DDI_KGZ_2009_PHC_v01_M_v03_A_IPUMS
Minnesota Population Center
2016-04-25
NADA
Version 6.4 (April 2016): 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)
Census of Population and Housing of the Kyrgyz Republic 2009 - IPUMS Subset
PHC 2009 (IPUMS Harmonized Subset)
KGZ_2009_PHC_v01_M_v03_A_IPUMS
National Statistical Committee of the Kyrgyz Republic
Minnesota Population Center
(c) Copyright 2009, National Statistical Committee of the Kyrgyz Republic and Minnesota Population Center
NADA
National Statistical Committee of the Kyrgyz Republic
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.
Technical Household Variables -- HOUSEHOLD
Technical Person Variables -- PERSON
Geography: Global Variables -- HOUSEHOLD
Dwelling Characteristics Variables -- HOUSEHOLD
Demographic Variables -- PERSON
Education Variables -- PERSON
Fertility and Mortality Variables -- PERSON
Nativity and Birthplace Variables -- PERSON
Work Variables -- PERSON
Disability Variables -- PERSON
Group Quarters Variables -- HOUSEHOLD
Income Variables -- PERSON
Constructed Family Interrelationship Variables -- PERSON
Constructed Household Variables -- HOUSEHOLD
Geography: A-L Variables -- HOUSEHOLD
Migration Variables -- PERSON
Ethnicity and Language Variables -- PERSON
Work: Industry 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.
Kyrgyz Republic
National coverage
District
Individuals, households, and housing units
UNITS IDENTIFIED:
- Dwellings: Yes
- Vacant units: No
- Households: Yes
- Individuals: Yes
- Group quarters: Yes
- Special populations: Homeless people, temporarily absent persons, and temporary residents
UNIT DESCRIPTIONS:
- Dwellings: The totality of all living quarters, regardless of ownership and employment at the time of the census, including residential buildings, special houses (like hostels, houses for lonely and old people, children's homes, boarding houses for disabled, school hostels and boarding school), flats, service housings, holiday homes, hotels, other living accomodations in other buildings suited for living whether or not they are intended for living.
- Households: A group of people sharing the same housing unit (or one person living alone), jointly keeping the house, i.e. fully or partially pooling their individual budgets for common expenditures for food and daily living needs or having a common budget who may or may not be related by kinship.
- Group quarters: Groups of people living at the same institution (housing unit), sharing meals, without having individual budgets or common consumer expenditures, subject to the same general rules, and usually unrelated by kinship.
The entire population of the country, including private and institutional households, their accommodation and living conditions
Census/enumeration data [cen]
MICRODATA SOURCE: National Statistical Committee of the Kyrgyz Republic
SAMPLE DESIGN: 20% sample drawn by the country: systematic sample of every 5th household or every 5th individual in collective household
10% sample drawn by MPC from the 20% sample: systematic sample of every 2nd household
SAMPLE UNIT: Households
SAMPLE FRACTION: 10%
SAMPLE SIZE (person records): 564,986
Face-to-face [f2f]
Three census forms: List of Residents (Form 1), Census Questionnaire - Population (Form 2), and Census Questionnaire - Housing Fund (Form 3)
De jure, CENSUS DAY: March 24, 2009, FIELD WORK PERIOD: March 24-April 2, 2009
Direct interview
Self-weighted. Expansion factor = 10.
COVERAGE: 100%
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:
Kyrgyz Republic, National Statistical Committee of the Kyrgyz Republic, Census of Population and Housing of the Kyrgyz Republic, 2009
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.
KGZ2009-H-H
Household records
0
43
KGZ2009-P-H
Person records
0
104
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.
RECTYPE is a 1-digit alphabetic (non-numeric) variable.
H = Household record
P = Person record
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.
SERIAL is a 10-digit numeric variable.
The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes.
Technical Household Variables -- HOUSEHOLD
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.
PERSONS is a 3-digit numeric variable.
Technical Household 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
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
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
Wall or building material
Wall or building material
Wall or building material
Wall or building material
Wall or building material
NIU (not in universe)
100
No walls
200
Cardboard, scrap, and miscellaneous materials
201
Waste, scrap, or discarded material
202
Fabric or discarded material
203
Zinc, fabric, cardboard, tins, and waste material
204
Cardboard sheet
205
Plastic sheeting, cardboard
206
Makeshift, salvaged, or improvised materials
207
Reused materials
300
Wood
310
Rough wood
320
Wood, fibercement or plywood
330
Wood, formica, and other
340
Wood or bamboo
350
Wood or straw
400
Other plant-based materials
401
Plantain leaves and similar material
402
Bamboo or cane
403
Bamboo, sawali, cogon, nipa
404
Straw or bamboo
405
Grass, straw or reed
406
Reed, bamboo, or palm
407
Cane, palm leaves, logs
408
Palm leaves or palm planks
500
Masonry, stone, cement, adobe, metal, glass, and other fabricated materials (sometimes mixed with wood)
501
Brick, block, stone, or cement
502
Brick, stone, concrete
503
Brick, stone, or substitutes (dividing panels made of reinforced concrete)
504
Brick, stone, or substitutes (dividing panels made of wood)
505
Brick or tile
506
Brick or stone
507
Brick or cement block
508
Brick with plaster exterior
509
Brick without plaster exterior
510
Burnt or stabilized brick
511
Brick
512
Unburnt brick
513
Unburnt brick with cement
514
Unburnt brick with mud
515
Concrete
516
Landcrete
517
Cement blocks
518
Cement blocks or brick
519
Cement blocks or brick, unfinished
520
Cement and adobe bricks
521
Cement and stone block
522
Reinforced concrete, pre-cast concrete panels, or steel skeleton framed concrete
523
Concrete, reinforced concrete, blocks, panels
524
Adobe
525
Adobe walls with plaster exterior
526
Adobe walls without plaster exterior
527
Adobe with cement exterior
528
Adobe (tabique, quinche)
529
Wood and earth adobe
530
Wood and cement adobe
531
Mud or adobe
532
Pressed dirt
533
Clay
534
Coated clay/mud with sticks/cane
535
Clay or clay-covered sticks
536
Netted bamboo or cane with mud
537
Bundle of mud, straw, other materials
538
Mud with wood/wattle
539
Pole and mud
540
Mud with cement
541
Unfinished lathe and plaster, stucco, etc.
542
Stone
543
Hand-laid stone
544
Quarried stone
545
Cut stone and concrete
546
Cemented stone
547
Stone with clay
548
Blocks of light material
549
Prefabricated material
550
Asbestos
551
Metal or asbestos sheet
552
Metal or iron sheet
553
Metal or fibercement sheeting
554
Galvanized iron or aluminum
555
Tin
556
Glass
557
Cloth
558
Covintec panels
559
Mixed material
560
Mixed material: part wood; part concrete, brick, or stone
561
Wood plastered with clay, adobe, other materials; wood pressed panels; rolled mud bricks; etc.
570
Mainly permanent materials
600
Other material
999
Unknown/missing
This variable indicates the primary material used in the construction of the dwelling, particularly the dwelling's exterior walls.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Stories in structure
Stories in structure
Stories in structure
Stories in structure
Stories in structure
NIU (not in universe)
1
1 story
2
2 stories
3
3 stories
4
4 stories
5
5 stories
6
6 stories
7
7 stories
8
8 stories
9
9 stories
10
10 stories
11
11 stories
12
12 stories
13
13 stories
14
14 stories
15
15 stories
16
16 stories
17
17 stories
18
18 stories
19
19 stories
25
25 stories
99
Unknown
STORIES indicates the number of floors or levels in the building containing the responding housing unit.
Dwelling Characteristics 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 RÃos [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
RÃo 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
Potosà [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
Piauà [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
EspÃrito 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 AraucanÃa [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
BolÃvar 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, QuindÃo, 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 GuainÃa [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 RÃo [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
HolguÃn [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
ElÃas 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
MarÃa 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 MacorÃs [Province: Dominican Republic]
214024
Sánchez RamÃrez [Province: Dominican Republic]
214025
Santiago [Province: Dominican Republic]
214026
Santiago RodrÃguez [Province: Dominican Republic]
214027
Valverde [Province: Dominican Republic]
218001
Azuay [Province: Ecuador]
218002
BolÃvar [Province: Ecuador]
218004
Carchi [Province: Ecuador]
218005
Cotopaxi [Province: Ecuador]
218006
Chimborazo [Province: Ecuador]
218007
El Oro [Province: Ecuador]
218009
Cañar, Esmeraldas, Guayas, ManabÃ, Manga del Cura [Disputed canton], Pichincha, El Piedrero [Disputed canton], Los RÃos, 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, SucumbÃos [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
ÃŽle-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 Potosà [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
MadrÃz [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
RÃo 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, ChiriquÃ, 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 Paraguarà [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
ApurÃmac [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
JunÃn [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 MartÃn [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
PenÃnsula de Setúbal [Subregion: Portugal]
620185
LezÃria 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
PaÃs 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
AndalucÃa [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
RÃo 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
BolÃvar [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
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
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
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
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
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
Dwelling number
Dwelling number
Dwelling number
Dwelling number
Dwelling number
Dwelling number
All records
This variable indicates the dwelling number.
This is a 7-digit numeric variable with 0 implied decimal places
Technical Household Variables -- HOUSEHOLD
IPUMS
Household number (within dwelling)
Household number (within dwelling)
Household number (within dwelling)
Household number (within dwelling)
Household number (within dwelling)
Household number (within dwelling)
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
This variable indicates the household number (within dwelling).
Technical Household Variables -- HOUSEHOLD
IPUMS
Number of households in dwelling
Number of households in dwelling
Number of households in dwelling
Number of households in dwelling
Number of households in dwelling
Number of households in dwelling
All records
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
13
13
This variable indicates the number of households in the dwelling.
Technical Household Variables -- HOUSEHOLD
IPUMS
Number of persons in dwelling
Number of persons in dwelling
Number of persons in dwelling
Number of persons in dwelling
Number of persons in dwelling
Number of persons in dwelling
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
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
This variable indicates the number of persons in the dwelling.
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
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
27
27
This variable indicates the number of persons in the household.
Technical Household Variables -- HOUSEHOLD
IPUMS
Number of structure
Number of structure
Number of structure
Number of structure
Number of structure
Number of structure
All households
1
1
2
2
3
3
4
4
5
5
6
6
7
7
This variable indicates the number of the structure.
Technical Household Variables -- HOUSEHOLD
IPUMS
Residential premise type
Residential premise type
Residential premise type
Residential premise type
Residential premise type
Questions 1 -- 5 to be completed for residential buildings
[Questions 1-5]
1. Classification of residential premise by type
[] 1 Building with one housing unit
[] 2 Building with more than one housing unit (block)
[] 3 Building for persons residing in institutional establishments
[] 4 Hostels
[] 5 Hotels
[] 6 Unfinished residential building
[] 7 Dilapidated residential premises
[] 8 Other buildings
All households
1
Buildings with one housing unit
2
Buildings with more than one housing unit
3
Institutional housing
4
Hostel
6
Unfinished residential building
8
Other buildings
9
Unknown
This variable indicates the residential premise type.
Group Quarters Variables -- HOUSEHOLD
IPUMS
Number of stories
Number of stories
Number of stories
Number of stories
Number of stories
Questions 1 -- 5 to be completed for residential buildings
[Questions 1-5]
2. Number of stories
[] 1 Single-story
[] 2 Two-story
[] 3 3-5- story
[] 4 6-9- story
[] 5 10 and more stories
Households, excluding institutions
1
Single story
2
Two story
3
3 to 5 stories
4
6 to 9 stories
5
10 or more stories
9
NIU (Not in universe)
This variable indicates the number of stories of the residential premise.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Wall material of premises
Wall material of premises
Wall material of premises
Wall material of premises
Wall material of premises
Questions 1 -- 5 to be completed for residential buildings
[Questions 1-5]
3. Wall materials of premises
[] 1 Brick
[] 2 Combined reinforced concrete, panel (monolith)
[] 3 Cinder block
[] 4 Wood
[] 5 Adobe brick
[] 6 Mixed material
[] 7 Other
Households, excluding institutions
1
Brick
2
Concrete, reinforced concrete, panel (monolith)
3
Cinder block
4
Wood
5
Adobe or clay
6
Mixed material
7
Other
9
NIU (Not in universe)
This variable indicates the wall material of the premises.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Construction period
Construction period
Construction period
Construction period
Construction period
Questions 1 -- 5 to be completed for residential buildings
[Questions 1-5]
4. Construction period
If rebuilt, extended, year of construction is considered initial year of construction.
[] 1 Before 1946
[] 2 1946-1960
[] 3 1961-1970
[] 4 1971-1980
[] 5 1981-1990
[] 6 1991-2000
[] 7 2001-2005
[] 8 2005-2008
Households, excluding institutions
1
Before 1946
2
1946 - 1960
3
1961 - 1970
4
1971 - 1980
5
1981 - 1990
6
1991 - 2000
7
2001-2005
8
2006 - 2008
9
NIU (Not in universe)
This variable indicates the construction period for the dwelling.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Seismic stability
Seismic stability
Seismic stability
Seismic stability
Seismic stability
Questions 1 -- 5 to be completed for residential buildings
[Questions 1-5]
5. Seismic stability
1 [] Constructed for earthquake resistance
2 [] Constructed without seismic stability
3 [] Unknown
Households not in institutional premises
1
Constructed for earthquake resistance
2
Constructed without seismic stability
8
Unknown
9
NIU (Not in universe)
This variable indicates the seismic stability of the residence.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Type of occupied residential premise
Type of occupied residential premise
Type of occupied residential premise
Type of occupied residential premise
Type of occupied residential premise
Questions 6 -- 10 to be completed for residential premise
[Questions 6-10 were asked for residential premises.]
6. Type of occupied residential premise in a building
[] 1 Separate house
[] 2 Part of separate house
[] 3 Separate apartment
[] 4 Common (multifamily) apartment
[] 5 Room, apartment in hostel
[] 6 Part of house for old and disabled people, children's home, etc.
[] 7 Part of premises in other institutional establishments
[] 8 Premises in hotels
[] 9 Country house (Dachas)
[] 10 Other residential premise (including lodging)
[] 11 Other non-residential premises used for residence
[] 12 Premise is n/a
All households
1
Separate house
2
Part of a separate house
3
Separate apartment
4
Common (multifamily) apartment
5
Room, apartment in hostel
9
Country house (dachas)
99
Unknown
This variable indicates the type of occupied residential premise.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Occupancy
Occupancy
Occupancy
Occupancy
Occupancy
Questions 6 -- 10 to be completed for residential premise
[Questions 6-10 were asked for residential premises.]
7. Occupancy
[] 1 Occupied for constant residence
[] 2 Not occupied
Households, excluding institutions
1
Residence occupied
2
Unoccupied
9
NIU (Not in universe)
This variable indicates whether the residence is occupied.
Technical Household Variables -- HOUSEHOLD
IPUMS
Total area of dwelling (square meters)
Total area of dwelling (square meters)
Total area of dwelling (square meters)
Total area of dwelling (square meters)
Total area of dwelling (square meters)
Questions 6 -- 10 to be completed for residential premise
[Questions 6-10 were asked for residential premises.]
9. Size of area, [m2]
Floor area _ _ _
Residential area _ _ _
o/w for other purposes _ _ _
Households, excluding institutions
This variable indicates the total area occupied by the household in squared meters.
This is a 3-digit numeric variable with 0 implied decimal places
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Residential area of dwelling (square meters)
Residential area of dwelling (square meters)
Residential area of dwelling (square meters)
Residential area of dwelling (square meters)
Residential area of dwelling (square meters)
Questions 6 -- 10 to be completed for residential premise
[Questions 6-10 were asked for residential premises.]
9. Size of area, [m2]
Floor area _ _ _
Residential area _ _ _
o/w for other purposes _ _ _
Households, excluding institutions
This variable indicates the number of square meters in the household used as residential area.
This is a 3-digit numeric variable with 0 implied decimal places
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Number of rooms occupied by household
Number of rooms occupied by household
Number of rooms occupied by household
Number of rooms occupied by household
Number of rooms occupied by household
Questions 6 -- 10 to be completed for residential premise
[Questions 6-10 were asked for residential premises.]
10. Number of rooms
How many rooms in premise unit, excluding kitchen and bathroom?
_ _ room[s]
Households, excluding institutions
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10+
99
NIU (Not in universe)
This variable indicates the number of rooms occupied by the household.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Urban or rural
Urban or rural
Urban or rural
Urban or rural
Urban or rural
Urban or rural
All households
1
Urban
2
Rural
This variable indicates whether the household is located in an urban or rural area.
Geography: A-L 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.
HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description.
Technical Household Variables -- HOUSEHOLD
IPUMS
Kyrgyz Republic, Region 1999 - 2009 [Level 1; consistent boundaries, GIS]
Kyrgyz Republic, Region 1999 - 2009 [Level 1; consistent boundaries, GIS]
Kyrgyz Republic, Region 1999 - 2009 [Level 1; consistent boundaries, GIS]
Kyrgyz Republic, Region 1999 - 2009 [Level 1; consistent boundaries, GIS]
Kyrgyz Republic, Region 1999 - 2009 [Level 1; consistent boundaries, GIS]
417001
Gorkenesh Bishkek
417002
Issyk-Kul
417003
Dzhalal-Abad
417004
Naryn
417005
Batken
417006
Oshskaya
417007
Talasskaya
417008
Chuya
GEO1_KG identifies the household's region (oblast) or city (shaar) within the Kyrgyz Republic in all sample years. Regions or cities are the first level administrative units of the country. GEO1_KG is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_KG can be downloaded from the GIS Boundary files page in the IPUMS International web site.
The full set of geography variables for Kyrgyz Republic 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 Kyrgyz Republic. Year specific geography and maps along with variables that are spatially harmonized at the second level of geography and account for political boundary changes across census years will become available in the near future.
Geography: A-L Variables -- HOUSEHOLD
IPUMS
Kyrgyz Republic, District 1999 - 2009 [Level 2; inconsistent boundaries, harmonized by name]
Kyrgyz Republic, District 1999 - 2009 [Level 2; inconsistent boundaries, harmonized by name]
Kyrgyz Republic, District 1999 - 2009 [Level 2; inconsistent boundaries, harmonized by name]
Kyrgyz Republic, District 1999 - 2009 [Level 2; inconsistent boundaries, harmonized by name]
Kyrgyz Republic, District 1999 - 2009 [Level 2; inconsistent boundaries, harmonized by name]
2205
Ak-Suisk district
2210
Dzheti-Oguz district
2215
Issyk Kul district
2220
Tonsk district
2225
Tyup district
2410
City of Karakol
2420
City of Balykchi
3204
Ala-Bukin district
3207
Bazar-Korgon district
3211
Aksyi district
3215
Nooken district
3220
Suzak district
3223
Toguz-Torouz district
3225
Toktogul district
3230
Chatkalsk district
3408
City of Kok-Yangak
3410
City of Dzhalal Abad
3420
City of Tash-Kumyr
3430
City of MaiLuu-Suu
3440
City of Kara-Kul
4210
Ak-Talin district
4220
At-Bashin district
4230
Dzhumgal district
4235
Kochkor district
4245
Naryn oblast
4249
Tien Shan district
4400
City of Naryn
5214
Batken Rayon, City of Kenesh Batken
5236
Liailiak Rayon
5258
Kadamjai Rayon
5420
City of Suliukta
5430
City of Kyzyl-Kiya
6207
Alay district
6211
Aravan district
6226
Kara-Suisk district
6242
Nookat district
6246
Kara-Kuldjin district
6255
Uzghen district
6259
Chon-Alay district
6400
City of Osh
7215
Kara-Buurin district
7220
Bakai-Atinsk district
7225
Manas district
7232
Talas district
7400
City of Talas
8203
Alamudun district
8206
Ysyk-Atinsk district
8209
Zhaiyl district
8213
Kemin district
8217
Moscow district
8219
Panfilov district
8222
Sokuluk district
8223
Chui district
8400
City of Chui-Tokmok
11201
Bishkek city: Lenin district
11202
Bishkek city: October district
11203
Bishkek city: Pervomaysky district
11204
Bishkek city: Sverdlovsk district
11999
Districts with less than 15,000 population in Gorkenesh Bishkek
GEO2_KGX identifies the district (rayon) within the Kyrgyz Republic in all sample years. Districts are the second level administrative units of the country, after states. GEO2_ KGX is harmonized by name and does not account for boundary changes over time.
The full set of geography variables for the Kyrgyz Republic 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 the Kyrgyz Republic. Year specific geography and maps along with variables that are spatially harmonized at the second level of geography and account for political boundary changes across census years will become available in the near future.
Geography: A-L 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
Year structure was built
Year structure was built
Year structure was built
Year structure was built
Year structure was built
NIU (not in universe)
1870
1870 or earlier
1871
1871
1872
1872
1873
1873
1874
1874
1875
1875
1876
1876
1877
1877
1878
1878
1879
1879
1880
1880
1881
1881
1882
1882
1883
1883
1884
1884
1885
1885
1886
1886
1887
1887
1888
1888
1889
1889
1890
1890
1891
1891
1892
1892
1893
1893
1894
1894
1895
1895
1896
1896
1897
1897
1898
1898
1899
1899
1900
1900
1901
1901
1902
1902
1903
1903
1904
1904
1905
1905
1906
1906
1907
1907
1908
1908
1909
1909
1910
1910
1911
1911
1912
1912
1913
1913
1914
1914
1915
1915
1916
1916
1917
1917
1918
1918
1919
1919
1920
1920
1921
1921
1922
1922
1923
1923
1924
1924
1925
1925
1926
1926
1927
1927
1928
1928
1929
1929
1930
1930
1931
1931
1932
1932
1933
1933
1934
1934
1935
1935
1936
1936
1937
1937
1938
1938
1939
1939
1940
1940
1941
1941
1942
1942
1943
1943
1944
1944
1945
1945
1946
1946
1947
1947
1948
1948
1949
1949
1950
1950
1951
1951
1952
1952
1953
1953
1954
1954
1955
1955
1956
1956
1957
1957
1958
1958
1959
1959
1960
1960
1961
1961
1962
1962
1963
1963
1964
1964
1965
1965
1966
1966
1967
1967
1968
1968
1969
1969
1970
1970
1971
1971
1972
1972
1973
1973
1974
1974
1975
1975
1976
1976
1977
1977
1978
1978
1979
1979
1980
1980
1981
1981
1982
1982
1983
1983
1984
1984
1985
1985
1986
1986
1987
1987
1988
1988
1989
1989
1990
1990
1991
1991
1992
1992
1993
1993
1994
1994
1995
1995
1996
1996
1997
1997
1998
1998
1999
1999
2000
2000
2001
2001
2002
2002
2003
2003
2004
2004
2005
2005
2006
2006
2007
2007
2008
2008
2009
2009
2010
2010
2011
2011
9998
Under construction
9999
Unknown
BUILTYR indicates the year in which construction was completed on the building in which the household resides.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Age of structure, coded from intervals
Age of structure, coded from intervals
Age of structure, coded from intervals
Age of structure, coded from intervals
Age of structure, coded from intervals
Less than 1 year old
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
101
101
102
102
103
103
104
104
105
105
106
106
107
107
108
108
109
109
110
110
111
111
112
112
113
113
114
114
115
115
116
116
117
117
118
118
119
119
120
120
121
121
122
122
123
123
124
124
125
125
126
126
127
127
128
128
129
129
130
130
131
131
132
132
133
133
134
134
135
135
136
136
137
137
138
138
139
139
140
140
141
141
142
142
143
143
144
144
145
145
146
146
147
147
148
148
149
149
150
150
151
151
152
152
153
153
154
154
155
155
156
156
157
157
158
158
159
159
160
160
161
161
162
162
163
163
164
164
165
165
166
166
167
167
168
168
169
169
170
170
171
171
172
172
173
173
174
174
175
175
176
176
177
177
178
178
179
179
180
180
181
181
182
182
183
183
184
184
185
185
186
186
187
187
188
188
189
189
190
190
191
191
192
192
193
193
194
194
195
195
196
196
197
197
198
198
199
199
200
200+
998
Unknown
999
NIU (not in universe)
AGESTRUCT2 gives the estimated age of the structure.
Dwelling Characteristics Variables -- HOUSEHOLD
IPUMS
Living area in square meters
Living area in square meters
Living area in square meters
Living area in square meters
Living area in square meters
LIVEAREA describes the total living area in the dwelling inhabited by the household.
LIVEAREA is a 3-digit numeric variable.
000 = NIU (not in universe)
999 = Unknown
Unless otherwise specified: 998+
Austria 1991-2001: 150+
Belarus 1999: 201+
Germany 1987: 361+
Hungary 2001: 260+
Iran 2006: 501+
Italy 2001: 150+
Romania 2002: 221+
Slovenia 2002: 101+
Spain 2001: 181+
Switzerland 1980-1990: 400+
Switzerland 2000: 500+
Dwelling Characteristics 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.
PERNUM is a 3-digit numeric variable.
Technical Person 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
Year of birth
Year of birth
Year of birth
Year of birth
Year of birth
NIU (not in universe)
1843
1843
1845
1845
1850
1850
1853
1853
1854
1854
1856
1856
1858
1858
1859
1859
1860
1860
1861
1861
1862
1862
1863
1863
1864
1864
1865
1865
1866
1866
1867
1867
1868
1868
1869
1869
1870
1870
1871
1871
1872
1872
1873
1873
1874
1874
1875
1875
1876
1876
1877
1877
1878
1878
1879
1879
1880
1880
1881
1881
1882
1882
1883
1883
1884
1884
1885
1885
1886
1886
1887
1887
1888
1888
1889
1889
1890
1890
1891
1891
1892
1892
1893
1893
1894
1894
1895
1895
1896
1896
1897
1897
1898
1898
1899
1899
1900
1900
1901
1901
1902
1902
1903
1903
1904
1904
1905
1905
1906
1906
1907
1907
1908
1908
1909
1909
1910
1910
1911
1911
1912
1912
1913
1913
1914
1914
1915
1915
1916
1916
1917
1917
1918
1918
1919
1919
1920
1920
1921
1921
1922
1922
1923
1923
1924
1924
1925
1925
1926
1926
1927
1927
1928
1928
1929
1929
1930
1930
1931
1931
1932
1932
1933
1933
1934
1934
1935
1935
1936
1936
1937
1937
1938
1938
1939
1939
1940
1940
1941
1941
1942
1942
1943
1943
1944
1944
1945
1945
1946
1946
1947
1947
1948
1948
1949
1949
1950
1950
1951
1951
1952
1952
1953
1953
1954
1954
1955
1955
1956
1956
1957
1957
1958
1958
1959
1959
1960
1960
1961
1961
1962
1962
1963
1963
1964
1964
1965
1965
1966
1966
1967
1967
1968
1968
1969
1969
1970
1970
1971
1971
1972
1972
1973
1973
1974
1974
1975
1975
1976
1976
1977
1977
1978
1978
1979
1979
1980
1980
1981
1981
1982
1982
1983
1983
1984
1984
1985
1985
1986
1986
1987
1987
1988
1988
1989
1989
1990
1990
1991
1991
1992
1992
1993
1993
1994
1994
1995
1995
1996
1996
1997
1997
1998
1998
1999
1999
2000
2000
2001
2001
2002
2002
2003
2003
2004
2004
2005
2005
2006
2006
2007
2007
2008
2008
2009
2009
2010
2010
2011
2011
2012
2012
2013
2013
9999
Unknown
BIRTHYR gives the person's year of birth.
Demographic Variables -- PERSON
IPUMS
Educational attainment, Kyrgyz Republic
Educational attainment, Kyrgyz Republic
Educational attainment, Kyrgyz Republic
Educational attainment, Kyrgyz Republic
Educational attainment, Kyrgyz Republic
None or less than primary
1
Illiterate
2
Less than primary, literate
10
Primary general
20
Basic general
30
Secondary
31
Basic vocational
32
Secondary, specialized
33
Secondary, general
40
Higher education
41
Higher education, incomplete
42
Bachelor's
43
Specialist
44
Master's
45
Higher education, complete
98
Unknown
99
NIU (not in universe)
EDUCKG indicates the person's educational attainment in terms of the level of schooling completed.
Education 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
Sex
Sex
Sex
Sex
Sex
1
Male
2
Female
9
Unknown
SEX reports the sex (gender) of the respondent.
Demographic Variables -- PERSON
IPUMS
Consensual union
Consensual union
Consensual union
Consensual union
Consensual union
1
Yes, in consensual union
2
No, married
8
Unknown
9
NIU (not in universe)
CONSENS indicates whether the respondent was in a consensual union -- a de facto marriage.
Demographic Variables -- PERSON
IPUMS
Month of birth
Month of birth
Month of birth
Month of birth
Month of birth
1
January
2
February
3
March
4
April
5
May
6
June
7
July
8
August
9
September
10
October
11
November
12
December
98
Unknown
99
NIU (not in universe)
BIRTHMO indicates the person's month of birth.
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
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 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
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
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
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
Citizenship
Citizenship
Citizenship
Citizenship
Citizenship
1
Citizen, not specified
2
Citizen by birth
3
Naturalized citizen
4
Not a citizen
5
Without citizenship, stateless
8
Unknown
9
NIU (not in universe)
CITIZEN indicates the person's citizenship status within the country in which they were enumerated.
Nativity and Birthplace 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
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
District of birth, Kyrgyz Republic
District of birth, Kyrgyz Republic
District of birth, Kyrgyz Republic
District of birth, Kyrgyz Republic
District of birth, Kyrgyz Republic
101
Batken Rayon
102
Kadamjai Rayon
103
Liailiak Rayon
104
City of Kyzyl-Kiya
105
City of Suliukta
106
City of Kenesh Batken
107
Unknown city, Batken region
201
Ala-Bukin district
202
Bazar-Korgon district
203
Aksyi district
204
Nooken district
205
Suzak district
206
Toguz-Torouz district
207
Toktogul district
208
Chatkalsk district
209
City of Dzhalal Abad
210
City of Kara-Kul
211
City of Kok-Yangak
212
City of MaiLuu-Suu
213
City of Tash-Kumyr
219
Unknown district or city, Jalal-Abad region
301
Ak-Suisk district
302
Dzheti-Oguz district
303
Issyk Kul district
304
Tonsk district
305
Tyup district
306
City of Karakol
307
City of Balykchi
309
Unknown district or city, Issyk-Kul region
401
Ak-Talin district
402
At-Bashin district
403
Dzhumgal district
404
Kochkor district
405
Tien Shan district
406
City of Naryn
409
Unknown district or city Naryn region
501
Alay district
502
Aravan district
503
Kara-Kuldjin district
504
Kara-Suisk district
505
Nookat district
506
Uzghen district
507
Chon-Alay district
508
City of Osh
601
Bakai-Atinsk district
602
Kara-Buurin district
603
Manas district
604
Talas district
605
City of Talas
609
Unknown district or city, Talasskaya region
701
Alamudun district
702
Zhaiyl district
703
Kemin district
704
Moscow district
705
Panfilov district
706
Sokuluk district
707
Ysyk-Atinsk district
708
City of Chui-Tokmok
709
Unknown district, Chuya region
801
City of Bishkek
997
Born in Kyrgyz Republic, not specified
998
Foreign country
999
Unknown
BPLKG indicates the person's district (rayon) of birth within Kyrgyz Republic.
Nativity and Birthplace 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
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
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.
IND is a 5-digit numeric variable.
Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes.
Please see the codes for: KG2009A_0437
Work Variables -- PERSON
IPUMS
Source of livelihood
Source of livelihood
Source of livelihood
Source of livelihood
Source of livelihood
1
Work
2
Property or entrepreneurial income
3
Pension
4
Unemployment benefits
5
Illness or disability benefits
6
Other social support
7
Under state security or care
8
Scholarship
9
Apprenticeship
10
Credits, savings, or capital sale
11
Household support (dependent)
12
Assistance from relatives in country
13
Assistance from relatives, acquintances abroad
14
Multiple sources
15
Other
99
Unknown
INCSRC indicates the respondent's primary source of livelihood, whether from work, benefits, or various other categories.
Income 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.
MOMLOC is a 3-digit numeric variable.
0 = No mother of this person present in the household.
1 or higher = The person number of this person's mother
Constructed Family Interrelationship Variables -- PERSON
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.
POPLOC is a 3-digit numeric variable.
0 = No father of this person present in the household.
1 or higher = The person number of this person's father
Constructed Family Interrelationship Variables -- PERSON
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.
SPLOC is a 3-digit numeric variable.
0 = No spouse of this person present in the household.
1 or higher = The person number of this person's spouse
Constructed Family Interrelationship Variables -- PERSON
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).
FAMUNIT is a 2-digit numeric variable.
If there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on.
Constructed Family Interrelationship Variables -- PERSON
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
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
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
This variable indicates the person number (within household).
Technical Person Variables -- PERSON
IPUMS
Location of absent persons
Location of absent persons
Location of absent persons
Location of absent persons
Location of absent persons
Location of absent persons
Persons who are absent from the household
1
Issyk Kul district
2
Karakol district
3
Jalal Abad city
4
Tash Kumyr city
5
Batken district
6
Sulukta city
7
Kyzyl-Kiya city
8
Kara-Suisk district
9
Uzghen district
10
Ysyk-Atinsk district
11
Zhaiyl district
12
Sokuluk district
13
Tokmok City
14
Other areas of Kyrgyz Republic
21
China
22
Kazakhstan
23
Republic of Korea
24
Saudi Arabia
25
Russia
26
Uzbekistan
29
Other Asia
31
Germany
32
Switzerland
33
Turkey
34
Ukraine
39
Other Europe
49
Africa
51
Eastern Samoa (USA)
59
Other Americas, Oceania, and Antarctic
98
Unknown
99
NIU (Not in universe)
This variable indicates the geographic location of a non-present member of the household.
Migration Variables -- PERSON
IPUMS
How long have absent persons been away
How long have absent persons been away
How long have absent persons been away
How long have absent persons been away
How long have absent persons been away
How long have absent persons been away
Persons who are absent from the household
1
Less than a month
2
Up to a year
3
More than a year
9
NIU (Not in universe)
This variable indicates how long a non-present member of the household has been away.
Migration Variables -- PERSON
IPUMS
Reason for absence
Reason for absence
Reason for absence
Reason for absence
Reason for absence
Reason for absence
Persons who are absent from the household
1
Work
2
Learning
4
Sem. Obst.
5
Other
9
NIU (Not in universe)
This variable indicates the reason for absence of non-present members of the household.
Migration Variables -- PERSON
IPUMS
Relationship to person enumerated first
Relationship to person enumerated first
Relationship to person enumerated first
Relationship to person enumerated first
Relationship to person enumerated first
1. Relationship to the person enumerated first in a household
[] 1 First person recorded
[] 2 Spouse
[] 3 Daughter, son
[] 4 Parent
[] 5 Sibling
[] 6 Parent-in-law
[] 7 Daughter-in-law, brother-in-law
[] 8 Grandparent
[] 9 Grandchild
[] 10 Other relative
[] 11 No relation
No. of the mother or father (from column 1 of the list) _ _
All persons
1
Person enumerated first
2
Spouse
3
Daughter or son
4
Parent
5
Sibling
6
Parent-in-law
7
Daughter- or son-in-law
8
Grandparent
9
Grandchild/great grandchild
10
Other relative
11
No relation
This variable indicates the person's relationship to the person enumerated first.
Demographic Variables -- PERSON
IPUMS
Number of the mother or father
Number of the mother or father
Number of the mother or father
Number of the mother or father
Number of the mother or father
1. Relationship to the person enumerated first in a household
[] 1 First person recorded
[] 2 Spouse
[] 3 Daughter, son
[] 4 Parent
[] 5 Sibling
[] 6 Parent-in-law
[] 7 Daughter-in-law, brother-in-law
[] 8 Grandparent
[] 9 Grandchild
[] 10 Other relative
[] 11 No relation
No. of the mother or father (from column 1 of the list) _ _
All persons
No mother or father in the 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
This variable indicates the number of the person's mother or father.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Sex
Sex
Sex
Sex
Sex
2. Sex
[] 1 Male
[] 2 Female
All persons
1
Male
2
Female
This variable indicates the person's sex.
Demographic Variables -- PERSON
IPUMS
Absent on census night
Absent on census night
Absent on census night
Absent on census night
Absent on census night
3. Residential status
[] 1 Absent
[] 2 Residing
All persons
Residing
1
Absent
This variable indicates if the person was absent on the census night.
Migration Variables -- PERSON
IPUMS
Month of birth
Month of birth
Month of birth
Month of birth
Month of birth
4. Date of birth
Day _ _
Month _ _
Year _ _ _ _
Age _ _ _
All persons
1
January
2
February
3
March
4
April
5
May
6
June
7
July
8
August
9
September
10
October
11
November
12
December
This variable indicates the person's month of birth.
Demographic Variables -- PERSON
IPUMS
Year of birth
Year of birth
Year of birth
Year of birth
Year of birth
4. Date of birth
Day _ _
Month _ _
Year _ _ _ _
Age _ _ _
All persons
1912
1912 or earlier
1913
1913
1914
1914
1915
1915
1916
1916
1917
1917
1918
1918
1919
1919
1920
1920
1921
1921
1922
1922
1923
1923
1924
1924
1925
1925
1926
1926
1927
1927
1928
1928
1929
1929
1930
1930
1931
1931
1932
1932
1933
1933
1934
1934
1935
1935
1936
1936
1937
1937
1938
1938
1939
1939
1940
1940
1941
1941
1942
1942
1943
1943
1944
1944
1945
1945
1946
1946
1947
1947
1948
1948
1949
1949
1950
1950
1951
1951
1952
1952
1953
1953
1954
1954
1955
1955
1956
1956
1957
1957
1958
1958
1959
1959
1960
1960
1961
1961
1962
1962
1963
1963
1964
1964
1965
1965
1966
1966
1967
1967
1968
1968
1969
1969
1970
1970
1971
1971
1972
1972
1973
1973
1974
1974
1975
1975
1976
1976
1977
1977
1978
1978
1979
1979
1980
1980
1981
1981
1982
1982
1983
1983
1984
1984
1985
1985
1986
1986
1987
1987
1988
1988
1989
1989
1990
1990
1991
1991
1992
1992
1993
1993
1994
1994
1995
1995
1996
1996
1997
1997
1998
1998
1999
1999
2000
2000
2001
2001
2002
2002
2003
2003
2004
2004
2005
2005
2006
2006
2007
2007
2008
2008
2009
2009
This variable indicates the person's year of birth.
Demographic Variables -- PERSON
IPUMS
Age
Age
Age
Age
Age
4. Date of birth
Day _ _
Month _ _
Year _ _ _ _
Age _ _ _
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
94
94
95
95
96
96+
This variable indicates the person's age.
Demographic Variables -- PERSON
IPUMS
Nationality
Nationality
Nationality
Nationality
Nationality
5. Nationality
________
All persons
1
Kyrgyz
2
Azerbaijani
3
Armenian
4
Belarusian
5
Georgian
6
Kazakh
9
Moldovan
10
Russian
11
Tajik
12
Turkmen
13
Uzbek
14
Ukrainian
18
Avar
25
American
28
Arab
31
Afghan (Pashtun)
33
Balkar
34
Bashkir
38
Bulgarian
48
Greek
50
Dargin
52
Dungan
53
Jewish
62
Kalmyk
66
Karachai
71
Chinese
74
Korean
81
Kurd
83
Lezgin
88
Mordovian
94
German
101
Persian
102
Polish
112
Tatar
120
Turkish
122
Meskhetian Turkish
123
Ottoman
127
Uighur
135
Hemshil
139
Romany
142
Chechen
144
Chuvash
161
Pakistani (Punjabis, Sindhis, Baluchis)
199
Other
This variable indicates the person's nationality.
Nativity and Birthplace Variables -- PERSON
IPUMS
Mother tongue
Mother tongue
Mother tongue
Mother tongue
Mother tongue
6. Language
6. 1 Mother tongue
________
All persons
1
Kyrgyz
2
Azerbaijani
3
Armenian
4
Belarusian
5
Georgian
6
Kazakh
8
Russian
9
Tajik
10
Turkmen
11
Uzbek
12
Ukrainian
15
Avar
21
English
23
Arabic
26
Afghan
28
Bashkir
32
Bulgarian
41
Dargin
42
Dungan
49
Yazdi
51
Kalmykia
54
Karachay-Balkar
59
Chinese
62
Korean
68
Kurdish
72
Lezgin
83
German
89
Persian
100
Tatar
107
Turkish
108
Turkic
112
Uigur
119
Chemshil
122
Gypsy
125
Chechen
146
Pakistan (Urdu)
199
Other
This variable indicates the person's mother tongue.
Ethnicity and Language Variables -- PERSON
IPUMS
Second fluently spoken language
Second fluently spoken language
Second fluently spoken language
Second fluently spoken language
Second fluently spoken language
6. Language
6. 2 Other fluently spoken languages
________
Persons who speak a second language
1
Kyrgyz
5
Georgian
6
Kazakh
8
Russian
9
Tajik
11
Uzbek
12
Ukrainian
21
English
23
Andean
42
Dungan
49
Yezidsky
59
Chinese
62
Korean
83
German
100
Tatar
107
Turkish
112
Uigur
115
French
199
Other
999
No second language spoken
This variable indicates the person's second fluently spoken language.
Ethnicity and Language Variables -- PERSON
IPUMS
Third fluently spoken language
Third fluently spoken language
Third fluently spoken language
Third fluently spoken language
Third fluently spoken language
6. Language
6. 2 Other fluently spoken languages
________
Persons who speak a third language
1
Kyrgyz
6
Kazakh
8
Russian
9
Tajik
11
Uzbek
21
English
23
Arabic
42
Dungan
49
Yezidsky
59
Chinese
62
Korean
83
German
100
Tatar
107
Turkish
112
Uigur
115
French
199
Other
999
No third language spoken
This variable indicates the person's third fluently spoken language.
Ethnicity and Language Variables -- PERSON
IPUMS
District or city of birth
District or city of birth
District or city of birth
District or city of birth
District or city of birth
7. Place of birth (name a town, rayon, country)
________
All persons
100
Abroad
11000
Bishkek
21000
Osh
22050
Ak-Suisk district
22100
Dzheti-Oguz district
22150
Issyk Kul district
22200
Tonsk district
22250
Tyup district
22999
Unknown district, Issyk-Kul region
24100
Karakol district
24200
Balykchy district
24999
Unknown city, Issyk-Kul region
32040
Ala-Bukin district
32070
Bazar-Korgon district
32110
Aksyi district
32150
Nooken district
32200
Suzak district
32230
Toguz-Torouz district
32250
Toktogul district
32300
Chatkalsk district
32999
Unknown district, Jalal-Abad region
34100
Jalal Abad city
34200
Tash Kumyr city
34300
Mailuu-Suu city
34400
Kara-Kul city
34999
Unknown city, Jalal-Abad region
42100
Ak-Talin district
42200
At-Bashin district
42300
Dzhumgal district
42350
Kochkor district
42450
Tien Shan district
42999
Unknown district, Naryn region
44999
Unknown city, Naryn region
52140
Batken district
52360
Lailyak district
52580
Kadamzhai district
54000
Kara-Suu region
54100
G. Batken city
54200
Sulukta city
54300
Kyzyl-Kiya city
62070
Alay district
62110
Aravan district
62260
Kara-Suisk district
62420
Nookat district
62460
Kara-Kuldjin district
62550
Uzghen district
62590
Chon-Alay district
72150
Kara-Buurin district
72200
Bakai-Atinsk district
72250
Manas district
72320
Talas district
72999
Unkonwn district, Talas region
74999
Unknown city, Talas region
82030
Alamudun district
82060
Ysyk-Atinsk district
82090
Zhaiyl district
82130
Kemin district
82170
Moscow district
82190
Panfilov district
82220
Sokuluk district
84000
Tokmok City
89999
Unknown district, Chui region
This variable indicates the person's place of birth.
Nativity and Birthplace Variables -- PERSON
IPUMS
Country of birth
Country of birth
Country of birth
Country of birth
Country of birth
7. Place of birth (name a town, rayon, country)
________
All persons
1
Kyrgyz Republic
4
Afghanistan
31
Azerbaijan
51
Armenia
112
Belarus
156
China
268
Georgia
276
Germany
356
India
364
Iran
398
Kazakhstan
410
Republic of Korea
498
Moldova
586
Pakistan
643
Russia
762
Tajikistan
792
Turkey
795
Turkmenistan
804
Ukraine
840
United States of America (USA)
860
Uzbekistan
910
Other Asia
920
Africa
930
Other Europe
940
Other Americas
998
Undocumented
This variable indicates the person's country of birth.
Nativity and Birthplace Variables -- PERSON
IPUMS
Citizenship
Citizenship
Citizenship
Citizenship
Citizenship
8. Citizenship
[] 1 Kyrgyz Republic
[] 2 Without citizenship
Citizen of another country (specify the country) _ _ _
All persons
1
Kyrgyz Republic
2
Stateless
3
Other country
This variable indicates the person's citizenship status.
Nativity and Birthplace Variables -- PERSON
IPUMS
Residing from birth in current settlement
Residing from birth in current settlement
Residing from birth in current settlement
Residing from birth in current settlement
Residing from birth in current settlement
9. Constantly residing
9.1 Residing temporarily from birth in this settlement
[] 1 Yes
[] 2 No
If "NO" specify
The year you have been temporarily residing here ________
Place of previous residence (name a town, rayon, country)
________
All persons
1
Yes
2
No
This variable indicates if the person has resided in their current settlement since birth.
Migration Variables -- PERSON
IPUMS
Year moved to current settlement
Year moved to current settlement
Year moved to current settlement
Year moved to current settlement
Year moved to current settlement
9. Constantly residing
9.1 Residing temporarily from birth in this settlement
[] 1 Yes
[] 2 No
If "NO" specify
The year you have been temporarily residing here ________
Place of previous residence (name a town, rayon, country)
________
Persons who have not lived in the same settlement since birth
1934
1934 or earlier
1935
1935
1936
1936
1937
1937
1938
1938
1939
1939
1940
1940
1941
1941
1942
1942
1943
1943
1944
1944
1945
1945
1946
1946
1947
1947
1948
1948
1949
1949
1950
1950
1951
1951
1952
1952
1953
1953
1954
1954
1955
1955
1956
1956
1957
1957
1958
1958
1959
1959
1960
1960
1961
1961
1962
1962
1963
1963
1964
1964
1965
1965
1966
1966
1967
1967
1968
1968
1969
1969
1970
1970
1971
1971
1972
1972
1973
1973
1974
1974
1975
1975
1976
1976
1977
1977
1978
1978
1979
1979
1980
1980
1981
1981
1982
1982
1983
1983
1984
1984
1985
1985
1986
1986
1987
1987
1988
1988
1989
1989
1990
1990
1991
1991
1992
1992
1993
1993
1994
1994
1995
1995
1996
1996
1997
1997
1998
1998
1999
1999
2000
2000
2001
2001
2002
2002
2003
2003
2004
2004
2005
2005
2006
2006
2007
2007
2008
2008
2009
2009
9999
NIU (Not in universe)
This variable indicates the year when the person moved to current residence.
Migration Variables -- PERSON
IPUMS
Reason for moving
Reason for moving
Reason for moving
Reason for moving
Reason for moving
9.2 Reasons for residence change
[] 1 Economical
[] 2 Social
[] 3 Ecological (climatic)
[] 4 Other reasons
Persons who have not been in the same residence since birth
1
Economic
2
Social
3
Environmental (climatic)
4
Other reasons
9
NIU (Not in universe)
This variable indicates the person's reason for moving.
Migration Variables -- PERSON
IPUMS
Marital status
Marital status
Marital status
Marital status
Marital status
10. Marital status
(persons 15 years and over)
[] 1 Never married
[] 2 Registered married
[] 3 Not registered married
[] 4 Widowed
[] 5 Divorced
[] 6 Separated
No. of wife [or] husband (from column 1 of the form [1]) _ _
Persons age 15+
1
Single (never married)
2
Registered married
3
Not registered married (in union)
4
Widowed
5
Divorced
6
Separated
9
NIU (Not in universe)
This variable indicates the person's marital status.
Demographic Variables -- PERSON
IPUMS
Person number of spouse
Person number of spouse
Person number of spouse
Person number of spouse
Person number of spouse
10. Marital status
(persons 15 years and over)
[] 1 Never married
[] 2 Registered married
[] 3 Not registered married
[] 4 Widowed
[] 5 Divorced
[] 6 Separated
No. of wife [or] husband (from column 1 of the form [1]) _ _
All persons
No spouse identified
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
This variable indicates the person number of the person's spouse.
Constructed Family Interrelationship Variables -- PERSON
IPUMS
Education level
Education level
Education level
Education level
Education level
11. Education
(for persons 10 years and over)
[] 1 Higher - Bachelor
[] 2 Higher - Specialist
[] 3 Higher - Magister
[] 4 Higher incomplete
[] 5 Secondary specialized
[] 6 Prevocational (vocational)
[] 7 Secondary general
[] 8 Basic (compulsory general)
[] 9 Elementary general
[] 10 Without elementary general education
Persons age 6+
1
Higher - bachelor
2
Higher - specialist
3
Higher - master
4
Incomplete higher
5
Secondary vocational
6
Initial vocational
7
Secondary general
8
Basic general education
9
Completed primary
10
Less than primary education
98
Unknown
99
NIU (Not in universe)
This variable indicates the person's education level.
Education Variables -- PERSON
IPUMS
Read and write
Read and write
Read and write
Read and write
Read and write
11. Education
(for persons 10 years and over)
11.1 Are you able to read and write?
(for persons without elementary general education)
[] 11 Yes
[] 12 No
Persons age 6+ who had less than primary education
1
Yes
2
No
8
Unknown
9
NIU (Not in universe)
This variable indicates if the person knows how to read and write.
Education Variables -- PERSON
IPUMS
Type of degree
Type of degree
Type of degree
Type of degree
Type of degree
11. Education
(for persons 10 years and over)
11.2 Persons with scientific degree, specify
[] 13 Candidate of sciences
[] 14 Doctor of sciences
Persons age 10+ with scientific degree
1
Candidate of sciences
2
Doctor of sciences
9
NIU (Not in universe)
This variable indicates the person's type of degree.
Education Variables -- PERSON
IPUMS
Type of educational institution attending
Type of educational institution attending
Type of educational institution attending
Type of educational institution attending
Type of educational institution attending
12. Type of educational establishment you are attending
For persons 6 years and over
[] 1 Graduate and doctorate
[] 2 Higher educational establishment
[] 3 Secondary specialized educational establishment
[] 4 Vocational school
[] 5 General educational establishment of all types
[] 6 Other school
[] 7 Not attending
Persons age 6+
1
Graduate and doctorate
2
Higher educational establishment
3
Secondary specialized educational establishment
4
Vocational school
5
General educational establishment of all types
6
Other school
7
Not attending
9
NIU (Not in universe)
This variable indicates to which type of educational institution the person is attending.
Education Variables -- PERSON
IPUMS
Attending preschool
Attending preschool
Attending preschool
Attending preschool
Attending preschool
13. Are you attending preschool?
For persons of preschool age
[] 1 Yes
[] 2 No
Persons age 6 and under
1
Yes
2
No
8
Unknown
9
NIU (Not in universe)
This variable indicates if the child is attending preschool.
Education Variables -- PERSON
IPUMS
Sources of income
Sources of income
Sources of income
Sources of income
Sources of income
14. Sources of income
[] 1 Income from employment
[] 2 Scholarship (stipend)
[] 3 Pension
[] 4 Subsidy
[] 5 Other type of state support
[] 6 Savings
[] 7 Income from property
[] 8 On dependence
[] 9 Other sources
From above listed, specify the main source of income _
All persons
1
Income from employment
2
Scholarship
3
Pension
4
Allowance
5
Other type of state support
6
Savings
7
Income from property
8
Dependent
9
Other source
This variable indicates the person's sources of income.
Income Variables -- PERSON
IPUMS
Type of industry, enterprise or organization
Type of industry, enterprise or organization
Type of industry, enterprise or organization
Type of industry, enterprise or organization
Type of industry, enterprise or organization
15. Employment
For persons 12 years and over
15.1 Place of work and activity type of an enterprise, organization (detailed name of activity)
________
Persons age 12+ who are employed
4
Agriculture
13
Vegetable, ornamental plants and nursery products
17
Growing of fruit, nuts, beverage crops and spices
21
Breeding cattle
23
Sheep, goats, horses, asses, mules and hinnies
29
Farming of poultry
34
Animal husbandry, n.e.c.
37
Growing of crops combined with farming of animals (mixed farming)
40
Providing services in crop
43
Provision of livestock, except veterinary activities
50
Forestry and logging
54
Providing services to forestry and logging
59
Hunting, fishing and pisiculture
67
Mining and agglomeration of hard coal and lignite
84
Crude oil and natural gas
88
Providing services for oil and gas
92
Mining of uranium and thorium ores
97
Mining of iron ores
101
Mining of non-ferrous ores, except uranium and thorium ores
120
Gravel and sand extraction
131
Quarrying and extraction, n.e.c.
142
Meat and fish production
152
Fruit and vegetable preserving and processing
159
Manufacture of oils and fats
166
Milk and cheese
169
Manufacture of ice cream
172
Manufacture of grain mill products and starches
184
Manufacture of bread; manufacture of confectionery non-durable storage
186
Manufacture of rusks and biscuits, confectionery manufacture long-term storage
188
Sugar production
190
Manufacture of cocoa, chocolate and sugar confectionery
192
Production of pasta
194
Processing of tea and coffee
200
Manufacture of other food products not elsewhere classified
205
Distilled and fermented alcoholic beverages
209
Wine and cider production
213
Manufacture of other non-distilled fermented beverages from material
217
Manufacture of malt
219
Production of mineral waters and soft drinks
223
Manufacture of tobacco products
228
Spinning of cotton fibers
231
Carded wool fiber spinning
260
Manufacture of textiles and related products
270
Manufacture of carpets and rugs
287
Manufacture of knitted and crocheted fabrics and clothing
291
Leather related production
294
Manufacture of workwear
296
Manufacture of clothing
300
Manufacture of other wearing apparel and accessories
320
Manufacture of wood, wood pulp and related products
350
Manufacture of paper and paper products
370
Publishing
377
Printing of newspapers
379
Printing, n.e.c.
400
Production of petroleum
434
Manufacture of pharmaceuticals
439
Manufacture of soap and detergents, cleaning and polishing preparations
476
"
479
Manufacture of chemical products, including plastics, paints, fertilizers, etc.
483
Glass and ceramic manufacture
514
Manufacture of bricks, tiles and construction products, in baked clay
517
Production of cement
525
Manufacture of concrete, plaster, cement and stone work
556
Metal and metal products
598
Manufacture of metal structures
603
Manufacture of structural metal products
620
Main engineering processes
623
Manufacture of metal cutlery, tools, locks, wire and related fabricated metal products
646
Manufacture of engines, machines, and related equipment
734
Manufacture of electric domestic appliances, office machinery, and computers
748
Manufacture of electric motors, generators and transformers
752
Manufacture of electricity distribution and control apparatus
762
Manufacture of electric lamps and lighting equipment
769
Manufacture of electrical equipment, except electrical equipment for engines and vehicles sreds
777
Manufacture of electrical and radioactive
780
Manufacture of transmission equipment
785
Production of equipment for the reception, recording and reproduction of sound and pictures
790
Manufacture of medical and surgical equipment and orthopedic adapted
822
Car production
863
Manufacture of chairs and seating
869
Manufacture of other furniture
871
Manufacture of mattresses
893
Other manufacturing and production
914
Steam and hot water
920
Collection, purification and distribution of water
925
Demolition, excavation, and exploratory drilling
933
Civil works
938
Construction of roads, airfields and sport facilities
940
Construction of water projects
947
Electric installation work
951
Plumbing
956
Stuccoing
958
Joinery and carpentry installation work
962
Painting and glazing
964
Other finishing work
972
Motor trade
976
Maintenance and repair of motor vehicles
979
Sale of motor vehicle parts and accessories
988
Retail sale of automotive fuel
992
Sales agents
1011
Wholesale trade
1100
Retail sale in non-specialized stores with food, beverages
1102
Other retail sale in non-specialized stores
1105
Retail sale of fruit and vegetables
1107
Retail sale of meat and meat products
1112
Retail trade in bakery products, cakes, flour confectionery and sugar confectionery
1118
Other retail sale of food in specialized stores
1121
Retail sale of pharmaceutical products
1125
Retail sale of perfume and cosmetics
1128
Retail sale of textiles
1130
Retail sale of clothing
1133
Retail sale of footwear and leather goods
1136
Retail sale of furniture and home furnishings
1139
Retail sale of electrical household appliances and radio and television goods
1143
Retail sale of hardware, paints and glass
1145
Retail sale of books, newspapers and stationery
1147
Other retail sale in specialized stores
1159
Other retail sales
1162
Retail sale via stalls and markets
1169
Repair of footwear and other leather products
1172
Repair of electrical household goods
1177
Repair of household goods personal effects, not elsewhere classified
1187
Provision of services of hotels with restaurants
1189
Providing services hotels without restaurants
1192
Providing services youth tourist camps and mountain tourist bases
1196
The provision of services other places to live
1199
Service delivery restaurants
1201
Service provision bars
1204
Providing services canteens and institutions
1206
Delivery of prepared food
1211
Railway transport
1214
Other land passenger transport, following a schedule
1218
Taxi operation
1220
Other land passenger transport
1222
Freight transport
1229
Activities of river transport
1234
Air transport, following time-table
1237
Air transport, not-scheduled
1246
Other transport and related auxiliary activities
1257
Activities of travel agencies
1260
Organization of cargo transportation
1265
Postal and courier activities
1266
National post activities
1271
Telecommunications
1276
Central banking
1278
Other monetary intermediation
1285
Providing a credit
1294
Pension benefits
1299
Other financial intermediation and insurance, n.e.c.
1314
Development, buying, and selling of real estate
1322
Agencies Real estate
1325
Real Estate Management
1329
Transportation and machine rental
1365
Computing and database consulting, maintenance and repair
1369
Research and development on natural sciences, engineering, social science, and humanities
1376
Legal activities
1379
Activities in the field of accounting and auditing
1383
Market research, business management consulting, and holding company management
1388
Activities in the field of architecture, engineering research and technical advice in these
1395
Technical testing and research
1400
Advertising activity
1403
Labour recruitment and selection of staff
1406
Investigation and security
1409
Maintenance and cleaning of industrial and residential buildings, equipment and vehicles
1412
Photographic activities
1419
State management
1427
Management of social programs
1429
Regulate and promote the efficient conduct of economic activity
1431
Support services by government
1434
International activities
1436
Defence activities
1438
Activities in the field of justice and justice
1440
Activities to ensure public order and safety
1442
Security activities in emergencies
1445
Activities in the area of ??compulsory social insurance
1450
Primary education (first stage)
1455
General secondary education (second stage)
1457
Technical and vocational secondary education
1461
Higher education
1466
Adult and other education not included in other categories
1473
Hospital activities
1479
Medical practice
1481
Dental Practice
1483
Other human health activities
1486
Veterinary activities
1489
Social services with and without accommodation
1497
Activities of business and employers organizations
1499
Activities of professional organizations
1502
Activities of political organizations and trade unions
1505
Activities of religious organizations
1509
Activities of other membership organizations nec
1513
Production and dissemination of films and videos
1520
Activities in the field of radio and television
1523
For art
1527
Operation of arts facilities
1529
Activity fairs and amusement parks
1531
Other spectacular and entertaining activity
1536
News agency activities
1539
Library and archives activities
1545
Museums activities and preservation of historical sites and buildings
1548
The activity of botanical and zoological gardens and nature reserves
1552
Operation of sports facilities
1554
Other activities in the field of sport
1557
Activities Gambling
1559
Other activities and recreation, not nec
1563
Laundry, dry cleaning and dyeing of textile and fur products
1566
Hairdressing and other beauty treatment
1568
Funeral and related services
1570
Physical well-being activities
1577
Activities of households as employers of domestic staff
1582
Activities of extraterritorial organizations
1597
Production of electricity
1602
Power transmission
1604
Distribution and sale of electricity
1605
Electrical Distribution
1609
Production of gaseous fuel
1611
Distribution of gaseous fuels through pipelines and selling it
1651
Software development and consulting in this field
1653
Providing secretarial services and translation services
1657
Provision of other services to consumers
1660
Removal and treatment of waste water
1662
Removal and treatment of solid waste
1664
Sanitation, decontamination and similar services
1665
Sanitation, decontamination and similar services
1668
Activities of households producing goods for own use
1672
Activities of households for production services for own consumption
1679
Other industries, n.e.c.
9998
Unknown
9999
NIU (Not in universe)
This variable indicates the activity type of the enterprise or organization that the person works for.
Work: Industry Variables -- PERSON
IPUMS
Employment status
Employment status
Employment status
Employment status
Employment status
15. Employment
For persons 12 years and over
16 Status in employment
[] 1 Employed
[] 2 Self-employed
Persons age 12+ who have income from employment
1
Employed
2
Self-employed
9
NIU (Not in universe)
This variable indicates the person's employment status.
Work Variables -- PERSON
IPUMS
Looking for work
Looking for work
Looking for work
Looking for work
Looking for work
15. Employment
For persons 12 years and over
17. Looking for work?
For unemployed persons 15 years and over
[] 1 Yes
[] 2 No
If yes,
[] 3 Ready to start work next two weeks
if no, specify the reason
[] 4 Absence of work
[] 5 Illness, disability
[] 6 Family reasons
[] 7 No need to work
[] 8 Other reasons
Persons age 15+ who are not employed
1
Yes
2
No
9
NIU (Not in universe)
This variable indicates if an unemployed person is looking for work.
Work Variables -- PERSON
IPUMS
Reason not looking for work
Reason not looking for work
Reason not looking for work
Reason not looking for work
Reason not looking for work
15. Employment
For persons 12 years and over
17. Looking for work?
For unemployed persons 15 years and over
[] 1 Yes
[] 2 No
If yes,
[] 3 Ready to start work next two weeks
if no, specify the reason
[] 4 Absence of work
[] 5 Illness, disability
[] 6 Family reasons
[] 7 No need to work
[] 8 Other reasons
Persons age 15+ who are unemployed and not looking for work
1
Lack of work
2
Illness, disability
3
Family reasons
4
No need to work
5
Another reason
8
Unknown
9
NIU (Not in universe)
This variable indicates the reason of an unemployed person for not looking for work.
Work Variables -- PERSON
IPUMS
Total number of children born
Total number of children born
Total number of children born
Total number of children born
Total number of children born
18. Women, 15 years of age and over, specify
How many children have you given birth to?
Boys _ _
Girls _ _
How many children are alive?
Boys _ _
Girls _ _
How many of them live elsewhere?
Boys _ _
Girls _ _
Females age 15+
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
NIU (Not in universe)
This variable indicates the total number of children born to a woman.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of male children born
Number of male children born
Number of male children born
Number of male children born
Number of male children born
18. Women, 15 years of age and over, specify
How many children have you given birth to?
Boys _ _
Girls _ _
How many children are alive?
Boys _ _
Girls _ _
How many of them live elsewhere?
Boys _ _
Girls _ _
Females age 15+
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10+
99
NIU (Not in universe)
This variable indicates the number of male children born to a woman.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of female children born
Number of female children born
Number of female children born
Number of female children born
Number of female children born
18. Women, 15 years of age and over, specify
How many children have you given birth to?
Boys _ _
Girls _ _
How many children are alive?
Boys _ _
Girls _ _
How many of them live elsewhere?
Boys _ _
Girls _ _
Females age 15+
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10+
99
NIU (Not in universe)
This variable indicates the number of female children born to a woman.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of children surviving
Number of children surviving
Number of children surviving
Number of children surviving
Number of children surviving
18. Women, 15 years of age and over, specify
How many children have you given birth to?
Boys _ _
Girls _ _
How many children are alive?
Boys _ _
Girls _ _
How many of them live elsewhere?
Boys _ _
Girls _ _
Females age 15+
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+
99
NIU (Not in universe)
This variable indicates the number of children born to a woman that are still alive.
Fertility and Mortality 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
18. Women, 15 years of age and over, specify
How many children have you given birth to?
Boys _ _
Girls _ _
How many children are alive?
Boys _ _
Girls _ _
How many of them live elsewhere?
Boys _ _
Girls _ _
Females age 15+
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9+
99
NIU (Not in universe)
This variable indicates the number of male children born to a woman that are still alive.
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
18. Women, 15 years of age and over, specify
How many children have you given birth to?
Boys _ _
Girls _ _
How many children are alive?
Boys _ _
Girls _ _
How many of them live elsewhere?
Boys _ _
Girls _ _
Females age 15+
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9+
99
NIU (Not in universe)
This variable indicates the number of female children born to a woman that are still alive.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of children born that are living elsewhere
Number of children born that are living elsewhere
Number of children born that are living elsewhere
Number of children born that are living elsewhere
Number of children born that are living elsewhere
18. Women, 15 years of age and over, specify
How many children have you given birth to?
Boys _ _
Girls _ _
How many children are alive?
Boys _ _
Girls _ _
How many of them live elsewhere?
Boys _ _
Girls _ _
Females age 15+ who ever had children
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12+
98
Unknown
99
NIU (Not in universe)
This variable indicates the number of children born to a woman that are living elsewhere.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of male children born that are living elsewhere
Number of male children born that are living elsewhere
Number of male children born that are living elsewhere
Number of male children born that are living elsewhere
Number of male children born that are living elsewhere
18. Women, 15 years of age and over, specify
How many children have you given birth to?
Boys _ _
Girls _ _
How many children are alive?
Boys _ _
Girls _ _
How many of them live elsewhere?
Boys _ _
Girls _ _
Females age 15+ who ever had male children
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8+
99
NIU (Not in universe)
This variable indicates the number of male children born to a woman that are living elsewhere.
Fertility and Mortality Variables -- PERSON
IPUMS
Number of female children born that are living elsewhere
Number of female children born that are living elsewhere
Number of female children born that are living elsewhere
Number of female children born that are living elsewhere
Number of female children born that are living elsewhere
18. Women, 15 years of age and over, specify
How many children have you given birth to?
Boys _ _
Girls _ _
How many children are alive?
Boys _ _
Girls _ _
How many of them live elsewhere?
Boys _ _
Girls _ _
Females age 15+ who ever had female children
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8+
99
NIU (Not in universe)
This variable indicates the number of female children born to a woman that are living elsewhere.
Fertility and Mortality 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.
PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description.
Technical Person 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
Years residing in current locality
Years residing in current locality
Years residing in current locality
Years residing in current locality
Years residing in current locality
Less than 1 year
1
1 year (or 1 year or less)
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
19
19 years
20
20 years
21
21 years
22
22 years
23
23 years
24
24 years
25
25 years
26
26 years
27
27 years
28
28 years
29
29 years
30
30 years
31
31 years
32
32 years
33
33 years
34
34 years
35
35 years
36
36 years
37
37 years
38
38 years
39
39 years
40
40 years
41
41 years
42
42 years
43
43 years
44
44 years
45
45 years
46
46 years
47
47 years
48
48 years
49
49 years
50
50 years
51
51 years
52
52 years
53
53 years
54
54 years
55
55 years
56
56 years
57
57 years
58
58 years
59
59 years
60
60 years
61
61 years
62
62 years
63
63 years
64
64 years
65
65 years
66
66 years
67
67 years
68
68 years
69
69 years
70
70 years
71
71 years
72
72 years
73
73 years
74
74 years
75
75 years
76
76 years
77
77 years
78
78 years
79
79 years
80
80 years
81
81 years
82
82 years
83
83 years
84
84 years
85
85 years
86
86 years
87
87 years
88
88 years
89
89 years
90
90 years
91
91 years
92
92 years
93
93 years
94
94 years
95
95+
96
Less than 5 years
97
More than 5 years
98
Unknown
99
NIU (not in universe)
MIGYRS1 indicates how many years the person has resided in their current locality of residence.
Migration Variables -- PERSON
IPUMS
Reason for migration
Reason for migration
Reason for migration
Reason for migration
Reason for migration
NIU (not in universe)
10
Work
11
Seeking work
12
Job relocation
13
Job assignment
14
Opportunity
15
Proximity to work
19
Other work
20
Family move
21
Follow household head
22
Follow spouse
23
Follow relative
30
Study
31
End of education
40
Marriage, divorce, widowhood
41
Marriage or union
42
Divorce or widowhood
50
Insecurity, disaster, or violence
51
War
52
Violence or insecurity
53
Social or political problems, including security
54
Natural disaster
57
Natural disaster or insecurity
58
Environmental/climatic
60
Other reason
61
Health
62
Repatriation
63
Retirement
64
House or flat acquisition
65
Housing problems
66
Visiting
67
Ordination
68
Military or institutional housing
69
Other reason, not elsewhere classified
99
Not specified
MIGCAUSE indicates the reason why the person moved from their previous place of residence.
Migration 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
Speaks English
Speaks English
Speaks English
Speaks English
Speaks English
1
Yes
2
No
8
Unknown
9
NIU (not in universe)
SPEAKENG indicates whether the respondent could speak English or if English was the respondent's language of literacy.
Ethnicity and Language Variables -- PERSON
IPUMS
Mother tongue, Kyrgyz Republic
Mother tongue, Kyrgyz Republic
Mother tongue, Kyrgyz Republic
Mother tongue, Kyrgyz Republic
Mother tongue, Kyrgyz Republic
1
Kyrgyz
2
Azerbaijani
3
Armenian
4
Belarusian
5
Georgian
6
Kazakh
7
Russian
8
Tajik
9
Turkmen
10
Uzbek
11
Ukrainian
12
Avar
13
Agul
14
English
15
Arabic
16
Afghan
17
Bashkir
18
Bulgarian
19
Greek
20
Dargin
21
Dungan
22
Hebrew
23
Yazdi
24
Kalmykia
25
Karachay-Balkar
26
"
27
Chinese
28
Korean
29
Kurdish
30
Lak
31
Lezgin
32
Mordovian
33
German
34
Persian
35
Tatar
36
Turkish
37
Turkic
38
Uigur
39
Chemshil
40
Gypsy
41
Chechen
42
Chuvash
43
Pakistan (Urdu)
44
Hindi
98
Response suppressed
99
Unknown
MTONGKG indicates the respondent's native tongue. If they had difficulty naming a tongue, the one used most often in the household was identified. Parents were to determine the language of children too young to speak.
Ethnicity and Language Variables -- PERSON
IPUMS
Country of birth
Country of birth
Country of birth
Country of birth
Country of birth
NIU (not in universe)
10000
Africa
11000
Eastern Africa
11010
Burundi
11020
Comoros
11030
Djibouti
11040
Eritrea
11050
Ethiopia
11051
Ethiopia (including Eritrea)
11060
Kenya
11070
Madagascar
11080
Malawi
11090
Mauritius
11100
Mozambique
11110
Reunion
11120
Rwanda
11130
Seychelles
11140
Somalia
11150
South Sudan
11160
Uganda
11170
Tanzania
11180
Zambia
11190
Zimbabwe
11990
Eastern Africa, n.s.
12000
Middle Africa
12010
Angola
12020
Cameroon
12030
Central African Republic
12040
Chad
12050
Congo
12060
Democratic Republic of Congo
12070
Equatorial Guinea
12080
Gabon
12090
Sao Tome and Principe
12990
Middle Africa, n.s.
13000
Northern Africa
13010
Algeria
13011
Algeria/Tunisia
13020
Egypt
13021
Egypt/Sudan
13030
Libya
13040
Morocco
13050
Sudan
13060
Tunisia
13070
Western Sahara
13990
Northern Africa, n.s.
14000
Southern Africa
14010
Botswana
14020
Lesotho
14030
Namibia
14040
South Africa
14050
Swaziland
14990
Southern Africa, n.s.
15000
Western Africa
15010
Benin
15020
Burkina Faso
15021
Upper Volta
15030
Cape Verde
15040
Ivory Coast
15050
Gambia
15060
Ghana
15070
Guinea
15080
Guinea-Bissau
15081
Guinea-Bissau and Cape Verde
15090
Liberia
15100
Mali
15110
Mauritania
15120
Niger
15130
Nigeria
15140
St. Helena and Ascension
15150
Senegal
15160
Sierra Leone
15170
Togo
15990
West Africa, n.s.
19990
Africa, other and n.s.
19991
Central and South Africa
19992
East and Central Africa
19993
Southeastern Africa
19994
Saharan Africa
20000
Americas
21000
Caribbean
21010
Anguilla
21020
Antigua-Barbuda
21030
Aruba
21040
Bahamas
21050
Barbados
21060
British Virgin Islands
21070
Cayman Isles
21080
Cuba
21090
Dominica
21100
Dominican Republic
21110
Grenada
21120
Guadeloupe
21130
Haiti
21140
Jamaica
21150
Martinique
21160
Montserrat
21170
Netherlands Antilles
21180
Puerto Rico
21190
St. Kitts-Nevis
21200
St. Croix
21210
St. John
21220
St. Lucia
21230
St Thomas
21240
St. Vincent
21250
Trinidad and Tobago
21260
Turks and Caicos
21270
U.S. Virgin Islands
21990
Other Caribbean and n.s.
21991
Caribbean commonwealth, n.s.
22000
Central America
22010
Belize/British Honduras
22020
Costa Rica
22030
El Salvador
22040
Guatemala
22050
Honduras
22060
Mexico
22070
Nicaragua
22080
Panama
22081
Panama Canal Zone
22990
Central America, n.s.
22991
Central America and Caribbean
23000
South America
23010
Argentina
23020
Bolivia
23030
Brazil
23040
Chile
23050
Colombia
23060
Ecuador
23070
Falkland Islands
23080
French Guiana
23090
Guyana/British Guiana
23100
Paraguay
23110
Peru
23120
Suriname
23130
Uruguay
23140
Venezuela
23990
South America, other and n.s.
23991
South America or Central America, n.s.
23992
Central/South America and Caribbean
24000
North America
24010
Bermuda
24020
Canada
24030
Greenland
24040
United States
24990
North America, other and n.s.
24991
North America/Oceania
29990
Americas, other and n.s.
30000
Asia
31000
Eastern Asia
31010
China
31011
Hong Kong
31012
Macau
31013
Taiwan
31020
Japan
31030
Korea
31031
Korea, DPR (North)
31032
Korea, RO (South)
31040
Mongolia
31990
Eastern Asia, n.s.
32000
South-Central Asia
32010
Afghanistan
32020
Bangladesh
32030
Bhutan
32040
India
32041
India/Pakistan
32042
India/Pakistan/Bangladesh/Sri Lanka
32050
Iran
32060
Kazakhstan
32070
Kyrgyzstan
32080
Maldives
32090
Nepal
32100
Pakistan
32101
Pakistan/Bangladesh
32110
Sri Lanka (Ceylon)
32120
Tajikistan
32130
Turkmenistan
32140
Uzbekistan
32999
South-Central Asia, n.s.
33000
South-Eastern Asia
33010
Brunei
33020
Cambodia (Kampuchea)
33030
East Timor
33040
Indonesia
33050
Laos
33060
Malaysia
33070
Myanmar (Burma)
33080
Philippines
33090
Singapore
33100
Thailand
33110
Vietnam
33990
South-Eastern Asia, n.s.
34000
Western Asia
34010
Armenia
34020
Azerbaijan
34030
Bahrain
34040
Cyprus
34050
Georgia
34060
Iraq
34070
Israel
34071
Israel/Palestine
34080
Jordan
34090
Kuwait
34100
Lebanon
34110
Palestinian Territories
34111
West Bank
34112
Gaza Strip
34120
Oman
34130
Qatar
34140
Saudi Arabia
34150
Syria
34151
Syria/Lebanon
34160
Turkey
34170
United Arab Emirates
34180
Yemen
34990
Western Asia, n.s.
34991
Middle East
39990
Asia, other and n.s.
39991
Central Asia and Middle East, n.s.
39992
Far East, n.s.
39993
Eastern/Southeast Asia, n.s.
39994
Asia/Middle East, other and n.s.
40000
Europe
41000
Eastern Europe
41010
Belarus
41020
Bulgaria
41021
Bulgaria/Greece
41030
Czech Republic/Czechoslovakia
41040
Hungary
41050
Poland
41060
Moldova
41070
Romania
41080
Russia/USSR
41090
Slovakia
41100
Ukraine
41990
Eastern Europe, other and n.s.
41991
Albania, Bulgaria, Czech, Hungary, Romania, Yugoslavia
41992
Central-Eastern Europe
42000
Northern Europe
42010
Denmark
42020
Estonia
42030
Faroe Islands
42040
Finland
42050
Iceland
42060
Ireland
42070
Latvia
42080
Lithuania
42090
Norway
42100
Svalbard and Jan Mayen Islands
42110
Sweden
42120
United Kingdom
42990
Northern Europe, n.s.
43000
Southern Europe
43010
Albania
43020
Andorra
43030
Bosnia and Herzegovina
43040
Croatia
43050
Gibraltar
43060
Greece
43070
Italy
43071
Vatican City
43080
Malta
43090
Portugal
43100
San Marino
43110
Slovenia
43120
Spain
43121
Spain/Portugal
43130
Macedonia
43140
Yugoslavia
43141
Montenegro
43142
Serbia
43143
Serbia and Montenegro
43144
Kosovo
43990
Southern Europe, n.s.
43991
Gibraltar/Malta
43992
Portugal/Greece
43993
Italy, Holy See, San Marino
44000
Western Europe
44010
Austria
44020
Belgium
44021
Belgium/Luxemburg
44022
Belgium/Netherlands/Luxemburg
44030
France
44040
Germany
44041
Germany/Austria
44042
West Germany
44050
Liechtenstein
44060
Luxembourg
44070
Monaco
44080
Netherlands
44090
Switzerland
44990
Western Europe, n.s.
44991
Belgium, Denmark, Luxembourg, Netherlands
49991
Turkey and U.S.S.R.
49992
European Union
49993
European Union (Original 15)
49994
Other European Union
49995
EEA, Switzerland, associated microstates
49999
Europe, other and n.s.
50000
Oceania
51000
Australia and New Zealand
51010
Australia
51020
New Zealand
51030
Norfolk Islands
51999
Australia and New Zealand, n.s.
52000
Melanesia
52010
Fiji
52020
New Caledonia
52030
Papua New Guinea
52040
Solomon Islands
52050
Vanuatu (New Hebrides)
52999
Melanesia, n.s.
53000
Micronesia
53010
Kiribati
53020
Marshall Islands
53030
Nauru
53040
Northern Mariana Isls.
53050
Palau
53990
Micronesia, n.e.c.
54000
Polynesia
54010
Cook Islands
54020
French Polynesia
54030
Niue
54040
Pitcairn Island
54050
Samoa
54060
Eastern Samoa
54070
Tokelau
54080
Tonga
54090
Tuvalu
54100
Wallis and Futuna Isls.
54990
Polynesia, n.s.
55000
U.S. Pacific Possessions
55010
American Samoa
55020
Baker Island
55030
Guam
55040
Howland Island
55050
Johnston Atoll
55060
Kingman Reef
55070
Midway Islands
55080
Wake Island
55990
Other US Pacific
59990
Oceania, n.s.
60000
OTHER ABROAD
60100
U.S. Outlying Areas and Territories
60200
Africa/Other
60300
Central/South America or Africa
60400
Asia/Africa
60500
Europe, Australia, New Zealand
60600
Other commonwealth
60700
Asia, Australia, Oceania, n.s.
69900
Other countries, not specified
99999
Unknown
BPLCOUNTRY indicates the person's country of birth.
Nativity and Birthplace 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
Nativity status
Nativity status
Nativity status
Nativity status
Nativity status
NIU (not universe)
1
Native-born
2
Foreign-born
9
Unknown/missing
NATIVITY indicates whether the person was native- or foreign-born.
Nativity and Birthplace 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.]
This is a 4-digit numeric variable with 0 implied decimal places
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.]
This is a 9-digit numeric variable with 0 implied decimal places
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.]
This is a 10-digit numeric variable with 0 implied decimal places
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.]
This is a 3-digit numeric variable with 0 implied decimal places
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.]
This is a 1-digit numeric variable with 0 implied decimal places
Technical Person Variables -- PERSON
IPUMS