PHC 2000

 Reference ID MNG-NSO-EN-PHC-2000-v1.0 Created on Sep - 03 - 2021
Year 2000 Last modified Feb - 25 - 2026
Country Mongolia Page views 169
Producer(s) National Statistical Office Downloads 0
Collection(s) Population and Housing Census

Overview

Identification

COUNTRY

Mongolia

TITLE

PHC 2000
 

STUDY TYPE

Population and Housing Census [hh/popcen]
 

SERIES INFORMATION

The first census in the 20th century was conducted in 1918. Further censuses being conducted in 1935, 1944, 1956, 1963, 1969, 1979,1989 and 2000.

In 1918, the population of the Empire of Bogd was estimated at 647.5 thousand persons. In its day the 1956 census was considered as technically advanced conducted by an established and dedicated census organization. New advances were introduced for the census of 1963, particularly the first use of a computer, which was expected to speed processing and generally improve census methodology. The basic design of the census was developed by the Commission for Mutual Economic Assistance to assure conformity with other censuses in the region. 1017.1 thousand persons were enumerated in the 1963 census. The censuses of 1969, 1979 and 1989 also followed the methodological guidelines developed by the Commission. Moreover, in accordance with UN recommendations these three censuses were conducted once in 10 years and included questions on housing. From 1979 the population and housing censuses were conducted jointly with population surveys using broad-based questionnaires. For instance, the survey of industrial and agricultural workers, 'Workers' and 'Herdsmen', were conducted together with the 1979 census. The survey of unemployed population, and the survey among women on reproductive issues were conducted in 1989. The 2000 census differed from earlier censuses in many ways. As the first to be

conducted during the transitional period to a market economy, it was expected to reflect a changing emphasis in the demand for economic and social data. The 2000 census was based largely on United Nations principles and recommendations for conducting censuses and thus, in meeting global

standards, could be thought of as the first truly modern census to be conductedin the country.

On 5 January 2000, there were 2,373,493 persons enumerated as residents of Mongolia. Of this figure 1,177,981 were males and 1,195,512 were females. At the 1989 census, the resident population was 2,043,954 persons. Thus, during the eleven years between the censuses the population grew by 16.1 percent, which is equivalent to an average annual rate of about 1.4 percent. This rate is low compared with the recent past. From 1956 the growth rate increased sharply, remaining above an annual equivalent of 2.5 percent up to the 1989 census. Thus the current inter-censal growth rate is the lowest since 1944.
 

ID NUMBER

MNG-NSO-EN-PHC-2000-v1.0

Version

VERSION DESCRIPTION

-v2.0:Edited data for internal use only.
 

PRODUCTION DATE

2001-07-01

Overview

ABSTRACT

The objective of the Population and housing census 2000 is to provide comprehensive and basic statistical data required to study changes in economic, social and demographic status of Mongolia for the last 11 years and its reasons and determinants, to plan economic and social development of the first years of next century and formulate state policies to implement such planned measures and make researches and analysis. As well as, it would be collected compiled new data required to assess a process of first stage of implementation and elaborate for the “Population Development Policy of Mongolia”, which approved by the parliament.

The advantage of census conducting is to be provided comprehensive information for summarizing and evaluating states of population growth, migration, settlement, education, employment, housing condition and behavior of the population groups processed and disaggregated by all administrative units compared with other population data sources. Moreover, census is significant to provide accurate data to international partners at the present time, which Mongolian foreign relations have expanding and collaboration with international organization has becoming more close.

The census would be crucial for revision of accuracy and reality of annual population statistics.
 

KIND OF DATA

Census/enumeration data [cen]
 

UNITS OF ANALYSIS

- Households

- Houses

- Member of households
 

Scope

NOTES

In the early discussions on the scope of the population census it was agreed that the following topics would be included:

Social and demographic characteristics

Name

Relation to household head

Date of birth

Age

Sex

Marital status

Citizenship

Ethnicity

Geographical and migration characteristics

Residential status

Duration of residence

Place of birth

Place of residence five years ago

Educational characteristics

Educational level

Literacy

School attendance

Economic characteristics

Activity status

Occupation

Industry

Employment status

Unemployment
 

Coverage

GEOGRAPHIC COVERAGE

All aimags, soums, districts, bags, horoos and capital city.
 

UNIVERSE

a.Population census

The census shall be covered the persons as followed:

- Citizens of Mongolia who are in the country at the time of census;

- Foreigners and persons without citizenship who are living in Mongolia for more than 183 days and

foreigners persons without citizenship who are taking permission to stay for over 6 months from the

authorized organizations;

- Citizens of Mongolia and their families who worked at the diplomatic representative offices,

consulates and in the international organizations in foreign countries at the time of census;

- Citizens of Mongolia who are temporarily absent from Mongolia due to work, study and stay in

overseas by personal reasons during the census period;

b.Housing census

The following types of living quarters shall be covered in the housing census:

- House

- Apartment

- Students dormitory

- Public dormitory

- Other public apartment

- Non-living quarters

- All types of gers

Another important concept for the measurement of coverage related to the timing of the census. While the enumeration covered the seven-day period from 5-11 January 2000, it is important for the interpretation of the data that the census results relate to a more precise point in time. The night of 4th January 2000 was designated as census night. Generally, this concept of a fixed census night did not cause problems for respondents or enumerators. However, in the few cases where location on census night did introduce difficulty, where, for example, the respondent traveled during census night, the more precise time reference of midnight on census night was introduced.
 

Producers and Sponsors

PRIMARY INVESTIGATOR(S)

Name Affiliation
National Statistical Office of Mongolia  

OTHER PRODUCER(S)

Name Affiliation Role
United Nations Statistical Division   Assistance

FUNDING

Name Abbreviation Role
Government of Mongolia GOF Financial assistance
United Nations Population Fund UNFPA Financial assistance

OTHER ACKNOWLEDGEMENTS

Name Affiliation Role
Australian Bureau of Statistics ABS Active assistance
United Nations Statistical Commission UNSC Active assistance

Metadata Production

METADATA PRODUCED BY

Name Abbreviation Affiliation Role
Nansalmaa Zundiu   NSO Documentation of the study
Tsolmon Tserendejid   NSO Documentation of the study

DATE OF METADATA PRODUCTION

2008-02-15

DDI DOCUMENT VERSION

Version 1.0
 

DDI DOCUMENT ID

DDI-MNG-NSO-EN-PHC-2000-v1.0

Sampling

Sampling Procedure


None sampled.
 

Deviations from Sample Design


None reported
 

Response Rate


None reported
 

Weighting


None reported

Data Collection

Data Collection Dates

Start End Cycle
2000-01-05 2000-01-11 1

Data Collection Mode

Face-to-face [f2f]

DATA COLLECTION NOTES


The census enumeration shall be commenced at 8 a.m. on 5 January 2000, and it completed on 11 January. The post enumeration census shall be conducted from 12 January 2000 over three days. The midnight of 4 January 2000 is the census moment, and babies born after the census moment as well persons died before the census moment would not enumerated in the census.
The enumeration shall be reached to living quarters (usual place of residence) and counted people and their housing with its condition in order to interview accordance with census questionnaire.
The enumerators shall be counted usual place of residence as houses, apartments, gers and public dormitory of all households and persons, who are covering the census in order to record their housing with its condition.

Data Collectors

Name Abbreviation Affiliation
National Statistical Office of Mongolia NSO  

SUPERVISION


The obligations and duties of supervisors
The supervisors would be work with main duties as to control for enumerators execution, provide accuracy of responses, receive and check all completed questionnaires, produce preliminary results on fixed time and carry out post-enumeration in order to conduct census with high quality and full coverage.
a.The obligations and duties of supervisors
1.To obtain knowledge and skills able to find and correct any fault of enumerators through active participation in the census trainings and well learning of questionnaire and its filling instruction,
2.To follow-up guides, recommendations and instructions of census commissions and temporary bureaus in soums and bags/khoroos of aimag center soums,
3.To revise whether enumerators cover all population according to census maps, which have approved by census bureaus or not and whether they able to take accurate responses for the questions in questionnaire,
4.To investigate with heads and members of census commission, temporary bureau own responsible boundary compared with approved census map, if there is any difference, to make adjunct/identification, inform to census commissions of soum, district, bag and khoroo, to make resolution and to exactly arrange boundary with nearby census part,
5.To visit particular households in own responsible part (does not matter they live apartment, non-living quarter, ger or other places) accordance with census map, revise a number of households in the particular housing, names of resident people, visitors, who are staying less than the six months and temporary absent ones and identify whether any one is missing or not,
6.To check enumerators whether did lists of people, who are perhaps absent at home during the census days or not, give advice precede how and when cover them in the census and in the particular cases, to make complex measurements from the commissions of bags and khoroos,
7.To make a special consideration to cover people who live in house top/roof, porch, duct of heating system, forests and cliffs and power the control,
8.To introduce with enumerators' cases to make overall revision on population mobility in urban areas, observe and note perhaps births, deaths and migration at the census period and to work closely with census commissions of bags and khoroos in this matter,
9.To actively involve in advocacy to publicize purpose, principles, rules and significance of the census to the public,
10.To produce detailed schedule to work with enumerators during the stages of preparation, census conducting and receiving census materials, approved by census commission and introduce it to the enumerators and follow it strictly,
11.To deliver census maps for every enumerators and introduce for them,
12.To personify introduce with process of enumerators' work for the first two days of census, give an advice, check each completed questionnaires, if there is any mistake, make correction and provide instruction to fill without any mistake, urban supervisors should be check completed questionnaires in the particular day and rural supervisors must be check all completed questionnaires in the next day. To ask head of census commission to change particular enumerator, who is making mistakes repeatedly even the giving instruction on regular basis,
13.To check attendance of all enumerators, if anyone didn't come, shall be clarify his/her causes and inform to the head of census commission, and make appropriate decision immediately,
14.Each enumerator should be counted 15 percent of total households and person to be counted during the census days, for instance, rural enumerator should be counted 4-5 households or 23-27 people and urban enumerator must be counted 10-12 households or 45-53 people. This limit is essential to monitor census process. Although, on Saturday and Sunday of 8-9 January 2000 enumerators should try to count as more as possible. Supervisor should be monitor for it.
15.Supervisors shall be informed to the temporary bureau of soum, bag and khoroo how many people have counted in their responsible areas, ask to census commission of soum, bag and khoroo issues on additional enumerators, if needed.
16.When supervisors check completed questionnaires, shall be use them neat and tidy accordance with census instruction because of all questionnaires will become main document for compiling results of state population and housing census,
17.To participate controlling enumeration carry out from the census commission of soum, bag, khoroo in person,
18.To express own views to the census commission about improvement of daily arrangements of the census, faced problems and its solutions,
19.To control for enumerators to use and keep questionnaires neat and tidy and without faulty,
20.To compile preliminary results of census by forms UD-1, 2, 3, 4, 5 and submit to temporary bureau of soum, district, bag and khoroo on fixed time,
21.To hand over exactly counted questionnaires and other forms to the enumerators, return them separately by filled up and blank questionnaires and other forms, and reckon up with temporary bureau,
22.All supervisors should keep responses confidential in accordance with Mongolian Law on "Confidentiality of private information"(paragraph 4, article 5) and Mongolian Law on Statistics (article 3, chapter 22), revised in 1997,
b.Forbidden things for the supervisors
1.To give away responses confidential to the other individuals except of staffs for census commission and temporary bureau of soum, bag and khoroo,
2.To waste and destroy filled up questionnaires,
3.To fold, crush and tear up filled up questionnaires,
4.To correct and check filled up questionnaires by other pens and pencils coloured as red, black and green etc, except blue and dark blue,

Data Processing

Data Editing


During the early planning stages it was clear that the existing hardware and peripherals in NSO were not sufficient to enable it to process a modern census. However, with the financial assistance of UNFPA, under the MON/97/P10 project, “Strengthening the Capacity of the National Statistical Office in Data Processing, Analysis and Dissemination”, and the MON/97/P04 project, “Strengthening the Population and Reproductive Health Database for Mongolia”, NSO was provided with new equipment, components and software. It was thus able to establish the basis for strengthening the technical capacity required for the 2000 census. The NSO purchased a range of equipment including 38 Compaq computers, two ACER server computers and other equipment.

On the software side, the NSO decided to process the census using IMPS (Integrated Microcomputer Processing System). Apart from the use of IMPS, the NSO developed other census applications, for example, using the CLIPPER and VISUAL BASIC languages. A special application to speed coding named SEARCH was also developed. Data entry was designed for LAN using a Windows NT Server V4.0 as the control center. The system facilitated data processing, restricting archiving and control functions to the server. Daily progress reports were also provided as part of the Data Control System.
Editing was completed in two stages. In the first stage records were edited manually and in the second they were automatically edited using the editing module of the IMPS package, Concor. The BPCS staff monitored editing work. All editing was completed by 15 October 2000.

Other Processing


Immediately following the census, all records were checked for completeness at the aimag and district levels before being dispatched to the NSO for further processing. On arrival at the NSO, the batches were again checked and receipt was recorded. An important task was in data preparation involved the coding of census responses. From early March, the coding and data entry operations commenced. While most of the coding was done manually the system was designed to undertake limited computer assisted coding for the more complex questions. This automatic coding saved valuable time and resulted in more uniform and high quality coding.The data entry for the PHC 2000 is done by DPTD at the NSO head office in Ulaanbaatar. Data entry operations began on 24 April 2000. A number of controls were set up to ensure the operation went smoothly. A computer program was developed to record progress in data entry and in the performance of individual operators. To further monitor the efficiency and accuracy of data entry, all census materials of all districts of Ulaanbaatar and all aimag center soums were double-entered.

During actual operations 49 persons were working as data entry operators, nine persons were working as re-entry operators and eight persons were working as supervisors. Until July 2000 all staff operated in two shifts, each working for six days per week. By the end of July 2000 all data entry other than the special batches provided by the Ministries of Foreign Affairs, Defence and Justice had been completed. The coverage rules for these Ministries were complex and special edit rules needed to be developed.

 

file name

File: household.NSDstat

Valid cases: 546143

Width: 3

Type: numeric

Range: 1 - 921

Value Category Cases

File: household.NSDstat

Valid cases: 546143

Width: 2

Type: numeric

Range: 1 - 51

Value Category Cases

1


Arkhangai

24475



4.48%

2


Bayan_Olgii

19311



3.54%

3


Bayankhongor

20638



3.78%

4


Bulgan

15455



2.83%

5


Govi_Altai

14854



2.72%

6


Dornogovi

12251



2.24%

7


Dornod

17355



3.18%

8


Dundgovi

12291



2.25%

9


Zavkhan

21658



3.97%

10


Ovorkhangai

26945



4.93%

11


Omnogovi

11864



2.17%

12


Sukhbaatar

12810



2.35%

13


Selenge

22931



4.2%

14


Tov

23877



4.37%

15


Uvs

20413



3.74%

16


Khovd

18266



3.34%

17


Khovsgol

28814



5.28%

18


Khentii

17533



3.21%

19


Darkhan_Uul

19783



3.62%

20


Ulaanbaatar

164277



30.08%

21


Orkhon

17367



3.18%

22


Govisumber

2975



0.54%

23


Russia

0



0.54%

24


China

0



0.54%

25


Korea

0



0.54%

26


North Korea

0



0.54%

27


Germany

0



0.54%

28


Japan

0



0.54%

29


USA

0



0.54%

30


Turkey

0



0.54%

31


UK

0



0.54%

32


Bulgaria

0



0.54%

33


жїЎъб»pa

0



0.54%

34


India

0



0.54%

35


Kanad

0



0.54%

36


Lao

0



0.54%

37


Italia

0



0.54%

38


France

0



0.54%

39


Pakistan

0



0.54%

40


Yugaslavia

0



0.54%

41


Philippines

0



0.54%

42


Hungaria

0



0.54%

43


Czech

0



0.54%

44


Slovak Republic

0



0.54%

45


Austria

0



0.54%

46


Finland

0



0.54%

47


Viet nam

0



0.54%

48


Australia

0



0.54%

49


Poland

0



0.54%

50


Kazakstan

0



0.54%

51


Other

0



0.54%

File: household.NSDstat

Valid cases: 546143

Width: 2

Type: numeric

Range: 1 - 27

Value Category Cases

File: household.NSDstat

Valid cases: 546143

Width: 2

Type: numeric

Range: 0 - 29

Value Category Cases

0


No tosgon



0.54%

1


Tsagaan nuur



0.54%

2


Shargaljuut



0.54%

3


Saikhankhoroo



0.54%

4


Khyalganat



0.54%

5


Guulin



0.54%

6


Bayantooroi



0.54%

8


Zamiin_Uud



0.54%

9


Zulegtei



0.54%

11


Erdes



0.54%

12


Ereen



0.54%

13


Tosontsengel



0.54%

14


Tavantolgoi



0.54%

15


Zuunkharaa



0.54%

16


Tunkhel



0.54%

17


Kherkh



0.54%

18


Dulaankhaan



0.54%

19


Bugant



0.54%

20


Khotol



0.54%

21


Khailaastai



0.54%

22


Khar_Tarvagtai



0.54%

23


Khoshoot



0.54%

25


Khatgal



0.54%

27


Bor_Ondor



0.54%

28


Berkh



0.54%

29


Chandgana tal



0.54%

File: household.NSDstat

Valid cases: 546143

Width: 1

Type: numeric

Range: 1 - 5

Value Category Cases

1


Capital

164277



30.08%

2


Aimag center

119499



21.88%

3


Village

17082



3.13%

4


Soum center

85759



15.7%

5


Countryside

159526



29.21%

File: household.NSDstat

Valid cases: 546143

Width: 2

Type: numeric

Range: 1 - 96

Value Category Cases

File: household.NSDstat

Valid cases: 546143

Width: 3

Type: numeric

Range: 1 - 931

Value Category Cases

File: household.NSDstat

Valid cases: 546143

Width: 1

Type: numeric

Range: 1 - 3

Value Category Cases

1


House.own house

522621



95.69%

2


Shared house

17958



3.29%

3


Dormitory other

5564



1.02%

File: household.NSDstat

Valid cases: 546143

Width: 2

Type: numeric

Range: 1 - 99

Value Category Cases

File: household.NSDstat

Valid cases: 546143

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


House

270703



49.57%

2


Ger

275440



50.43%

File: household.NSDstat

Valid cases: 270703

Width: 1

Type: numeric

Range: 1 - 7

Value Category Cases

1


House

133919



49.47%

2


Apartment

119219



44.04%

3


Students dormito

4914



1.82%

4


Public dormitory

4579



1.69%

5


Other public.ap

3694



1.36%

6


Non_living quart

3479



1.29%

7


Other

899



0.33%

Sysmiss


275440


File: household.NSDstat

Valid cases: 270703

Width: 2

Type: numeric

Range: 0 - 99

Value Category Cases

0


19



0.01%

1


119089



43.99%

2


100508



37.13%

3


42256



15.61%

4


7440



2.75%

5


748



0.28%

6


291



0.11%

7


94



0.03%

8


76



0.03%

9


30



0.01%

10


35



0.01%

11


27



0.01%

12


90



0.03%

Sysmiss


275440


File: household.NSDstat

Valid cases: 270703

Width: 3

Type: numeric

Range: 0 - 999

Value Category Cases

File: household.NSDstat

Valid cases: 270703

Width: 1

Type: numeric

Range: 1 - 3

Value Category Cases

1


Centralized

121176



44.76%

2


Non_centralized

33473



12.37%

3


Other

116054



42.87%

Sysmiss


275440


File: household.NSDstat

Valid cases: 270703

Width: 1

Type: numeric

Range: 1 - 5

Value Category Cases

1


Hot & cold water

108194



39.97%

2


Cold water pipe

18567



6.86%

3


Well

86996



32.14%

4


Hand well

18089



6.68%

5


Other

38857



14.35%

Sysmiss


275440


File: household.NSDstat

Valid cases: 270703

Width: 1

Type: numeric

Range: 1 - 4

Value Category Cases

1


Through tube

39767



14.69%

2


Special hollow

140044



51.73%

3


Outside of house

63633



23.51%

4


No special place

27259



10.07%

Sysmiss


275440


File: household.NSDstat

Valid cases: 270703

Width: 1

Type: numeric

Range: 1 - 3

Value Category Cases

1


In.of.house sep

120226



44.41%

2


In.of.h public

8181



3.02%

3


Outside of house

142296



52.57%

Sysmiss


275440


File: household.NSDstat

Valid cases: 270703

Width: 1

Type: numeric

Range: 1 - 3

Value Category Cases

1


In house_sole us

209730



77.48%

2


No kitchen

57175



21.12%

3


In house_shared

3798



1.4%

Sysmiss


275440


File: household.NSDstat

Valid cases: 270703

Width: 1

Type: numeric

Range: 1 - 3

Value Category Cases

1


In house_sole us

113119



41.79%

2


No bathroom/show

151824



56.09%

3


In house_shared

5760



2.13%

Sysmiss


275440


File: household.NSDstat

Valid cases: 275440

Width: 1

Type: numeric

Range: 0 - 7

Value Category Cases

File: household.NSDstat

Valid cases: 275440

Width: 2

Type: numeric

Range: 0 - 96

Value Category Cases

File: household.NSDstat

Valid cases: 275440

Width: 1

Type: numeric

Range: 1 - 5

Value Category Cases

1


Well

82579



29.98%

2


Hand well

48574



17.64%

3


River, spring

116217



42.19%

4


Lake, pool

1604



0.58%

5


Other

26466



9.61%

Sysmiss


270703


File: household.NSDstat

Valid cases: 275440

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Yes

199932



72.59%

2


No

75508



27.41%

Sysmiss


270703


File: household.NSDstat

Valid cases: 275440

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Yes

212700



77.22%

2


No

62740



22.78%

Sysmiss


270703


File: household.NSDstat

Valid cases: 275440

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Yes

146607



53.23%

2


No

128833



46.77%

Sysmiss


270703


File: household.NSDstat

Valid cases: 546143

Width: 1

Type: numeric

Range: 1 - 3

Value Category Cases

1


Government

49839



9.13%

2


Private

490932



89.89%

3


Mixed

5372



0.98%

File: household.NSDstat

Valid cases: 546143

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Yes

368924



67.55%

2


No

177219



32.45%

File: household.NSDstat

Valid cases: 546143

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Yes

92898



17.01%

2


No

453245



82.99%

File: household.NSDstat

Valid cases: 2442717

Width: 3

Type: numeric

Range: 1 - 921

Value Category Cases

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 1 - 51

Value Category Cases

1


Arkhangai

98600



4.04%

2


Bayan_Olgii

92073



3.77%

3


Bayankhongor

85848



3.51%

4


Bulgan

63158



2.59%

5


Govi_Altai

64649



2.65%

6


Dornogovi

52692



2.16%

7


Dornod

78131



3.2%

8


Dundgovi

52097



2.13%

9


Zavkhan

91275



3.74%

10


Ovorkhangai

112908



4.62%

11


Omnogovi

47718



1.95%

12


Sukhbaatar

57277



2.34%

13


Selenge

102659



4.2%

14


Tov

101590



4.16%

15


Uvs

91253



3.74%

16


Khovd

87856



3.6%

17


Khovsgol

121201



4.96%

18


Khentii

72712



2.98%

19


Darkhan_Uul

86275



3.53%

20


Ulaanbaatar

795007



32.55%

21


Orkhon

74953



3.07%

22


Govisumber

12785



0.52%

23


Russia

0



0.52%

24


China

0



0.52%

25


Korea

0



0.52%

26


North Korea

0



0.52%

27


Germany

0



0.52%

28


Japan

0



0.52%

29


USA

0



0.52%

30


Turkey

0



0.52%

31


UK

0



0.52%

32


Bulgaria

0



0.52%

33


Romania

0



0.52%

34


India

0



0.52%

35


Kanad

0



0.52%

36


Lao

0



0.52%

37


Italia

0



0.52%

38


France

0



0.52%

39


Pakistan

0



0.52%

40


Yugaslavia

0



0.52%

41


Philippines

0



0.52%

42


Hungaria

0



0.52%

43


Czech

0



0.52%

44


Slovak Republic

0



0.52%

45


Austria

0



0.52%

46


Finland

0



0.52%

47


Viet nam

0



0.52%

48


Australia

0



0.52%

49


Poland

0



0.52%

50


Kazakstan

0



0.52%

51


Other

0



0.52%

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 1 - 27

Value Category Cases

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 0 - 29

Value Category Cases

0


No tosgon



0.52%

1


Tsagaan nuur



0.52%

2


Shargaljuut



0.52%

3


Saikhankhoroo



0.52%

4


Khyalganat



0.52%

5


Guulin



0.52%

6


Bayantooroi



0.52%

8


Zamiin_Uud



0.52%

9


Zulegtei



0.52%

11


Erdes



0.52%

12


Ereen



0.52%

13


Tosontsengel



0.52%

14


Tavantolgoi



0.52%

15


Zuunkharaa



0.52%

16


Tunkhel



0.52%

17


Kherkh



0.52%

18


Dulaankhaan



0.52%

19


Bugant



0.52%

20


Khotol



0.52%

21


Khailaastai



0.52%

22


Khar_Tarvagtai



0.52%

23


Khoshoot



0.52%

25


Khatgal



0.52%

27


Bor_Ondor



0.52%

28


Berkh



0.52%

29


Chandgana tal



0.52%

File: household.NSDstat

Valid cases: 2442717

Width: 1

Type: numeric

Range: 1 - 5

Value Category Cases

1


Capital

795007



32.55%

2


Aimag center

531133



21.74%

3


Village

74967



3.07%

4


Soum center

379701



15.54%

5


Countryside

661909



27.1%

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 1 - 96

Value Category Cases

File: household.NSDstat

Valid cases: 2442716

Width: 3

Type: numeric

Range: 1 - 931

Value Category Cases

File: household.NSDstat

Valid cases: 2442717

Width: 1

Type: numeric

Range: 1 - 3

Value Category Cases

1


House.own house

2341025



95.84%

2


Shared house

63111



2.58%

3


Dormitory other

38581



1.58%

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 1 - 99

Value Category Cases

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 1 - 35

Value Category Cases

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 1 - 11

Value Category Cases

1


Household head

541149



22.15%

2


Wife/husband

385174



15.77%

3


Daughter/son

1097814



44.94%

4


Parents

32285



1.32%

5


Sister/brother

86813



3.55%

6


Parents in law

9547



0.39%

7


Daugh/son in law

21420



0.88%

8


Grandparents

3325



0.14%

9


Granchild

96155



3.94%

10


Other relative

96191



3.94%

11


Non_relative

72844



2.98%

File: household.NSDstat

Valid cases: 2442717

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Male

1213533



49.68%

2


Female

1229184



50.32%

File: household.NSDstat

Valid cases: 2442717

Width: 4

Type: numeric

Range: 1893 - 2000

Value Category Cases

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 1 - 12

Value Category Cases

File: household.NSDstat

Valid cases: 2442717

Width: 3

Type: numeric

Range: 0 - 107

Value Category Cases

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 1 - 88

Value Category Cases

1


Mongolian

2434138



99.65%

23


Russia

3433



0.14%

24


China

2205



0.09%

25


Korea

369



0.02%

26


North Korea

63



0%

27


Germany

72



0%

28


Japan

160



0.01%

29


USA

312



0.01%

30


Turkey

138



0.01%

31


UK

82



0%

32


Bulgaria

3



0%

33


Romania

0



0%

34


India

30



0%

35


Kanad

33



0%

36


Lao

5



0%

37


Italia

5



0%

38


France

14



0%

39


Pakistan

16



0%

40


Yugaslavia

15



0%

41


Philippines

42



0%

42


Hungaria

8



0%

43


Czech

11



0%

44


Slovak Republic

5



0%

45


Austria

4



0%

46


Finland

24



0%

47


Viet nam

14



0%

48


Australia

5



0%

49


Poland

6



0%

50


Kazakstan

658



0.03%

51


Other

739



0.03%

88


Non_citizenship

108



0%

File: household.NSDstat

Valid cases: 2434138

Width: 2

Type: numeric

Range: 1 - 30

Value Category Cases

1


Khalkh

1993753



81.91%

2


Kazak

104296



4.28%

3


Dorvod

68268



2.8%

4


Buriad

42464



1.74%

5


Bayad

52246



2.15%

6


Dariganga

32811



1.35%

7


Uriankhai

25657



1.05%

8


Zakhchin

30389



1.25%

9


Darkhad

19399



0.8%

10


Torguud

12912



0.53%

11


Oold

14953



0.61%

12


Khoton

9125



0.37%

13


Myangad

6217



0.26%

14


Barga

2592



0.11%

15


Uzemchin

2437



0.1%

16


Kharchin

268



0.01%

17


Tsakhar

125



0.01%

18


Khotgoid

7364



0.3%

19


Eljigen

155



0.01%

20


Tsaatan

304



0.01%

21


Khamnigan

574



0.02%

22


Khashuud

184



0.01%

23


Sartuul

1564



0.06%

24


Tuva

4875



0.2%

25


Khorchin

150



0.01%

26


Uzbek

386



0.02%

27


Khalimag

5



0%

28


Russian/Mongolia

163



0.01%

29


Chinese/Mongolia

176



0.01%

30


Other eth of Mon

326



0.01%

Sysmiss


8579


File: household.NSDstat

Valid cases: 2442717

Width: 1

Type: numeric

Range: 1 - 3

Value Category Cases

1


Resident

2312012



94.65%

2


Temporary absen

61481



2.52%

3


Visitor

69224



2.83%

File: household.NSDstat

Valid cases: 130705

Width: 2

Type: numeric

Range: 0 - 51

Value Category Cases

1


Arkhangai

5833



4.46%

2


Bayan_Olgii

1823



1.39%

3


Bayankhongor

3364



2.57%

4


Bulgan

3628



2.78%

5


Govi_Altai

3296



2.52%

6


Dornogovi

2957



2.26%

7


Dornod

5271



4.03%

8


Dundgovi

2124



1.63%

9


Zavkhan

5157



3.95%

10


Ovorkhangai

4287



3.28%

11


Omnogovi

1920



1.47%

12


Sukhbaatar

2808



2.15%

13


Selenge

4329



3.31%

14


Tov

6522



4.99%

15


Uvs

3379



2.59%

16


Khovd

2975



2.28%

17


Khovsgol

5568



4.26%

18


Khentii

4164



3.19%

19


Darkhan_Uul

4110



3.14%

20


Ulaanbaatar

25421



19.45%

21


Orkhon

4118



3.15%

22


Govisumber

785



0.6%

23


Russia

3353



2.57%

24


China

1068



0.82%

25


Korea

8683



6.64%

26


North Korea

59



0.05%

27


Germany

2514



1.92%

28


Japan

1224



0.94%

29


USA

2344



1.79%

30


Turkey

235



0.18%

31


UK

467



0.36%

32


Bulgaria

117



0.09%

33


Romania

2



0%

34


India

135



0.1%

35


Kanad

48



0.04%

36


Lao

16



0.01%

37


Italia

23



0.02%

38


France

155



0.12%

39


Pakistan

9



0.01%

40


Yugaslavia

19



0.01%

41


Philippines

24



0.02%

42


Hungaria

1405



1.07%

43


Czech

1233



0.94%

44


Slovak Republic

76



0.06%

45


Austria

71



0.05%

46


Finland

8



0.01%

47


Viet nam

23



0.02%

48


Australia

62



0.05%

49


Poland

1853



1.42%

50


Kazakstan

577



0.44%

51


Other

1063



0.81%

Sysmiss


2312012


File: household.NSDstat

Valid cases: 130705

Width: 2

Type: numeric

Range: 0 - 27

Value Category Cases

1


32149



24.6%

2


11739



8.98%

3


10505



8.04%

4


4216



3.23%

5


7455



5.7%

6


5095



3.9%

7


7513



5.75%

8


3074



2.35%

9


6411



4.9%

10


2537



1.94%

11


2103



1.61%

12


3298



2.52%

13


5307



4.06%

14


6742



5.16%

15


2631



2.01%

16


1652



1.26%

17


4764



3.64%

18


3310



2.53%

19


3143



2.4%

20


1765



1.35%

21


617



0.47%

22


3470



2.65%

23


410



0.31%

24


285



0.22%

25


104



0.08%

26


137



0.1%

27


273



0.21%

Sysmiss


2312012


File: household.NSDstat

Valid cases: 2442717

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Since birth

1818997



74.47%

2


Moved in

623720



25.53%

File: household.NSDstat

Valid cases: 623720

Width: 2

Type: numeric

Range: 1 - 51

Value Category Cases

1


Arkhangai

36955



5.92%

2


Bayan_Olgii

11062



1.77%

3


Bayankhongor

21559



3.46%

4


Bulgan

23453



3.76%

5


Govi_Altai

31513



5.05%

6


Dornogovi

26126



4.19%

7


Dornod

21701



3.48%

8


Dundgovi

14738



2.36%

9


Zavkhan

43037



6.9%

10


Ovorkhangai

26312



4.22%

11


Omnogovi

10358



1.66%

12


Sukhbaatar

17633



2.83%

13


Selenge

29315



4.7%

14


Tov

44986



7.21%

15


Uvs

34597



5.55%

16


Khovd

28745



4.61%

17


Khovsgol

24688



3.96%

18


Khentii

18232



2.92%

19


Darkhan_Uul

22835



3.66%

20


Ulaanbaatar

106695



17.11%

21


Orkhon

13079



2.1%

22


Govisumber

2840



0.46%

23


Russia

5615



0.9%

24


China

1627



0.26%

25


Korea

418



0.07%

26


North Korea

61



0.01%

27


Germany

427



0.07%

28


Japan

150



0.02%

29


USA

335



0.05%

30


Turkey

108



0.02%

31


UK

75



0.01%

32


Bulgaria

72



0.01%

33


Romania

2



0%

34


India

57



0.01%

35


Kanad

18



0%

36


Lao

9



0%

37


Italia

8



0%

38


France

24



0%

39


Pakistan

14



0%

40


Yugaslavia

20



0%

41


Philippines

9



0%

42


Hungaria

119



0.02%

43


Czech

202



0.03%

44


Slovak Republic

32



0.01%

45


Austria

16



0%

46


Finland

21



0%

47


Viet nam

15



0%

48


Australia

11



0%

49


Poland

91



0.01%

50


Kazakstan

2705



0.43%

51


Other

1000



0.16%

Sysmiss


1818997


File: household.NSDstat

Valid cases: 623720

Width: 4

Type: numeric

Range: 1902 - 1999

Value Category Cases

File: household.NSDstat

Valid cases: 2442717

Width: 2

Type: numeric

Range: 1 - 51

Value Category Cases

1


Arkhangai

136141



5.57%

2


Bayan_Olgii

101558



4.16%

3


Bayankhongor

108744



4.45%

4


Bulgan

77369



3.17%

5


Govi_Altai

97065



3.97%

6


Dornogovi

55618



2.28%

7


Dornod

84402



3.46%

8


Dundgovi

65446



2.68%

9


Zavkhan

135599



5.55%

10


Ovorkhangai

137117



5.61%

11


Omnogovi

54724



2.24%

12


Sukhbaatar

72102



2.95%

13


Selenge

87617



3.59%

14


Tov

111366



4.56%

15


Uvs

127961



5.24%

16


Khovd

112393



4.6%

17


Khovsgol

145315



5.95%

18


Khentii

79740



3.26%

19


Darkhan_Uul

52506



2.15%

20


Ulaanbaatar

557489



22.82%

21


Orkhon

28342



1.16%

22


Govisumber

6194



0.25%

23


Russia

2983



0.12%

24


China

1513



0.06%

25


Korea

311



0.01%

26


North Korea

60



0%

27


Germany

183



0.01%

28


Japan

101



0%

29


USA

279



0.01%

30


Turkey

127



0.01%

31


UK

57



0%

32


Bulgaria

32



0%

33


Romania

6



0%

34


India

42



0%

35


Kanad

22



0%

36


Lao

5



0%

37


Italia

5



0%

38


France

16



0%

39


Pakistan

16



0%

40


Yugaslavia

19



0%

41


Philippines

5



0%

42


Hungaria

35



0%

43


Czech

60



0%

44


Slovak Republic

14



0%

45


Austria

7



0%

46


Finland

21



0%

47


Viet nam

19



0%

48


Australia

6



0%

49


Poland

28



0%

50


Kazakstan

1024



0.04%

51


Other

913



0.04%

File: household.NSDstat

Valid cases: 613231

Width: 2

Type: numeric

Range: 1 - 51

Value Category Cases

1


Arkhangai

10497



1.71%

2


Bayan_Olgii

3465



0.57%

3


Bayankhongor

6613



1.08%

4


Bulgan

14990



2.44%

5


Govi_Altai

8521



1.39%

6


Dornogovi

15837



2.58%

7


Dornod

16097



2.62%

8


Dundgovi

6127



1%

9


Zavkhan

27792



4.53%

10


Ovorkhangai

13112



2.14%

11


Omnogovi

10265



1.67%

12


Sukhbaatar

15712



2.56%

13


Selenge

35619



5.81%

14


Tov

42385



6.91%

15


Uvs

33649



5.49%

16


Khovd

21835



3.56%

17


Khovsgol

14380



2.34%

18


Khentii

19940



3.25%

19


Darkhan_Uul

39727



6.48%

20


Ulaanbaatar

201393



32.84%

21


Orkhon

40671



6.63%

22


Govisumber

7623



1.24%

23


Russia

2017



0.33%

24


China

739



0.12%

25


Korea

297



0.05%

26


North Korea

44



0.01%

27


Germany

273



0.04%

28


Japan

130



0.02%

29


USA

221



0.04%

30


Turkey

99



0.02%

31


UK

69



0.01%

32


Bulgaria

22



0%

33


Romania

6



0%

34


India

41



0.01%

35


Kanad

21



0%

36


Lao

5



0%

37


Italia

8



0%

38


France

16



0%

39


Pakistan

14



0%

40


Yugaslavia

10



0%

41


Philippines

12



0%

42


Hungaria

56



0.01%

43


Czech

66



0.01%

44


Slovak Republic

22



0%

45


Austria

11



0%

46


Finland

18



0%

47


Viet nam

18



0%

48


Australia

11



0%

49


Poland

77



0.01%

50


Kazakstan

2007



0.33%

51


Other

651



0.11%

Sysmiss


1829486


File: household.NSDstat

Valid cases: 2089291

Width: 1

Type: numeric

Range: 1 - 7

Value Category Cases

1


Less than primar

405895



19.43%

2


Primary

441083



21.11%

3


Grade 4_8

479539



22.95%

4


Grade 9_10

405843



19.42%

5


Technical vocati

69097



3.31%

6


Diploma

143688



6.88%

7


High

144146



6.9%

Sysmiss


353426


File: household.NSDstat

Valid cases: 405895

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Literate

310366



76.46%

2


Illiterate

95529



23.54%

Sysmiss


2036822


File: household.NSDstat

Valid cases: 1257016

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Yes

596381



47.44%

2


No

660635



52.56%

Sysmiss


1185701


File: household.NSDstat

Valid cases: 1579251

Width: 1

Type: numeric

Range: 1 - 6

Value Category Cases

1


Never married

530398



33.59%

2


Married

787550



49.87%

3


Living together

116345



7.37%

4


Separated

18607



1.18%

5


Divorced

24639



1.56%

6


Widowed

101712



6.44%

Sysmiss


863466


File: household.NSDstat

Valid cases: 1579251

Width: 1

Type: numeric

Range: 1 - 2

Value Category Cases

1


Yes

796112



50.41%

2


No

783139



49.59%

Sysmiss


863466


File: household.NSDstat

Valid cases: 796112

Width: 4

Type: numeric

Range: 110 - 9998

Value Category Cases

File: household.NSDstat

Valid cases: 796112

Width: 3

Type: numeric

Range: 11 - 998

Value Category Cases

File: household.NSDstat

Valid cases: 796112

Width: 1

Type: numeric

Range: 1 - 6

Value Category Cases

1


Employee

328090



41.21%

2


Employer

10174



1.28%

3


Self employed

250036



31.41%

4


Member of cooper

3804



0.48%

5


HH member workin

200541



25.19%

6


Other

3467



0.44%

Sysmiss


1646605


File: household.NSDstat

Valid cases: 783139

Width: 1

Type: numeric

Range: 1 - 7

Value Category Cases

1


Studying

179520



22.92%

2


On pension/retir

170369



21.75%

3


Disabled

38472



4.91%

4


Home duties

79504



10.15%

5


No work availabl

95131



12.15%

6


Looking for job

173309



22.13%

7


Other

46834



5.98%

Sysmiss


1659578