brazil]
76053
Distrito Federal [State: Brazil]
112001
Brest [Region: Belarus]
112002
Vitebsk [Region: Belarus]
112003
Gomel [Region: Belarus]
112004
Grodno [Region: Belarus]
112006
Minsk [Region: Belarus]
112007
Mogilev [Region: Belarus]
116001
Banteay Meanchey [Province: Cambodia]
116002
Battambang [Province: Cambodia]
116003
Kampong Cham [Province: Cambodia]
116004
Kampong Chhnang [Province: Cambodia]
116005
Kampong Speu [Province: Cambodia]
116006
Kampong Thom [Province: Cambodia]
116007
Kampot [Province: Cambodia]
116008
Kandal [Province: Cambodia]
116009
Koh Kong [Province: Cambodia]
116010
Kratie [Province: Cambodia]
116011
Mondul Kiri [Province: Cambodia]
116012
Phnom Penh [Province: Cambodia]
116013
Preah Vihear [Province: Cambodia]
116014
Prey Veng [Province: Cambodia]
116015
Pursat [Province: Cambodia]
116016
Rotanak Kiri [Province: Cambodia]
116017
Siem Reap and Otdar Meanchey [Province: Cambodia]
116018
Preah Sihanouk [Province: Cambodia]
116019
Stung Treng [Province: Cambodia]
116020
Svay Rieng [Province: Cambodia]
116021
Takeo [Province: Cambodia]
116023
Kep [Province: Cambodia]
116024
Pailin [Province: Cambodia]
120002
Centre, Sud [Province: Cameroon]
120003
Est [Province: Cameroon]
120004
Nord, Adamoua , Extrème Nord [Province: Cameroon]
120005
Littoral [Province: Cameroon]
120007
Nord Ouest [Province: Cameroon]
120008
Ouest [Province: Cameroon]
120010
Sud Ouest [Province: Cameroon]
124010
Newfoundland and Labrador [Province: Canada]
124011
Prince Edward Island, Yukon, Northwest Territories, and Nunavut [Province: Canada]
124012
Nova Scotia [Province: Canada]
124013
New Brunswick [Province: Canada]
124024
Quebec [Province: Canada]
124035
Ontario [Province: Canada]
124046
Manitoba [Province: Canada]
124047
Saskatchewan [Province: Canada]
124048
Alberta [Province: Canada]
124059
British Columbia [Province: Canada]
152002
Antofagasta and Tarapacá [Region: Chile]
152004
Atacama and Coquimbo [Region: Chile]
152007
Del Maule [Region: Chile]
152008
Del Biobio [Region: Chile]
152009
La Araucanía [Region: Chile]
152010
Aysen del Gral Carlos Ibáñez del Campo and Los Lagos [Region: Chile]
152012
Magallanes and La Antártica Chilena [Region: Chile]
152013
Libertador General Bernardo O"Higgins, Metropolitana de Santiago, and Valparaiso [Region: Chile]
152099
Unknown [Region: Chile]
156011
Beijing (municipality) [Province: China]
156012
Tianjin (municipality) [Province: China]
156013
Hebei [Province: China]
156014
Shanxi [Province: China]
156015
Inner Mongolia [Province: China]
156021
Liaoning [Province: China]
156022
Jilin [Province: China]
156023
Heilongjiang [Province: China]
156031
Shanghai (municipality) [Province: China]
156032
Jiangsu [Province: China]
156033
Zhejiang [Province: China]
156034
Anhui [Province: China]
156035
Fujian [Province: China]
156036
Jiangxi [Province: China]
156037
Shangdong [Province: China]
156041
Henan [Province: China]
156042
Hubei [Province: China]
156043
Hunan [Province: China]
156044
Guangdong and Hainan [Province: China]
156045
Guangxi [Province: China]
156051
Sichuan [Province: China]
156052
Guizhou [Province: China]
156053
Yunnan [Province: China]
156054
Tibet [Province: China]
156061
Shaanxi [Province: China]
156062
Gansu [Province: China]
156063
Qinghai [Province: China]
156064
Ningxia [Province: China]
156065
Xinjiang [Province: China]
170005
Antioquia [Department: Colombia]
170008
Atlántico [Department: Colombia]
170011
Bogotá [Department: Colombia]
170013
Bolívar and Sucre [Department: Colombia]
170015
Boyacá and Casanare [Department: Colombia]
170018
Caquetá [Department: Colombia]
170019
Cauca [Department: Colombia]
170023
Córdoba [Department: Colombia]
170025
Cundinamarca [Department: Colombia]
170027
Chocó [Department: Colombia]
170041
Huila [Department: Colombia]
170044
La Guajira [Department: Colombia]
170047
Cesar and Magdalena [Department: Colombia]
170050
Meta and Vichada [Department: Colombia]
170052
Nariño [Department: Colombia]
170054
Norte de Santander [Department: Colombia]
170066
Caldas, Quindío, and Risaralda [Department: Colombia]
170068
Santander [Department: Colombia]
170073
Tolima [Department: Colombia]
170076
Valle [Department: Colombia]
170081
Arauca [Department: Colombia]
170086
Putumayo [Department: Colombia]
170088
San Andrés [Department: Colombia]
170091
Amazonas [Department: Colombia]
170095
Guaviare, Vaupés, and Guainía [Department: Colombia]
188001
San José [Province: Costa Rica]
188002
Alajuela [Province: Costa Rica]
188003
Cartago [Province: Costa Rica]
188004
Heredia [Province: Costa Rica]
188005
Guanacaste [Province: Costa Rica]
188006
Puntarenas [Province: Costa Rica]
188007
Limón [Province: Costa Rica]
192001
Pinar del Río [Province: Cuba]
192002
La Habana [Province: Cuba]
192003
Ciudad de la Habana [Province: Cuba]
192004
Matanzas [Province: Cuba]
192005
Villa Clara [Province: Cuba]
192006
Cienfuegos [Province: Cuba]
192007
Sancti Spiritus [Province: Cuba]
192008
Ciego de Avila [Province: Cuba]
192009
Camagüey [Province: Cuba]
192010
Las Tunas [Province: Cuba]
192011
Holguín [Province: Cuba]
192012
Granma [Province: Cuba]
192013
Santiago de Cuba [Province: Cuba]
192014
Guantánamo [Province: Cuba]
192099
Isla de la Juventud [Province: Cuba]
214001
Federal district and Santo Domingo [Province: Dominican Republic]
214002
Azua [Province: Dominican Republic]
214003
Baoruco [Province: Dominican Republic]
214004
Barahona [Province: Dominican Republic]
214005
Dajabón [Province: Dominican Republic]
214006
Duarte [Province: Dominican Republic]
214007
Elías Piña [Province: Dominican Republic]
214008
El Seibo and Hato Mayor [Province: Dominican Republic]
214009
Espaillat [Province: Dominican Republic]
214010
Independencia [Province: Dominican Republic]
214011
La Altagracia and La Romana [Province: Dominican Republic]
214013
La Vega and Monseñor Nouel [Province: Dominican Republic]
214014
María Trinidad Sánchez and Samaná [Province: Dominican Republic]
214015
Monte Cristi [Province: Dominican Republic]
214016
Pedernales [Province: Dominican Republic]
214017
Peravia and San José de Ocoa [Province: Dominican Republic]
214018
Puerto Plata [Province: Dominican Republic]
214019
Hermanas Mirabal [Province: Dominican Republic]
214021
San Cristóbal and Monte Plata [Province: Dominican Republic]
214022
San Juan [Province: Dominican Republic]
214023
San Pedro de Macorís [Province: Dominican Republic]
214024
Sánchez Ramírez [Province: Dominican Republic]
214025
Santiago [Province: Dominican Republic]
214026
Santiago Rodríguez [Province: Dominican Republic]
214027
Valverde [Province: Dominican Republic]
218001
Azuay [Province: Ecuador]
218002
Bolívar [Province: Ecuador]
218004
Carchi [Province: Ecuador]
218005
Cotopaxi [Province: Ecuador]
218006
Chimborazo [Province: Ecuador]
218007
El Oro [Province: Ecuador]
218009
Cañar, Esmeraldas, Guayas, Manabí, Manga del Cura [Disputed canton], Pichincha, El Piedrero [Disputed canton], Los Ríos, Santa Elena, Santo Domingo de las Tsáchilas, Galápagos [Disputed canton], Pichincha, El Piedrero
218010
Imbabura, Las Golondrinas [Disputed canton] [Disputed canton]
218011
Loja [Province: Ecuador]
218014
Morona Santiago [Province: Ecuador]
218016
Pastaza [Province: Ecuador]
218018
Tungurahua [Province: Ecuador]
218019
Zamora Chinchipe [Province: Ecuador]
218021
Napo, Orellana, Sucumbíos [Province: Ecuador]
218099
Unknown [Province: Ecuador]
222001
Ahuachapán [Department: El Salvador]
222002
Santa Ana [Department: El Salvador]
222003
Sonsonate [Department: El Salvador]
222004
Chalatenango [Department: El Salvador]
222005
La Libertad [Department: El Salvador]
222006
San Salvador [Department: El Salvador]
222007
Cuscatlán [Department: El Salvador]
222008
La Paz [Department: El Salvador]
222009
Cabañas [Department: El Salvador]
222010
San Vicente [Department: El Salvador]
222011
Usulután [Department: El Salvador]
222012
San Miguel [Department: El Salvador]
222013
Morazán [Department: El Salvador]
222014
La Unión [Department: El Salvador]
231001
Tigray [Region: Ethiopia]
231002
Affar [Region: Ethiopia]
231003
Amhara [Region: Ethiopia]
231004
Oromiya [Region: Ethiopia]
231005
Somali [Region: Ethiopia]
231006
Benishangul-Gumz [Region: Ethiopia]
231007
Southern Nations, Nationalities, and People (SNPP) [Region: Ethiopia]
231012
Gambela [Region: Ethiopia]
231013
Harari [Region: Ethiopia]
231014
Addis Ababa [Region: Ethiopia]
231015
Dire Dawa [Region: Ethiopia]
231017
Special region [Region: Ethiopia]
238094
Falkland Islands [Province: Argentina]
239094
South Georgia and South Sandwich Islands [Province: Argentina]
242001
Ba [Province: Fiji]
242003
Bua, Cakaudrove [Province: Fiji]
242006
Kadavu, Lau, Lomaiviti, Rotuma [Province: Fiji]
242007
Macuata [Province: Fiji]
242008
Nadroha [Province: Fiji]
242009
Naitasiri, Rewa [Province: Fiji]
242011
Ra [Province: Fiji]
242014
Serua, Namosi [Province: Fiji]
242015
Tailevu [Province: Fiji]
242099
Ships, unknown [Province: Fiji]
250001
Guadeloupe [Oversea Department, France]
250002
Martinique [Oversea Department, France]
250003
French Guyana [Oversea Department, France]
250004
Réunion Island [Oversea Department, France]
250011
Île-de-France [Region: France]
250021
Champagne-Ardenne [Region: France]
250022
Picardy [Region: France]
250023
Upper Normandy [Region: France]
250024
Centre [Region: France]
250025
Lower Normandy [Region: France]
250026
Burgundy [Region: France]
250031
North Pas-de-Calais [Region: France]
250041
Lorraine [Region: France]
250042
Alsace [Region: France]
250043
Franche-Comté [Region: France]
250052
Loire Valley [Region: France]
250053
Brittany [Region: France]
250054
Poitou-Charentes [Region: France]
250072
Aquitaine [Region: France]
250073
Midi-Pyrénées [Region: France]
250074
Limousin [Region: France]
250082
Rhône-Alpes [Region: France]
250083
Auvergne [Region: France]
250091
Languedoc-Roussillon [Region: France]
250093
Provence-Alpes-Riviera [Region: France]
250094
Corsica [Region: France]
250999
Unknown [Region: France]
275001
Jenin [Governorate: Palestine]
275005
Tubas [Governorate: Palestine]
275010
Tulkarm [Governorate: Palestine]
275015
Nablus [Governorate: Palestine]
275020
Qalqiliya [Governorate: Palestine]
275025
Salfit [Governorate: Palestine]
275030
Ramallah and Al-Bireh [Governorate: Palestine]
275035
Jericho [Governorate: Palestine]
275040
Jerusalem [Governorate: Palestine]
275045
Bethlehem [Governorate: Palestine]
275050
Hebron [Governorate: Palestine]
275055
North Gaza [Governorate: Palestine]
275060
Gaza [Governorate: Palestine]
275065
Deir Al-Balah [Governorate: Palestine]
275070
Khan Yunis [Governorate: Palestine]
275075
Rafah [Governorate: Palestine]
276001
Schleswig-Holstein [State: Germany]
276002
Hamburg [State: Germany]
276003
Niedersachsen [State: Germany]
276004
Bremen [State: Germany]
276005
Nordrhein-Westfalen [State: Germany]
276006
Hessen [State: Germany]
276007
Rheinland-Pfalz [State: Germany]
276008
Baden-Württemberg [State: Germany]
276009
Bayern [State: Germany]
276010
Saarland [State: Germany]
276012
Brandenburg [State: Germany]
276013
Mecklenburg-West Pomerania [State: Germany]
276014
Saxony [State: Germany]
276015
Saxony-Anhalt [State: Germany]
276016
Thuringia [State: Germany]
276017
East Berlin [State: Germany]
276018
West Berlin [State: Germany]
276099
NIU (Not in universe) [State: Germany]
288001
Western [Region: Ghana]
288002
Central [Region: Ghana]
288003
Greater Accra [Region: Ghana]
288004
Volta [Region: Ghana]
288005
Eastern [Region: Ghana]
288006
Ashanti [Region: Ghana]
288007
Brong Ahafo [Region: Ghana]
288008
Northern [Region: Ghana]
288009
Upper East [Region: Ghana]
288010
Upper West [Region: Ghana]
300001
Etolia and Akarnania [Department: Greece]
300003
Viotia [Department: Greece]
300004
Evia [Department: Greece]
300005
Evrytania [Department: Greece]
300006
Fthiotida [Department: Greece]
300007
Fokida [Department: Greece]
300011
Argolida [Department: Greece]
300012
Arkadia [Department: Greece]
300013
Achaia [Department: Greece]
300014
Ilia [Department: Greece]
300015
Korinthia [Department: Greece]
300016
Lakonia [Department: Greece]
300017
Messinia [Department: Greece]
300021
Zakynthos [Department: Greece]
300022
Kerkyra [Department: Greece]
300023
Kefallinia [Department: Greece]
300024
Lefkada [Department: Greece]
300031
Arta [Department: Greece]
300032
Thesprotia [Department: Greece]
300033
Ioannina [Department: Greece]
300034
Preveza [Department: Greece]
300041
Karditsa [Department: Greece]
300042
Larissa [Department: Greece]
300043
Magnissia [Department: Greece]
300044
Trikala [Department: Greece]
300051
Grevena [Department: Greece]
300052
Drama [Department: Greece]
300053
Imathia [Department: Greece]
300054
Thessaloniki [Department: Greece]
300055
Kavala [Department: Greece]
300056
Kastoria [Department: Greece]
300057
Kilkis [Department: Greece]
300058
Kozani [Department: Greece]
300059
Pella [Department: Greece]
300061
Pieria [Department: Greece]
300062
Serres [Department: Greece]
300063
Florina [Department: Greece]
300064
Chalkidiki and Aghion Oros [Department: Greece]
300071
Evros [Department: Greece]
300072
Xanthi [Department: Greece]
300073
Rodopi [Department: Greece]
300081
Dodekanissos [Department: Greece]
300082
Kyklades [Department: Greece]
300083
Lesvos [Department: Greece]
300084
Samos [Department: Greece]
300085
Chios [Department: Greece]
300091
Iraklio [Department: Greece]
300092
Lassithi [Department: Greece]
300093
Rethymno [Department: Greece]
300094
Chania [Department: Greece]
300101
Prefecture of Athens [Department: Greece]
300102
Prefecture of East Attiki [Department: Greece]
300103
Prefecture of West Attiki [Department: Greece]
300104
Prefecture of Pireas [Department: Greece]
324001
Boké [Region: Guinea]
324002
Faranah [Region: Guinea]
324003
Kankan [Region: Guinea]
324004
Kindia, Labe, Mamou [Region: Guinea]
324007
N'zerekore [Region: Guinea]
324008
Conakry [Region: Guinea]
332003
Nord (North) and Nord'est (North East) [Department: Haiti]
332006
Centre (Central), L'Artibonite, Ouest (West), Sud'Est (South East) [Department: Haiti]
332007
Grand'Anse, Nippes, Sud (South) [Department: Haiti]
332009
Nord'Ouest (North West) [Department: Haiti]
356001
Jammu and Kashmir [State: India]
356002
Himachal Pradesh [State: India]
356003
Punjab [State: India]
356004
Chandigarh [State: India]
356006
Haryana [State: India]
356007
Delhi [State: India]
356008
Rajasthan [State: India]
356009
Uttar Pradesh and Uttaranchal [State: India]
356010
Bihar and Jharkhand [State: India]
356011
Sikkim [State: India]
356012
Arunachal Pradesh [State: India]
356013
Nagaland [State: India]
356014
Manipur [State: India]
356015
Mizoram [State: India]
356016
Tripura [State: India]
356017
Meghalaya [State: India]
356018
Assam [State: India]
356019
West Bengal [State: India]
356021
Orissa [State: India]
356023
Chhattisgarh and Madhya Pradesh [State: India]
356024
Gujarat [State: India]
356026
Dadra and Nagar Haveli [State: India]
356027
Maharashtra [State: India]
356028
Andhra Pradesh [State: India]
356029
Karnataka [State: India]
356030
Daman and Diu and Goa [State: India]
356031
Lakshadweep [State: India]
356032
Kerala [State: India]
356033
Tamil Nadu [State: India]
356034
Pondicherry [State: India]
356035
Andaman and Nicobar Islands [State: India]
360011
Nanggroe Aceh Darussalam [Province: Indonesia]
360012
Sumatera Utara [Province: Indonesia]
360013
Sumatera Barat [Province: Indonesia]
360014
Riau and Kepulauan Riau [Province: Indonesia]
360015
Jambi [Province: Indonesia]
360016
Sumatera Selatan and Bangka Belitung [Province: Indonesia]
360017
Bengkulu [Province: Indonesia]
360018
Lampung [Province: Indonesia]
360031
DKI Jakarta [Province: Indonesia]
360032
West Java and Banten [Province: Indonesia]
360033
Jawa Tengah [Province: Indonesia]
360034
DI Yogyakarta [Province: Indonesia]
360035
Jawa Timur [Province: Indonesia]
360051
Bali [Province: Indonesia]
360052
Nusa Tenggara Barat [Province: Indonesia]
360053
East Nusa Tenggara [Province: Indonesia]
360061
Kalimantan Barat [Province: Indonesia]
360062
Kalimantan Tengah [Province: Indonesia]
360063
Kalimantan Selatan [Province: Indonesia]
360064
Kalimantan Timur [Province: Indonesia]
360071
Sulawesi Utara and Gorontalo [Province: Indonesia]
360072
Sulawesi Tengah [Province: Indonesia]
360073
Sulawesi Selatan, Sulawesi Tenggara and Sulawesi Barat [Province: Indonesia]
360081
Maluku and Maluku Utara [Province: Indonesia]
360094
Papua and Papua Barat [Province: Indonesia]
364000
Markazi [Province: Iran]
364001
Gilan [Province: Iran]
364002
Mazandaran [Province: Iran]
364003
East Azarbayejan [Province: Iran]
364004
West Azarbayejan [Province: Iran]
364005
Kermanshah [Province: Iran]
364006
Khuzestan [Province: Iran]
364007
Fars [Province: Iran]
364008
Kerman [Province: Iran]
364009
Khorasan-e- Razavi [Province: Iran]
364010
Esfahan [Province: Iran]
364011
Sistan and Baluchestan [Province: Iran]
364012
Kordestan [Province: Iran]
364013
Hamedan [Province: Iran]
364014
Chaharmahal and Bakhtiyari [Province: Iran]
364015
Lorestan [Province: Iran]
364016
Ilam [Province: Iran]
364017
Kohgiluyeh and Boyerahmad [Province: Iran]
364018
Bushehr [Province: Iran]
364019
Zanjan [Province: Iran]
364020
Semnan [Province: Iran]
364021
Yazd [Province: Iran]
364022
Hormozgan [Province: Iran]
364023
Tehran [Province: Iran]
364024
Ardebil [Province: Iran]
364025
Qom [Province: Iran]
364026
Qazvin [Province: Iran]
364027
Golestan [Province: Iran]
364028
North Khorasan [Province: Iran]
364029
South Khorasan [Province: Iran]
368011
Dhok [Governorate: Iraq]
368012
Nineveh [Governorate: Iraq]
368013
Al-Sulaimaniya [Governorate: Iraq]
368014
Al-Tameem [Governorate: Iraq]
368015
Arbil [Governorate: Iraq]
368021
Diala [Governorate: Iraq]
368022
Al-Anbar [Governorate: Iraq]
368023
Baghdad [Governorate: Iraq]
368024
Babylon [Governorate: Iraq]
368025
Kerbela [Governorate: Iraq]
368026
Wasit [Governorate: Iraq]
368027
Salah Al-Deen [Governorate: Iraq]
368028
Al-Najaf [Governorate: Iraq]
368031
Al-Qadisiya [Governorate: Iraq]
368032
Al-Muthanna [Governorate: Iraq]
368033
Thi-Qar [Governorate: Iraq]
368034
Maysan [Governorate: Iraq]
368035
Al-Basrah [Governorate: Iraq]
372001
Border [Region: Ireland]
372002
Dublin [Region: Ireland]
372003
Mid-East [Region: Ireland]
372004
Midlands [Region: Ireland]
372005
Mid-West [Region: Ireland]
372006
South-East [Region: Ireland]
372007
South-West [Region: Ireland]
372008
West [Region: Ireland]
376001
Jerusalem [District: Israel]
376002
Northern [District: Israel]
376003
Haifa [District: Israel]
376004
Central [District: Israel]
376005
Tel-Aviv [District: Israel]
376006
Southern [District: Israel]
376009
Judea, Samaria, and Gaza areas [District: Israel]
380001
Piemonte-Valle d'Aosta [Region: Italy]
380003
Lombardia [Region: Italy]
380004
Trentino-Alto Adige [Region: Italy]
380005
Veneto [Region: Italy]
380006
Friuli-Venezia Giulia [Region: Italy]
380007
Liguria [Region: Italy]
380008
Emilia-Romagna [Region: Italy]
380009
Toscana [Region: Italy]
380010
Umbria [Region: Italy]
380011
Marche [Region: Italy]
380012
Lazio [Region: Italy]
380013
Abruzzo [Region: Italy]
380014
Molise [Region: Italy]
380015
Campania [Region: Italy]
380016
Puglia [Region: Italy]
380017
Basilicata [Region: Italy]
380018
Calabria [Region: Italy]
380019
Sicilia [Region: Italy]
380020
Sardegna [Region: Italy]
388001
Kingston [Parish: Jamaica]
388002
Saint Andrew [Parish: Jamaica]
388003
Saint Thomas [Parish: Jamaica]
388004
Portland [Parish: Jamaica]
388005
Saint Mary [Parish: Jamaica]
388006
Saint Ann [Parish: Jamaica]
388007
Trelawny [Parish: Jamaica]
388008
Saint James [Parish: Jamaica]
388009
Hanover [Parish: Jamaica]
388010
Westmoreland [Parish: Jamaica]
388011
Saint Elizabeth [Parish: Jamaica]
388012
Manchester [Parish: Jamaica]
388013
Clarendon [Parish: Jamaica]
388014
Saint Catherine [Parish: Jamaica]
400011
Amman [Governorate: Jordan]
400012
Balqa [Governorate: Jordan]
400013
Zarqa [Governorate: Jordan]
400014
Madaba [Governorate: Jordan]
400021
Irbid [Governorate: Jordan]
400022
Mafraq [Governorate: Jordan]
400023
Jarash [Governorate: Jordan]
400024
Ajlun [Governorate: Jordan]
400031
Karak [Governorate: Jordan]
400032
Tafilah [Governorate: Jordan]
400033
Ma'an [Governorate: Jordan]
400034
Aqaba [Governorate: Jordan]
404001
Nairobi [Province: Kenya]
404002
Central Province [Province: Kenya]
404003
Coast Province [Province: Kenya]
404004
Eastern Province [Province: Kenya]
404005
North-Eastern Province [Province: Kenya]
404006
Nyanza Province [Province: Kenya]
404007
Rift Valley Province [Province: Kenya]
404008
Western Province [Province: Kenya]
417001
Gorkenesh Bishkek [Region: Kyrgyz Republic]
417002
Issyk-Kul [Region: Kyrgyz Republic]
417003
Dzhalal-Abad [Region: Kyrgyz Republic]
417004
Naryn [Region: Kyrgyz Republic]
417005
Batken [Region: Kyrgyz Republic]
417006
Oshskaya [Region: Kyrgyz Republic]
417007
Talasskaya [Region: Kyrgyz Republic]
417008
Chuya [Region: Kyrgyz Republic]
430006
Bong [County: Liberia]
430009
Grand Bassa and Rivercess [County: Liberia]
430012
Grand Cape Mount [County: Liberia]
430015
Grand Gedeh and River Gee [County: Liberia]
430021
Lofa and Gbarpolu [County: Liberia]
430027
Maryland and Grand Kru [County: Liberia]
430030
Montserrado, Bomi, and Margibi [County: Liberia]
430033
Nimba [County: Liberia]
430039
Sinoe [County: Liberia]
454101
Chitipa [District: Malawi]
454102
Karonga [District: Malawi]
454103
Nkhata Bay, Likoma [District: Malawi]
454104
Rumphi [District: Malawi]
454105
Mzimba, Mzuzu city [District: Malawi]
454201
Kasungu [District: Malawi]
454202
Nkhota Kota [District: Malawi]
454203
Ntchisi [District: Malawi]
454204
Dowa [District: Malawi]
454205
Salima [District: Malawi]
454206
Lilongwe [District: Malawi]
454207
Mchinji [District: Malawi]
454208
Dedza [District: Malawi]
454209
Ntcheu [District: Malawi]
454301
Mangochi [District: Malawi]
454302
Machinga [District: Malawi]
454303
Zomba [District: Malawi]
454304
Chiradzulu [District: Malawi]
454305
Blantyre [District: Malawi]
454307
Thyolo [District: Malawi]
454308
Mulanje [District: Malawi]
454310
Chikwawa [District: Malawi]
454311
Nsanje [District: Malawi]
454313
Mwanza, Neno [District: Malawi]
458001
Johor [State: Malaysia]
458002
Kedah [State: Malaysia]
458003
Kelantan [State: Malaysia]
458004
Melaka [State: Malaysia]
458005
Negeri Sembilan [State: Malaysia]
458006
Pahang [State: Malaysia]
458007
Pulau Pinang [State: Malaysia]
458008
Perak [State: Malaysia]
458009
Perlis [State: Malaysia]
458010
Selangor and Kuala Lumpur Federal Territory [State: Malaysia]
458011
Terengganu [State: Malaysia]
458012
Sabah and Labuan Federal Territory [State: Malaysia]
458013
Sarawak [State: Malaysia]
466001
Kayes [Region: Mali]
466002
Koulikoro [Region: Mali]
466003
Sikasso [Region: Mali]
466004
Ségou [Region: Mali]
466005
Mopti [Region: Mali]
466006
Tombouctou [Region: Mali]
466007
Gao and Kidal [Region: Mali]
466009
Bamako [Region: Mali]
466099
Unknown [Region: Mali]
484001
Aguascalientes [State: Meico]
484002
Baja California [State: Meico]
484003
Baja California Sur [State: Meico]
484004
Campeche [State: Meico]
484005
Coahuila [State: Meico]
484006
Colima [State: Meico]
484007
Chiapas [State: Meico]
484008
Chihuahua [State: Meico]
484009
Distrito Federal [State: Meico]
484010
Durango [State: Meico]
484011
Guanajuato [State: Meico]
484012
Guerrero [State: Meico]
484013
Hidalgo [State: Meico]
484014
Jalisco [State: Meico]
484015
México [State: Meico]
484016
Michoacán [State: Meico]
484017
Morelos [State: Meico]
484018
Nayarit [State: Meico]
484019
Nuevo León [State: Meico]
484020
Oaxaca [State: Meico]
484021
Puebla [State: Meico]
484022
Querétaro [State: Meico]
484023
Quintana Roo [State: Meico]
484024
San Luis Potosí [State: Meico]
484025
Sinaloa [State: Meico]
484026
Sonora [State: Meico]
484027
Tabasco [State: Meico]
484028
Tamaulipas [State: Meico]
484029
Tlaxcala [State: Meico]
484030
Veracruz [State: Meico]
484031
Yucatán [State: Meico]
484032
Zacatecas [State: Meico]
496001
Arkhangai [Province: Mongolia]
496002
Bayan-Ölgii [Province: Mongolia]
496003
Bayankhongor [Province: Mongolia]
496004
Bulgan [Province: Mongolia]
496005
Govi-Altai [Province: Mongolia]
496006
Dornogovi [Province: Mongolia]
496007
Dornod [Province: Mongolia]
496008
Dundgovi and Govisumber [Province: Mongolia]
496009
Zavkhan [Province: Mongolia]
496010
Övörkhangai [Province: Mongolia]
496011
Ömnögovi [Province: Mongolia]
496012
Sükhbaatar [Province: Mongolia]
496013
Selenge [Province: Mongolia]
496014
Töv [Province: Mongolia]
496015
Uvs [Province: Mongolia]
496016
Khovd [Province: Mongolia]
496017
Khövsgöl [Province: Mongolia]
496018
Khentii [Province: Mongolia]
496019
Darkhan-Uul [Province: Mongolia]
496020
Ulaanbaatar [Province: Mongolia]
496021
Orkhon [Province: Mongolia]
504001
Oued-Ed-Dahab-Lagouira [Region: Morocco]
504002
Laâyoune-Boujdour-Sakia El Hamra [Region: Morocco]
504003
Guelmin-Es-Samara [Region: Morocco]
504004
Souss-Massa-Draâ [Region: Morocco]
504005
Charb-Chrarda-Béni Hssen [Region: Morocco]
504006
Chaouia-Ouardigha [Region: Morocco]
504007
Marrakech-Tensift-Al Haouz [Region: Morocco]
504008
Oriental [Region: Morocco]
504009
Grand-Casablanca [Region: Morocco]
504010
Rabat-Salé-Zemmour-Zaer [Region: Morocco]
504011
Doukala Abda [Region: Morocco]
504012
Tadla Azilal [Region: Morocco]
504013
Meknès-Tafilalet [Region: Morocco]
504014
Fès-Boulemane [Region: Morocco]
504015
Taza-Al Heiceima-Taounate [Region: Morocco]
504016
Tanger-Tétouan [Region: Morocco]
508001
Niassa [Province: Mozambique]
508002
Cabo Delgado [Province: Mozambique]
508003
Nampula [Province: Mozambique]
508004
Zambézia [Province: Mozambique]
508005
Tete [Province: Mozambique]
508006
Manica [Province: Mozambique]
508007
Sofala [Province: Mozambique]
508008
Inhambane [Province: Mozambique]
508009
Gaza [Province: Mozambique]
508010
Maputo province [Province: Mozambique]
508011
Maputo city [Province: Mozambique]
524001
Mechi [Administrative zone: Nepal]
524002
Koshi [Administrative zone: Nepal]
524003
Sagarmatha [Administrative zone: Nepal]
524004
Janakpur [Administrative zone: Nepal]
524005
Bagmati [Administrative zone: Nepal]
524006
Narayani [Administrative zone: Nepal]
524007
Gandaki [Administrative zone: Nepal]
524008
Dhawalagiri [Administrative zone: Nepal]
524009
Lumbini [Administrative zone: Nepal]
524010
Rapti [Administrative zone: Nepal]
524011
Bheri [Administrative zone: Nepal]
524012
Karnali [Administrative zone: Nepal]
524013
Seti [Administrative zone: Nepal]
524014
Mahakali [Administrative zone: Nepal]
558005
Nueva Segovia [Department: Nicaragua]
558010
Jinotega [Department: Nicaragua]
558020
Madríz [Department: Nicaragua]
558030
Chinandega [Department: Nicaragua]
558035
Leon and Esteli [Department: Nicaragua]
558040
Matagalpa [Department: Nicaragua]
558050
Boaco [Department: Nicaragua]
558055
Managua [Department: Nicaragua]
558060
Masaya [Department: Nicaragua]
558065
Chontales [Department: Nicaragua]
558070
Granada [Department: Nicaragua]
558075
Carazo [Department: Nicaragua]
558080
Rivas [Department: Nicaragua]
558085
Río San Juan [Department: Nicaragua]
558093
Atlántico Norte and Atlántico Sur [Department: Nicaragua]
558099
Unknown [Department: Nicaragua]
566001
Abia [State: Nigeria]
566002
Adamawa [State: Nigeria]
566003
Akwa Ibom [State: Nigeria]
566004
Anambra [State: Nigeria]
566005
Bauchi [State: Nigeria]
566006
Bayelsa [State: Nigeria]
566007
Benue [State: Nigeria]
566008
Borno [State: Nigeria]
566009
Cross River [State: Nigeria]
566010
Delta [State: Nigeria]
566011
Ebonyi [State: Nigeria]
566012
Edo [State: Nigeria]
566013
Ekiti [State: Nigeria]
566014
Enugu [State: Nigeria]
566015
Gombe [State: Nigeria]
566016
Imo [State: Nigeria]
566017
Jigawa [State: Nigeria]
566018
Kaduna [State: Nigeria]
566019
Kano [State: Nigeria]
566020
Katsina [State: Nigeria]
566021
Kebbi [State: Nigeria]
566022
Kogi [State: Nigeria]
566023
Kwara [State: Nigeria]
566024
Lagos [State: Nigeria]
566025
Nasarawa [State: Nigeria]
566026
Niger [State: Nigeria]
566027
Ogun [State: Nigeria]
566028
Ondo [State: Nigeria]
566029
Osun [State: Nigeria]
566030
Oyo [State: Nigeria]
566031
Plateau [State: Nigeria]
566032
Rivers [State: Nigeria]
566033
Sokoto [State: Nigeria]
566034
Taraba [State: Nigeria]
566035
Yobe [State: Nigeria]
566036
Zamfara [State: Nigeria]
566037
Federal Capital Territory Abuja [State: Nigeria]
566099
Unknown [State: Nigeria]
586001
North-West Frontier Province [Province: Pakistan]
586002
Fata [Province: Pakistan]
586003
Punjab, Islamabad [Province: Pakistan]
586004
Sind [Province: Pakistan]
586005
Baluchistan [Province: Pakistan]
586007
Northern areas [Province: Pakistan]
586008
Kashmir [Province: Pakistan]
591002
Coclé [Province: Panama]
591003
Colón, Comarca Kuna Yala (San Blas) [Province: Panama]
591004
Bocas de Toro, Chiriquí, Comarca Ngäbe Buglé, Veraguas [Province: Panama]
591005
Comarca Emberá, Darién [Province: Panama]
591006
Herrera [Province: Panama]
591007
Los Santos [Province: Panama]
591008
Panamá [Province: Panama]
600000
Asunción [Department: Paraguay]
600001
Concepción [Department: Paraguay]
600002
San Pedro [Department: Paraguay]
600007
Itapúa [Department: Paraguay]
600008
Misiones and Ñeembucú [Department: Paraguay]
600009
Guairá, Caazapá, and Paraguarí [Department: Paraguay]
600010
Cordillera, Caaguazú, Alto Paraná, and Canindeyú [Department: Paraguay]
600011
Central [Department: Paraguay]
600013
Amambay [Department: Paraguay]
600015
Presidente Hayes, Boqueron, and Alto Paraguay [Department: Paraguay]
600099
Unknown [Department: Paraguay]
604001
Amazonas [Region: Peru]
604002
Ancash [Region: Peru]
604003
Apurímac [Region: Peru]
604004
Arequipa [Region: Peru]
604005
Ayacucho [Region: Peru]
604006
Cajamarca [Region: Peru]
604007
Callao [Region: Peru]
604008
Cusco [Region: Peru]
604009
Huancavelica [Region: Peru]
604010
Huánuco [Region: Peru]
604011
Ica [Region: Peru]
604012
Junín [Region: Peru]
604013
La Libertad [Region: Peru]
604014
Lambayeque [Region: Peru]
604015
Lima [Region: Peru]
604016
Loreto [Region: Peru]
604017
Madre de Dios [Region: Peru]
604018
Moquegua [Region: Peru]
604019
Pasco [Region: Peru]
604020
Piura [Region: Peru]
604021
Puno [Region: Peru]
604022
San Martín [Region: Peru]
604023
Tacna [Region: Peru]
604024
Tumbes [Region: Peru]
604025
Ucayali [Region: Peru]
608001
Ilocos [Region: Philippines]
608002
Cagayan Valley [Region: Philippines]
608003
Central Luzon [Region: Philippines]
608004
Southern Tagalog [Region: Philippines]
608005
Bicol [Region: Philippines]
608006
Western Visayas [Region: Philippines]
608007
Central Visayas [Region: Philippines]
608008
Eastern Visayas [Region: Philippines]
608009
Western Mindanao [Region: Philippines]
608011
Northern Mindanao, Southern Mindanao, and Caraga [Region: Philippines]
608012
Central Mindanao and Autonomous Region of Muslim Mindanao [Region: Philippines]
608013
National Capital Region [Region: Philippines]
608014
Cordillera Administrative Region [Region: Philippines]
620111
Minho-Lima [Subregion: Portugal]
620112
Cávado [Subregion: Portugal]
620113
Ave [Subregion: Portugal]
620114
Grande Porto [Subregion: Portugal]
620115
Tâmega [Subregion: Portugal]
620116
Entre Douro e Vouga [Subregion: Portugal]
620117
Douro [Subregion: Portugal]
620118
Alto Trás-os-Montes [Subregion: Portugal]
620150
Algarve [Subregion: Portugal]
620161
Baixo Vouga [Subregion: Portugal]
620162
Baixo Mondego [Subregion: Portugal]
620163
Pinhal Litoral [Subregion: Portugal]
620165
Dão-Lafões [Subregion: Portugal]
620166
Oeste [Subregion: Portugal]
620167
Médio Tejo [Subregion: Portugal]
620169
Other Center [Subregion: Portugal]
620171
Grande Lisboa [Subregion: Portugal]
620172
Península de Setúbal [Subregion: Portugal]
620185
Lezíria do Tejo [Subregion: Portugal]
620189
Other Alentejo [Subregion: Portugal]
620200
Região Autónoma dos Açores [Subregion: Portugal]
620300
Região Autónoma da Madeira [Subregion: Portugal]
630101
G7201001 [PUMA: Puerto Rico]
630104
G7201002, G7201003, G7201004 [PUMA: Puerto Rico]
630110
G7201100 [PUMA: Puerto Rico]
630180
G7201800 [PUMA: Puerto Rico]
630200
G7200100, G7200200, G7200300, G7200400, G7200500, G72000700, G7201200, G7201300, G7201400, G7201500, G7201600, G7201700, G7201900, G7202000, G7202100, G7202200, G7202300, G7202400, G7202600, G7200600, G7200801, G7200802, G7200900 [PUMA: Puerto Rico]
630250
G7202500 [PUMA: Puerto Rico]
642001
Alba [County: Romania]
642002
Arad [County: Romania]
642003
Arges [County: Romania]
642004
Bacau [County: Romania]
642005
Bihor [County: Romania]
642006
Bistrita Nasaud [County: Romania]
642007
Botosani [County: Romania]
642008
Brasov [County: Romania]
642009
Braila [County: Romania]
642010
Buzau [County: Romania]
642011
Caras Severin [County: Romania]
642012
Cluj [County: Romania]
642013
Constanta [County: Romania]
642014
Covasna [County: Romania]
642015
Dimbovita [County: Romania]
642016
Dolj [County: Romania]
642017
Galati [County: Romania]
642018
Gorj [County: Romania]
642019
Harghita [County: Romania]
642020
Hunedoara [County: Romania]
642022
Iasi [County: Romania]
642024
Maramures [County: Romania]
642025
Mehedinti [County: Romania]
642026
Mures [County: Romania]
642027
Neamt [County: Romania]
642028
Olt [County: Romania]
642029
Prahova [County: Romania]
642030
Satu Mare [County: Romania]
642031
Salaj [County: Romania]
642032
Sibiu [County: Romania]
642033
Suceava [County: Romania]
642034
Teleorman [County: Romania]
642035
Timis [County: Romania]
642036
Tulcea [County: Romania]
642037
Vaslui [County: Romania]
642038
Valcea [County: Romania]
642039
Vrancea [County: Romania]
642043
Bucharest Sector 1 to 6 [County: Romania]
642051
Calarasi, Giurgiu, Ialomita, Ilfov [County: Romania]
646001
Kigali City [Province: Rwanda]
646002
Kigali Ngali [Province: Rwanda]
646004
Gitarama [Province: Rwanda]
646005
Butare [Province: Rwanda]
646006
Gikongoro [Province: Rwanda]
646007
Cyangugu [Province: Rwanda]
646008
Kibuye [Province: Rwanda]
646009
Gisenyi [Province: Rwanda]
646010
Ruhengeri [Province: Rwanda]
646012
Byumba, Kibungo and Umutara [Province: Rwanda]
686001
Dakar [Region: Senegal]
686002
Diourbel [Region: Senegal]
686003
Fatick [Region: Senegal]
686004
Kaolack [Region: Senegal]
686005
Kolda [Region: Senegal]
686008
Louga, Saint Louis, Matam [Region: Senegal]
686009
Tambacounda [Region: Senegal]
686010
Thiès [Region: Senegal]
686011
Ziguinchor [Region: Senegal]
694011
Kailahun [District: Sierra Leone]
694012
Kenema [District: Sierra Leone]
694013
Kono [District: Sierra Leone]
694021
Bombali [District: Sierra Leone]
694022
Kambia [District: Sierra Leone]
694023
Koinadugu [District: Sierra Leone]
694024
Port Loko [District: Sierra Leone]
694025
Tonkolili [District: Sierra Leone]
694031
Bo [District: Sierra Leone]
694032
Bonthe [District: Sierra Leone]
694033
Moyamba [District: Sierra Leone]
694034
Pujehun [District: Sierra Leone]
694041
Western - rural [District: Sierra Leone]
694042
Western - urban [District: Sierra Leone]
704001
Ninh Binh, Hoa Binh, Ha Noi, Phu Tho, Vinh Phuc, Ha Nam, and Nam Dinh [Province: Vietnam]
704002
Ha Giang and Tuyen Quang [Province: Vietnam]
704004
Cao Bang [Province: Vietnam]
704014
Son La [Province: Vietnam]
704015
Lai Chau, Dien Bien, Lao Cai, and Yen Bai [Province: Vietnam]
704019
Bac Kan and Thai Nguyen [Province: Vietnam]
704020
Lang Son [Province: Vietnam]
704022
Quang Ninh [Province: Vietnam]
704024
Bac Giang, and Bac Ninh [Province: Vietnam]
704030
Hai Duong and Hung Yen [Province: Vietnam]
704031
Hai Phong [Province: Vietnam]
704034
Thai Binh [Province: Vietnam]
704038
Thanh Hoa [Province: Vietnam]
704040
Nghe An and Ha Tinh [Province: Vietnam]
704046
Quang Binh, Quang Tri, and Thua Thien - Hue [Province: Vietnam]
704049
Da Nang and Quang Nam [Province: Vietnam]
704051
Binh Dinh and Quang Ngai [Province: Vietnam]
704054
Phu Yen and Khanh Hoa [Province: Vietnam]
704060
Thuan Hai, Ninh Thuan, and Binh Thuan [Province: Vietnam]
704062
Gia Lai and Kon Tum [Province: Vietnam]
704066
Dak Lak and Dak Nong [Province: Vietnam]
704068
Lam Dong [Province: Vietnam]
704072
Tay Ninh [Province: Vietnam]
704074
Binh Duong and Binh Phuoc [Province: Vietnam]
704075
Dong Nai and Ba Ria - Vung Tau [Province: Vietnam]
704079
Ho Chi Minh City [Province: Vietnam]
704080
Long An [Province: Vietnam]
704082
Tien Giang [Province: Vietnam]
704083
Ben Tre [Province: Vietnam]
704086
Vinh Long and Tra Vinh [Province: Vietnam]
704087
Dong Thap [Province: Vietnam]
704089
An Giang [Province: Vietnam]
704091
Kien Giang [Province: Vietnam]
704094
Hau Giang, Can Tho City, and Soc Trang [Province: Vietnam]
704096
Bac Lieu and Ca Mau [Province: Vietnam]
705001
Pomurska [Region: Slovenia]
705002
Podravska [Region: Slovenia]
705003
Koroška [Region: Slovenia]
705004
Savinjska [Region: Slovenia]
705005
Zasavska [Region: Slovenia]
705006
Spodnjeposavska [Region: Slovenia]
705007
Jugovzhodna Slovenija [Region: Slovenia]
705008
Osrednjeslovenska [Region: Slovenia]
705009
Gorenjska [Region: Slovenia]
705010
Notranjsko-kraška [Region: Slovenia]
705011
Goriška [Region: Slovenia]
705012
Obalno-kraška [Region: Slovenia]
705099
Unknown [Region: Slovenia]
710001
Western Cape [Province: South Africa]
710004
Free State [Province: South Africa]
710005
Eastern Cape, KwaZulu-Natal [Province: South Africa]
710007
Gauteng, Limpopo, Mpumalanga, North West, Northern Cape [Province: South Africa]
710999
Unknown [Province: South Africa]
724011
Galicia [Communities and Autonomous Cities: Spain]
724012
Principado de Asturias [Communities and Autonomous Cities: Spain]
724013
Cantabria [Communities and Autonomous Cities: Spain]
724021
País Vasco [Communities and Autonomous Cities: Spain]
724022
Comunidad Foral de Navarra [Communities and Autonomous Cities: Spain]
724023
La Rioja [Communities and Autonomous Cities: Spain]
724024
Aragón [Communities and Autonomous Cities: Spain]
724030
Comunidad de Madrid [Communities and Autonomous Cities: Spain]
724041
Castilla y León [Communities and Autonomous Cities: Spain]
724042
Castilla-La Mancha [Communities and Autonomous Cities: Spain]
724043
Extremadura [Communities and Autonomous Cities: Spain]
724051
Cataluña [Communities and Autonomous Cities: Spain]
724052
Comunidad Valenciana [Communities and Autonomous Cities: Spain]
724053
Illes Balears [Communities and Autonomous Cities: Spain]
724061
Andalucía [Communities and Autonomous Cities: Spain]
724062
Región de Murcia [Communities and Autonomous Cities: Spain]
724063
Ciudad Autónoma de Ceuta [Communities and Autonomous Cities: Spain]
724064
Ciudad Autónoma de Melilla [Communities and Autonomous Cities: Spain]
724070
Canarias [Communities and Autonomous Cities: Spain]
724099
Unknown [Communities and Autonomous Cities: Spain]
728071
Upper Nile [State: South Sudan]
728072
Jonglei [State: South Sudan]
728073
Unity [State: South Sudan]
728081
Warrap [State: South Sudan]
728082
Northern Bahr El Ghazal [State: South Sudan]
728083
Western Bahr El Ghazal [State: South Sudan]
728084
Lakes [State: South Sudan]
728091
Western Equatoria [State: South Sudan]
728092
Central Equatoria [State: South Sudan]
728093
Eastern Equatoria [State: South Sudan]
729011
Northern [State: Sudan]
729012
Nahr El Nil [State: Sudan]
729021
Red Sea [State: Sudan]
729022
Kassala [State: Sudan]
729023
Al Gedarif [State: Sudan]
729031
Khartoum [State: Sudan]
729041
Al Gezira [State: Sudan]
729042
White Nile [State: Sudan]
729043
Sinnar [State: Sudan]
729044
Blue Nile [State: Sudan]
729051
North Kordofan [State: Sudan]
729052
South Kordofan [State: Sudan]
729061
North Darfur [State: Sudan]
729062
West Darfur [State: Sudan]
729063
South Darfur [State: Sudan]
756001
Zurich [Canton: Switzerland]
756002
Bern [Canton: Switzerland]
756003
Luzern (Lucerne) [Canton: Switzerland]
756004
Uri [Canton: Switzerland]
756005
Schwyz [Canton: Switzerland]
756006
Obwalden (Obwald) [Canton: Switzerland]
756007
Nidwalden (Nidwald) [Canton: Switzerland]
756008
Glarus [Canton: Switzerland]
756009
Zug [Canton: Switzerland]
756010
Fribourg [Canton: Switzerland]
756011
Solothurn [Canton: Switzerland]
756012
Basel-Stadt (Basel-City) [Canton: Switzerland]
756013
Basel-Landschaft (Basel-Country) [Canton: Switzerland]
756014
Schaffhausen [Canton: Switzerland]
756015
Outer and Inner Rhodes [Canton: Switzerland]
756017
St. Gallen (St. Gall) [Canton: Switzerland]
756018
Graubundun (Grisons) [Canton: Switzerland]
756019
Aargau (Argovia) [Canton: Switzerland]
756020
Thurgau (Thurgovia) [Canton: Switzerland]
756021
Ticino [Canton: Switzerland]
756022
Vaud [Canton: Switzerland]
756023
Valais [Canton: Switzerland]
756024
Neuchatel [Canton: Switzerland]
756025
Geneva [Canton: Switzerland]
756026
Jura [Canton: Switzerland]
764010
Bangkok [Province: Thailand]
764011
Samut Prakan [Province: Thailand]
764012
Nonthaburi [Province: Thailand]
764013
Pathum Thani [Province: Thailand]
764014
Phra Nakhon si Ayutthaya [Province: Thailand]
764015
Ang Thong [Province: Thailand]
764016
Lop Buri [Province: Thailand]
764017
Sing Buri [Province: Thailand]
764018
Chai Nat [Province: Thailand]
764019
Prachin Buri and Sa Kaeo [Province: Thailand]
764020
Chon Buri [Province: Thailand]
764021
Rayong [Province: Thailand]
764022
Chanthaburi [Province: Thailand]
764023
Trat [Province: Thailand]
764024
Chachoengsao [Province: Thailand]
764026
Nakhon Nayok [Province: Thailand]
764027
Saraburi [Province: Thailand]
764030
Nakhon Ratchasima [Province: Thailand]
764031
Buri Ram [Province: Thailand]
764032
Surin [Province: Thailand]
764033
Si Sa Ket [Province: Thailand]
764034
Ubon Ratchathani, Yasothon and Amnat Charoen [Province: Thailand]
764036
Chaiyaphum [Province: Thailand]
764040
Khon Kaen [Province: Thailand]
764041
Udon Thani and Nong Bua Lam Phu [Province: Thailand]
764042
Loei [Province: Thailand]
764043
Nong Khai [Province: Thailand]
764044
Maha Sarakham [Province: Thailand]
764045
Roi Et [Province: Thailand]
764046
Kalasin [Province: Thailand]
764047
Sakon Nakhon [Province: Thailand]
764048
Nakhon Phanom and Mukdahan [Province: Thailand]
764050
Chiang Mai [Province: Thailand]
764051
Lamphun [Province: Thailand]
764052
Lampang [Province: Thailand]
764053
Uttaradit [Province: Thailand]
764054
Phrae [Province: Thailand]
764055
Nan [Province: Thailand]
764057
Chiang Rai and Phayao [Province: Thailand]
764058
Mae Hong Son [Province: Thailand]
764060
Nakhon Sawan [Province: Thailand]
764061
Uthai Thani [Province: Thailand]
764062
Kamphaeng Phet [Province: Thailand]
764063
Tak [Province: Thailand]
764064
Sukhothai [Province: Thailand]
764065
Phitsanulok [Province: Thailand]
764066
Phichit [Province: Thailand]
764067
Phetchabun [Province: Thailand]
764070
Ratchaburi [Province: Thailand]
764071
Kanchanaburi [Province: Thailand]
764072
Suphanburi [Province: Thailand]
764073
Nakhon Pathom [Province: Thailand]
764074
Samut Sakhon [Province: Thailand]
764075
Samut Songkhram [Province: Thailand]
764076
Phetchaburi [Province: Thailand]
764077
Prachuap Khiri Khan [Province: Thailand]
764080
Nakhon Si Thammarat [Province: Thailand]
764081
Krabi [Province: Thailand]
764082
Phangnga [Province: Thailand]
764083
Phuket [Province: Thailand]
764084
Surat Thani [Province: Thailand]
764085
Ranong [Province: Thailand]
764086
Chumphon [Province: Thailand]
764090
Songkhla [Province: Thailand]
764091
Satun [Province: Thailand]
764092
Trang [Province: Thailand]
764093
Phatthalung [Province: Thailand]
764094
Pattani [Province: Thailand]
764095
Yala [Province: Thailand]
764096
Narathiwat [Province: Thailand]
792001
Adana, Gaziantep, Osmaniye and Kilis [Province: Turkey]
792002
Adiyaman [Province: Turkey]
792003
Afyon [Province: Turkey]
792004
Agri [Province: Turkey]
792005
Amasya [Province: Turkey]
792006
Ankara and Kirikkale [Province: Turkey]
792007
Antalya [Province: Turkey]
792008
Artvin [Province: Turkey]
792009
Aydin [Province: Turkey]
792010
Balikesir [Province: Turkey]
792011
Bilecik [Province: Turkey]
792012
Bingöl [Province: Turkey]
792013
Bitlis [Province: Turkey]
792014
Bolu and Düzce [Province: Turkey]
792015
Burdur [Province: Turkey]
792017
Çanakkale [Province: Turkey]
792019
Çorum [Province: Turkey]
792020
Denizli [Province: Turkey]
792021
Diyarbakir [Province: Turkey]
792022
Edirne [Province: Turkey]
792023
Elazig [Province: Turkey]
792024
Erzincan [Province: Turkey]
792025
Erzurum [Province: Turkey]
792026
Eskisehir [Province: Turkey]
792028
Giresun [Province: Turkey]
792029
Gümüshane and Bayburt [Province: Turkey]
792031
Hatay [Province: Turkey]
792032
Isparta [Province: Turkey]
792033
Mersin (içel) [Province: Turkey]
792034
Istanbul, Bursa, Kocaeli and Yalova [Province: Turkey]
792035
Izmir [Province: Turkey]
792036
Kars, Ardahan and Igdir [Province: Turkey]
792037
Kastamonu [Province: Turkey]
792038
Kayseri [Province: Turkey]
792039
Kirklareli [Province: Turkey]
792040
Kirsehir [Province: Turkey]
792042
Konya and Karaman [Province: Turkey]
792043
Kütahya [Province: Turkey]
792044
Malatya [Province: Turkey]
792045
Manisa [Province: Turkey]
792046
Kahramanmaras [Province: Turkey]
792047
Mardin, Hakkari, Siirt, Batman and Sirnak [Province: Turkey]
792048
Mugla [Province: Turkey]
792049
Mus [Province: Turkey]
792050
Nevsehir [Province: Turkey]
792051
Nigde and Aksaray [Province: Turkey]
792052
Ordu [Province: Turkey]
792053
Rize [Province: Turkey]
792054
Sakarya [Province: Turkey]
792055
Samsun [Province: Turkey]
792057
Sinop [Province: Turkey]
792058
Sivas [Province: Turkey]
792059
Tekirdag [Province: Turkey]
792060
Tokat [Province: Turkey]
792061
Trabzon [Province: Turkey]
792062
Tunceli [Province: Turkey]
792063
Sanliurfa [Province: Turkey]
792064
Usak [Province: Turkey]
792065
Van [Province: Turkey]
792066
Yozgat [Province: Turkey]
792067
Zonguldak, Çankiri, Karabuk and Bartin [Province: Turkey]
800101
Kalangala [District: Uganda]
800102
Kampala [District: Uganda]
800103
Kiboga [District: Uganda]
800104
Luwero and Nakasongola [District: Uganda]
800105
Masaka and Sembabule [District: Uganda]
800107
Mubende [District: Uganda]
800108
Mukono and Kayunga [District: Uganda]
800110
Rakai [District: Uganda]
800113
Mpigi and Wakiso [District: Uganda]
800203
Iganga, Buguri, and Mayuge [District: Uganda]
800204
Jinja [District: Uganda]
800205
Kamuli [District: Uganda]
800206
Kapchorwa [District: Uganda]
800208
Kumi [District: Uganda]
800209
Mbale and Sironko [District: Uganda]
800210
Pallisa [District: Uganda]
800211
Soroti, Katakwi, and Kaberamaido [District: Uganda]
800212
Busia and Tororo [District: Uganda]
800301
Moyo and Adjumani [District: Uganda]
800302
Apac [District: Uganda]
800303
Arua and Yumbe [District: Uganda]
800304
Gulu [District: Uganda]
800306
Kotido [District: Uganda]
800307
Lira [District: Uganda]
800308
Moroto and Nakapiripirit [District: Uganda]
800310
Nebbi [District: Uganda]
800312
Kitgum and Pader [District: Uganda]
800401
Bundibugyo [District: Uganda]
800403
Hoima [District: Uganda]
800404
Kabale [District: Uganda]
800405
Kabarole, Kamwenge, and Kyenjojo [District: Uganda]
800406
Kasese [District: Uganda]
800407
Kibaale [District: Uganda]
800408
Kisoro [District: Uganda]
800409
Masindi [District: Uganda]
800410
Bushenyi, Mbarara, and Ntungamo [District: Uganda]
800412
Rukungiri and Kanungu [District: Uganda]
800999
Unknown [District: Uganda]
804001
The Autonomous Republic of Crimea [Region: Ukraine]
804005
Vinnytska oblast [Region: Ukraine]
804007
Volynska oblast [Region: Ukraine]
804012
Dnipropetrovska oblast [Region: Ukraine]
804014
Donetska oblast [Region: Ukraine]
804018
Zhytomyrska oblast [Region: Ukraine]
804021
Zakarpatska oblast [Region: Ukraine]
804023
Zaporizka oblast [Region: Ukraine]
804026
Ivano-Frankivska oblast [Region: Ukraine]
804032
Kyivska oblast [Region: Ukraine]
804035
Kirovohradska oblast [Region: Ukraine]
804044
Luhanska oblast [Region: Ukraine]
804046
Lvivska oblast [Region: Ukraine]
804048
Mykolaivska oblast [Region: Ukraine]
804051
Odeska oblast [Region: Ukraine]
804053
Poltavska oblast [Region: Ukraine]
804056
Rivnenska oblast [Region: Ukraine]
804059
Sumska oblast [Region: Ukraine]
804061
Ternopilska oblast [Region: Ukraine]
804063
Kharkivska oblast [Region: Ukraine]
804065
Khersonska oblast [Region: Ukraine]
804068
Khmelnytska oblast [Region: Ukraine]
804071
Cherkaska oblast [Region: Ukraine]
804073
Chernivetska oblast [Region: Ukraine]
804074
Chernihivska oblast [Region: Ukraine]
804080
Kyiv [Region: Ukraine]
804085
Sevastopol [Region: Ukraine]
818001
Cairo [Governorate: Egypt]
818002
Alexandria [Governorate: Egypt]
818003
Port Said [Governorate: Egypt]
818004
Suez [Governorate: Egypt]
818011
Damietta [Governorate: Egypt]
818012
Dakahlia [Governorate: Egypt]
818013
Sharkia [Governorate: Egypt]
818014
Kaliobia [Governorate: Egypt]
818015
Kafr Sheikh [Governorate: Egypt]
818016
Gharbia [Governorate: Egypt]
818017
Menoufia [Governorate: Egypt]
818018
Behera [Governorate: Egypt]
818019
Ismailia [Governorate: Egypt]
818021
Giza [Governorate: Egypt]
818022
Bani Swif [Governorate: Egypt]
818023
Fayoum [Governorate: Egypt]
818024
Menia [Governorate: Egypt]
818025
Asiut [Governorate: Egypt]
818026
Sohag [Governorate: Egypt]
818027
Qena [Governorate: Egypt]
818028
Aswan [Governorate: Egypt]
818029
Luxor [Governorate: Egypt]
818031
Red Sea [Governorate: Egypt]
818032
New Valley [Governorate: Egypt]
818033
Marsa Matroh [Governorate: Egypt]
818034
North Sinai [Governorate: Egypt]
818035
South Sinai [Governorate: Egypt]
826011
North East [Region: United Kingdom]
826013
North West [Region: United Kingdom]
826014
Yorkshire and the Humber [Region: United Kingdom]
826021
East Midlands [Region: United Kingdom]
826022
West Midlands [Region: United Kingdom]
826031
East of England [Region: United Kingdom]
826032
South East and London [Region: United Kingdom]
826040
South West [Region: United Kingdom]
826060
Scotland [Region: United Kingdom]
826070
Wales [Region: United Kingdom]
826080
Northern Ireland [Region: United Kingdom]
834001
Dodoma [Region: Tanzania]
834003
Kilimanjaro [Region: Tanzania]
834004
Tanga [Region: Tanzania]
834005
Morogoro [Region: Tanzania]
834006
Pwani [Region: Tanzania]
834007
Dar es Salaam [Region: Tanzania]
834008
Lindi [Region: Tanzania]
834009
Mtwara [Region: Tanzania]
834010
Ruvumba [Region: Tanzania]
834011
Iringa [Region: Tanzania]
834012
Mbeya [Region: Tanzania]
834013
Singida [Region: Tanzania]
834014
Tabora [Region: Tanzania]
834015
Rukwa [Region: Tanzania]
834016
Kigoma [Region: Tanzania]
834017
Shinyanga [Region: Tanzania]
834018
Kagera [Region: Tanzania]
834019
Mwanza [Region: Tanzania]
834020
Mara [Region: Tanzania]
834021
Arusha and Manyara [Region: Tanzania]
834051
Zanzibar North [Region: Tanzania]
834052
Zanzibar South [Region: Tanzania]
834053
Zanzibar Town/West [Region: Tanzania]
834054
Pemba North [Region: Tanzania]
834055
Pemba South [Region: Tanzania]
840001
Alabama [State: U.S.]
840002
Alaska [State: U.S.]
840004
Arizona [State: U.S.]
840005
Arkansas [State: U.S.]
840006
California [State: U.S.]
840008
Colorado [State: U.S.]
840009
Connecticut [State: U.S.]
840010
Delaware [State: U.S.]
840011
District of Columbia [State: U.S.]
840012
Florida [State: U.S.]
840013
Georgia [State: U.S.]
840015
Hawaii [State: U.S.]
840016
Idaho [State: U.S.]
840017
Illinois [State: U.S.]
840018
Indiana [State: U.S.]
840019
Iowa [State: U.S.]
840020
Kansas [State: U.S.]
840021
Kentucky [State: U.S.]
840022
Louisiana [State: U.S.]
840023
Maine [State: U.S.]
840024
Maryland [State: U.S.]
840025
Massachusetts [State: U.S.]
840026
Michigan [State: U.S.]
840027
Minnesota [State: U.S.]
840028
Mississippi [State: U.S.]
840029
Missouri [State: U.S.]
840030
Montana [State: U.S.]
840031
Nebraska [State: U.S.]
840032
Nevada [State: U.S.]
840033
New Hampshire [State: U.S.]
840034
New Jersey [State: U.S.]
840035
New Mexico [State: U.S.]
840036
New York [State: U.S.]
840037
North Carolina [State: U.S.]
840038
North Dakota [State: U.S.]
840039
Ohio [State: U.S.]
840040
Oklahoma [State: U.S.]
840041
Oregon [State: U.S.]
840042
Pennsylvania [State: U.S.]
840044
Rhode Island [State: U.S.]
840045
South Carolina [State: U.S.]
840046
South Dakota [State: U.S.]
840047
Tennessee [State: U.S.]
840048
Texas [State: U.S.]
840049
Utah [State: U.S.]
840050
Vermont [State: U.S.]
840051
Virginia [State: U.S.]
840053
Washington [State: U.S.]
840054
West Virginia [State: U.S.]
840055
Wisconsin [State: U.S.]
840056
Wyoming [State: U.S.]
840099
State not identified [State: U.S.]
854001
Boucle du Mouhoun [Region: Burkina Faso]
854002
Cascades [Region: Burkina Faso]
854003
Centre [Region: Burkina Faso]
854004
Centre-Est [Region: Burkina Faso]
854005
Centre-Nord [Region: Burkina Faso]
854006
Centre-Ouest [Region: Burkina Faso]
854007
Centre-Sud [Region: Burkina Faso]
854008
Est [Region: Burkina Faso]
854009
Hauts-Bassins [Region: Burkina Faso]
854010
Nord [Region: Burkina Faso]
854011
Plateau Central [Region: Burkina Faso]
854012
Sahel [Region: Burkina Faso]
854013
Sud-Ouest [Region: Burkina Faso]
858001
Montevideo [Department: Uruguay]
858002
Artigas [Department: Uruguay]
858003
Canelones [Department: Uruguay]
858004
Cerro Largo [Department: Uruguay]
858005
Colonia [Department: Uruguay]
858006
Durazno [Department: Uruguay]
858007
Flores [Department: Uruguay]
858008
Florida [Department: Uruguay]
858009
Lavalleja [Department: Uruguay]
858010
Maldonado [Department: Uruguay]
858011
Paysandú [Department: Uruguay]
858012
Río Negro [Department: Uruguay]
858013
Rivera [Department: Uruguay]
858014
Rocha [Department: Uruguay]
858015
Salto [Department: Uruguay]
858016
San Jose [Department: Uruguay]
858017
Soriano [Department: Uruguay]
858018
Tacuarembó [Department: Uruguay]
858019
Treinta Y Tres [Department: Uruguay]
862001
Federal District, Vargas [State: Venezuela]
862002
Amazonas Federal Territory [State: Venezuela]
862003
Anzoátegui [State: Venezuela]
862004
Apure [State: Venezuela]
862005
Aragua [State: Venezuela]
862007
Bolívar [State: Venezuela]
862008
Carabobo [State: Venezuela]
862009
Cojedes [State: Venezuela]
862010
Amacuros Delta Federal Territory [State: Venezuela]
862011
Falcón [State: Venezuela]
862012
Guárico [State: Venezuela]
862013
Lara [State: Venezuela]
862014
Barinas, Mérida [State: Venezuela]
862015
Miranda [State: Venezuela]
862016
Monagas [State: Venezuela]
862017
Nueva Esparta, Federal Dependencies [State: Venezuela]
862018
Portuguesa [State: Venezuela]
862019
Sucre [State: Venezuela]
862020
Táchira [State: Venezuela]
862021
Trujillo [State: Venezuela]
862022
Yaracuy [State: Venezuela]
862023
Zulia [State: Venezuela]
894001
Central [Province: Zambia]
894002
Copperbelt [Province: Zambia]
894003
Eastern, Muchinga, Northern [Province: Zambia]
894004
Luapula [Province: Zambia]
894005
Lusaka [Province: Zambia]
894008
North Western [Province: Zambia]
894009
Southern [Province: Zambia]
894010
Western [Province: Zambia]
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.
Geography: Global Variables -- HOUSEHOLD
IPUMS
Water supply
Water supply
Water supply
Water supply
Water supply
NIU (not in universe)
10
Yes, piped water
11
Piped inside dwelling
12
Piped, exclusively to this household
13
Piped, shared with other households
14
Piped outside the dwelling
15
Piped outside dwelling, in building
16
Piped within the building or plot of land
17
Piped outside the building or lot
18
Have access to public piped water
20
No piped water
99
Unknown
WATSUP describes the physical means by which the housing unit receives its water. The primary distinction is whether or not the household had piped (running) water.
Utilities Variables -- HOUSEHOLD
IPUMS
Telephone availability
Telephone availability
Telephone availability
Telephone availability
Telephone availability
NIU (not in universe)
1
No
2
Yes
9
Unknown/missing
PHONE indicates the availability of a telephone in the dwelling.
Utilities Variables -- HOUSEHOLD
IPUMS
Cellular phone availability
Cellular phone availability
Cellular phone availability
Cellular phone availability
Cellular phone availability
NIU (not in universe)
1
Yes
2
No
9
Unknown
CELL indicates the availability of a cellular phone in the household.
Utilities Variables -- HOUSEHOLD
IPUMS
Trash disposal
Trash disposal
Trash disposal
Trash disposal
Trash disposal
NIU (not in universe)
10
Collected by a sanitation service
11
Collected directly from the household or dwelling
12
Collected indirectly from a garbage container or deposit
13
Collected by a sanitation service only
14
Collected by a sanitation service and disposed of in some other manner
20
Disposed of in some other manner
21
Burned or buried
22
Burned
23
Buried
24
Thrown into street, vacant land, or common area
25
Thrown into river, lake, ocean, lagoon, etc.
26
Thrown into canyon or gulley
27
Dumped in pit
28
Communal refuse dump
29
Own refuse dump
30
Authorized refuse dump
31
Illegal refuse dump
32
Other dumping
33
Outside
34
In the fields
35
Fed to animals
36
Composted
37
Heap
38
Garden
39
Other, none
99
Unknown/missing
This variable indicates whether the household's waste or garbage is collected by a sanitation service or disposed of in some other manner.
Utilities Variables -- HOUSEHOLD
IPUMS
Number of rooms
Number of rooms
Number of rooms
Number of rooms
Number of rooms
Part of a room; no rooms
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30+
98
Unknown
99
NIU (not in universe)
ROOMS indicates the number of rooms occupied by the housing unit.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Toilet
Toilet
Toilet
Toilet
Toilet
NIU (not in universe)
10
No toilet
11
No flush toilet
20
Have toilet, type not specified
21
Flush toilet
22
Non-flush, latrine
23
Non-flush, other and unspecified
99
Unknown
TOILET indicates whether the household had access to a toilet and, in most cases, whether it was a flush toilet or other type of installation.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Floor material
Floor material
Floor material
Floor material
Floor material
NIU (not in universe)
100
None/unfinished (earth)
110
Sand
120
Dung
200
Finished
201
Cement, tile, or brick
202
Cement
203
Concrete
204
Cement screed
205
Ceramic tile
206
Paving stone, cement tile
207
Stone
208
Brick
209
Brick or stone
210
Brick or cement
211
Block
212
Terrazzo
213
Wood
214
Palm, bamboo
215
Parquet
216
Parquet, tile, vinyl
217
Parquet, tile, marble
218
Ceramic, marble, granite
219
Ceramic, marble, tile, or vinyl
220
Marble
221
Mosaic
222
Tile
223
Tile, linoleum, ceramic, etc
224
Tile, cement
225
Tile, stone
226
Tile, stone, brick
227
Tile, stone, vinyl, brick
228
Tile, vinyl, brick
229
Tile, vinyl
230
Vinyl, linoleum, etc
231
Asphalt sheet, vinyl, etc
232
Synthetic, plastic
233
Cane
234
Carpet
235
Scrap material
236
Other finished, n.e.c.
999
Unknown/missing
FLOOR indicates the dwelling's predominant flooring material.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Number of deaths in household last year
Number of deaths in household last year
Number of deaths in household last year
Number of deaths in household last year
Number of deaths in household last year
None
1
1 death
2
2 deaths
3
3 deaths
4
4 deaths
5
5 deaths
6
6 deaths
7
7 or more deaths
8
Unknown
9
NIU (not in universe)
MORTNUM indicates the number of deaths in the household in the past year.
Other Household Variables -- HOUSEHOLD
IPUMS
Any deaths in household last year
Any deaths in household last year
Any deaths in household last year
Any deaths in household last year
Any deaths in household last year
1
Yes
2
No
8
Unknown/missing
9
NIU (not in universe)
ANYMORT indicates whether there were any deaths in the household in the past year.
Other Household Variables -- HOUSEHOLD
IPUMS
Nigeria, Zone
Nigeria, Zone
Nigeria, Zone
Nigeria, Zone
Nigeria, Zone
1
North Central
2
North East
3
North West
4
South East
5
South South
6
South West
9
Unknown
ZONENG indicates the household's zones within Nigeria in all sample years. ZONENG is harmonized by name and does not account for boundary changes over time.
The full set of geography variables for Nigeria 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.
Geography: M-Z Variables -- HOUSEHOLD
IPUMS
Urban-rural status
Urban-rural status
Urban-rural status
Urban-rural status
Urban-rural status
1
Rural
2
Urban
9
Unknown
URBAN indicates whether the household was located in a place designated as urban or as rural.
Geography: Global Variables -- HOUSEHOLD
IPUMS
Sewage
Sewage
Sewage
Sewage
Sewage
NIU (not in universe)
10
Connected to sewage system or septic tank
11
Sewage system (public sewage disposal)
12
Septic tank (private sewage disposal)
20
Not connected to sewage disposal system
99
Unknown
SEWAGE indicates whether the household has access to a sewage system or septic tank.
Utilities Variables -- HOUSEHOLD
IPUMS
Television set
Television set
Television set
Television set
Television set
NIU (not in universe)
10
No
20
Yes, color or black-and-white not specified
21
1 television
22
2 televisions
23
3 televisions
24
4 televisions
25
5 televisions
26
6 televisions
27
7 televisions
28
8 televisions
29
9+ televisions
30
Yes, color only
31
1 color tv
32
2 color tvs
33
3+ color tvs
40
Yes, black-and-white only
41
1 black-white tv
42
2 black-white tvs
43
3+ black-white tvs
50
Yes, both color and black-and-white
52
2+ color and black-white tvs
53
3+ color and black-white tvs
54
4+ color and black-white tvs
99
Unknown/missing
TV indicates whether the household had a television.
Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD
IPUMS
Radio in household
Radio in household
Radio in household
Radio in household
Radio in household
NIU (not in universe)
1
No
2
Yes
9
Unknown/missing
RADIO indicates whether the household had a radio.
Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD
IPUMS
Number of families in household
Number of families in household
Number of families in household
Number of families in household
Number of families in household
Vacant household
1
1 family
2
2 families
3
3 families
4
4 families
5
5 families
6
6 families
7
7 families
8
8 families
9
9 or more families
NFAMS is a constructed variable that indicates the number of families within each household. 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 her servant contains two families; a household consisting of a large, multiple-generation extended family with no lodgers or servants would count 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.
Constructed Household Variables -- HOUSEHOLD
IPUMS
Head's location in household
Head's location in household
Head's location in household
Head's location in household
Head's location in household
HEADLOC gives the person number of the head of household in samples in which persons are organized into households.
Constructed Household Variables -- HOUSEHOLD
IPUMS
Household classification
Household classification
Household classification
Household classification
Household classification
Vacant household
1
One-person household
2
Married/cohab couple, no children
3
Married/cohab couple with children
4
Single-parent family
5
Polygamous family
6
Extended family, relatives only
7
Composite household, family and non-relatives
8
Non-family household
9
Unclassified subfamily
10
Other relative or non-relative household
11
Group quarters
99
Unclassifiable
HHTYPE is a constructed variable that describes the composition of households.
HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ.
Constructed Household Variables -- HOUSEHOLD
IPUMS
Continent and region of country
Continent and region of country
Continent and region of country
Continent and region of country
Continent and region of country
11
Eastern Africa
12
Middle Africa
13
Northern Africa
14
Southern Africa
15
Western Africa
21
Caribbean
22
Central America
23
North America
24
South America
31
Central Asia
32
Eastern Asia
33
Southern Asia
34
South-Eastern Asia
35
Western Asia
41
Eastern Europe
42
Northern Europe
43
Southern Europe
44
Western Europe
51
Australia and New Zealand
52
Melanesia
53
Micronesia
54
Polynesia
REGIONW identifies the continent and region of each country.
Geography: Global Variables -- HOUSEHOLD
IPUMS
Group quarters (collective dwelling) status
Group quarters (collective dwelling) status
Group quarters (collective dwelling) status
Group quarters (collective dwelling) status
Group quarters (collective dwelling) status
Vacant
10
Households
20
Group quarters, n.s.
21
Institutions
22
Other group quarters
29
1-person unit created by splitting large household
99
Unknown/group quarters not identified
GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools.
Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification.
Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions.
Group Quarters Variables -- HOUSEHOLD
IPUMS
Subsample number
Subsample number
Subsample number
Subsample number
Subsample number
1st 1% subsample
1
2nd 1% subsample
2
3rd 1% subsample
3
4th 1% subsample
4
5th 1% subsample
5
6th 1% subsample
6
7th 1% subsample
7
8th 1% subsample
8
9th 1% subsample
9
10th 1% subsample
10
11th 1% subsample
11
12th 1% subsample
12
13th 1% subsample
13
14th 1% subsample
14
15th 1% subsample
15
16th 1% subsample
16
17th 1% subsample
17
18th 1% subsample
18
19th 1% subsample
19
20th 1% subsample
20
21st 1% subsample
21
22nd 1% subsample
22
23rd 1% subsample
23
24th 1% subsample
24
25th 1% subsample
25
26th 1% subsample
26
27th 1% subsample
27
28th 1% subsample
28
29th 1% subsample
29
30th 1% subsample
30
31st 1% subsample
31
32nd 1% subsample
32
33rd 1% subsample
33
34th 1% subsample
34
35th 1% subsample
35
36th 1% subsample
36
37th 1% subsample
37
38th 1% subsample
38
39th 1% subsample
39
40th 1% subsample
40
41st 1% subsample
41
42nd 1% subsample
42
43rd 1% subsample
43
44th 1% subsample
44
45th 1% subsample
45
46th 1% subsample
46
47th 1% subsample
47
48th 1% subsample
48
49th 1% subsample
49
50th 1% subsample
50
51st 1% subsample
51
52nd 1% subsample
52
53rd 1% subsample
53
54th 1% subsample
54
55th 1% subsample
55
56th 1% subsample
56
57th 1% subsample
57
58th 1% subsample
58
59th 1% subsample
59
60th 1% subsample
60
61st 1% subsample
61
62nd 1% subsample
62
63rd 1% subsample
63
64th 1% subsample
64
65th 1% subsample
65
66th 1% subsample
66
67th 1% subsample
67
68th 1% subsample
68
69th 1% subsample
69
70th 1% subsample
70
71st 1% subsample
71
72nd 1% subsample
72
73rd 1% subsample
73
74th 1% subsample
74
75th 1% subsample
75
76th 1% subsample
76
77th 1% subsample
77
78th 1% subsample
78
79th 1% subsample
79
80th 1% subsample
80
81st 1% subsample
81
82nd 1% subsample
82
83rd 1% subsample
83
84th 1% subsample
84
85th 1% subsample
85
86th 1% subsample
86
87th 1% subsample
87
88th 1% subsample
88
89th 1% subsample
89
90th 1% subsample
90
91st 1% subsample
91
92nd 1% subsample
92
93rd 1% subsample
93
94th 1% subsample
94
95th 1% subsample
95
96th 1% subsample
96
97th 1% subsample
97
98th 1% subsample
98
99th 1% subsample
99
100th 1% subsample
SUBSAMP allocates each case to one of 100 subsample replicates, randomly numbered from 0 to 99. Each subsample is nationally representative and preserves any stratification of the sample from which it is drawn. Users who need a representative subset of a sample can use SUBSAMP to select their cases. For example, to randomly extract 10% of the cases from a sample, select any 10 of the 100 subsamples.
Technical Household Variables -- HOUSEHOLD
IPUMS
Number of unrelated persons
Number of unrelated persons
Number of unrelated persons
Number of unrelated persons
Number of unrelated persons
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9+
UNREL indicates the number of persons in the household who are unrelated to the head.
Group Quarters Variables -- HOUSEHOLD
IPUMS
Dwelling number
Dwelling number
Dwelling number
Dwelling number
Dwelling number
Dwelling number
All records
This variable indicates the dwelling number.
Technical Household Variables -- HOUSEHOLD
IPUMS
Number of persons in household
Number of persons in household
Number of persons in household
Number of persons in household
Number of persons in household
Number of persons in household
All records
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
17
17
19
19
This variable indicates the number of persons in the household.
Technical Household Variables -- HOUSEHOLD
IPUMS
Dwelling created by splitting apart a large dwelling or household
Dwelling created by splitting apart a large dwelling or household
Dwelling created by splitting apart a large dwelling or household
Dwelling created by splitting apart a large dwelling or household
Dwelling created by splitting apart a large dwelling or household
Dwelling created by splitting apart a large dwelling or household
All records
No problem
1
Yes: households within a large dwelling were split apart into separate dwellings
2
Yes: persons within a large household were split apart into separate dwellings
This variable indicates that the dwelling was created by splitting apart a large dwelling or household.
Technical Household Variables -- HOUSEHOLD
IPUMS
Zone
Zone
Zone
Zone
Zone
Part A: Identification
1. State _ _
2. LGA _ _
3. RIC _ _ _ _
4. EA code _ _ _ _
5. Enumeration area name ____
6. Sector _
7. HU No _ _
8. Name of head of HH ____
9. Address ____
All households
1
North Central
2
North East
3
North West
4
South East
5
South South
6
South West
This variable indicates the zone of the household.
Geography: M-Z Variables -- HOUSEHOLD
IPUMS
State
State
State
State
State
Part A: Identification
1. State _ _
2. LGA _ _
3. RIC _ _ _ _
4. EA code _ _ _ _
5. Enumeration area name ____
6. Sector _
7. HU No _ _
8. Name of head of HH ____
9. Address ____
Q1.State: This is the name of the state in which the household is located.
01 Abia
02 Adamawa
03 Akwa-Ibom
04 Anambra
05 Bauchi
06 Bayelsa
07 Benue
08 Borno
09 Cross River
10 Delta
11 Ebonyi
12 Edo
13 Ekiti
14 Enugu
15 Gombe
16 Imo
17 Jigawa
18 Kaduna
19 Kano
20 Katsina
21 Kebbi
22 Kogi
23 Kwara
24 Lagos
25 Nasarawa
26 Niger
27 Ogun
28 Ondo
29 Osun
30 Oyo
31 Plateau
32 Rivers
33 Sokoto
34 Taraba
35 Yobe
36 Zamfara
37 FCT
All households
1
Abia
2
Adamawa
3
Akwa ibom
4
Anambra
5
Bauchi
6
Bayelsa
7
Benue
8
Borno
9
Cross Rivers
10
Delta
11
Ebonyi
12
Edo
13
Ekiti
14
Enugu
15
Gombe
16
Imo
17
Jigawa
18
Kaduna
19
Kano
20
Katsina
21
Kebbi
22
Kogi
23
Kwara
24
Lagos
25
Nassarawa
26
Niger
27
Ogun
28
Ondo
29
Osun
30
Oyo
31
Plateau
32
Rivers
33
Sokoto
34
Taraba
35
Yobe
36
Zamfara
37
Federal Capital Territory Abuja
This variable indicates the state in which the household is located.
Geography: M-Z Variables -- HOUSEHOLD
IPUMS
Urban-rural
Urban-rural
Urban-rural
Urban-rural
Urban-rural
Part A: Identification
1. State _ _
2. LGA _ _
3. RIC _ _ _ _
4. EA code _ _ _ _
5. Enumeration area name ____
6. Sector _
7. HU No _ _
8. Name of head of HH ____
9. Address ____
Q6. Sector: The code of each of the sector within a state is one digit. Enter one for urban and two for rural.
All households
1
Urban
2
Rural
This variable indicates the urban-rural status of the household.
Geography: M-Z Variables -- HOUSEHOLD
IPUMS
Response status
Response status
Response status
Response status
Response status
10. Response status
[] 1 Completed
[] 2 Partly completed
[] 3 Not at home
[] 4 Refused
[] 5 Household not located
[] 6 Moved away
[] 7 Other (specify)
Q10. Response status:
The response options listed are: Completed =1, Partly completed = 2, Not at home = 3; Refused = 4, Household not located = 5, and Moved away = 6. The column for response status should be completed at the end of interview by shading the appropriate bubble. (Only one option should be shaded.)
All households
1
Completed
2
Partly completed
3
Not at home
4
Refused
5
Household not located
6
Moved away
7
Others
9
Unknown
This variable indicates the response status.
Technical Household Variables -- HOUSEHOLD
IPUMS
Household number within housing unit
Household number within housing unit
Household number within housing unit
Household number within housing unit
Household number within housing unit
Questionnaire Ref. No:
HH No. within HU _ of _
Q11. Questionnaire reference number:
Q11. Household within housing unit:
This box is to be completed to indicate number of households within housing unit being canvassed. For one household in the housing unit, enter 1 of 1
For two households in the housing unit, enter 1 of 2 for the first and 2 of 2 for the second household and so on.
Q11B. Questionnaire within HH: Each questionnaire has been designed to seek information on 15 members of the household. If there are more than 15 members of the household, additional questionnaire(s) will be required. For 15-member household enter 1 of 1.
But for more than 15-member household, enter 1 of 2 in the first questionnaire, and 2 of 2 will be entered in second questionnaire.
Pg. 22
However if three sets are used, enter 1 of 3 in the first questionnaire, 2 of 3 in the second questionnaire and 3 of 3 in third questionnaire.
All households
1
1
2
2
3
3
4
4
7
7
8
8
9
9
99
Unknown
This variable indicates the household number within the housing unit.
Technical Household Variables -- HOUSEHOLD
IPUMS
Number of households in housing unit
Number of households in housing unit
Number of households in housing unit
Number of households in housing unit
Number of households in housing unit
Questionnaire Ref. No:
HH No. within HU _ of _
Q11. Questionnaire reference number:
Q11. Household within housing unit:
This box is to be completed to indicate number of households within housing unit being canvassed. For one household in the housing unit, enter 1 of 1
For two households in the housing unit, enter 1 of 2 for the first and 2 of 2 for the second household and so on.
Q11B. Questionnaire within HH: Each questionnaire has been designed to seek information on 15 members of the household. If there are more than 15 members of the household, additional questionnaire(s) will be required. For 15-member household enter 1 of 1.
But for more than 15-member household, enter 1 of 2 in the first questionnaire, and 2 of 2 will be entered in second questionnaire.
Pg. 22
However if three sets are used, enter 1 of 3 in the first questionnaire, 2 of 3 in the second questionnaire and 3 of 3 in third questionnaire.
All households
1
1
2
2
3
3
4
4
6
6
7
7
8
8
9
9
99
Unknown
This variable indicates the number of households within the housing unit.
Technical Household Variables -- HOUSEHOLD
IPUMS
Main water source
Main water source
Main water source
Main water source
Main water source
12. Major source of water for drinking and cooking
[] 1 Pipe borne water treated
[] 2 Pipe borne water untreated
[] 3 Bore hole/hand pump
[] 4 Well/spring protected
[] 5 Well/spring unprotected
[] 6 Rain water
[] 7 Streams/pond/river
[] 8 Tanker/truck/vendor
[] 9 Other ____
Q12. Major Source of water for cooking and drinking:
Different sources of water for drinking (type of water supply) have been listed and pre-coded 1-8. Shade the one that is most commonly used for drinking and cooking in that household.
If there is any other type apart from the options listed, you should specify it under 'others' which is code 9.
All households
1
Treated pipe-borne water
2
Untreated pipe-borne water
3
Bore hole hand pump
4
Protected well spring
5
Unprotected well spring
6
Rain water
7
Stream, pond, or river
8
Tanker truck vendor
9
Other
99
Unknown
This variable indicates the household's main source of water for drinking and cooking.
Utilities Variables -- HOUSEHOLD
IPUMS
Distance to water source
Distance to water source
Distance to water source
Distance to water source
Distance to water source
13. Distance to source of water
[] 1 In dwelling
[] 2 Within 500m
[] 3 500-1km
[] 4 1km or more
Q13. Distance to source of water:
Four major categories of distance to source of water are listed below, you are to shade the appropriate option: In dwelling = 1, Within 500 metres = 2, 500 metres -- 1km = 3, 1km or more = 4
All households
1
In dwelling
2
Within 500m
3
500 to 1 km
4
1 km or more
99
Unknown
This variable indicates the distance between the dwelling and the main water source.
Utilities Variables -- HOUSEHOLD
IPUMS
Type of housing unit
Type of housing unit
Type of housing unit
Type of housing unit
Type of housing unit
14. Type of housing unit
[] 1 Single room
[] 2 Flat
[] 3 Duplex
[] 4 Whole building
[] 5 Other ____
Q14. Types of housing unit:
A list of type of housing unit has been provided and pre-coded.
You only need to shade the code which applies to appropriate type of housing unit occupied by the respondent.
All households
1
Single room
2
Flat
3
Duplex
4
Whole building
5
Other
99
Unknown
This variable indicates the type of housing unit.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Number of living rooms in the housing unit
Number of living rooms in the housing unit
Number of living rooms in the housing unit
Number of living rooms in the housing unit
Number of living rooms in the housing unit
15. Number of living rooms in housing unit _ _
Q15. Number of living Rooms in Housing Unit:
The number of rooms in the HU that the household use for relaxation and sleeping, including the visitor's room(s).
You are to find out the number of living rooms in the housing unit and enter the number in the box provided. If the number given is less than ten (10), start with a leading zero e.g. 01, 02, etc.
All households
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15+
99
Unknown
This variable indicates the number of living rooms in the housing unit.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Monthly rent for housing unit in Naira
Monthly rent for housing unit in Naira
Monthly rent for housing unit in Naira
Monthly rent for housing unit in Naira
Monthly rent for housing unit in Naira
16. Monthly rent (in =N=) for housing unit: _ _ _ _ _ _
Q16. Monthly Rent in Naira:
Find how much in Naira, the HH pays monthly for the HU. If the household is living on owner-occupier or pays no rent at all, or pays nominal or subsidized rent, find out how much ordinarily the type of HU goes for in the neighbourhood and enter the inputted rent. If the rent is N506.00 enter it as 00506
In addition, if you are given an annual rent amount, divide it by 12 to get the monthly rent.
All households
This variable indicates the monthly rent for housing unit in Naira.
Household Economic Variables -- HOUSEHOLD
IPUMS
Tenure status
Tenure status
Tenure status
Tenure status
Tenure status
17. Tenure
[] 1 Normal rent
[] 2 Free
[] 3 Nominal/subsidized rent
[] 4 Owner occupier
Q17. Tenure:
There are four major categories of tenure. You are to shade the appropriate bubble.
Tenure (Rent status):
Rent status has been divided into four groups namely:
(a) Normal rents: This refer to an occupier paying the amount normally paid as rent in the area where he's living, for the same number and types of rooms occupied.
Pg. 24
(b) Rent Free: Where the occupier pays no rent for the apartment occupied, e.g. a family house.
(c) Nominal /Subsidized Rent: Where the occupier pays rent which is below what others pay in the same area. The rent may be due to the relationship between the landlord and the occupier.
(d) Owner Occupier: In this case, the house is occupied by the owner.
All households
1
Normal rent
2
Free
3
Nominal subsidized rent
4
Owner occupied
99
Unknown
This variable indicates the tenure status of the household.
Household Economic Variables -- HOUSEHOLD
IPUMS
Floor material
Floor material
Floor material
Floor material
Floor material
18. Material of dwelling floor:
[] 1 Wood/tile
[] 2 Planks/concrete
[] 3 Dirt/straw/without concrete
[] 4 Other (specify)
Q18. Material for dwelling:
Ask for/ observe the type of material used for the floor of the rooms and shade.
However, three major types of dwelling floor are listed and pre-coded, shade appropriately. If there is other type of floor material used other than those listed, shade the bubble '4' and specify.
All households
1
Wood or tile
2
Planks or concrete
3
Dirt or straw without concrete
4
Other
9
Unknown
This variable indicates the material of the floor of the dwelling.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Toilet facility
Toilet facility
Toilet facility
Toilet facility
Toilet facility
19. Toilet facilities
[] 1 None
[] 2 Toilet on water
[] 3 Flush to sewage
[] 4 Flush to septic tank
[] 5 Pail/bucket
[] 6 Covered pit latrine
[] 7 Uncovered pit latrine
[] 8 V.I.P. latrine
[] 9 Other ____
Q19. Toilet facilities:
There are eight major categories of toilet facilities. You are to shade the appropriate bubble. If there is another type of toilet facility different from those listed, shade 9 under 'others' and specify.
All households
1
None
2
Toilet on water
3
Flush to sewage
4
Flush to septic tank
5
Pail bucket
6
Covered pit latrine
7
Uncovered pit latrine
8
Ventilated improved pit (VIP) latrine
9
Other
99
Unknown
This variable indicates the type of toilet facility used by the household.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Distance to toilet facility
Distance to toilet facility
Distance to toilet facility
Distance to toilet facility
Distance to toilet facility
20. Distance of toilet facility from the dwelling:
[] 1 In dwelling
[] 2 Within 500m
[] 3 500-1km
[] 4 1km or more
Q20. Distance of toilet facilities from the dwellings:
There are four major categories of distance to toilet from the dwelling. Shade the appropriate option.
All households
1
In dwelling
2
Within 500m
3
500m to 1 km
4
1 km or more
9
Unknown
This variable indicates the distance between the dwelling and the toilet facility used by the household.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Refuse disposal
Refuse disposal
Refuse disposal
Refuse disposal
Refuse disposal
21. Type of refusal disposal most often used:
[] 1 HH bin collected by government
[] 2 HH bin collected private agency
[] 3 Government bin or shed
[] 4 Disposal within compound
[] 5 Unauthorized refuse heap
[] 6 Other ____
Q21. Types of refuse disposal most often used:
There are five types of refuse disposal listed, Shade the type most often used by the household. If there is any other type apart from those listed, you should shade code 6 'others' and specify.
All households
1
Household bin collected by government
2
Household bin collected by private agency
3
Government bin or shed
4
Disposal within compound
5
Unauthorized refuse heap
6
Other
9
Unknown
This variable indicates the type of refuse disposal most often used in the household.
Utilities Variables -- HOUSEHOLD
IPUMS
Cooking fuel
Cooking fuel
Cooking fuel
Cooking fuel
Cooking fuel
22. Type of fuel used for cooking
[] 1 Electricity
[] 2 Gas
[] 3 Kerosine
[] 4 Wood
[] 5 Coal
Q22. Type of fuel most commonly used for cooking:
Five types of fuel are listed. You should shade the main type most commonly used by the household.
All households
1
Electricity
2
Gas
3
Kerosene
4
Wood
5
Coal
9
Unknown
This variable indicates type of fuel used by the household for cooking.
Utilities Variables -- HOUSEHOLD
IPUMS
Electricity supply
Electricity supply
Electricity supply
Electricity supply
Electricity supply
23. Electricity supply
[] 1 PHCN (NEPA) only
[] 2 Rural electrification only
[] 3 Private generator only
[] 4 PHCN (NEPA) / generator
[] 5 Rural electricity / generator
[] 6 None
Q23. Electricity supply:
Types of electricity supply have been listed and pre-coded. You are to shade the appropriate code. If however there is no electricity supply at all in the housing unit, shade 6.
All households
1
PHCN-NEPA only (Power Holding Company of Nigeria)
2
Rural electrification only
3
Private generator only
4
PHCN-NEPA generator
5
Rural electricity generator
6
None
9
Unknown
This variable indicates the source of the household's electricity supply.
Utilities Variables -- HOUSEHOLD
IPUMS
Radio
Radio
Radio
Radio
Radio
24. Information and communication technology (ICT)
Radio
[] 1 Own
[] 2 Access
[] 3 None
Q24. Information and Communication Technology (ICT):
Some information and communication equipment have been listed. Ask the respondent if he or she or any member of the household owns, has access to or does not have any of the gadgets listed and shade the appropriate bubble. For each item, only one option must be chosen.
All households
1
Own
2
Access
3
None
9
Unknown
This variable indicates whether the household owns or has access to a radio.
Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD
IPUMS
Television
Television
Television
Television
Television
24. Information and communication technology (ICT)
Television
[] 1 Own
[] 2 Access
[] 3 None
Q24. Information and Communication Technology (ICT):
Some information and communication equipment have been listed. Ask the respondent if he or she or any member of the household owns, has access to or does not have any of the gadgets listed and shade the appropriate bubble. For each item, only one option must be chosen.
All households
1
Own
2
Access
3
None
9
Unknown
This variable indicates whether the household owns or has access to a television.
Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD
IPUMS
Fixed telephone
Fixed telephone
Fixed telephone
Fixed telephone
Fixed telephone
24. Information and communication technology (ICT)
Telephone (fixed)
[] 1 Own
[] 2 Access
[] 3 None
Q24. Information and Communication Technology (ICT):
Some information and communication equipment have been listed. Ask the respondent if he or she or any member of the household owns, has access to or does not have any of the gadgets listed and shade the appropriate bubble. For each item, only one option must be chosen.
All households
1
Own
2
Access
3
None
9
Unknown
This variable indicates whether the household owns or has access to a fixed telephone.
Utilities Variables -- HOUSEHOLD
IPUMS
Mobile telephone
Mobile telephone
Mobile telephone
Mobile telephone
Mobile telephone
24. Information and communication technology (ICT)
Telephone (mobile)
[] 1 Own
[] 2 Access
[] 3 None
Q24. Information and Communication Technology (ICT):
Some information and communication equipment have been listed. Ask the respondent if he or she or any member of the household owns, has access to or does not have any of the gadgets listed and shade the appropriate bubble. For each item, only one option must be chosen.
All households
1
Own
2
Access
3
None
9
Unknown
This variable indicates whether the household owns or has access to a mobile telephone.
Utilities Variables -- HOUSEHOLD
IPUMS
Personal computer
Personal computer
Personal computer
Personal computer
Personal computer
24. Information and communication technology (ICT)
Personal computer (PC)
[] 1 Own
[] 2 Access
[] 3 None
Q24. Information and Communication Technology (ICT):
Some information and communication equipment have been listed. Ask the respondent if he or she or any member of the household owns, has access to or does not have any of the gadgets listed and shade the appropriate bubble. For each item, only one option must be chosen.
All households
1
Own
2
Access
3
None
9
Unknown
This variable indicates whether the household owns or has access to a personal computer.
Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD
IPUMS
Internet service
Internet service
Internet service
Internet service
Internet service
24. Information and communication technology (ICT)
Internet service
[] 1 Own
[] 2 Access
[] 3 None
Q24. Information and Communication Technology (ICT):
Some information and communication equipment have been listed. Ask the respondent if he or she or any member of the household owns, has access to or does not have any of the gadgets listed and shade the appropriate bubble. For each item, only one option must be chosen.
All households
1
Own
2
Access
3
None
9
Unknown
This variable indicates whether the household owns or has access to internet service.
Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD
IPUMS
Number of visits
Number of visits
Number of visits
Number of visits
Number of visits
Number of visits
All households
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
27
27
30
30
61
61
62
62
63
63
71
71
81
81
91
91
99
Unknown
This variable indicates the number of visits to the household.
Technical Household Variables -- HOUSEHOLD
IPUMS
Raising factor, household records
Raising factor, household records
Raising factor, household records
Raising factor, household records
Raising factor, household records
Raising factor, household records
All households
This variable indicates the raising factor for Hweight for household records.
Technical Household Variables -- HOUSEHOLD
IPUMS
Adjustment factor, household records
Adjustment factor, household records
Adjustment factor, household records
Adjustment factor, household records
Adjustment factor, household records
Adjustment factor, household records
All households
Unknown
138
138
158
158
164
164
165
165
176
176
177
177
179
179
187
187
190
190
191
191
196
196
199
199
203
203
209
209
212
212
218
218
219
219
222
222
229
229
230
230
232
232
241
241
243
243
248
248
268
268
272
272
275
275
290
290
294
294
298
298
310
310
322
322
330
330
361
361
413
413
496
496
536
536
This variable indicates the adjustment factor for Hweight for household records.
Technical Household Variables -- HOUSEHOLD
IPUMS
Hweight, household records
Hweight, household records
Hweight, household records
Hweight, household records
Hweight, household records
Hweight, household records
All households
This variable indicates Hweight for household records. Hweight is the product of the raising factor and adjustment factor.
Technical Household Variables -- HOUSEHOLD
IPUMS
Hweight1, household records
Hweight1, household records
Hweight1, household records
Hweight1, household records
Hweight1, household records
Hweight1, household records
All households
Unknown
43893
43893
53062
53062
53650
53650
56159
56159
72926
72926
73938
73938
75919
75919
77207
77207
78775
78775
79399
79399
81434
81434
89504
89504
95843
95843
100373
100373
102691
102691
108669
108669
111685
111685
114019
114019
114984
114984
115843
115843
117431
117431
118519
118519
120272
120272
120843
120843
124484
124484
126588
126588
131632
131632
134856
134856
141226
141226
155181
155181
173801
173801
197045
197045
220886
220886
226348
226348
236669
236669
270869
270869
373171
373171
This variable indicates Hweight1 for household records. Hweight1 is a factor of HHweight.
Technical Household Variables -- HOUSEHOLD
IPUMS
Adjustment factor 1, household records
Adjustment factor 1, household records
Adjustment factor 1, household records
Adjustment factor 1, household records
Adjustment factor 1, household records
Adjustment factor 1, household records
All households
Unknown
97
97
108
108
126
126
127
127
130
130
131
131
132
132
134
134
135
135
136
136
137
137
138
138
139
139
140
140
141
141
142
142
144
144
145
145
147
147
148
148
150
150
154
154
155
155
158
158
161
161
188
188
687
687
1231
1231
This variable indicates the adjustment factor for HHweight for household records.
Technical Household Variables -- HOUSEHOLD
IPUMS
HHweight, household records
HHweight, household records
HHweight, household records
HHweight, household records
HHweight, household records
HHweight, household records
All households
Unknown
58816
58816
73226
73226
75815
75815
83158
83158
98053
98053
99180
99180
104009
104009
106679
106679
109571
109571
116822
116822
118162
118162
120763
120763
122790
122790
128886
128886
138010
138010
138633
138633
158590
158590
163229
163229
164347
164347
165327
165327
166727
166727
167111
167111
171121
171121
171789
171789
178002
178002
191495
191495
217488
217488
228116
228116
229417
229417
255602
255602
316887
316887
317242
317242
331329
331329
507513
507513
509234
509234
795839
795839
1374847
1374847
This variable indicates HHweight for household records. HHweight is a product of Adjustment factor 1 and Hweight1. This weight was computed by the national statistical agency and should be used for most types of analysis of household records.
Technical Household Variables -- HOUSEHOLD
IPUMS
Number of fertility records
Number of fertility records
Number of fertility records
Number of fertility records
Number of fertility records
Number of fertility records
All households
1
1
2
2+
9
Unknown
This variable indicates the number of fertility records.
Other Household Variables -- HOUSEHOLD
IPUMS
Number of mortality records
Number of mortality records
Number of mortality records
Number of mortality records
Number of mortality records
Number of mortality records
All households
1
1
2
2
4
4
9
Unknown
This variable indicates the number of mortality records.
Other Household Variables -- HOUSEHOLD
IPUMS
Household weight
Household weight
Household weight
Household weight
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.
Technical Household Variables -- HOUSEHOLD
IPUMS
Nigeria, State 2006 - 2010 [Level 1; consistent boundaries, GIS]
Nigeria, State 2006 - 2010 [Level 1; consistent boundaries, GIS]
Nigeria, State 2006 - 2010 [Level 1; consistent boundaries, GIS]
Nigeria, State 2006 - 2010 [Level 1; consistent boundaries, GIS]
Nigeria, State 2006 - 2010 [Level 1; consistent boundaries, GIS]
566001
Abia
566002
Adamawa
566003
Akwa Ibom
566004
Anambra
566005
Bauchi
566006
Bayelsa
566007
Benue
566008
Borno
566009
Cross River
566010
Delta
566011
Ebonyi
566012
Edo
566013
Ekiti
566014
Enugu
566015
Gombe
566016
Imo
566017
Jigawa
566018
Kaduna
566019
Kano
566020
Katsina
566021
Kebbi
566022
Kogi
566023
Kwara
566024
Lagos
566025
Nasarawa
566026
Niger
566027
Ogun
566028
Ondo
566029
Osun
566030
Oyo
566031
Plateau
566032
Rivers
566033
Sokoto
566034
Taraba
566035
Yobe
566036
Zamfara
566037
Federal Capital Territory Abuja
566099
Unknown
GEO1_NG identifies the household's state within Nigeria in all sample years. States are the first level administrative units of the country. GEO1_NG is spatially harmonized to account for political boundary changes across census years; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_NG can be downloaded from the GIS Boundary files page in the IPUMS International web site.
The full set of geography variables for Nigeria 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.
At the present moment, IPUMS International is only releasing integrated geography for the first level of geography for Nigeria. Year specific geography and maps will become available in the near future.
Geography: M-Z Variables -- HOUSEHOLD
IPUMS
Number of married couples in household
Number of married couples in household
Number of married couples in household
Number of married couples in household
Number of married couples in household
No married couples in household
1
1 couple
2
2 couples
3
3 couples
4
4 couples
5
5 couples
6
6 couples
7
7 couples
8
8 couples
9
9 or more couples
NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household.
NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household).
Constructed Household Variables -- HOUSEHOLD
IPUMS
Number of mothers in household
Number of mothers in household
Number of mothers in household
Number of mothers in household
Number of mothers in household
No mothers in household
1
1 mother
2
2 mothers
3
3 mothers
4
4 mothers
5
5 mothers
6
6 mothers
7
7 mothers
8
8 mothers
9
9 or more mothers in household
NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household.
NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household).
Constructed Household Variables -- HOUSEHOLD
IPUMS
Number of fathers in household
Number of fathers in household
Number of fathers in household
Number of fathers in household
Number of fathers in household
No fathers in household
1
1 father
2
2 fathers
3
3 fathers
4
4 fathers
5
5 fathers
6
6 fathers
7
7 fathers
8
8 fathers
9
9 or more fathers in household
NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household.
NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household).
Constructed Household Variables -- HOUSEHOLD
IPUMS
Country
Country
Country
Country
Country
32
Argentina
40
Austria
50
Bangladesh
51
Armenia
68
Bolivia
76
Brazil
112
Belarus
116
Cambodia
120
Cameroon
124
Canada
152
Chile
156
China
170
Colombia
188
Costa Rica
192
Cuba
214
Dominican Republic
218
Ecuador
222
El Salvador
231
Ethiopia
242
Fiji
250
France
275
Palestine
276
Germany
288
Ghana
300
Greece
324
Guinea
332
Haiti
348
Hungary
356
India
360
Indonesia
364
Iran
368
Iraq
372
Ireland
376
Israel
380
Italy
388
Jamaica
400
Jordan
404
Kenya
417
Kyrgyz Republic
430
Liberia
454
Malawi
458
Malaysia
466
Mali
484
Mexico
496
Mongolia
504
Morocco
508
Mozambique
524
Nepal
528
Netherlands
558
Nicaragua
566
Nigeria
586
Pakistan
591
Panama
600
Paraguay
604
Peru
608
Philippines
620
Portugal
630
Puerto Rico
642
Romania
646
Rwanda
662
Saint Lucia
686
Senegal
694
Sierra Leone
704
Vietnam
705
Slovenia
710
South Africa
724
Spain
728
South Sudan
729
Sudan
756
Switzerland
764
Thailand
792
Turkey
800
Uganda
804
Ukraine
818
Egypt
826
United Kingdom
834
Tanzania
840
United States
854
Burkina Faso
858
Uruguay
862
Venezuela
894
Zambia
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).
Technical Household Variables -- HOUSEHOLD
IPUMS
Electricity
Electricity
Electricity
Electricity
Electricity
NIU (not in universe)
1
Yes
2
No
9
Unknown
ELECTRIC indicates whether the household had access to electricity.
Utilities Variables -- HOUSEHOLD
IPUMS
Ownership of dwelling [general version]
Ownership of dwelling [general version]
Ownership of dwelling [general version]
Ownership of dwelling [general version]
Ownership of dwelling [general version]
NIU (not in universe)
1
Owned
2
Not owned
9
Unknown
OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation.
Household Economic Variables -- HOUSEHOLD
IPUMS
Ownership of dwelling [detailed version]
Ownership of dwelling [detailed version]
Ownership of dwelling [detailed version]
Ownership of dwelling [detailed version]
Ownership of dwelling [detailed version]
NIU (not in universe)
100
Owned
110
Owned, already paid
120
Owned, still paying
130
Owned, constructed
140
Owned, inherited
190
Owned, other
191
Owned, house
192
Owned, condominium
193
Apartment proprietor
194
Shared ownership
200
Not owned
210
Renting, not specified
211
Renting, government
212
Renting, local authority
213
Renting, parastatal
214
Renting, private
215
Renting, private company
216
Renting, individual
217
Renting, collective
218
Renting, joint state and individual
219
Renting, public subsidized
220
Renting, private subsidized
221
Renting, co-tenant
222
Renting, relative of tenant
223
Renting, cooperative
224
Renting, with a job or business
225
Renting, loan-backed habitation
226
Renting, mixed contract
227
Furnished dwelling
228
Sharecropping
230
Subletting
231
Rent to own
239
Renting, other
240
Occupied de facto/squatting
250
Free/usufruct (no cash rent)
251
Free, provided by employer
252
Free, without work or services
253
Free, provided by family or friend
254
Free, private
255
Free, public
256
Free, condemned
257
Free, other
290
Not owned, other
999
Unknown
OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation.
Household Economic Variables -- HOUSEHOLD
IPUMS
Cooking fuel
Cooking fuel
Cooking fuel
Cooking fuel
Cooking fuel
NIU (not in universe)
10
None
20
Electricity
30
Petroleum gas, unspecified
31
Gas -- piped/utility
32
Gas -- tanked or bottled
33
Propane
35
Liquefied petroleum gas
40
Petroleum liquid
41
Oil, kerosene, and other liquid fuels
42
Kerosene/paraffin
43
Kerosene or oil
44
Kerosene or gasoline
45
Gasoline
46
Cocinol
50
Wood, coal, and other solid fuels
51
Wood and other plant fuels
52
Non-wood plant materials
53
Coal or charcoal
54
Charcoal
55
Coal
56
Wood or charcoal
60
Multiple fuels
61
Bottled gas and wood
62
Propane and electricity
63
Propane, kerosene, and electricity
64
Propane and kerosene
65
Kerosene and electrictiy
66
Other combinations
70
Other
71
Alcohol
72
Biogas
73
Discarded or waste material
74
Dung/manure
75
Dung or grass
76
Solar energy
77
Candle
99
Unknown/missing
FUELCOOK indicates the predominant type of fuel or energy used for cooking.
Utilities Variables -- HOUSEHOLD
IPUMS
Internet access
Internet access
Internet access
Internet access
Internet access
NIU (not in universe)
1
No
2
Yes
9
Unknown
INTERNET indicates whether or not the household had an internet connection.
Utilities Variables -- HOUSEHOLD
IPUMS
Computer
Computer
Computer
Computer
Computer
NIU (not in universe)
1
No
2
Yes
9
Unknown/missing
COMPUTER indicates whether the household had a personal computer.
Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD
IPUMS
Person number
Person number
Person number
Person number
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.
Technical Person Variables -- PERSON
IPUMS
Sex
Sex
Sex
Sex
Sex
1
Male
2
Female
9
Unknown
SEX reports the sex (gender) of the respondent.
Demographic Variables -- PERSON
IPUMS
Children ever born
Children ever born
Children ever born
Children ever born
Children ever born
No children
1
1 child
2
2 children
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30+
98
Unknown
99
NIU (not in universe)
CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of female children ever born
Number of female children ever born
Number of female children ever born
Number of female children ever born
Number of female children ever born
No children
1
1 child
2
2 children
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30+
98
Unknown
99
NIU (not in universe)
CHBORNF indicates the number of female children ever born to a woman. Only live births are counted.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of male children ever born
Number of male children ever born
Number of male children ever born
Number of male children ever born
Number of male children ever born
No children
1
1 child
2
2 children
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30+
98
Unknown
99
NIU (not in universe)
CHBORNM indicates the number of male children ever born to a woman. Only live births are counted.
Fertility and Mortality Variables -- PERSON
IPUMS
School attendance
School attendance
School attendance
School attendance
School attendance
NIU (not in universe)
1
Yes
2
No, not specified
3
No, attended in the past
4
No, never attended
9
Unknown/missing
SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census.
Education Variables -- PERSON
IPUMS
Literacy
Literacy
Literacy
Literacy
Literacy
NIU (not in universe)
1
No, illiterate
2
Yes, literate
9
Unknown/missing
LIT indicates whether or not the respondent could read and write in any language. A person is typically considered literate if he or she can both read and write. All other persons are illiterate, including those who can either read or write but cannot do both.
Education Variables -- PERSON
IPUMS
Activity status (employment status) [general version]
Activity status (employment status) [general version]
Activity status (employment status) [general version]
Activity status (employment status) [general version]
Activity status (employment status) [general version]
NIU (not in universe)
1
Employed
2
Unemployed
3
Inactive
9
Unknown/missing
EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information.
The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others.
Employment status is sometimes referred to in other sources as "activity status".
Work Variables -- PERSON
IPUMS
Activity status (employment status) [detailed version]
Activity status (employment status) [detailed version]
Activity status (employment status) [detailed version]
Activity status (employment status) [detailed version]
Activity status (employment status) [detailed version]
NIU (not in universe)
100
Employed, not specified
110
At work
111
At work, and 'student'
112
At work, and 'housework'
113
At work, and 'seeking work'
114
At work, and 'retired'
115
At work, and 'no work'
116
At work, and other situation
117
At work, family holding, not specified
118
At work, family holding, not agricultural
119
At work, family holding, agricultural
120
Have job, not at work in reference period
130
Armed forces
131
Armed forces, at work
132
Armed forces, not at work in reference period
133
Military trainee
140
Marginally employed
200
Unemployed, not specified
201
Unemployed 6 or more months
202
Worked fewer than 6 months, permanent job
203
Worked fewer than 6 months, temporary job
210
Unemployed, experienced worker
220
Unemployed, new worker
230
No work available
240
Inactive unemployed
300
Inactive (not in labor force)
310
Housework
320
Unable to work/disabled
321
Permanent disability
322
Temporary illness
323
Disabled or imprisoned
330
In school
340
Retirees and living on rent
341
Living on rents
342
Living on rents or pension
343
Retirees/pensioners
344
Retired
345
Pensioner
346
Non-retirement pension
347
Disability pension
348
Retired without benefits
350
Elderly
351
Elderly or disabled
360
Institutionalized
361
Prisoner
370
Intermittent worker
371
Not working, seasonal worker
372
Not working, occasional worker
380
Other income recipient
390
Inactive, other reasons
391
Too young to work
392
Dependent
999
Unknown/missing
EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information.
The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others.
Employment status is sometimes referred to in other sources as "activity status".
Work Variables -- PERSON
IPUMS
Status in employment (class of worker) [general version]
Status in employment (class of worker) [general version]
Status in employment (class of worker) [general version]
Status in employment (class of worker) [general version]
Status in employment (class of worker) [general version]
NIU (not in universe)
1
Self-employed
2
Wage/salary worker
3
Unpaid worker
4
Other
9
Unknown/missing
CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples.
Class of worker is often referred to as "status in employment" in other sources.
Work Variables -- PERSON
IPUMS
Status in employment (class of worker) [detailed version]
Status in employment (class of worker) [detailed version]
Status in employment (class of worker) [detailed version]
Status in employment (class of worker) [detailed version]
Status in employment (class of worker) [detailed version]
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
200
Wage/salary worker
201
Management
202
Non-management
203
White collar (non-manual)
204
Blue collar (manual)
205
White and blue collar
206
Day laborer
207
Employee, with a permanent job
208
Employee, occasional, temporary, contract
209
Employee without legal contract
210
Wage/salary worker, private employer
211
Apprentice
212
Religious worker
213
Wage/salary worker, non-profit, NGO
214
White collar, private
215
Blue collar, private
216
Paid family worker
217
Cooperative employee
220
Wage/salary worker, government
221
Federal, government employee
222
State government employee
223
Local government employee
224
White collar, public
225
Blue collar, public
226
Public companies
227
Civil servants, local collectives
230
Domestic worker (work for private household)
240
Seasonal migrant
241
Seasonal migrant, no broker
242
Seasonal migrant, uses broker
250
Other wage and salary
251
Canal zone/commission employee
252
Government employment/training program
253
Mixed state/private enterprise/parastatal
254
Government public work program
300
Unpaid worker
310
Unpaid family worker
320
Apprentice, unpaid or unspecified
330
Trainee
340
Apprentice or trainee
350
Works for others without wage
400
Other
999
Unknown/missing
CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples.
Class of worker is often referred to as "status in employment" in other sources.
Work Variables -- PERSON
IPUMS
Sector of employment
Sector of employment
Sector of employment
Sector of employment
Sector of employment
NIU (not in universe)
10
Public
20
Private
21
Private, not elsewhere classified
22
Individual/family enterprise, and self-employed
23
Foreign
30
Mixed: public-private or parastatal
40
Collective or cooperative
50
Foreign government or non-governmental organization
60
Other, unspecified
61
Canal zone
62
Faith-based organization
99
Unknown
EMPSECT indicates the economic sector in which the person was employed. Economic sector is defined in terms of ownership or control of the enterprise in which the person worked.
Work Variables -- PERSON
IPUMS
Employment disability
Employment disability
Employment disability
Employment disability
Employment disability
1
Disabled
2
Not disabled
8
Unknown
9
NIU (not in universe)
DISEMP indicates if the respondent was economically inactive because of disabilities.
Disability Variables -- PERSON
IPUMS
Age
Age
Age
Age
Age
Less than 1 year
1
1 year
2
2 years
3
3
4
4
5
5
6
6
7
7
8
8
9
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
100
100+
999
Not reported/missing
AGE gives age in years as of the person's last birthday prior to or on the day of enumeration.
Demographic Variables -- PERSON
IPUMS
Hours worked outside of main occupation
Hours worked outside of main occupation
Hours worked outside of main occupation
Hours worked outside of main occupation
Hours worked outside of main occupation
No hours
1
1 hour
2
2 hours
3
3 hours
4
4 hours
5
5 hours
6
6 hours
7
7 hours
8
8 hours
9
9 hours
10
10 hours
11
11 hours
12
12 hours
13
13 hours
14
14 hours
15
15 hours
16
16 hours
17
17 hours
18
18 hours
19
19 hours
20
20 hours
21
21 hours
22
22 hours
23
23 hours
24
24 hours
25
25 hours
26
26 hours
27
27 hours
28
28 hours
29
29 hours
30
30 hours
31
31 hours
32
32 hours
33
33 hours
34
34 hours
35
35 hours
36
36 hours
37
37 hours
38
38 hours
39
39 hours
40
40 hours
41
41 hours
42
42 hours
43
43 hours
44
44 hours
45
45 hours
46
46 hours
47
47 hours
48
48 hours
49
49 hours
50
50 hours
51
51 hours
52
52 hours
53
53 hours
54
54 hours
55
55 hours
56
56 hours
57
57 hours
58
58 hours
59
59 hours
60
60 hours
61
61 hours
62
62 hours
63
63 hours
64
64 hours
65
65 hours
66
66 hours
67
67 hours
68
68 hours
69
69 hours
70
70 hours
71
71 hours
72
72 hours
73
73 hours
74
74 hours
75
75 hours
76
76 hours
77
77 hours
78
78 hours
79
79 hours
80
80 hours
81
81 hours
82
82 hours
83
83 hours
84
84 hours
85
85 hours
86
86 hours
87
87 hours
88
88 hours
89
89 hours
90
90 hours
91
91 hours
92
92 hours
93
93 hours
94
94 hours
95
95 hours
96
96 hours
98
Unknown
99
NIU (not in universe)
HRSADD indicates the number of hours the respondent typically worked per week in jobs unrelated to their primary occupation. Time spent outside of the workplace in work-related tasks was to be included; time set aside for meals was to be excluded.
Comparable information for the person's primary occupation can be found in the variable HRSMAIN.
Work Variables -- PERSON
IPUMS
Mother's location in household
Mother's location in household
Mother's location in household
Mother's location in household
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.
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.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Father's location in household
Father's location in household
Father's location in household
Father's location in household
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.
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.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Spouse's location in household
Spouse's location in household
Spouse's location in household
Spouse's location in household
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.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Rule for linking parent
Rule for linking parent
Rule for linking parent
Rule for linking parent
Rule for linking parent
No parent of person in household
11
Link to head or spouse, unambiguous
12
Link to head or spouse, ambiguous
21
Child-Grandchild, within empirical child cap
22
Child-Grandchild, within constructed child cap
23
Child-Grandchild, exceeds child cap
31
Specified Other Relatives, within empirical child cap
32
Specified Other Relatives, within constructed child cap
33
Specified Other Relatives, exceeds child cap
41
Other Relatives, within empirical child cap
42
Other Relatives, within constructed child cap
51
Non-Relatives, within empirical child cap
52
Non-Relatives, within constructed child cap
PARRULE describes the criteria by which the IPUMS-International variables MOMLOC and POPLOC linked the person to a probable mother and/or father.
IPUMS-International establishes child-parent links according to five basic rules, and PARRULE gives the number of the rule that applied to the link in question. A link to any parent automatically generates a second link to that parent's spouse or partner, so only one rule is needed to describe both MOMLOC and POPLOC.
The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Rule for linking spouse
Rule for linking spouse
Rule for linking spouse
Rule for linking spouse
Rule for linking spouse
No spouse present
1
Rule 1: strong relationship pairing, couple adjacent
2
Rule 2: strong relationship pairing, couple not adjacent
3
Rule 3: weak relationship pairing, couple adjacent
4
Rule 4: weak relationship pairing, couple not adjacent
5
Rule 5: weak consensual union pairings
6
Rule 6: sample-specific rules (usually child-to-child)
SPRULE explains the criteria by which the IPUMS-International variable SPLOC linked the person to his/her probable spouse.
IPUMS-International establishes spouse-spouse links according to five basic rules, and SPRULE gives the number of the rule that applied to the link in question. A sixth rule identifies sample-specific linking procedures only imposed in selected instances.
The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Probable stepmother
Probable stepmother
Probable stepmother
Probable stepmother
Probable stepmother
Biological mother or no mother present
1
Mother has no children borne or surviving
2
Child reports mother is deceased
3
Explicitly identified step relationship
4
Mother reports no children in the home
5
Age difference implausible
6
Child exceeds known fertility of mother
STEPMOM indicates whether a person's mother, as identified by MOMLOC, was most probably not the person's biological mother. Non-zero values of STEPMOM explain why it is probable that the person's mother was a step- or adopted mother. A value of 0 indicates no likely stepmother because (1) the mother identified in MOMLOC was probably the biological mother or (2) there is no mother of this person present in the household.
The codes for STEPMOM are as follows:
0 = Biological mother or no mother of this person present in household.
1 = Mother has no children borne 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.
See PARRULE for a description of the linking process.
Users should note that there are many stepmothers and adopted mothers in the population that cannot be identified with information available in the censuses. Therefore, STEPMOM will always under-represent their actual number in the population.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Probable stepfather
Probable stepfather
Probable stepfather
Probable stepfather
Probable stepfather
Biological father or no father present
1
Child reports father is deceased
2
Explicitly identified step relationship
3
Age difference implausible
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.
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.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Man with more than one wife linked
Man with more than one wife linked
Man with more than one wife linked
Man with more than one wife linked
Man with more than one wife linked
No more than one wife linked via SPLOC
1
More than one wife linked via SPLOC
POLYMAL indicates if a man had more than one wife linked to him in the constructed IPUMS variable SPLOC -- Spouse's Location in Household.
The point of POLYMAL is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Woman is second or higher order wife
Woman is second or higher order wife
Woman is second or higher order wife
Woman is second or higher order wife
Woman is second or higher order wife
Person is not the 2nd or higher order wife linked via SPLOC
1
Person is the 2nd or higher order wife linked via SPLOC
POLY2ND indicates if a woman was the second or higher order wife linked to a husband in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The variable does not suggest the actual marital order of wives, only their relative positions in the person order of the household as it was enumerated.
The point of POLY2ND is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Family unit membership
Family unit membership
Family unit membership
Family unit membership
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).
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Number of own family members in household
Number of own family members in household
Number of own family members in household
Number of own family members in household
Number of own family members in household
1
1 family member present
2
2 family members present
3
3 family members present
4
4
5
5
6
6
7
7
8
8
9
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 more persons
FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them.
FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membebership). 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).
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Number of own children in household
Number of own children in household
Number of own children in household
Number of own children in household
Number of own children in household
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9 or more children in household
NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Number of own children under age 5 in household
Number of own children under age 5 in household
Number of own children under age 5 in household
Number of own children under age 5 in household
Number of own children under age 5 in household
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9 or more 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.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Age of eldest own child in household
Age of eldest own child in household
Age of eldest own child in household
Age of eldest own child in household
Age of eldest own child in household
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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
99
No own child in household
ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household.
ELDCH is top-coded at age 50 or older.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Age of youngest own child in household
Age of youngest own child in household
Age of youngest own child in household
Age of youngest own child in household
Age of youngest own child in household
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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
99
No own child in household
YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household.
YNGCH is top-coded at age 50 or older.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Relationship to household head [general version]
Relationship to household head [general version]
Relationship to household head [general version]
Relationship to household head [general version]
Relationship to household head [general version]
1
Head
2
Spouse/partner
3
Child
4
Other relative
5
Non-relative
6
Other relative or non-relative
9
Unknown
RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person).
Demographic Variables -- PERSON
IPUMS
Relationship to household head [detailed version]
Relationship to household head [detailed version]
Relationship to household head [detailed version]
Relationship to household head [detailed version]
Relationship to household head [detailed version]
1000
Head
2000
Spouse/partner
2100
Spouse
2200
Unmarried partner
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 of sibling-in-law
4900
Other relative, not elsewhere classified
4910
Other relative with same family name
4920
Other relative with different family name
4930
Other relative, not specified (secondary family)
5000
Non-relative
5100
Friend/guest/visitor/partner
5110
Partner/friend
5111
Friend
5112
Partner/roommate
5113
Housemate/roommate
5120
Visitor
5130
Ex-spouse
5140
Godparent
5150
Godchild
5200
Employee
5210
Domestic employee
5220
Relative of employee, n.s.
5221
Spouse of servant
5222
Child of servant
5223
Other relative of servant
5300
Roomer/boarder/lodger/foster child
5310
Boarder
5311
Boarder or guest
5320
Lodger
5330
Foster child
5340
Tutored/foster child
5350
Tutored child
5400
Employee, boarder or guest
5500
Other specified non-relative
5510
Agregado
5520
Temporary resident, guest
5600
Group quarters
5610
Group quarters, non-inmates
5620
Institutional inmates
5900
Non-relative, n.e.c.
6000
Other relative or non-relative
9999
Unknown
RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person).
Demographic Variables -- PERSON
IPUMS
Marital status [general version]
Marital status [general version]
Marital status [general version]
Marital status [general version]
Marital status [general version]
NIU (not in universe)
1
Single/never married
2
Married/in union
3
Separated/divorced/spouse absent
4
Widowed
9
Unknown/missing
[program universe for et,mz samples.
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.
Demographic Variables -- PERSON
IPUMS
Marital status [detailed version]
Marital status [detailed version]
Marital status [detailed version]
Marital status [detailed version]
Marital status [detailed version]
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
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
360
Married, spouse absent
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
[program universe for et,mz samples.
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.
Demographic Variables -- PERSON
IPUMS
Age at first marriage or union
Age at first marriage or union
Age at first marriage or union
Age at first marriage or union
Age at first marriage or union
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
AGEMARR indicates the person's age at first marriage or consensual union.
Demographic Variables -- PERSON
IPUMS
Number of children dead
Number of children dead
Number of children dead
Number of children dead
Number of children dead
None
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20+
98
Unknown/missing
99
NIU (not in universe)
CHDEAD reports how many of the children ever born to a woman were no longer living at the time of the census. Women were to consider all live births by all fathers; they were to exclude still births.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own female children in household
Number of own female children in household
Number of own female children in household
Number of own female children in household
Number of own female children in household
None
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
17
17
20
20
22
22
98
Unknown
99
NIU (not in universe)
HOMEFEM indicates the number of female children born living in the household with their mother (the respondent).
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own female children living elsewhere
Number of own female children living elsewhere
Number of own female children living elsewhere
Number of own female children living elsewhere
Number of own female children living elsewhere
None
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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)
AWAYFEM indicates the number of surviving biological female children not living in the household with their mother (the respondent).
Fertility and Mortality Variables -- PERSON
IPUMS
Hours worked in main occupation
Hours worked in main occupation
Hours worked in main occupation
Hours worked in main occupation
Hours worked in main occupation
0 hours
1
1 hour
2
2 hours
3
3 hours
4
4 hours
5
5 hours
6
6 hours
7
7 hours
8
8 hours
9
9 hours
10
10 hours
11
11 hours
12
12 hours
13
13 hours
14
14 hours
15
15 hours
16
16 hours
17
17 hours
18
18 hours
19
19 hours
20
20 hours
21
21 hours
22
22 hours
23
23 hours
24
24 hours
25
25 hours
26
26 hours
27
27 hours
28
28 hours
29
29 hours
30
30 hours
31
31 hours
32
32 hours
33
33 hours
34
34 hours
35
35 hours
36
36 hours
37
37 hours
38
38 hours
39
39 hours
40
40 hours
41
41 hours
42
42 hours
43
43 hours
44
44 hours
45
45 hours
46
46 hours
47
47 hours
48
48 hours
49
49 hours
50
50 hours
51
51 hours
52
52 hours
53
53 hours
54
54 hours
55
55 hours
56
56 hours
57
57 hours
58
58 hours
59
59 hours
60
60 hours
61
61 hours
62
62 hours
63
63 hours
64
64 hours
65
65 hours
66
66 hours
67
67 hours
68
68 hours
69
69 hours
70
70 hours
71
71 hours
72
72 hours
73
73 hours
74
74 hours
75
75 hours
76
76 hours
77
77 hours
78
78 hours
79
79 hours
80
80 hours
81
81 hours
82
82 hours
83
83 hours
84
84 hours
85
85 hours
86
86 hours
87
87 hours
88
88 hours
89
89 hours
90
90 hours
91
91 hours
92
92 hours
93
93 hours
94
94 hours
95
95 hours
96
96 hours
97
97 hours
98
98 hours
99
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)
HRSMAIN indicates the number of hours the respondent worked per week in jobs related to their primary occupation.
Work Variables -- PERSON
IPUMS
Educational attainment, Nigeria
Educational attainment, Nigeria
Educational attainment, Nigeria
Educational attainment, Nigeria
Educational attainment, Nigeria
NIU (not in universe)
100
None
200
Nursery
201
Nursery, pre-class
202
Nursery, year 1
203
Nursery, year 2
204
Nursery, year unknown
301
Primary, year 1
302
Primary, year 2
303
Primary, year 3
304
Primary, year 4
305
Primary, year 5
306
Primary, year 6
310
Lower 6
400
Junior Secondary School (JSS)
401
Junior Secondary School, year 1
402
Junior Secondary School, year 2
403
Junior Secondary School, year 3
410
Modern school
420
Senior Secondary School (SSS)
421
Senior Secondary School, year 1
422
Senior Secondary School, year 2
423
Senior Secondary School, year 3
430
Upper 6
510
Teacher training
520
Vocational or technical
530
National certificate of education (NCE)
610
A-Level or National Diploma (ND)
620
Bachelor or Higher National Diploma (HND)
630
Post-graduate
700
Other
710
Quranic
720
Quranic integrated
730
Adult education
998
Unknown
EDUCNG indicates the person's educational attainment in terms of the level of schooling completed.
Education Variables -- PERSON
IPUMS
Children surviving
Children surviving
Children surviving
Children surviving
Children surviving
No children
1
1 child
2
2 children
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30+
98
Unknown
99
NIU (not in universe)
CHSURV reports the number of children born to a woman who were still living at the time of the census.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of female children surviving
Number of female children surviving
Number of female children surviving
Number of female children surviving
Number of female children surviving
No children
1
1 child
2
2 children
3
3
4
4
5
5
6
6
7
7
8
8
9
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)
CHSURVF indicates the number of female children ever born to a woman who were still living at the time of the census.
Fertility and Mortality Variables -- PERSON
IPUMS
Industry, general recode
Industry, general recode
Industry, general recode
Industry, general recode
Industry, general recode
NIU (not in universe)
10
Agriculture, fishing, and forestry
20
Mining
30
Manufacturing
40
Electricity, gas and water
50
Construction
60
Wholesale and retail trade
70
Hotels and restaurants
80
Transportation and communications
90
Financial services and insurance
100
Public administration and defense
110
Services, not specified
111
Real estate and business services
112
Education
113
Health and social work
114
Other services
120
Private household services
130
Other industry, n.e.c.
998
Response suppressed
999
Unknown
INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples.
"Industry" refers to the activity or product of the establishment or sector in which a person worked.
Work Variables -- PERSON
IPUMS
Number of male children surviving
Number of male children surviving
Number of male children surviving
Number of male children surviving
Number of male children surviving
No children
1
1 child
2
2 children
3
3
4
4
5
5
6
6
7
7
8
8
9
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)
CHSURVM indicates the number of male children ever born to a woman who were still living at the time of the census.
Fertility and Mortality Variables -- PERSON
IPUMS
Person number (within household)
Person number (within household)
Person number (within household)
Person number (within household)
Person number (within household)
Person number (within household)
All records
Household record
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
This variable indicates the person number (within household).
Technical Person Variables -- PERSON
IPUMS
Person ID
Person ID
Person ID
Person ID
Person ID
Person ID
All persons
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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
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
76
76
77
77
78
78
79
79
80
80
81
81
91
91
92
92
93
93
94
94
95
95
96
96
This variable indicates the person ID.
Technical Person Variables -- PERSON
IPUMS
Relationship to head
Relationship to head
Relationship to head
Relationship to head
Relationship to head
Part B: Person(s) present in household (for all persons who slept in this household last night)
1. Relationship to head
[] 1 Head
[] 2 Spouse
[] 3 Own child
[] 4 Step child
[] 5 Grand child
[] 6 Brother/sister
[] 7 Niece/nephew
[] 8 Brother/sister-in-law
[] 9 Parent
[] 10 Parent-in-law
[] 11 Other relative
[] 12 Maid/nanny/house servant
[] 13 Non-relative
Col. 1: Relationship to head:
The first column should always be coded (01) since the head of the household should always be listed in the first column, regardless of whether or not the head is present at the time of interview, each household must have one and only one head. Other members should be identified in one of thirteen categories.
How each member listed in the household is related to the head of the household should be indicated against each person's name in column 1. Where there are more than one wife in the household, the first wife will
Pg. 27
be listed first, followed by her children and then the second wife, followed by her children in that order.
All persons
1
Head
2
Spouse
3
Own child
4
Step child
5
Grand child
6
Brother or sister
7
Niece or nephew
8
Brother- or sister-in-law
9
Parent
10
Parent-in-law
11
Other relative
12
Maid, nanny or house servant
13
Non-relative
This variable indicates the person?s relationship to the household head.
Demographic Variables -- PERSON
IPUMS
Residence status
Residence status
Residence status
Residence status
Residence status
Part B: Person(s) present in household (for all persons who slept in this household last night)
2. Residence status
[] 1 Usually resident in HH
[] 2 Not usually resident in HH
Col.2: Residence Status:
A member of the household could either be described as usually resident or not usually resident in the household. Circle code 1 for "usually resident in HH", or code 2 for "not usually resident in HH" as may be applicable. A usual resident is expected to live or has been living in the household for at least 6 months.
All persons
1
Usually resident in household
2
Not usually resident in household
9
Unknown
This variable indicates the person?s residence status.
Demographic Variables -- PERSON
IPUMS
Age last birthday
Age last birthday
Age last birthday
Age last birthday
Age last birthday
Part B: Person(s) present in household (for all persons who slept in this household last night)
3. Age (last birthday) _ _
Col.3: Age last birthday:
Fill in the age [in completed years] for every member of household. If one's age is 12 years and 10 months, you will fill 12 years for the person. For a person who is 99 years or above, write 98 years for such person.
All persons
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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
95
95
96
96
97
97
98
98
99
99
This variable indicates the person?s age last birthday.
Demographic Variables -- PERSON
IPUMS
Sex
Sex
Sex
Sex
Sex
Part B: Person(s) present in household (for all persons who slept in this household last night)
4. Sex
[] 1 Male
[] 2 Female
Col.4: Sex:
Shade 1 for male and 2 for female. Ensure that code 1 and 2 are not shaded at the same time for a person.
All persons
1
Male
2
Female
This variable indicates the person?s sex.
Demographic Variables -- PERSON
IPUMS
Marital status
Marital status
Marital status
Marital status
Marital status
Part B: Person(s) present in household (for all persons who slept in this household last night)
5. Marital status
[] 1 Married
[] 2 Divorced
[] 3 Separated
[] 4 Widowed
[] 5 Never married
Col. 5: Marital Status:
The marital status is pre-coded below in 5 categories, shade which ever is applicable: Married = 1, Divorced = 2, Separated = 3, Widow = 4 and Never married = 5. Ensure that no member is left blank.
All persons
1
Married
2
Divorced
3
Separated
4
Widowed
5
Never married
This variable indicates the person?s marital status.
Demographic Variables -- PERSON
IPUMS
Form of marriage
Form of marriage
Form of marriage
Form of marriage
Form of marriage
Part B: Person(s) present in household (for all persons who slept in this household last night)
6. If married, what form of marriage?
[] 1 Ordinance
[] 2 Customary
[] 3 Mutual agreement
Col. 6: Form of Marriage:
For a person who is married, the form of marriage is categorised into three,namely: Ordinance = 1, Customary = 2, and Mutual Agreement = 3. Record appropriately.
Persons who are married
1
Ordinance
2
Customary
3
Mutual agreement
8
Unknown
9
NIU (not in universe)
This variable indicates the person?s form of marriage.
Demographic Variables -- PERSON
IPUMS
Attendance at formal school
Attendance at formal school
Attendance at formal school
Attendance at formal school
Attendance at formal school
Part B: Person(s) present in household (for all persons who slept in this household last night)
7. Attendance at formal school
[] 1 Never
[] 2 Now in school
[] 3 Before but not now
Col. 7: Attendance at Formal school:
This is in three categories such as, 'never in school',
'Now in school' and 'in school before but not now' precoded as 1, 2 and 3 respectively. Shade which ever is applicable.
All persons
1
Never
2
Now in school
3
Before but not now
This variable indicates the person?s attendance at formal school.
Education Variables -- PERSON
IPUMS
Highest level reached
Highest level reached
Highest level reached
Highest level reached
Highest level reached
Part B: Person(s) present in household (for all persons who slept in this household last night)
8. Highest level reached
[] 1 Below primary
[] 2 Primary
[] 3 Secondary
[] 4 Post secondary
Col 8: Highest level of Education Reached:
Four categories have been pre-coded: Below Pry = 1, Primary = 2, Secondary = 3 and Post Secondary =4. Shade which ever option is applicable.
Persons who ever attended school
1
Below primary
2
Primary
3
Secondary
4
Post secondary
8
Unknown
9
NIU (not in universe)
This variable indicates the person?s highest level of education reached.
Education Variables -- PERSON
IPUMS
Highest grade reached
Highest grade reached
Highest grade reached
Highest grade reached
Highest grade reached
Part B: Person(s) present in household (for all persons who slept in this household last night)
0. Member number _ _
Col.9: Highest grade reached:
A person must have actually finished a class or form. The HIGHEST CLASS/FORM is the last full class or form completed and not the present one being attended. For example, if the person is now in primary six (6) then the highest class completed is primary five (5). Someone currently attending JSS-3 would be recorded as having completed JSS-2. A doubles zero (00) code is used only for persons who are yet to complete nursery or primary one as the case may be. A person whose highest grade reached is preschool, and also someone who attended standard 1 but did not complete the year may be coded as N1 or N2 accordingly.
Persons who ever attended school
1
Pre-class
2
Nursery 1
3
Nursery 2
4
Primary 1
5
Primary 2
6
Primary 3
7
Primary 4
8
Primary 5
9
Primary 6
10
JSS 1
11
JSS 2
12
JSS 3
13
SSS 1
14
SSS 2
15
SSS 3
16
ALevels OND
17
BSC HND
18
Post graduate
19
Others
98
Unknown
99
NIU (not in universe)
This variable indicates the person?s highest grade reached.
Education Variables -- PERSON
IPUMS
Literacy in any language
Literacy in any language
Literacy in any language
Literacy in any language
Literacy in any language
Part B: Person(s) present in household (for all persons who slept in this household last night)
10. Literacy in any language
[] 1 Yes
[] 2 No
3.3 Literacy:
A person is literate if he can read and write in any language, and can carry out simple activities such as writing letters or engage in simple conversation in a language.
Col. 10: Literacy in any Language:
Shade 1 if literate in any language, otherwise shade 2. If a person is literate, he or she can write and read in any language, and carry out simple activities such as writing letters, simple conversation, etc in that language.
All persons
1
Yes
2
No
8
Unknown
This variable indicates the person?s literacy in any language.
Education Variables -- PERSON
IPUMS
Main job of previous week
Main job of previous week
Main job of previous week
Main job of previous week
Main job of previous week
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
Col. 11: Main Job Previous Week:
This implies the main work done last week. A list of such job is provided and coded 1 to 9. You should note the skip Instructions.
All persons
1
Worked for pay
2
Had job but did not work
3
Worked for profit
4
On attachment but did not work
5
Apprenticeship
6
Kept home
7
Went to school
8
Did nothing
This variable indicates the person?s main job of previous work.
Work Variables -- PERSON
IPUMS
Reasons for doing nothing
Reasons for doing nothing
Reasons for doing nothing
Reasons for doing nothing
Reasons for doing nothing
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
12. If person did nothing, what was the reason?
(If options 6-8 go to col. 42)
[] 1 Looked for job
[] 2 Sick
[] 3 Believed no job available
[] 4 Laid off 30 days or less
[] 5 Waiting to join work
[] 6 Retired
[] 7 Invalid
[] 8 Others
Col. 12: If person did nothing previous week what was the reason:
If the respondent did nothing in the previous week, you need to ask for the reason. Enter which code that is applicable. If however the reason for doing nothing is not among the 7 options listed, then shade 8 (others) and specify.
Persons age 10+ who did nothing the previous week
1
Looked for job
2
Sick
3
Believed no job available
4
Laid off 30 days or less
5
Waiting to join work
6
Retired
7
Invalid
8
Others
98
Unknown
99
NIU (not in universe)
This variable indicates the person?s reasons for doing nothing.
Work Variables -- PERSON
IPUMS
Length of unemployment
Length of unemployment
Length of unemployment
Length of unemployment
Length of unemployment
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
12. If person did nothing, what was the reason?
(If options 6-8 go to col. 42)
[] 1 Looked for job
[] 2 Sick
[] 3 Believed no job available
[] 4 Laid off 30 days or less
[] 5 Waiting to join work
[] 6 Retired
[] 7 Invalid
[] 8 Others
13. Length of unemployment
(From the last paid work)
[] 1 Less than 1 month
[] 2 Between 1 and 2 months
[] 3 Between 2 and 3 months
[] 4 Between 3 and 4 months
[] 5 More than 4 months
[] 6 Never had a paid work
Next person
Col. 13: Length of Unemployment:
If the person did nothing previous week and reasons for doing nothing is any of codes 1 to 6 in column 12, find out the number of months the person has been without job and enter this as the length of unemployment.
Persons age 10+ who did nothing the previous week and were not retired or invalid
1
Less than 1 month
2
Between 1 and 2 months
3
Between 2 and 3 months
4
Between 3 and 4 months
5
More than 4 months
6
Never had paid work
8
Unknown
9
NIU (not in universe)
This variable indicates the person?s length of unemployment.
Work Variables -- PERSON
IPUMS
Wants to change job
Wants to change job
Wants to change job
Wants to change job
Wants to change job
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
14. Do you like to change job?
[] 1 Yes
[] 2 No
Col. 14: Do you like to change job:
This question will ascertain whether someone attempted to change job. It is not sufficient for the person to have desired of new job, an affirmative response is only appropriate for person who actually attempted to change jobs. If the person did not seek to change job, the interviewer will shade/ bubble No (2) and skips to column 16.
Persons age 10+ who were economically active the previous week
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
This variable indicates if the person wants to change job.
Work Variables -- PERSON
IPUMS
Reason for wanting to change jobs
Reason for wanting to change jobs
Reason for wanting to change jobs
Reason for wanting to change jobs
Reason for wanting to change jobs
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
14. Do you like to change job?
[] 1 Yes
[] 2 No
15. Reason for the change
[] 1 Low income in present job
[] 2 Job doesn't match skill
[] 3 Job environment not congenial
[] 4 Excessive hours of work
[] 5 Precarious job(s)
[] 6 Inadequate tools
[] 7 Equipment or training for assigned task
[] 8 Travel to work difficulties
[] 9 Inconvenient work schedules
[] 10 Recurring work stoppage
[] 11 Prolonged non wage payment
Col. 15: Reason for the change:
This question is asked only from persons who wanted to change job(s). Probe to get accurate response(s) and fill in the code of the major reason in the spaced provided.
Persons age 10+ who were economically active the previous week and reported wanting to change jobs
1
Low income in present job
2
Job does not match skill
3
Job environment not congenial
4
Excessive hours for work
5
Precarious job or jobs
6
Inadequate tools
7
Equipment or training for assigned task
8
Travel to work difficulties
9
Inconvenient work schedules
10
Recurring work stoppage
11
Prolonged non wage payment
98
Unknown
99
NIU (not in universe)
This variable indicates the person?s reason for wanting to change jobs.
Work Variables -- PERSON
IPUMS
Industry of main job
Industry of main job
Industry of main job
Industry of main job
Industry of main job
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
16. Primary or main occupation _ _
See occupational codes on page 10
Col. 17: Industry:
Record the code of the industry where the respondent is working. The industries are Agric, Forestry and Fishing; Mining and Quarrying: Manufacturing; Electricity, Gas and water; construction; Whole/Retail Trade, Hotels and Restaurants, Transport, Storage and communications, Financing, Insurance, Real Estate, Business Services; Community, social and personnel services; activities not adequately defined. A nurse in Shell Company will be classified as in Mining and Quarrying industry, while a nurse in the General Hospital will be in community, social and personnel services industry.
Persons age 10+ who were economically active the previous week
1
Agriculture, hunting and related services
2
Forestry, logging and related services
5
Fishing
10
Mining of coal and ignite, extraction of peat
11
Extraction of crude petroleum
12
Mining of uranium and thorium ores
13
Mining of metal ores
14
Other mining and quarrying
15
Manufacturing of food products and beverages
16
Manufacturing of tobacco products
17
Manufacturing of textiles
18
Manufacturing of washing apparel, dressing and dying of fur
19
Trimming and dressing of leather, manufacture of luggage
20
Manufacture of wood and of products
21
Manufacture of paper and paper products
22
Publishing, printing and reproduction of recorded media
23
Manufacture of coke, refined petroleum products
24
Manufacture of chemical and chemical products
25
Manufacture of rubber and plastic products
26
Manufacture of non-metallic mineral products
27
Manufacture of basic metals
28
Manufacture of fabricated metal products
29
Manufacture of machinery and equipment not elsewhere classified.
30
Manufacture of office, accounting and computing machinery
31
Manufacture of electrical machinery and apparatus not elsewhere classified.
32
Manufacture of radio, television and communication equipment
33
Manufacture of medical, precision and optical instrument
34
Manufacture of motor vehicles, trailers and semi trailers
35
Manufacture of other transport equipment
36
Manufacture of furniture, manufacturing not elsewhere classified.
37
Recycling
40
Electricity, gas, stream and hot water supply
41
Collection, purification and distribution of water
45
Construction
50
Sale maintenance and repair of motor vehicles
51
Wholesale trade and commission trade
52
Retail trade, except of motor vehicles
55
Hotels and restaurants
60
Land transport and transport via pipe lines
61
Water transport
62
Air transport
63
Supporting and auxiliary transport activities
64
Post and telecommunications
65
Financial intermediation, except insurance
66
Insurance and pension funding
67
Activities auxiliary to financial intermediation
70
Real estate activities
71
Renting of machinery and equipment
72
Computer and related activities
73
Research and development
74
Other business activities
75
Public administration and defense
80
Education
85
Health and social work
90
Sewage and refuse disposal
91
Activities of membership organizations not elsewhere classified.
92
Recreational, cultural and sporting activities
93
Other service activities
95
Activities of private households as employers
96
Undifferentiated goods producing activities
97
Undifferentiated services producing activities
99
Extra territorial organizations and bodies
998
Unknown
999
NIU (not in universe)
This variable indicates the industry of the person's main job.
Work Variables -- PERSON
IPUMS
Employment status
Employment status
Employment status
Employment status
Employment status
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
18. Employment status
[] 1 Employer
[] 2 Employee
[] 3 Own account worker
[] 4 Members of producer coop.
[] 5 Unpaid family worker
[] 6 Others
2.9 Employment Status:
This describes the working situation and personality engaged in employment. E.g
(a) Employees:
These are workers with employment contracts (explicit or implicit, written or oral), which give them a basic remuneration in cash (in form of wages, salaries, bonuses, commission from sales, piece rates etc) or in kind (in form of food, fuel, housing or training). These include paid apprentices and paid trainees, casual and seasonal workers, employees of producers' cooperative, etc whether in the private or public sector.
(b) Employers:
These are those who work on their own account or with one or a few partners and they may engage on a continuous or regular basis, one or more persons to work for them in their business as employees. Their business may be a corporation or a household or unincorporated enterprise
(c ) Own-Account workers:
This includes those who work on their own account or with one or more partners and do not engage any employee on a continuous
Pg. 11
or regular basis. However, they may engage employees as long as it is not on a regular or continuous basis and they may work with the help of (unpaid) contributing family members
(d) Contributing Family Workers:
These are those who work in a market-oriented establishment operated by a relation living in the same household and are not partners in the business. They include young persons who work without pay in a business operated by a relation (e.g. uncle, grandmother) and may not necessarily live in the same household.
(f) Others:
This is the residual category of workers who could not be classified under any of the group mentioned above.
Col. 18: Employment Status:
The employment status of an individual is any of options 1 to 5. You only need to shade the appropriate code of the respondent's employment status and shade bubble (6) for others.
Persons age 10+ who were economically active the previous week
1
Employer
2
Employee
3
Own account worker
4
Member of producer coop
5
Unpaid family worker
6
Other
8
Unknown
9
NIU (not in universe)
This variable indicates the person?s employment status.
Work Variables -- PERSON
IPUMS
Hours of work per week in primary job
Hours of work per week in primary job
Hours of work per week in primary job
Hours of work per week in primary job
Hours of work per week in primary job
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
19. Hours of work per week _ _
Col. 19: Hours of Work (Main Job):
On the main job, state the number of hours (approximate) the respondent spends per week and enter it in the space provided. It attracts a code of two digits. Official working hours per week is 40 hours.
Persons age 10+ who were economically active the previous week
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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
74
74
75
75
76
76
77
77
78
78
79
79
80
80
82
82
84
84
85
85
86
86
88
88
89
89
90
90
91
91
93
93
96
96
98
98
99
99
998
Unknown
999
NIU (not in universe)
This variable indicates the person?s hours of work per week in their primary job.
Work Variables -- PERSON
IPUMS
Industrial sector
Industrial sector
Industrial sector
Industrial sector
Industrial sector
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
20. Institutional sector
[] 1 Private company
[] 2 Public company
[] 3 Parastatals
[] 4 Ministries
[] 5 Others
Col. 20 Institutional Sector:
Five codes were provided for institutional sector shade appropriately.
Persons age 10+ who were economically active the previous week
1
Private company
2
Public company
3
Parastatals
4
Ministries
5
Other
8
Unknown
9
NIU (not in universe)
This variable indicates the person?s industrial sector.
Work Variables -- PERSON
IPUMS
Contributes to National Health Insurance Scheme (NHIS)
Contributes to National Health Insurance Scheme (NHIS)
Contributes to National Health Insurance Scheme (NHIS)
Contributes to National Health Insurance Scheme (NHIS)
Contributes to National Health Insurance Scheme (NHIS)
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
21. Contribute to National Health Insurance Scheme (NHIS)?
[] 1 Yes
[] 2 No
Col. 21 Contribution to Health Insurance Scheme (NHIS):
A respondent can either contribute to NHIS or not, shade accordingly.
Persons age 10+ who were economically active the previous week
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
This variable indicates the person?s contribution to NHIS.
Work Variables -- PERSON
IPUMS
Secondary job
Secondary job
Secondary job
Secondary job
Secondary job
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
22. Secondary job _ _
See occupational codes on page 10
Col. 22: Secondary Job:
Any other economic activity engaged in by the respondent during the week apart from the main job is referred to as secondary job. Enumerator should carefully probe for secondary occupation. One way of finding out about secondary jobs is to ask how a person spends his/her time after his/her main occupation hours. If the respondent does not have secondary job, skip to col. 26.
Persons age 10+ who were economically active the previous week and had a second job
NIU (not in universe)
1
Agriculture, hunting and related service activities
2
Forestry, logging and related service activities
5
Fishing
10
Mining of coal and ignite, extraction of peat
11
Extraction of crude petroleum
12
Mining of uranium and thorium ores
13
Mining of metal ores
14
Other mining and quarrying
15
Manufacturing of food products and beverages
16
Manufacturing of tobacco products
17
Manufacturing of textiles
18
Manufacturing of washing apparel, dressing and dying of fur
19
Trimming and dressing of leather, manufacture of luggage
20
Manufacture of wood and of products
21
Manufacture of paper and paper products
22
Publishing, printing and reproduction of recorded media
23
Manufacture of coke, refined petroleum products
24
Manufacture of chemical and chemical products
25
Manufacture of rubber and plastic products
26
Manufacture of non-metallic mineral products
27
Manufacture of basic metals
28
Manufacture of fabricated metal products
29
Manufacture of machinery and equipment not elsewhere classified
30
Manufacture of office, accounting and computing machinery
31
Manufacture of electrical machinery and apparatus not elsewhere classified
32
Manufacture of radio, television and communication equipment
33
Manufacture of medical, precision and optical instrument
34
Manufacture of motor vehicles, trailers and semi trailers
35
Manufacture of other transport equipment
36
Manufacture of furniture, manufacturing not elsewhere classified.
37
Recycling
40
Electricity, gas, stream and hot water supply
41
Collection, purification and distribution of water
45
Construction
50
Sale maintenance and repair of motor vehicles
51
Wholesale trade and commission trade
52
Retail trade, except of motor vehicles
55
Hotels and restaurants
56
"
60
Land transport and transport via pipe lines
61
Water transport
62
Air transport
63
Supporting and auxiliary transport activities
64
Post and telecommunications
65
Financial intermediation, except insurance
66
Insurance and pension funding
67
Activities auxiliary to financial intermediation
70
Real estate activities
71
Renting of machinery and equipment
72
Computer and related activities
73
Research and development
74
Other business activities
75
Public administration and defense
80
Education
85
Health and social work
90
Sewage and refuse disposal
91
Activities of membership organizations not elsewhere classified
92
Recreational, cultural and sporting activities
93
Other service activities
95
Activities of private households as employers
96
Undifferentiated goods producing activities
97
Undifferentiated services producing activities
98
Extra territorial organizations and bodies
99
Unknown
This variable indicates the person?s secondary job.
Work Variables -- PERSON
IPUMS
Industry of secondary job
Industry of secondary job
Industry of secondary job
Industry of secondary job
Industry of secondary job
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
22. Secondary job _ _
See occupational codes on page 10
23. Industry of secondary job _ _
See industry codes on page 10
Col. 23: Industry of Secondary Job:
The industry of the secondary job engaged in by the respondent during the previous week of the survey should be entered here. It should be noted however that household chores career done by a lady should not
Pg. 32
be considered as secondary job because she does not earn income from it. For persons without secondary job, leave the space blank and skip to col. 26.
Persons age 10+ who were economically active the previous week and had a second job
1
Agriculture, hunting and forestry
2
Fishing
3
Mining and quarrying
4
Manufacturing
5
Electricity, gas and water supply
6
Construction
7
Wholesale and retail trade
8
Hotels and restaurant
9
Transport, storage and communication
10
Financial intermediation
11
Real estate, renting and business activities
12
Public administration and defense, compulsory social security
13
Education
14
Health and social work
15
Other community, social and personal service activities
16
Activities of private households
17
Extra territorial organizations and bodies
98
Unknown
99
NIU (not in universe)
This variable indicates the person?s industry of secondary job.
Work Variables -- PERSON
IPUMS
Employment status in secondary job
Employment status in secondary job
Employment status in secondary job
Employment status in secondary job
Employment status in secondary job
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
22. Secondary job _ _
See occupational codes on page 10
24. Employment status in the secondary job
[] 1 Employer
[] 2 Employee
[] 3 Own account worker
[] 4 Producer coop. member
[] 5 Unpaid family worker
[] 6 Others
Col. 24: Employment Status:
The employment status of an individual are listed and coded 1 to 5. Shade the appropriate code or shade bubble (6) for others and specify.
Persons age 10+ who were economically active the previous week and had a second job
1
Employer
2
Employee
3
Own account worker
4
Member of producer cooperative
5
Unpaid family worker
6
Others
9
NIU (not in universe)
This variable indicates the person?s employment status in their secondary job.
Work Variables -- PERSON
IPUMS
Hours of work per week in secondary job
Hours of work per week in secondary job
Hours of work per week in secondary job
Hours of work per week in secondary job
Hours of work per week in secondary job
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
22. Secondary job _ _
See occupational codes on page 10
25. Hours of work per week _ _
Col. 25: Hours of Work in Secondary Job:
Hours of work spent on secondary job should be recoded in two digit.
Persons age 10+ who were economically active the previous week and had a second job
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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
56
56
57
57
59
59
60
60
62
62
63
63
68
68
70
70
72
72
75
75
77
77
80
80
82
82
84
84
88
88
98
98
99
NIU (not in universe)
This variable indicates the person?s hours of work per week in their secondary job.
Work Variables -- PERSON
IPUMS
Would work extra hours
Would work extra hours
Would work extra hours
Would work extra hours
Would work extra hours
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
19. Hours of work per week _ _
25. Hours of work per week _ _
Check: if Col. 19 + Col. 25 is 40 hours or more, go to col. 27, else [continue]
26. If you are given extra hours will you do it?
[] 1 Yes, voluntary
[] 2 No, involuntary
Col. 26: Extra Hour:
If somebody is working for less than 40hrs in the combination of both primary ( main ) job and secondary occupation, ask whether she/he will do extra hours if given the opportunity and shade appropriately.
Persons age 10+ who were economically active the previous week and worked less than 40 hours in their primary and secondary jobs
1
Yes, voluntary
2
No, involuntary
8
Unknown
9
NIU (not in universe)
This variable indicates whether if give extra hours, the person will work them.
Work Variables -- PERSON
IPUMS
Engaged in voluntary or social work
Engaged in voluntary or social work
Engaged in voluntary or social work
Engaged in voluntary or social work
Engaged in voluntary or social work
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
27. Are you engaged in voluntary or social work?
[] 1 Yes
[] 2 No
Col. 27: Voluntary or Social Work:
Two codes are provided for voluntary or social work, which is classified as non profit institution. Ask if the respondent is engaged in voluntary or social activities and record 1 for yes and 2 for No.
Persons age 10+ who were economically active the previous week
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
This variable indicates if the person is engaged in voluntary or social work.
Other Person Variables -- PERSON
IPUMS
Area of volunteer work
Area of volunteer work
Area of volunteer work
Area of volunteer work
Area of volunteer work
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
27. Are you engaged in voluntary or social work?
[] 1 Yes
[] 2 No
28. In which area of volunteering?
If yes in col. 27
[] 1 Art and recreation
[] 2 Education/research
[] 3 Health
[] 4 Social services
[] 5 Environment
[] 6 Development and housing
[] 7 Civil advocacy
[] 8 Philanthropy
[] 9 Religion
[] 10 International
[] 11 Business/professional
[] 12 Other (specify)
Col. 28: Area of Volunteering:
Eleven areas of volunteering have been provided for social or voluntary work. Write the appropriate code.
Persons age 10+ who are engaged in volunteer or social work
1
Art and recreation
2
Education
3
Health
4
Social Services
5
Environment
6
Development and housing
7
Civil advocacy
8
Philanthropy
9
Religion
10
International
11
Business or professional
12
Other
99
NIU (not in universe)
This variable indicates the person?s area of volunteer work.
Other Person Variables -- PERSON
IPUMS
Hours per week in volunteer or social work
Hours per week in volunteer or social work
Hours per week in volunteer or social work
Hours per week in volunteer or social work
Hours per week in volunteer or social work
Part B: Persons(s) present in household continued? (For persons age 10 years and above)
[Applies to questions 11-63]
11. Main job previous week
(If options 1-5 go to Col. 14, and if options 6 or 7 go to next person)
[] 1 Worked for pay
[] 2 Got job but did not work
[] 3 Worked for profit
[] 4 On attachment but didn't work
[] 5 Apprenticeship
[] 6 Kept home
[] 7 Went to school
[] 8 Did nothing
27. Are you engaged in voluntary or social work?
[] 1 Yes
[] 2 No
29. Hours of work per week _ _
Col. 29: Hours of work per week:
This question is asked of all persons that are engaged in volunteering or social work.
Persons age 10+ who are engaged in volunteer or social work
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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
24
24
25
25
26
26
27
27
28
28
30
30
32
32
33
33
34
34
35
35
36
36
37
37
38
38
40
40
41
41
42
42
43
43
44
44
45
45
46
46
47
47
48
48
49
49
50
50
52
52
54
54
55
55
56
56
60
60
62
62
75
75
82
82
85
85
90
90
92
92
95
95
98
Unknown
99
NIU (not in universe)
This variable indicates the person?s hours per week in volunteer or social work.
Other Person Variables -- PERSON
IPUMS
Started new building project last year
Started new building project last year
Started new building project last year
Started new building project last year
Started new building project last year
Housing project (For persons age 20 years and above)
[Applies to questions 64-67]
64. Did you start any new building in 20??
[] 1 Yes
[] 2 No
Col 64-67 Housing Project:
Only persons that are aged 20 years and above are eligible to answer the questions on housing project.
Col 64: Starting a new building project:
Ask whether the eligible member of household started any new building project last year. Enter '1' if yes, otherwise enter '2' and skip to next person or next part.
Persons age 20+
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
This variable indicates if the person started a new building project last year.
Other Person Variables -- PERSON
IPUMS
Type of building started
Type of building started
Type of building started
Type of building started
Type of building started
Housing project (For persons age 20 years and above)
[Applies to questions 64-67]
64. Did you start any new building in 20??
[] 1 Yes
[] 2 No
65. What is the type of building?
[] 1 Residential
[] 2 Commercial
[] 3 Industrial
[] 4 Other
Col 64-67 Housing Project:
Only persons that are aged 20 years and above are eligible to answer the questions on housing project.
Col 65: Type of building started:
Indicate the type of building project that the household member started last year.
Persons age 20+ who started a new building project
1
Residential
2
Commercial
3
Industrial
4
Other
8
Unknown
9
NIU (not in universe)
This variable indicates the type of new building project started.
Other Person Variables -- PERSON
IPUMS
Stage of completion of building project
Stage of completion of building project
Stage of completion of building project
Stage of completion of building project
Stage of completion of building project
Housing project (For persons age 20 years and above)
[Applies to questions 64-67]
64. Did you start any new building in 20??
[] 1 Yes
[] 2 No
66. What is the state of completion of the building as at December 31, 20??
[] 1 Foundation level
[] 2 Window level
[] 3 Lentel level
[] 4 Roofing level
[] 5 Completed totally
Col 64-67 Housing Project:
Only persons that are aged 20 years and above are eligible to answer the questions on housing project.
Col 67: Period the Project was completed:
For those who completed building project that they embarked upon within last year, ask which quarter of last year that the project was completed.
Persons age 20+ who started a new building project
1
Foundation level
2
Window level
3
Lented level
4
Roofing level
5
Completed totally
8
Unknown
9
NIU (not in universe)
This variable indicates the stage of completion of the new building project.
Other Person Variables -- PERSON
IPUMS
When was building project completed
When was building project completed
When was building project completed
When was building project completed
When was building project completed
Housing project (For persons age 20 years and above)
[Applies to questions 64-67]
64. Did you start any new building in 20??
[] 1 Yes
[] 2 No
66. What is the state of completion of the building as at December 31, 20??
[] 1 Foundation level
[] 2 Window level
[] 3 Lentel level
[] 4 Roofing level
[] 5 Completed totally
67. If col. 66=code 5 then, when was it completed?
[] 1 1st quarter
[] 2 2nd quarter
[] 2 3rd quarter
[] 4 4th quarter
Col 64-67 Housing Project:
Only persons that are aged 20 years and above are eligible to answer the questions on housing project.
Col 67: Period the Project was completed:
For those who completed building project that they embarked upon within last year, ask which quarter of last year that the project was completed.
Persons age 20+ who started a new building project and completed it
1
1st quarter
2
2nd quarter
3
3rd quarter
4
4th quarter
8
Unknown
9
NIU (not in universe)
This variable indicates when the person?s building project was completed.
Other Person Variables -- PERSON
IPUMS
Raising factor, person records
Raising factor, person records
Raising factor, person records
Raising factor, person records
Raising factor, person records
Raising factor, person records
All persons
This variable indicates the raising factor for Hweight for person records.
Technical Person Variables -- PERSON
IPUMS
Adjustment factor, person records
Adjustment factor, person records
Adjustment factor, person records
Adjustment factor, person records
Adjustment factor, person records
Adjustment factor, person records
All persons
138
138
158
158
164
164
165
165
176
176
177
177
179
179
187
187
190
190
191
191
196
196
199
199
203
203
209
209
212
212
218
218
219
219
222
222
229
229
230
230
232
232
241
241
243
243
248
248
268
268
272
272
275
275
290
290
294
294
298
298
310
310
322
322
330
330
361
361
413
413
496
496
536
536
This variable indicates the adjustment factor for Hweight for person records.
Technical Person Variables -- PERSON
IPUMS
Hweight, person records
Hweight, person records
Hweight, person records
Hweight, person records
Hweight, person records
Hweight, person records
All persons
This variable indicates Hweight for persons records. Hweight is a product of the raising factor and the adjustment factor.
Technical Person Variables -- PERSON
IPUMS
Total hours (grouped)
Total hours (grouped)
Total hours (grouped)
Total hours (grouped)
Total hours (grouped)
Total hours (grouped)
All persons
1
1 to 15
2
15 to 39
3
40
4
41 to 47
5
48 to 56
6
More than 56
99
Unknown
This variable indicates the total hours (grouped).
Work Variables -- PERSON
IPUMS
Hweight1, person records
Hweight1, person records
Hweight1, person records
Hweight1, person records
Hweight1, person records
Hweight1, person records
43893
43893
53062
53062
53650
53650
56159
56159
72926
72926
73938
73938
75919
75919
77207
77207
78775
78775
79399
79399
81434
81434
89504
89504
95843
95843
100373
100373
102691
102691
108669
108669
111685
111685
114019
114019
114984
114984
115843
115843
117431
117431
118519
118519
120272
120272
120843
120843
124484
124484
126588
126588
131632
131632
134856
134856
141226
141226
155181
155181
173801
173801
197045
197045
220886
220886
226348
226348
236669
236669
270869
270869
373171
373171
This variable indicates Hweight1 for person records. Hweight1 is a factor of HHweight.
Technical Person Variables -- PERSON
IPUMS
Adjustment factor 1, person records
Adjustment factor 1, person records
Adjustment factor 1, person records
Adjustment factor 1, person records
Adjustment factor 1, person records
Adjustment factor 1, person records
97
97
108
108
126
126
127
127
130
130
131
131
132
132
134
134
135
135
136
136
137
137
138
138
139
139
140
140
141
141
142
142
144
144
145
145
147
147
148
148
150
150
154
154
155
155
158
158
161
161
188
188
687
687
1231
1231
This variable indicates the adjustment factor for HHweight for person records.
Technical Person Variables -- PERSON
IPUMS
HHweight, person records
HHweight, person records
HHweight, person records
HHweight, person records
HHweight, person records
HHweight, person records
58816
58816
73226
73226
75815
75815
83158
83158
98053
98053
99180
99180
104009
104009
106679
106679
109571
109571
116822
116822
118162
118162
120763
120763
122790
122790
128886
128886
138010
138010
138633
138633
158590
158590
163229
163229
164347
164347
165327
165327
166727
166727
167111
167111
171121
171121
171789
171789
178002
178002
191495
191495
217488
217488
228116
228116
229417
229417
255602
255602
316887
316887
317242
317242
331329
331329
507513
507513
509234
509234
795839
795839
1374847
1374847
This variable indicates HHweight for person records. HHweight is a product of Adjustment factor 1 and Hweight1. This weight was computed by the national statistical agency and should be used for most types of analysis of person records.
Technical Person Variables -- PERSON
IPUMS
Ever pregnant
Ever pregnant
Ever pregnant
Ever pregnant
Ever pregnant
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
5. Ever pregnant?
[] 1 Yes
[] 2 No
How to complete Part D: Female contraceptive prevalence.
Col 0 List of women ever married or Aged 15 years and above:
Look through the general list of all persons in the household and copy out the names of all women that are ever married or those that are aged 15 years and over, and enter them in the space provided in this column.
Col.5 Ever pregnant:
Indicate by shading '1' if the woman has ever been pregnant and '2' if she has never been pregnant.
Note:
If 'no' is the answer to Col. 5, skip to col. 13 for the woman.
If 'Yes' is the answer to Col. 5, continue interview with the woman.
Females age 15+ or ever-married
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
This variable indicates if the woman has ever been pregnant.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own male children living in the household
Number of own male children living in the household
Number of own male children living in the household
Number of own male children living in the household
Number of own male children living in the household
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
6. Number of own children living in this HH
Male _
Female _
How to complete Part D: Female contraceptive prevalence.
Col. 6 Number of own Children Living in this Household:
Indicate the number of the children living in the household by gender.
Females age 15+ or ever-married who have ever been pregnant
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
98
Unknown
99
NIU (not in universe)
This variable indicates the woman?s number of own male children living in the household.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own female children living in the household
Number of own female children living in the household
Number of own female children living in the household
Number of own female children living in the household
Number of own female children living in the household
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
6. Number of own children living in this HH
Male _
Female _
How to complete Part D: Female contraceptive prevalence.
Col. 6 Number of own Children Living in this Household:
Indicate the number of the children living in the household by gender.
Females age 15+ or ever-married who have ever been pregnant
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
98
Unknown
99
NIU (not in universe)
This variable indicates the woman?s number of own female children living in the household.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own male children living elsewhere
Number of own male children living elsewhere
Number of own male children living elsewhere
Number of own male children living elsewhere
Number of own male children living elsewhere
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
7. Number of own children living elsewhere
Male _
Female _
How to complete Part D: Female contraceptive prevalence.
Col. 7 Number of own Children Living Elsewhere:
State the number of the children of the woman living elsewhere by gender. For example, some of the children may be in boarding school.
Females age 15+ or ever-married who have ever been pregnant
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
98
Unknown
99
NIU (not in universe)
This variable indicates the woman?s number of own male children living elsewhere.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own female children living elsewhere
Number of own female children living elsewhere
Number of own female children living elsewhere
Number of own female children living elsewhere
Number of own female children living elsewhere
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
7. Number of own children living elsewhere
Male _
Female _
How to complete Part D: Female contraceptive prevalence.
Col. 7 Number of own Children Living Elsewhere:
State the number of the children of the woman living elsewhere by gender. For example, some of the children may be in boarding school.
Females age 15+ or ever-married who have ever been pregnant
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
98
Unknown
99
NIU (not in universe)
This variable indicates the woman?s number of own female children living elsewhere.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own male children that have died
Number of own male children that have died
Number of own male children that have died
Number of own male children that have died
Number of own male children that have died
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
8. Number of own children that have died
Male _
Female _
How to complete Part D: Female contraceptive prevalence.
Col. 8 Number of own Children that have Died:
State the number of the children that may have died by gender. However, care should be exercised in asking about children who have died. Note that Children of previous marriage should be included in the answers to columns 6-8
Females age 15+ or ever-married who have ever been pregnant
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
98
Unknown
99
NIU (not in universe)
This variable indicates the woman?s number of own male children that have died.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own female children that have died
Number of own female children that have died
Number of own female children that have died
Number of own female children that have died
Number of own female children that have died
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
8. Number of own children that have died
Male _
Female _
How to complete Part D: Female contraceptive prevalence.
Col. 8 Number of own Children that have Died:
State the number of the children that may have died by gender. However, care should be exercised in asking about children who have died. Note that Children of previous marriage should be included in the answers to columns 6-8
Females age 15+ or ever-married who have ever been pregnant
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
98
Unknown
99
NIU (not in universe)
This variable indicates the woman?s number of own female children that have died.
Fertility and Mortality Variables -- PERSON
IPUMS
Currently pregnant
Currently pregnant
Currently pregnant
Currently pregnant
Currently pregnant
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
9. Currently pregnant
[] 1 Yes
[] 2 No
How to complete Part D: Female contraceptive prevalence.
Col 9 Currently Pregnant:
If the woman is currently pregnant shade 1, otherwise, shade 2.
Females age 15+ or ever-married
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
This variable indicates if the woman is currently pregnant.
Fertility and Mortality Variables -- PERSON
IPUMS
Registered with clinic
Registered with clinic
Registered with clinic
Registered with clinic
Registered with clinic
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
If pregnant?
[Applies to questions 10-12]
10. Are you registered with the clinic?
[] 1 Yes
[] 2 No
How to complete Part D: Female contraceptive prevalence.
Col 9 Currently Pregnant:
If the woman is currently pregnant shade 1, otherwise, shade 2.
Col. 10 If pregnant -- Ask whether registered with clinic:
For pregnant women, ask whether they are registered with the clinic (Public or Private). Shade 1 if yes, otherwise, shade 2.
Females age 15+ or ever-married who are currently pregnant
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
This variable indicates whether a currently pregnant woman is registered with a clinic.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of visits to clinic in a month
Number of visits to clinic in a month
Number of visits to clinic in a month
Number of visits to clinic in a month
Number of visits to clinic in a month
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
If pregnant?
[Applies to questions 10-12]
11. How many times do you go to the clinic in a month? _ _
How to complete Part D: Female contraceptive prevalence.
Col 9 Currently Pregnant:
If the woman is currently pregnant shade 1, otherwise, shade 2.
Col. 11 Attendance at the Clinic:
If pregnant and registered with clinic, ask for the number of times the woman attends clinic in a month.
Females age 15+ or ever-married who are currently pregnant
1
1
2
2
3
3
4
4
5
5+
98
Unknown
99
NIU (not in universe)
This variable indicates the woman?s number of visits to a clinic in a month.
Fertility and Mortality Variables -- PERSON
IPUMS
Received anti-tetanus
Received anti-tetanus
Received anti-tetanus
Received anti-tetanus
Received anti-tetanus
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
If pregnant?
[Applies to questions 10-12]
12. Received anti-tetanus?
[] 1 Yes
[] 2 No
How to complete Part D: Female contraceptive prevalence.
Col 9 Currently Pregnant:
If the woman is currently pregnant shade 1, otherwise, shade 2.
Col. 12 Receive Anti-Tetanus Injection:
Ask whether the pregnant woman received anti- tetanus and shade the appropriate bubble.
Females age 15+ or ever-married who have ever been pregnant
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
This variable indicates if the woman received anti-tetanus vaccine.
Fertility and Mortality Variables -- PERSON
IPUMS
Currently using family planning
Currently using family planning
Currently using family planning
Currently using family planning
Currently using family planning
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
13. Currently using FP?
(Ask only if age 15-49 years)
[] 1 Yes
[] 2 No
If 2=No, go to D15
How to complete Part D: Female contraceptive prevalence.
Col. 13 Family Planning (Woman age 15-49 yrs only):
If the woman is using family planning, shade 1, otherwise, shade 2 and skip to col. 15.
Females age 15-49
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
This variable indicates if the woman is currently using family planning.
Fertility and Mortality Variables -- PERSON
IPUMS
Method of family planning
Method of family planning
Method of family planning
Method of family planning
Method of family planning
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
13. Currently using FP?
(Ask only if age 15-49 years)
[] 1 Yes
[] 2 No
If 2=No, go to D15
14. Which method?
[] 1 Pill
[] 2 Condom
[] 3 Injection
[] 4 IUD
[] 5 Female sterilization
[] 6 Male sterilization
[] 7 Douche
[] 8 Norplant
[] 9 Foaming tab
[] 10 Diaphragm
[] 11 Foam jelly
[] 12 Traditional methods
[] 13 Abstinence
[] 14 Withdrawal
[] 15 Rhythm
[] 16 Others
How to complete Part D: Female contraceptive prevalence.
Col. 13 Family Planning (Woman age 15-49 yrs only):
If the woman is using family planning, shade 1, otherwise, shade 2 and skip to col. 15.
Col. 14 Method of Family Planning Used:
For women that are currently using family planning, ask for the method and record as provided in the options 01-16.
Females age 15-49 who currently used family planning
1
Pill
2
Condom
3
Injection
4
IUD
5
Female sterilization
6
Male sterilization
7
Douche
8
Norplant
9
Foaming tab
10
Diaphragm
11
Foam jelly
12
Traditional methods
13
Abstinence
14
Withdrawal
15
Rhythm
98
Unknown
99
NIU (not in universe)
This variable indicates the woman?s method of family planning.
Fertility and Mortality Variables -- PERSON
IPUMS
Age at first marriage
Age at first marriage
Age at first marriage
Age at first marriage
Age at first marriage
Part D: Female contraceptive prevalence - Children ever born by women married or aged 15 years and over
[Applies to questions 0-15]
15. If ever married, age at first marriage _ _
How to complete Part D: Female contraceptive prevalence.
Col. 15 If Ever Married -- Age at First Marriage:
For women who have ever been married, state the age at first marriage.
Ever-married females
1
1
2
2
3
3
5
5
6
6
7
7
8
8
9
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
44
44
45
45
46
46
47
47
48
48
50
50
51
51
55
55
57
57
68
68
70
70
71
71
72
72
73
73
74
74
75
75
76
76
77
77
78
78
79
79
87
87
92
92
97
97
98
Unknown
99
NIU (not in universe)
This variable indicates the woman's age at first marriage.
Fertility and Mortality Variables -- PERSON
IPUMS
Polygamous union
Polygamous union
Polygamous union
Polygamous union
Polygamous union
NIU (not in universe)
1
No, in monogamous union
2
Yes, in polygamous union
3
Man in polygamous union
4
Polygamous man, 2 wives
5
Polygamous man, 3 or more wives
6
Woman in polygamous union
7
Polygamous marriage, 2 wives
8
Polygamous marriage, 3 or more wives
9
First wife
10
Second wife
11
Third or higher order wife
99
Unknown/missing
POLYGAM indicates whether the respondent was in a polygamous union and, in some samples, the number of wives or the rank order of the wife.
Demographic Variables -- PERSON
IPUMS
Person weight
Person weight
Person weight
Person weight
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.
Technical Person Variables -- PERSON
IPUMS
Industry, unrecoded
Industry, unrecoded
Industry, unrecoded
Industry, unrecoded
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.
Work Variables -- PERSON
IPUMS
Number of own male children living elsewhere
Number of own male children living elsewhere
Number of own male children living elsewhere
Number of own male children living elsewhere
Number of own male children living elsewhere
None
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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)
AWAYMALE indicates the number of surviving biological male children not living in the household with their mother (the respondent).
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own male children in household
Number of own male children in household
Number of own male children in household
Number of own male children in household
Number of own male children in household
None
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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
24
24
25
25
98
Unknown
99
NIU (not in universe)
HOMEMALE indicates the number of male children born living in the household with their mother (the respondent).
Fertility and Mortality Variables -- PERSON
IPUMS
Years of schooling
Years of schooling
Years of schooling
Years of schooling
Years of schooling
None or pre-school
1
1 year
2
2 years
3
3 years
4
4 years
5
5 years
6
6 years
7
7 years
8
8 years
9
9 years
10
10 years
11
11 years
12
12 years
13
13 years
14
14 years
15
15 years
16
16 years
17
17 years
18
18 years or more
90
Not specified
91
Some primary
92
Some technical after primary
93
Some secondary
94
Some tertiary
95
Adult literacy
96
Special education
97
Response suppressed
98
Unknown/missing
99
NIU (not in universe)
YRSCHOOL indicates the highest grade/level of schooling the person had completed, in years. Only formal schooling is counted. YRSCHOOL accounts for the number of years of study, regardless of the track or kind of study. Information on degree and/or technical track is available in EDATTAIN. Years of schooling for Israel, categorized into intervals, are given in YRSCHOOL2.
Users should pay close attention to the top-codes in each sample, as discussed in the comparability section.
Education Variables -- PERSON
IPUMS
Educational attainment, international recode [general version]
Educational attainment, international recode [general version]
Educational attainment, international recode [general version]
Educational attainment, international recode [general version]
Educational attainment, international recode [general version]
NIU (not in universe)
1
Less than primary completed
2
Primary completed
3
Secondary completed
4
University completed
9
Unknown
EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary.
EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish.
Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN.
Education Variables -- PERSON
IPUMS
Educational attainment, international recode [detailed version]
Educational attainment, international recode [detailed version]
Educational attainment, international recode [detailed version]
Educational attainment, international recode [detailed version]
Educational attainment, international recode [detailed version]
NIU (not in universe)
100
Less than primary completed (n.s.)
110
No schooling
120
Some primary completed
130
Primary (4 yrs) completed
211
Primary (5 yrs) completed
212
Primary (6 yrs) completed
221
Lower secondary general completed
222
Lower secondary technical completed
311
Secondary, general track completed
312
Some college completed
320
Secondary or post-secondary technical completed
321
Secondary, technical track completed
322
Post-secondary technical education
400
University completed
999
Unknown/missing
EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary.
EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish.
Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN.
Education Variables -- PERSON
IPUMS
Number of own children in household
Number of own children in household
Number of own children in household
Number of own children in household
Number of own children in household
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20+
98
Unknown
99
NIU (not in universe)
HOMECHILD indicates the number of surviving biological children living in the household with their mother (the respondent) at the time of the census.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of own children living elsewhere
Number of own children living elsewhere
Number of own children living elsewhere
Number of own children living elsewhere
Number of own children living elsewhere
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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)
AWAYCHILD indicates the number of surviving biological children not living in the household with their mother (the respondent) at the time of the census.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of female children dead
Number of female children dead
Number of female children dead
Number of female children dead
Number of female children dead
None
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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)
CHDEADFEM indicates the number of female children ever born to a woman who are no longer living. Stillbirths are not counted.
It is possible to calculate total child deaths for samples that have both the "Female children ever born" and "Female children surviving" variables. That is not done in CHDEADFEM, which includes only the samples that directly reported the information in the appropriate form.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of male children dead
Number of male children dead
Number of male children dead
Number of male children dead
Number of male children dead
None
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
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)
CHDEADMALE indicates the number of male children ever born to a woman who are no longer living. Stillbirths are not counted.
It is possible to calculate total child deaths for samples that have both the "Male children ever born" and "Male children surviving" variables. That is not done in CHDEADMALE, which includes only the samples that directly reported the information in the appropriate form.
Fertility and Mortality Variables -- PERSON
IPUMS
Age, grouped into intervals
Age, grouped into intervals
Age, grouped into intervals
Age, grouped into intervals
Age, grouped into intervals
1
0 to 4
2
5 to 9
3
10 to 14
4
15 to 19
5
15 to 17
6
18 to 19
7
18 to 24
8
20 to 24
9
25 to 29
10
30 to 34
11
35 to 39
12
40 to 44
13
45 to 49
14
50 to 54
15
55 to 59
16
60 to 64
17
65 to 69
18
70 to 74
19
75 to 79
20
80+
98
Unknown
AGE2 gives computed years of age grouped into intervals.
Demographic Variables -- PERSON
IPUMS
Year [person version]
Year [person version]
Year [person version]
Year [person version]
Year [person version]
[This file is just a placeholder. See the household version of the variable.]
Technical Person Variables -- PERSON
IPUMS
IPUMS sample identifier [person version]
IPUMS sample identifier [person version]
IPUMS sample identifier [person version]
IPUMS sample identifier [person version]
IPUMS sample identifier [person version]
[This file is just a placeholder. See the household version of the variable.]
Technical Person Variables -- PERSON
IPUMS
Household serial number [person version]
Household serial number [person version]
Household serial number [person version]
Household serial number [person version]
Household serial number [person version]
[This file is just a placeholder. See the household version of the variable.]
Technical Person Variables -- PERSON
IPUMS
Country [person version]
Country [person version]
Country [person version]
Country [person version]
Country [person version]
[This file is just a placeholder. See the household version of the variable.]
Technical Person Variables -- PERSON
IPUMS
Record type [person version]
Record type [person version]
Record type [person version]
Record type [person version]
Record type [person version]
[This file is just a placeholder. See the household version of the variable.]
Technical Person Variables -- PERSON
IPUMS