Users’ Manual for Handling Resampled Micro Data ofMongolia Household Socio Economic Survey

Mongolia HSES 2012
(Version 2.0)

2019
The Institute of Statistical Mathematics (ISM)
andStatistical Information Institute for Consulting and Analysis (SINFONICA)

1

History of revision of the manualVersion 2.0: Finalized in March 2019 based on the discussion during the Workshop in
November - December 2018.



Version 1.0 in November 2018 for the Workshop in November 2018.

Manual Mongolia HSES 2012 Version 2.0

2

CONTENTS

Mongolia HSES 2012
1. About this Manual

Page 4

2. Outline of the survey

5

3. Data and metadata provided

8

4. Data import
4.1 Import STATA data files into R

11

4.2 Generated list of variable names in each data frame

13

4.3 Identifier

49

4.4 Weight51

5. Data check5.1 Structure of each data file52

5.2 Summary of each variable74

5.3 Frequency tables of categorical variables

94

5.4 Consistency check of identifier

107

6. Household income
6.1 Results of household income

108

6.2 Wage income

111

6.3 Pension

116

6.4 Income from livestock121

6.5 Agricultural income

125

6.6 Business income

129

6.7 Other income

134

6.8 Total household income

137

7. Household expenditure
7.1 Results of household expendituree

139

7.2 Related questionnaire and data files

142

7.3 Food
7.3.1 Urban diary145

7.3.2 Rural food 7 days

145

7.3.3 Imputed unit price

145

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7.4 Non-food
7.4.1 Non-food156

7.4.2 Food out

157

7.4.3 Energy

157

7.4.4 Payment service

158

7.4.5 Loan

159

9. Micro data to be provided

161

Attachments:

142

1. The questionnaire
1.1 SES-1: Diary for the keeping in households

167

1.2 SES-2a: Household food consumption (by diary)173

1.3 SES-2b: Household food consumption (by recall)182

1.4 SES-3: Section 0 to section 13

191

2. Data dictionary: Database documentation

232

Manual Mongolia HSES 2012 Version 2.0

4Chapter 1. About this Manual
1. This manual was prepared for users to use the next 80% resampled micro data sets of Mongolia
Household Socio Economic Survey (HSES) 2012.
CSV format[1] "Household_80.csv""Individual_80.csv"[3] "Llivestock_80.csv""Livestock Expenditure_80.csv"[5] "Product_80.csv""Crop_80.csv"[7] "Agriultural Expenditure_80.csv" "Enterprise_80.csv"[9] "Other income_80.csv""Remittance_80.csv"[11] "Savings loan_80.csv""Energy_80.csv"[13] "Payment service_80.csv""Durable_80.csv"[15] "Non-Food_80.csv""Urban Diary_80.csv"[17] "Rural Food 7 day_80.csv""Foodstuffs_80.csv"[19] "Foodout_80.csv""Basicvars_80.csv"

R format
The elements of the list object of “outfiles.80”correspond to;[1] "Household.80""Individual.80"[3] "Llivestock.80""Livestock Expenditure.80"[5] "Product.80""Crop.80"[7] "Agriultural Expenditure.80" "Enterprise.80"[9] "Other income.80""Remittance.80"[11] "Savings loan.80""Energy.80"[13] "Payment service.80""Durable.80"[15] "Non-Food.80""Urban Diary.80"[17] "Rural Food 7 day.80""Foodstuffs.80"[19] "Foodout.80""Basicvars.80"

2. The original micro data sets composed of all the samples were provided by Mongolian NSO basedon the Charter for Experimental Laboratory for Research Purpose Statistical Use of Micro Data, andresampled at the rate of 80% by Sinfonica.
3. This manual was first compiled in November 2018 by;
Hiroshige Furuta
Visiting Senior Research Fellow, Sinfonica

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5Chapter 2.

Outline of Mongolia HSES 2012

The below table describes mainly on the household socio-economic survey.
Objectives of the

To evaluate and monitor the income and expenditure of households, update thesurveybasket and weights for consumer price index, and offer inputs to the national
accounts.

Topics covered by

Covered basic socio-economic information about the members of households,

the survey

education, health, employment, livestock, crop production, household businessand other income, housing and energy, durable goods, non-food expendituresand food consumption.

Frequency of theConducted HSES in a comprehensive form every three years and in an

surveyabbreviated form annually.

Survey period

Covered a 12-month period from January 2012 to December 2012

Coverage of the

Geographical coverage: National

surveyHouseholds (defined as a group of persons who usually live and eat
together) Household members (defined as members of the household who usually
live in the household, which may include people who did not sleep in thehousehold the previous night, but does not include visitors who slept in
the household the previous night but not usually live in the household) The following households and population group were excluded from thissurvey.
1) Foreign citizens (employees of foreign embassies and consular corps,
International organizations and their contractors as well as tourists)
2) Prisoners (If a household head is jailed less than 11 months, or its member
less than 6 months, they still will be included in the survey.)
3) Persons living in social welfare facilities
4) Military person on term based/temporary duty

Sample designThe 2012 HSES used the sampling frame which was developed by the
NSO based on 2005 population figures obtained from local registration
offices. This updated sampling frame was of great importance because thespacial distribution of the population had changed dramatically over thelast years and any frame based on the Census 2000 would not be relevant

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6anymore.


Three explicit strata: Ulaanbaatar, Aimag centers, and Rural (soumcenters and the countryside).



A two-stage process in urban areas;
In Ulaanbaatar, 360 khesegs were initially selected, from each of which
10 households were chosen.
In aimag centers, 12 or 24 bags were initially selected, and then 10
households from each bag.

A three-stage process in rural areas;
In rural areas, first 52 soums, then 12 bags in each soum and finally 8households in each bag were selected.

All 1,248 primary sampling units or clusters (units, bags or soums) wereselected with a probability proportional to their sizes and were randomly
allocated into twelve months of survey fieldwork.

The sample of 11,232 households was allocated as follows: 3,600 in
Ulaanbaatar, 2,640 in aimag centers and 4,992 in rural areas and soum
centers. However, the actual sample size used for this analysis is slightly
smaller: 3,572 households in Ulaanbaatar; 2,639 in aimag centers; and4,987 in rural areas and small towns. The difference is explained by 60
households, for which complete information was unavailable and werethus, excluded.

Sample size: 12,811 households in HSES 2012.

Data collectionFace-to-facemethodThe overall data quality is to be considered of good standard. On the one
hand, the large amounts of information that the HSES collects fromhouseholds imposed new demands on operational strategies and data
management compared to the previous HSES.

Data entry anddata check

All procedures were streamlined and centralized, which is likely to have
had a positive impact on the quality of the information.

On the other hand, three different rounds of consistency checks wereapplied to the data: first during the data entry process, then during thecompilation of the raw data files and finally during the preparation of thisreport. In all cases, it was possible to compare these listings against actual
questionnaires filled out by households (and at least during the first round

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of checks, some households were visited again) and the data wereamended whenever a mistake was found.


Databases for the HSES 2007/08 have been unified and data error
checking was made (by using STATA program) in cooperation withworking group.

Publication
Technical and

Conducted HSES 2007-08 with support of World Bank.

financialNo description about World Bank in HSES 2012.

assistance

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8Chapter 3. Data and metadata provided


NADA

The following data and metadata are downloaded from Mongolian NSO’s website.
URL: http://web.nso.mn/nada/index.php/catalog/79/ (accessed on 20180816)

 Household data files
File names in STATA format;[1] "Household.dta""Individual.dta"[3] "Llivestock.dta""Livestock Expenditure.dta"[5] "Product.dta""Crop.dta"[7] "Agriultural Expenditure.dta" "Enterprise.dta"[9] "Other income.dta""Remittance.dta"[11] "Savings loan.dta""Energy.dta"[13] "Payment service.dta""Durable.dta"[15] "Non-Food.dta""Urban Diary.dta"[17] "Rural Food 7 day.dta""Foodstuffs.dta"[19] "Foodout.dta""Basicvars.dta"

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9 Metadata
Codebook

HSES_Dbase_codebook_2012.pdf (1)HSES_Dbase_codebook_2012_revised.pdf (2)Database documentation including variable labels and value labels.
However, it does not include “18 Foodstuff”.
(2) was provided on the occasion of the workshop.

Survey report

None

Questionnaire

HSES_2012_Questionnaire.xlsx (1)MHSES_2012_F1diary_ENG.xlsx (2)MHSES_2012_F2food_ENG.xlsx (3)HSES_2012_F2_3C_Mon_last.xlsx (4)The questionnaire form in English was not available at the website.
It was provided by NSO upon request.
However, questionnaire forms of Urban Diary, Rural Food 7 day, Foodout andFoodstuffs are not included in the above Excel file (1).
On the occasion of the workshop, Excel files (2) and (3) were provided uponrequest. (2) is diary form for urban food. (3) is the summary of urban food, and rural
food in 7-days.
Foodout questions was newly introduced in HSES 2012, and they were at thebottom of questionnaire form (2).
Foodstuff questionnaire was also newly introduced in HSES 2012. It related togovernment food assistance program, and was not used for estimation of
consumption. Indeed, the food assistance received free was written in Diary for
urban or RecallFood for rural.
The questionnaire form in Mongolian language was available at sheet “PMT” forurban and “PMT_rural” for rural in Excel (4).

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

IHSN

Unfortunately, the latest survey is HSES 2011.

http://catalog.ihsn.org/index.php/catalog/4719/related_citations (accessed on 20180815)

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11Chapter 4. Data import
4.1 Import STATA data files into R> STATA.files<-list.files()> STATA.files[1] "Agriultural Expenditure.dta" "Basicvars.dta"[3] "Crop.dta""Durable.dta"[5] "Energy.dta""Enterprise.dta"[7] "Foodout.dta""Foodstuffs.dta"[9] "Household.dta""Individual.dta"[11] "Livestock Expenditure.dta" "Llivestock.dta"[13] "Non-Food.dta""Other income.dta"[15] "Payment service.dta""Product.dta"[17] "Remittance.dta""Rural Food 7 day.dta"[19] "Savings loan.dta""Urban Diary.dta"

Remarks:
In addition to the 17 files of HSES 2010, the next three files were added:
Savings loan.dta
Foodstucks.dta
Foodout.dta> STATA.files<-STATA.files[c(9,10,12,11,16,3,1,6,14,17,19,5,15,4,13,20,18,8,7,2)]> STATA.files[1] "Household.dta""Individual.dta"[3] "Llivestock.dta""Livestock Expenditure.dta"[5] "Product.dta""Crop.dta"[7] "Agriultural Expenditure.dta" "Enterprise.dta"[9] "Other income.dta""Remittance.dta"[11] "Savings loan.dta""Energy.dta"[13] "Payment service.dta""Durable.dta"[15] "Non-Food.dta""Urban Diary.dta"[17] "Rural Food 7 day.dta""Foodstuffs.dta"[19] "Foodout.dta""Basicvars.dta"# Imported STATA files into R using package of “readstata13”> library(readstata13)> library(foreign)> outfiles<-list()> for(j in 1:20){+ outfiles<-c(outfiles,list(read.dta13(STATA.files[j],convert.factors=F)))+}> length(outfiles)[1] 20Manual Mongolia HSES 2012 Version 2.0

12# Made list of data file names, number of records and variables> for(j in 1:20) cat(j,":",STATA.files[j],":",dim(outfiles[[j]]),"¥n")
1 : Household.dta : 12811 88
2 : Individual.dta : 47908 129
3 : Llivestock.dta : 14498 15
4 : Livestock Expenditure.dta : 9011 10
5 : Product.dta : 74050 16
6 : Crop.dta : 2353 15
7 : Agriultural Expenditure.dta : 11518 10
8 : Enterprise.dta : 2342 31
9 : Other income.dta : 333086 20
10 : Remittance.dta : 3670 17
11 : Savings loan.dta : 6305 19
12 : Energy.dta : 115299 15
13 : Payment service.dta : 166543 13
14 : Durable.dta : 563684 12
15 : Non-Food.dta : 4624771 15
16 : Urban Diary.dta : 867273 23
17 : Rural Food 7 day.dta : 708480 16
18 : Foodstuffs.dta : 12811 17
19 : Foodout.dta : 25578 12
20 : Basicvars.dta : 12811 12

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4.2 Generated list of variable names in each data frame
Summary:
1. The household identifier is “identif” in each file.
The variable “ind_id” of “Individual.dta” and “Remittance.dta” is the individual identifier within thehousehold.
The household weight is given as “hhweight” in “Basicvars.dta”.
2. The value labels of aimag and location are displayed only in the first file.
3. In some files, value labels are not properly displayed, that is, not in English.
4. The item codes of “Urban Diary.dta” and “Rural Food 7 day.dta” are consistent.
5. The variable of “newaimag” in “Basicvars.dta” is the same as “aimag” of other files.
6. As for “10 Relationship to head” in “individual.dta”, the value label of “7 BROTHER/SISTER IN
LAW” should be read as “7 SON?DAUGHTER IN LAW”

Manual Mongolia HSES 2012 Version 2.0

14> for(k in 1:20){+ df<-outfiles[[k]]+ cb<-vector(length=ncol(df),mode="list")+ # cb: data frame of codebook+ for(j in 1:length(cb)){+ cb[[j]]$varname<-names(df)[j]+ cb[[j]]$varlabel<-attributes(df)$var.labels[j]+ cb[[j]]$vallabel<-(attributes(df)$label.table[attributes(df)$val.labels])[[j]]+}+ # print codebook+ cat("¥n¥n",k,"### ",STATA.files[k]," ###¥n")+ for(j in 1:length(cb)){+ cat(format(j,width=2),format(cb[[j]]$varname,width=10),+
format(cb[[j]]$varlabel,width=30),"¥n")+if( ( (k>1 & cb[[j]]$varname!= "location" & cb[[j]]$varname!= "aimag"
length(cb[[j]])==3 ){+ t<-cb[[j]]$vallabel+ for(h in 1:length(t)){+ cat(rep(" ",10),format(t[h],width=3),format(names(t)[h],width=30),"¥n")+ } # end of for h+ #}+ } # end of if+ } # end of for j+ } # end of for k

1 ### Household.dta ###1 identif
group(identif)
2 yearYear
3 quarter
Quarter
4 cluster
Cluster
5 aimag
Aimag
11 Ulaanbaatar (11)21 Dornod (21)22 Suhbaatar (22)23 Hentii (23)41 Tuv (41)42 Govisumber (42)43 Selenge (43)44 Dornogovi (44)45 Darhan-Uul (45)46 Umnugovi (46)48 Dundgovi (48)61 Orhon (61)62 Uvurhangai (62)63 Bulgan (63)64 Bayanhongor (64)
65 Arhangai (65)67 Huvsgul (67)
81 Zavhan (81)82 Govi-Altai (82)
83 Bayan-Ulgii (83)84 Hovd (84)
85 Uvs (85)Manual Mongolia HSES 2012 Version 2.0) || k==1 ) &15

6 soum
7 location

Soum
Location
1 Capital
2 Aimag center
3 Soum center
4 Rural

8 interviewer Interviewer
9 supervisor Supervisor
10 operator Operator
11 q0008
8. Household Members
12 hh_nohousehold_id
13 q0009
9. aDOEEI O￣￣ADEEI NIIAIEO
14 q0010I÷nii oaaa
15 v1_dd
Day
16 v1_mmMonth
17 v1_yyYear
18 v1_res
v1_Result
1 COMPLETE
2 PARTIALLY COMPLETED
3 NO RESPONDENT IN THE HOUSEHOLD
4 HOUSEHOLD TEMPERARILY NOT PRESENT
5 POSTPONED
6 REFUSED
7 HOUSEHOLD NOT FOUND
19 v2_dd
Visit 2 DD
20 v2_mm
Visit 2 MM
21 v2_yy
Visit 2 YY
22 v2_res
Visit 2 Result
1 COMPLETE
2 PARTIALLY COMPLETED
3 NO RESPONDENT IN THE HOUSEHOLD
4 HOUSEHOLD TEMPERARILY NOT PRESENT
5 POSTPONED
6 REFUSED
7 HOUSEHOLD NOT FOUND
23 v3_dd
Visit 3 DD
24 v3_mm
Visit 3 MM
25 v3_yy
Visit 3 YY
26 v3_res
Visit 3 Result
1 COMPLETE
2 PARTIALLY COMPLETED
3 NO RESPONDENT IN THE HOUSEHOLD
4 HOUSEHOLD TEMPERARILY NOT PRESENT
5 POSTPONED
6 REFUSED
7 HOUSEHOLD NOT FOUND
27 v4_dd
Visit 4 DD
28 v4_mm
Visit 4 MM
29 v4_yy
Visit 4 YY
30 v4_res
Visit 4 Result
1 COMPLETE
2 PARTIALLY COMPLETED
3 NO RESPONDENT IN THE HOUSEHOLD
4 HOUSEHOLD TEMPERARILY NOT PRESENTManual Mongolia HSES 2012 Version 2.0

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31 q0701

32 q0707

33 q0715

34 q0716
35 q0717

36 q0718
37 q0801

38 q0802
39 q0907

40 q1001

41 q1002
42 q1003

43 q1004
44 visitor
45 ndays
46 q1101
47 q1102

48 q1103

49 q1104
50 q1105

5 POSTPONED
6 REFUSED
7 HOUSEHOLD NOT FOUND
Q0701 Raised or Owned Herding,poultry or any animal?
1 YES
2 NO
Q0707 Has produced animal products past 12m?
1 YES
2 NO
Q0715 Agricultural land in past 12 m?
1 YES
2 NO
Q0716 What is total amount owned the past 12M
Q0717 Has vegetables, fruits in pas 12M
1 YES
2 NO
Q0718 What is total amount agricultural land HH members past
Q0801 Are there household enterprises?
1 YES
2 NO
Q0802 How many enterprises?
Q0907 Has any member received money or goods
1 YES
2 NO
Q1001
1 YES
2 NO
Q1002
Q1003
1 YES
2 NO
Q1004
Number of visitors Cover Form 2
Number of days Cover Form 2(11.01) Number of dwellings(11.02) Is main dwelling?
1 YES
2 NO
(11.03) Type of Dwellings
1 GER
2 APARTMENT
3 BUILDING
4 DETACHED HOUSE
5 STUDENT'S DORMITORY
6 WORKER'S DORMITORY
7 OTHER DORMITORY ACCOMODATION
8 NON-LIVING QUARTERS
9 OTHER(11.04) Number of rooms in the dwelling(11.05) Main material of the walls
1 BRICKS
2 CEMENT
3 WOOD
4 STONE

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51 q1106

52 q1107

53 q110854 q1109
55 q1110
56 q1111
57 q111258 q1113

59 q1114

60 q1115
61 q1116
62 q1117

63 q1118

64 q111965 q1120
66 q1121
67 q1122

68 q1123

5 OTHER(11.06) Main material of the roof
1 METAL
2 ASPHALT ROOF SHINGLES
3 TILE
4 OTHER(11.07) Main material of the floor
1 WOOD
2 CEMENT
3 EARTH
4 OTHER(11.08) Living area
(11.09) Total useful area
(11.10) What is the total area occupies(11.11) Number of walls in the ger(11.12) Covering of the ceiling
1 SINGLE
2 DOUBLE(11.13) Covering of the frame
1 SINGLE
2 DOUBLE(11.14) Main material of the floor
1 WOOD
2 EARTH
3 OTHER
(11.15) How old is this dwelling99 ***Undefined Label(11.16) How long have you been living(11.17) Type of ownership
1 STATE
2 ORGANIZATION'S
3 PRIVATE(11.18) How was acquired
1 RENTING
2 INHERITED
3 GIFT
4 BUILT BY OURSELVES
5 PURCHASED
6 PRIVATIZED
7 OTHER
(11.19) Did you borrow any money to acquire
1 YES
2 NO
(11.20) If you wanted to rent, how much
99 ***Undefined Label(11.21) How much do you pay for rent
(11.22) What is the main source of heating
1 CENTRALIZED2 TRADITIONAL FIRE WOOD/COAL/ DUNG STOVE
3 PRIVATE ELECTRICAL HEATER
4 PRIVATE LOW PRESSURE BOILER
5 OTHERS(11.23) Source of electricity
1 CENTRAL SYSTEM

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69 q1124

70 q1125

71 q1126
72 q1127

73 q112874 q1129

75 q1130_1
76 q1130_2
77 q1130_3
78 q1130_4
79 q1131

80 q1132a
81 q1132b82 q1133

83 q1134
84 q1135_1

85 q1135_2

86 q1135_3

2 LOCAL SYSTEM/DIESEL STATION
3 SOLAR SUSTEM
4 WIND SYSTEM
5 SMALL GEN-SET
6 CANDEL
7 OTHER
(11.24) Electricity resource adequate for operating electricd
1 YES
2 NO
(11.25) Water supply
1 CENTRALIZED: HOT & COLD WATER PIPE
2 CENTRALIZED: COLD WATER PIPE ONLY
3 PROTECTED WELL
4 UNPROTECTED WELL
5 TRANSPORTATION DISTRIBUTION
6 SPRING, RIVER
7 SNOW, ICE
8 OTHER
(11.26)
Household waste disposal
1
2
3 NO SPECIAL PLACE
4 OTHERS
What type of toilet do you have
1 SEPARATE
2 PUBLIC
3 OUTSIDE THE DWELLING
4 NO TOILET
Has a telephone
1 YES, LAND LINE PHONE
2 YES, MOBILE PHONE
3 YES, BOTH LAND AND MOBILE PHONE
4 NO
1130. 3-Distance to the nearest medical care
1130. 4-Distance to the nearest pharmacy
1130. 5-Distance to the nearest well1131. Anybody from your household own or exploit land ?
1 YES
2 NO
1132. How many hectares does your household OWN?
1132. How many hectares does your household OPERATE?
1133. Use internet normally?
1 YES
2 NO
1134. How many household member
1135_1. Where used internet, at home
1 YES
2 NO
1135_2. Where used internet, at work
1 YES
2 NO
1135_3. Where used internet, internet cafe

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87 q1135_4

88 q1135_5

1 YES
2 NO
1135_4. Where used interne, free public accesst
1 YES
2 NO
1135_5. Where used internet, other
1 YES
2 NO

2 ### Individual.dta ###1 identif
group(identif)
2 ind_id
Ind_id3 cluster
Cluster
4 aimag
Aimag
5 soumSoum
6 location Location
7 quarter
Quarter
8 interviewer Interviewer
9 supervisor Supervisor
10 q0102
1.02 Relationship to head
1 HEAD
2 WIFE / HUSBAND
3 SON / DAUGHTER
4 FATHER / MOTHER
5 BROTHER / SISTER
6 FATHER / MOTHER IN LAW
7 BROTHER / SISTER IN LAW
8 GRAND PARENT
9 GRANDCHILD
10 OTHER RELATIVE
11 OTHER
11 q0103
1.03 Sex
1 MALE
2 FEMALE
12 q01041.04 Year of birth
13 q0105y
1.05 Age Yrs
14 q0105m
1.05 Age Mths
15 q0106
1.06 Marital Status
1 MARRIED
2 LIVING TOGETHER
3 SEPARATED
4 DIVORCED
5 WIDOWED
6 NEVER MARRIED
16 q0107
1.07 Spouse ID CODE
98 ***Undefined Label
17 q0108
1.08 Father ID CODE
98 ***Undefined Label
99 ***Undefined Label
18 q01091.09 Mother ID CODE
98 ***Undefined Label
99 ***Undefined Label
19 q0110a1.10 Days away past month

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20 q0110
21 q0111

22 q0201

23 q0202

24 q0203
25 q0204

26 q0205

27 q0206_1
28 q0206_2
29 q0206_3
30 q0206_4
31 q0206_5
32 q0207

33 q0208

34 q0209
35 q02101.10 Months away
1.11 Is HH member?
1 YES
2 NO
2.01 Is 6 years or more?
1 YES
2 NO
2.02 Is answering personally?
1 YES
2 NO
2.03 Respondent ID CODE
2.04 Highest certificate obtained
1 NONE
2 PRIMARY
3 SECONDARY
4 COMPLETE SECONDARY
5 VOCATIONAL
6 DEGREE OR HIGHER EDUCATION DIPLOMA
7 BACHELOR
8 MASTER
9 PHD, DOCTOR DEGREE
10 OTHER
2.05 Can read a letter?
1 YES, EASILY
2 YES, WITH DIFFICULTY
3 NO
2.06_1 Ooadoa
2.06_2 Ooadoa
2.06_3 Ooadoa
2.06_4 Ooadoa
2.06_5 Ooadoa
2.07 Check age/ between 8-35 years
1 YES
2 NO
2.08 Reason never attended school
1 CHILD NOT INTRESTED
2 PARENTS NOT INTERESTED
3 DIFFICULT TRAINING
4 POOR TRAINING QUALITY
5 POOR SCHOOL CONDITIONS
6 LACK OF BUDGET
7 REQUIRED TO WORK
8 SICK/DISABLED
9 HAD TO LOOK AFTER OTHERS
10 SCHOOL TOO FAR
11 MIGRATION
12 SHORTAGE OF DORMITORY
13 OTHERS
2.09 Respondent ID CODE
2.10 Highest certificate obtained
1 NONE
2 PRIMARY
3 SECONDARY
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36 q0211

37 q0212

38 q0213
39 q0214

40 q0215

41 q0216t

42 q0216g
43 q0217

44 q0218

45 q0219

5 VOCATIONAL
6 DEGREE OR HIGHER EDUCATION DIPLOMA
7 BACHELOR
8 MASTER
9 PHD, DOCTOR DEGREE
10 OTHER
2.11 Can read a letter?
1 YES, EASILY
2 YES, WITH DIFFICULTY
3 NO
4
2.12 Are you attending School?
1 YES
2 NO, DROPPEDOUT
3 NO, NEVER ATTENDED
4 NO, COMPLETED
2.13
2.14 Check age/ between 8-35 years
1 YES
2 NO
2.15 Reason never attended school
1 CHILD NOT INTRESTED
2 PARENTS NOT INTERESTED
3 DIFFICULT TRAINING
4 POOR TRAINING QUALITY
5 POOR SCHOOL CONDITIONS
6 LACK OF BUDGET
7 REQUIRED TO WORK
8 SICK/DISABLED
9 HAD TO LOOK AFTER OTHERS
10 SCHOOL TOO FAR
11 MIGRATION
12 SHORTAGE OF DORMITORY
13 OTHERS
2.16 Current education TYPE
1 GENERAL
2 VOCATIONAL
3 COLLEGE, UNIVERSITY
4 OTHER (ECLE-SIASTICAL, NON FORMAL)
2.16 Current education GRADE
2.17 Type of School
1 PUBLIC
2 PRIVATE
3 OTHER
2.18 School Location
1 CAPITAL CITY
2 AIMAG CENTER
3 SOUM CENTER
4 ABROAD
2.19 Place where person lives during school
1 HOME
2 GER APPART FROM HH
3 DORMITORY
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46 q0220
47 q0221
48 q0222

49 q0223

50 q0224

5 OTHER
2.20
2.21
2.22 Pay tuition?
1 YES
2 NO
2.23
1 OEEI
2 ￣A￣E
2.24
1 NODAAEOUI OaDEEI NAI
2 AAIA, AAIE
3 OAA
4 YOYA YO, OaDaE NAAAI
5 AONAA O￣I
6 AAAAAAUI aieii IEII OENUI AAEAOOEEAAA, AAAAAAUIEDAYI
51 q0225
52 q0226_1
53 q0226_2
54 q0226_3
55 q0226_4
56 q0226_5
57 q0226_6
58 q0226_7
59 q0301

60 q0302
61 q0303

62 q0304

63 q0305

64 q0306

7 AONAA
2.25
2.26_1 Expenditures during past 12 months in room rent
2.26_2 Expenditures during past 12 months in tuition paid by
2.26_3 Expenditures during past 12 months in books and suppl
2.26_4 Expenditures during past 12 months in uniforms
2.26_5 Expenditures during past 12 months in transport
2.26_6 Expenditures during past 12 months in others
2.26_7 Expenditures during past 12 months in TOTAL
3.01 Answering personally?
1 YES
2 NO
3.02 Respondent ID CODE
3.03 Any health problem during past month?
1 YES
2 NO
3.04 Health problem (1)1 RESPIRATORY SYSTEM
2 DIGESTIVE SYSTEM
3 URINARY AND SEXUAL ORGAN
4 BLOOD CIRCULATION SYSTEM
5 DAMAGE OR INTOXICATION BY EXTERNAL IMPA
6 OTHER
3.05 Did you seek treatment in past 1 M?
1 YES
2 NO
3.06 Why didn't seek treatment?
1 NOT SERIOUS ENOUGH
2 HEALTH FACILITY TOO FAR
3 NO TRANSPORTATION
4 HEALTH CARE TOO EXPENSIVE
5 TRANSPORT TOO EXPENSIVE
6 HEALTH WORKERS NOT FRIENDLY
7 HEALTH WORKERS NOT PRESENT
8 HEALTH CARE NOT GOOD QUALITY
9 NO MONEY
10 TREATED MYSELF

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65 q0307

66 q0308_1

67 q0308_2

68 q0309
69 q0310

70 q0311
71 q0312

72 q0313

73 q0314a
74 q0314b
75 q0315
76 q0316
77 q0317

78 q0318

79 q0319

11 DIDN'T KNOW FROM WHERE TO GET TREATMENT
12 TRADITIONAL HEALER
3.07 Where was treatment provided?
1 OEEI
2 ￣A￣E
3.08 Who provided medical service for your treatment? - First
1 SPECIALISED DOCTOR
2 FAMILY DOCTOR
3 MEDSISTER
4 CHIROPRACTOR
5 TRADITIONAL HEALER
6 OTHER
3.08 Who provided medical service for your treatment? - Second
1 SPECIALISED DOCTOR
2 FAMILY DOCTOR
3 MEDSISTER
4 CHIROPRACTOR
5 TRADITIONAL HEALER
6 OTHER
3.09 Amount paid in facility or healt practitioner
3.10 Have bought medicines in the past M ?
1 YES
2 NO
3.11 Amount spent in medicines
3.12 Have stayed at hospital in past 12 M?
1 YES
2 NO
3.13 What was the Hospital ?
1 CENTRAL HOSPITAL/CLINIC
2 AIMAG/DISTRICT CLINIC
3 SOUM CENTER FAMILY CLINIC
4 PRIVATE
5 ABROAD
6 OTHER
3.14_1 How much did you pay for all costs
3.14_2 How much did you pay for all costs
3.15 Amount spent in transportation
3.16
3.17
1 OEEI
2 ￣A￣E
3.18
1 EEEIEEEEI AIEII OaDaEANaI IYDAYAEEEI YIIYEYA
2 AEIAA/ A￣￣DAEEI IYAANYI YIIYEYA
3 NOI, NOI AOIAUI AIEII aDOEEI YIIYEYA
4 OOAEEI
5 AAAAAAAA
6 AONAA
3.19
1 IYDAYAEEEI EO YI×
2 aDOEEI YI×
3 NOAEEAA×
4 AADEA×
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80 q0320
81 q0321
82 q0322
83 q0323

84 q0324

85 q0325

86 q0401

87 q0402

88 q0403

89 q0404

90 q0405

91 q0406

92 q0407

93 q0501
94 q0502
95 q0503
96 q0504
97 q0505
98 q0506
99 q0507

6 AONAA
3.20 Oiiia
3.21 Ooadoa
3.22 Ooadoa
3.23
1 OEEI
2 ￣A￣E
3.24
1 OEEI
2 ￣A￣E
3.25
1 OEEI
2 ￣A￣E
4.01 Respondent 10 yrs or more?
1 YES
2 NO
4.02 Answering by himself?
1 YES
2 NO
4.03 ID CODE of respondent
1 OEEI
2 ￣A￣E
4.04 Did you any job for the past 7 days?
1 YES
2 NO
4.05 What kind of work was the main job you did?
1 WAGE JOB
2 UNPAID WORK
3 SELF EMPLOYED HERDING
4 SELF EMPLOYED AGRICULTURE
5 OTHER
4.06 Any permanent job despite you did no job in last 7 day
1 YES
2 NO
4.07 Main reasong for not doing job in last 7 days
1 YI
2 ADaIAaA
3 NOOEAAO
4 OADEA
5 AEAODAAI/ OADOIAA
6 AYEAYA×
7 YIYAOYEI ￣D AAIAOOEAO OIIEIEA AIIO
8 YDYAOYEI ￣DEEI NOAAEEA AIIO
9 OOAIEE
10 AAAOOD OAAEO
11 AONAA
5.01
5.02
5.03
5.04
5.05
5.06
5.07

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100 q0508
101 q0509
102 q0510
103 q0511
104 q0512
105 q0513
106 q0514
107 q0601

5.08
5.09
5.10
5.11
5.12
5.13
5.14
6.01
1 OEEI
2 ￣A￣E108 q0602

6.02
1 OEEI
2 ￣A￣E

109 q0603
110 q0604

6.03
6.04
1 OEEI
2 ￣A￣E

111 q0605

6.05
1 OAEEIOAE AAEE
2 OAEEI OaENA￣E AAEE
3 IAE AA AOOE
4 AACAD OADEAEAI
5 AONAA

112 q0606

6.06
1 OEEI
2 ￣A￣E

113 q0607

6.07
1 aA×OYE
2 AEDYINYI
3 AONAUA ANADNAI
4 AIAD× AAENAI
5 O￣D CIANIEO
6 OEEDEUI ×AIADOAE AAEEOAE
7 AAEE IEAIIA￣E
8 AONAA

114 q0608

6.08
1 OEEI
2 ￣A￣E

115 q0609

6.09
1 OaAaEIaD, OAEAIA, ￣EE×EEAYYIEE OYEOYNO OAIANAI
2 IAEC, IaOaA, OAIAAOAI NAAAIAAANAA OONEAIA O￣NNYI
3 OYAEYE, IYAYYEEEEI CADUI AAAOO OAENAI
4 NIIEIA aaDaa CADEAE aANaI
5 AAEE IEAIA× IADO aDAaAaE aA× OAIANAI
6 AONAA

116 q0610

6.10
1 ITOOAI/NODAA×
2 aIAaD IANOAE
3 AYDEEI AAEEOAE , O￣￣OYA ANADAAA
4 AAEE O￣EYYA AAEAAA
5 OEEDEUI ×AIADOAE AAEE YDOYEAYA
6 aA×OYE O￣I ANADAAA

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7 OaAAEEEI AYDOOYYEOYE
8 AONAA117 q0611

6.11
1 OEEI
2 ￣A￣E

118 q0612
119 q0613
120 q0614
121 q0615

6.12
6.13
6.14
6.15
1 IaOaDEaE
2 OIDOII
3 OOAUOAAO EIIIAIE
4 OsCAAADEAAAIAE OADEOOEAAAOAE EIIIAIE
5 OaDEEI aI×EO ￣EEAAYDEEI AACAD
6 IDII IOOAEEI aI×EO ￣EEAAYDEEI AACAD
7 OaNaAO AAEAOOEEAAA
8 OaDEEI AON AAEAOOEEAAA
9 AONAA

122 q0616

6.16
1 OEEI
2 ￣A￣E123 q0617_1
124 q0617_2
125 q0617_3
126 q0618

6.17_1
6.17_2
6.17_3
6.18
1 OEEI
2 ￣A￣E

127 q0619_1
128 q0619_2
129 q0619_3

6.19_1
6.19_2
6.19_33 ### Llivestock.dta ###1 identif
group(identif)
2 ani_id
animal
1 Cattle
2 Horses
3 Camels
4 Sheep
5 Goats
6 Others
3 cluster
Cluster
4 aimag
2. Aimag5 soum
3.Soum
6 location 4. Location
7 q0702_1
7.02 TOTAL
8 q0702_2
7.02 Number of female
9 q0702_3
7.02 Number of young
10 q0703
7.03 Use for own food
11 q0704
7.03 Number of sold
12 q0705
7.03 Amount received
13 quarter
Quarter
14 interviewer 5. Interviewer

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27

15 supervisor 6. Supervisor

4 ### Livestock Expenditure.dta ###1 identif
group(identif)
2 exp_id
ani_exp
1 Animal Feed
2 Drugs and veterinary costs
3 Gassoline/ Oil
4 Taxes and Insurance
5 Wage, pay
6 Fence, machine
7 Other
3 cluster
Cluster
4 aimag
2. Aimag5 soum
3. Soum
6 location 4. Location
7 q0706
7.06 Expenditures on this [herding activity] in the last 1
8 quarter
Quarter
9 interviewer 5. Interviewer
10 supervisor 6. Supervisor

5 ### Product.dta ###1 identif
group(identif)
2 byprod_id byprod
1 Goat cashmere, kg
2 Wool, hair, cashmere, kg
3 Skins and hides, pieces
4 Milk, airag, liters
5 Eggs, (number)
6 Other by-products
3 cluster
Cluster
4 aimag
2. Aimag5 soum
3. Soum
6 location 4. LOCATION
7 q0708
7.08
8 q0709
7.09 Total Production
9 q0710
7.10 Quantity consumed by household
10 q0711
7.11 Quantity sold
11 q0712
7.12 Total amount received from sales
12 q0713
7.13 Quantity produced and sold
13 q0714
7.14 Total amount received from produced and sold
14 quarter
Quarter
15 interviewer 5. Interviewer
16 supervisor 6. Supervisor

6 ### Crop.dta ###1 identif
group(identif)
2 crop_id
crop
1 Potatoes
2 Carrots
3 Turnip

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4 Cabbage
5 Beetroot
6 Onion
7 Garlic
8 Tomatoes
9 Cucumber
10 Fruits
11 Wheat
12 Haylage
13 Other
3 cluster
4 aimag
5 soum
6 location
7 q0719

Cluster
2. Aimag
3. Soum
4. Location
7.19 Did harvest during past 12 M?
1 OEEI
2 ￣A￣E
8 q0720
7.20 Total harvest in past 12 M in KG
9 q0721
7.21 Quantity consumed by your HH
10 q0722
7.22 Quantity used for animal feed
11 q0723q
7.23 Quantity sold (KG)
12 q0723t
7.23 Total amount sold (Tugrugs)
13 quarter
Quarter
14 interviewer 5. Interviewer
15 supervisor 6. Supervisor

7 ### Agriultural Expenditure.dta ###1 identif
group(identif)
2 exp_idexp
1 Seeds
2 Fertilizers
3 Extermination of vermin
4 Wages & salaries
5 Equipment & Tools
6 Spare parts
7 Repairs and services
8 Raw materials
9 Gasoline, fuel10 Taxes, insurances and fees
11 Transport
12 Rent
13 Others
3 cluster
Cluster
4 aimag
2. Aimag5 soum
3. Soum
6 location 4. Location
7 q0724
7.24 Total expenditures on item during past 12 mths
8 quarter
Quarter
9 interviewer 5. Interviewer
10 supervisor 6. Supervisor

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29

1 identif
group(identif)
2 enEnterprise Number (1-2-3)
3 aimag
2. Aimag4 soum
3.Soum5 location 4. Location
6 q0803
8.03 ISIC
7 q0804
8.04 What % of this enterprise is owned by members
8 q0805
8.05 How many members work in this enterprise
9 q0806
8.06 How many not members work in this enterprise past mont
10 q0807_01 8.07_01 Wage of labor
11 q0807_02 8.07_02 Expenditures in: Goods for resale
12 q0807_03 8.07_03 Expenditures in: Raw materials
13 q0807_04 8.07_04 Expenditures in: Gasoline, fuel14 q0807_05 8.07_05 Expenditures in: water, steam
15 q0807_06 8.07_06 Expenditures in: Equipment
16 q0807_07 8.07_07 Expenditures in: Rental of facilities
17 q0807_08 8.07_08 Expenditures in: Spare parts
18 q0807_09 8.07_09 Expenditures in: Repair and maintenance
19 q0807_10 8.07_10 Expenditures in: Tax, fees, patent, license, insura
20 q0807_11 8.07_11 Expenditures in: Other expenses(labor, water, steam
21 q0807_99 8.07_99 TOTAL EXPENSES
22 q0808
8.08 Months in operation?
23 q0809_1a 8.09_1a. Amount received in a average month (per mth)
24 q0809_1b 8.09_1b Number of average months
25 q0809_2a 8.09_2 a. Amount received in a bad month (per mth)26 q0809_2b 8.09_2 b. Number of bad months
27 q0809_3a 8.09_3 a. Amount received in a good month (per mth)28 q0809_3b 8.09_3 b. Number of good months
29 quarter
Quarter
30 interviewer 5. Interviewer
31 supervisor 6. Supervisor

9 ### Other income.dta ###1 identif
group(identif)
2 income_id income
1 State pension
2 Special Pension
3 Unemployment benefit
4 Maternity benefits
5 Disability pension
6 Survivor pension
7 Illness payments
8 Funeral payments
9 Human development fund allowances (received in cash)
10 Human development fund allowances (transferred to account)
11 Human development fund allowances (student, superiority, other)
12 Mother benefit
13 Student benefit
14 Other social benefit
15 Rent of own assets (land, buildings, vehicles, equipment)
16 Sale of assets
17 Inheritances and wedding presents
18 Loan repayments

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19 Withdrawals from bank savings
20 Income from other sources
21 Savings?
22 Dividends?
23 Loan?
24 Treasury Bond?
25 Gambling, lottery and contest
26 Other income (from intellectual property & other)
3 cluster
4 aimag
5 soum
6 location
7 q0901

Cluster
2. Aimag
3. Soum
4. Location
9.01 Has anybody received ...
1 OEEI
2 ￣A￣E
8 q0902_ic ID CODE 1
9 q0902_t
9.02 Amount during the past 12 mths (1)10 q0903_ic ID CODE 2
11 q0903_t
9.03 Amount during the past 12 mths (2)12 q0904_ic ID CODE 3
13 q0904_t
9.04 Amount during the past 12 mths (3)14 q0905_ic ID CODE 4
15 q0905_t
9.05 Amount during the past 12 mths (4)16 q0906_ic ID CODE 5
17 q0906_t
9.05 Amount during the past 12 mths (5)18 quarter
Quarter
19 interviewer 5. Interviewer
20 supervisor 6. Supervisor

10 ### Remittance.dta ###1 identif
group(identif)
2 ln
Line Number
3 cluster
Cluster
4 aimag
2. Aimag5 soum
3. Soum
6 location 4. Location
7 ind_id
ID CODE
8 q0909
9.09 Who gave the gift
1 GOVERNMENT
2 COMPANIES AND ORGANIZATIONS
3 NGOs4 PARENTS, CHILDREN, RELATIVES
5 OTHER INDIVIDUALS (FRIENDS, NEIGHBORS,
6 FOREIGN & INTERNATIONAL ORGANIZATIONS,
7 OTHERS
9 q0910
9.10 Purpose of the receipt
1 HOUSEHOLD USE
2 EDUCATION8 TUITION FEE
3 MEDICAL TREATMENT
4 PURCHASE OF DWELLING
5 HOLIDAY
6 FUNERAL
7 HOUDEHOLD ENTERPRISE

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31

8 OTHER
9.11 From where the gifts
1 Capital city
2 Aimag center
3 Soum center4 Countryside
5 immigration
11 q0912
9.12 from wich country the gift (code)
12 q0913
9.13 How much was received during the past 12 M (TUGR)
13 q0914
9.14 Do receive it regularly?
1 YES, weekly
2 YES, monthly
3 YES, quarterly
4 YES, annualy
5 NO
14 q0915
9.15 How do you receive it?
15 quarter
Quarter
16 interviewer 5. Interviewer
17 supervisor 6.Supervisor

10 q0911

11 ### Savings loan.dta ###1 identif
group(identif)
2 cluster
Cluster
3 aimag
2. Aimag4 soum
3. Soum
5 location 4. Location
6 loan_id
Loan Number
7 q1005
10.05 Kind of loans?
1 Salary loan
2 Retirement loan
3 Mortgage loan
4 Consumer loan
5 Stockman loan
6 Business loan
7 Financing solutions
8 Vehicle-car loan
9 Other
8 q1006
10.06 Did you get this loan in the past 12 months?
1 Yes
2 No
9 q1007
10.07 Total loan of past 12 months
10 q1008
10.08 Is it possible for your household to repay the loan in time?
1 Yes
2 No
3 Don't know
11 q1009
10.09 Where do you or does any member of this household get this loans?
1 Bank2 Non bank financial institution
3 Savings and credit cooperatives
4 Employer or organization
5 Individual
6 Pawn shop
7 Others

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32

12 q1010a

10.10 What was the loan purpose/function?
1 HH expenses
2 Buy the car
3 Business
4 Buy the land
5 Buy the durable goods
6 Building a house
7 Send a HH member abroad
8 Others
13 q1010b
10.10 What was the loan purpose/function?
1 HH expenses
2 Buy the car
3 Business
4 Buy the land
5 Buy the durable goods
6 Building a house
7 Send a HH member abroad
8 Others
14 q1010c
10.10 What was the loan purpose/function?
1 HH expenses
2 Buy the car
3 Business
4 Buy the land
5 Buy the durable goods
6 Building a house
7 Send a HH member abroad
8 Others
15 q1011
10.11 How much money do you repaid for this loan in the past 1 month?
16 q1012
10.12 How much money do you repaid for this loan in the past 12 month?
17 quarter
Quarter
18 interviewer 5. Interviewer
19 supervisor 6. Supervisor

12 ### Energy.dta ###1 identif
group(identif)
2 cluster
Cluster
3 aimag
2. Aimag4 soum
3. Soum
5 location 4. location
6 energy_id Source Number
1 Electricity
2 Firewood, m3
3 Firewood, bag
4 Coal, ton
5 Coal, bag
6 Dung, ton
7 Dung, bag
8 Gas fuel, l
9 Other
7 q1136
11.36 Have used the source?
1 OEEI
2 ￣A￣E
8 q1137
11.37 How do you mainly obtain [FUEL]?

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33

1 aaDNAaa AYEOAYAYA
2 OOAAEAAA AAAAA
3 AYEOAYAYA, OOAAEAAA AAAAA
4 AONAA
9 q1138
1138. How much have you consumed for the past 12 motnths?
10 q1139
1139. Amount spend on purchases of ... in past month
11 q1140
1140. Amount spend on purchases of ... in past 12 months
12 q11411141. Value of ... received free in past 12 months
13 quarter
quarter
14 interviewer 5. Interviewer
15 supervisor 6. supervisor

13 ### Payment service.dta ###1 identif
group(identif)
2 cluster
Cluster
3 aimag
2. Aimag4 soum
3. Soum
5 location 4. Location
6 itemService Number
1 Heating fees
2 Water use fees
3 Hot water fees
4 Dirty water
5 Garbage disposal
6 Housing space fees
7 Other services (lift…)
8 Other fees (repair of plumbing)
9 Drinking water /transported/
10 House rent: Ger
11 House rent: Apartment, house
12 Charges of repair of dwelling
13 Other
7 q11421142. Have bought or received free.. during past 12 m?
1 YES
2 NO
8 q1143
1143. Amount spend on purchases of .. during past month
9 q11441144. Amount spend on purchases of .. during past 12 months
10 q1145
1145. Value of .. received free during past 12 months
11 quarter
Quarter
12 interviewer 5. Interviewer
13 supervisor 6. Supervisor

14 ### Durable.dta ###1 identif
group(identif)
2 cluster
Cluster
3 aimag
2. Aimag4 soum
3. Soum
5 location 4. Location
6 durable_id GOOD NUMBER
1 Refrigerator
2 Vacuum Cleaner
3 Washing machine

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4 Sewing machine
5 Electric or Gas Stove
6 Electric Heater
7 Electric Gen-set
8 Electric Iron
9 Oven10 Rice cooker
11 Water purifier
12 Iron Stove/Brick stove
13 Other home appliances & equipment
14 Traditional Style Bed, Wooden Bed
15
16 Sofa
17 Iron Bed
18 Room divider
19 Bedroom furniture sets
20 Wardrobe Closet
21 Wooden Table
22 Wooden Trunk
23 Carpet
24 Other furniture
25 Radio
26 Black & White TV
27 Color TV
28 Tape Player, CD Player
29 Video Cassette Player
30 Video Camera
31 Camera
32 Computer
33 Other electronic good
34 Bicycle
35 Motorcycle
36 Truck, Large truck
37 Car38 Bus39 Tractor, harvester
40 Other household transportation
41 Ger
42 House, Dwelling
43 Garage
44 Summer House
7 q1201
12.01 Number of durable good
8 q12021202 How long have you used this good
9 q12031203 Please value this good
10 quarter
Quarter
11 interviewer 5. Interviewer
12 supervisor 6. Supervisor

15 ### Non-Food.dta ###1 identif
group(identif)
2 row13IA
3 itemNon-food Item code
20101 Men: Leather jacket, deel

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3520102 Men: Winter jacket, winter deel20103 Men: Overcoat
20104 Men: Other leather jacket, winter jacke
20105 Men: Suit, costume20106 Men: Wool and cashmere sweater
20107 Men: Other shirts
20108 Men: Traditional deel20109 Men: Sport wear
20110 Men: Hat, neckwear
20111 Men: Trousers
20112 Men: T-shirts
20113 Men: Underwear
20114 Men: pants (pyjamas ) and nightrobe
20115 Men: Socks
20116 Men: Tights
20117 Other men's clothing and footwear
20201 Women: Leather jacket, deel
20202 Women: Winter jacket, winter deel20203 Women: Overcoat
20204 Women: Other leather jacket, winter jac
20205 Women: Suit, costume20206 Women: Wool and cashmere sweater
20207 Women: Other shirts
20208 Women: Traditional deel20209 Women: Unlined dress and skirts
20210 Women: Sport wear
20211 Women: Hat, neckwear
20212 Women: Trousers
20213 Women: T-shirts
20214 Women: Underwear
20215 Women: pants (pyjamas ) and nightrobe
20216 Women: Socks
20217 Women: Tights
20218 Other women's clothing and footwear
20301 Children: Leather jacket, deel
20302 Children: Winter jacket, winter deel
20303 Children: Overcoat
20304 Children: Other leather jacket, winter20305 Children: Suit, costume20306 Children: Wool and cashmere sweater
20307 Children: Other shirts
20308 Children: Traditional deel
20309 Children: Unlined dress and skirts
20310 Children: Sport wear
20311 Children: Hat, neckwear
20312 Children: Trousers
20313 Children: T-shirts
20314 Children: Underwear
20315 Children: pants (pyjamas ) and nightrobe
20316 Children: Socks
20317 Children: Tights
20318 Other children's clothing and footwear
20319 All sorts of clothing for children aged
20320 Wrapping and other articles for infants

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3620401 Hat, neckwear, gloves
20402 Tie, belts
20403 Handkerchief
20404 Sewing treads
20405 Other (ribbons, press-studs, zip-fasten
20501 Dry cleaning
20502 Laundering
20503 Dyeing of garments
20504 Mending, repair
20505 Hire of garments
20601 Winter shoes
20602 Spring or autumn shoes
20603 Summer shoes, boot20604 Slippers
20605 Summer slippers
20606 Sport
20607 Traditional shoes and buriad shoes
20608 Felt
20609 Other footwear
20610 Footwear for children aged 0-2
20701 Repair of footwear
20702 Shoe cleaning services
20703 Cost for lease of shoes
20801 Woolen cloth, m
20802 Cloth Daalimba,m20803 Tsagaan yambuu, m20804 Cotton cloth, m
20805 Satin, m
20806 All kind of silk, m
20807 Synthetic, m
20808 Cotton, kg
20809 Carded wool
20810 Other......
20901 Furnished and wooden beds
20902 Sofas
20903 Metal beds
20904 Wall and wardrobes
20905 Kitchen furnitures
20906 Bedroom furnitures
20907 Table and chairs
20908 Chest
20909 Electric lamp
20910 Painting and scultures
20911 Mattress20912 Bath room accessories
20913 Mirror
20914 Beds for children
20915 Other furnitures and accessories
20916 Cost for repair and services
20917 Carpets
20918 Strip of carpet/mat
20919 Capping
20920 Oilcloth for the floor
20921 Other floor covering

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3720922 Cost for repair and services
21001 Curtains
21002 Bedsheets
21003 Bed covering
21004 Towel
21005 Bath towel
21006 Tablecloth
21007 Other woven, sewn and cloth appliances
21008 Cost for repair and services
21101 Refrigerators
21102 Vacuum cleaner
21103 Washing mashine
21104 Sewing mashine
21105 Electric and gas stove
21106 Electric heating
21107 Generators
21108 Electric fan
21109 Electric iron
21110 Electric ring/Electric hob
21111 Safe
21112 Other electric appliances (air conditio
21113 Cost for repair and services
21114 Coffee pot
21115 Rice cooker
21116 Bread roaster
21117 Water boiler and electric tea pot
21118 Other (Coffee mixer etc.)
21119 Cost for repair and services
21201 Glasses
21202 Ceramic ware/china-ware
21203 Vacuum flask
21204 Knife, spoon and fork
21205 Plastic utensils
21206 Metal and cast iron utensils
21207 Other utensils
21208 Cost for repair and services
21301 Saws
21302 Spade
21303 Rake
21304 Other (drill, nipper e.g)
21305 Door accessories (hinge e.g)
21306 Electric accessories (breaker, cable)
21307 Flashlight
21308 Lamp
21309 Battery
21310 Bell21311 Signal accessories
21312 Other
21313 Cost of repair and service
21401 Laundry soap, piece
21402 Washing powder/detergent, piece
21403 Match, piece
21404 Candle, piece
21405 Shoe polish, piece

Manual Mongolia HSES 2012 Version 2.0

3821406 Sterilization materials, kg
21407 Other cleaning materials
21408 Brush, besom, piece
21409 Garbage basin, piece21410 Brush, polisher, piece21411 Clothes-hanger, piece
21412 Needle for sewing and woven, piece
21413 Nails, nut, screw
21414 Glue, scotch tape21415 Other tools
21416 House sweeper
21417 Cost disinfection and sterilization
21418 Dry cleaning
21419 Cost for lease of domestic goods
21501 Tablets, vitamins
21502 Injection
21503 Other(condoms,IUD, bandage, thermometer
21504 Eye glasses, contact lenses
21505 Other devices (hearing devices, artific21506 Outpatients clinic examination
21507 Dental care
21508 Other medical services (to give an inje
21509 In patient
21601 Car
21602 Bus
21603 Trucks
21604 Motorcycle
21605 Bicycle
21606 Carting
21607 Repair and services of auto vehicles
21608 Wheels
21609 Spare parts of auto mobile21610 Gasoline, diesel
21611 Other fuel21612 Cost of repair and service
21613 Technical inspection and diagnostics
21614 Lease of garage
21615 Other (Charge for using roads, driving
21616 Cost for transportation rent
21701 Cost for bus and trolleybus
21702 Railway passenger service: Domestic
21703 Railway passenger service: Internationa
21704 Railway freight21705 Taxi cost: Inside the city
21706 Road transportation service: inter-urba
21707 Road transport: Inside the city
21708 Road freight : Inter-urban
21709 Air: Domestic
21710 Air: International
21711 Luggage cost of air
21712 Cost for traveling by water transport
21713 Freight of water transport
21714 Other transports
21801 Letters, parcel, post card

Manual Mongolia HSES 2012 Version 2.0

3921802 Stamps, envelope (new)21803 Telephone, fax mashine
21804 Repair cost of telephone and fax mashin
21805 Calling: Inter-urban
21806 Calling: International
21807 Telephone charge
21808 Mobile/cell phone
21809 Service charge of telegraph, telex and21810 Lease cost of telephone and fax
21811 Installing charge of equipments
21812 Calling card
21813 Charge for internet service
21901 Radio
21902 Black-white TV
21903 Color TV
21904 TV aerial
21905 Tape-recorder21906 Video player
21907 Video camer
21908 Binoculars
21909 Camera
21910 Computer
21911 Calculator
21912 Audio and video cassette, CD
21913 Films
21914 Repair cost of above equipments
21915 Travel tools (boat etc)
21916 Musical instruments (guitar etc)
21917 Billiard board
21918 Repair cost of above tools
22001 Playing card
22002 Chess
22003 Puzzle
22004 Dolls
22005 Car
22006 Electric toys
22007 Other toys
22008 Collection (stamp-collection etc)
22009 Cassette with games, CD
22010 Sport tools (skiing etc)
22011 Gun
22012 Tent
22013 Live and artificial flowers
22014 Xristmas tree
22015 Pets
22016 Food for pets
22017 Shelter, tie and bowl of pets
22018 Services related to the pets(care, trea
22101 Driving lessons
22102 Fee for sport s group study
22103 Performance fee (cinema, drama, concert
22104 Service charge for puppet places
22105 Renting for sport tools
22106 Charge for radio and TV set (cabel TV)

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4022107 Develop and print out photo films
22108 Lottery
22201 Newspapers and journals
22202 Notebook
22203 Pen
22204 Pencil
22205 Books and dictionary
22206 Paper
22207 Other printed matters (post card, calen
22208 Other stationary (ink, erassor, folder
22301 Total cost for recreation and travel
22401 Tuition fee: pre-primary
22402 Tuition fee: primary
22403 Tuition fee: literacy programmes for st
22404 Tuition fee: secondary
22405 Tertiary
22406 Course
22501 Restaurants, cafes
22502 Canteens in schools, works canteens
22503 Accommodation services of hotels
22504 Accommodation services of holidays vill22505 Accommodation services of boarding scho
22601 Toothbrush
22602 Tooth paste
22603 Beauty soap
22604 Toilet paper
22605 Sanitary nupkins
22606 Hairdressing
22607 Beauty salon
22608 Electric razors
22609 Hair dryier
22610 Other electric appliances
22611 Repair of such appliances
22612 Non-electrical razors
22613 Other non-electrical appliances
22614 Beauty powder
22615 Perfume22616 Other beauty products
22701 Valuables
22702 Watches
22703 Repair for valuables
22704 Watch repair
22705 Suitcase
22706 Bag
22707 Wallet
22708 Babys cart, chair
22709 Tube, lighter, ash-tray
22710 Sun glasses, umbrella
22711 Appliances for funeral (coffin, stone e
22712 Repair of above appliances
22801 Service fees for caring elders and disa
22901 Health insurance
22902 Life insurance
22903 Dwelling insurance

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4122904 Transport insurance
22905 Other
23001 Fee for financial consultation
23002 Service fees for banks and other financ
23101 Fees for administrative documents (for23102 Payment for the services of property ma
23103 Fees for legal services, employment age
23104 Charges for the leasing or rental
23105 Other services
23201 Wall paper, package
23202 Oil paint, l
23203 Bricks, piece
23204 Cement, kg
23205 Glass, m2
23206 Other......
24101 Apartment
24102 House
24103 Ger (complete)
24104 Tent frame
24105 Tent covering
24106 Yard
24107 Stove
24108 Other
24201 Income tax
24202 Cattle tax
24203 Land tax
24204 Other taxes
24301 Gifts for individual
24302 Cost for celebration and wedding
24303 For church and temple
24304 For institution
24305 Other
4 cluster
5 aimag
6 soum
7 location
8 q1301

Cluster
2. Aimag
3. Soum
4. Location
1301. Have you bought or received for the last 12 Ms
1 YES
2 NO
9 q13021302. Purchased during the past month
10 q1303
1303. Purchased during the past 12 months
11 q1304
1304. Received free during the past 12 months
12 q1305
13.05
13 quarter
Quarter
14 interviewer 5.Interviewer
15 supervisor 6. Supervisor

16 ### Urban Diary.dta ###1 identif
group(identif)
2 cluster
Cluster
3 aimag
2. Aimag4 soum
3. Soum
5 location 4. Location

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42

6 row14
7 itemFood Item code
8 q1401_1
14.01_1 First 10 - Total consumed
9 q1401_2
14.01_2 First 10 - Purchased
10 q1401_3
14.01_3 First 10 - Reseived free
11 q1401_4
14.01_4 First 10 - Own production
12 q1402_1
14.02_1 Second 10 - Total consumed
13 q1402_2
14.02_2 Second 10 - Purchased
14 q1402_3
14.02_3 Second 10 - Reseived free
15 q1402_4
14.02_4 Second 10 - Own production
16 q1403_1
14.03_1 Third 10 - Total consumed
17 q1403_2
14.03_2 Third 10 - Purchased
18 q1403_3
14.03_3 Third 10 Reseived free
19 q1403_4
14.03_4 Third 10 Own production
20 q1404
1404 Average unit price21 quarter
Quarter
22 interviewer 5. Interviewer
23 supervisor 6. Supervisor

17 ### Rural Food 7 day.dta ###1 identif
group(identif)
2 row15
3 itemItem Code
10101 Bread (1 piece = 670 gr) - piece
10102 Rice - Kg
10103 Flour, highest grade - Kg
10104 Flour, grade 1 - Kg
10105 Flour, grade 2 - Kg
10106 Other flour - Kg
10107 Noodle,domestic - Kg
10108 Noodle, import - Kg
10109 Bakery - Kg
10110 Biscuit - Kg
10111 Cake - Kg
10112 Millet - Kg
10113 Other rice (farina…) - Kg
10114 Pizza - Piece
10115 Other flour and flour products - Kg
10201 Mutton - Kg10202 Beef - Kg10203 Goat meat - Kg10204 Horse meat - Kg10205 Camel meat - Kg
10206 Dried meat - Kg10207 chicken - Kg10208 Pork - Kg10209 Bacon - Kg
10210 Game - Kg
10211 Other poultry - Kg
10212 Animal interior - Kg
10213 Sausage,salami kg - Kg10214 Sausage - Kg10215 Canned meat - Kg

Manual Mongolia HSES 2012 Version 2.0

4310216 Other meat, meat products - Kg
10301 Fish - Kg
10302 Dried, smoked, salted fish - Kg10303 Canned fish - Kg10304 Other fish and seafood - Kg
10401 Milk - Lt
10402 Youghurt - Lt
10403 Eggs - Nb
10404 Dried curds - Kg
10405 Horse milk, l - Lt
10406 Curds - Kg
10407 Cheese, national - Kg
10408 Cheese - Kg
10409 Curds - Kg
10410 Other milk products - Kg
10411 Dried and coffee milk - Kg
10412 Condensed milk - Lt
10413 Sour cream - Kg
10414 Dried eggs - Kg
10415 Other milk, cheese and eggs - N/A
10501 Butter - kg
10502 Margarine - kg
10503 Vegetable oil - Lt
10504 Edible animal fats - kg
10505 Cream - kg
10506 Melted butter - kg
10507 Olive oil - Lt
10508 Other oils and fats - kg
10601 Apple - Kg
10602 Mandarin - Kg
10603 Raisin,kg - Kg
10604 Other fresh fruit ,kg - Kg
10605 Wild fruit - Kg
10606 Dried fruit - Kg
10607 Wild nuts,kg - Kg
10608 Other nuts - Kg
10609 Other Fruits /watermelon etc./ - Kg
10701 Potato - Kg
10702 Cabbage - Kg10703 Carrot - Kg
10704 Turnip - Kg
10705 Onion - Kg
10706 Garlic - Gr
10707 Tomato - Kg
10708 Cucumber - Kg
10709 Jelly sticks - Kg
10710 Canned cucumber - Kg10711 Canned vegetable salad - Kg
10712 Pepper - Kg
10713 Mushrooms - Kg10714 Other vegetables - Kg
10801 Sugar - Kg
10802 Lump sugar - Kg10803 Sugar substitution - Gr

Manual Mongolia HSES 2012 Version 2.0

4410804 Candy - Kg10805 Sweet - Kg
10806 Chocolate - Gr
10807 Honey - Gr
10808 Compotes - Gr
10809 Jam - Gr
10810 Icecream - Gr10811 Chewing gum - Piece
10812 Syrop - Gr
10813 Other (marmalades, sugar, jam) - N/A
10901 Salt - Gr
10902 Vinegar - Gr
10903 Ketchup - Gr
10904 Mayonnaise - kg
10905 Yeast - Gr
10906 Spice - Gr
10907 Babyfood - kg
10908 Other spices, other food - N/A
11001 Green tea - Gr
11002 Tea - Gr
11003 Coffee - Gr
11004 Cocoa - Gr
11005 Other tea, coffee - Gr
11101 Beverage - Lt
11102 Juice - Lt
11103 Pure water, bottled - Lt
11104 Other soft drinks - Lt
11201 Vodka, domestic - Lt
11202 Beer, domestic - Lt
11203 Vodka, imported - Lt
11204 Beer, imported - Lt
11205 Wine - Lt
11206 Other alcoholic beverages - Lt
11301 Cigarette, imported - Box
11302 Cigarette, domestic - Box
11303 Tobacco - Gr
11304 Snuff - Gr
11305 Other (tobacco) - Gr
4 cluster
Cluster
5 aimag
2. Aimag6 soum
3.Soum
7 location 4. Location
8 q1501
1501. Have you consumed food during the 7 days
9 q15021502. Total consumed in the past 7 days
10 q1503
1503. Consumed from purchases
11 q1504
1504. Unit price12 q1505
1505. Consumed from Received free
13 q1506
1506. Consumed from Produced
14 quarter
Quarter
15 interviewer 5. Interviewer
16 supervisor 6. Supervisor

18 ### Foodstuffs.dta ###Manual Mongolia HSES 2012 Version 2.0

45

1 identif
2 cluster
3 aimag
4 soum5 location
6 q1601

7 q1602

8 q1603y
9 q1603m
10 q1603d
11 q1604
12 q1605

group(identif)
Cluster
2. Aimag
3. Soum
4. Location(16.01)
1 OEEI
2 ￣A￣E(16.02)
1 OEEI
2 ￣A￣E(16.03)(16.04)(16.05)
1 OEEI
2 ￣A￣E

13 q1606(16.06)
1 OEEI
2 ￣A￣E

14 q1607(16.07)
1 OEEI
2 ￣A￣E

15 quarter
Quarter
16 interviewer 5. Interviewer
17 supervisor 6. Supervisor

19 ### Foodout.dta ###1 identif
group(identif)
2 cluster
Cluster
3 aimag
2. Aimag4 soum
3. Soum
5 location 4. Location
6 itemitem
22501 Restaurants, cafes
22502 Canteens in schools, works canteens
7 q1507
1 YES
2 NO
8 q1508
14.06/ 15.08
9 q1509
14.07/ 15.09
10 quarter
Quarter
11 interviewer 5. Interviewer
12 supervisor 6. Supervisor

20 ### Basicvars.dta ###1 identif
group(identif)
2 cluster
Cluster
3 newaimag New code of aimag
11 Ulaanbaatar

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46

21 Dornod
22 Sukhbaatar
23 Khentii
41 Tov
42 Govisumber
43 Selenge
44 Dornogovi
45 Darkhan-Uul
46 Omnogovi
48 Dundgovi
61 Orkhon
62 Ovorkhangai
63 Bulgan
64 Bayankhongor
65 Arkhangai
67 Khovsgol
81 Zavkhan
82 Govi-Altai
83 Bayan-Olgii
84 Khovd
85 Uvs
4 location Strata 4 locations
5 urbanUrban/rural
1 Urban
2 Rural6 region
Region1 West2 Highlands
3 Central
4 East5 Ulaanbaatar
7 monthCalendar month of the interview
8 quarter
Calendar quarter of the interview
9 strata
Strata 3
10 hhweight Last weight
11 hhsize
Household size
12 aimagsoum Combinations of aimags and soums>

Manual Mongolia HSES 2012 Version 2.0

47References The variable of newaimag in “Basicvars.dta” is the same as “aimag”.
> dim(outfiles[[1]])[1] 12811
88> dim(outfiles[[20]])[1] 12811
12> table(outfiles[[1]]$identif==outfiles[[20]]$identif)
TRUE
12811
> table(outfiles[[1]]$aimag==outfiles[[20]]$newaimag)
TRUE
12811


The item codes of “Urban Diary.dta” and “Rural Food 7 day.dta” are consistent.

> length(unique(outfiles[[16]]$item))[1] 123> length(unique(outfiles[[17]]$item))[1] 123> setdiff(unique(outfiles[[16]]$item),unique(outfiles[[17]]$item))
integer(0)> setdiff(unique(outfiles[[17]]$item),unique(outfiles[[16]]$item))
integer(0)The value label of “7 BROTHER/SISTER IN LAW” should be read as “7 SON?DAUGHTER
IN LAW”.

HSES 2012

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48

Population and housing census 2010

Note: “SON/DAUGHTER IN LAW” is correctly displayed in HSES 2012 questionnaire in English.
The delegates from Mongolia to the workshop agreed to the above point.

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49

4.3 Identifier
Household identifier> d<-outfiles[[20]] # Basicvars> dim(d)[1] 12811
12


The variable of “identif”is unique identifier and the number of unique “identif” is 12,811.

> length(unique(d$identif))[1] 12811> sum(duplicated(d$identif))[1] 0Person identifierPerson identifier is the combination of “identif” and “ind_id” for data frames of“Individual”.

# Generated person identifier “PID”.
02 Individual

PID in data frame “Individual” is unique.

> df<-outfiles[[2]]> dim(df)[1] 47908 129> df$PID<-df$identif*100+df$ind_id> head(df[,c(1:2,130)])
identif ind_id PID
1
1
1 101
2
1
2 102
3
1
3 103
4
2
1 201
5
2
2 202
6
2
3 203
> sum(duplicated(df$PID))[1] 0> outfiles[[2]]<-df

10 Remittance

PID in data frame “Remittance” is not unique.
There are 303 duplicated PID in data frame “Remittance”.

> df<-outfiles[[10]]> dim(df)[1] 3670
17> df$PID<-df$identif*100+df$ind_id> head(df[,c(1,7,18)])

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50

1
2
3
4
5
6

identif ind_id
PID
13
1 1301160
1 16001167
1 16701176
5 17605186
1 18601189
1 18901> sum(duplicated(df$PID))[1] 303# Example of duplicated PID> head(df[duplicated(df$PID),])
identif ln cluster aimag soum location ind_id q0909 q0910 q0911 q0912
32
467 2
226
82
1
2
1
4
2
3
NA
65
591 2
284
21 28
4
1
4
5
1
NA
68
596 2
284
21 28
4
1
4
5
1
NA
73
604 2
285
21 28
4
1
4
5
2
NA
75
605 2
286
21 28
4
1
4
5
3
NA
78
613 2
289
21
1
2
2
4
1
3
NA
q0913 q0914 q0915 quarter interviewer supervisor
PID
32 1000000
521282 46701
65 500000
431
121 59101
68 700000
431
121 59601
73 400000
441
121 60401
75 300000
431
1
21 60501
78 500000
541
221 61302> df[df$identif==467,]
identif ln cluster aimag soum location ind_id q0909 q0910 q0911 q0912
31
467 1
226
82
1
2
1
4
1
3
NA
32
467 2
226
82
1
2
1
4
2
3
NA
q0913 q0914 q0915 quarter interviewer supervisor
PID
31 1020000
211
2
82 46701
32 1000000
521282 46701
Summary: The person with PID=46701 received two kind of remittance.

> outfiles[[10]]<-df

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51

4.4 WeightThe variable of household weight is “hhweight” in data frame “Basicvars”.

The estimated number of household is 739,058.

> sum(d$hhweight)[1] 739058.2
The estimated number of household members is 2,688,597, based on “Basicvars” file.

> sum(d$hhweight*d$hhsize)[1] 2688597
The estimated number of household members is 2,688,597, based on “Individual” file.

> df<-outfiles[[2]]> dim(df)[1] 47908 130> df<-merge(df,d[,c("identif","hhweight")],by="identif",all.x=T)> dim(df)[1] 47908 131# Selected household members> df<-subset(df,q0111==1)> dim(df)[1] 46648 131> sum(df$hhweight)[1] 2688597> nrow(df)/nrow(d)[1] 3.641246> sum(d$hhweight*d$hhsize)/sum(d$hhweight)[1] 3.637869

Number of households
Number of household members
Household size

Un-weighted
12,81846,6483.64

Weighted
739,058
2,688,597
3.64

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52Chapter 5. Data Check
5.1 Structure of each data file
> Rnames<-sub(".dta","",STATA.files)> for(j in 1:20){+ cat("##",j,"#### ",Rnames[j]," #########\n")+ print(str(outfiles[[j]]))+ cat("\n\n")+ }## 1 #### Household #########'data.frame': 12811 obs. of 88 variables:$ identif: int 1 2 3 4 5 6 7 8 9 10 ...
$ year: int 12 12 12 12 12 12 12 12 12 12 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ cluster: int 1 1 1 1 1 1 1 1 6 6 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 3 4 3 4 4 3 4 3 3 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
$ operator : int 65 65 65 65 65 65 65 65 65 65 ...
$ q0008: int 3 4 3 4 5 6 8 4 5 6 ...
$ hh_no: int 2 3 4 5 6 7 8 12 1 2 ...
$ q0009: int 1 1 1 1 1 1 1 3 1 1 ...
$ q0010: int 1 1 1 1 1 1 1 1 1 1 ...
$ v1_dd: int 20 21 20 21 19 19 22 22 31 30 ...
$ v1_mm: int 3 3 3 3 3 3 3 3 1 1 ...
$ v1_yy: int 12 12 12 12 12 12 12 12 12 12 ...
$ v1_res: int 1 1 1 1 1 1 1 1 1 1 ...
$ v2_dd: int NA NA NA NA NA NA NA NA NA NA ...
$ v2_mm: int NA NA NA NA NA NA NA NA NA NA ...
$ v2_yy: int NA NA NA NA NA NA NA NA NA NA ...
$ v2_res: int NA NA NA NA NA NA NA NA NA NA ...
$ v3_dd: int NA NA NA NA NA NA NA NA NA NA ...
$ v3_mm: int NA NA NA NA NA NA NA NA NA NA ...
$ v3_yy: int NA NA NA NA NA NA NA NA NA NA ...
$ v3_res: int NA NA NA NA NA NA NA NA NA NA ...
$ v4_dd: int NA NA NA NA NA NA NA NA NA NA ...
$ v4_mm: int NA NA NA NA NA NA NA NA NA NA ...
$ v4_yy: int NA NA NA NA NA NA NA NA NA NA ...
$ v4_res: int NA NA NA NA NA NA NA NA NA NA ...
$ q0701: int 1 1 1 2 1 1 2 1 2 2 ...
$ q0707: int 1 1 1 NA 1 1 NA 1 NA NA ...
$ q0715: int 2 2 2 2 2 2 2 2 2 2 ...
$ q0716: num NA NA NA NA NA NA NA NA NA NA ...
$ q0717: int NA NA NA NA NA NA NA NA NA NA ...
$ q0718: num NA NA NA NA NA NA NA NA NA NA ...
$ q0801: int 2 2 2 2 2 2 2 2 2 2 ...
$ q0802: int NA NA NA NA NA NA NA NA NA NA ...
$ q0907: int 2 2 2 2 2 2 2 2 2 2 ...
$ q1001: int 2 2 2 2 2 2 2 2 2 2 ...
$ q1002: int NA NA NA NA NA NA NA NA NA NA ...
$ q1003: int 2 1 2 2 2 1 2 1 1 2 ...

Manual Mongolia HSES 2012 Version 2.0

53$ q1004: int NA 1 NA NA NA 1 NA 1 1 NA ...
$ visitor: int 0 0 0 0 0 0 0 0 0 0 ...
$ ndays: int 0 0 0 0 0 0 0 0 0 0 ...
$ q1101: int 1 1 1 1 1 1 1 1 1 1 ...
$ q1102: int 1 1 1 1 1 1 1 1 1 1 ...
$ q1103: int 1 4 1 1 1 1 3 1 3 1 ...
$ q1104: int NA 1 NA NA NA NA NA NA 1 NA ...
$ q1105: int NA 3 NA NA NA NA NA NA 3 NA ...
$ q1106: int NA 1 NA NA NA NA NA NA 2 NA ...
$ q1107: int NA 1 NA NA NA NA NA NA 1 NA ...
$ q1108: num NA 20 NA NA NA NA NA NA 30 NA ...
$ q1109: num NA 28 NA NA NA NA NA NA 40 NA ...
$ q1110: int NA NA NA NA NA NA NA NA NA NA ...
$ q1111: int 5 NA 5 5 5 5 5 5 NA 4 ...
$ q1112: int 1 NA 1 1 2 2 1 2 NA 2 ...
$ q1113: int 1 NA 1 1 2 2 1 2 NA 2 ...
$ q1114: int 2 NA 2 2 2 2 2 2 NA 1 ...
$ q1115: int 3 5 9 12 15 11 16 15 6 5 ...
$ q1116: int 3 5 9 12 15 11 16 15 6 5 ...
$ q1117: int 3 3 3 3 3 3 3 3 3 3 ...
$ q1118: int 4 4 4 4 4 4 4 4 5 4 ...
$ q1119: int 2 2 2 2 2 2 2 2 2 2 ...
$ q1120: int 99 99 99 99 99 99 99 99 99 99 ...
$ q1121: int NA NA NA NA NA NA NA NA NA NA ...
$ q1122: int 4 4 4 4 4 4 4 4 4 4 ...
$ q1123: int 3 1 6 1 3 3 1 3 1 1 ...
$ q1124: int 2 1 2 1 1 2 1 2 1 1 ...
$ q1125: int 6 3 6 3 6 6 3 6 3 3 ...
$ q1126: int 4 3 4 3 4 4 3 4 4 3 ...
$ q1127: int 4 2 4 2 3 4 2 3 2 2 ...
$ q1128: int 4 3 4 3 4 4 2 3 3 3 ...
$ q1129: int 1 1 1 4 1 4 1 4 1 4 ...
$ q1130_1: num 50 1 45 1 30 45 1.5 30 1 1 ...
$ q1130_2: num 50 1 45 1 30 45 1.5 30 1 1 ...
$ q1130_3: num 50 1 45 1 30 45 1.5 30 1 1 ...
$ q1130_4: num 0 1 0 1 0 0 1 0 1 1 ...
$ q1131: int 2 1 2 2 2 2 2 2 1 2 ...
$ q1132a: int NA 700 NA NA NA NA NA NA 700 NA ...
$ q1132b: int NA 0 NA NA NA NA NA NA 0 NA ...
$ q1133: int 2 2 2 2 2 2 2 2 2 2 ...
$ q1134: int NA NA NA NA NA NA NA NA NA NA ...
$ q1135_1: int NA NA NA NA NA NA NA NA NA NA ...
$ q1135_2: int NA NA NA NA NA NA NA NA NA NA ...
$ q1135_3: int NA NA NA NA NA NA NA NA NA NA ...
$ q1135_4: int NA NA NA NA NA NA NA NA NA NA ...
$ q1135_5: int NA NA NA NA NA NA NA NA NA NA ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:12"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 251 252 251 251 251 251 251 251 ...
- attr(*, "val.labels")= Named chr "" "" "" "" ...
..- attr(*, "names")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Year" "Quarter" "Cluster" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 41..$ q1135_5 : Named int 1 2

Manual Mongolia HSES 2012 Version 2.0

54.. ..- attr(*, "names")= chr "YES " "NO "..$ q1135_4 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q1135_3 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q1135_2 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q1135_1 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q1133 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q1131 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q1129 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "YES, LAND LINE PHONE" "YES, MOBILE PHONE" "YES, BOTH LAND AND MOBILE
PHONE" "NO"..$ q1128 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "SEPARATE" "PUBLIC" "OUTSIDE THE DWELLING" "NO TOILET"..$ q1127 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "" "" "NO SPECIAL PLACE" "OTHERS"..$ q1125: Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "CENTRALIZED: HOT & COLD WATER PIPE" "CENTRALIZED: COLD WATER PIPE
ONLY" "PROTECTED WELL" "UNPROTECTED WELL" ...
..$ q1124 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q1123: Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "CENTRAL SYSTEM " "LOCAL SYSTEM/DIESEL STATION " "SOLAR SUSTEM ""WIND SYSTEM " ...
..$ q1122: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "CENTRALIZED" "TRADITIONAL FIRE WOOD/COAL/ DUNG STOVE" "PRIVATE
ELECTRICAL HEATER" "PRIVATE LOW PRESSURE BOILER" ...
..$ q1120 : Named int 99.. ..- attr(*, "names")= chr "***Undefined Label"..$ q1119 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q1118: Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "RENTING " "INHERITED " "GIFT " "BUILT BY OURSELVES " ...
..$ q1117 : Named int 1 2 3.. ..- attr(*, "names")= chr "STATE " "ORGANIZATION'S" "PRIVATE "..$ q1115 : Named int 99.. ..- attr(*, "names")= chr "***Undefined Label"..$ q1114 : Named int 1 2 3.. ..- attr(*, "names")= chr "WOOD" "EARTH" "OTHER"..$ q1113 : Named int 1 2.. ..- attr(*, "names")= chr "SINGLE" "DOUBLE"..$ q1112 : Named int 1 2.. ..- attr(*, "names")= chr "SINGLE" "DOUBLE"..$ q1107 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "WOOD" "CEMENT" "EARTH" "OTHER"..$ q1106 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "METAL" "ASPHALT ROOF SHINGLES" "TILE" "OTHER"..$ q1105: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "BRICKS" "CEMENT" "WOOD" "STONE" ...
..$ q1103: Named int 1 2 3 4 5 6 7 8 9.. ..- attr(*, "names")= chr "GER" "APARTMENT" "BUILDING" "DETACHED HOUSE" ...
..$ q1102 : Named int 1 2

Manual Mongolia HSES 2012 Version 2.0

55.. ..- attr(*, "names")= chr "YES " "NO "..$ q1003 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q1001 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q0907 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q0801 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q0717 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q0715 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q0707 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ q0701 : Named int 1 2.. ..- attr(*, "names")= chr "YES " "NO "..$ v4_res : Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "COMPLETE " "PARTIALLY COMPLETED" "NO RESPONDENT IN THE HOUSEHOLD""HOUSEHOLD TEMPERARILY NOT PRESENT" ...
..$ v3_res : Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "COMPLETE " "PARTIALLY COMPLETED" "NO RESPONDENT IN THE HOUSEHOLD""HOUSEHOLD TEMPERARILY NOT PRESENT" ...
..$ v2_res : Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "COMPLETE " "PARTIALLY COMPLETED" "NO RESPONDENT IN THE HOUSEHOLD""HOUSEHOLD TEMPERARILY NOT PRESENT" ...
..$ v1_res : Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "COMPLETE " "PARTIALLY COMPLETED" "NO RESPONDENT IN THE HOUSEHOLD""HOUSEHOLD TEMPERARILY NOT PRESENT" ...
..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 12811 88
NULL## 2 #### Individual #########'data.frame':
47908 obs. of 130 variables:$ identif: int 1 1 1 2 2 2 2 3 3 3 ...
$ ind_id: int 1 2 3 1 2 3 4 1 2 3 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 4 3 3 3 3 4 4 4 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
$ q0102: int 1 2 3 1 2 3 3 1 2 3 ...
$ q0103: int 1 2 2 1 2 2 1 1 2 2 ...
$ q0104: int 1988 1988 2009 1987 1983 2006 2010 1984 1984 2003 ...
$ q0105y: int 23 23 3 25 28 6 2 28 28 8 ...
$ q0105m: int NA NA NA NA NA NA NA NA NA NA ...
$ q0106: int 2 2 NA 2 2 NA NA 2 2 NA ...

Manual Mongolia HSES 2012 Version 2.0

56$ q0107$ q0108$ q0109$ q0110a$ q0110$ q0111$ q0201$ q0202$ q0203$ q0204$ q0205$ q0206_1$ q0206_2$ q0206_3$ q0206_4$ q0206_5$ q0207$ q0208$ q0209$ q0210$ q0211$ q0212$ q0213$ q0214$ q0215$ q0216t$ q0216g$ q0217$ q0218$ q0219$ q0220$ q0221$ q0222$ q0223$ q0224$ q0225$ q0226_1$ q0226_2$ q0226_3$ q0226_4$ q0226_5$ q0226_6$ q0226_7$ q0301$ q0302$ q0303$ q0304$ q0305$ q0306$ q0307$ q0308_1$ q0308_2$ q0309$ q0310$ q0311$ q0312

: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: num
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int
: int

2 1 NA 2 1 NA NA 2 1 NA ...
99 99 1 99 99 1 1 99 99 1 ...
99 99 2 99 99 2 2 99 99 2 ...
0 0 0 0 0 0 0 0 0 0 ...
0 0 0 0 0 0 0 0 0 0 ...
1 1 1 1 1 1 1 1 1 1 ...
2 2 1 2 2 1 1 2 2 2 ...
NA NA 1 NA NA 2 2 NA NA NA ...
NA NA 2 NA NA 2 2 NA NA NA ...
NA NA 4 NA NA 1 4 NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
1 1 2 1 1 1 2 1 1 1 ...
1 2 NA 1 2 2 NA 2 1 2 ...
NA 1 NA NA 1 1 NA 2 NA 2 ...
2 4 NA 2 8 1 NA 2 2 1 ...
1 NA NA 2 NA 2 NA 2 2 2 ...
4 4 NA 4 4 1 NA 4 4 1 ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA 1 NA NA NA 1 ...
NA NA NA NA NA 1 NA NA NA 3 ...
NA NA NA NA NA 1 NA NA NA 1 ...
NA NA NA NA NA 3 NA NA NA 2 ...
NA NA NA NA NA 1 NA NA NA 4 ...
NA NA NA NA NA 1 NA NA NA 1 ...
NA NA NA NA NA 5 NA NA NA 10 ...
NA NA NA NA NA 2 NA NA NA 2 ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA 0 NA NA NA 0 ...
NA NA NA NA NA 0 NA NA NA 0 ...
NA NA NA NA NA 60000 NA NA NA 60000 ...
NA NA NA NA NA 18000 NA NA NA 18000 ...
NA NA NA NA NA 0 NA NA NA 0 ...
NA NA NA NA NA 0 NA NA NA 0 ...
NA NA NA NA NA 78000 NA NA NA 78000 ...
1 2 2 1 2 2 2 2 1 2 ...
NA 1 1 NA 1 1 1 2 NA 2 ...
1 1 1 1 1 1 1 2 2 2 ...
NA NA NA NA NA NA NA 1 2 2 ...
2 2 2 2 2 2 2 2 2 2 ...
NA NA NA NA NA NA NA NA NA NA ...
2 2 2 2 2 2 2 2 2 2 ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...
NA NA NA NA NA NA NA NA NA NA ...

Manual Mongolia HSES 2012 Version 2.0

57$ q0313: int NA NA NA NA NA NA NA NA NA NA ...
$ q0314a: int NA NA NA NA NA NA NA NA NA NA ...
$ q0314b: int NA NA NA NA NA NA NA NA NA NA ...
$ q0315: int 2 2 2 2 2 2 2 2 2 2 ...
$ q0316: int NA NA NA NA NA NA NA NA NA NA ...
$ q0317: int 2 2 2 2 2 2 2 2 2 2 ...
$ q0318: int NA NA NA NA NA NA NA NA NA NA ...
$ q0319: int NA NA NA NA NA NA NA NA NA NA ...
$ q0320: int NA NA NA NA NA NA NA NA NA NA ...
$ q0321: int NA NA NA NA NA NA NA NA NA NA ...
$ q0322: int NA NA NA NA NA NA NA NA NA NA ...
$ q0323: int 2 2 1 2 2 2 2 2 2 2 ...
$ q0324: int 2 2 2 2 2 2 2 2 2 2 ...
$ q0325: int 2 2 2 2 2 2 2 2 2 2 ...
$ q0401: int 2 1 2 2 1 2 2 2 1 2 ...
$ q0402: int NA 2 NA NA 2 NA NA NA 1 NA ...
$ q0403: int NA NA NA NA NA NA NA NA 1 NA ...
$ q0404: int NA NA NA NA NA NA NA NA 2 NA ...
$ q0405: int NA NA NA NA NA NA NA NA NA NA ...
$ q0406: int NA NA NA NA NA NA NA NA 2 NA ...
$ q0407: int NA NA NA NA NA NA NA NA NA NA ...
$ q0501: int 1 1 2 1 1 2 2 1 1 2 ...
$ q0502: int 1 1 NA 1 1 NA NA 1 2 NA ...
$ q0503: int 2 2 NA 2 2 NA NA 2 NA NA ...
$ q0504: int NA NA NA NA NA NA NA NA 4 NA ...
$ q0505: int NA NA NA NA NA NA NA NA 3 NA ...
$ q0506: int NA NA NA NA NA NA NA NA 2003 NA ...
$ q0507: int NA NA NA NA NA NA NA NA 1 NA ...
[list output truncated]- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:20"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= Named chr "" "" "" "aimag" ...
..- attr(*, "names")= chr "" "" "" "aimag" ...
- attr(*, "var.labels")= chr "group(identif)" "Ind_id" "Cluster" "Aimag" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 64..$ q0618 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0616 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0615: Named int 1 2 3 4 5 6 7 8 9.. ..- attr(*, "names")= chr"IaOaDEaE" "OIDOII" "OOAUOAAO EIIIAIE" "OsCAAADEAAAIAEOADEOOEAAAOAE EIIIAIE" ...
..$ q0611 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0610: Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "ITOOAI/NODAA × " "aIAaD IANOAE" "AYDEEI AAEEOAE , O￣￣ OYAANADAAA" "AAEE O￣EYYA AAEAAA" ...
..$ q0609: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "OaAaEIaD, OAEAIA, ￣EE×EEAYYIEE OYEOYNO OAIANAI" "IAEC, IaOaA,OAIAAOAI NAAAIAAANAA OONEAIA O￣NNYI" "OYAEYE, IYAYYEEEEI CADUI AAAOO OAENAI" "NIIEIA aaDaa CADEAE
aANaI" ...
..$ q0608 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"Manual Mongolia HSES 2012 Version 2.0

58..$ q0607: Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "aA×OYE" "AEDYINYI" "AONAUA ANADNAI" "AIAD× AAENAI" ...
..$ q0606 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0605: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "OAEEIOAE AAEE" "OAEEI OaENA ￣ E AAEE" "IAE AA AOOE" "AACADOADEAEAI" ...
..$ q0604 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0602 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0601 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0407: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "YI" "ADaIAaA" "NOOEAAO" "OADEA" ...
..$ q0406 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0405: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "WAGE JOB" "UNPAID WORK" "SELF EMPLOYED HERDING" "SELF EMPLOYEDAGRICULTURE" ...
..$ q0404 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0403 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0402 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0401 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0325 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0324 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0323 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0319: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "IYDAYAEEEI EO YI×" "aDOEEI YI×" "NOAEEAA×" "AADEA×" ...
..$ q0318: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "EEEIEEEEI AIEII OaDaEANaI IYDAYAEEEI YIIYEYA" "AEIAA/ A￣￣DAEEIIYAANYI YIIYEYA" "NOI, NOI AOIAUI AIEII aDOEEI YIIYEYA" "OOAEEI" ...
..$ q0317 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0313 : Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "CENTRAL HOSPITAL/CLINIC " "AIMAG/DISTRICT CLINIC " "SOUM CENTERFAMILY CLINIC " "PRIVATE " ...
..$ q0312 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0310 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0308_2 : Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "SPECIALISED DOCTOR" "FAMILY DOCTOR" "MEDSISTER" "CHIROPRACTOR" ...
..$ q0308_1 : Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "SPECIALISED DOCTOR" "FAMILY DOCTOR" "MEDSISTER" "CHIROPRACTOR" ...
..$ q0307 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0306: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "NOT SERIOUS ENOUGH " "HEALTH FACILITY TOO FAR " "NO TRANSPORTATION

Manual Mongolia HSES 2012 Version 2.0

59" "HEALTH CARE TOO EXPENSIVE " ...
..$ q0305 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0304: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "RESPIRATORY SYSTEM" "DIGESTIVE SYSTEM" "URINARY AND SEXUAL ORGAN""BLOOD CIRCULATION SYSTEM" ...
..$ q0303 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0301 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0224: Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "NODAAEOUI OaDEEI NAI" "AAIA, AAIE" "OAA" "YOYA YO, OaDaE NAAAI" ...
..$ q0223 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q0222 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0219: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "HOME" "GER APPART FROM HH" "DORMITORY" "RELATIVES" ...
..$ q0218 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "CAPITAL CITY" "AIMAG CENTER" "SOUM CENTER" "ABROAD"..$ q0217 : Named int 1 2 3.. ..- attr(*, "names")= chr "PUBLIC " "PRIVATE " "OTHER "..$ q0216t : Named int 1 2 3 4.. ..- attr(*, "names")= chr"GENERAL" "VOCATIONAL" "COLLEGE, UNIVERSITY" "OTHER(ECLE-SIASTICAL, NON FORMAL)"..$ q0215 : Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "CHILD NOT INTRESTED" "PARENTS NOT INTERESTED" "DIFFICULT TRAINING""POOR TRAINING QUALITY" ...
..$ q0214 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0212 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "YES" "NO, DROPPEDOUT" "NO, NEVER ATTENDED" "NO, COMPLETED"..$ q0211 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "YES, EASILY" "YES, WITH DIFFICULTY" "NO" ""..$ q0210: Named int 1 2 3 4 5 6 7 8 9 10.. ..- attr(*, "names")= chr "NONE" "PRIMARY" "SECONDARY" "COMPLETE SECONDARY" ...
..$ q0208: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "CHILD NOT INTRESTED" "PARENTS NOT INTERESTED" "DIFFICULT TRAINING""POOR TRAINING QUALITY" ...
..$ q0207 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0205 : Named int 1 2 3.. ..- attr(*, "names")= chr "YES, EASILY" "YES, WITH DIFFICULTY" "NO"..$ q0204: Named int 1 2 3 4 5 6 7 8 9 10.. ..- attr(*, "names")= chr "NONE" "PRIMARY" "SECONDARY" "COMPLETE SECONDARY" ...
..$ q0202 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0201 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0111 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0109 : Named int 98 99.. ..- attr(*, "names")= chr "***Undefined Label" "***Undefined Label"..$ q0108 : Named int 98 99.. ..- attr(*, "names")= chr "***Undefined Label" "***Undefined Label"..$ q0107 : Named int 98

Manual Mongolia HSES 2012 Version 2.0

60.. ..- attr(*, "names")= chr "***Undefined Label"..$ q0106: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "MARRIED" "LIVING TOGETHER" "SEPARATED" "DIVORCED" ...
..$ q0103 : Named int 1 2.. ..- attr(*, "names")= chr "MALE" "FEMALE"..$ q0102: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "HEAD" "WIFE / HUSBAND" "SON / DAUGHTER" "FATHER / MOTHER" ...
..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 47908 129
NULL## 3 #### Llivestock #########'data.frame': 14498 obs. of 15 variables:$ identif: int 1 1 1 1 2 2 2 2 3 3 ...
$ ani_id: int 1 2 4 5 1 2 4 5 1 2 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 4 4 3 3 3 3 4 4 ...
$ q0702_1: int 41 12 60 80 60 40 160 120 8 8 ...
$ q0702_2: int 12 4 30 50 19 11 56 30 4 3 ...
$ q0702_3: int 8 1 20 30 11 5 46 16 4 2 ...
$ q0703: int 1 0 10 10 1 1 5 5 1 1 ...
$ q0704: int 0 0 0 0 0 0 20 0 1 0 ...
$ q0705: int 0 0 0 0 0 0 1400000 0 500000 0 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:22"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 252 252 252 252 ...
- attr(*, "val.labels")= Named chr "" "ani_id" "" "aimag" ...
..- attr(*, "names")= chr "" "ani_id" "" "aimag" ...
- attr(*, "var.labels")= chr "group(identif)" "animal" "Cluster" "2. Aimag" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 3..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
..$ ani_id : Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "Cattle" "Horses" "Camels" "Sheep" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 14498 15
NULL## 4 #### Livestock Expenditure#########

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61'data.frame':
9011 obs. of 10 variables:$ identif: int 1 1 2 2 2 3 3 5 5 6 ...
$ exp_id: int 1 2 1 2 3 1 2 1 2 1 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 3 3 3 4 4 4 4 4 ...
$ q0706: int 50000 50000 40000 110000 240000 30000 50000 100000 60000 40000 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:22"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 253 251 251 251- attr(*, "val.labels")= Named chr "" "exp_id" "" "aimag" ...
..- attr(*, "names")= chr "" "exp_id" "" "aimag" ...
- attr(*, "var.labels")= chr "group(identif)" "ani_exp" "Cluster" "2. Aimag" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 3..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
..$ exp_id : Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "Animal Feed" "Drugs and veterinary costs" "Gassoline/ Oil" "Taxes
and Insurance" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 9011 10
NULL## 5 #### Product #########'data.frame': 74050 obs. of 16 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ byprod_id : int 1 2 3 4 5 6 7 8 9 10 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 4 4 4 4 4 4 4 4 ...
$ q0708: int 60 0 80 0 NA NA NA NA NA 0 ...
$ q0709: num 60 NA 16 NA 10 10 1 0 0 NA ...
$ q0710: num 0 NA 0 NA 0 0 0 NA NA NA ...
$ q0711: num 60 NA 16 NA 10 10 1 NA NA NA ...
$ q0712: int 42000 NA 1120000 NA 50000 70000 22000 NA NA NA ...
$ q0713: num 0 NA 0 NA 0 0 0 NA NA NA ...
$ q0714: int 0 NA 0 NA 0 0 0 NA NA NA ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:22"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 252 255 255 255 ...
- attr(*, "val.labels")= Named chr "" "byprod_id" "" "aimag" ...

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62..- attr(*, "names")= chr "" "byprod_id" "" "aimag" ...
- attr(*, "var.labels")= chr "group(identif)" "byprod" "Cluster" "2. Aimag" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 3..$ location : Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag: Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
..$ byprod_id: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "Goat cashmere, kg" "Wool, hair, cashmere, kg" "Skins andhides, pieces " "Milk, airag, liters" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 74050 16
NULL## 6 #### Crop #########'data.frame':
2353 obs. of 15 variables:$ identif: int 12 12 12 12 23 50 51 55 55 55 ...
$ crop_id: int 1 3 4 6 1 1 1 1 2 4 ...
$ cluster: int 6 6 6 6 11 28 28 28 28 28 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 40 40 40 40 40 ...
$ location: int 3 3 3 3 3 3 3 3 3 3 ...
$ q0719: int 1 1 1 1 1 1 1 1 1 1 ...
$ q0720: num 500 50 30 25 100 2000 300 600 100 800 ...
$ q0721: num 100 10 10 5 100 500 300 400 20 300 ...
$ q0722: int 0 0 0 0 0 0 0 0 0 0 ...
$ q0723q: int 400 40 20 20 0 1500 0 200 80 500 ...
$ q0723t: int 200000 24000 16000 20000 0 900000 0 90000 48000 400000 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 2 2 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:23"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 251 255 255 253 ...
- attr(*, "val.labels")= Named chr "" "crop_id" "" "aimag" ...
..- attr(*, "names")= chr "" "crop_id" "" "aimag" ...
- attr(*, "var.labels")= chr "group(identif)" "crop" "Cluster" "2. Aimag" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 4..$ q0719 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
..$ crop_id : Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "Potatoes" "Carrots" "Turnip" "Cabbage" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 2353 15
NULL

Manual Mongolia HSES 2012 Version 2.0

63## 7 #### Agriultural Expenditure #########'data.frame': 11518 obs. of 10 variables:$ identif: int 12 12 12 12 12 12 12 12 12 12 ...
$ exp_id: int 1 2 3 4 5 6 7 8 9 10 ...
$ cluster: int 6 6 6 6 6 6 6 6 6 6 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location : int 3 3 3 3 3 3 3 3 3 3 ...
$ q0724: int 60000 0 0 0 0 0 0 0 0 0 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:23"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 253 251 251 251- attr(*, "val.labels")= Named chr "" "exp_id" "" "aimag" ...
..- attr(*, "names")= chr "" "exp_id" "" "aimag" ...
- attr(*, "var.labels")= chr "group(identif)" "exp" "Cluster" "2. Aimag" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 3..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
..$ exp_id : Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr"Seeds" "Fertilizers" "Extermination of vermin" "Wages &salaries" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 11518 10
NULL## 8 #### Enterprise #########'data.frame':
2342 obs. of 31 variables:$ identif: int 14 28 40 42 50 53 81 99 106 115 ...
$ en: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 25 25 25 40 40 52 1 1 1 ...
$ location: int 3 3 3 4 3 3 3 2 2 2 ...
$ q0803: num 3600 4520 1622 1430 4721 ...
$ q0804: int 100 100 100 100 100 100 100 100 100 100 ...
$ q0805: int 1 1 2 1 0 1 1 2 2 1 ...
$ q0806: int 0 0 0 0 1 1 0 0 0 0 ...
$ q0807_01: int 0 0 0 0 1684800 1296000 0 0 0 0 ...
$ q0807_02 : int 0 0 0 0 13000000 20000000 0 6000000 6000000 0 ...
$ q0807_03 : int 0 250000 1400000 300000 0 0 0 0 0 0 ...
$ q0807_04 : int 0 0 0 0 400000 1200000 3600000 0 0 1250000 ...
$ q0807_05 : int 100000 150000 50000 0 120000 200000 0 0 0 0 ...
$ q0807_06: int 0 0 0 0 0 0 0 0 0 0 ...
$ q0807_07: int 0 0 0 0 0 0 0 960000 0 0 ...
$ q0807_08: int 0 0 0 0 0 0 200000 0 0 160000 ...
$ q0807_09: int 0 0 0 0 0 0 150000 0 0 30000 ...
$ q0807_10 : int 0 0 0 0 180000 1000000 100000 48000 70000 0 ...

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64$ q0807_11: int 0 0 0 0 0 0 0 600000 2400000 0 ...
$ q0807_99: int 100000 400000 1450000 300000 15384800 23696000 4050000 7608000 8470000
1440000 ...
$ q0808: int 12 6 9 9 12 12 7 12 12 4 ...
$ q0809_1a: int 60000 300000 300000 75000 1400000 2000000 840000 1500000 800000 1000000 ...
$ q0809_1b: int 4 2 3 3 4 4 2 3 4 1 ...
$ q0809_2a: int 40000 150000 200000 45000 1300000 1500000 560000 900000 700000 600000 ...
$ q0809_2b: int 4 2 3 2 4 4 2 6 4 1 ...
$ q0809_3a : int 70000 450000 500000 90000 1600000 4000000 1120000 2000000 1200000 1350000 ...
$ q0809_3b: int 4 2 3 4 4 4 3 3 4 2 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 1 1 1 2 3 1 2 2 2 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:24"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 251 251 251 255 251 251 251 253 ...
- attr(*, "val.labels")= Named chr "" "" "aimag" "" ...
..- attr(*, "names")= chr "" "" "aimag" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Enterprise Number (1-2-3)" "2. Aimag" "3.Soum" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 2..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 2342 31
NULL## 9 #### Other income #########'data.frame':
333086 obs. of 20 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ income_id : int 1 2 3 4 5 6 7 8 9 10 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 4 4 4 4 4 4 4 4 ...
$ q0901: int 2 2 2 2 2 2 2 2 1 2 ...
$ q0902_ic : int NA NA NA NA NA NA NA NA 1 NA ...
$ q0902_t: int NA NA NA NA NA NA NA NA 252000 NA ...
$ q0903_ic : int NA NA NA NA NA NA NA NA 2 NA ...
$ q0903_t: int NA NA NA NA NA NA NA NA 252000 NA ...
$ q0904_ic : int NA NA NA NA NA NA NA NA 0 NA ...
$ q0904_t: int NA NA NA NA NA NA NA NA NA NA ...
$ q0905_ic : int NA NA NA NA NA NA NA NA NA NA ...
$ q0905_t: int NA NA NA NA NA NA NA NA NA NA ...
$ q0906_ic : int NA NA NA NA NA NA NA NA NA NA ...
$ q0906_t: int NA NA NA NA NA NA NA NA NA NA ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:27"

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65- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 251 251 253 251 ...
- attr(*, "val.labels")= Named chr "" "income_id" "" "aimag" ...
..- attr(*, "names")= chr "" "income_id" "" "aimag" ...
- attr(*, "var.labels")= chr "group(identif)" "income" "Cluster" "2. Aimag" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 4..$ q0901: Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ location : Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag: Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
..$ income_id: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "State pension" "Special Pension" "Unemployment benefit" "Maternity
benefits" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 333086 20
NULL## 10 #### Remittance #########'data.frame':
3670 obs. of 17 variables:$ identif: int 13 160 167 176 186 189 191 192 214 216 ...
$ ln: int 1 1 1 1 1 1 1 1 1 1 ...
$ cluster: int 6 77 80 85 87 87 94 94 99 99 ...
$ aimag: int 65 83 83 83 83 83 83 83 83 83 ...
$ soum: int 13 25 25 37 37 37 37 37 1 1 ...
$ location: int 3 3 3 4 4 4 4 3 2 2 ...
$ ind_id: int 1 1 1 5 1 1 1 1 1 2 ...
$ q0909: int 4 4 4 1 1 1 4 4 1 7 ...
$ q0910: int 1 8 1 1 1 1 1 1 1 1 ...
$ q0911: int 1 4 4 3 3 3 3 1 2 2 ...
$ q0912: int NA NA NA NA NA NA NA NA NA NA ...
$ q0913: int 300000 1200000 50000 140000 100000 15000 50000 500000 140000 140000 ...
$ q0914: int 3 5 4 4 5 5 5 5 4 4 ...
$ q0915: int 1 1 4 1 4 4 4 4 2 1 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 2 3 3 2 2 3 3 1 1 ...
$ supervisor : int 65 83 83 83 83 83 83 83 83 83 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:29"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= Named chr "" "" "" "aimag" ...
..- attr(*, "names")= chr "" "" "" "aimag" ...
- attr(*, "var.labels")= chr "group(identif)" "Line Number" "Cluster" "2. Aimag" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 6..$ q0914: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "YES, weekly " "YES, monthly " "YES, quarterly " "YES, annualy " ...
..$ q0911: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "Capital city" "Aimag center" "Soum center" "Countryside" ...
..$ q0910: Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "HOUSEHOLD USE" "EDUCATION8 TUITION FEE" "MEDICAL TREATMENT"Manual Mongolia HSES 2012 Version 2.0

66"PURCHASE OF DWELLING" ...
..$ q0909: Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "GOVERNMENT" "COMPANIES AND ORGANIZATIONS" "NGOs" "PARENTS,
CHILDREN, RELATIVES" ...
..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 3670 17
NULL## 11 #### Savings loan #########'data.frame':
6305 obs. of 19 variables:$ identif: int 2 6 8 9 11 18 19 20 21 22 ...
$ cluster: int 1 1 1 6 6 11 11 11 11 11 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 3 4 4 3 3 3 3 3 3 3 ...
$ loan_id: int 1 1 1 1 1 1 1 1 1 1 ...
$ q1005: int 1 5 5 7 7 2 2 7 2 8 ...
$ q1006: int 1 1 1 1 1 1 1 1 1 1 ...
$ q1007: int 3000000 700000 2700000 1200000 1200000 600000 315000 200000 1800000 5000000 ...
$ q1008: int 1 1 1 1 1 1 1 1 1 1 ...
$ q1009: int 1 1 2 1 1 1 1 1 1 1 ...
$ q1010a: int 2 1 2 4 4 1 1 5 1 2 ...
$ q1010b: int NA NA NA NA NA NA NA NA NA NA ...
$ q1010c: int NA NA NA NA NA NA NA NA NA NA ...
$ q1011: int 250000 0 120000 67500 80100 170000 65000 40000 105000 319000 ...
$ q1012: int 1500000 0 980000 540000 320400 340000 135000 40000 105000 638000 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 2 2 2 2 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:30"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 251 251 251 251 251 253 251 ...
- attr(*, "val.labels")= Named chr "" "" "aimag" "" ...
..- attr(*, "names")= chr "" "" "aimag" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Cluster" "2. Aimag" "3. Soum" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 9..$ q1010c : Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "HH expenses" "Buy the car" "Business" "Buy the land" ...
..$ q1010b : Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "HH expenses" "Buy the car" "Business" "Buy the land" ...
..$ q1010a : Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "HH expenses" "Buy the car" "Business" "Buy the land" ...
..$ q1009: Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "Bank" "Non bank financial institution" "Savings and credit
cooperatives" "Employer or organization" ...
..$ q1008 : Named int 1 2 3.. ..- attr(*, "names")= chr "Yes " "No " "Don't know"..$ q1006 : Named int 1 2

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67.. ..- attr(*, "names")= chr "Yes" "No"..$ q1005: Named int 1 2 3 4 5 6 7 8 9.. ..- attr(*, "names")= chr "Salary loan" "Retirement loan" "Mortgage loan" "Consumer loan" ...
..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 6305 19
NULL## 12 #### Energy #########'data.frame':
115299 obs. of 15 variables:$ identif: int 1 1 1 1 1 1 1 1 1 2 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 4 4 4 4 4 4 4 3 ...
$ energy_id : int 1 2 3 4 5 6 7 8 9 1 ...
$ q1136: int 2 1 2 2 2 2 2 2 2 1 ...
$ q1137: int NA 1 NA NA NA NA NA NA NA NA ...
$ q1138: num NA 10 NA NA NA NA NA NA NA NA ...
$ q1139: int NA 0 NA NA NA NA NA NA NA 10000 ...
$ q1140: int NA 60000 NA NA NA NA NA NA NA 120000 ...
$ q1141: int NA 0 NA NA NA NA NA NA NA 0 ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:30"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 251 251 251 251 251 255 253 ...
- attr(*, "val.labels")= Named chr "" "" "aimag" "" ...
..- attr(*, "names")= chr "" "" "aimag" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Cluster" "2. Aimag" "3. Soum" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 5..$ q1137: Named int 1 2 3 4.. ..- attr(*, "names")= chr "aaDNAaa AYEOAYAYA" "OOAAEAAA AAAAA" "AYEOAYAYA, OOAAEAAA AAAAA""AONAA"..$ q1136: Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ energy_id: Named int 1 2 3 4 5 6 7 8 9.. ..- attr(*, "names")= chr "Electricity" "Firewood, m3" "Firewood, bag" "Coal, ton" ...
..$ location : Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag: Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 115299 15
NULL

Manual Mongolia HSES 2012 Version 2.0

68## 13 #### Payment service #########'data.frame':
166543 obs. of 13 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 4 4 4 4 4 4 4 4 ...
$ item: int 1 2 3 4 5 6 7 8 9 10 ...
$ q1142: int 2 2 2 2 2 2 2 2 2 2 ...
$ q1143: int NA NA NA NA NA NA NA NA NA NA ...
$ q1144: num NA NA NA NA NA NA NA NA NA NA ...
$ q1145: int NA NA NA NA NA NA NA NA NA NA ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:32"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 251 251 251 251 253 255 253 ...
- attr(*, "val.labels")= Named chr "" "" "aimag" "" ...
..- attr(*, "names")= chr "" "" "aimag" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Cluster" "2. Aimag" "3. Soum" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 4..$ q1142 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ item: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "Heating fees" "Water use fees" "Hot water fees" "Dirty water" ...
..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 166543 13
NULL## 14 #### Durable #########'data.frame':
563684 obs. of 12 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 4 4 4 4 4 4 4 4 ...
$ durable_id : int 1 2 3 4 5 6 7 8 9 10 ...
$ q1201: int 0 0 0 0 0 0 1 0 0 0 ...
$ q1202: int NA NA NA NA NA NA 48 NA NA NA ...
$ q1203: int NA NA NA NA NA NA 300000 NA NA NA ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:36"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 251 251 251 251 252 253 251 ...

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69- attr(*, "val.labels")= Named chr "" "" "aimag" "" ...
..- attr(*, "names")= chr "" "" "aimag" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Cluster" "2. Aimag" "3. Soum" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 3..$ durable_id: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr"Refrigerator" "Vacuum Cleaner" "Washing machine" "Sewing
machine" ...
..$ location : Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag: Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 563684 12
NULL## 15 #### Non-Food #########'data.frame': 4624771 obs. of 15 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ row13: int 2 3 4 5 6 7 8 9 10 11 ...
$ item: int 20101 20102 20103 20104 20105 20106 20107 20108 20109 20110 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 4 4 4 4 4 4 4 4 ...
$ q1301: int 2 2 1 2 2 1 2 2 2 2 ...
$ q1302: int NA NA 0 NA NA 0 NA NA NA NA ...
$ q1303: int NA NA 45000 NA NA 20000 NA NA NA NA ...
$ q1304: int NA NA 0 NA NA 0 NA NA NA NA ...
$ q1305: int NA NA 0 NA NA 0 NA NA NA NA ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:11"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 252 252 251 251 251 251 253 253 ...
- attr(*, "val.labels")= Named chr "" "" "item" "" ...
..- attr(*, "names")= chr "" "" "item" "" ...
- attr(*, "var.labels")= chr "group(identif)" "IA" "Non-food Item code" "Cluster" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 4..$ q1301 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
..$ item: Named int 20101 20102 20103 20104 20105 20106 20107 20108 20109 20110 ...
.. ..- attr(*, "names")= chr "Men: Leather jacket, deel" "Men: Winter jacket, winter deel" "Men: Overcoat" "Men: Other leather jacket, winter jacke " ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 4624771 15

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70

NULL

## 16 #### Urban Diary #########'data.frame':
867273 obs. of 23 variables:$ identif: int 97 97 97 97 97 97 97 97 97 97 ...
$ cluster: int 54 54 54 54 54 54 54 54 54 54 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 1 1 1 1 1 1 1 1 1 1 ...
$ location: int 2 2 2 2 2 2 2 2 2 2 ...
$ row14: int 2 3 4 5 6 7 8 9 10 11 ...
$ item: int 10101 10102 10103 10104 10105 10106 10107 10108 10109 10110 ...
$ q1401_1: num 4 0.9 NA 2.8 NA ...
$ q1401_2: num 4 0.9 NA 2.8 NA ...
$ q1401_3: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1401_4: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1402_1: num 5 1 NA 3 NA NA NA NA 2.5 NA ...
$ q1402_2: num 5 1 NA 3 NA NA NA NA 2.5 NA ...
$ q1402_3: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1402_4: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1403_1: num 6 2 NA 4 NA NA NA NA 2 NA ...
$ q1403_2: num 6 2 NA 4 NA NA NA NA 2 NA ...
$ q1403_3: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1403_4: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1404: num 600 1800 NA 900 NA NA NA NA 2300 NA ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 2 2 2 2 2 2 2 2 2 2 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:57"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 251 251 252 252 255 255 255 ...
- attr(*, "val.labels")= Named chr "" "" "aimag" "" ...
..- attr(*, "names")= chr "" "" "aimag" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Cluster" "2. Aimag" "3. Soum" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 2..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 867273 23
NULL## 17 #### Rural Food 7 day #########'data.frame':
708480 obs. of 16 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ row15: int 2 3 4 5 6 7 8 9 10 11 ...
$ item: int 10101 10102 10103 10104 10105 10106 10107 10108 10109 10110 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 4 4 4 4 4 4 4 4 ...

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71$ q1501: num 2 1 2 1 2 2 2 2 2 2 ...
$ q1502: num NA 1 NA 8 NA NA NA NA NA NA ...
$ q1503: num NA 1 NA 8 NA NA NA NA NA NA ...
$ q1504: num NA 1800 NA 700 NA NA NA NA NA NA ...
$ q1505: num NA 0 NA 0 NA NA NA NA NA NA ...
$ q1506: num NA 0 NA 0 NA NA NA NA NA NA ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:11"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 252 252 251 251 251 255 255 255 ...
- attr(*, "val.labels")= Named chr "" "" "item" "" ...
..- attr(*, "names")= chr "" "" "item" "" ...
- attr(*, "var.labels")= chr "group(identif)" "" "Item Code" "Cluster" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 3..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
..$ item: Named int 10101 10102 10103 10104 10105 10106 10107 10108 10109 10110 ...
.. ..- attr(*, "names")= chr "Bread (1 piece = 670 gr) - piece " "Rice - Kg " "Flour, highest
grade - Kg " "Flour, grade 1 - Kg " ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 708480 16
NULL## 18 #### Foodstuffs #########'data.frame': 12811 obs. of 17 variables:$ identif: int 1 2 3 4 5 6 7 8 9 10 ...
$ cluster: int 1 1 1 1 1 1 1 1 6 6 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 3 4 3 4 4 3 4 3 3 ...
$ q1601: int 1 1 1 1 1 1 2 1 2 2 ...
$ q1602: int 2 2 2 2 2 2 NA 2 NA NA ...
$ q1603y: int NA NA NA NA NA NA NA NA NA NA ...
$ q1603m: int NA NA NA NA NA NA NA NA NA NA ...
$ q1603d: int NA NA NA NA NA NA NA NA NA NA ...
$ q1604: int NA NA NA NA NA NA NA NA NA NA ...
$ q1605: int NA NA NA NA NA NA NA NA NA NA ...
$ q1606: int NA NA NA NA NA NA NA NA NA NA ...
$ q1607: int NA NA NA NA NA NA NA NA NA NA ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:16"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 251 251 251 251 252 251 251 ...
- attr(*, "val.labels")= Named chr "" "" "aimag" "" ...
..- attr(*, "names")= chr "" "" "aimag" "" ...

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72- attr(*, "var.labels")= chr "group(identif)" "Cluster" "2. Aimag" "3. Soum" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 7..$ q1607 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q1606 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q1605 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q1602 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ q1601 : Named int 1 2.. ..- attr(*, "names")= chr "OEEI" "￣A￣E"..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 12811 17
NULL## 19 #### Foodout #########'data.frame': 25578 obs. of 12 variables:$ identif: int 1 1 2 2 3 3 4 4 5 5 ...
$ cluster: int 1 1 1 1 1 1 1 1 1 1 ...
$ aimag: int 65 65 65 65 65 65 65 65 65 65 ...
$ soum: int 13 13 13 13 13 13 13 13 13 13 ...
$ location: int 4 4 3 3 4 4 3 3 4 4 ...
$ item: int 22501 22502 22502 22501 22501 22502 22501 22502 22501 22502 ...
$ q1507: int 2 2 2 2 2 2 2 2 2 2 ...
$ q1508: int NA NA NA NA NA NA NA NA NA NA ...
$ q1509: int NA NA NA NA NA NA NA NA NA NA ...
$ quarter: int 1 1 1 1 1 1 1 1 1 1 ...
$ interviewer: int 3 3 3 3 3 3 3 3 3 3 ...
$ supervisor : int 65 65 65 65 65 65 65 65 65 65 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:17"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 251 251 252 251 253 253 251 ...
- attr(*, "val.labels")= Named chr "" "" "aimag" "" ...
..- attr(*, "names")= chr "" "" "aimag" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Cluster" "2. Aimag" "3. Soum" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 4..$ q1507 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ item: Named int 22501 22502.. ..- attr(*, "names")= chr "Restaurants, cafes" "Canteens in schools, works canteens"..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Capital" "Aimag center" "Soum center" "Rural"..$ aimag : Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar (11)" "Dornod (21)" "Suhbaatar (22)" "Hentii (23)" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2

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73- attr(*, "orig.dim")= int 25578 12
NULL## 20 #### Basicvars #########'data.frame': 12811 obs. of 12 variables:$ identif : int 1 2 3 4 5 6 7 8 9 10 ...
$ cluster : int 1 1 1 1 1 1 1 1 6 6 ...
$ newaimag : int 65 65 65 65 65 65 65 65 65 65 ...
$ location : int 4 4 4 4 4 4 4 4 4 4 ...
$ urban: int 2 2 2 2 2 2 2 2 2 2 ...
$ region: int 2 2 2 2 2 2 2 2 2 2 ...
$ month: int 3 3 3 3 3 3 3 3 1 1 ...
$ quarter : int 1 1 1 1 1 1 1 1 1 1 ...
$ strata: int 3 3 3 3 3 3 3 3 3 3 ...
$ hhweight : num 65 65 65 65 65 ...
$ hhsize : int 3 4 3 4 5 6 8 4 5 6 ...
$ aimagsoum: int 63 63 63 63 63 63 63 63 63 63 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:17"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 251 251 251 251 251 251 255 ...
- attr(*, "val.labels")= Named chr "" "" "newaimag" "location" ...
..- attr(*, "names")= chr "" "" "newaimag" "location" ...
- attr(*, "var.labels")= chr"group(identif)" "Cluster" "New code of aimag" "Strata 4locations" ...
- attr(*, "version")= int 113- attr(*, "label.table")=List of 4..$ region : Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "West" "Highlands" "Central" "East" ...
..$ urban : Named int 1 2.. ..- attr(*, "names")= chr "Urban" "Rural"..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Ulaanbaatar" "Aimagcenter" "Soumcenter" "Countryside"..$ newaimag: Named int 11 21 22 23 41 42 43 44 45 46 ...
.. ..- attr(*, "names")= chr "Ulaanbaatar" "Dornod" "Sukhbaatar" "Khentii" ...
- attr(*, "expansion.fields")= list()- attr(*, "byteorder")= int 2- attr(*, "orig.dim")= int 12811 12
NULL

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74

5.2 Summary of each variable> for(j in 1:20){+ cat("##",j,"#### ",Rnames[j]," #########\n")+ print(summary(outfiles[[j]]))+ cat("\n\n")+ }## 1 #### Household #########
identifyear
quarterMin. :
1 Min. :12 Min. :1.000
1st Qu.: 3204 1st Qu.:12 1st Qu.:2.000
Median : 6406 Median :12 Median :3.000
Mean : 6406 Mean :12 Mean :2.562
3rd Qu.: 9608 3rd Qu.:12 3rd Qu.:4.000
Max. :12811 Max. :12 Max. :4.000

clusterMin. : 1.0
1st Qu.: 374.0
Median : 754.0
Mean : 733.7
3rd Qu.:1088.0
Max. :1428.0

aimag
Min.
:11.0
1st Qu.:11.0
Median :45.0
Mean :44.1
3rd Qu.:65.0
Max. :85.0

soum
Min.
: 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.87
3rd Qu.:25.00
Max. :76.00

locationMin.
:1.00
1st Qu.:1.00
Median :2.00
Mean :2.38
3rd Qu.:3.00
Max. :4.00

interviewer
Min.
: 1.00
1st Qu.: 1.00
Median : 2.00
Mean : 6.51
3rd Qu.: 5.00
Max. :34.00

supervisor
Min. : 1.00
1st Qu.: 3.00
Median :45.00
Mean :41.58
3rd Qu.:65.00
Max. :85.00

operator
Min. : 1.00
1st Qu.: 2.00
Median :45.00
Mean :41.21
3rd Qu.:65.00
Max. :85.00

q0008
Min. : 1.000
1st Qu.: 3.000
Median : 4.000
Mean : 3.667
3rd Qu.: 5.000
Max. :15.000

hh_noMin. : 1.000
1st Qu.: 3.000
Median : 6.000
Mean : 5.757
3rd Qu.: 8.000
Max. :13.000

q0009
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean :1.331
3rd Qu.:1.000
Max.
:3.000q0010
Min.
:1.000
1st Qu.:1.000
Median :3.000
Mean :2.559
3rd Qu.:4.000
Max.
:8.000v1_dd
Min.
: 1.00
1st Qu.: 1.00
Median : 8.00
Mean :11.49
3rd Qu.:22.00
Max.
:31.00v1_mm
Min.
: 1.000
1st Qu.: 4.000
Median : 7.000
Mean : 6.671
3rd Qu.:10.000
Max.
:12.000

v1_yy
Min. :12
1st Qu.:12
Median :12
Mean :12
3rd Qu.:12
Max. :12v2_yyMin. :12
1st Qu.:12
Median :12
Mean :12
3rd Qu.:12
Max. :12

v1_resMin. :1.000
1st Qu.:1.000
Median :1.000
Mean :1.555
3rd Qu.:2.000
Max. :7.000

v2_dd
v2_mm
Min. : 1.00 Min. : 1.000
1st Qu.:10.00 1st Qu.: 4.000
Median :11.00 Median : 7.000
Mean :11.36 Mean : 6.682
3rd Qu.:11.00 3rd Qu.:10.000
Max. :31.00 Max. :12.000
NA's :5745
NA's :5745
v2_resv3_dd
v3_mmMin. :1.000 Min. : 1.00 Min. : 1.000
1st Qu.:2.000 1st Qu.:20.00 1st Qu.: 4.000
Median :2.000 Median :21.00 Median : 7.000
Mean :1.963 Mean :20.33 Mean : 6.684
3rd Qu.:2.000 3rd Qu.:21.00 3rd Qu.:10.000
Max. :7.000 Max. :31.00 Max. :12.000

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75

NA's :5745
v3_yy
Min.
:12
1st Qu.:12
Median :12Mean:12
3rd Qu.:12
Max.
:13
NA's
:5768
v4_yy
Min. :12.00
1st Qu.:12.00
Median :12.00
Mean :12.02
3rd Qu.:12.00
Max. :13.00
NA's :6971
q0715
Min. :1.000
1st Qu.:2.000
Median :2.000
Mean :1.925
3rd Qu.:2.000
Max. :2.000:5745
NA's :5768
NA's :5768
v3_res
v4_dd
v4_mm
Min.
:1.000
Min.
: 1.0
Min.
: 1.000
1st Qu.:1.000 1st Qu.:22.0
1st Qu.: 4.000
Median :2.000
Median :29.0
Median : 7.000
Mean:1.779
Mean
:23.5
Mean
: 6.706
3rd Qu.:2.000 3rd Qu.:30.0
3rd Qu.:10.000
Max.
:6.000
Max.
:31.0
Max.
:12.000
NA's
:5768
NA's
:6971
NA's
:6971
v4_resq0701
q0707
Min. :1.000 Min. :1.000
Min. :1.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:1.000
Median :1.000 Median :2.000
Median :1.000
Mean :1.044 Mean :1.634
Mean :1.072
3rd Qu.:1.000
3rd Qu.:2.000
3rd Qu.:1.000
Max. :4.000 Max. :2.000
Max. :2.000
NA's :6971
NA's :8118
q0716
q0717
q0718
Min. :
10 Min. :1.000 Min. :10.0
1st Qu.:100
1st Qu.:1.000
1st Qu.:84.2
Median :500 Median :1.000 Median :425.0
Mean : 11136 Mean :1.077 Mean : 8583.4
3rd Qu.:2602
3rd Qu.:1.000
3rd Qu.:2000.0Max. :1500000 Max. :2.000 Max. :1500000.0
NA's :11851
NA's :11851 NA's :11925
q0801
q0802
q0907
q1001
Min. :1.000 Min. :1.000 Min. :1.00 Min. :1.000
1st Qu.:2.000
1st Qu.:1.000
1st Qu.:2.00
1st Qu.:2.000
Median :2.000 Median :1.000 Median :2.00 Median :2.000
Mean :1.836 Mean :1.116 Mean :1.81 Mean :1.763
3rd Qu.:2.000
3rd Qu.:1.000
3rd Qu.:2.00
3rd Qu.:2.000
Max. :2.000 Max. :3.000 Max. :2.00 Max. :2.000
NA's :10708
q1002
q1003
q1004
visitorMin. :
0 Min. :1.000 Min. :1.000 Min. : 0.0000
1st Qu.: 75500 1st Qu.:1.000 1st Qu.:1.000 1st Qu.: 0.0000
Median : 300000 Median :2.000 Median :1.000
Median : 0.0000
Mean : 1338806 Mean :1.562 Mean :1.133 Mean : 0.4958
3rd Qu.: 1000000 3rd Qu.:2.000 3rd Qu.:1.000
3rd Qu.: 0.0000
Max.
:90000000
Max.
:2.000Max.
:5.000Max.
:50.0000
NA's :9780
NA's :7204
ndays
q1101
q1102
q1103
Min. : 0.000 Min. :0.000 Min. :1.00 Min. :1.00
1st Qu.: 0.000
1st Qu.:1.000
1st Qu.:1.00
1st Qu.:1.00
Median : 0.000 Median :1.000 Median :1.00 Median :2.00
Mean : 3.657 Mean :1.129 Mean :1.07 Mean :2.33
3rd Qu.: 0.000
3rd Qu.:1.000
3rd Qu.:1.00
3rd Qu.:4.00
Max. :200.000 Max. :5.000 Max. :2.00 Max. :9.00
q1104
Min. : 1.000
1st Qu.: 1.000
Median : 2.000
Mean : 1.822
3rd Qu.: 2.000
Max.
:11.000

NA's

q1105
Min.
:1.000
1st Qu.:1.000
Median :2.000
Mean :2.234
3rd Qu.:3.000
Max.
:5.000q1106
Min.
:1.000
1st Qu.:1.000
Median :2.000
Mean :1.762
3rd Qu.:2.000
Max.
:4.000q1107
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean :1.424
3rd Qu.:2.000
Max.
:4.000Manual Mongolia HSES 2012 Version 2.0

76

NA's :6001
q1108
Min.
: 4.00
1st Qu.: 24.00
Median : 32.00
Mean : 37.52
3rd Qu.: 47.00
Max.
:360.00
NA's :6001
q1112
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :1.724
3rd Qu.:2.000
Max. :2.000
NA's :6867
q1116
Min. : 0.00
1st Qu.: 4.00
Median :10.00
Mean :12.95
3rd Qu.:20.00
Max. :99.00

NA's

:6001
NA's :6001
NA's :6001
q1109
q1110
q1111
Min.
: 6.00Min.
: 4.00Min.
:3.000
1st Qu.: 30.00
1st Qu.: 10.00
1st Qu.:4.000
Median : 42.00 Median : 20.00 Median :5.000
Mean : 47.41 Mean : 32.14 Mean :4.974
3rd Qu.: 56.00
3rd Qu.: 30.00
3rd Qu.:5.000Max.
:360.00Max.
:394.00
Max.
:8.000NA's :6001
NA's :12754
NA's :6867
q1113
q1114
q1115
Min. :1.000 Min. :1.000
Min. : 0.00
1st Qu.:1.000
1st Qu.:1.000
1st Qu.: 7.00
Median :2.000 Median :2.000
Median :20.00
Mean :1.725 Mean :1.549
Mean :34.97
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:49.00
Max. :2.000 Max. :3.000
Max. :99.00
NA's :6867
NA's :6867
q1117
q1118
q1119
Min. :1.000 Min. :1.000
Min. :1.000
1st Qu.:3.000
1st Qu.:4.000
1st Qu.:2.000
Median :3.000
Median :4.000
Median :2.000
Mean :2.953 Mean :4.117
Mean :1.886
3rd Qu.:3.000
3rd Qu.:5.000
3rd Qu.:2.000
Max. :3.000 Max. :7.000
Max. :2.000
NA's :383
NA's :3144
q1120
q1121
q1122
q1123
Min. :
99 Min. :0 Min. :1.000 Min. :1.00
1st Qu.:99
1st Qu.: 54000
1st Qu.:4.000
1st Qu.:1.00
Median :99 Median : 150000 Median :4.000 Median :1.00
Mean : 28969 Mean : 197224 Mean :3.317 Mean :1.42
3rd Qu.:99
3rd Qu.: 300000
3rd Qu.:4.000
3rd Qu.:1.00
Max.
:3125000
Max.
:1500000
Max.
:5.000Max.
:7.00
NA's :390
NA's :12421
q1124
q1125
q1126
q1127
Min. :1.000 Min. :1.000 Min. :1.000
Min. :1.000
1st Qu.:1.000
1st Qu.:3.000
1st Qu.:3.000
1st Qu.:1.000
Median :1.000 Median :3.000 Median :3.000
Median :1.000
Mean :1.127 Mean :3.592 Mean :2.856
Mean :1.727
3rd Qu.:1.000
3rd Qu.:5.000
3rd Qu.:4.000
3rd Qu.:2.000
Max. :2.000 Max. :8.000 Max. :4.000
Max. :4.000

q1128
Min. :1.000
1st Qu.:3.000
Median :3.000
Mean :2.711
3rd Qu.:3.000
Max. :4.000

q1129
Min. :1.000
1st Qu.:2.000
Median :2.000
Mean :2.101
3rd Qu.:2.000
Max. :4.000

q1130_3
Min. : 0.000
1st Qu.: 0.300
Median : 1.000
Mean : 6.065
3rd Qu.: 2.000
Max. :160.000

q1130_1
Min. : 0.000
1st Qu.: 0.500
Median : 1.000
Mean : 6.441
3rd Qu.: 2.500
Max. :160.000

q1130_4
Min. : 0.000
1st Qu.: 0.100
Median : 0.300
Mean : 1.232
3rd Qu.: 0.800
Max. :100.000

q1131
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :1.567
3rd Qu.:2.000
Max. :2.000

q1130_2
Min.
: 0.000
1st Qu.: 0.500
Median : 1.000
Mean : 6.237
3rd Qu.: 3.000
Max. :160.000
q1132aMin. :
0.0
1st Qu.: 350.0
Median : 700.0
Mean: 669.4
3rd Qu.: 700.0
Max. :50000.0

Manual Mongolia HSES 2012 Version 2.0

77

q1134
Min. :0.000
1st Qu.:1.000
Median :2.000
Mean:2.0143rd Qu.:3.000
Max.
:7.000NA's :9562
q1135_4
Min. :1.000
1st Qu.:2.000
Median :2.000
Mean :1.791
3rd Qu.:2.000
Max. :2.000
NA's :9562

NA's
:7269
q1135_1
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean:1.555
3rd Qu.:2.000
Max.
:2.000NA's :9562
q1135_5
Min. :1.000
1st Qu.:2.000
Median :2.000
Mean :1.929
3rd Qu.:2.000
Max. :2.000
NA's
:9562

## 2 #### Individual #########
identif
ind_idMin. :
1 Min. : 1.000
1st Qu.: 3157 1st Qu.: 1.000
Median : 6349 Median : 2.000
Mean : 6392 Mean : 2.732
3rd Qu.: 9587 3rd Qu.: 4.000
Max. :12811 Max. :15.000

clusterMin. : 1.0
1st Qu.: 373.0
Median : 762.0
Mean : 737.6
3rd Qu.:1097.0
Max. :1428.0

aimagMin. :11.00
1st Qu.:11.00
Median :45.00
Mean :44.56
3rd Qu.:65.00
Max. :85.00

soumMin. : 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.72
3rd Qu.:25.00
Max. :76.00

location
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :2.373
3rd Qu.:3.000
Max. :4.000

quarterMin. :1.000
1st Qu.:2.000
Median :3.000
Mean :2.555
3rd Qu.:4.000
Max. :4.000

interviewer
Min. : 1.00
1st Qu.: 1.00
Median : 2.00
Mean : 6.56
3rd Qu.: 5.00
Max. :34.00

supervisor
Min. : 1.00
1st Qu.: 3.00
Median :45.00
Mean :42.02
3rd Qu.:65.00
Max. :85.00

q0102
Min. : 1.000
1st Qu.: 1.000
Median : 3.000
Mean : 2.677
3rd Qu.: 3.000
Max. :11.000

q0103
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :1.513
3rd Qu.:2.000
Max. :2.000

q0104
Min. :1912
1st Qu.:1970
Median :1986
Mean :1983
3rd Qu.:1999
Max. :2012

q0105yMin. : 0.00
1st Qu.:13.00
Median :25.00
Mean:28.28
3rd Qu.:42.00
Max.
:99.00q0105mMin. : 0.00
1st Qu.: 3.00
Median : 5.00
Mean
: 5.56
3rd Qu.: 8.00
Max.
:11.00NA's :46947
q0109
Min. : 1.0
1st Qu.: 2.0
Median :99.0

q0106
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean:2.106
3rd Qu.:2.000
Max.
:6.000NA's :13387
q0110aMin. : 0.00
1st Qu.: 0.00
Median : 0.00

q0107
Min.
: 1.000
1st Qu.: 1.000
Median : 2.000
Mean: 4.625
3rd Qu.: 2.000
Max.
:98.000
NA's :28264
q0110
Min. : 0.0000
1st Qu.: 0.0000
Median : 0.0000

q1132bMin. :
0
1st Qu.:0
Median :0
Mean: 1006
3rd Qu.: 465
Max.
:500000
NA's :7272
q1135_2
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :1.556
3rd Qu.:2.000
Max. :2.000
NA's :9562

q0108
Min. : 1.00
1st Qu.: 1.00
Median :99.00

q1133
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean:1.746
3rd Qu.:2.000
Max.
:2.000q1135_3
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :1.653
3rd Qu.:2.000
Max. :2.000
NA's :9562

Manual Mongolia HSES 2012 Version 2.0

78Mean :59.98
3rd Qu.:99.00
Max. :99.00

Mean :51.8
3rd Qu.:99.0
Max. :99.0

Mean : 2.71
3rd Qu.: 0.00
Max. :31.00

Mean : 0.8698
3rd Qu.: 0.0000
Max. :12.0000

q0111
Min. :1.000
1st Qu.:1.000
Median :1.000
Mean :1.026
3rd Qu.:1.000
Max. :2.000

q0201
q0202
q0203
Min. :1.000 Min. : 1.00
Min. :1.00
1st Qu.:2.000
1st Qu.: 1.00
1st Qu.:1.00
Median :2.000 Median : 2.00
Median :2.00
Mean :1.883 Mean : 1.76
Mean :1.55
3rd Qu.:2.000
3rd Qu.: 2.00
3rd Qu.:2.00
Max. :2.000 Max. :10.00
Max. :2.00
NA's :1260
NA's :42454
NA's :42454
q0204
q0205
q0206_1
q0206_2
Min. :1.00
Min. :1.00
Min. :
0 Min. :0
1st Qu.:1.00
1st Qu.:1.00
1st Qu.:0
1st Qu.: 10000
Median :3.00
Median :1.00
Median :0 Median : 20000
Mean :3.89
Mean :1.04
Mean : 17440
Mean: 24931
3rd Qu.:8.00
3rd Qu.:1.00
3rd Qu.:0
3rd Qu.: 35000
Max. :9.00
Max. :3.00
Max. :3000000 Max. :250000
NA's :44888 NA's :45474 NA's :45474
NA's :45474
q0206_3
q0206_4
q0206_5
q0207
Min. :
0 Min. :0 Min. :0 Min. :1.000
1st Qu.:0 1st Qu.:0 1st Qu.: 20000 1st Qu.:1.000
Median :0 Median :0 Median : 30000 Median :1.000
Mean: 3100Mean: 13779
Mean: 59249
Mean:1.125
3rd Qu.:0 3rd Qu.: 20000 3rd Qu.: 50000 3rd Qu.:1.000
Max. :540000 Max. :600000 Max. :3000000 Max. :2.000
NA's :45474
NA's :45474
NA's :45474
NA's
:1260
q0208
q0209
q0210
q0211
Min. :1.00 Min. : 1.000 Min. : 1.000 Min. :1.00
1st Qu.:1.00
1st Qu.: 1.000
1st Qu.: 2.000
1st Qu.:1.00
Median :2.00 Median : 2.000 Median : 4.000
Median :1.00
Mean :1.52 Mean : 1.752 Mean : 3.834 Mean :1.33
3rd Qu.:2.00
3rd Qu.: 2.000
3rd Qu.: 4.000
3rd Qu.:2.00
Max. :2.00 Max. :10.000 Max. :10.000 Max. :3.00
NA's :7106 NA's :26693
NA's :7106
NA's :36752
q0212
q0213
q0214
q0215
Min. :1.000 Min. : 1.00 Min. :1.00
Min. : 1.00
1st Qu.:1.000
1st Qu.: 3.00
1st Qu.:1.00
1st Qu.: 1.00
Median :4.000 Median : 4.00 Median :2.00
Median : 2.00
Mean :2.934 Mean : 4.43 Mean :1.52
Mean : 4.35
3rd Qu.:4.000
3rd Qu.: 5.00
3rd Qu.:2.00
3rd Qu.: 8.00
Max. :4.000 Max. :11.00 Max. :2.00
Max. :13.00
NA's :7106
NA's :45687 NA's :44804
NA's :46404
q0216tq0216gq0217
q0218
Min. :1.0
Min. : 0.00 Min. :1.00
Min. :1.00
1st Qu.:1.0
1st Qu.: 2.00
1st Qu.:1.00
1st Qu.:1.00
Median :1.0
Median : 4.00 Median :1.00
Median :2.00
Mean :1.5
Mean : 5.15 Mean :1.09
Mean :1.92
3rd Qu.:2.0
3rd Qu.: 8.00
3rd Qu.:1.00
3rd Qu.:3.00
Max. :4.0
Max. :12.00 Max. :3.00
Max.
:4.00
NA's :35191 NA's :35191 NA's :35191
NA's :35191
q0219
q0220
q0221
q0222
Min. :1.00
Min. : 0.00 Min. : 0.0
Min. :1.00
1st Qu.:1.00
1st Qu.: 0.70
1st Qu.: 10.0
1st Qu.:1.00
Median :1.00
Median : 1.50 Median : 20.0
Median :2.00

Manual Mongolia HSES 2012 Version 2.0

79

Mean :1.73
Mean :22.58 Mean : 33.8
Mean :1.74
3rd Qu.:3.00
3rd Qu.:10.00
3rd Qu.: 40.0
3rd Qu.:2.00
Max. :5.00
Max. :99.00 Max. :150.0
Max.
:2.00
NA's :35191 NA's :35191 NA's :35191
NA's :35191
q0223
q0224
q0225
q0226_1
Min. :1.00
Min. :1.00
Min. : 25000 Min. :0
1st Qu.:2.00
1st Qu.:1.00
1st Qu.: 500000 1st Qu.:
0Median :2.00
Median :2.00
Median :1000000 Median :0
Mean :1.79
Mean :1.97
Mean :1168718 Mean : 41538
3rd Qu.:2.00
3rd Qu.:2.00
3rd Qu.:1500000
3rd Qu.:0
Max. :2.00
Max. :7.00
Max. :8000000 Max. :3600000
NA's :44635 NA's :47221 NA's :47221
NA's :35191
q0226_2
q0226_3
q0226_4
q0226_5
Min. :
0 Min. :0 Min. :0 Min. :0
1st Qu.:0 1st Qu.: 30000 1st Qu.:0 1st Qu.:
0Median :0 Median : 50000 Median :0 Median :0
Mean : 212127 Mean : 61174 Mean : 19118 Mean : 34492
3rd Qu.:0 3rd Qu.: 75000 3rd Qu.: 25000 3rd Qu.: 30000
Max. :7000000 Max. :650000 Max. :500000 Max. :2500000
NA's:35191NA's:35191NA's:35191NA's:35191q0226_6
q0226_7
q0301
q0302
Min. :
0 Min. :0 Min. :1.000 Min. : 1.00
1st Qu.:0
1st Qu.:58000
1st Qu.:1.000
1st Qu.: 1.00
Median :0 Median : 105000 Median :2.000 Median : 2.00
Mean
: 39354 Mean : 407803 Mean :1.568 Mean : 1.75
3rd Qu.: 29000
3rd Qu.: 400000
3rd Qu.:2.000
3rd Qu.: 2.00
Max.
:3000000
Max.
:11992000
Max.
:2.000Max.
:10.00NA's :35191
NA's :35191
NA's :1260
NA's :21406
q0303
q0304
q0305
q0306
Min. :1.000 Min. :1.00
Min. :1.00 Min. :0.00
1st Qu.:1.000
1st Qu.:1.00
1st Qu.:2.00
1st Qu.:3.00
Median :1.000 Median :3.00
Median :2.00 Median :4.00
Mean :1.065 Mean :3.44
Mean :1.96 Mean :4.18
3rd Qu.:1.000
3rd Qu.:6.00
3rd Qu.:2.00
3rd Qu.:6.00
Max. :2.000 Max. :7.00
Max. :2.00 Max. :6.00
NA's :1260
NA's :44873 NA's :1260 NA's :46048
q0307
q0308_1
q0308_2
q0309
Min. :1.000 Min. :1.00
Min. :0.00
Min. : 0.00
1st Qu.:2.000
1st Qu.:1.00
1st Qu.:0.00
1st Qu.: 0.00
Median :2.000 Median :4.00
Median :0.00
Median : 2.00
Mean :1.933 Mean :3.25
Mean :0.38
Mean : 5.79
3rd Qu.:2.000
3rd Qu.:5.00
3rd Qu.:0.00
3rd Qu.:10.00
Max. :2.000 Max. :6.00
Max. :6.00
Max. :31.00
NA's :1260
NA's :44791 NA's :44792
NA's :44791
q0310
q0311
q0312
q0313
Min. :0.0
Min. : 1.00 Min. :1.00
Min. :1.00
1st Qu.:1.0
1st Qu.: 1.00
1st Qu.:2.00
1st Qu.:1.00
Median :1.0
Median : 3.00 Median :2.00
Median :1.00
Mean :1.2
Mean : 5.79 Mean :2.38
Mean :1.23
3rd Qu.:1.0
3rd Qu.:11.00
3rd Qu.:3.00
3rd Qu.:1.00
Max. :2.0
Max. :12.00 Max. :6.00
Max.
:6.00
NA's :44790 NA's :47292 NA's :45406
NA's :45406
q0314aq0314bq0315
q0316
Min. :
0 Min. :0 Min. :1.000 Min. :2
1st Qu.:3000
1st Qu.:0
1st Qu.:2.000
1st Qu.:5000
Median : 20000 Median :0 Median :2.000 Median : 10000

Manual Mongolia HSES 2012 Version 2.0

80

Mean : 83957 Mean : 33240 Mean :1.894 Mean : 23774
3rd Qu.: 60000 3rd Qu.: 20000 3rd Qu.:2.000 3rd Qu.: 20000
Max.
:10000000
Max.
:6000000
Max.
:2.000Max.
:3000000NA's:45407NA's:45407
NA's
:1263
NA's
:42965
q0317
q0318
q0319
q0320
Min. :1.000 Min. :1.00
Min. :1.00
Min. : 1.00
1st Qu.:2.000
1st Qu.:1.00
1st Qu.:1.00
1st Qu.: 9.00
Median :2.000 Median :2.00
Median :1.00
Median : 10.00
Mean :1.895 Mean :2.23
Mean :1.03
Mean : 13.22
3rd Qu.:2.000
3rd Qu.:3.00
3rd Qu.:1.00
3rd Qu.: 14.00
Max. :2.000 Max. :6.00
Max. :4.00
Max. :365.00
NA's :1262
NA's :43003 NA's :43003
NA's :43003
q0321
q0322
q0323
q0324
Min. :
0 Min. :0 Min. :1.000 Min. :1.000
1st Qu.:0 1st Qu.:0 1st Qu.:2.000 1st Qu.:2.000
Median : 30000 Median : 20000 Median :2.000 Median :2.000
Mean : 185999 Mean : 67697
Mean:1.872Mean:1.995
3rd Qu.: 180000
3rd Qu.: 60000
3rd Qu.:2.000
3rd Qu.:2.000
Max.
:20000000
Max.
:6000000
Max.
:2.000Max.
:2.000NA's :43003
NA's :43002
NA's :1260
NA's :1260
q0325
q0401
q0402
q0403
Min. :1.000 Min. :1.000 Min. :1.00
Min. :1.00
1st Qu.:2.000
1st Qu.:1.000
1st Qu.:1.00
1st Qu.:1.00
Median :2.000 Median :2.000 Median :1.00
Median :1.00
Mean :1.994 Mean :1.709 Mean :1.32
Mean :1.13
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:2.00
3rd Qu.:1.00
Max. :2.000 Max. :2.000 Max. :2.00
Max. :2.00
NA's :1260
NA's :1262
NA's :34345
NA's :38620
q0404
q0405
q0406
q0407
Min. :1.00
Min. :1.00
Min. :1.00
Min. : 1.00
1st Qu.:2.00
1st Qu.:1.00
1st Qu.:1.00
1st Qu.: 2.00
Median :2.00
Median :4.00
Median :2.00
Median : 2.00
Mean :1.81
Mean :3.31
Mean :1.61
Mean : 3.09
3rd Qu.:2.00
3rd Qu.:5.00
3rd Qu.:2.00
3rd Qu.: 4.00
Max. :2.00
Max. :8.00
Max. :2.00
Max. :11.00
NA's :39810 NA's :46334 NA's :39810
NA's :44776
q0501
q0502
q0503
q0504
Min. :1.000 Min. :1.000 Min. :1.000
Min. :1.0
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:2.000
1st Qu.:2.0
Median :1.000 Median :1.000 Median :2.000
Median :3.0
Mean :1.285 Mean :1.332 Mean :1.957
Mean :2.5
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:3.0
Max. :2.000 Max. :2.000 Max. :2.000
Max. :6.0
NA's :1262
NA's :14551 NA's :25611
NA's :35885
q0505
q0506
q0507
q0508
Min. :1.00
Min. :1937
Min. :1.00
Min. :1.000
1st Qu.:3.00
1st Qu.:1989
1st Qu.:1.00
1st Qu.:2.000
Median :3.00
Median :2000
Median :1.00
Median :2.000
Mean :3.73
Mean :1995
Mean :1.12
Mean :1.993
3rd Qu.:5.00
3rd Qu.:2005
3rd Qu.:1.00
3rd Qu.:2.000
Max. :9.00
Max. :2012
Max. :2.00
Max.
:2.000NA's :35885 NA's :35885 NA's :35881
NA's :9
q0509
q0510
q0511
q0512
Min. : 4.0 Min. :1.00
Min. : 0.00
Min. :1.00
1st Qu.:336.0
1st Qu.:1.00
1st Qu.: 1.00
1st Qu.:1.00
Median :410.0 Median :1.00
Median : 3.00
Median :2.00

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81

Mean :476.1 Mean :1.95
Mean : 3.72
Mean :1.67
3rd Qu.:752.0
3rd Qu.:3.00
3rd Qu.: 5.00
3rd Qu.:2.00
Max. :840.0 Max. :7.00
Max. :24.00
Max.
:2.00
NA's :47580 NA's :47580 NA's :47580
NA's :47580
q0513
q0514
q0601
q0602
Min. :
0 Min. : 11300 Min. :1.000 Min. :1.000
1st Qu.:0
1st Qu.: 545000
1st Qu.:1.000
1st Qu.:1.000
Median : 150000 Median : 2200000 Median :1.000
Median :1.000
Mean : 426396 Mean : 3073052 Mean :1.192 Mean :1.487
3rd Qu.: 500000 3rd Qu.: 5000000 3rd Qu.:1.000
3rd Qu.:2.000
Max.
:3680000
Max.
:15000000
Max.
:2.000Max.
:2.000NA's:47801NA's:47801
NA's
:1264
NA's
:10206
q0603
q0604
q0605
q0606
Min. : 1.000 Min. :1.000
Min.
:1.000Min.
:1.000
1st Qu.: 1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:2.000
Median : 2.000 Median :2.000 Median :1.000 Median :2.000
Mean : 1.763 Mean :1.543 Mean :2.128 Mean :1.915
3rd Qu.: 2.000 3rd Qu.:2.000
3rd Qu.:3.000
3rd Qu.:2.000
Max.
:10.000
Max.
:2.000Max.
:5.000Max.
:2.000NA's:29530NA's:10206NA's:30694NA's:27419
q0607
q0608
q0609
q0610
Min. :1.00
Min. :1.000 Min. :1.00
Min. :1.000
1st Qu.:4.00
1st Qu.:2.000
1st Qu.:2.00
1st Qu.:1.000
Median :6.00
Median :2.000 Median :2.00
Median :1.000
Mean :5.22
Mean :1.967 Mean :2.73
Mean :2.446
3rd Qu.:7.00
3rd Qu.:2.000 3rd Qu.:3.00
3rd Qu.:3.000
Max. :8.00
Max. :2.000 Max. :6.00
Max. :8.000
NA's :46163 NA's :29163 NA's :47293
NA's :29778
q0611
q0612
q0613
q0614
Min. :1.00
Min. :111.0 Min. : 111.0 Min. : 2.00
1st Qu.:2.00
1st Qu.:413.0
1st Qu.: 149.1
1st Qu.: 40.00
Median :2.00
Median :612.0 Median :4329.0
Median : 48.00
Mean :1.84
Mean :560.5 Mean :3885.3 Mean : 50.03
3rd Qu.:2.00
3rd Qu.:713.0
3rd Qu.:6910.0
3rd Qu.: 60.00
Max. :2.00
Max. :997.0 Max. :9900.0 Max. :140.00
NA's :42285 NA's :28946 NA's :28946
NA's :28946
q0615
q0616
q0617_1
q0617_2
Min. :1.000 Min. :1.000 Min. :0 Min. :0
1st Qu.:4.000
1st Qu.:1.000
1st Qu.: 215000
1st Qu.: 2145500
Median :8.000 Median :1.000 Median : 340000
Median : 3600000
Mean:7.069Mean:1.425Mean: 378014
Mean: 4173211
3rd Qu.:9.000
3rd Qu.:2.000
3rd Qu.: 500000
3rd Qu.: 5400000
Max.
:9.000Max.
:2.000Max.
:6500000
Max.
:70200000
NA's:28946NA's :28943
NA's:37006NA's:37006q0617_3
q0618
q0619_1
q0619_2
Min. :
0 Min. :1.00
Min. :
0 Min. :0
1st Qu.:0 1st Qu.:2.00
1st Qu.:0 1st Qu.: 300000
Median :0 Median :2.00
Median :0 Median : 800000
Mean : 87889 Mean :1.97
Mean : 146265 Mean : 1702074
3rd Qu.:0 3rd Qu.:2.00
3rd Qu.: 200000 3rd Qu.: 1970000
Max. :18000000 Max. :2.00
Max.
:3000000
Max.
:24000000
NA's:37006NA's:37003NA's:47591NA's:47592q0619_3
PID
Min. :
0 Min. :101
1st Qu.:0 1st Qu.: 315703
Median :0 Median : 634902

Manual Mongolia HSES 2012 Version 2.0

82

Mean : 145047
3rd Qu.:0
Max. :30000000
NA's :47591

Mean : 639155
3rd Qu.: 958701
Max. :1281104## 3 #### Llivestock #########
identif
ani_idclusterMin. :
1 Min. :1.000 Min. : 1
1st Qu.: 3095
1st Qu.:2.000
1st Qu.: 230
Median : 6282 Median :4.000 Median : 482
Mean : 6000 Mean :3.144 Mean : 541
3rd Qu.: 9608
3rd Qu.:5.000
3rd Qu.: 731
Max. :12788 Max. :6.000 Max. :1425
soumMin. : 1.00
1st Qu.:13.00
Median :25.00
Mean :26.52
3rd Qu.:40.00
Max. :76.00

location
Min. :1.000
1st Qu.:3.000
Median :4.000
Mean :3.441
3rd Qu.:4.000
Max. :4.000

aimag
Min. :11.00
1st Qu.:43.00
Median :63.00
Mean :57.61
3rd Qu.:81.00
Max. :85.00

q0702_1
Min. : 0.00
1st Qu.:7.00
Median : 20.00
Mean : 53.06
3rd Qu.: 59.00
Max. :3500.00

q0702_2
Min. : 0.00
1st Qu.:2.00
Median :7.00
Mean : 20.12
3rd Qu.: 20.00
Max. :1600.00
NA's
:72
q0704
q0705
Min. : 0.000 Min. :0
1st Qu.: 0.000
1st Qu.:0
Median : 0.000 Median :0
Mean : 3.545 Mean : 414418
3rd Qu.: 1.000
3rd Qu.: 170000
Max.
:500.000
Max.
:36000000

q0702_3
q0703
Min. : 0.00 Min. : 0.000
1st Qu.:2.00
1st Qu.: 0.000
Median : 5.00 Median : 1.000
Mean : 16.19 Mean : 3.644
3rd Qu.: 18.00
3rd Qu.: 5.000
Max. :1280.00 Max. :150.000
NA's :72
NA's :1
quarterinterviewer
supervisor
Min. :1.000 Min. : 1.000 Min. : 1.0
1st Qu.:2.000 1st Qu.: 1.000 1st Qu.:43.0
Median :3.000 Median : 2.000 Median :63.0
Mean :2.571 Mean : 2.123 Mean :57.5
3rd Qu.:4.000 3rd Qu.: 3.000 3rd Qu.:81.0
Max. :4.000 Max. :34.000 Max. :85.0## 4 #### Livestock Expenditure #########
identif
exp_idclusteraimag
Min. :
1 Min. :1.00 Min. : 1.0
Min. :11.00
1st Qu.: 3176
1st Qu.:1.00
1st Qu.: 269.0
1st Qu.:43.00
Median : 6322 Median :2.00 Median : 526.0
Median :62.00
Mean : 6144 Mean :2.24 Mean : 586.1
Mean :57.25
3rd Qu.: 9614 3rd Qu.:3.00 3rd Qu.: 782.0
3rd Qu.:81.00
Max. :12788 Max. :7.00 Max. :1425.0
Max. :85.00
soumlocation
q0706
quarterMin. : 1.00 Min. :1.000 Min. :1000 Min. :1.000
1st Qu.:10.00
1st Qu.:3.000
1st Qu.:36000
1st Qu.:2.000
Median :22.00 Median :4.000
Median : 100000
Median :3.000
Mean:26.15Mean:3.413Mean: 236415
Mean:2.5843rd Qu.:40.00
3rd Qu.:4.000
3rd Qu.: 240000
3rd Qu.:4.000
Max.
:76.00Max.
:4.000Max.
:27280000
Max.
:4.000Manual Mongolia HSES 2012 Version 2.0

83interviewer
Min. : 1.000
1st Qu.: 1.000
Median : 2.000
Mean : 2.304
3rd Qu.: 3.000
Max. :34.000

supervisor
Min. : 1.00
1st Qu.:43.00
Median :62.00
Mean :57.06
3rd Qu.:81.00
Max. :85.00## 5 #### Product #########
identif
byprod_id
clusterMin. :
1 Min. : 1 Min. : 1.0
1st Qu.: 3084 1st Qu.: 5 1st Qu.: 214.0
Median : 6280 Median : 9 Median : 462.0
Mean : 6001 Mean : 9 Mean : 539.9
3rd Qu.: 9593 3rd Qu.:13 3rd Qu.: 732.0
Max. :12788 Max. :17 Max. :1425.0
soumMin. : 1.00
1st Qu.:13.00
Median :25.00
Mean:26.42
3rd Qu.:40.00
Max.
:76.00q0710
Min. :
0.0
1st Qu.:0.0
Median :0.0
Mean : 235.7
3rd Qu.:1.0
Max. :18800.0
NA's :53335
q0714
Min. :
0
1st Qu.:0
Median :0
Mean : 11151
3rd Qu.:0Max.
:8157500
NA's :53335

aimagMin. :11.00
1st Qu.:44.00
Median :63.00
Mean :58.61
3rd Qu.:81.00
Max. :85.00

location
Min. :1.000
1st Qu.:3.000
Median :4.000
Mean:3.388
3rd Qu.:4.000
Max.
:4.000q0708
q0709
Min. : 0.0 Min. :0.0
1st Qu.:0.0
1st Qu.:0.0
Median : 0.0 Median :0.0
Mean: 15.2Mean: 146.4
3rd Qu.:3.0
3rd Qu.:10.0
Max.
:4000.0Max.
:41000.0
NA's :34860
NA's :28129
q0711
q0712
q0713
Min. :
0.0 Min. :0 Min. :0.00
1st Qu.:1.0
1st Qu.:7530
1st Qu.:0.00
Median :4.0 Median : 35000 Median :0.00
Mean : 62.9 Mean : 289745 Mean : 20.41
3rd Qu.:14.0
3rd Qu.: 130000
3rd Qu.:0.00
Max. :31000.0 Max. :23500000 Max. :32637.00
NA's :53335
NA's :53335
NA's :53335
quarterinterviewer
supervisor
Min. :1.000 Min. : 1.000 Min. : 1.00
1st Qu.:2.000
1st Qu.: 1.000
1st Qu.:44.00
Median :3.000 Median : 2.000 Median :63.00
Mean :2.573 Mean : 2.192 Mean
:58.51
3rd Qu.:4.000
3rd Qu.: 3.000
3rd Qu.:81.00
Max.
:4.000Max.
:34.000Max.
:85.00## 6 #### Crop
identif
Min. : 12
1st Qu.: 3214
Median : 5993
Mean : 6152
3rd Qu.: 9306
Max. :12808#########
crop_id
Min. : 1.000
1st Qu.: 1.000
Median : 3.000
Mean : 4.554
3rd Qu.: 7.000
Max. :13.000

soumMin. : 1.0
1st Qu.: 1.0

location
Min. :1.0
1st Qu.:2.0

clusterMin. : 2.0
1st Qu.: 361.0
Median : 620.0
Mean : 700.4
3rd Qu.:1176.0
Max. :1428.0

q0719
Min. :1
1st Qu.:1

q0720
Min.
:
1st Qu.:aimag
Min. :11.00
1st Qu.:43.00
Median :61.00
Mean :53.97
3rd Qu.:81.00
Max. :85.00

0.5
25.0

Manual Mongolia HSES 2012 Version 2.0

84Median :10.0
Mean :15.8
3rd Qu.:28.0
Max. :76.0
q0721
Min. : 0.0
1st Qu.: 10.0
Median : 50.0
Mean : 158.4
3rd Qu.: 150.0
Max. :7000.0
NA's :183
quarterMin. :1.000
1st Qu.:2.000
Median :2.000
Mean :2.511
3rd Qu.:3.000
Max. :4.000

Median :3.0
Mean :2.7
3rd Qu.:3.0
Max. :4.0

Median :1
Mean :1
3rd Qu.:1
Max. :2

Median : 100.0
Mean: 1860.9
3rd Qu.: 700.0
Max.
:200000.0
NA's
:1
q0722
q0723qq0723tMin. :
0.0 Min. :0.0 Min. :0
1st Qu.:0.0 1st Qu.:
0.0 1st Qu.:
0Median :0.0 Median :0.0Median :0
Mean : 530.6 Mean :985.2 Mean : 387190
3rd Qu.:0.0 3rd Qu.:
50.0 3rd Qu.: 40000
Max. :90000.0 Max. :200000.0 Max. :80000000
NA's :1
NA's :1
NA's :1
interviewer
supervisor
Min. : 1.00 Min. : 1.00
1st Qu.: 1.00
1st Qu.:43.00
Median : 2.00 Median :61.00
Mean : 3.17 Mean :53.45
3rd Qu.: 3.00
3rd Qu.:81.00
Max. :33.00 Max. :85.00## 7 #### Agriultural Expenditure #########
identif
exp_idclusteraimag
Min. : 12 Min. : 1 Min. : 2.0
Min. :11.00
1st Qu.: 2986 1st Qu.: 4 1st Qu.: 200.0
1st Qu.:43.00
Median : 5985 Median : 7 Median : 579.0
Median :61.00
Mean : 5936 Mean : 7 Mean : 646.2
Mean :56.91
3rd Qu.: 9189 3rd Qu.:10 3rd Qu.: 903.0
3rd Qu.:83.00
Max. :12808 Max. :13 Max. :1428.0
Max. :85.00
soumlocation
q0724
quarterMin. : 1.00 Min. :1.000 Min. :0 Min. :1.000
1st Qu.: 1.00
1st Qu.:2.000
1st Qu.:0
1st Qu.:2.000
Median :19.00 Median :3.000 Median :0 Median :2.000
Mean :19.53 Mean :2.834 Mean : 42266 Mean :2.479
3rd Qu.:31.00
3rd Qu.:3.000
3rd Qu.:0
3rd Qu.:3.000
Max.
:76.00Max.
:4.000Max.
:19500000
Max.
:4.000interviewer
supervisor
Min. : 1.000 Min.
: 1.00
1st Qu.: 1.000 1st Qu.:43.00
Median : 2.000 Median :61.00
Mean : 3.062 Mean :56.45
3rd Qu.: 3.000 3rd Qu.:83.00
Max. :33.000 Max. :85.00## 8 #### Enterprise #########
identifenaimag
Min. : 14 Min. :1.000 Min. :11.00
1st Qu.: 3419
1st Qu.:1.000
1st Qu.:11.00
Median : 6462 Median :1.000 Median :45.00
Mean : 6501 Mean :1.106 Mean :45.27
3rd Qu.: 9497
3rd Qu.:1.000
3rd Qu.:67.00
Max. :12810 Max. :3.000 Max. :85.00
NA's :2

soumMin. : 1.00
1st Qu.: 1.00
Median :10.00
Mean :14.89
3rd Qu.:25.00
Max. :76.00

Manual Mongolia HSES 2012 Version 2.0

85

location
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :2.076
3rd Qu.:3.000
Max. :4.000

q0803
q0804
q0805
Min. : 113 Min. : 10.00
Min. :0.000
1st Qu.:4510 1st Qu.:100.00
1st Qu.:1.000
Median :4730 Median :100.00
Median :1.000
Mean :4508
Mean: 98.42Mean:1.208
3rd Qu.:4922 3rd Qu.:100.00
3rd Qu.:1.000
Max. :9820 Max. :100.00
Max. :4.000
NA's :1
q0806
q0807_01
q0807_02
Min. : 0.0000 Min. :0 Min. :0
1st Qu.: 0.0000
1st Qu.:0
1st Qu.:0
Median : 0.0000 Median :0 Median :0
Mean : 0.4829 Mean : 1081737 Mean : 7841800
3rd Qu.: 0.0000
3rd Qu.:0
3rd Qu.: 4800000
Max. :60.0000 Max. :240000000 Max. :400000000
q0807_03
Min.
:0
1st Qu.:0
Median :0
Mean : 1256217
3rd Qu.:0Max.
:540000000

q0807_04
Min.
:0
1st Qu.:0
Median :0
Mean : 1415578
3rd Qu.: 1000000
Max.
:132000000

q0807_05
Min.
:0
1st Qu.:0
Median :0
Mean : 179470
3rd Qu.:14250
Max.
:50000000

q0807_06
Min. :
0
1st Qu.:0
Median :0
Mean : 166538
3rd Qu.:0
Max. :74000000

q0807_07
Min. :
0
1st Qu.:0
Median :0
Mean : 650450
3rd Qu.: 100000
Max. :120000000

q0807_08
Min.
:0
1st Qu.:0
Median :0
Mean: 202505
3rd Qu.:0
Max.
:70000000

q0807_09
Min. :
0
1st Qu.:0
Median :0
Mean : 60278
3rd Qu.:0
Max. :10000000

q0807_10
Min. :
0
1st Qu.:0
Median :0
Mean : 236920
3rd Qu.:72000
Max. :108000000

q0807_11
Min.
:0
1st Qu.:0
Median :0
Mean: 571059
3rd Qu.: 270000
Max.
:60000000

q0807_99
Min.
:0
1st Qu.: 1100000
Median : 3942000
Mean : 13662550
3rd Qu.: 11105250
Max. :608160000

q0808
Min. : 1.000
1st Qu.: 8.000
Median :12.000
Mean : 9.764
3rd Qu.:12.000
Max. :12.000

q0809_2aMin. :
0
1st Qu.:200000Median : 450000
Mean : 1289478
3rd Qu.: 1000000
Max. :300000000
NA's :16

q0809_2bMin. :0.000
1st Qu.:2.000
Median :3.000
Mean :2.895
3rd Qu.:4.000
Max. :9.000
NA's :16

q0809_1aMin. :
0
1st Qu.:350000Median :750000Mean : 2018899
3rd Qu.: 1600000
Max. :315000000
NA's:3q0809_3aMin. :
0
1st Qu.:450000Median : 1000000
Mean : 2643750
3rd Qu.: 2100000
Max. :400000000
NA's :15

q0809_1b
Min. : 0.000
1st Qu.: 2.000
Median : 4.000
Mean : 3.764
3rd Qu.: 5.000
Max. :12.000
NA's:3q0809_3bMin. : 0.00
1st Qu.: 2.00
Median : 3.00
Mean : 3.15
3rd Qu.: 4.00
Max. :12.00
NA's :15

Manual Mongolia HSES 2012 Version 2.0

86quarterMin.
:1.000
1st Qu.:2.000
Median :3.000
Mean :2.556
3rd Qu.:4.000
Max.
:4.000interviewer
Min.
: 1.000
1st Qu.: 1.000
Median : 2.000
Mean : 6.591
3rd Qu.: 8.000
Max.
:34.000

supervisor
Min.
: 1.00
1st Qu.: 3.00
Median :45.00
Mean :42.52
3rd Qu.:67.00
Max.
:85.00## 9 #### Other income #########
identif
income_id
cluster
Min.
:
1
Min.
: 1.0
Min.
:
1.0
1st Qu.: 3203 1st Qu.: 7.0 1st Qu.: 374.0
Median : 6406
Median :14.0
Median : 754.0
Mean: 6406
Mean
:13.5
Mean
: 733.7
3rd Qu.: 9609 3rd Qu.:20.0 3rd Qu.:1088.0
Max.
:12811
Max.
:26.0
Max.
:1428.0
soumMin. : 1.00
1st Qu.: 1.00
Median :16.00
Mean:17.87
3rd Qu.:25.00
Max. :76.00

location
Min. :1.00
1st Qu.:1.00
Median :2.00
Mean
:2.38
3rd Qu.:3.00
Max. :4.00

aimag
Min.
:11.0
1st Qu.:11.0
Median :45.0
Mean
:44.1
3rd Qu.:65.0
Max.
:85.0

q0901
Min. :1.00
1st Qu.:2.00
Median :2.00
Mean
:1.92
3rd Qu.:2.00
Max. :2.00

q0902_ic
Min. : 0.00
1st Qu.: 1.00
Median : 1.00
Mean
: 1.49
3rd Qu.: 2.00
Max. :12.00
NA's:306543q0902_tq0903_ic
q0903_tq0904_ic
Min.
:
0
Min.
: 0.00
Min.
:
0
Min.
: 0.0
1st Qu.:187850
1st Qu.: 0.00
1st Qu.: 185850
1st Qu.: 0.0
Median : 247800 Median : 2.00
Median : 247800
Median : 3.0
Mean:747161Mean: 1.12Mean: 352993
Mean: 2.2
3rd Qu.:660000
3rd Qu.: 2.00
3rd Qu.: 247800
3rd Qu.: 3.0
Max.
:220000000
Max.
:12.00Max.
:10000000
Max.
:98.0
NA's :306545
NA's :306544 NA's :319200
NA's :319201
q0904_tq0905_ic
q0905_tq0906_ic
Min. : 3000 Min. : 0.0
Min. :
7200 Min. : 0.0
1st Qu.: 185850
1st Qu.: 0.0
1st Qu.: 185850
1st Qu.: 0.0
Median : 229150 Median : 4.0
Median : 229150 Median : 0.0
Mean : 217903 Mean : 2.8
Mean : 214804 Mean :19.4
3rd Qu.: 247800
3rd Qu.: 4.0
3rd Qu.: 247800
3rd Qu.: 5.0
Max. :2160000 Max. :98.0
Max. :1740000 Max. :98.0
NA's :323424
NA's :323424 NA's :326475
NA's :326476
q0906_tquarterinterviewer
supervisor
Min. : 10000 Min. :1.000 Min. : 1.00 Min. : 1.00
1st Qu.: 208650
1st Qu.:2.000
1st Qu.: 1.00
1st Qu.: 3.00
Median : 247800
Median :3.000
Median : 2.00
Median :45.00
Mean : 350757 Mean :2.562 Mean
: 6.51Mean:41.58
3rd Qu.: 455400
3rd Qu.:4.000
3rd Qu.: 5.00
3rd Qu.:65.00
Max.
:11704000Max.
:4.000Max.
:34.00Max.
:85.00NA's :329821## 10 #### Remittance #########
identiflnclusterMin. : 13 Min. :1.0 Min. : 6.0

aimag
Min. :11.00

Manual Mongolia HSES 2012 Version 2.0

87

1st Qu.: 3388
Median : 6674
Mean : 6308
3rd Qu.: 9856
Max. :12808

1st Qu.:1.0
Median :1.0
Mean :1.6
3rd Qu.:2.0
Max. :8.0

soumMin. : 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.71
3rd Qu.:25.00
Max. :76.00

location
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :2.357
3rd Qu.:3.000
Max. :4.000

q0910
Min. :1.000
1st Qu.:1.000
Median :1.000
Mean:1.811
3rd Qu.:2.000
Max.
:8.000q0911
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean:2.367
3rd Qu.:3.000
Max.
:5.000

q0914
Min.
:1.00
1st Qu.:4.00
Median :5.00
Mean
:4.42
3rd Qu.:5.00
Max. :5.00

q0915
Min.
:1.00
1st Qu.:1.00
Median :1.00
Mean
:2.05
3rd Qu.:4.00
Max. :5.00

1st Qu.: 452.0
Median : 574.0
Mean : 711.3
3rd Qu.:1053.0
Max. :1428.0

1st Qu.:11.00
Median :45.00
Mean :39.69
3rd Qu.:48.00
Max. :85.00

ind_idMin. : 1.00
1st Qu.: 1.00
Median : 1.00
Mean : 1.81
3rd Qu.: 2.00
Max. :11.00

q0909
Min. :1.000
1st Qu.:2.000
Median :4.000
Mean :3.362
3rd Qu.:4.000
Max. :7.000

q0912
q0913
Min. : 23.0
Min. :
3000
1st Qu.:408.0
1st Qu.: 200000
Median :410.0
Median : 400000
Mean:474.4Mean: 863345
3rd Qu.:752.0
3rd Qu.: 850000
Max.
:840.0Max.
:30000000
NA's :3400
quarterinterviewer
Min.
:1.000Min.
: 1.000
1st Qu.:2.000
1st Qu.: 1.000
Median :3.000
Median : 2.000
Mean:2.549Mean: 6.737
3rd Qu.:4.000
3rd Qu.: 7.750
Max.
:4.000Max.
:34.000

supervisor
Min. : 1.00
1st Qu.: 3.00
Median :45.00
Mean:37.043rd Qu.:48.00
Max.
:85.00## 11 #### Savings loan #########
identifclusteraimag
Min. :
2 Min. : 1.0 Min. :11.0
1st Qu.: 3119 1st Qu.: 365.0 1st Qu.:23.0
Median : 6294 Median : 681.0 Median :46.0
Mean : 6284 Mean : 716.6 Mean :48.6
3rd Qu.: 9468 3rd Qu.:1090.0 3rd Qu.:67.0
Max. :12810 Max. :1428.0 Max. :85.0

soumMin. : 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.73
3rd Qu.:28.00
Max. :76.00

location
Min. :1.000
1st Qu.:2.000
Median :2.000
Mean :2.453
3rd Qu.:3.000
Max. :4.000

q1006
Min. :1.000
1st Qu.:1.000
Median :1.000
Mean :1.133
3rd Qu.:1.000
Max. :2.000

loan_id
Min. :1.000
1st Qu.:1.000
Median :1.000
Mean :1.121
3rd Qu.:1.000
Max. :3.000

q1005
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :3.275
3rd Qu.:5.000
Max. :9.000

Manual Mongolia HSES 2012 Version 2.0

88

q1007
q1008
q1009
Min. :
2 Min. :1.000 Min. :1.000
1st Qu.: 1000000
1st Qu.:1.000
1st Qu.:1.000
Median : 2000000 Median :1.000 Median :1.000
Mean : 4448704 Mean :1.051 Mean :1.168
3rd Qu.: 5000000
3rd Qu.:1.000
3rd Qu.:1.000
Max. :200000000 Max. :3.000 Max. :7.000
NA's :841
q1010bq1010cq1011
Min. :0.000 Min. :0.000 Min. :0
1st Qu.:1.000
1st Qu.:3.000
1st Qu.:80000
Median :4.000 Median :8.000 Median : 160000
Mean :4.029 Mean :5.659 Mean : 241670
3rd Qu.:6.000
3rd Qu.:8.000
3rd Qu.: 285000
Max. :8.000 Max. :8.000 Max. :18000000
NA's :5556
NA's :6141
NA's :1
quarterinterviewer
supervisor
Min. :1.000
Min.
: 1.000Min.
: 1.00
1st Qu.:2.000
1st Qu.: 1.000
1st Qu.:23.00
Median :3.000 Median : 2.000 Median :46.00
Mean :2.536 Mean : 4.934 Mean :46.89
3rd Qu.:3.000
3rd Qu.: 3.000
3rd Qu.:67.00
Max.
:4.000Max.
:34.000Max.
:85.00## 12 #### Energy #########
identifclusterMin. :
1 Min. : 1.0
1st Qu.: 3203 1st Qu.: 374.0
Median : 6406 Median : 754.0
Mean : 6406 Mean : 733.7
3rd Qu.: 9609 3rd Qu.:1088.0
Max. :12811 Max. :1428.0
location
Min. :1.00
1st Qu.:1.00
Median :2.00
Mean :2.38
3rd Qu.:3.00
Max. :4.00

aimagMin. :11.0
1st Qu.:11.0
Median :45.0
Mean :44.1
3rd Qu.:65.0
Max. :85.0

q1010aMin. :1.000
1st Qu.:1.000
Median :1.000
Mean :2.592
3rd Qu.:3.000
Max. :8.000
q1012
Min. :
0
1st Qu.: 340000
Median : 900000
Mean : 1711844
3rd Qu.: 2038725
Max. :70000000
NA's :1

soum
Min. : 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.87
3rd Qu.:25.00
Max. :76.00

energy_id
q1136
Min. :1 Min. :1.000
1st Qu.:3 1st Qu.:2.000
Median :5 Median :2.000
Mean :5 Mean :1.752
3rd Qu.:7 3rd Qu.:2.000
Max. :9 Max. :2.000

q1137
Min. :0.00
1st Qu.:1.00
Median :2.00
Mean :1.76
3rd Qu.:2.00
Max. :4.00
NA's:97212
q1138
q1139
q1140
q1141
Min. : 0.00 Min. :0 Min. :0 Min. :0
1st Qu.:3.00 1st Qu.:0 1st Qu.: 60000 1st Qu.:
0Median : 5.00 Median : 2500 Median : 130000 Median :0
Mean : 24.99 Mean : 11014 Mean : 160370 Mean : 6312
3rd Qu.: 10.00
3rd Qu.: 15000
3rd Qu.: 225000 3rd Qu.:
0
Max. :1500.00 Max. :1670000 Max. :3600000 Max. :1000000
NA's :97211
NA's :86665
NA's :86662
NA's :86665
quarterinterviewer
supervisor
Min. :1.000 Min. : 1.00 Min. : 1.00
1st Qu.:2.000
1st Qu.: 1.00
1st Qu.: 3.00
Median :3.000 Median : 2.00 Median :45.00

Manual Mongolia HSES 2012 Version 2.0

89Mean :2.562
3rd Qu.:4.000
Max. :4.000

Mean : 6.51
3rd Qu.: 5.00
Max. :34.00

Mean :41.58
3rd Qu.:65.00
Max. :85.00## 13 #### Payment service #########
identifclusteraimag
Min. :
1 Min. : 1.0 Min. :11.0
1st Qu.: 3203 1st Qu.: 374.0 1st Qu.:11.0
Median : 6406 Median : 754.0 Median :45.0
Mean : 6406 Mean : 733.7 Mean :44.1
3rd Qu.: 9609 3rd Qu.:1088.0 3rd Qu.:65.0
Max. :12811 Max. :1428.0 Max. :85.0
locationMin.
:1.00
1st Qu.:1.00
Median :2.00
Mean
:2.38
3rd Qu.:3.00
Max.
:4.00
q1144
Min. :
0
1st Qu.: 14400
Median : 30000
Mean : 71701
3rd Qu.: 59160
Max. :9000000
NA's :140529
supervisor
Min. : 1.00
1st Qu.: 3.00
Median :45.00
Mean:41.58
3rd Qu.:65.00
Max.
:85.00

item
Min.
: 1
1st Qu.: 4Median : 7
Mean: 7
3rd Qu.:10
Max.
:13

q1142
q1143
Min.
:1.000Min.
:
0
1st Qu.:2.000
1st Qu.:1000
Median :2.000
Median :2500
Mean:1.844Mean:6410
3rd Qu.:2.000
3rd Qu.:4560
Max.
:2.000Max.
:3000000
NA's
:1
NA's
:140527
q1145
quarterinterviewer
Min. :
0 Min. :1.000 Min. : 1.00
1st Qu.:0
1st Qu.:2.000
1st Qu.: 1.00
Median :0 Median :3.000 Median : 2.00
Mean : 1053 Mean :2.562 Mean : 6.51
3rd Qu.:0
3rd Qu.:4.000 3rd Qu.: 5.00
Max. :6000000 Max. :4.000 Max. :34.00
NA's :140529## 14 #### Durable #########
identifclusterMin. :
1 Min. : 1.0
1st Qu.: 3203 1st Qu.: 374.0
Median : 6406 Median : 754.0
Mean : 6406 Mean : 733.7
3rd Qu.: 9609 3rd Qu.:1088.0
Max. :12811 Max. :1428.0
location
Min. :1.00
1st Qu.:1.00
Median :2.00
Mean :2.38
3rd Qu.:3.00

soumMin. : 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.87
3rd Qu.:25.00
Max. :76.00

durable_id
Min. : 1.00
1st Qu.:11.75
Median :22.50
Mean :22.50
3rd Qu.:33.25

aimag
Min. :11.0
1st Qu.:11.0
Median :45.0
Mean :44.1
3rd Qu.:65.0
Max. :85.0
q1201
Min. : 0.0000
1st Qu.: 0.0000
Median : 0.0000
Mean : 0.3757
3rd Qu.: 1.0000

soumMin. : 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.87
3rd Qu.:25.00
Max. :76.00
q1202
Min. : 1.0
1st Qu.: 24.0
Median : 60.0
Mean : 97.1
3rd Qu.: 120.0

Manual Mongolia HSES 2012 Version 2.0

90

Max.

:4.00

Max.

q1203
Min. :
1000
1st Qu.:40000
Median :90000
Mean : 1450801
3rd Qu.:300000Max. :350000000
NA's :388384:44.00Max.

quarterMin. :1.000
1st Qu.:2.000
Median :3.000
Mean :2.562
3rd Qu.:4.000
Max. :4.000:15.0000interviewer
Min. : 1.00
1st Qu.: 1.00
Median : 2.00
Mean : 6.51
3rd Qu.: 5.00
Max. :34.00## 15 #### Non-Food #########
identif
row13
Min.
:
1
Min.
: 2.0
1st Qu.: 3203
1st Qu.:108.0
Median : 6406
Median :210.0
Mean : 6406
Mean
:210.5
3rd Qu.: 9609
3rd Qu.:312.0
Max.
:12811
Max.
:428.0item
Min.
:20101
1st Qu.:20903
Median :21504
Mean:21598
3rd Qu.:22106
Max.
:24309aimag
Min. :11.0
1st Qu.:11.0
Median :45.0
Mean :44.1
3rd Qu.:65.0
Max. :85.0

location
Min. :1.00
1st Qu.:1.00
Median :2.00
Mean :2.38
3rd Qu.:3.00
Max. :4.00

soumMin. : 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.87
3rd Qu.:25.00
Max. :76.00

q1302
Min. :
0
1st Qu.:0
Median :0
Mean :
5240
3rd Qu.:0
Max. :60000000
NA's :3924335
q1305
Min. :
0
1st Qu.:0
Median :
0
Mean
:
360
3rd Qu.:0Max.
:20700000
NA's :3924311

Max.
NA's

:1800.0:388384
supervisor
Min. : 1.00
1st Qu.: 3.00
Median :45.00
Mean :41.58
3rd Qu.:65.00
Max. :85.00

clusterMin.
:
1.0
1st Qu.: 374.0
Median : 754.0
Mean: 733.7
3rd Qu.:1088.0
Max.
:1428.0q1301
Min. :1.000
1st Qu.:2.000
Median :2.000
Mean :1.848
3rd Qu.:2.000
Max. :2.000

q1303
q1304
Min. :
0 Min.
:
0
1st Qu.:10000 1st Qu.:
0Median :24000 Median :0
Mean :
96371 Mean:
3312
3rd Qu.:60000 3rd Qu.:
0
Max. :300000000 Max.
:51000000
NA's :3923395
NA's:3924352
quarterinterviewer
supervisor
Min. :1.000 Min. : 1.00 Min. : 1.00
1st Qu.:2.000 1st Qu.: 1.00 1st Qu.: 3.00
Median :3.000
Median : 2.00
Median :45.00
Mean:2.562Mean: 6.51Mean:41.58
3rd Qu.:4.000
3rd Qu.: 5.00
3rd Qu.:65.00
Max.
:4.000Max.
:34.00Max.
:85.00## 16 #### Urban Diary #########
identifclusteraimag
Min. : 97 Min. : 49.0 Min. :11.00
1st Qu.: 3443 1st Qu.: 669.0 1st Qu.:11.00
Median : 6614 Median : 979.0 Median :11.00
Mean : 6753 Mean : 892.2 Mean :33.43
3rd Qu.: 9785
3rd Qu.:1156.0
3rd Qu.:61.00
Max. :12811 Max. :1428.0 Max. :85.00

soumMin. : 1.000
1st Qu.: 1.000
Median : 1.000
Mean : 7.991
3rd Qu.:16.000
Max. :25.000

Manual Mongolia HSES 2012 Version 2.0

91

location
Min. :1.000
1st Qu.:1.000
Median :1.000
Mean :1.493
3rd Qu.:2.000
Max. :2.000
q1401_2
Min. : 0.0
1st Qu.:0.5
Median : 1.4
Mean: 33.0
3rd Qu.: 5.0
Max. :4600.0
NA's :710691
q1402_2
Min. : 0.0
1st Qu.:0.5
Median : 1.4
Mean : 33.0
3rd Qu.:5.0
Max. :3400.0
NA's :714471
q1403_2
Min. : 0.0
1st Qu.:0.5
Median : 1.5
Mean : 33.7
3rd Qu.:5.0
Max. :4000.0
NA's :713857
quarterMin. :1.000
1st Qu.:2.000
Median :3.000
Mean :2.559
3rd Qu.:4.000
Max. :4.000

row14Min. : 2.00
1st Qu.: 34.00
Median : 73.00
Mean : 72.71
3rd Qu.:108.00
Max. :148.00

item
Min. :10101
1st Qu.:10216
Median :10603
Mean :10592
3rd Qu.:10811
Max. :11305

q1401_1
Min. : 0.0
1st Qu.: 0.1
Median : 1.0
Mean : 26.2
3rd Qu.:3.5
Max. :4600.0
NA's :665933
q1401_3
q1401_4
q1402_1
Min. : 0.0 Min. :0e+00
Min. : 0.0
1st Qu.:0.0
1st Qu.:0e+00
1st Qu.:0.1
Median : 0.0 Median :0e+00
Median : 0.9
Mean
:
0.5
Mean
:1e-01
Mean : 26.2
3rd Qu.: 0.0 3rd Qu.:0e+00
3rd Qu.:3.5
Max. :1500.0 Max. :1e+03
Max. :3400.0
NA's :710757 NA's :710752 NA's :671507
q1402_3
q1402_4
q1403_1
Min. : 0.0 Min. : 0.0 Min. : 0.0
1st Qu.:0.0
1st Qu.:0.0
1st Qu.:0.2
Median : 0.0 Median : 0.0 Median : 1.0
Mean : 0.5 Mean : 0.1 Mean : 27.2
3rd Qu.:0.0
3rd Qu.:0.0
3rd Qu.:3.8
Max. :1800.0 Max. :1100.0 Max. :4000.0
NA's :714598 NA's :714591 NA's :674064
q1403_3
q1403_4
q1404
Min. : 0.0 Min. : 0.0 Min. :0
1st Qu.:0.0
1st Qu.:0.0
1st Qu.: 700
Median : 0.0 Median : 0.0 Median : 1500
Mean : 0.4 Mean : 0.1 Mean : 2274
3rd Qu.:0.0
3rd Qu.:0.0
3rd Qu.: 3000
Max. :1800.0 Max. :1050.0 Max. :80000
NA's :713962 NA's :713946 NA's :668338
interviewer
supervisor
Min. : 1.00 Min. : 1.00
1st Qu.: 2.00
1st Qu.: 2.00
Median : 4.00 Median : 3.00
Mean :10.24 Mean :28.86
3rd Qu.:19.00
3rd Qu.:61.00
Max. :34.00 Max. :85.00## 17 #### Rural Food 7 day #########
identifrow15
itemMin. :
1 Min. : 2.00 Min. :10101
1st Qu.: 3058 1st Qu.: 34.00 1st Qu.:10216
Median : 6298 Median : 73.00 Median :10603
Mean : 5981 Mean : 72.71 Mean :10592
3rd Qu.: 9539
3rd Qu.:108.00
3rd Qu.:10811
Max. :12691 Max. :148.00 Max. :11305

clusterMin. : 1.0
1st Qu.: 249.8
Median : 492.5
Mean : 539.7
3rd Qu.: 732.2
Max. :1392.0

aimag
Min. :21.00
1st Qu.:43.00
Median :62.00
Mean :57.15

q1501
Min. :1.000
1st Qu.:2.000
Median :2.000
Mean :1.864

soumMin. : 4.00
1st Qu.:16.00
Median :28.00
Mean :29.96

location
Min. :3.000
1st Qu.:3.000
Median :3.000
Mean :3.467

Manual Mongolia HSES 2012 Version 2.0

92

3rd Qu.:70.50
Max. :85.00

3rd Qu.:40.00
Max. :76.00

3rd Qu.:4.000
Max. :4.000

q1502
Min. : 0.0
1st Qu.: 0.5
Median :2.0
Mean: 29.9
3rd Qu.:7.0
Max.
:2700.0
NA's :611783
q1506
Min. : 0.0
1st Qu.: 0.0
Median : 0.0
Mean : 0.6
3rd Qu.: 0.0
Max.
:1400.0
NA's :611831

q1503
Min. : 0.0
1st Qu.: 0.1
Median :1.0
Mean: 28.33rd Qu.:4.9
Max.
:2550.0
NA's :611782
quarterMin. :1.000
1st Qu.:2.000
Median :3.000
Mean :2.567
3rd Qu.:4.000
Max.
:4.000q1504
q1505
Min. :
0.0 Min. : 0
1st Qu.:0.5 1st Qu.: 0Median : 780.0
Median :0
Mean: 1268.2
Mean:
1
3rd Qu.: 1800.0
3rd Qu.:0
Max.
:30000.0Max.
:2700
NA's :611776
NA's:611845
interviewer
supervisor
Min. :1.000 Min. :21.00
1st Qu.:1.000 1st Qu.:43.00
Median :2.000
Median :62.00
Mean :1.948 Mean :57.15
3rd Qu.:3.000 3rd Qu.:70.50
Max.
:4.000Max.
:85.00## 18 #### Foodstuffs #########
identifclusteraimag
Min. :
1 Min. : 1.0 Min. :11.0
1st Qu.: 3204 1st Qu.: 374.0 1st Qu.:11.0
Median : 6406 Median : 754.0 Median :45.0
Mean : 6406 Mean : 733.7 Mean :44.1
3rd Qu.: 9608 3rd Qu.:1088.0 3rd Qu.:65.0
Max. :12811 Max. :1428.0 Max. :85.0

3rd Qu.:2.000
Max. :2.000

soumMin. : 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.87
3rd Qu.:25.00
Max.
:76.00location
Min. :1.00
1st Qu.:1.00
Median :2.00
Mean :2.38
3rd Qu.:3.00
Max. :4.00

q1601
q1602
q1603yMin. :1.000 Min. :1.000 Min. :2009
1st Qu.:2.000 1st Qu.:2.000
1st Qu.:2011
Median :2.000 Median :2.000 Median :2012
Mean :1.834 Mean :1.975 Mean :2011
3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2012
Max. :2.000 Max. :2.000 Max. :2012
NA's
:96
NA's
:10723NA's:12758q1603mq1603dq1604
q1605
Min. : 1.000 Min. : 1.00 Min. : 5000 Min. :1.000
1st Qu.: 4.250 1st Qu.: 2.00 1st Qu.: 21000 1st Qu.:1.000
Median : 7.000 Median :15.00 Median : 35000 Median :1.000
Mean : 7.278 Mean :14.09 Mean : 45104 Mean :1.096
3rd Qu.:10.000 3rd Qu.:25.00 3rd Qu.: 60000 3rd Qu.:1.000
Max. :20.000 Max. :30.00 Max. :120000 Max. :2.000
NA's:12757NA's:12757NA's:12758NA's:12759q1606
q1607
quarterinterviewer
Min. :1.000 Min. :1.000 Min. :1.000
Min.
: 1.00
1st Qu.:2.000
1st Qu.:2.000
1st Qu.:2.000
1st Qu.: 1.00
Median :2.000 Median :2.000 Median :3.000
Median : 2.00
Mean :1.865 Mean :1.804 Mean :2.562
Mean : 6.51
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:4.000
3rd Qu.: 5.00
Max. :2.000 Max. :2.000 Max. :4.000
Max. :34.00
NA's :12759 NA's :12760
supervisor
Min. : 1.00

Manual Mongolia HSES 2012 Version 2.0

93

1st Qu.: 3.00
Median :45.00
Mean:41.58
3rd Qu.:65.00
Max.
:85.00## 19 #### Foodout #########
identifclusterMin. :
1 Min. : 1.0
1st Qu.: 3198
1st Qu.: 374.0
Median : 6396 Median : 752.0
Mean : 6401 Mean : 733.4
3rd Qu.: 9605
3rd Qu.:1089.0
Max.
:12811
Max.
:1428.0

aimag
Min. :11.00
1st Qu.:11.00
Median :45.00
Mean :44.15
3rd Qu.:65.00
Max.
:85.00location
Min. :1.000
1st Qu.:1.000
Median :2.000
Mean :2.383
3rd Qu.:3.000
Max. :4.000

q1507
Min. :0.000
1st Qu.:2.000
Median :2.000
Mean :1.872
3rd Qu.:2.000
Max. :2.000

q1509
Min.
:
0
1st Qu.:0
Median :0
Mean : 9502
3rd Qu.:0Max.
:1728000
NA's :22306

item
Min. :22501
1st Qu.:22501
Median :22501
Mean :22501
3rd Qu.:22502
Max. :22502
quarterMin. :1.000
1st Qu.:2.000
Median :3.000
Mean :2.561
3rd Qu.:4.000
Max.
:4.000soum
Min. : 1.00
1st Qu.: 1.00
Median :16.00
Mean :17.88
3rd Qu.:25.00
Max.
:76.00

q1508
Min.
:
0
1st Qu.: 10488
Median : 29050
Mean : 48107
3rd Qu.: 60000
Max. :2359000
NA's:22306
interviewer
supervisor
Min. : 1.000 Min. : 1.00
1st Qu.: 1.000
1st Qu.: 3.00
Median : 2.000 Median :45.00
Mean : 6.494 Mean :41.64
3rd Qu.: 5.000
3rd Qu.:65.00
Max.
:34.000Max.
:85.00## 20 #### Basicvars #########
identifcluster
newaimaglocation
Min. :
1 Min. : 1.0 Min. :11.0
Min. :1.000
1st Qu.: 3204 1st Qu.: 374.0 1st Qu.:11.0
1st Qu.:1.000
Median : 6406 Median : 754.0 Median :45.0
Median :2.000
Mean : 6406 Mean : 733.7 Mean :44.1
Mean :2.411
3rd Qu.: 9608 3rd Qu.:1088.0 3rd Qu.:65.0
3rd Qu.:3.000
Max. :12811 Max. :1428.0 Max. :85.0
Max. :4.000
urban
regionmonth
quarterMin. :1.00 Min. :1.000 Min. : 1.000
Min. :1.000
1st Qu.:1.00 1st Qu.:2.000 1st Qu.: 4.000
1st Qu.:2.000
Median :1.00 Median :3.000 Median : 7.000
Median :3.000
Mean :1.45 Mean :3.081 Mean : 6.687
Mean :2.562
3rd Qu.:2.00 3rd Qu.:5.000 3rd Qu.:10.000
3rd Qu.:4.000
Max. :2.00 Max. :5.000 Max. :12.000
Max. :4.000
stratahhweight
hhsizeaimagsoum
Min.
:1.00
Min.
: 5.056
Min.
: 1.000Min.
: 1.00
1st Qu.:1.00 1st Qu.: 31.911 1st Qu.: 3.000 1st Qu.: 9.00
Median :2.00
Median : 52.942
Median : 4.000
Median :36.00
Mean
:2.17
Mean
: 57.689
Mean: 3.641Mean:38.47
3rd Qu.:3.00 3rd Qu.: 90.987 3rd Qu.: 5.000 3rd Qu.:62.00
Max. :3.00 Max. :194.445 Max. :15.000 Max. :93.00

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5.3 Frequency tables of categorical variables
DATA CHECK OF CATEGORICAL VARIABLES> for(k in 1:20){+ df<-outfiles[[k]]+ cb<-vector(length=ncol(df),mode="list")+ # cb: data frame of codebook+ n<-length(cb)+ if(k>1) {n<- n-1}
+ for(j in 1:n){+ cb[[j]]$varname<-names(df)[j]+ cb[[j]]$varlabel<-attributes(df)$var.labels[j]+ cb[[j]]$vallabel<-(attributes(df)$label.table[attributes(df)$val.labels])[[j]]+ }+ # print+ cat("\n\n","#### FREQUENCY OF VARIABLES IN ",k,":", Rnames[k],+ "#########################################\n\n")+ for(j in 1:length(cb)){+ if(k>=14 & k<=19 & j==2) {next}+ if(k==15 & j==3) {next}+ if(k==17 & j==3) {next}+ if(k==1 & is.element(j,c(60,65))) {next}+ if(length(cb[[j]])==3){ # including value labels+
cat(" -----",j,":",cb[[j]]$varname," :",cb[[j]]$varlabel,"------------------------")+
print(table(outfiles[[k]][j],useNA="ifany"))+ } # end of if+ } # end of for j+ } # end of for k#### FREQUENCY OF VARIABLES IN 1 : Household #########################################----- 5 : aimag : Aimag -----------------------11 21 22 23 41 43 44 45 46
48 61 62 63 64
3578 312 408 504 504 407 309 693 312 600 696 504 312 4088485
312 720----- 7 : location : Location -----------------------1
2
3
43578 3473 3071 2689----- 18 : v1_res : v1_Result -----------------------1
2
3
4
5
6
7
6755 5519 206 202 97
3 29----- 22 : v2_res : Visit 2 Result -----------------------1
2
3
4
5
6
7 <NA>
1086 5509 202 194
70
2
3 5745----- 26 : v3_res : Visit 3 Result -----------------------123456 <NA>
2136 4557 159 152 36
3 5768----- 30 : v4_res : Visit 4 Result -----------------------1
2
4 <NA>
5589 249
2 6971

Manual Mongolia HSES 2012 Version 2.0

65 67
504 600

81 82
408 312

83
408

95

----- 31 : q0701 : Q0701 Raised or Owned Herding,poultry or any animal? --------------1
24693 8118----- 32 : q0707 : Q0707 Has produced animal products past 12m? --------------------1
2 <NA>
4353 340 8118----- 33 : q0715 : Q0715 Agricultural land in past 12 m? -----------------------1
2
960 11851----- 35 : q0717 : Q0717 Has vegetables, fruits in pas 12M -----------------------1
2 <NA>
886
74 11851----- 37 : q0801 : Q0801 Are there household enterprises? -----------------------1
22103 10708----- 39 : q0907 : Q0907 Has any member received money or goods ---------------------1
22433 10378----- 40 : q1001 : Q1001 -----------------------1
23031 9780----- 42 : q1003 : Q1003 -----------------------1
25607 7204----- 47 : q1102 : (11.02) Is main dwelling? -----------------------1
211915 896----- 48 : q1103 : (11.03) Type of Dwellings -----------------------1
2
3
4
5
6
7
8
9
5833 2319 320 3968
9 109 18557
11----- 50 : q1105 : (11.05) Main material of the walls -----------------------12
3
45 <NA>
2064 1687 2739
44 276 6001----- 51 : q1106 : (11.06) Main material of the roof -----------------------1
2
34 <NA>
3062 2703 651 394 6001----- 52 : q1107 : (11.07) Main material of the floor -----------------------1
2
34 <NA>
4476 2010 97 227 6001----- 57 : q1112 : (11.12) Covering of the ceiling -----------------------1
2 <NA>
1643 4301 6867----- 58 : q1113 : (11.13) Covering of the frame -----------------------1
2 <NA>
1632 4312 6867----- 59 : q1114 : (11.14) Main material of the floor -----------------------1
2
3 <NA>
2869 2884 191 6867----- 62 : q1117 : (11.17) Type of ownership -----------------------1
2
3
217 166 12428----- 63 : q1118 : (11.18) How was acquired -----------------------1
2
3
4
5
6
7 <NA>
390 1483 888 4583 4075 623 386 383----- 64 : q1119 : (11.19) Did you borrow any money to acquire -----------------------1
2 <NA>

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961103 8564 3144----- 67 : q1122 : (11.22) What is the main source of heating -----------------------123
452617 425 68 9684 17----- 68 : q1123 : (11.23) Source of electricity -----------------------1
2
3
4
5
6
7
10358
62 215286
28 10421----- 69 : q1124 : (11.24) Electricity resource adequate for operating electricd -------1
211184 1627----- 70 : q1125 : (11.25) Water supply -----------------------1
2
3
4
5
6
7
8
2131 402 4514 1356 2575 1621 176
36----- 72 : q1127 : Household waste disposal -----------------------12
3
46561 3590 2262 398----- 73 : q1128 : What type of toilet do you have -----------------------12
3
42472 227 8642 1470----- 74 : q1129 : Has a telephone -----------------------1
2
3
4
488 11087 684 552----- 79 : q1131 : 1131. Anybody from your household own or exploit land ? --------------1
25544 7267----- 82 : q1133 : 1133. Use internet normally? -----------------------1
23249 9562----- 84 : q1135_1 : 1135_1. Where used internet, at home -----------------------1
2 <NA>
1447 1802 9562----- 85 : q1135_2 : 1135_2. Where used internet, at work -----------------------1
2 <NA>
1444 1805 9562----- 86 : q1135_3 : 1135_3. Where used internet, internet café -----------------------1
2 <NA>
1127 2122 9562----- 87 : q1135_4 : 1135_4. Where used interne, free public accesst ----------------1
2 <NA>
680 2569 9562----- 88 : q1135_5 : 1135_5. Where used internet, other -----------------------1
2 <NA>
231 3018 9562#### FREQUENCY OF VARIABLES IN 2 : Individual #########################################----- 4 : aimag : Aimag -----------------------11
21
22
23
41
43
44
45
46
67
13538 1130 1571 1840 1766 1405 1089 2545
985
1957
81
82
83
84
85
1485 1137 1996 1327 3054----- 6 : location : Location -----------------------1
2
3
4

48

61

62

63

64

65

2174

2684

1827

1161

1445

1792

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9713538 12964 11405 10001----- 10 : q0102 : 1.02 Relationship to head -----------------------1
2
3
4
5
6
7
8
9
10
11
12815 9049 21765 515 782 106 433
40 1969 415
19----- 11 : q0103 : 1.03 Sex -----------------------1
223309 24599----- 15 : q0106 : 1.06 Marital Status -----------------------123456 <NA>
11231 17863 1781 443 601 2602 13387----- 16 : q0107
12
39050 9184
349: 1.07 Spouse ID CODE -----------------------4
5
6
7
8
9
10
11
209
107
73
34
5
3
7
5

12
1

13
2

14
2

98 <NA>613 28264----- 17 : q0108 : 1.08 Father ID CODE -----------------------1
2
3
4
5
6
7
8
9
10
11
12
13
14
99
18273
324
231
107
73
46
27
1
1
4
3
4
1
1 28812----- 18 : q0109 : 1.09 Mother ID CODE -----------------------1
2
3
4
5
6
7
8
9
10
11
12
14
99
3291 18557
740
357
192
93
41
19
8
2
3
1
1 24603----- 21 : q0111 : 1.11 Is HH member? -----------------------1
246648 1260----- 22 : q0201 : 2.01 Is 6 years or more? -----------------------1
2 <NA>
5454 41194 1260----- 23 : q0202 : 2.02 Is answering personally? -----------------------1
2
3
4
5
6
7
9
10 <NA>
1833 3329 169
64
38
15
3
2
1 42454----- 25 : q0204 : 2.04 Highest certificate obtained -----------------------1
2
3
4
5
6
7
8
9 <NA>
1263
35 319 427
39 106
23 516 292 44888----- 26 : q0205 : 2.05 Can read a letter? -----------------------1
2
3 <NA>
2345
76
13 45474----- 32 : q0207 : 2.07 Check age/ between 8-35 years -----------------------1
2 <NA>
40802 5846 1260----- 33 : q0208 : 2.08 Reason never attended school -----------------------1
2 <NA>
19587 21215 7106----- 35 : q0210 : 2.10 Highest certificate obtained -----------------------1
2
3
4
5
6
7
8
9
10 <NA>
5127 6032 8258 11501 1498 2056 2421 3527
354
28 7106----- 36 : q0211 : 2.11 Can read a letter? -----------------------1
2
3 <NA>
8282 2086 788 36752----- 37 : q0212 : 2.12 Are you attending School? -----------------------1
2
34 <NA>
12717 2221 883 24981 7106----- 39 : q0214 : 2.14 Check age/ between 8-35 years -----------------------1
2 <NA>
1504 1600 44804----- 40 : q0215 : 2.15 Reason never attended school -----------------------1
2
3
4
5
6
7
8
9
10
11
12
13 <NA>530 29827
3
16
64 146 276
46
12
12
3
71 46404----- 41 : q0216t : 2.16 Current education TYPE ------------------------

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1
2
3
4 <NA>
9428 338 2890
61 35191----- 43 : q0217 : 2.17 Type of School -----------------------1
2
3 <NA>
11591 1069
57 35191----- 44 : q0218 : 2.18 School Location -----------------------1
2
34 <NA>
5010 3849 3776
82 35191----- 45 : q0219 : 2.19 Place where person lives during school -----------------------12
3
45 <NA>
9050 417 1162 1798 290 35191----- 48 : q0222 : 2.22 Pay tuition? -----------------------1
2 <NA>
3273 9444 35191----- 49 : q0223 : 2.23 -----------------------1
2 <NA>
687 2586 44635----- 50 : q0224 : 2.24 -----------------------1
2
3
4
5
6
7 <NA>
177 451
339
3
1
13 47221----- 59 : q0301 : 3.01 Answering personally? -----------------------1
2 <NA>
20146 26502 1260----- 61 : q0303 : 3.03 Any health problem during past month? -----------------------1
2 <NA>
43617 3031 1260----- 62 : q0304 : 3.04 Health problem (1) -----------------------1
2
3
4
5
6
7 <NA>
1095 336 278
1 392 658 275 44873----- 63 : q0305 : 3.05 Did you seek treatment in past 1 M? -----------------------1
2 <NA>
1855 44793 1260----- 64 : q0306 : 3.06 Why didn't seek treatment? -----------------------0
1
2
3
4
5
6 <NA>
2 192 130 193 460 399 484 46048----- 65 : q0307 : 3.07 Where was treatment provided? -----------------------1
2 <NA>
3117 43531 1260----- 66 : q0308_1 : 3.08 Who provided medical service for your treatment? - First -----123456 <NA>
994 330 167 646 491 489 44791----- 67 : q0308_2 : 3.08 Who provided medical service for your treatment? - Second -----0
1
2
3
4
5
6 <NA>
2751
88
64
34
76
45
58 44792----- 69 : q0310 : 3.10 Have bought medicines in the past M ? -----------------------0
1
2 <NA>
1 2502 615 44790----- 71 : q0312 : 3.12 Have stayed at hospital in past 12 M? -----------------------123456 <NA>
588 721 901 264
7
21 45406----- 72 : q0313 : 3.13 What was the Hospital ? -----------------------123456 <NA>
2016 44971299 45406----- 77 : q0317 : 3.17 -----------------------1
2 <NA>
4902 41744 1262

Manual Mongolia HSES 2012 Version 2.0

99----- 78 : q0318 : 3.18 -----------------------123456 <NA>
1424 1741 1027 645
17
51 43003----- 79 : q0319 : 3.19 -----------------------1
2
34 <NA>
4831
39
15
20 43003----- 83 : q0323 : 3.23 -----------------------1
2 <NA>
5963 40685 1260----- 84 : q0324 : 3.24 -----------------------1
2 <NA>
248 46400 1260----- 85 : q0325 : 3.25 -----------------------1
2 <NA>
266 46382 1260----- 86 : q0401 : 4.01 Respondent 10 yrs or more? -----------------------1
2 <NA>
13562 33084 1262----- 87 : q0402 : 4.02 Answering by himself? -----------------------1
2 <NA>
9288 4275 34345----- 88 : q0403 : 4.03 ID CODE of respondent -----------------------1
2 <NA>
8098 1190 38620----- 89 : q0404 : 4.04 Did you any job for the past 7 days? -----------------------1
2 <NA>
1574 6524 39810----- 90 : q0405 : 4.05 What kind of work was the main job you did? -----------------------1
2
3
4
5
6
7
8 <NA>
489 250
30 39981 22719
79 46334----- 91 : q0406 : 4.06 Any permanent job despite you did no job in last 7 day ---------1
2 <NA>
3132 4966 39810----- 92 : q0407 : 4.07 Main reasong for not doing job in last 7 days -----------------------1
2
3
4
5
6
7
8
9
10
11 <NA>705 1322 188 241
6 384
87
7 144
17
31 44776----- 107 : q0601 : 6.01 -----------------------1
2 <NA>
37703 8941 1264----- 108 : q0602 : 6.02 -----------------------1
2 <NA>
19327 18375 10206----- 110 : q0604 : 6.04 -----------------------1
2 <NA>
17213 20489 10206----- 111 : q0605 : 6.05 -----------------------12
3
45 <NA>
9624 312 4934 140 2204 30694----- 112 : q0606 : 6.06 -----------------------1
2 <NA>
1746 18743 27419----- 113 : q0607 : 6.07 -----------------------1
2
3
4
5
6
7
8 <NA>
170 126 125 176 151 469 189 339 46163----- 114 : q0608 : 6.08 -----------------------1
2 <NA>

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615 18130 29163----- 115 : q0609 : 6.09 -----------------------123456 <NA>
98 220 184
778
28 47293----- 116 : q0610 : 6.10 -----------------------1
2
3
4
5
6
7
8 <NA>
9515 3608 1758 551
64 119 1012 1503 29778----- 117 : q0611 : 6.11 -----------------------1
2 <NA>
922 4701 42285----- 121 : q0615 : 6.15 -----------------------1
2
3
4
5
6
7
8
9 <NA>
140 102 733 4084 406
96 3900 257 9244 28946----- 122 : q0616 : 6.16 -----------------------1
2 <NA>
10903 8062 28943----- 126 : q0618 : 6.18 -----------------------1
2 <NA>
315 10590 37003#### FREQUENCY OF VARIABLES IN 3 : Llivestock #########################################----- 2 : ani_id : animal -----------------------1
2
3
4
5
6
3411 2844 565 3671 3937
70----- 4 : aimag : 2. Aimag -----------------------11 21 22 23 41 43 44 45 46
48 61 62
181 475 1022 832 852 369 392 167 491 1081 312 954
8485
470 1416----- 6 : location : 4. Location -----------------------1
2
3
4
181 1601 4357 8359

63 64
546 81565 67
824 1137

81 82
762 62283778#### FREQUENCY OF VARIABLES IN 4 : Livestock Expenditure ############################----- 2 : exp_id : ani_exp -----------------------1
2
3
4
5
6
7
3211 2633 2149 241 450 239 88----- 4 : aimag : 2. Aimag -----------------------11 21 22 23 41 43 44 45 46
48 61 62
185 267 482 609 659 254 263 178 297 720 305 481
8485
222 1115----- 6 : location : 4. Location -----------------------12
3
4
185 1062 2606 5158

63 64
298 36765
67429 56281 82
484 233#### FREQUENCY OF VARIABLES IN 5 : Product #########################################----- 2 : byprod_id : byprod -----------------------1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
4354 4353 4361 4353 4355 4358 4356 4356 4356 4356 4356 4356 4356 4356 4356 4356 4356

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83
601

101

----- 4 : aimag : 2. Aimag -----------------------11 21 22 23 41 43 44 45 46
48 61 62 63 64 65 67 81 82
83
865 2074 4556 3842 4216 1819 1700 1037 2550 6035 1751 5168 2431 4505 4250 5865 3961 3009 4777
84852210 7429----- 6 : location : 4. LOCATION -----------------------12
3
4865 9010 24701 39474#### FREQUENCY OF VARIABLES IN 6 : Crop #########################################----- 2 : crop_id : crop -----------------------1 2 3 4 5 6 7 8 9 10 11 12 13
659 336 254 156 123 234 29 98 163 51 26 182 42----- 4 : aimag : 2. Aimag -----------------------11 21 22 23 41 43 44 45 46 48 61 62 63 64 65 67 81 82 83 84 85
135 75 32 213 88 354 14 235 26 1 223 53 161 21 41 54 82 35 220 17 273----- 6 : location : 4. Location -----------------------1 2 3 4
135 848 957 413----- 7 : q0719 : 7.19 Did harvest during past 12 M? -----------------------1
2
2352
1

#### FREQUENCY OF VARIABLES IN 7 : Agriultural Expenditure ########################----- 2 : exp_id : exp -----------------------1 2 3 4 5 6 7 8 9 10 11 12 13
886 886 886 886 886 886 886 886 886 886 886 886 886----- 4 : aimag : 2. Aimag -----------------------11 21 22 23 41 43 44 45 46
48 61 62585 273 169 910 767 1287 52 923 78
13 871 338
8485
78 1469----- 6 : location : 4. Location -----------------------1
2
3
4
585 3289 5096 2548

63 64
767 10465 67
338 28681 82
83
507 143 1560#### FREQUENCY OF VARIABLES IN 8 : Enterprise #########################################----- 3 : aimag : 2. Aimag -----------------------11 21 22 23 41 43 44 45 46 48 61 62 63 64 65
714 51 71 61 57 54 50 159 39 109 132 92 48 65 44----- 5 : location : 4. Location -----------------------1 2 3 4
714 890 583 155

67 81
31 106

82
54

83
82

84 85
52 271#### FREQUENCY OF VARIABLES IN 9 : Other income ########################################----- 2 : income_id: income ------------------------

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
12812 12811 12811 12809 12812 12811 12811 12811 12811 12806 12814 12811 12811 12813 12811 12811

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17
18
19
20
21
22
23
24
25
26
12811 12811 12811 12811 12811 12811 12811 12811 12811 12811----- 4 : aimag
11
93028
81
10608

: 2. Aimag ------------------------

21
22
23
41
43
8112 10608 13104 13104 10582
82
83
84
85
8112 10608 8112 18720

44458034 18018

46
48
61
62
8112 15600 18096 13104

63
64
65
67
8112 10608 13104 15600----- 6 : location : 4. Location -----------------------1
2
3
493028 90298 79846 69914----- 7 : q0901 : 9.01 Has anybody received ... -----------------------1
226536 306550#### FREQUENCY OF VARIABLES IN 10 : Remittance #########################################----- 4 : aimag : 2. Aimag -----------------------11 21 22 23 41 43 44 45 46
48 61 62 63 64 65
1051 145 195 131 118 21 105 91 889
28 182 68 23 25
68485
31 158----- 6 : location : 4. Location -----------------------12
3
41051 1033 812 774----- 8 : q0909 : 9.09 Who gave the gift -----------------------1
2
3
4
5
6
7
280 919 35 2266 55 29 86----- 9 : q0910 : 9.10 Purpose of the receipt -----------------------1
2
3
4
5
6
7
8
2639 338 257
55 21025
27 119----- 10 : q0911 : 9.11 From where the gifts -----------------------12
3
451035 1213 734 417 271----- 13 : q0914 : 9.14 Do receive it regularly? -----------------------12345
22 339 131 760 2418

67
39

81
247

82
64

83
53

#### FREQUENCY OF VARIABLES IN 11 : Savings loan #########################################----- 3 : aimag : 2. Aimag -----------------------11 21 22 23 41 43 44 45 46
48 61 62 63 64 65 67 81 82
83
1194 145 225 352 300 191 186 408 156 288 360 272 198 242 171 229 241 147 239
8485
175 586----- 5 : location : 4. Location -----------------------12
3
41194 2076 2019 1016----- 7 : q1005 : 10.05 Kind of loans? -----------------------1
2
3
4
5
6
7
8
9
2492 955 310 381 708 611 460 124 264----- 8 : q1006 : 10.06 Did you get this loan in the past 12 months?
---------1
25464 841----- 10 : q1008 : 10.08 Is it possible for your household to repay the loan in time? ---1
2
3

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103

6116
55 134----- 11 : q1009 : 10.09 Where do you or does any member of this household get this loans? ---1
2
3
4
5
6
7
5945 10336
69 10820
24----- 12 : q1010a : 10.10 What was the loan purpose/function? -----------------------1
2
3
4
5
6
7
8
3399 656 695 106 419 586 43 401----- 13 : q1010b : 10.10 What was the loan purpose/function? -----------------------0
1
2
3
4
5
6
7
8 <NA>
11 206 88 48 32 140 57
14 153 5556----- 14 : q1010c : 10.10 What was the loan purpose/function? -----------------------0
1
2
3
4
5
6
7
8 <NA>
10
19
3
12
7
14
11
1
87 6141#### FREQUENCY OF VARIABLES IN 12 : Energy #########################################----- 3 : aimag: 2. Aimag ------------------------

11
32202
81
3672

23
4536
84
2808

21
2808
82
2808

22
3672
83
3672

41
4536
85
6480

43
3663

44
2781

45
6237

46
2808

48
5400

61
6264

62
4536

63
2808

64
3672

65
4536

67
5400

----- 5 : location : 4. location -----------------------12
3
432202 31257 27639 24201----- 6 : energy_id : Source Number -----------------------1
2
3
4
5
6
7
8
9
12811 12811 12811 12811 12811 12811 12811 12811 12811----- 7 : q1136 : 11.36 Have used the source? -----------------------1
228633 86666----- 8 : q1137 : 11.37 How do you mainly obtain [FUEL]?
-----------------------0
12
34 <NA>
1 5157 12374 311 244 97212#### FREQUENCY OF VARIABLES IN 13 : Payment service #########################################----- 3 : aimag: 2. Aimag ------------------------

11
46514
81
5304

23
6552
84
4056

21
4056
82
4056

22
5304
83
5304

41
6552
85
9360

43
5291

44
4017

45
9009

46
4056

48
7800

61
9048

62
6552

63
4056

64
5304

65
6552

67
7800

----- 5 : location : 4. Location -----------------------1
2
3
446514 45149 39923 34957----- 6 : item : Service Number -----------------------1
2
3
4
5
6
7
8
9
10
11
12
13
12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811----- 7 : q1142 : 1142. Have bought or received free.. during past 12 m? -----------1
2 <NA>
26013 140529
1#### FREQUENCY OF VARIABLES IN 14 : Durable #########################################----- 3 : aimag: 2. Aimag ------------------------

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11
157432
65
22176

21
13728
67
26400

22
17952
81
17952

23
22176
82
13728

41
22176
83
17952

43
17908
84
13728

44
13596
85
31680

45
30492

46
13728

48
26400

61
30624

62
22176

63
13728

64
17952

----- 5 : location : 4. Location -----------------------12
3
4157432 152812 135124 118316----- 6 : durable_id : GOOD NUMBER -----------------------1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811
33
34
35
36
37
38
39
40
41
42
43
44
12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811 12811#### FREQUENCY OF VARIABLES IN 15 : Non-Food #########################################----- 5 : aimag
111291658631126322111263264147288: 2. Aimag ------------------------

22
14728865
18194423
1819446721660041
1819448114728843146927821126324411154983147288452501738411263246112632
85259920482166006125125662
181944----- 7 : location : 4. Location -----------------------12
3
41291658 1253753 1108631 970729----- 8 : q1301 : 1301. Have you bought or received for the last 12 Ms ---------------1
2701349 3923422#### FREQUENCY OF VARIABLES IN 16 : Urban Diary #########################################----- 3 : aimag
11440094
65
14760

21
14760
67
14760

22
14760
81
14760

: 2. Aimag -----------------------23
14760
82
14760

41
14760
83
14760

43
14637
84
14760

44
14391
85
29520

45
73431

46
14760

48
14760

61
73800

62
14760

63
14760

64
14760

----- 5 : location : 4. Location -----------------------1
2440094 427179#### FREQUENCY OF VARIABLES IN 17 : Rural Food 7 day #########################################----- 5 : aimag: 2. Aimag ------------------------

21
22
23
41
43
44
45
46
48
61
62
63
64
65
67
81
23616 35424 47232 47232 35424 23616 11808 23616 59040 11808 47232 23616 35424 47232 59040 35424
82
83
84
85
23616 35424 23616 59040----- 7 : location : 4. Location -----------------------3
4377733 330747#### FREQUENCY OF VARIABLES IN 18 : Foodstuffs #########################################----- 3 : aimag: 2. Aimag ------------------------

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105

11 21 22 23 41 43 44 45 46
48 61 623578 312 408 504 504 407 309 693 312 600 696 5048485
312 720----- 5 : location : 4. Location -----------------------1
2
3
43578 3473 3071 2689----- 6 : q1601 : (16.01) -----------------------1
2 <NA>
2115 10600
96----- 7 : q1602 : (16.02) -----------------------1
2 <NA>
53 2035 10723----- 12 : q1605 : (16.05) -----------------------1
2 <NA>
47
5 12759----- 13 : q1606 : (16.06) -----------------------1
2 <NA>
7
45 12759----- 14 : q1607 : (16.07) -----------------------1
2 <NA>
10
41 12760

63 64
312 40865 67
504 600

81 82
408 31283408#### FREQUENCY OF VARIABLES IN 19 : Foodout #########################################----- 3 : aimag : 2. Aimag -----------------------11
21
22
23
41
43
44
45
46
48 61 627114 624 816 1008 1008 814 618 1386 624 1199 1392 10088485
624 1439----- 5 : location : 4. Location -----------------------12
3
47114 6944 6142 5378----- 6 : item : item -----------------------22501 22502
12811 12767----- 7 : q1507 : -----------------------0
1
2
6 3265 22307

63 64 65 67
624 816 1008 1200

81 82
816 62483816#### FREQUENCY OF VARIABLES IN 20 : Basicvars #########################################----- 3 : newaimag : New code of aimag -----------------------11 21 22 23 41 43 44 45 46
48 61 62 63 64
3578 312 408 504 504 407 309 693 312 600 696 504 312 4088485
312 720----- 4 : location : Strata 4 locations -----------------------1
2
3
43578 3473 2672 3088----- 5 : urban : Urban/rural -----------------------1
2
7051 5760----- 6 : region : Region ------------------------

Manual Mongolia HSES 2012 Version 2.0

65 67
504 600

81 82
408 312

83
408

106

1
2
3
4
5
2160 3024 2825 1224 3578

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107

5.4 Consistency check of identifierFound no unmatched household identifier “identif”.

> HHID<-outfiles[[1]]$identif> length(HHID)[1] 12811> for(j in 1:20) cat("\n",j,":",sum(!is.element(outfiles[[j]]$identif,HHID)))
1 : 0
2 : 0
3 : 0
4 : 0
5 : 0
6 : 0
7 : 0
8 : 0
9 : 0
10 : 011 : 012 : 013 : 014 : 0
15 : 0
16 : 017 : 018 : 019 : 020 : 0Manual Mongolia HSES 2012 Version 2.0

108Chapter 6. Household Income
6.1 Results of household income

According to the Mongolian NSO’s database of www.1212.mn, the monthly average income
per household in 2012 is as the next.
Type of income
Total revenue

2012
819,996.

1. Monetary income - Total

741,917.

Wages and salaries

372,114.

Pensions and allowance

155,686.

Income from household businesses *145,740.

Other

68,377.

Received from others free of charge

31,967.

Foodstuff, which consumed from private farm or enterprise

46,112.

http://www.1212.mn/tables.aspx?tbl_id=DT_NSO_1900_001V2&SOUM_select_all=0&S
OUMSingleSelect=_0&HSES1_select_all=0&HSES1SingleSelect=&YearY_select_all=0&YearYSingleSelect=_2012_2011_2010&viewtype=table(accessed on 13 November 2018)


Remarks: Income from household businessAccording to the delegates from Mongolia to the workshop, income from business inthe above table includes;
Income from livestock products

Income from agriculture / crop products/

Income from non-agricultural production and services

Manual Mongolia HSES 2012 Version 2.0

109Manual Mongolia HSES 2012 Version 2.0

110



Also the metadata is provided on the web as follows;

Manual Mongolia HSES 2012 Version 2.0

111



Generated household-level monthly income data for each income component.

6.2 Wage income
Data frame: 02 Individual (HSES 2012)
Variables from questionnaire/codebook
q0616: Do you receive any salary in cash and/or in kind?
q0617_1: Salary amount in the past monthq0617_2: Salary amountin the past12 months
q0617_3: Bonuses and special allowances (12M)q0618: Did you any another job for the past 12 months?
q0619_1: Salary amount in the past monthq0619_2: Salary amountin the past 12 months
q0619_3: Bonuses and special allowances (12M)
Note: The wage questions of HSES 2012 are different from questionnaire HSES 2010.

> d<-outfiles[[2]]> dim(d)[1] 47908
129> colnames(d)[1] "identif"[6] "location"[11] "q0103"[16] "q0107"[21] "q0111"[26] "q0205"[31] "q0206_5"[36] "q0211"[41] "q0216t"[46] "q0220"[51] "q0225"[56] "q0226_5"[61] "q0303"[66] "q0308_1"[71] "q0312"[76] "q0316"[81] "q0321"[86] "q0401"[91] "q0406"[96] "q0504"[101] "q0509"[106] "q0514"[111] "q0605"[116] "q0610"[121] "q0615"[126] "q0618"# 02_indiv"ind_id""quarter""q0104""q0108""q0201""q0206_1""q0207""q0212""q0216g""q0221""q0226_1""q0226_6""q0304""q0308_2""q0313""q0317""q0322""q0402""q0407""q0505""q0510""q0601""q0606""q0611""q0616""q0619_1""cluster""aimag""interviewer" "supervisor""q0105y""q0105m""q0109""q0110a""q0202""q0203""q0206_2""q0206_3""q0208""q0209""q0213""q0214""q0217""q0218""q0222""q0223""q0226_2""q0226_3""q0226_7""q0301""q0305""q0306""q0309""q0310""q0314a""q0314b""q0318""q0319""q0323""q0324""q0403""q0404""q0501""q0502""q0506""q0507""q0511""q0512""q0602""q0603""q0607""q0608""q0612""q0613""q0617_1""q0617_2""q0619_2""q0619_3"

Manual Mongolia HSES 2012 Version 2.0"soum""q0102""q0106""q0110""q0204""q0206_4""q0210""q0215""q0219""q0224""q0226_4""q0302""q0307""q0311""q0315""q0320""q0325""q0405""q0503""q0508""q0513""q0604""q0609""q0614""q0617_3"

112



10,903 household members received any salary, and 315 did another job.

> table(d$q0616,useNA="always")1
2 <NA>
10903 8062 28943> table(d$q0618,useNA="always")1
2 <NA>
315 10590 37003


The data shows that q0617_1 is monthly and q0617_2 is annual.

> d2<-subset(d,q0616==1&q0618==1)> head(d2[,122:129])
q0616 q0617_1 q0617_2 q0617_3 q0618 q0619_1 q0619_2 q0619_3
798
1 196000 1350000 230000
10 1000000
0866
1 320000 3840000 280000
1 145000 1740000
01025
1 140400 1684800
0
1 140400 1263600
01099
1 221000 2652000 353600
1
0 1250000
01219
1 200000 2400000
01 360000 4320000
01262
1 490000 5880000
010 1000000
0Regarding two reference periods: last month and last year, the HSES 2010 survey report
describes as follows for non-food consumption (at page 69);

“In this case information was taken from the last month if available, and if thehousehold did not purchase anything in the last 30 days, information on the last year
will be considered.”# Estimated monthly wage at each record level> d3<-d[c(1:2,122:129)]> dim(d3)[1] 47908
10> head(d3)identif ind_id q0616 q0617_1 q0617_2 q0617_3 q0618 q0619_1 q0619_2 q0619_3
1
1
1
2
NA
NA
NA
NA
NA
NA
NA
2
1
2
2
NA
NA
NA
NA
NA
NA
NA
3
1
3
NA
NA
NA
NA
NA
NA
NA
NA
4
2
1
NA
NA
NA
NA
NA
NA
NA
NA
5
2
2
1 250000 3000000
0
2
NA
NA
NA
6
2
3
NA
NA
NA
NA
NA
NA
NA
NA
>d3[is.na(d3)]<-0# wage1: primary job> d3$wage1<-ifelse(d3$q0617_1>0, d3$q0617_1, d3$q0617_2/12)> d3$wage1<-d3$wage1+d3$q0617_3/12

Manual Mongolia HSES 2012 Version 2.0

113# wage2: secondary job> d3$wage2<-ifelse(d3$q0619_1>0, d3$q0619_1, d3$q0619_2/12)> d3$wage2<-d3$wage2+d3$q0619_3/12# wage3: total> d3$wage3<-d3$wage1+d3$wage2> head(d3[d3$wage2>0,])
identif ind_id q0616 q0617_1 q0617_2 q0617_3 q0618 q0619_1 q0619_2
798
197
1
1 196000 1350000 230000
10 1000000
866
212
2
1 320000 3840000 280000
1 145000 1740000
1025
251
2
1 140400 1684800
0
1 140400 1263600
1099
273
1
1 221000 2652000 353600
1
0 1250000
1219
305
2
1 200000 2400000
01 360000 4320000
1262
314
1
1 490000 5880000
010 1000000
q0619_3
wage1
wage2
wage3
798
0 215166.7 83333.33 298500.0866
0 343333.3 145000.00 488333.3
1025
0 140400.0 140400.00 280800.01099
0 250466.7 104166.67 354633.3
1219
0 200000.0 360000.00 560000.01262
0 490000.0 83333.33 573333.3# Number of wage earners within the household> addmargins(table(tapply(d3$wage1,d3$identif,function(x) sum(x>0))))
0
1
2
3
4
5
6
7
Sum
5547 4192 2632
355
71
12
1
1 12811Aggregated at household level Generated function to aggregate at household level> CollapseBy<-function(df,hhid,cols,ID=NULL){+ # Version 2_20161217+ # To aggregate variables assigned by cols in data frame df at hhid level+ # df: data frame+ # hhid: household variable+ # cols: variables to be aggregated+ # HHID: household id codes to be matched, or+ #unique(df$hhid) if not specified++ if(is.numeric(hhid)){ hhid<-colnames(df)[hhid] }+ if(is.numeric(cols)){ cols<-colnames(df)[cols] }+ if(!missing(ID)) { y<-data.frame(ID,row.names=NULL)+ }else{ y<-data.frame(unique(df[,hhid]),row.names=NULL) }+ colnames(y)<-hhid+ for(j in cols){+ t<-aggregate(df[,j],list(df[,hhid]),sum,na.rm=T)+ colnames(t)<-c(hhid,j)+ y<-merge(y,t,by=hhid,all.x=T)+ }Manual Mongolia HSES 2012 Version 2.0

114+ y[is.na(y)]<-0+ return (y)+ }> HHID<-outfiles[[1]]$identif # 1-12811> length(HHID)[1] 12811> df<-CollapseBy(d3,"identif","wage3",HHID)> dim(df)[1] 12811
2> head(df)identif wage3
1
1
0
2
2 250000
3
3
0
4
4
0
5
5
0
6
6
0
> df<-merge(df,outfiles[[20]][c("identif","hhweight")])> dim(df)[1] 12811
3> head(df)identif wage3 hhweight1
1
0 65.01397
2
2 250000 65.01397
3
3
0 65.01397
4
40 65.01397
550 65.01397
6
6
0 65.01397> round(weighted.mean(df$wage3,df$hhweight))[1] 380021
Remarks:
Monthly average wage income in 2012 is 372,114 in the statistical table of NSO’s website.
> hhinc<-df> save(hhinc,outfiles,STATA.files,CollapseBy,file="hhinc.RData")#################################################### Bonus, etc#q0617_3: Bonuses and special allowances (12M)#q0619_3: Bonuses and special allowances (12M)> d[is.na(d)]<-0> d$bonus<-(d$q0617_3+d$q0619_3)/12> head(d[d$q0617_3>0&d$q0619_3>0,c(1,130,125,129,131)])
identif
PID q0617_3 q0619_3
bonus

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115

33419
42553

8911 891101 2000000
11388 1138801 2700000

1e+06 250000.0
7e+05 283333.3> df<-CollapseBy(d,"identif","bonus",HHID)> dim(df)[1] 12811
2> df<-merge(df,outfiles[[20]][c("identif","hhweight")])> round(weighted.mean(df$bonus,df$hhweight))[1] 6561



SummaryMonthly wage income of 372 thousand Riels in the Report may not include bonuses.

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116

6.3 Pension (OTHER INCOME)
data file: 09 Other income
income_id: 1 to 26# income_id number of HSES 20121

State pension

2

Special Pension

3

Unemployment benefit

4

Maternity benefits

5

Disability pension

6

Survivor pension

7

Illness payments

8

Funeral payments

9

Human development fund allowances (received in cash)

10

Human development fund allowances (transferred to account)

11

Human development fund allowances (student, superiority, other)

12

Mother benefit

13

Student benefit

14

Other social benefit

15

Rent of own assets (land, buildings, ve

16Sale of assets

17

Inheritances and wedding presents

18

Loan repayments

19

Withdrawals from bank savings

20

Income from other sourses

21

savings?

22

Dividends?

23

Loan?

24

Treasury Bond?

25

Gambling, lottery and contest

26

Other income (from intellectual propert# Average amount of other income by income_id> d<-outfiles[[9]]> dim(d)[1] 333086
20

Manual Mongolia HSES 2012 Version 2.0

117> length(unique(d$identif))[1] 12811> d[is.na(d)]<-0> d$pension<-round(rowSums(d[,seq(9,17,by=2)])/12) # sum of person 1 to 5
> head(d[d$pension>0,])
identif income_id cluster aimag soum location q0901 q0902_ic q0902_t
9
1
9
1
65
13
4
1
1 252000
35
2
9
1
65
13
3
1
1 252000
61
3
9
1
65
13
4
1
1 252000
87
4
9
1
65
13
3
1
1 252000
113
5
9
1
65
13
4
1
1 252000
139
6
9
1
65
13
4
1
1 252000
q0903_ic q0903_t q0904_ic q0904_t q0905_ic q0905_t q0906_ic q0906_t
92 252000
0
0
0
0
0
0
35
2 252000
3 252000
4 25200000612 252000
3 252000000087
2 252000
3 252000
4 25200000113
2 252000
3 252000
4 252000
5 252000139
2 252000
3 252000
4 252000
98 504000
quarter interviewer supervisor pension
9
1
3
65
42000
35
1
3
65
84000
61
1
3
65
63000
87
1
3
65
84000
113
1
3
65 105000
1391
3
65 126000# Aggregate pension at household level by income_id> t<-tapply(d$pension,list(d$identif,d$income_id),sum)> dim(t)[1] 12811
26> colnames(t)[1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14"[15] "15" "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26"> head(t)1 2 3 4 5 6 7 8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
1 0 0 0 0 0 0 0 0 42000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
2 0 0 0 0 0 0 0 0 84000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
3 0 0 0 0 0 0 0 0 63000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
4 0 0 0 0 0 0 0 0 84000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
5 0 0 0 0 0 0 0 0 105000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
6 0 0 0 0 0 0 0 0 126000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0> tail(t)1 2 3 4 5 6 7 8
9 10
11
12
13 14 15 16 17 18
1912806 155833 0 0 0 0 0 0 0 47967 0 55000 8333
0 0 0 0 0 0012807
0 0 0 0 0 0 0 0 54633 000
0 0 0 0 0 0 1000000
12808 205833 0 0 0 0 0 0 0 98942 0 96667 8333 29167 0 0 0 0 00Manual Mongolia HSES 2012 Version 2.0

118

12809
0 0 0 0 0 0 0 0 41300
12810
0 0 0 0 0 0 0 0 37858
12811 155833 0 0 0 0 0 0 0 41300
20 21 22 23 24 25 26
12806 0 0 0 0 0 0 012807 0 0 0 0 0 0 012808 0 0 0 0 0 0 012809 0 0 0 0 0 0 012810 0 0 0 0 0 0 012811 0 0 0 0 0 0 0

0
0
0
0
0
0
0
0
0 55000 8333 40833

0
0
0

0
0
0

0
0
0

0
0
0

# Average monthly income by income_id> tt<-apply(t,2,function(x) weighted.mean(x,hhinc$hhweight))> round(tt)
1
2
3
4
5
6
7
8
9
10
11
56850
196
105
NA 11107 2357
882
185 61658
NA 12352
13
14
15
16
17
18
19
20
21
22
23
2918 1156 4663 15297
501
575 12258 3262 1533
647
83
25
26
129
362
> tt[is.na(tt)]<-0> sum(tt)[1] 191077.2

0
0
0

0
458333
0

12
1859
24
144

[1] "State pension"[2] "Special Pension"[3] "Unemployment benefit"[4] "Maternity benefits"[5] "Disability pension"[6] "Survivor pension"[7] "Illness payments"[8] "Funeral payments"[9] "Human development fund allowances (received in cash)"[10] "Human development fund allowances (transferred to account)"[11] "Human development fund allowances (student, superiority, other)"[12] "Mother benefit"[13] "Student benefit"[14] "Other social benefit"[15] "Rent of own assets (land, buildings, vehicles, equipment)"[16] "Sale of assets"[17] "Inheritances and wedding presents"[18] "Loan repayments"[19] "Withdrawals from bank savings"[20] "Income from other sources"[21] "Savings?"[22] "Dividends?"[23] "Loan?"[24] "Treasury Bond?"[25] "Gambling, lottery and contest"

Manual Mongolia HSES 2012 Version 2.0

119[26] "Other income (from intellectual property & other)"> data.frame(Income_item=names(a),Income=as.integer(tt),row.names=NULL)
Income_item Income
1
State pension 56849
2
Special Pension
195
3
Unemployment benefit
104
4
Maternity benefits
05Disability pension 11107
6
Survivor pension
2357
7
Illness payments
882
8
Funeral payments
184
9
Human development fund allowances (received in cash) 61657
10
Human development fund allowances (transferred to account)0
11 Human development fund allowances (student, superiority, other) 12351
12
Mother benefit
1858
13
Student benefit
2917
14
Other social benefit
1156
15
Rent of own assets (land, buildings, vehicles, equipment)
4662
16
Sale of assets 15296
17
Inheritances and wedding presents
500
18
Loan repayments575
19
Withdrawals from bank savings 12257
20
Income from other sources
3262
21
Savings?
1533
22
Dividends?
646
23
Loan?
83
24
Treasury Bond?
144
25
Gambling, lottery and contest
128
26
Other income (from intellectual property & other)361

Sum of income_id from 1 to 14 is almost the same as the results table.

> round(sum(tt[1:14]))[1] 151624> round(sum(tt[15:20]))[1] 36556> round(sum(tt[21:26]))[1] 2897# Generated variables of subtotal at household-level dataframe> s<-data.frame(t)> s$oi0114<-rowSums(s[1:14])> s$oi1520<-rowSums(s[15:20])> s$oi2126<-rowSums(s[21:26])> head(s[s$oi1520>0&s$oi2126,])

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120

X1 X2 X3
X4 X5 X6 X7 X8
X9 X10
X11X12
X13 X14 X15
931 285300 0 0
0 0 0 0 0 41300
0
0
0
0
0
0
1000 210600 0 0
0 0 0 0 0 42000
00 200000001002
0 0 0 26000 0 0 0 0 84000
0
0
0
0
0
0
1006
0 0 0
0 0 0 0 0 168000
00 200000001011 140000 0 0
0 0 0 0 0 21000
0
0
0
0
0
0
1022
0 0 0
0 0 0 0 0 84000
0 41667
0 11667
00
X16 X17 X18
X19 X20
X21 X22X23 X24
X25 X26 oi0114 oi1520
931 833333
0
0
0
0
0
0
0
0 391667
0 326600 833333
1000
000 66667
0 4583000
00 272600 66667
1002
00
0 41667
0 20000000
0
0 110000 41667
1006
00
0 83333
0 21667000
00 188000 83333
1011
000 50000 10000000
00 161000
5000
1022
0
0
0 33333
0 16667
0 16667000 137334 33333
oi2126931 391667
1000
4583
1002 20000
1006 21667
1011 10000
1022 33334> hhinc.save<-hhinc> hhinc<-cbind(hhinc,s[27:29])> str(hhinc)'data.frame':
12811 obs. of 6 variables:$ identif : int 1 2 3 4 5 6 7 8 9 10 ...
$ wage3: num 0 250000 0 0 0 0 200000 0 250000 0 ...
$ hhweight: num 65 65 65 65 65 ...
$ oi0114 : num 42000 84000 63000 84000 105000 ...
$ oi1520 : num 0 0 0 0 0 0 0 0 0 0 ...
$ oi2126 : num 0 0 0 0 0 0 0 0 0 0 ...
> head(hhinc)identif wage3 hhweight oi0114 oi1520 oi2126
1
1
0 65.01397 42000
0022 250000 65.01397 84000
003
30 65.01397 63000
004
4
0 65.01397 84000
005
50 65.01397 105000
006
6
0 65.01397 126000
00> hhinc[is.na(hhinc)]<-0> round(apply(hhinc[c(2,4:6)],2,function(x) weighted.mean(x,hhinc$hhweight)))
wage3 oi0114 oi1520 oi2126
380021 155493

36556

2897

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121

6.4 Income from livestock
Data frame: 03 Livestock
ani_id: animal number
q0702_1: total number of animals
q0702_2: number of female
q0702_3: number of young
q0703: use for own foodq0704: number of sold
q0705: amount received> d<-outfiles[[3]]> dim(d)[1] 14498
15> head(d[!is.na(d$q0705),])
identif ani_id cluster aimag soum location q0702_1 q0702_2 q0702_3 q0703 q0704 q0705
1
1
1
1
65 13
4
41
12
8
1
0
0
2
1
2
1
65
13
4
12
4
1
0
0
0
3
1
4
1
65 13
4
60
30
20
10
0
0
4
1
5
1
65 13
4
80
50
30
10
0
0
5
2
1
1
65
13
3
60
19
11
1
0
0
6
2
2
1
65 13
3
40
11
5
1
0
0
quarter interviewer supervisor
1
1
3
65
2
1
3
65
3
1
3
65
4
1
3
65
5
1
3
65
6
1
3
65



The number of households with animals is 4,675.

> nrow(subset(d,q0702_1>0))[1] 14495> length(unique(subset(d,q0702_1>0)$identif))[1] 4675



Number of sample households by herding animal> t<-addmargins(table(d$ani_id,useNA="ifany"))> names(t)<-c("Cattle","Horse","Camel","Sheep","Goat","Other","Total")> tCattle Horse Camel Sheep
Goat Other Total
3411
2844
565
3671
3937
70 14498
Aggregated q0705 (amount received) at household-level.

> df<-CollapseBy(d,"identif","q0705",HHID)> dim(df)Manual Mongolia HSES 2012 Version 2.0

122[1] 12811

2> df$revenue<-round(df$q0705/12)> dim(df)[1] 12811
3> head(df)identifq0705 revenue
1
1
0
0
2
2 1400000 116667
3
3 1100000
91667
4
4
0
0
5
5 95000079167
6
6 5970000 497500# Monthly revenue

Data frame: 04 Livestock_exp
exp_id: exp number 1-7
q0706: expenditure on this herding activity in the last 12 months> d<-outfiles[[4]]> dim(d)[1] 9011
10> head(d)identif exp_id cluster aimag soum location q0706 quarter interviewer supervisor
1
1
1
1
65
13
4 50000
1
3
65
2
1
2
1
65
13
4 50000
1
3
65
3
2
1
1
65
13
3 40000
1
3
65
4
2
2
1
65
13
3 110000
1
3
65
5
2
3
1
65
13
3 240000
1
3
65
6
3
1
1
65
13
4 30000
1
3
65> addmargins(table(d$exp_id))
1
2
3
4
5
6
7 Sum
3211 2633 2149 241 450 239
88 9011> df<-merge(df, CollapseBy(outfiles[[4]],"identif","q0706",HHID),by="identif")> dim(df)[1] 12811
4> df$cost<-round(df$q0706/12) # Monthly cost
> dim(df)[1] 12811
5> head(df)identifq0705 revenue q0706 cost1
1
00 100000 8333
22 1400000 116667 390000 32500
33 1100000
91667 80000 6667
4
4
0
0
0
0
5
5 950000
79167 160000 13333
66 5970000 497500 100000 8333

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123Remarks:
There are cases without revenue but with positive cost.
> table(df$revenue==0&df$cost>0)
FALSE TRUE
10788 2023

Data frame: 05 Product (by-product)
byprod_id: 1-17
q0709: total quantity of production
q0710: quantity consumed by household
q0711: quantity sold as raw material
q0712: total amount received from sales
q0713: quantity produced and sold
q0714: total amount received from produced and sold> d<-outfiles[[05]]> dim(d)[1] 74050
16> head(d)identif byprod_id cluster aimag soum location q0708 q0709 q0710 q0711
q0712 q0713
1
1
1
1
65
13
4
60
60
0
60
42000
0
2
1
2
1
65
13
4
0
NA
NA
NA
NA
NA
3
1
3
1
65
13
4
80
16
0
16 1120000
0
4
1
4
1
65
13
4
0
NA
NA
NA
NA
NA
5
1
5
1
65
13
4
NA
10
0
10
50000
0
6
1
6
1
65
13
4
NA
10
0
10
70000
0
q0714 quarter interviewer supervisor
1
0
1
3
65
2
NA
1
3
65
3
0
1
3
65
4
NA
1
3
65
5
0
1
3
65
6
0
1
3
65
> df<-merge(df, CollapseBy(outfiles[[5]],"identif",c("q0712","q0714"),HHID),+ by="identif")> dim(df)[1] 12811
7> head(df)identifq0705 revenue q0706 cost
q0712
q0714
1
1
0
0 100000 8333 1304000 1500000
22 1400000 116667 390000 32500 2754000
033 1100000
91667 80000 6667 635000 900000
4
4
0
0
0
0
0
0
5
5 950000
79167 160000 13333 1468000 1900000
66 5970000 497500 100000 8333 1603000 2500000> df$byprod<-round((df$q0712+df$q0714)/12)# Monthly by-product

Manual Mongolia HSES 2012 Version 2.0

124> df$livestock<-df$revenue-df$cost+df$byprod # Monthly livestock income> head(df)identif q0505 revenue q0506 cost q0512
q0514 byprod livestock
1
1 0e+00
0 15000 1250 125000
0 104179167
2
2 7e+05
58333 81000 6750 626000 300000 77167
1287503
3 0e+00
0 12000 1000 16000
0
1333
333
4
4 0e+00
0 29000 2417 780000 270000 87500
85083
55 0e+00
000 67000
0
5583
5583
6
6 0e+00
0 80000 6667 106000 1200000 108833
102166> livestock<-df> apply(livestock,2,function(x) round(weighted.mean(x,hhinc$hhweight)))
identif
q0705
revenue
q0706
cost
q0712
q0714
6421
38389431991
13475011229
38229717327
livestock
54064

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byprod33302

125

6.5 Agricultural (Crop) income
Data frame: 06 crop
crop_id: 1-13
q0719: Did harvest during past 12 months
q0720: total harvest during past 12 months
q0721: quantity consumed by own household
q0722: quantity used for animal feed
q0723q: quantity sold (kg)q0723t: total amount sold (MNT)> d<-outfiles[[6]]> dim(d)[1] 2353
15> head(d)identif crop_id cluster aimag soum location q0719 q0720 q0721 q0722 q0723q
1
12
1
6
65
13
3
1
500
100
0
400
2
12
3
6
65
13
3
1
50
10
0
40
3
12
4
6
65
13
3
1
30
10
0
20
4
12
6
6
65
13
3
1
25
5
0
20
5
23
1
11
65
13
3
1
100
100
0
0
6
50
1
28
65
40
3
1 2000500
01500
q0723t quarter interviewer supervisor
1 200000
1
365
2 24000
1
365
3 16000
1
3
65
4 20000
1
3
65
5
0
1
2
65
6 9000001
2
65

The data set is only for harvesting crops with one exception.

> table(d$q0719)
1
2
2352
1



The number of sample households harvesting crops is 805.

> length(unique(d$identif))[1] 874
The number of households by harvesting crop

> t<-table(d$crop_id)
> t
1
2
3
4
5
6
659 336 254 156 123 234

7
29

8
9
98 163

10
51

11 12
26 182

13
42

Manual Mongolia HSES 2012 Version 2.0

126> names(attributes(d)$label.table["crop_id"][[1]])[1] "Potatoes" "Carrots" "Turnip""Cabbage" "Beetroot" "Onion"[7] "Garlic""Tomatoes" "Cucumber" "Fruits""Wheat""Haylage"[13] "Other"> names(t)<-names(attributes(d)$label.table["crop_id"][[1]])> tPotatoes Carrots
Turnip Cabbage Beetroot
Onion
Garlic Tomatoes
659
336
254
156
123
234
29
98
CucumberFruitsWheat Haylage
Other
163
51
26
182
42


Aggregated q0723t at household level.

> df<-CollapseBy(d,"identif","q0723t",HHID)> dim(df)[1] 12811
2> df$revenue<-round(df$q0723t/12) # Monthly revenue> head(df[df$revenue>0,])
identif q0723t revenue
12
12 260000
21667
50
50 900000
75000
55
55 538000
44833
148
148 120000
10000
167
167 300000
25000
170
170 200000
16667

Data frame: 07 agric_exp
exp_id: 1-13
q0724: total expenditure on item during past 12 months> d<-outfiles[[7]]> dim(d)[1] 11518
10> head(d)identif exp_id cluster aimag soum location q0724 quarter interviewer
1
12
1
6
65
13
3 60000
1
3
2
12
2
6
65
13
3
0
1
3
3
12
3
6
65
13
3
0
1
3
4
12
4
6
65
13
3
0
1
3
5
12
5
6
65
13
3
0
1
3
6
12
6
6
65
13
3
0
1
3
supervisor
1
65
2
65
3
65
4
65
5
65
6
65

Manual Mongolia HSES 2012 Version 2.0

127> table(d$exp_id)
1
2
3
4
5
6
7
8
9 10 11 12 13
886 886 886 886 886 886 886 886 886 886 886 886 886


The number of unique household is 886.

> length(unique(d$identif))[1] 886The number of records with positive value of q0724 is 1,693.

> table(d$q0724>0)
FALSE TRUE
9825 1693


Aggregated q0724 at household level.

> df<-merge(df,CollapseBy(d,"identif","q0724",HHID),by="identif")> dim(df)[1] 12811
4> df$cost<-round(df$q0724/12) # Monthly cost
> df$crop<-df$revenue-df$cost # Monthly crop income> head(df[df$revenue>0,])
identif q0723t revenue q0724 cost crop12
12 260000
21667 60000 5000 16667
50
50 900000
75000 210000 17500 57500
55
55 538000
44833 100000 8333 36500
148
148 120000
10000 220000 18333 -8333
167
167 300000
25000 80000 6667 18333
170
170 200000
16667 28000 2333 14334> table(df$crop<0)
FALSE
12307


TRUE
504

Replaced negative crop income with zero.

> df$crop2<-ifelse(df$crop<0,0,df$crop)> head(df[df$revenue>0,])
identif q0723t revenue q0724 cost crop crop2
1212 260000
21667 60000 5000 16667 16667
50
50 900000
75000 210000 17500 57500 57500
55
55 538000
44833 100000 8333 36500 36500
148
148 120000
10000 220000 18333 -8333
0
167
167 300000
25000 80000 6667 18333 18333
170
170 200000
16667 28000 2333 14334 14334> crop<-df

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128> apply(crop,2,function(x) round(weighted.mean(x,hhinc$hhweight)))
identif q0723t revenue
q0724
cost
crop
crop2
6421
62672
5223
35285
2940
2282
2842

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129

6.6 BUSINESS INCOME
Data frame: 08 Enterprise
en: enterprise_noq0804: percentage owned by household members (%)
q0807_99: total expenses
q0808: months in operation
q0809_1a: amount received in an average month (per month)q0809_1b: number of average months
q0809_2a: amount received in a bad month (per month)q0809_2b: number of bad months
q0809_3a: amount received in a good month (per month)q0809_3b: number of good months> d<-outfiles[[8]]> dim(d)[1] 2342
31> head(d)identif en aimag soum location q0803 q0804 q0805 q0806 q0807_01 q0807_02
1
14 1
65
13
3 3600
100
1
0
0
0
2
28 1
65
25
3 4520
100
1
0
0
0
3
40 1
65
25
3 1622
100
2
0
0
0
4
42 1
65
25
4 1430
100
1
0
0
0
5
50 1
65
40
3 4721100
0
1 1684800 13000000
6
53 1
65
40
3 4510100
11 1296000 20000000
q0807_03 q0807_04 q0807_05 q0807_06 q0807_07 q0807_08 q0807_09 q0807_10
100100000000002250000015000000000
3 1400000
0
50000
0
0
0
0
0
4
300000
0
0
0
0
0
0
0
5
0
40000012000000001800006
0 1200000
2000000000 1000000
q0807_11 q0807_99 q0808 q0809_1a q0809_1b q0809_2a q0809_2b q0809_3a1
0100000
12
60000
4
40000
4
70000
2
0
4000006300000215000024500003
0 1450000
93000003200000350000040300000
9
75000
3
45000
2
90000
5
0 15384800
12 1400000
4 1300000
4 1600000
6
0 23696000
12 2000000
4 1500000
4 4000000
q0809_3b quarter interviewer supervisor
1
4
1
3
65
2
2
1
1
65
3
3
1
1
65
4
4
1
1
65
5
4
1
2
65
6
4
1
3
65

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130



Number of months in q0808 and q0809 are consistent.

> table(d$q0808==(d$q0809_1b+d$q0809_2b+d$q0809_3b))
TRUE
2324



Generated variable of total monthlyrevenue as;(q0809_1b*q0809_1a + q0809_2b*q0809_2a + q0809_3b*q0809_3a)/12> d[is.na(d)]<-0> d$revenue<-round((d$q0809_1b*d$q0809_1a + d$q0809_2b*d$q0809_2a ++ d$q0809_3b*d$q0809_3a)/12)> head(d[,c(1,2,23:28,32)])
identif en q0809_1a q0809_1b q0809_2a q0809_2b q0809_3a q0809_3b revenue
1
14 1
60000
4
40000
4
70000
4
56667
2
28 1
300000215000024500002 150000
3
40 1
300000320000035000003 250000
4
42 1
75000
3
45000
2
90000
4
56250
5
50 1 1400000
4 1300000
4 1600000
4 1433333
6
53 1 2000000
4 1500000
4 4000000
4 2500000

Generated variable of monthly business income as;(revenue-q0807_10/12)*q0804/100
where,
q0804: percentage owned by household members (%)# distribution of q0804> summary(d$q0804)
Min. 1st Qu. Median
Mean 3rd Qu.
10.00 100.00 100.00
98.42 100.00> addmargins(table(d$q0804))
10
20
25
30
33
34
40
50
1
3
4
5
2
1
5
39


Max.
100.00
60
3

70
2

80
3

Dominant percentage is “100%”, followed by “50%”.

> d$cost<-round(d$q0807_99/12)> d$business<-round((d$revenue-d$cost)*d$q0804/100)> head(d[,c(1:2,7,21,32:34)])
identif en q0804 q0807_99 revenue
cost business
1
14 1
100
100000
56667
8333
48334
2
28 1
100
400000 150000
33333
116667340 1
100 1450000 250000 120833
129167442 1
100300000
56250
25000
31250
5
50 1
100 15384800 1433333 1282067
1512666
53 1
100 23696000 2500000 1974667
525333Manual Mongolia HSES 2012 Version 2.0

90 100 Sum
2 2272 2342

131

> head(d[d$q0804<100, c(1:2,7,21,32:34)])
identif en q0804 q0807_99 revenue
cost business
40
306 1
50 11710000 1200000 975833
112084162917 1
4025000081167 20833
24134
165
925 1
50 1750000 416667 145833
135417166926 1
50525000 301667 43750
128958
168
928 1
50
30000
10000
2500
3750
171
939 1
50
870000 250000 72500
88750> table(d$business<0)
FALSE TRUE
2229
113
> head(d[d$business<0, c(1:2,7,21,32:34)])
identif en q0804 q0807_99 revenue
cost business57
390 1
100 5566000 206667 463833 -257166
58391 1
100 4148000 169167 345667 -176500
60395 1
100 2512000
95833 209333 -113500
74
472 2
100 3638800 116667 303233 -186566
167
927 1
100 4160000 325000 346667-21667209
1187 1
100 10440000 150000 870000 -720000
business2: replace negative income at firm level with zero.

> d$business2<-ifelse(d$business<0,0,d$business)> head(d[d$business<0, c(1:2,7,21,32:35)])
identif en q0804 q0807_99 revenue
cost business business2
57
390 1
100 5566000 206667 463833 -257166
0
58
391 1
100 4148000 169167 345667 -176500
0
60
395 1
100 2512000
95833 209333 -113500
0
74
472 2
100 3638800 116667 303233 -186566
0
167
927 1
100 4160000 325000 346667-2166702091187 1
100 10440000 150000 870000 -720000
0

Aggregated at householdlevel> df<-CollapseBy(d,"identif",c("revenue","cost","business","business2"),HHID)> dim(df)[1] 12811
5> head(df[df$business>0,])
identif revenue
cost business business2
14
14
56667
8333
48334
48334
28
28 150000
33333
116667
11666740
40 250000 120833
129167129167
42
42
56250
25000
31250
31250
50
50 1433333 1282067
15126615126653
53 2500000 1974667
525333525333> head(df[df$business<0,])identif revenue
cost business business2

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132

390
390 206667 463833 -257166
0
391
391 169167 345667 -176500
0
395
395
95833 209333 -113500
0927
927 325000 346667-2166701187
1187 150000 870000 -720000
014051405 175000 348333 -173333
0> head(df[df$business<0&df$business2>0,])
identif revenue
cost business business2
1454
1454 596666 1210333 -613667
37333
2151
2151 9166667 10016667 -850000
1250004685
4685 1920416 1963750-433348333
5797
5797 458334
491667-3333316667
8424
8424 3704167 3924417 -220250
52250
11655
11655 1096667 1130000-33333
191667> table(df$business<0)
FALSE TRUE
12706
105



business3: replace negative income at household level with zero

> df$business3<-ifelse(df$business<0,0,df$business)> head(df[df$business<0&df$business2>0,])
identif revenue
cost business business2 business3
1454
1454 596666 1210333 -613667
37333
0
2151
2151 9166667 10016667 -850000
12500004685
4685 1920416 1963750-433348333
05797
5797 458334
491667-3333316667
08424
8424 3704167 3924417 -220250
52250
0
11655
11655 1096667 1130000-33333
1916670> apply(df[-1],2,function(x) round(weighted.mean(x,hhinc$hhweight)))
revenuecost business business2 business3
356256220088122797130536130470business4: replace outlier revenue> 7,000,000 with zero> range(df$revenue)[1]
0 347916667> table(df$revenue>7000000)
FALSE TRUE
12703
108
> df$business4<-ifelse(df$revenue>7000000,0,df$business3)> apply(df[-1],2,function(x) round(weighted.mean(x,hhinc$hhweight)))
revenuecost business business2 business3 business4
35625622008812279713053613047064715

Manual Mongolia HSES 2012 Version 2.0

133> range(df$business4)[1]
0 5579167> business<-df# The monthly business income in the survey report is 146 thousand in 2012.

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134

6.7 Other (REMITTANCE) income
Data frame: 10 remittance # Section 7
q0909: Who gave the giftq0910: Purpose of the receipt
q0911: From where the gifts
q0913: Amount received during the past 12 months
q0914: Do receive it regularly?
q0915: How do you receive it?

> d<-outfiles[[10]]> dim(d)[1] 3670
18> head(d)identif ln cluster aimag soum location ind_id q0909 q0910 q0911 q0912
1
13 1
6
65
13
3
1
4
1
1
NA
2
160 1
77
83
25
3
1
4
8
4
NA
3
167 1
80
83
25
3
1
4
1
4
NA
4
176 1
85
83
37
4
5
1
1
3
NA
5
186 1
87
83
37
4
1
1
1
3
NA
6
189 1
87
83
37
4
1
1
1
3
NA
q0913 q0914 q0915 quarter interviewer supervisor
PID
1 30000031
1
3
65 1301
2 1200000
5112
83 16001
3
50000
4
4
1
3
83 16701
4 14000041
1
3
83 17605
5 100000541
2
83 18601
6
15000
5
4
1
2
83 18901Who gave the gift?

> t<-table(d$q0909)> names(t)<-names(attributes(d)$label.table["q0909"][[1]])> t
GOVERNMENT280
COMPANIES AND ORGANIZATIONS
919
NGOs
35
PARENTS, CHILDREN, RELATIVES
2266
OTHER INDIVIDUALS (FRIENDS, NEIGHBORS,
55
FOREIGN & INTERNATIONAL ORGANIZATIONS,
29
OTHERS86

Manual Mongolia HSES 2012 Version 2.0

135



Purpose of the receipt> t<-table(d$q0910)> names(t)<-names(attributes(d)$label.table["q0910"][[1]])> t
HOUSEHOLD USE EDUCATION8 TUITION FEE
MEDICAL TREATMENT
2639
338
257
PURCHASE OF DWELLINGHOLIDAY
FUNERAL
55
210
25
HOUDEHOLD ENTERPRISE
OTHER
27
119



From where the gifts?

> t<-table(d$q0911)> names(t)<-names(attributes(d)$label.table["q0911"][[1]])> tCapital city Aimag center Soum center Countryside immigration
1035
1213
734
417
271


From which country the gifts (code)?

> t<-table(d$q0912)> names(t)<-names(attributes(d)$label.table["q0912"][[1]])> t
23 24 36 40 56 100 124 138 156 192 203 250 276 372 380 392 408 410 418
1
4
3
1
1
2
3
1
9
1
7 10
5
3
2 11 27 1011
512 566 616 643 752 756 764 792 826 840
1
1
1
3 12
2
7
7
4 39


Do receive it regularly?

> t<-table(d$q0914)> names(t)<-names(attributes(d)$label.table["q0914"][[1]])> t
YES, weekly
YES, monthly YES, quarterly
YES, annualy
22
339
131
760
NO
2418



How do you receive it?

> t<-table(d$q0915)> names(t)<-c("CASH","BY ACCOUNT","CASH REMITTANCE","IN KIND","OTHER")> t
CASH
BY ACCOUNT CASH REMITTANCE
IN KIND
2156
298
193
924

Manual Mongolia HSES 2012 Version 2.0

OTHER
99

136

 The amount of q0913 is positive for all records.
> table(d$q0913>0)
TRUE
3670


Aggregated at household level> df<-CollapseBy(d,"identif","q0913",HHID)> dim(df)[1] 12811
2> df$other<-round(df$q0913/12)> head(df[df$q0913>0,])
identifq0913 other13
13 300000 25000
160
160 1200000 100000
167
167
50000
4167
176
176 140000 11667
186
186 100000
8333
189
189
15000
1250
> weighted.mean(df$other,hhinc$hhweight)[1] 23138.21
Remarks:
The amount of other is 68,377 according to the results table.
Considering the sum of pension and other, almost the same.

PensionOther
Sum

My estimates
194,368
23,138217,506> other<-df

Manual Mongolia HSES 2012 Version 2.0

Results table
155,686
68,377224,063

137

6.8 Total household income
Generated data frame consisted of household income components.

> dim(hhinc)[1] 12811
6> colnames(hhinc)[1] "identif" "wage3""hhweight" "oi0114""oi1520""oi2126"> hhinc<-merge(hhinc,livestock[,c("identif","livestock")],by="identif")> hhinc<-merge(hhinc,crop[,c("identif","crop","crop2")],by="identif")>hhinc<-merge(hhinc,business[,c("identif","business","business2","business3","business4")],by="identif")> hhinc<-merge(hhinc,other[,c("identif","other")],by="identif")> head(hhinc)identif wage3 hhweight oi0114 oi1520 oi2126 livestock crop crop2
1
1
0 65.01397 42000
0022533400
2
2 250000 65.01397 84000
00313667003
3
0 65.01397 63000
00212917004
4
0 65.01397 84000
0
0
0
0
0
5
5
0 65.01397 105000
0034650100
6
60 65.01397 126000
0083108400business business2 business3 business4 other
1
0
0
0
0
0
2
0
0
0
0
0
3
0
0
0
0
0
4
0
0
0
0
0
5
0
0
0
0
0
6
0
0
0
0
0
 Mean monthly income per household by item
> t<-apply(hhinc[c(-1,-3)],2,function(x) round(weighted.mean(x,hhinc$hhweight)))> data.frame(item=names(t),mean=t,row.names=NULL)
item
mean
1
wage3 380021
2
oi0114 155493
3oi1520 36556
4oi21262897
5 livestock 54064
6
crop
2282
7
crop2
2842
8
business 122797
9 business2 130536
10 business3 130470
11 business4 64715
12
other 23138

Manual Mongolia HSES 2012 Version 2.0

138



Comparison with the survey report 2012

Type of income

ReportTotal revenue

My trial

Remarks

819,996.

1. Monetary income - Total

741,917.

784,987

Wages and salaries

372,114.

380,021

wage3

Pensions and allowance

155,686.

155,493

oi0114

Income from household businesses

145,740.

186,882

livestock, crop, business2

Other68,377.

62,591oi1520, oi2126, otherReceived from others free of charge

31,967.

Foodstuff, which consumed fromprivate farm or enterprise

46,112.

> sum(t[c(5,6,9)])[1] 186882> sum(t[c(3,4,12)])[1] 62591> sum(t[c(1:6,9,12)])[1] 784987> save(outfiles,CollapseBy,hhinc,livestock,crop,business,other,file="hhinc20181117.RData")

Manual Mongolia HSES 2012 Version 2.0

139Chapter 7. Household Expenditure
7.1 Results of household expenditure

According to the Mongolian NSO’s database of www.1212.mn, the monthly average
iexpenditure per household in 2012 is as the next.

Type of expenditure
Total expenditure2012
820,263.

1. Monetary expenditure - Total

742,184.

Food expenses

207,858.

Non-food expenses and services

518,750.

Gifts and benefits gave for others

15,576.

Received from other free of charge

31,968.

Foodstuff, which consumed from private farm or enterprise

46,112.

http://www.1212.mn/tables.aspx?tbl_id=DT_NSO_1900_001V2&SOUM_select_all=0&S
OUMSingleSelect=_0&HSES1_select_all=0&HSES1SingleSelect=&YearY_select_all=0&YearYSingleSelect=_2012_2011_2010&viewtype=table(accessed on 13 November 2018)

Manual Mongolia HSES 2012 Version 2.0

140Manual Mongolia HSES 2012 Version 2.0

141



Also the metadata is provided on the web as follows;

Manual Mongolia HSES 2012 Version 2.0

142

7.2 Related questionnaire and data files

Expenditure type

Data file

Questionnaire

16 Urban diary

Section 11 Household food

Food
Urban foodexpenditure
Rural food

17 Rural food 7days

Section 12 Household foodexpenditure

Non-food
Non-food

15 Non-food

Section 13 Non-food expenditureand consumption

Foodout

19 Foodout (one file both for

Bottom of Section 11 and Section

urban and rural)of 12 Food consumption/ not inhouseholdEnergy12 Energy

Section 11 Housing, energy

Payment

13 Pyment service

Section 12 Payment service

11 Savings loan

Section 12 Savings and loan

2 Individual (?)

Section 5 Migration

service
Repayment for
loan

Transfer paid

Foodout

Foodout questionnaire was newly introduced in HSES 2012. The questions are at the bottom ofSection 11 and Section 12.
Food out for urban;
Recorded every day in Diary,
Keyed-in on tablet by enumerator, sending data to server,
Food summary computed by server
Food out for rural;
Section 12 for the past 7 days,

Manual Mongolia HSES 2012 Version 2.0

143

The file of “foodout” is one file composed of urban foodout and rural foodout.
The reference period differs by urban/rural.
Urban: one month (location = 1 or 2)
Rural: 7 days (location = 3 or 4)
So, firstly convert rural 7 days to one month.

Remarks:
Foodout was covered in Non-food questionnaire in SES 2010.

Manual Mongolia HSES 2012 Version 2.0

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

Imputed unit price

Unit prices for estimating in-kind consumption were imputed and applied as the following order;

Order

Applied price

uprice1

Own price

meduprice2

Median price of cluster (PSU)

clusterprice3

Median price of aimag divided by location

aimagprice4

Median price of location

locationprice5

Median price of national

nationalprice

Manual Mongolia HSES 2012 Version 2.0

145

7.3 Food
7.3.1 Urban diary

item
quantity

item: 10101 to 11305
purchasedq1401_2 + q1402_2 + q1403_2

received freeq1401_3 + q1402_3 + q1403_3

own production

q1401_4 + q1402_4 + q1403_4

unit priceq1404

7.3.2 Rural food 7 days

item
quantity

item: 10101 to 11305
purchasedq1503 * 4.3

received freeq1505 * 4.3

own production

q1506 * 4.3

unit priceq1504

7.3.3 Imputed unit price# Urban diary> d<-outfiles[[16]]> dim(d)[1] 867273

23> colnames(d)[1] "identif""item""cluster""aimag""soum"[6] "location""row14""q1401_1""q1401_2""q1401_3"[11] "q1401_4""q1402_1""q1402_2""q1402_3""q1402_4"[16] "q1403_1""q1403_2""q1403_3""q1403_4""q1404"Manual Mongolia HSES 2012 Version 2.0

146[21] "quarter""interviewer" "supervisor"> addmargins(table(is.na(d$uprice)))
FALSE

TRUE

Sum

198935 668338 867273> sum(!is.na(d$uprice) & d$uprice==0)[1] 4057> d$uprice<-ifelse(!is.na(d$uprice) & d$uprice==0, NA, d$uprice)> addmargins(table(is.na(d$uprice)))
FALSE

TRUE

Sum

194878 672395 867273# meduprice> m<-aggregate(d$uprice,list(d$identif,d$item),FUN=median,na.rm=T)> dim(m)[1] 867273

3> head(m)Group.1 Group.2

x

1

97

10101 600

2

9810101 600

3

9910101 600

4100

10101 600

5

101

10101 600

6

10210101 600

> colnames(m)<-c("identif","item","meduprice")> head(m)identif item meduprice1

97 10101600

2

98 10101600

3

99 10101600

4100 10101

600

5

101 10101

600

6

102 10101

600> addmargins(table(is.na(m$meduprice)))
FALSE

TRUE

Sum

194878 672395 867273

Manual Mongolia HSES 2012 Version 2.0

147> d<-merge(d,m,by=c("identif","item"),all.x=T)> dim(d)[1] 867273

25> colnames(d)[1] "identif""item""cluster""aimag""soum"[6] "location""row14""q1401_1""q1401_2""q1401_3"[11] "q1401_4""q1402_1""q1402_2""q1402_3""q1402_4"[16] "q1403_1""q1403_2""q1403_3""q1403_4""q1404"[21] "quarter""interviewer" "supervisor" "uprice""meduprice"> table(!is.na(d$meduprice) & d$meduprice==d$uprice)
FALSE

TRUE

672395 194878# clusterprice> m<-aggregate(d$uprice,list(d$cluster,d$item),FUN=median,na.rm=T)> dim(m)[1] 87084

3> head(m)Group.1 Group.2

x

1

49

10101 600

2

5010101 600

3

51

10101 600

4

5210101 600

55310101 600

6

5410101 600

> colnames(m)<-c("cluster","item","clusterprice")> head(m)cluster item clusterprice1

49 10101600

250 10101600

3

51 10101600

452 10101600

5

53 10101600

6

54 10101600> addmargins(table(is.na(m$clusterprice)))
FALSE TRUESum

Manual Mongolia HSES 2012 Version 2.0

14846926 40158 87084> d<-merge(d,m,by=c("cluster","item"),all.x=T)> dim(d)[1] 867273

26> head(d)cluster item identif aimag soum location row14 q1401_1 q1401_2 q1401_3
1

100 10101

226

83

1

2

2

2

2

0

2

100 10101

224

83

1

2

2

0

NA

NA

3

100 10101

221

83

1

2

2

7

7

0

4

100 10101

225

83

1

2

2

3

3

0

5

100 10101

227

83

1

2

2

2

2

0

6

100 10101

223

83

1

2

2

2

2

0

q1401_4 q1402_1 q1402_2 q1402_3 q1402_4 q1403_1 q1403_2 q1403_3 q1403_4
1

0

4

4

0

0

3

3

0

0

2

NA

2

2

0

0

3

3

0

0

3

0

8

8

0

0

4

4

0

0

4

0

4

4

0

0

2

2

0

0

5

0

4

4

0

0

3

3

0

0

6

0

4

4

0

0

3

3

0

0

q1404 quarter interviewer supervisor uprice meduprice clusterprice
1 1000

1

1

83

1000

1000

900

2

900

1

1

83

900

900

900

3

900

1

1

83

900

900

900

4 1500

1

3

83

1500

1500

900

5

800

1

1

83

800

800

900

6

800

1

1

83

800

800

900

> addmargins(table(is.na(d$clusterprice)))
FALSE

TRUE

Sum

467142 400131 867273> addmargins(table(is.na(d$meduprice),is.na(d$clusterprice)))
FALSE
FALSE 194878

TRUE

Sum

0 194878

TRUE 272264 400131 672395
Sum

467142 400131 867273

Manual Mongolia HSES 2012 Version 2.0

149



Number of NA in meduprice was 672,395. It decreased to 400,131 of NA in clusterprice.

# aimagprice> m<-aggregate(d$uprice,list(d$aimag,d$location,d$item),FUN=median,na.rm=T)> dim(m)[1] 2583

4> head(m)Group.1 Group.2 Group.3

x

1

11

1

10101 650

2

21

2

10101 600

3

22

2

10101 650

4

23

2

10101 800

5

41

2

10101 680

6

43

2

10101 700

> colnames(m)<-c("aimag","location","item","aimagprice")> head(m)aimag location item aimagprice
1

11

1 10101

650

2

21

2 10101

600

3

22

2 10101

650

4

23

2 10101

800

5

41

2 10101

680

6

43

2 10101700> d<-merge(d,m,by=c("aimag","location","item"),all.x=T)> dim(d)[1] 867273

27> head(d)aimag location item cluster identif soum row14 q1401_1 q1401_2 q1401_3
1

11

1 10101

1221

2740

25

2

5

5

0

2

11

1 10101

1221

2737

25

2

8

8

0

3

11

1 10101

1221

2745

25

2

10

10

0

4

11

1 10101

1221

2741

25

2

7

7

0

5

11

1 10101

994

11654

10

2

7

7

0

6

11

1 10101

1221

2739

25

2

10

10

0

Manual Mongolia HSES 2012 Version 2.0

150q1401_4 q1402_1 q1402_2 q1402_3 q1402_4 q1403_1 q1403_2 q1403_3 q1403_4
1

0

7

7

0

0

5

5

0

0

2

0

6

6

0

0

6

6

0

0

3

0

6

6

0

0

9

9

0

0

4

0

9

9

0

0

13

13

0

0

5

0

4

4

0

0

4

4

0

0

6

0

9

9

0

0

10

10

0

0

q1404 quarter interviewer supervisor uprice meduprice clusterprice
1

680

1

15

2

680

680

650

2

650

1

15

2

650

650

650

3

650

1

15

2

650

650

650

4

650

1

15

2

650

650

650

5

650

4

24

1

650

650

650

6

650

1

15

2

650

650

650

aimagprice
1

650

2

650

3

650

4

650

5

650

6

650

> addmargins(table(is.na(d$clusterprice),is.na(d$aimagprice)))
FALSE
FALSE 467142

TRUE

Sum

0 467142

TRUE 335815 64316 400131
Sum802957 64316 867273# locationprice> m<-aggregate(d$uprice,list(d$location,d$item),FUN=median,na.rm=T)> dim(m)[1] 2463> head(m)Group.1 Group.2

x

1

1

10101 650

2210101 725

Manual Mongolia HSES 2012 Version 2.0

151

3

1

10102 1800

4

210102 1700

5

110103 950

6

210103 900

> colnames(m)<-c("location","item","locationprice")> head(m)location item locationprice1

1 10101650

2

2 10101725

3

1 101021800

42 101021700

5

1 10103950

6

2 10103900> d<-merge(d,m,by=c("location","item"),all.x=T)> dim(d)[1] 867273

28> head(d)location item aimag cluster identif soum row14 q1401_1 q1401_2 q1401_3
1

1 10101

11

1221

2740

25

2

5

5

0

2

1 10101

11

1221

2737

25

2

8

8

0

3

1 10101

11

1221

2745

25

2

10

10

0

4

1 10101

11

1221

2741

25

2

7

7

0

5

1 10101

11

994

11654

10

2

7

7

0

6

1 10101

11

1221

2739

25

2

10

10

0

q1401_4 q1402_1 q1402_2 q1402_3 q1402_4 q1403_1 q1403_2 q1403_3 q1403_4
1

0

7

7

0

0

5

5

0

0

2

0

6

6

0

0

6

6

0

0

3

0

6

6

0

0

9

9

0

0

4

0

9

9

0

0

13

13

0

0

5

0

4

4

0

0

4

4

0

0

6

0

9

9

0

0

10

10

0

0

q1404 quarter interviewer supervisor uprice meduprice clusterprice
1

680

1

15

2

680

680

650

2

650

1

15

2

650

650

650

3

650

1

15

2

650

650

650

Manual Mongolia HSES 2012 Version 2.0

152

4

650

1

15

2

650

650

650

5

650

4

24

1

650

650

650

6

650

1

15

2

650

650

650

aimagprice locationprice
1

650

650

2

650

650

3

650

650

4

650

650

5

650

650

6

650

650

> addmargins(table(is.na(d$aimagprice),is.na(d$locationprice)))
FALSE

TRUE

FALSE 802957

Sum

0 802957

TRUE

53687 10629 64316

Sum856644 10629 867273# nationalprice> m<-aggregate(d$uprice,list(d$item),FUN=median,na.rm=T)> dim(m)[1] 1232> head(m)Group.1x110101 700210102 1800

3

10103 950

4

10104 800

510105 650

6

10106 1600

> colnames(m)<-c("item","nationalprice")> head(m)item nationalprice
1 10101700

2 101021800

3 10103950

4 10104800

Manual Mongolia HSES 2012 Version 2.0

153

5 10105650

6 101061600> head(m[is.na(m$nationalprice),])item nationalprice123 11305
NA

item=11305: Other (tobaco)

Imputed unit price was missing even in nationalprice.
> d<-merge(d,m,by=c("item"),all.x=T)> dim(d)[1] 867273

29> head(d)item location aimag cluster identif soum row14 q1401_1 q1401_2 q1401_3
1 10101

1

11

1221

2740

25

2

5

5

0

2 10101

1

11

1221

2737

25

2

8

8

0

3 10101

1

11

1221

2745

25

2

10

10

0

4 10101

1

11

1221

2741

25

2

7

7

0

5 10101

1

11

994

11654

10

2

7

7

0

6 10101

1

11

1221

2739

25

2

10

10

0

q1401_4 q1402_1 q1402_2 q1402_3 q1402_4 q1403_1 q1403_2 q1403_3 q1403_4
1

0

7

7

0

0

5

5

0

0

2

0

6

6

0

0

6

6

0

0

3

0

6

6

0

0

9

9

0

0

4

0

9

9

0

0

13

13

0

0

5

0

4

4

0

0

4

4

0

0

6

0

9

9

0

0

10

10

0

0

q1404 quarter interviewer supervisor uprice meduprice clusterprice
1

680

1

15

2

680

680

650

2

650

1

15

2

650

650

650

3

650

1

15

2

650

650

650

4

650

1

15

2

650

650

650

5

650

4

24

1

650

650

650

6

650

1

15

2

650

650

650

aimagprice locationprice nationalprice
1

650

650

700

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154

2

650

650

700

3

650

650

700

4

650

650

700

5

650

650

700

6

650

650

700

> addmargins(table(is.na(d$locationprice),is.na(d$nationalprice)))
FALSE

TRUE

FALSE 856644
TRUE
Sum



Sum

0 856644

3578

7051 10629

8602227051 867273

up: unit price applied for estimation of expenditure> d$up<-d$meduprice> d$up<-ifelse(is.na(d$up),d$clusterprice,d$up)> d$up<-ifelse(is.na(d$up),d$aimagprice,d$up)> d$up<-ifelse(is.na(d$up),d$locationprice,d$up)> d$up<-ifelse(is.na(d$up),d$nationalprice,d$up)> head(d)item location aimag cluster identif soum row14 q1401_1 q1401_2 q1401_3
1 10101

1

11

1221

2740

25

2

5

5

0

2 10101

1

11

1221

2737

25

2

8

8

0

3 10101

1

11

1221

2745

25

2

10

10

0

4 10101

1

11

1221

2741

25

2

7

7

0

5 10101

1

11

994

11654

10

2

7

7

0

6 10101

1

11

1221

2739

25

2

10

10

0

q1401_4 q1402_1 q1402_2 q1402_3 q1402_4 q1403_1 q1403_2 q1403_3 q1403_4
1

0

7

7

0

0

5

5

0

0

2

0

6

6

0

0

6

6

0

0

3

0

6

6

0

0

9

9

0

0

4

0

9

9

0

0

13

13

0

0

5

0

4

4

0

0

4

4

0

0

6

0

9

9

0

0

10

10

0

0

q1404 quarter interviewer supervisor uprice meduprice clusterprice
1

680

1

15

2

680

680

650

2

650

1

15

2

650

650

650

Manual Mongolia HSES 2012 Version 2.0

155

3

650

1

15

2

650

650

650

4

650

1

15

2

650

650

650

5

650

4

24

1

650

650

650

6

650

1

15

2

650

650

650

aimagprice locationprice nationalprice up
1

650

650

700 680

2

650

650

700 650

3

650

650

700 650

4

650

650

700 650

5

650

650

700 650

6

650

650

700 650> addmargins(table(is.na(d$up)))
FALSE

TRUE

Sum

8602227051 867273# Estimation method of imputed unit price for rural food 7 days is the same as urban diary.

Manual Mongolia HSES 2012 Version 2.0

156

7.4 Non-food
7.4.1 Non-foodfile

15 Non-food

item

item: 20101 to 24309
drop 22501 (restaurants), 22502 (canteens)

value



purchasedq1303 / 12

received freeq1304 / 12

Change item codes for payment service

FROM

TO

23201

23501

23202

23502

23203

23503

23204

23504

23205

23505

23206

23506



Change item label

ITEM

LABEL

23101

"Fees for administ", modify

23102"Payment for the s", modify

23103"Fees for legal se", modify

23104"Charges for the l",

23105"Other services", modify

23201"Public service : heating",

23202"Public service : cold water", modify

23203"Public service : hot water", modify

23204"Public service : dirty water", modify

23205"Public service : waste, trash ", modify

23206"Private service : fees of area", modify

modifymodifyManual Mongolia HSES 2012 Version 2.0

157

23207

"Private service : use elevator", modify

23208"Other services fe", modify

23209"House rent: Ger", modify

23210"House rent:

23211"Water, /brought b", modify

23212"Charges of repair", modify

23213"Others", modify

23301"Electricity, kbt", modify

23401"Firewood, m3", modify

23402"Dung,", modify

23403"Coal, ton", modify

23404"Gas, l",23405

"Other fuels", modify

23501"Wall paper, packa", modify

23502"Oil paint, l", modify

23503"Bricks, piece", modify

23504"Cement, kg", modify

23505"Glass, m2", modify

23506"Other......",

Apartment", modify

modifymodify7.4.2 Food out
file

19 Foodout

item

22501: restaurants
22502: canteens

urban
value

location=1 or 2purchasedq1508

received free

q1509

rural

location=3 or 4purchasedq1508 * 4.3

received freeq1509 * 4.3

7.4.3 Energy

Manual Mongolia HSES 2012 Version 2.0

158

file

12 Energy

itemenergy_id: 1 to 9

value



purchasedq1140 / 12

received freeq1141 / 12

Change item

ITEM

NEW

1

23301

Electricity

2

23401

Firewood

3

23401

Firewood

4

23403

Coal

5

23403

Coal

6

23402

Dung

7

23402

Dung

8

23404

Gas

9

23405

Other fuels

7.4.4 Payment service
file

13 Payment service

item

1 to 13value

purchasedq1144 / 12

received freeq1145 / 12

Change item

ITEM

NEW

1

23201

Public service: heating

2

23202

Public service: cold water

3

23203

Public service: hot water

4

23204

Public service: dirty water

5

23205

Public service: waste, trash

6

23206

Private service: fees of area

Manual Mongolia HSES 2012 Version 2.0

159

7

23207

Private service: use of elevator

8

23208

Other services fe

9

23211

Water, /brought b

10

23209

House rent: Ger

11

23210

House rent: Apartment

12

23212

Charges of repair

13

23213

Others

7.4.5 Loan
file

11 Savings loan

item

Repayment for loanvalueq1012 / 12

Manual Mongolia HSES 2012 Version 2.0

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Manual Mongolia HSES 2012 Version 2.0

161

Chapter 9.

Micro data to be provided

Strategy
1. Resampling
The data files which were provided by NSO will be resampled as follows;
1.1

To use household identifier identif in all data files.

1.2

To append personal identifier PID to individual datafiles; 02 individual and 10 Remittance.

1.3

To select 80% of identif by systematic sampling method.

1.4

To select records which identif belongs to the above selected identif from the data files.

2. The household weight hhweight in 20 Basicvars will be adjusted by dividing by 0.8.
3. Resampled data files will be provided in CSV and R format.
4. Others
The imputed unit price data provided by the delegates from Mongolia to the workshop will beappended to data files; “16 Urban Diary” and “17 Rural Food 7 days”.

Appending imputed unit price data
# Provided food data file with imputed unit price# "16_urb_diary.dta" appended with applied unit price along with clusterprice, aimagprice,
locationprice and nationalprice.
# df16: imported dataframe into R> colnames(f16)[1] "identif""cluster""aimag""soum"[5] "location""row14""item""q1401_1"[9] "q1401_2""q1401_3""q1401_4""q1402_1"[13] "q1402_2""q1402_3""q1402_4""q1403_1"[17] "q1403_2""q1403_3""q1403_4""uprice"[21] "quarter""interviewer""supervisor""newaimag"[25] "urban""region""month""strata"[29] "hhweight""hhsize""aimagsoum""meduprice"[33] "clusterprice""aimagprice""locationprice" "nationalprice"[37] "q14_pur""q14_res""q14_own"[41] "v14_res""v14_own""v14_pur"

Manual Mongolia HSES 2012 Version 2.0

162> d<-outfiles[[16]]> d<-merge(d,df16[c("identif","item","uprice","meduprice","clusterprice",+ "aimagprice","locationprice","nationalprice")],by=c("identif","item"))> dim(fd16)[1] 867273

29> colnames(fd16)[1] "identif""item""cluster""aimag"[5] "soum""location""row14""q1401_1"[9] "q1401_2""q1401_3""q1401_4""q1402_1"[13] "q1402_2""q1402_3""q1402_4""q1403_1"[17] "q1403_2""q1403_3""q1403_4""q1404"[21] "quarter""interviewer""supervisor""uprice"[25] "meduprice""clusterprice""aimagprice""locationprice"[29] "nationalprice"> outfiles[[16]]<-d# "17_rur_food_7d.dta" appended with applied unit price along with clusterprice, aimagprice,
locationprice and nationalprice# df17: imported dataframe into R> colnames(fd17)[1] "identif""item""row15""cluster"[5] "aimag""soum""location""q1501"[9] "q1502""q1503""q1504""q1505"[13] "q1506""quarter""interviewer""supervisor"[17] "uprice""meduprice""clusterprice""aimagprice"[21] "locationprice" "nationalprice"> d<-outfiles[[17]]> d<-merge(d,df17[c("identif","item","uprice","meduprice","clusterprice",+ "aimagprice","locationprice","nationalprice")],by=c("identif","item"))> dim(fd17)[1] 708480

22> colnames(fd17)[1] "identif""item""row15""cluster"[5] "aimag""soum""location""q1501"[9] "q1502""q1503""q1504""q1505"[13] "q1506""quarter""interviewer""supervisor"

Manual Mongolia HSES 2012 Version 2.0

163[17] "uprice""meduprice""clusterprice""aimagprice"[21] "locationprice" "nationalprice"> outfiles[[17]]<-dResampling# Selected 80% of hhid
> hhid<-outfiles[[20]]$identif# Basicvars> length(hhid)[1] 12811> range(hhid)[1]

1 12811> Int<-5> (St<-sample(1:5,1))[1] 3> hhid.selected<-hhid[(1:length(hhid))%%Int!=(St-1)]> length(hhid.selected)/length(hhid)[1] 0.8000156> hhid.selected<-hhid.selected[order(hhid.selected)]> head(hhid.selected)[1] 1 3 4 5 6 8# Resampled at the rate of 80%# outfiles[[1]] to outfiles[[20]]> Rnames.80<-paste(Rnames,".80",sep="")> Rnames.80[1] "Household.80""Individual.80"[3] "Llivestock.80""Livestock Expenditure.80"[5] "Product.80""Crop.80"[7] "Agriultural Expenditure.80" "Enterprise.80"[9] "Other income.80""Remittance.80"[11] "Savings loan.80""Energy.80"[13] "Payment service.80""Durable.80"[15] "Non-Food.80""Urban Diary.80"

Manual Mongolia HSES 2012 Version 2.0

164[17] "Rural Food 7 day.80""Foodstuffs.80"[19] "Foodout.80""Basicvars.80"> outfiles.80<-list()> for(j in 1:20){+ d<-outfiles[[j]]+ outfiles.80[[j]]<-subset(d,is.element(d$identif,hhid.selected))+ }> length(outfiles.80)[1] 20> for(j in 1:20){+ cat(format(Rnames.80[j],width=26),": ",+ format(nrow(outfiles.80[[j]]),width=7),",",+ format(ncol(outfiles.80[[j]]),width=3),"\n")+ }Household.80:10249 ,

88

Individual.80:

38440 , 130

Llivestock.80:

11663 ,

15

Livestock Expenditure.80:

7276 ,

10

Product.80:

59583 ,

16

Crop.80:

1857 ,

15

Agriultural Expenditure.80 :9100 ,

10

Enterprise.80:

1848 ,

31

Other income.80:

266474 ,20

Remittance.80:2949 ,

18

Savings loan.80:

5049 ,

19

Energy.80:

92241 ,

15

Payment service.80:

133237 ,13

Durable.80:

450956 ,12

Non-Food.80:

3699889 ,15

Urban Diary.80:

693843 ,29

Rural Food 7 day.80:

566784 ,22

Foodstuffs.80:

10249 ,

17

Foodout.80:

20464 ,

12

Manual Mongolia HSES 2012 Version 2.0

165

Basicvars.80:

10249 ,

12

# Adjusted weight in Basicvars> d<-outfiles.80[[20]]> d$WT<-d$hhweight/0.8> outfiles.80[[20]]<-d> sum(d$WT)[1] 738429.8> sum(outfiles[[20]]$hhweight)[1] 739058.2> save(outfiles,outfiles.80,hhid.selected,file="Resampling.RData")# Converted to CSV> CSVnames<-gsub("\\.","_",Rnames.80)> CSVnames<-paste(CSVnames,".csv",sep="")> CSVnames[1] "Household_80.csv""Individual_80.csv"[3] "Llivestock_80.csv""Livestock Expenditure_80.csv"[5] "Product_80.csv""Crop_80.csv"[7] "Agriultural Expenditure_80.csv" "Enterprise_80.csv"[9] "Other income_80.csv""Remittance_80.csv"[11] "Savings loan_80.csv""Energy_80.csv"[13] "Payment service_80.csv""Durable_80.csv"[15] "Non-Food_80.csv""Urban Diary_80.csv"[17] "Rural Food 7 day_80.csv""Foodstuffs_80.csv"[19] "Foodout_80.csv""Basicvars_80.csv"> for(j in 1:20){+ cmd<-paste("write.csv(outfiles.80[[",j,"]],'",CSVnames[j],"',row.names=F)",sep="")+ eval(parse(text=cmd))+ }# Resampled data set in csv format

Manual Mongolia HSES 2012 Version 2.0

166> list.files()[1] "Agriultural Expenditure_80.csv" "Basicvars_80.csv"[3] "Crop_80.csv""Durable_80.csv"[5] "Energy_80.csv""Enterprise_80.csv"[7] "Foodout_80.csv""Foodstuffs_80.csv"[9] "Household_80.csv""Individual_80.csv"[11] "Livestock Expenditure_80.csv""Llivestock_80.csv"[13] "Non-Food_80.csv""Other income_80.csv"[15] "Payment service_80.csv""Product_80.csv"[17] "Remittance_80.csv""Rural Food 7 day_80.csv"[19] "Savings loan_80.csv""Urban Diary_80.csv"

Manual Mongolia HSES 2012 Version 2.0

167

HSES-1

Appendix 2 to Order ../..
dated December 25, 2008of the Chairman of the NSO

All staffs at all levels of NSO should keep your responses confidential in accordance with Mongolian
Legislation on "Statistics" and "Confidentiality of private information".
We wish all teh best for you and your family.

DIARY FOR KEEPING IN HOUSEHOLDS/1st 10-DAYS OF A MONTH/

Quarter

Cluster number

NAME OF THE HOUSEHOLD HEAD

ADDRESSNAME OF THE INTERVIEWER

CODEDATE OF VISITS

YEAR

MONTH

DAY

RESULT*

VISIT 1VISIT 2

Result code*

VISIT 3Adequately filled -1

VISIT 4

Incompletely filled -2

NOTE

Manual Mongolia HSES 2012 Version 2.0

Householdnumber

168

Instruction to fill up diary in households
Food consumption of the households
The monthly food consumption of household members shall be recording by following
times divided into 3 groups. Namely,-         First ten days/1-10/-         Second ten days/11-20/-         Third ten days /21 to the end of month/
The dieary has the following structure.
1)      Cover2)      Instruction3)      Consumption-         The total consumed food items during the 10 days shall be recorded in 10 pages.
-         There are 30 rows for every 10 pages to record consumed food items per day. Everyrow is numbered with four digit-numbers:-         First 2 digits are number of day.
-         3-4 digits are ordinal numbers 1-30; number of consumed food items/.
Household members shall record consumed food items of the particular day on appropriate
page as follows.
1)      Household member shall be specify name of the consumed food items in (1).
Interviewer will code them later on. For example, mutton, imported rice, big red apple, andvegetable
oil etc.
     
Although the standard unis as kilogram, lite, piece etc. have been used to measure items,
sometimes members of particular households could purchase certain food items by nonstandard units from local markets. In such case household members should inform units
with their own ways. For instance, 1 kilogram, 350 grams, 4 apples, half bottle or one sacketc.
Note: Interviewers should convert each food items measured by non-standard units to thestandard units and identify respective quantities. In the 11th section, the all food items
should be recorded in standard units. For example, if respondent answered as half sackrice, the interviewer should convert it to kilograms.
3)      The main sources of consumed food items should be recorded in (3). The
corresponding code shall be copied from the resource code lists and if the item ispurchased the unit price should be written. For example, supose that the household
purchased 3kg potatoes by 350 tugrug per kg totalling 1050 tugrugs. And if 0.5 kg potatoes
is consumed in that day, the unit price should be written as 350 tugrug.
-         The last two columns shall be filled by the interviewer.
4)      (4) Codes for food items: The corresponding code should be chosen from the detailed
list of food items attached to the HSES-2a.
5)      (5) Quantities converted into standard units:As explained before, the interviewer shallconvert the quantities written in (2) into standard units and write the quantities expressedby standard untis. If those quantities are measured by standard units in column (2), theinterviewer will directly copy them into this column.

Manual Mongolia HSES 2012 Version 2.0

169

If household members had eaten meals in restautants, canteens etc, such consumption shallbe included in the household food consumption. However, any meal shall be recorded only
as “meal name” with its price regardless of the meal’s composition. For example, if ahousehold member has eaten a spagetti in a restaurant, it will be recorded as “spagetti”
with its price.
Short recommendation of converting some food items into standard units by using
available articles:-         one cup of rice- 200gm-         one flat, flour paste-150 gm-         one small spoon salt, sugar etc-15 gm-         one big spoon salt, sugar etc.-20 gm

Manual Mongolia HSES 2012 Version 2.0

170

Record-1: FOOD CONSUMPTIONLINE NUMBER(15.01)
Write the full description of the item consumed(15.03)(15.02)
Write sources
Write the quantity
consumed and the nameof the unit ofPurchased 21
measurement
Received free- 2

DAY
1
FOR OFFICE USE(15.04)(15.05)

Own production -3
ITEM CODE
If purchased, write
unit price
Code
ITEMS

QUANTITY, UNITTUGRIG

0101
0102
0103
0104
0105
0106
0107
0108
0109
0110
0111
0112
0113
0114
0115
0116
0117
0118
0119
0120
0121
0122
0123
0124
0125
0126
0127
0128
0129
0130

Manual Mongolia HSES 2012 Version 2.0

CODE

CONSUMEDQUANTITY

STANDARDQUANTITY171

HSES-1

Appendix 2 to Order ../..
dated December 25, 2008of the Chairman of the NSO

All Óëñûí
staffs atÑòàòèñòèêèéí
all levels of NSO
shouldresponses
confidential
accordancewith "ÕóâüMongolianÌîíãîë
àëáàíû
á¿õkeepøàòíûyouràæèëòíóóäòàíàéºðõ áîëîí inõóâüõ¿íèé íóóöûã
õ¿íèéLegislationon "Statistics"
and "Confidentialityof privateíóóöûí òóõàé" Ìîíãîë
Óëñûí õóóëü
áîëîí "Ñòàòèñòèêèéí
òóõàé" Ìîíãîë
Óëñûíinformation".
õóóëèéí 22 äóãààð ç¿éëèéí 3äóãààð çààëòûí äàãóó íóóöëàí õàäãàëíà.
We wish all teh best for you and your family.

DIARY FOR KEEPING IN HOUSEHOLDS/3rd 10-DAYS OF A MONTH/

Quarter

Cluster number

NAME OF THE HOUSEHOLD HEAD

ADDRESSNAME OF THE INTERVIEWER

CODEDATE OF VISITS

YEAR

MONTH

DAY

RESULT*

VISIT 1VISIT 2

Result code*

VISIT 3Adequately filled -1

VISIT 4

Incompletely filled -2

NOTE

Manual Mongolia HSES 2012 Version 2.0

Householdnumber

172

HOUSEHOLD FOOD CONSUMPTIONDAYLINE NUMBER(15.01)
Write the full description of the item consumed(15.03)(15.02)
Write sources
Write the quantity
consumed and the nameof the unit ofPurchased 21
measurement
Received free- 2

1
FOR OFFICE USE(15.04)(15.05)

Own production -3
ITEM CODE
If purchased, write
unit price
Code
ITEMS

QUANTITY, UNITTUGRIG

0101
0102
0103
0104
0105
0106
0107
0108
0109
0110
0111
0112
0113
0114
0115
0116
0117
0118
0119
0120
0121
0122
0123
0124
0125
0126
0127
0128
0129
0130

Manual Mongolia HSES 2012 Version 2.0

CODE

CONSUMEDQUANTITY

STANDARDQUANTITY173

Appendix 3 to Order ../..
dated December 25, 2008of the Chairman of the NSO

HSES-2à
1. Enumerator shall give the raw data within the 5th day of the next month to the supervisor according to
the approved format.
2. The survey supervisor shall submit the survey data to the NSO by e-mail within the 12th day of thenext month after the field work.

HOUSEHOLD SOCIO-ECONOMIC SURVEY
FOR THE HOUSEHOLDS OF THE CAPITAL CITY AND AIMAG CENTERSSECTION 0 - GENERAL QUESTIONS
1. HOUSEHOLD ID
Cluster number

HouseholdNo

NAME OF THE HOUSEHOLD HEAD

ADDRESS

2. Did any visitor stay here with yourhousehold for the last month?
ENUMERATORКод(SPECIFY NUMBER OF VISITORS)
3. How many days?

SUPERVISOR

Код

umber

Person/day(MULTIPLE THE NUMBER OF VISITORS BY DAYS STAYED )NOTE:Manual Mongolia HSES 2012 Version 2.0

174

SECTION 11: HOUSEHOLD FOOD CONSUMPTIONFOOD CONSUMPTION BY DIARY
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGSECOND 10 DAYS /11- 20/

FIRST 10 DAYS /1-10/(11.01)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consumed

ITEMS

Unit

2.
3.
4. OwnPurchase Received
productiondfree

THIRD 10 DAYS /21-30,/(11.02)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Received
freed

QUANTITYQUANTITY

4. Ownproduction(11.03)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Receiveddfree
QUANTITY

4. Ownproduction(11.04)AVERAGEPRICE OF THE
UNITS/Write theaverage price ofthe three 10days/

TUGRUGS / [UNIT]

FLOUR AND FLOUR PRODUCTS

10100
10101 Bread (1 piece = 670 gr)piece/ piece

10102 Rice

Kg

/ Kg

10103 Flour, highest grade

Kg

/ Kg

10104 Flour, grade 1

Kg

/ Kg

10105 Flour, grade 2

Kg

/ Kg

10106 Other (barley flower etc.)

kg

/ kg

10107 Noodle,domestic

Kg

/ Kg

10108 Noodle, import

Kg

/ Kg

10109 Bakery

Kg

/ Kg

10110 Biscuit

Kg

/ Kg

10111 Cake

Kg

/ Kg

10112 Millet

Kg

/ Kg

10113 Other rice (farina…)

Kg

/ Kg

10114 Pizzapiece/ piece

10115 Other flour and flour products

kg

/ kg

10199

Sub total 10102 - 10115
MEAT, MEAT PRODUCTS

10200
10201 Mutton

Kg

/ Kg

10202 Beef

Kg

/ Kg

10203 Goat meat

Kg

/ Kg

10204 Horse meat

Kg

/ Kg

10205 Camel meat

Kg

Manual Mongolia HSES 2012 Version 2.0

/ Kg

175

SECTION 11: HOUSEHOLD FOOD CONSUMPTIONFOOD CONSUMPTION BY DIARY
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGSECOND 10 DAYS /11- 20/

FIRST 10 DAYS /1-10/(11.01)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consumed

ITEMS

Unit

2.
3.
4. OwnPurchase Received
productiondfree

THIRD 10 DAYS /21-30,/(11.02)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Received

QUANTITY

freed

QUANTITY

4. Ownproduction(11.03)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Receiveddfree
QUANTITY

4. Ownproduction(11.04)AVERAGEPRICE OF THE
UNITS/Write theaverage price ofthe three 10days/

TUGRUGS / [UNIT]

10206 Dried meat

Kg

/ Kg

10207 chicken

Kg

/ Kg

10208 Pork

Kg

/ Kg

10209 Bacon

Kg

/ Kg

10210 Game

Kg

/ Kg

10211 Other poultry

Kg

/ Kg

10212 Animal interior

Kg

/ Kg

10213 Sausage,salami kg

Kg

/ Kg

10214 Sausage

Kg

/ Kg

10215 Canned and semi-processed meat

Kg

/ Kg

Kg

/ Kg

10216

Other (frozen dumplings, buuz, animal headand shiir

10299

Sub total 10201 - 10216
FISH AND SEAFOOD

10300
10301 Fish

Kg

/ Kg

10302 Dried, smoked, salted fish

Kg

/ Kg

10303 Canned fish

Kg

/ Kg

10304 Other (crab etc )

Kg

/ Kg

10399

Sub total 10301 - 10304
MILK, DIARY PRODUCTS AND EGGS

10400
10401 Milkliter

/ liter

10402 Youghurt

liter/ liter

10403 Eggs

piece

Manual Mongolia HSES 2012 Version 2.0/ piece176

SECTION 11: HOUSEHOLD FOOD CONSUMPTIONFOOD CONSUMPTION BY DIARY
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGSECOND 10 DAYS /11- 20/

FIRST 10 DAYS /1-10/(11.01)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consumed

ITEMS

Unit

2.
3.
4. OwnPurchase Received
productiondfree

THIRD 10 DAYS /21-30,/(11.02)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Received

QUANTITY

freed

QUANTITY

4. Ownproduction(11.03)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Receiveddfree
QUANTITY

4. Ownproduction(11.04)AVERAGEPRICE OF THE
UNITS/Write theaverage price ofthe three 10days/

TUGRUGS / [UNIT]

10404 Dried curds

kg

/ kg

10405 Horse milk, l

liter/ liter

10406 Curds

Kg

/ Kg

10407 Cheese, national

Kg

/ Kg

10408 Cheese

Kg

/ Kg

10409 Curd (not sour)

Kg

/ Kg

10410 Other milk products

Kg

/ Kg

10411 Dried and coffee milk

Kg

/ Kg

10412 Condensed milkliter

/ liter

10413 Sour cream

kg

/ kg

10414 Dried eggs
Other (milk with fruit flavor, flavored
10415
yoghurt etc.)
10499
Sub total 10401 - 10415

kg

/ kg

OILS AND FAT

10500
10501 Butter

kg

/ kg

10502 Margarine

kg

/ kg

10503 Vegetable oil

liter/ liter

10504 Edible animal fats

Kg

/ Kg

10505 Cream

Kg

/ Kg

10506 Tradiitional butter

Kg

/ Kg

10507 Olive oil

Liter/ Liter

10508 Other (marmot, pig oil etc.)

Kg

/ Kg

10599

Sub total 10501 - 10508

Manual Mongolia HSES 2012 Version 2.0

177

SECTION 11: HOUSEHOLD FOOD CONSUMPTIONFOOD CONSUMPTION BY DIARY
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGSECOND 10 DAYS /11- 20/

FIRST 10 DAYS /1-10/(11.01)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consumed

ITEMS

Unit

2.
3.
4. OwnPurchase Received
productiondfree

THIRD 10 DAYS /21-30,/(11.02)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Received
freed

QUANTITYQUANTITY

4. Ownproduction(11.03)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Receiveddfree
QUANTITY

4. Ownproduction(11.04)AVERAGEPRICE OF THE
UNITS/Write theaverage price ofthe three 10days/

TUGRUGS / [UNIT]FRUITS

10600
10601 Apple

Kg

/ Kg

10602 Mandarin

Kg

/ Kg

10603 Grape

Kg

/ Kg

10604 Watermelon

Kg

/ Kg

10605 Natural wild fruit

Kg

/ Kg

10606 Dried fruit

Kg

/ Kg

10607 Wild nuts,kg

Kg

/ Kg

10608 Other nuts

Kg

/ Kg

10609 Other Fruits

Kg

/ Kg

10699

Sub total 10601 - 10609
VEGETABLES

10700
10701 Potato

Kg

/ Kg

10702 Cabbage

Kg

/ Kg

10703 Carrot

Kg

/ Kg

10704 Turnip

Kg

/ Kg

10705 Onion

Kg

/ Kg

10706 Garlic

gm

/ gm

10707 Tomato

Kg

/ Kg

10708 Cucumber

Kg

/ Kg

10709 Jelly sticks

Kg

/ Kg

10710 Canned cucumber

Kg

/ Kg

10711 Canned vegetable saladKg10712 Pepper

Kg

/ Kg
Manual Mongolia HSES 2012 Version 2.0

/ Kg

178

SECTION 11: HOUSEHOLD FOOD CONSUMPTIONFOOD CONSUMPTION BY DIARY
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGSECOND 10 DAYS /11- 20/

FIRST 10 DAYS /1-10/(11.01)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consumed2.
3.
4. OwnPurchase Received
productiondfree

THIRD 10 DAYS /21-30,/(11.02)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Received
freed

QUANTITYQUANTITY

4. Ownproduction(11.03)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Receiveddfree
QUANTITY

4. Ownproduction(11.04)AVERAGEPRICE OF THE
UNITS/Write theaverage price ofthe three 10days/

TUGRUGS / [UNIT]

ITEMS

Unit

10713 Mushrooms, sea kale

Kg

/ Kg

Kg

/ Kg

10714

Other (processed vegetables,
spinach etc.)

10799

Sub total 10701 - 10714
SUGAR, SWEETS AND JAM

10800
10801 Sugar

Kg

/ Kg

10802 Lump sugar

Kg

/ Kg

10803 Sugar substitution

gm

/ gm

10804 Candy

kg

/ kg

10805 Sweet (chewable)

kg

/ kg

10806 Chocolate

gm

/ gm

10807 Honey

gm

/ gm

10808 Compote

gm

/ gm

10809 Jam

gm

/ gm

10810 Icecream

gm

/ gm

10811 Chewing gum

piece/ piece10812 Syrup

kg

/ kg

10813 Other (marmelade, sugar jam)10899

Sub total 10801 - 10813
OTHER FOOD

10900
10901 Salt

gm

/ gm

10902 Vinegar

gm

/ gm

10903 Ketchup, sauce

gm

/ gm

10904 Mayonnaisekg

Manual Mongolia HSES 2012 Version 2.0

/ kg

179

SECTION 11: HOUSEHOLD FOOD CONSUMPTIONFOOD CONSUMPTION BY DIARY
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGSECOND 10 DAYS /11- 20/

FIRST 10 DAYS /1-10/(11.01)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consumed

ITEMS

Unit

2.
3.
4. OwnPurchase Received
productiondfree

THIRD 10 DAYS /21-30,/(11.02)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Received
freed

QUANTITYQUANTITY

4. Ownproduction(11.03)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Receiveddfree
QUANTITY

4. Ownproduction(11.04)AVERAGEPRICE OF THE
UNITS/Write theaverage price ofthe three 10days/

TUGRUGS / [UNIT]

10905 Yeast

gm

/ gm

10906 Spice

gm

/ gm

10907 Babyfood

kg

/ kg

10908 Other (mustard etc)
Sub total 10901 - 10908

10999

TEA AND COFFEE

11000
11001 Green tea

gm

/ gm

11002 Tea

gm

/ gm

11003 Coffee

gm

/ gm

11004 Cocoa

gm

/ gm

gm

/ gm

11005

Other (tea substitute, coffee, tea
extract etc)
Sub total 11001 - 11005

11099

MINERAL WATER AND SOFT DRINKS

11100
11101 Drink (gasified and ungasified)liter/ liter

Juice (concentrated, fruit andvegetables)

liter/ liter

11103 Pure water, bottled

liter/ liter

11104 Other soft drinks (sirup etc.)

liter/ liter

11102

11199

Sub total 11101 - 11104
ALCOHOLIC BEVERAGES

11200
11201 Vodka, domestic

liter/ liter

11202 Beer, domestic

liter/ liter

11203 Vodka, imported

liter

Manual Mongolia HSES 2012 Version 2.0/ liter

180

SECTION 11: HOUSEHOLD FOOD CONSUMPTIONFOOD CONSUMPTION BY DIARY
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGSECOND 10 DAYS /11- 20/

FIRST 10 DAYS /1-10/(11.01)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consumed

ITEMS

Unit

2.
3.
4. OwnPurchase Received
productiondfree
QUANTITY

THIRD 10 DAYS /21-30,/(11.02)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Received
freed

QUANTITY

4. Ownproduction(11.03)
MAIN SOURCES OF CONSUMED
ITEMS

1. Total
consume3.
2.
dPurchase Receiveddfree
QUANTITY

4. Ownproduction(11.04)AVERAGEPRICE OF THE
UNITS/Write theaverage price ofthe three 10days/

TUGRUGS / [UNIT]

11204 Beer, imported

liter/ liter

11205 Wine

liter

/ liter

11206 Other alcoholic beverages

liter/ liter11299

Sub total 11201 - 11206
TOBACCO AND CIGARETTES

11300
11301 Cigarette, imported

box

/box

11302 Cigarette, domestic

box

/box

11303 Tobacco

gm

/ gm

11304 Snuff

gm

/ gm

11305 Other (Chewing and leaf tobacco)

gm

/ gm

11399

Sub total 11301 -Manual Mongolia HSES 2012 Version 2.0

181

FOOD ITEMS
CodeFOOD ITEMS
Unit

10100 Flour and flour products
10101 Bread (1 piece = 670 gr)

Code

FOOD ITEMS
Unit

10400 Milk, diary products, eggs

Code

FOOD ITEMS
Unit

Code

kg

11100 Pure water, soft drinks, juice

liter
liter

10401 Milk

liter

10705 Onion

kg

10402 Youghurt

liter

10706 Garlicgm

10103 Flour, highest gradekg

10403 Eggs

piece

10707 Tomato

kg

11101 Drink (gasified and ungasified)
Juice (concentrated, fruit and
11102
vegetables)
11103 Pure water, bottled

10104 Flour, grade 1

kg

10404 Dried curds

kg

10708 Cucumber

kg

11104 Other soft drinks (siryp etc.)

10105 Flour, grade 2kg

10405 Horse milk, l

liter

10709 Jelly sticks

kg

11200 Alcoholic bewerages

10102 Rice

piece
kg

Unit

10704 Turnip

liter
liter

10106 Other flour (barley flower etc)kg

10406 Curds

kg

10710 Canned cucumber

kg

11201 Vodka, domestic

liter

10107 Noodle,domestic

kg

10407 Cheese, nationalkg

10711 Canned vegetable saladkg

11202 Beer, domestic

liter

10108 Noodle, importkg

10408 Cheesekg

10712 Pepper

kg

11203 Vodka, imported

liter

10109 Bakerykg

10409 Curd (not sour)kg

10713 Mushrooms, sea kalekg

11204 Beer, imported

liter10110 Biscuitkg

10410 Other milk products

kg

10714

kg

11205 Wine

liter10111 Cakekg

10411 Dried and coffee milk

kg

10800 Sweet, fruit jam

11206 Other alcoholic beverages

liter

10112 Milletkg

10412 Condensed milk

liter

10801 Sugarkg

11300 Tobacco and cigarettes

kg

10413 Sour creamkg

10802 Lump sugar

kg

11301 Cigarette, imported

box

piece

10414 Dried eggs

kg

10803 Sugar substitution

gm

11302 Cigarette, domesticbox

10804 Candykg

11303 Tobaccogm

10805 Sweet (chewable)

kg

11304 Snuffgm

10806 Chocolate

gm

11305 Other (chewing and leaf tobacco)gm

10113 Other rice (farina…)
10114 Pizza
10115 Other flour and flour products (undried noodle etc)kg

10200 Meat, meat products

10415

Other (milk with fruit flavor, flavoredyoghurt etc.)

10500 Oils and fat

Other (processed vegetables, spinachetc)10201 Muttonkg

10501 Butter

10202 Beef

kg

10502 Margarine

kg

10807 Honeygm

10203 Goat meatkg

10503 Vegetable oil

liter

10808 Compote

gm

10204 Horse meatkg

10504 Edible animal fatskg

10809 Jam

gm

10205 Camel meatkg

10505 Creamkg

10810 Icecream

10206 Dried meatkg

10506 Traditional butterkg

10811 Chewing gum

10207 chicken

kg

10507 Olive oil

liter

10812 Syrup

10208 Pork

kg

10508 Other (marmot, pig oil etc)kg10813 Other (marmelade, sugar jam

10209 Bacon

kg10600 Fruit

10210 Gamekg

10601 Applekg

10901 Salt

gm

10211 Other poultrykg

10602 Mandarin

kg

10902 Vinegargm

10212 Animal interiorkg

10603 Grapekg

10903 Ketchup, saucegm

10213 Sausage,salami kg

kg

10604 Watermelon

kg

10904 Mayonnaise

kg

Sausagekg

10605 Áайгалèéн жимсkg

10905 Yeastgm

10215 Canned and semi-processed meatkg

10606 Dried fruit

kg

10906 Spicegm10216 Other (frozen dumplings, buuz etc)kg10607 Wild nuts,kg

kg

10907 Baby foodkg

10608 Other nuts

kg

10908 Other (mustard etc

kg

11000 Tea, coffee

10214

10300 Fish and seafood

kg

gm
piece
kg

10900 Other food

10301 Fishkg

10609 Other Fruits

10302 Dried, smoked, salted fishkg

10700 Vegetables

11001 Green tea

gm

10303 Canned fishkg

10701 Potato

kg

11002 Teagm

10304 Other (crabs etc )kg

10702 Cabbagekg

11003 Coffeegm

10703 Carrot

kg

11004 Cocoagm

Other (tea substitute, êîôå, coffee, tea
11005
Manual Mongolia
HSES
extractetc) 2012 Version 2.0

gm

182

Appendix 3 to Order ../..
dated December 25, 2008of the Chairman of the NSO

HSES-2b
1.Enumerator shall give the raw data within the 5th day of the next month to the supervisor according to
the approved format.
2. The survey supervisor shall submit the survey data to the NSO by e-mail within the 12th day of thenext month after the field work.

HOUSEHOLD SOCIO-ECONOMIC SURVEY
For the rural households /soum center and herders/
SECTION 0 - GENERAL QUESTIONS
1. HOUSEHOLD ID
Cluster number

HouseholdNo

NAME OF THE HOUSEHOLD HEAD

ADDRESS

2. Did any visitor stay here with yourhousehold for the last month?
ENUMERATOR(SPECIFY NUMBER OF VISITORS)

Code

3. How many days?
SUPERVISOR

Code

umber

Person/day(MULTIPLE THE NUMBER OF VISITORS BY DAYS STAYED )NOTE:Manual Mongolia HSES 2012 Version 2.0

183

SECTION 12: HOUSEHOLD FOOD CONSUMPTIONASK QUESTION (12.01) FOR ALL ITEMS FIRST, AND WRITE"1" IN THE FIRST COLUMN IF THE ANSWER IS YES AND
WRIETE "2" IN THE SECOND COLUMN OTHERWISE AND
THEN FOR THE ONES WHERE THE ANSWER IS "1: YES"ASK QUESTIONS (12.02) TO (12.06)(12.01)Have the household members consumed ..[ITEM].. During the past 7 days?
Yes

No

1

2

FOOD CONSUMPTION BY RECALLCONSUMPTION OF THE PAST 7 DAYS
MAIN SOURCES OF THE CONSUMPTION
TOTAL(12.02)(12.02)=(12.03)+(12.05)+(12.06)
ITEMS

UNIT

PURCHASE(12.03)How many quantity of [ Item ]did your household consume forthe past 7 days?
Consumed fromQUANTITY(12.04)the purchase

Unit price of thepurchased item

QUANTITYTUGRUG / [unit]

10101 Bread (1 piece = 670 gr)piece/ piece

10102 Rice

Kg

/ Kg

10103 Flour, highest grade

Kg

/ Kg

10104 Flour, grade 1

Kg

/ Kg

10105 Flour, grade 2

Kg

/ Kg

10106 Other flour (barley flour etc.)

Kg

/ Kg

10107 Noodle,domestic

Kg

/ Kg

10108 Noodle, import

Kg

/ Kg

10109 Bakery

Kg

/ Kg

10110 Biscuit

Kg

/ Kg

10111 Cake

Kg

/ Kg

10112 Millet

Kg

/ Kg

10113 Other rice (farina…)

Kg

/ Kg

Piece

/ Piece

10114 Pizza
10115 Other flour and flour products (undried noodle etc.)
10199

kg

/ kg

Sub total 10102 - 10115
MEAT, MEAT PRODUCTS

10200
10201 Mutton

Kg

/ Kg

10202 Beef

Kg

/ Kg

10203 Goat meat

Kg

Manual Mongolia HSES 2012 Version 2.0

OWN(12.05)(12.06)

Consumed from
Consumed fromthe itemown production
received free
QUANTITY

FLOUR AND FLOUR PRODUCTS

10100

RECEIVED FREE

/ Kg

QUANTITY184

SECTION 12: HOUSEHOLD FOOD CONSUMPTIONASK QUESTION (12.01) FOR ALL ITEMS FIRST, AND WRITE"1" IN THE FIRST COLUMN IF THE ANSWER IS YES AND
WRIETE "2" IN THE SECOND COLUMN OTHERWISE AND
THEN FOR THE ONES WHERE THE ANSWER IS "1: YES"ASK QUESTIONS (12.02) TO (12.06)(12.01)Have the household members consumed ..[ITEM].. During the past 7 days?
Yes

No

1

2

FOOD CONSUMPTION BY RECALLCONSUMPTION OF THE PAST 7 DAYS
MAIN SOURCES OF THE CONSUMPTION
TOTAL(12.02)(12.02)=(12.03)+(12.05)+(12.06)
ITEMS

UNIT

PURCHASE(12.03)How many quantity of [ Item ]did your household consume forthe past 7 days?
Consumed from

(12.04)the purchase

Unit price of thepurchased item

QUANTITYTUGRUG / [unit]

QUANTITY

10204 Horse meat

Kg

/ Kg

10205 Camel meat

Kg

/ Kg

10206 Dried meat

Kg

/ Kg

10207 Chicken

Kg

/ Kg

10208 Pork

Kg

/ Kg

10209 Bacon

Kg

/ Kg

10210 Game

Kg

/ Kg

10211 Other poultry

Kg

/ Kg

10212 Animal interior

Kg

/ Kg

10213 Sausage,salami kg

Kg

/ Kg

10214 Sausage

Kg

/ Kg

10215 Canned and semi-processed meat

Kg

/ Kg

10216 Other (frozen dumplings, buuz, animal heads etc.)

Kg

/ Kg

10299

Sub total 10201 - 10216
FISH AND SEAFOOD

10300
10301 Fish

Kg

/ Kg

10302 Dried, smoked, salted fish

Kg

/ Kg

10303 Canned fish

Kg

/ Kg

10304 Other fish and seafood (crab etc)

Kg

/ Kg

10399

Sub total 10301 - 10304
MILK, CHEESE AND EGGS

10400
10401 Milk

Liter

Manual Mongolia HSES 2012 Version 2.0/ Liter

RECEIVED FREE

OWN

(12.05)(12.06)

Consumed from
Consumed fromthe itemown production
received free
QUANTITYQUANTITY185

SECTION 12: HOUSEHOLD FOOD CONSUMPTIONASK QUESTION (12.01) FOR ALL ITEMS FIRST, AND WRITE"1" IN THE FIRST COLUMN IF THE ANSWER IS YES AND
WRIETE "2" IN THE SECOND COLUMN OTHERWISE AND
THEN FOR THE ONES WHERE THE ANSWER IS "1: YES"ASK QUESTIONS (12.02) TO (12.06)(12.01)Have the household members consumed ..[ITEM].. During the past 7 days?
Yes

No

1

2

FOOD CONSUMPTION BY RECALLCONSUMPTION OF THE PAST 7 DAYS
MAIN SOURCES OF THE CONSUMPTION
TOTAL(12.02)

PURCHASE(12.03)How many quantity of [ Item ]did your household consume forthe past 7 days?
Consumed from
(12.02)=(12.03)+(12.05)+(12.06)

ITEMS

UNIT

QUANTITY(12.04)the purchase

Unit price of thepurchased item

QUANTITYTUGRUG / [unit]

Liter/ Liter

10403 Eggs

ø/ø

10404 Dried curds

Kg

/ Kg

10405 Horse milk, l

Liter/ Liter

10406 Curds

Kg

/ Kg

10407 Cheese, national

Kg

/ Kg

10408 Cheese

Kg

/ Kg

10409 Curd (not sour)

Kg

/ Kg

10410 Other diary products

Kg

/ Kg

10411 Dried and coffee milk

Kg

/ Kg

10412 Condensed milk

Liter

/ Liter

10413 Sour cream

Kg

/ Kg

10414 Dried eggs

Kg

/ Kg

10415 Other (flavored yoghurt, fruit etc)
Sub total 10401 - 10415
OILS AND FAT

10500
10501 Butter

Kg

/ Kg

10502 Margarine

Kg

/ Kg

10503 Vegetable oil

Liter/ Liter

10504 Oil made of animal fat

Kg

/ Kg

10505 Traditional cream

Kg

/ Kg

10506 Traditional butter

Kg

Manual Mongolia HSES 2012 Version 2.0

OWN(12.05)(12.06)

Consumed from
Consumed fromthe itemown production
received free
QUANTITY

10402 Youghurt

10499

RECEIVED FREE

/ Kg

QUANTITY186

SECTION 12: HOUSEHOLD FOOD CONSUMPTIONASK QUESTION (12.01) FOR ALL ITEMS FIRST, AND WRITE"1" IN THE FIRST COLUMN IF THE ANSWER IS YES AND
WRIETE "2" IN THE SECOND COLUMN OTHERWISE AND
THEN FOR THE ONES WHERE THE ANSWER IS "1: YES"ASK QUESTIONS (12.02) TO (12.06)(12.01)Have the household members consumed ..[ITEM].. During the past 7 days?
Yes

No

1

2

FOOD CONSUMPTION BY RECALLCONSUMPTION OF THE PAST 7 DAYS
MAIN SOURCES OF THE CONSUMPTION
TOTAL(12.02)

PURCHASE(12.03)How many quantity of [ Item ]did your household consume forthe past 7 days?
Consumed from
(12.02)=(12.03)+(12.05)+(12.06)

ITEMS

UNIT

QUANTITY(12.04)the purchase

Unit price of thepurchased item

QUANTITYTUGRUG / [unit]

10507 Olive oil

Liter/ Liter

10508 Other (Pig, marmot oil, fat etc.)

Kg

/ Kg

10599

Sub total 10501 - 10508
FRUITS

10600
10601 Apple

Kg

/ Kg

10602 Mandarin

Kg

/ Kg

10603 Grape

Kg

/ Kg

10604 Watermelon

Kg

/ Kg

10605 Wild fruit

Kg

/ Kg

10606 Dried fruit

Kg

/ Kg

10607 Wild nut

Kg

/ Kg

10608 Other nut

Kg

/ Kg

10609 Other Fruits

Kg

/ Kg

10699

Sub total 10601 - 10609
VEGETABLES

10700
10701 Potato

Kg

/ Kg

10702 Cabbage

Kg

/ Kg

10703 Carrot

Kg

/ Kg

10704 Turnip

Kg

/ Kg

10705 Onion

Kg

/ Kg

10706 Garlic

Gm

/ Gm

10707 Tomato

Kg

Manual Mongolia HSES 2012 Version 2.0/ Kg

RECEIVED FREE

OWN

(12.05)(12.06)

Consumed from
Consumed fromthe itemown production
received free
QUANTITYQUANTITY187

SECTION 12: HOUSEHOLD FOOD CONSUMPTIONASK QUESTION (12.01) FOR ALL ITEMS FIRST, AND WRITE"1" IN THE FIRST COLUMN IF THE ANSWER IS YES AND
WRIETE "2" IN THE SECOND COLUMN OTHERWISE AND
THEN FOR THE ONES WHERE THE ANSWER IS "1: YES"ASK QUESTIONS (12.02) TO (12.06)(12.01)Have the household members consumed ..[ITEM].. During the past 7 days?
Yes

No

1

2

FOOD CONSUMPTION BY RECALLCONSUMPTION OF THE PAST 7 DAYS
MAIN SOURCES OF THE CONSUMPTION
TOTAL(12.02)(12.02)=(12.03)+(12.05)+(12.06)
ITEMS

UNIT

PURCHASE(12.03)How many quantity of [ Item ]did your household consume forthe past 7 days?
Consumed fromQUANTITY(12.04)the purchase

Unit price of thepurchased item

QUANTITYTUGRUG / [unit]

10708 Cucumber

Kg

/ Kg

10709 Jelly sticks

Kg

/ Kg

10710 Canned cucumber

Kg

/ Kg

10711 Canned vegetable salad

Kg

/ Kg

10712 Pepper

Kg

/ Kg

10713 Mushrooms, sea kale

Kg

/ Kg

10714 Other ( processed vegetables, spinach etc)

Kg

/ Kg

10799

Sub total 10701 - 10714
SUGAR, SWEET AND JAM

10800
10801 Sugar

Kg

/ Kg

10802 Lump sugar

Kg

/ Kg

10803 Sugar substitution

Gm

/ Gm

10804 Candy

Kg

/ Kg

10805 Sweet (chewable)

Kg

/ Kg

10806 Chocolate

Gm

/ Gm

10807 Honey

Gm

/ Gm

10808 Compote

Gm

/ Gm

10809 Jam

Gm

/ Gm

10810 Icecream

Gm

/ Gm

10811 Chewing gum

piece/ piece10812 Syrup

Kg

/ Kg

10813 Other (marmelade, sugar jam etc.)

Manual Mongolia HSES 2012 Version 2.0

RECEIVED FREE

OWN

(12.05)(12.06)

Consumed from
Consumed fromthe itemown production
received free
QUANTITYQUANTITY188

SECTION 12: HOUSEHOLD FOOD CONSUMPTIONASK QUESTION (12.01) FOR ALL ITEMS FIRST, AND WRITE"1" IN THE FIRST COLUMN IF THE ANSWER IS YES AND
WRIETE "2" IN THE SECOND COLUMN OTHERWISE AND
THEN FOR THE ONES WHERE THE ANSWER IS "1: YES"ASK QUESTIONS (12.02) TO (12.06)(12.01)Have the household members consumed ..[ITEM].. During the past 7 days?
Yes

No

1

2

FOOD CONSUMPTION BY RECALLCONSUMPTION OF THE PAST 7 DAYS
MAIN SOURCES OF THE CONSUMPTION
TOTAL(12.02)

PURCHASE(12.03)How many quantity of [ Item ]did your household consume forthe past 7 days?
Consumed from
(12.02)=(12.03)+(12.05)+(12.06)

ITEMS
10899

UNIT

(12.04)the purchase

Unit price of thepurchased item

QUANTITYTUGRUG / [unit]

QUANTITY

Sub total 10801 - 10813
OTHER FOOD

10900
10901 Salt

Gm

/ Gm

10902 Vinegar

Gm

/ Gm

10903 Ketchup

Gm

/ Gm

10904 Mayonnaise

Kg

/ Kg

10905 Yeast

Gm

/ Gm

10906 Spice

Gm

/ Gm

10907 Babyfood

Kg

/ Kg

10908 Other (mustard etc.)
10999

Sub total 10901 - 10908
TEA AND COFFEE

11000
11001 Green tea

Gm

/ Gm

11002 Tea

Gm

/ Gm

11003 Coffee

Gm

/ Gm

11004 Cocoa

Gm

/ Gm

11005 Other (tea substitute, coffee, tea extract etc)

Gm

/ Gm

11099

Sub total 11001 - 11005
PURE WATER, JUICE AND SOFT DRINKS

11100
11101 Drink (gasified and ungasified)

Liter/ Liter

11102 Juice (concentrated fruit and vegetable juice)

Liter/ Liter

11103 Pure water, bottled.

Liter

Manual Mongolia HSES 2012 Version 2.0/ Liter

RECEIVED FREE

OWN

(12.05)(12.06)

Consumed from
Consumed fromthe itemown production
received free
QUANTITYQUANTITY189

SECTION 12: HOUSEHOLD FOOD CONSUMPTIONASK QUESTION (12.01) FOR ALL ITEMS FIRST, AND WRITE"1" IN THE FIRST COLUMN IF THE ANSWER IS YES AND
WRIETE "2" IN THE SECOND COLUMN OTHERWISE AND
THEN FOR THE ONES WHERE THE ANSWER IS "1: YES"ASK QUESTIONS (12.02) TO (12.06)(12.01)Have the household members consumed ..[ITEM].. During the past 7 days?
Yes

No

1

2

FOOD CONSUMPTION BY RECALLCONSUMPTION OF THE PAST 7 DAYS
MAIN SOURCES OF THE CONSUMPTION
TOTAL(12.02)(12.02)=(12.03)+(12.05)+(12.06)
ITEMS11104 Other soft drinks

UNIT

PURCHASE(12.03)How many quantity of [ Item ]did your household consume forthe past 7 days?
Consumed fromQUANTITY(12.04)the purchase

Unit price of thepurchased item

QUANTITYTUGRUG / [unit]

Liter

RECEIVED FREE

OWN

(12.05)(12.06)

Consumed from
Consumed fromthe itemown production
received free
QUANTITYQUANTITY/ Liter

Sub total 11101 - 11104

11199

ALCOHOLIC BEVERAGES

11200
11201 Vodka, domestic

Liter/ Liter

11202 Beer, domestic

Liter/ Liter

11203 Vodka, imported

Liter/ Liter

11204 Beer, imported

Liter/ Liter

11205 Wine

Liter

/ Liter

11206 Other alcoholic beverages

Liter/ Liter

Sub total 11201 - 11206

11299

TOBACCO AND CIGARETTES

11300
11301 Cigarette, imported

Box

/ Box

11302 Cigarette, domestic

Box

/ Box

11303 Tobacco

Gm

/ Gm

11304 Snuff

Gm

/ Gm

11305 Other (chewing tobacco, leaf tobacco etc)

Gm

/ Gm

11399 Sub total 11301 - 11305

ITEM

Food consumption /not in household/(15.07)
Did you or any member of your household spent
following items during the past 7 days?
YES

1(15.08)How much did all members of your household spend on purchases of..[ITEM].. during the past 7 days?
Manual Mongolia HSES 2012 Version 2.0(15.09)What is the value of all ..[ITEM].. that all members of your household
received free from others during the past 7 days?

190

SECTION 12: HOUSEHOLD FOOD CONSUMPTIONASK QUESTION (12.01) FOR ALL ITEMS FIRST, AND WRITE"1" IN THE FIRST COLUMN IF THE ANSWER IS YES AND
WRIETE "2" IN THE SECOND COLUMN OTHERWISE AND
THEN FOR THE ONES WHERE THE ANSWER IS "1: YES"ASK QUESTIONS (12.02) TO (12.06)(12.01)Have the household members consumed ..[ITEM].. During the past 7 days?
Yes

No

1

2

FOOD CONSUMPTION BY RECALLCONSUMPTION OF THE PAST 7 DAYS
MAIN SOURCES OF THE CONSUMPTION
TOTAL(12.02)(12.02)=(12.03)+(12.05)+(12.06)
ITEMS
1
2

UNIT

PURCHASE(12.03)How many quantity of [ Item ]did your household consume forthe past 7 days?
Consumed fromQUANTITY(12.04)the purchase

Unit price of thepurchased item

QUANTITYTUGRUG / [unit]NO
2 → Next item
Restaurants, cafes
Canteens in schools, works canteens

Manual Mongolia HSES 2012 Version 2.0

RECEIVED FREE

OWN

(12.05)(12.06)

Consumed from
Consumed fromthe itemown production
received free
QUANTITYQUANTITYCluster number

HH No

SOUM CENTER - 3 RURAL - 4

CAPITAL - 1 AIMAG CENTER -2

Manual Mongolia HSES 2012 Version 2.0

MAIN HOUSEHOLDHOUSEHOLD AT THE ADDRESS WRITTENSUBSTITUTIVE HOUSEHOLD

9. HOUSEHOLD SAMPLE SELECTION(Equal to the sum of members answered "a right person to continue asking
questions" against Question 11, Section I.)

8. NUMBER OF HOUSEHOLD MEMBERS..........................................................

7. DATA ENTRY OPERATOR..........................................................

5. ENUMERATOR..........................................................
6. SUPERVISOR

4. LOCATION..........................................................

3. SOUM/DISTRICT..........................................................

2. AIMAG/CAPITAL

Quarter

1. HOUSEHOLD ID

1
2
3

Code

Code

Code

Code

Code

Code

Code

Code

SECTION 0-GENERAL QUESTIONS

DAY

MONTH

YEAR

1

.....................................................................................

Day…… month…… year………..

ADDRESS…………………………………………………………………………………..

FIST AND LAST NAME OF THE HOUSEHOLD HEAD ........................................................

HOUSEHOLD NOT FOUND

REFUSEDPOSTPONEDHOUSEHOLD TEMPERARILY NOT PRESENTNO RESPONDENT IN THE HOUSEHOLDPARTIALLY COMPLETEDCOMPLETE* Result code

4

3

2

1

VISITSDATERESULT*

7

6

5

4

3

1
2

1. The enumerator will submit the information in form sheets to the supervisor within the 5th of each month.
2. Statistial office/department of the Capital city/Aimag will send via email that information to the National Statistical Office (NSO) withinHSES-1
the 12th of that month.

HOUSEHOLD SOCIO-ECONOMIC SURVEY

Appendice 1 to Decree No. 01/179, dated November 29, 2011,of the Chairman of the National Statistical Office

191

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15

ID CODE

01

07

08

09

10

11

GRAND PARENT

GRANDCHILDOTHER RELATIVE

OTHER

06

2

05 FEMALE

FATHER / MOTHER IN LAWSON / DAUGHTER IN LAW

1

04 MALE

03

02

SEX

What is ..[NAME]'s.. relationship to thehousehold head?

NAME

BEFORE GOING ON TO
QUESTIONS 1.04-1.11,
HEAD
PLEASE FILL IN
QUESTIONS 1.01--1.03 ON WIFE / HUSBAND
THE NAME, RELATION TO SON / DAUGHTER
THE HEAD OF HH AND
FATHER / MOTHER
THE SEX FOR EACH
HOUSEHOLD MEMBER. BROTHER / SISTER(1.03)(1.02)(1.01)SECTION 1: HOUSEHOLD ROSTER(1.04)YEAR OF
BIRTH

What is the yearof birth of..[NAME]..?

YEARS

MTHS

AGE

FOR CHILDREN
YOUNGER THAN
ONE YEAR,WRITE THE AGE
IN MONTHS.

AGE INCOMPLETED
YEARS

AGE

(1.05)WIDOWEDDIVORCED

2(1.08)(1.08)(1.08)

4 ►(1.08)5 ►6 ►3

NOT CERTIFIEDSEPARATED2

1 ►CERTIFIEDMARRIED:

NEVER MARRIED

Marital status(1.06)(1.08)
FATHER'S ID
CODE(1.09)ID CODEID CODE(1.10)(1.10)(1.11)ID CODEDAYSMONTHS► NEXT PERSON

NO

YES

2

1

MOTHER'S ID 1. Was s/he permanently 2. Was s/he permanently at USING QUESTION (1.10), PLEASE DEFINE
IF S/HE IS A HOUSEHOLD MEMBER WHO
CODE
at her/his
her/his HOME/household
IS TO BE ASKED THE FURHTER
HOME/household during during the past 12 months? If
QUESTIONS.
the past 1 month? If not, not, for how many months
for how many days was was s/he away?
s/he away?
DO NOT INCLUDE A HOUSEHOLD HEAD
IFS/HE WAS AT HER/HIS
OR ANY HOUSEHOLD STUDENTMEMBERS AWAY FROM
IFS/HE WAS AT
HOME/HOUSEHOLDHOME/HOUSEHOLD FOR MORE THAN 11
HER/HISPERMANENTLY, WRITEMONTHS AND ANY OTHER MEMBERS
HOME/HOUSEHOLD"0".
AWAY FROM HOME/HOUSEHOLD FOR
PERMANENTLY, WRITE
MORE THAN 6 MONTHS.
"0".

IF SPOUSE IS NOTA HOUSEHOLD IF FATHER IS
IF MOTHER IS
MEMBER, CODE NOT A
NOT A
98.
HOUSEHOLD
HOUSEHOLD
MEMBER WRITE MEMBER WRITE
'98'
'99'

What is ..[NAME]..
spouse's ID
CODE?

(1.07)ONLY FOR HOUSEHOLD MEMBERS AGED 15 AND
ABOVE

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15

14

13

12

11

10

09

08

07

06

05

04

03

02

01

ID CODEYESNO►NEXT PERSONLOOK FROMTHE CHECK PAGE.

(2.01)CHECK IF ……[Name] IS
2-7 YEARS OLD.

1
2

RESPONDENT'S
ID CODE

PLEASE LOOK FROMTHE CHECK PAGE.

(2.02)PLEASE WRITE
THE ID CODE OF
THE RESPONDENT.

FOR ALL MEMBERS OF HOUSEHOLD AGED 2-7

SECTION 2. EDUCATIONYES 1 ►(2.05)
NO 2(2.03)
Does …..[Name] goto kindergarten or
nursery?

3

NO SPACE THERE►NEXT PERSONKINDERGARTEN/NURSERY ENVIRONMENT IS5
NO KINDERGARTEN/NURSERY6
DUE TO MIGRATION
7NO NEED
8
OTHER
9

4

2

LACK OF BUDGETKINDERGARTEN/NURSERY IS TOO FAR

1GOES TO SCHOOL(2.04)Why does not …..[Name]
go to kindergarten or nursery?

PART A. PRE-SCHOOL EDUCATIONPUBLICPRIVATE
OTHER(2.05)
What is the ownershp of…..[Name]'s
kindergarten/nursery?

1
2
3

TUGRUGSTUGRUGS1
2
Tuision fee paid Staioneryby the household and learningmaterials

TUGRUGS

3
Food served at
kindergarten/nursery

TUGRUGS4Other

TUGRUGS

5
Total

PLEASE GO TO THE NEXT PERSON AFTER THE QUESTIONS ARE DONE.

ONLY INCLUDE EXPENSES BY THE HOUSHEHOLD.
AFTER ASKING THE INDIVIDUAL AMOUNTS FOR EACH COLUMN,CALCULATE TOTAL. PROBE AND RECONCILE.

IF NOTHING, WRITE ZERO.
VALUE AND INCLUDE NON-CASH EXPENDITURES(2.06)How many tugrugs did your houshold spend on …..[Name]'s
pre-education in the last 12 months?

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12
13
14
15

11

10

09

08

07

06

05

04

03

02

01

ID CODE

12 ► NEXT PERSON

YES

NO

LOOK FROM THE CHECK
PAGE.

(2.07)CHECK IF S/HE IS AGED 6
AND ABOVE.

SECTION 2: EDUCATION

NO

2

YES 1

(2.10)►(2.08)IS THISMEMBERANSWERINGHERSELF/HIM
SELF?

RESPONDENT'S
ID CODECHECK FROM THE
CHECK PAGE.

6

4
5

3

1
2

DOCTOR►(2.12)EDUCATION LEVEL IS DETERMINEDBY THE HIGHEST EDUCATION LEVELOBTAINED

910MASTER

DEGREE OR HIGHER EDUCA 7BACHELOR8TECHNICAL SECONDARYHIGHER-SECONDARYVOCATIONALLOWER-SECONDARYNONEPRIMARYNO

YES, EASILY
YES, WITH
DIFFICULTY

4

3

2

1

NO, COMPLETEDNO,NEVER ATTENDED

NO. DROPPED OUT

YES►(2.14)►(2.16)

NEXT PERSON

4►

3

2

1

(2.12)Are you currently attending school? (If not,please ask if s/he has ever attended school)

PART B. EDUCATION OF HOUSEHOLD MEMBERS AGED 6 AND ABOVE

FOR ALL HOUSEHOLD MEMBERS AGED 6 AND ABOVE(2.09)(2.10)(2.11)Are you literate (Can you
WRITE THE ID CODE What is your education level?
read and write)?
OF THERESPONDENT.

GRADE

2

1

►NEXT PERSON

NO

YES

LOOK FROM THE
CHECK PAGE.

13

SCHOOL TOO FARDUE TO MIGRATIONHAD NO SPACE IN DORMITARYOTHER► NEXT PERSON

9
10
11
12

HAD TO LOOK AFTER OTHERS

7
8

6

5

4

1
2
3

HAD TO WORKDUE TO ILLNESS/DISABILITYLACK OF BUDGETSCHOOL ENVIRONMENT WASNOT GOODEDUCATION QUALITY WAS BAD

NOT INTERESTEDPARENTS NOT INTERESTEDSUBJECTS WERE DIFFICULTFOR ALL HOUSEHOLD MEMBERS WHO DROPPED OUT OF SCHOOL OR N
(2.13) (2.14)(2.15)At which CHECK IF..[NAME]..'S Why did you / [NAME] never attend
school?
AGE. IS 8 or
BETWEEN 8-35
YEARS.

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12
13
14
15

11

10

09

08

07

06

05

04

03

02

01

ID CODEPART B. EDUCATION OF HOUSEHOLD MEMBERS AGED 6 AND ABOVESCHOOLGRADE

KM

MINUTES5TUGRUGS

FOR ALL MEMBERS CURRENTLY ATTENDING SCHOOL AND ANSWERED "YES" TO QUESTION 2.12
(2.22)(2.23)(2.16)(2.17)(2.18)(2.19)(2.20)(2.21)(2.24)(2.25)
Which school are you attending and What is the Where is your /From whom did you/[NAME] How many
Where do you / does
Do you/Does … Did you / [NAME]
How many How longwhat grade are you in now??
ownership ..[NAME]..'s
tugrugs of..[NAME]..live while attending kilometers does it take [NAME]... pay receive any loan for receive loan?
of your /loan for tuition
school located?
school?
tuition last year
(one way) is you/..[NAME]. any tuition?
.[[NAME]..'s
did you/during the past 12
it to your. to travel one
school?
receive duringmonths/?
/..[NAME]'s way fromthe past 12
school from where
CLARIFY
IF
THE
months?
where you you/[NAME]
GOVERNMENT/STAT 1
live
live(s) during/..[NAME].. the school
TYPE
GRADE
CAPITAL CITY 1
YES 1
YES
1
COMPANY, BANK
2
1 lives during term to thisNO 2NO
2 ► (2.26) NGO
3
GENERAL EDUCATIO 1 1 TO 12 PUBLIC 1 AIMAG CENTER2HOME
the school school?
VOCATIONAL SCHOO 2 1 TO 3 PRIVATE 2 SOUM CENTER 3► (2.26)
PARENTS, RELATIVE 4
term?
OTHER
COLLEGE,ACCOMMODATIONINDIVIDUALS
UNIVERSITY
3 1 TO 6 OTHER 3 ABROAD
4 WHERE CHILDREN LIVE 2
5
WHILE ATTENDINGSCHOOLFOREIGN &OTHER
DORMITORY
3
INTERNATIONALRELIGIOUS
6
RELATIVES
4
ORGANIZATION,
NON-FORMALSTATEEDUCATION
OTHER
5AND FOREIGNER
40
FUND LOAN SHALL
WRITE '99' WRITE '99' IF
BE INCLUDEDDON'T
IF DON'T
OTHER
7
KNOW
KNOW

SECTION 2: EDUCATION

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13
14
15

11

10

09

08

07

06

05

04

03

02

01

ID CODEPART B. EDUCATION OF HOUSEHOLD MEMBERS AGED 6 AND ABOVE

2
Tuition paid by thehoushold

TUGRUGS1
Room rent anddormitory

TUGRUGSTUGRUGS

3
Books andstationery

TUGRUGS

4
Uniform

TUGRUGS

5
Transport

TUGRUGS

6
Others

PLEASE GO TO THE NEXT PERSON AFTER THE QUESTIONS ARE DONE.

TUGRUGS

7
Total

ONLY INCLUDE EXPENDITURES BY THE HOUSHEHOLD. AFTER ASKING THE INDIVIDUAL AMOUNTS FOR EACH COLUMN,CALCULATE TOTAL. PROBE AND RECONCILE.

IF NOTHING, WRITE ZERO.

FOR ALL MEMBERS CURRENTLY ATTENDING SCHOOL(2.26)How much did your household spend on your education in the last 12 months ?

SECTION 2: EDUCATION

6

196

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15

ID CODE

NO

►

YES

2

(3.03)

1

ID code

NO

►

YES

3
4

5

WORKING IN A FOREIGN COMPANY/ORGANIZATIONSSELF-EMPLOYED

2

7

6

2

CANNOT AFFORD IT
WORKING IN A PRIVATE COMPANYDUE TO NOT BEING SICK

1NO JOBWhy aren’t you / isn't [NAME] covered by health insurance?

(3.04)(3.05) OTHER

1(3.03)(3.02)(3.01)IS THISAre you/ is
COPY
PERSON[NAME]THE IDPRESENTCODE OF covered byAND
RESPOND healthANSWERING ENT
insurance?
FOR
FROM
HIMSELF/HE THE
RSELF/?
ROSTERSECTION 3: HEALTH

NO

YES
►

(3.07)

2

1(3.05)Have you / has[NAME] got any
disabilities?

OTHER

7

6

5

4

PHYSICALMENTAL

3

2

HEARING

1

SIGHT
SPEAKING(3.06)
Which disability?

NO

YES
►

FIRST

6

5

4

SECONDDAMAGE OR
INTOXICATION BY
EXTERNAL IMPACTBLOOD
CIRCULATIONSYSTEM

2
3

DIGESTIVE SYSTEMURINARY ANDSEXUAL ORGAN

DAYS(3.08)(3.09)
What health complaints did you / How long did you
miss your work,[NAME] have?
school or daily
activities due to theillness in the last
RESPIRATORY
1
one month?
SYSTEM(3.15) OTHER

2

1(3.07)
Did you / [NAME]
have any healthcomplaints in thepast month?

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01
02
03
04
05
06
07
08
09
10
11
12
13
14
15

ID CODENO

TRADITIONAL HEALER, CHIROPRACTIC► (3.12) TREATED MYSELF
2 DID`T KNOW FROM WHERE TO GETTREATMENT

12

11

10
OTHER

6

OTHER

8

6

TUGRUGTUGRUG►(3.17)

NO

YES

2

1

TUGRUGFOR ALL HOUSEHOLD MEMBERS(3.14)(3.10)(3.11)(3.12)(3.13)(3.15)(3.16)
During the past one How much did you pay for
OUTPATIENT EXPENSES
Why did you not get any treatment at a health facility or health provider for yourWhich level hospital did you seek Under whose supervision did you get
Did you seek
treatment from?
month, did you
all medicines and vitamins
health problems?
treatment (the very last time)?
treatment at a2.1.purchase and use on purchased on your own
health facility or
How
much
did
you
pay,
How
much
did
you
your own, without awithout a prescription in
health provider for
pay, either in money or either in money or in kind, prescription, any
the past one month?
your healthfortransportation
other
in
kind,
for
all
costs
medicines and immune
problems?
01
NOT SERIOUS ENOUGH
costs /accomodation, food, boosting vitamins?
associated with theoutpatient visits to a costs of anyone who
02
HEALTH FACILITY TOO FAR
accompanied you, andfacility or health
NO TRANSPORTATION03
CENTRALpractitioner during the gifts for health care workers
1
HOSPITAL/CLINIC
04
and practitioners,etc./
past one month?
HEALTH CARE TOO EXPENSIVE
during the past one month?
ONLY OUT
FOR ALL
TRANSPORT TOO EXPENSIVE
05
AIMAG/DISTRICT CLINIC
2 PROFESIONAL DOCTOR
1 /buying medicinesprescribed, medical
ALTERNATIVES,PATIENT CARE
test, etc./
SKIP TOAT PUBLIC AND
MEDICINE USED IN
06
FAMILY DOCTOR
2
SOUM, INTER-SOUM, AND
3
PRIVATEHEALTH WORKERS NOT FRIENDLYHOSPITAL WILL BE
FAMILY CLINICHEALTHFILLED IN(3.15)07
NURSE
3
HEALTH WORKERS NOT PRESENTFACILITY OR
QUESTIONS (3.21)
08
PRIVATE
4 CHIROPRACTIC
4HEALTH CARE NOT GOOD QUALITYHEALTHAND (3.26)
ABROAD
5
YES
1 NO MONEY09
TRADITIONAL HEALER
5

SECTION 3: HEALTH

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01
02
03
04
05
06
07
08
09
10
11
12
13
14
15

ID CODE2

NO►(3.23)1YES

INCLUDE HEALTH RESORT.

5 OTHER6

ABROADOTHERCHIROPRACTIC

PROFESSINAL DOCTOR

4 TRADITIONAL HEALER

3

2

1

4

3

NIGHTS9TUGRUGS

WRITE ZERO IF NOTHING

IF, DURING THE
PAST 12MONTHS, YOU
STAYED IN
HOSPITAL MORE
THAN ONCE, SUM
UP THE TOTALINCLUDE THE COST FOR
NUMBER OF
MEDICINE PRESCRIBED AND
1 DAYS.
PURCHASED BY HOUSEHOLDMEMBERS2(3.21)How much did you pay for all
costs associated with hospipal
stays, in cash or in kind, for the
past 12 months?

TREATMENT PROVIDED BY HEALTH FACILITIES IN MONGOLA(3.19)(3.20)
Under whose supervision did you How many nights
get treatment (the very last time)? did you spend in
hospital?

PRIVATESOUM AND INTER-SOUM
CLINICCENTRAL
CLINIC/SPECIALIZEDHOSPITALAIMAG/DISTRICT CLINIC

stay get treatment?

(3.17)
During the past 12 months, did you stay at a (3.18)
hospital or clinic overnight?
At which level hospital did you

SECTION 3: HEALTHTUGRUGS

WRITE ZERO IF NOTHING

YES
NO

1
2

NO

YES

2

1

NO

YES

2

1

(3.24)(3.25)
Did you suffer from from Did you suffer from fromany other infectious
hepatitis?
disease?

INFECTIOUS DISEASES-DURING THE PAST 12 MONTHS(3.22)(3.23)How much did you pay, either in Did you suffer frommoney or in kind, forrespiratory diseasetransportation and other costs
during the past 12/accomodation, food, costs ofmonths?
anyone who accompanied you,and gifts for health care workers
and practitioners,etc./ during thepast 12 months?

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02
03
04
05
06
07
08
09
10
11
12
13
14
15

ID CODE(4.02)(4.03)

YES

2

1

NEXT
► WOMANTRY TO INTERVIEW EACHWOMAN INDIVIDUALLY.

NO

YES

2

1
NEXT
► WOMANIS THIS WOMAN ANSWERING Have you ever had sexual
FOR HERSELF?
relationship?

N0 2 ► NEXT PERSON NO

YES 1

CHECK IF THE WOMAN IS
15-49 YEARS OLD.

(4.01)SECTION 4: REPRODUCTIVE HEALTHDON`T KNOW

NO

YES

3

2

1

10

► (4.06)► (4.06)

Have you had any abortion in your life?

(4.04)(4.06)(4.07)

7
8

NOT MARRIED
OTHER

11

10

09

CALENDAR
OTHER

08

07

06

05

04

03

02

01

MALE STERLIZATION

6

►NEXT
WOMAN

FEMALE STERLIZATIONCONDOM

DIDN`T WANT CHILD

2

1

DIAPHRAGMINJECTIONWITHDRAWAL

NO

YES

IUD
PATCH

5

4

3

2

1

WAS/WERE STUDYING

HAD A YOUNG CHILD

HUSBAND AND/OR PARENTS ODUE TO HEALTHDUE T O FAMILYCIRCUMTANCE/LACK OFMONEYPILL/DRUGS

What was the main reason for your last Are you (your partner)
Which method presently do you use forabortion?
presently using a method of contraception?
contraception?

(4.05)FOR WOMEN 15 - 49 YEARS OLD

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14

13

12

11

10

09

08

07

06

05

04

03

02

01

ID CODEYESNO►NEXT PERSON

1
2

Check if s/he is 15 years
old and above.

(5.01)

YES
NO

1
2

► (5.04)(5.02)
Where you born in thissoum/district?

SECTION 5: MIGRATION

YES
NO(5.04)
Where did you live
immediatally before
moving here?

CAPITAL CITY
AIMAG CENTER
1
SOUM CENTER
2
RURAL AREA
►NEXT PERSON ABROAD
OTHER(5.03)Have you ever migrated?

11

1 EDUCATION
2 LIVE NEAR TO MARKET
3 LIVE NEAR TO RELATIVES
4 BE OCCUPIED WITH HERDING
5 OTHER
6

5
6
7
8
9

4

3

MARRIAGE
HEALTH OF FAMILY

12

WORK, MISSIONJOB SEARCH

YEAR

YES
NO

1
2

(5.06)(5.07)In what year did Did you live here
you move here in 2008?
(move backhere)?

PART A. DOMESTIC MIGRATION(5.05)
What was the main reason you chose tomigrate here?

FOR ALL HOUSEHOLD MEMBERS 15 YEARS AND MORE

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15

14

13

12

11

10

09

08

07

06

05

04

03

02

01

ID CODE

YES
1
NO
2►NEXT PERSONMEMBERS WHO CHOSE"NO-2" IN THE QUESTION
1.11 WILL BE INCLUDED.

(5.08)Name household members
who have resided abroad
for more than 6 months.

NAME

CODE

(5.09)In which country is this member living?

12

TO WORK ON MISSION
TO RECEIVE MEDICAL TREATMENT
TO ACCOMPANY HER/HIS PARENTS AND/OR C
OTHERTO WORK PRIVATELY

3
4
5
6
7

YEARS

NO 2 ►NEXT PERSONTUGRUGS

INCLUDE NONCASH
TRANSFERSYES 1

TO WORK UNDER A LABOUR CONTRACT

2(5.13)How many tugrugs
did your household
transfer to thismember in the last
one month?

TUGRUGS

INCLUDE NON-CASH
TRANSFERSHow many tugrugs did yourhousehold transfer to thismember in the last 12
months?

(5.14)PART B. INTERNATIONAL MIGRATION(5.10)(5.11)(5.12)
For what purpose has this household member gone there For how long hass/he lived abroad? Has your household ever madeany cashand non-cash transfers to thismember?
TO STUDY
1

SECTION 5: MIGRATION

202

15

14

13

12

11

10

09

08

07

06

05

04

03

02

01

ID CODE2NO► NEXT PERSON NO

1 YES

YES

PLEASE LOOKFROM THE CHECK
PAGE.

2

► (6.04)

1

ID CODE

PLEASE LOOKFROM THECHECK PAGE.

NO

YES

(6.04)(6.05)► (6.06)

2

OTHER► (6.12)FARMING/CROP FARMING(6.06)

4 NO
5(6.07)I HAVE A SEASONAL JOB► (6.08) OTHER► (6.12)8(6.09)YES► NEXT PERSONI AM A STUDENT/PUPIL

3

OTHER
► (6.11)

FORMS TO JOB-PROVIDERS► (6.10) SUBMITTED APPLICATIONDISABLED

6 OTHER

5
8

7

1
2

► NEXT PERSON

4 YES
5 NO

HAVE A SEASONAL JOB

3

2

1

WAITING FOR A JOBHAVE HOUSEWORK, LOOKAFTER A CHILD► NEXT PERSON

1 I AM AGED.

2(6.11)

What is the reason that you did
Are you registered at
not search a job in the last week? the labour and social
welfare office?

(6.10)

POSTED ADVERTISEMENTS IN A
4
2 NEWSPAPER
LOOK AFTER A SICK PERSON 6

1 SEARCHED IN MEDIA
ADVERSISEMENTS

ASKED HELP FROM FRIENDSAND RELATIVESTURNED TO
THE LABOUR AND SOCIALWELFARE OFFICE

Did you search a What method did you use to search ajob? (NAME THE MAIN METHOD)
job in the lastweek?

(6.08)7 NO

6

5

TEMPORARY

2 COULD NOT FIND A JOB

1

4ON VACATION

32

PREGNANTLOOK AFTER OTHERS

1

SICK

What was the main reason that you
Although you did not did not work in the last week?
work in the last
week, did you workin the last 12
months?

3 YES

2UNPAIDSELF-EMPLOYED:1
ANIMAL HUSBANDRY/LIVESTOCK RAISING

1PAID JOB

ID CODE OF THE Did you work in the
IS THISlast 7 days?
What was the type of the job??
HOUSEHOLD RESPONDENTMEMBERANSWERINGHERSELF/HIM
SELF?

CHECK IF S/HE IS
AGED 10 AND
ABOVE.

(6.03)(6.02)(6.01)FOR ALL HOUSEHOLD MEMBERS AGED 10 AND ABOVESECTION 6. EMPLOYMENT

203

Manual Mongolia HSES 2012 Version 2.0

In which sector did you work?

What job did you have?

DETAILED DESCRIPTION OF THE JOBCATEGORY CODE OF
THE JOB

FOR THE HOUSEHOLD MEMBER WHO DID NOT WORK IN THE LAST WEEK, REGISTER THE MAINJOB S/HE HAD IN THE LAST 12 MONTHS.

WRITE THE NAME OF THE SECTOR

CODE FOR THE ECONOMIC
SECTORIF THE HOUSEHODL MEMBER HAD MORE THAN ONE JOBS, REGISTER THE ONE MOST IMPORTANT FIND AND WRITE THE CODE FOR THE JOB SECTOR FROM THE CATEGORIZATION OF THE
MAIN JOB.
ECONOMIC SECTOR.

(6.13)(6.12)FOR ALL HOUSEHOLD MEMBERS AGED 10 AND ABOVESECTION 6. EMPLOYMENTHOURSWhat is the ownership type of theorganization you worked for?

How many hours aweek did you workon average on this
job?

5
6

8
9

NON-GOVERNMENT ORGANIZATIONOTHERSTATE-BUDGET FUNDED ORGANIZAT 7

LOCALLY OWNED FACTORYSTATE-OWNEDFACTORY

43

LIMITED LIABILITY COMPANY

2CORPORATION

1COOPERATIVEPARTNERSHIP(6.15)(6.14)

204

Manual Mongolia HSES 2012 Version 2.0

What job did you have?

DETAILED DESCRIPTION OF THE JOBCATEGORY CODE OF
THE JOB

FOR THE HOUSEHOLD MEMBER WHO DID NOT WORK IN THE LAST WEEK, REGISTER THE MAINJOB S/HE HAD IN THE LAST 12 MONTHS.

NONEXT PERSON

1
2

YES

WRITE "2" IF SELFEMPLOYED.

Did you receive any cash
and non-cash salary fromworking in the last 12
months?

(6.12)TUGRUGIn the last one month
TUGRUGIn the last 12 months

Salary amountTUGRUG

Bonuses, benefits andcompensations received in thelast 12 months

NON-CASH ITEMS RECEIVED WILL BE VALUED AT THE MARKET RATE OF THAT TIME AND
ADDED TO THE CASH SALARY.

COUNT THE NET SALARY AFTER TAX, SOCIAL INSURANCE AND HEALTH INSURANCE FEES.

How much salary did you receive in total?

(6.16)FOR ALL HOUSEHOLD MEMBERS AGED 10 AND ABOVEIF THE HOUSEHODL MEMBER HAD MORE THAN ONE JOBS, REGISTER THE ONE MOST IMPORTANT
MAIN JOB.

FOR ALL HOUSEHOLD MEMBERS AGED 10 AND ABOVE(6.17)SECTION 6. EMPLOYMENTSECTION 6. EMPLOYMENT(6.19)►NEXT PERSON

NO

YES

1
2

TUGRUGIn the last one month
TUGRUGIn the last 12 months

Salary amountTUGRUG

Bonuses, benefits andcompensations received in thelast 12 months

NON-CASH ITEMS RECEIVED WILL BE VALUED AT THE MARKET RATE OF THAT TIME AND ADDEDTO THE CASH SALARY.

How much salary in total did you receive from all those temporary and other jobs you had?
Did you have any
temporary or other job atthe same time as thisjob in the last 12
ASK THE TOTAL AMOUNT OF SALARY RECEIVED FROM THE TEMPORARY AND THE OTHER JOB.
months?

(6.18)

205

Manual Mongolia HSES 2012 Version 2.0

Manual Mongolia HSES 2012 Version 2.0►

PART B

16

04

03

99 TOTAL

99

07

xxx

TUGRUGS

6 Other (chicken, poultry, swine, bee)

NUMBER

01
02

06

NUMBER

Total value/price of theanimals sold

05

xxx

Of which…
Female animal
Newbornused foryoung animals
breeding

INCLUDE LIVESTOCK SOLD
ALIVE AND SLAUGHTERED

sell

5 Goats

TOTAL

WRITE "0" IF NONE AND SKIP TO NEXTLIVESTOCK

use for own food4 Sheep

3 Camels

2 HorsesName of animals

2

NO

7.02
In the last 12 months, how many ..[ANIMALS].. did the household….
How many ..[ANIMAL].. does the household own
WRITE "0" IF NOTHING
now?
7.05
7.04
7.03

1

YES

TOTAL

Other (Repair, Steam, water, electricity, heating, Rent, etc. )Fence, equipment

Salary, wage

Tax, insurance

Gasoline/Petrol

Animal feed/Fodder
Animal drug and injection cos

TUGRUGS

WRITE "0" IF NOTHING

7.06
Expenditures on herding activities
in the last 12 months

A.1. ANIMAL HUSBANDRY/LIVESTOCK RAISING

Expenditures
Expenditure item

CHECK IF QUESTION (6.05) IS ANSWERED AS "3". INCLUDE HOUSEHOLDS WHICH ANSWERED 'NO ANIMAL HUSBANDRY/LIVESTOCK RAISING' IN THE SECTION 6, BUT HAVE THEIR OWN LIVESTOCKS.

1 Cattle

ROW NUMBER

Did your family have herding/anilmal farming in the last 12 months? /(Does your household have any livestock and pet? (INCLUDE POULTRY AND OTHER ANIMAL FARMING)/ROW NUMBER(7.01)SECTION 7: AGRICULTURAL PRODUCTION AND CONSUMPTION206

2 ► PART BNOManual Mongolia HSES 2012 Version 2.0
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Pieces

Pieces

PiecesLitersLitersLitersLitersLitersNumberKg

N/A

06 Goat

07 Cattle

08 Horse

09 Camel

10 Sheep-Ewe

11 Goat milk

12 Cow milk

13 Mare milk, airag

14 Camel milk

15 Eggs

16 Honey

17 Other* -Include the milk quantity used for diary products

XXXXXXXX

PiecesKg

04 Horse, Cattle's hair

PiecesKg

03 Goat cashmere

NUMBERQUANTITY

Total product(7.09)OTHER PRODUCTS

MILK, LITERS'

17

SKINS AND HIDES, PIECES

QUANTITY(7.10)
Consumed byhousehold

WOOL, HAIR, CASHMERE, KG.

►NEXT LIVESTOCKIF NOTHING, WRITE "0"(7.08)
Number of livestocks used for producing
products

05 Sheep

Kg

Kg

PRODUCT

1

YES

Did your household produce any wool, hair, cashmere, skins, hides, and milk products in the last 12 months?

02 Camel wool

(7.07)

01 Sheep wool

ROW NUMBERSECTION 7: AGRICULTURAL PRODUCTION AND CONSUMPTIONQUANTITY(7.11)
Total amountTUGRUGS
QUANTITYTUGRUGSPROCESSED AND SOLD
(7.13)(7.14)
Total amount
Total priceAs of the last 12 months

WRITE "0" IF NOTHING

SOLD(7.12)
Total price

Of which…

A.2. ANIMAL HUSBANDRY PRODUCTION

207

Manual Mongolia HSES 2012 Version 2.0(7.16)NAME OF THE CROP

99 TOTAL

13 Other (Barley, oat, rye, etc.)

12 Hay11 Wheat

10 Fruit

09 Cucumber

08 Tomato

07 Garlic

06 Onion

05 Beet04 Cabbage

03 Turnip

02 Carrot

NO►SECTION 8

2

NO

xxxxx

1

YES

►ASK ABOUT NEXT
CROP

(7.19)
Did you harvest ..[CROP].. during the past 12
months?

M2(7.18)(7.17)KILOGRAMSKILOGRAMS

by your household

18

xxxx

1
2

►SECTION 8KILOGRAMSTOTAL PRICETUGRUGS

QUANTITYKILOGRAMS(7.22)(7.23)
Quantity used for Soldanimal feed/fodder
INCLUDE THE PROCESSEDOf which:

The total size of the land where your household grew crops in the last 12 months

NO

YES

CHECK IF THE ANSWER TO QUESTION (6.05) WAS "4". BUT, IF THE
ANSWER WAS NOT "4" IN THE QUESTION (6.05), BUT GRAIN,VEGETABLE AND FRUIT WERE GROWN PRIVATELY, INCLUDE IT HERE.

M2

B. FARMING/CROP FARMING
Did your household grow any grain, vegetable, and fruit in the last 12 months?
Did you harvest any feed/fodder, and hay?

(7.20)
Total amount of..[CROP].. harvested in (7.21)
the last 12 months
Quantity consumed

FARMING PRODUCTION

What is the size of the land that you and your household member use for farming

1

2

YES

(7.15) Did you and any member of your household have any land for farning in the past 12 months?
INCLUDE LAND WHICH WAS NOT OWNED BY YOU AND YOUR HOUSEHOLD MEMBER, BUT
USED FOR FARMING.
INCLUDE LAND WHERE HAY AND FEED/FODDER WERE GROWN.

01 Potato

ROW NUMBERSECTION 7: AGRICULTURAL PRODUCTION AND CONSUMPTION

208

Seed

Equipment

Spare parts

Repair, service

05

06

07

Manual Mongolia HSES 2012 Version 2.0

Tax, insurance, fee

Transportation

Rent

10

11

12

EXPENDITURE ITEM

99 TOTAL

13 Other (Steam, water, electricity, heating, Post and communication, etc.)

Gasoline/Petrol

09

08 Raw material

Salary, wage

04

03 Extermination of vermin

02 Fertilizer

01

ROW NUMBER

EXPENDITURESTUGRUGS

WRITE "0" IF NOTHING(7.24)
Expenditure in the past
12 months?

19

209

► SECTION 9

How many members of your household work here?

(8.05)

Manual Mongolia HSES 2012 Version 2.0(8.09)(8.08)(8.07)

Goods for resale
Raw materials
Gasoline, fuelSteam, water, electricity, power, heating

02

03

04

TOTAL EXPENSE

99(a) What is the average amountof sale during a month with…..? 1(á) How many of the last 12
2months had…..?
3high sales

low sales

average sales

For how many months during the last 12 months did you run this production, trade and service?

Tax, fee, patent, license, insurance

Other expense (Transportation cost, Post, communication, internet, Loan interest)

10

11

Spare parts
Repair and maintenance

09

07

08

Equipment
Apartment/house rent

06

05

Salary to employees

01

How much was the expense in the last 12 months?

(8.06) How many people, besides your household members, did you let work here in the last month? IF NONE, WRITE "0".

How many percent of share of this production, trade, and service do your household members own?

WRITE THE CATEGORY CODE FOR THE ECONOMIC ACTIVITIESNAME THE PRODUCTION, TRADE, AND SERVICE?

2

NO(8.04)(8.03)1YES

CHECK IF THE ANSWER TO THE QUESTION (6.05) WAS "5".

(8.01) DID YOU RUN ANY NON-AGRICULTURAL PRODUCTION, TRADE, AND SERVICE IN THE LAST 12 MONTHS?

SECTION 8. NON-AGRICULTURAL PRODUCTION, TRADE, AND SERVICETUGRUGS(a) Tugrugs/month

Number of months

NumberNumber%

CODE:(á) Month

PRODUCTION, TRADE, ANDSERVICE ¹ 1

TUGRUGS(a) Tugrugs/month

Number of months

NumberNumber%

CODE:(á) Month

PRODUCTION, TRADE, ANDSERVICE ¹ 2

TUGRUGS(a) Tugrugs/month

Number of months

NumberNumber%

CODE:(á) Month

PRODUCTION, TRADE, ANDSERVICE ¹ 3(8.02) HOW MANY TYPES OF PRODUCTION, TRADE, AND SERVICE DID YOU RUN?

210

2

NO

► NEXT SOURCE

1

YES(9.01)
Did any of the household members receive income from ...[SOURCE]... during the last
12 months?

Share from the human development fund (monthly)

via transfer to an accountin cashManual Mongolia HSES 2012 Version 2.0

26 Other income (from intellectual property & other)

25 Gambling, contests, and lottery

24 Bond return

23 Loan interest

22 Stock dividend

21 Savings interest

INTERESTS AND RETURNS

20 Incomes from other sources

19 Withdrawals from bank savings

18 Loan repayments from others

17 Inheritances and wedding presents

16 Sale of assets

15 Rent of own assets (buildings, vehicles, equipment, land)

OTHER SOURCES

14 Other pensions and benefits (assistance to honored elders, etc.)

13 Student scholarships and allowances

12 Allowance to mothers who gave birth to and raised many children

Share from the human development fund
11 (for education, health insurance fee, purchase of accommodation,
health service fee, and for elders and the disabled)

1009

08 Funeral payments

07 Temporary incapacity benefits

06 Survivor's benefit for children

05 Disability pension

04 Maternity benefits

03 Unemployment benefit

02 Compensation

01 State pension

SOCIAL INSURANCE, SOCIAL WELFARE, PENSION, AND BENEFITSSOURCE NUMBERSECTION 9: OTHER INCOME

ID CODETUGRUGS21

ID CODETUGRUGS(9.03)PERSON # 2(9.02)PERSON # 1

ID CODETUGRUGSPERSON # 3(9.04)Who of the household members got income from ...[SOURCE]... and what was the total he/she received?

ID CODETUGRUGSPERSON # 4(9.05)ID CODETUGRUGSPERSON # 5(9.06)PART A. SOCIAL INSURANCE, SOCIAL WELFARE, PENSION, AND BENEFITS, AND INCOME FROM OTHER SOURCES

211

10

09

08

07

06

05

04

03

02

01

LINE NUMBER

45
6PARENTS, CHILDREN, RELATIVESOTHER INDIVIDUALS (FRIENDS, NEIGHBORS)FOREIGN & INTERNATIONAL ORGANIZATIONS, AND FOREIGHNINDIVIDUALSID CODE

3

NGOs

7

CELEBRATION

2COMPANIES AND ORGANIZATIONSOTHERHOUSING

1

GOVERNMENT/TREASURY FUND FOR EDUCATION

1COUNTRYSIDESOUM CENTERAIMAG CENTERCAPITAL CITY

678FUNERALOTHER

5 ABROAD

432

HOUSEHOLD BUSINESSMEDICAL TREATMENTPAYMENT FOR EDUCATION AND TUITION FEEDOMESTIC:

22

5

4

3

2

1
►(9.13)

NAME

CODE

From where were the gift, aid and donatio From which country were the gift and aid received?

HOUSHOLD CONSUPTION(9.11)On what did you spend the girt, aid, and donation?

(9.12)(9.14)TUGRUGNOYES

Annually

QuarterlyMonthly

WeeklyApproximately how many tugrugs did Are these gift, aid andyou receive during the past 12 months? donation received
regularly?
VALUE AND INCLUDE THE IN-KIND
ONES.

(9.13)PART B. GIFTS, AID, AND DONATION RECEIVED FROM OTHERS(9.10)WRITE DOWN EACH CASE OFRECEIVAL OF AID AND
DONATION SEPARATELY.

SECTION 10

Who and which organization gave the gift, aid and donation?

►(9.09)NO

PLEASE WRITE DOWN THE ID
CODE OF ANY HH MEMBER
WHO RECEIVED GIFTS, AID,AND DONATIONS.

1

2

YES

In the last 12 months, did any member of the household receive, in cash or in-kind, gifts, aid, and donations from individuals, relatives, friends, government or an aid organization?
INCLUDE SOCIAL WELFARE ALLOWANCES, BENEFITS AND SERVICE. INCLUDE GIFTS AND AID FOR EDUCATIONAL PURPOSES /TUTION FEE AND OTHER COSTS/.
DO NOT INCLUDE AID IN CASH OR IN-KIND THAT WILL BE REPAID.

(9.08)(9.07)SECTION 9: OTHER INCOME

5

4 Other

3 In-kind

2 via money transfer

1 Via a bank accountIn cashThrough which means are
the gift, aid and donation
received?

(9.15)

1

5

4

3

2

212

Manual Mongolia HSES 2012 Version 2.0

► SECTION 11

Manual Mongolia HSES 2012 Version 2.0

DO NOT KNOW

How many tugrugs did your houshehold repay for this loan in the last 1 month?

How many tugrugs did your houshehold repay for this loan in the last 12 months?

(10.11)

4

PURCHASE OF LANDOTHERSENDING HOUSEHOLD MEMBERS ABROAD

BUILDING AND BUYING AN ACCOMMODATION

2

3

PURCHASE OF A CARRUNNING A PRIVATE BUSINESSPURCHASE OF DURABLE GOODS

1

OTHER

4

3

SAVINGS AND CREDIT COOPERATIVESPAWN-SHOPINDIVIDUALEMPLOYER, OR ORGANIZATION

2NON BANK FINANCIAL INSTITUTION

2 ►(10.08)

3

1

YES
NO

TUGRUG

On what did you spend this/these loan(s)?
UP TO 3 CHOICES CAN BE SELECTED.
HOUSHOLD CONSUMPTION

1

BANK

From where did your houshold and members of your household receive this/these loans( `

1

2

YES

NO

Is it possible for your household to repay the loan in time?

(10.12)(10.10)(10.09)(10.08)

IF THE SAME TYPE OF LOAN IS MORE THAN ONE, COMBINE THEM.

If it was in the last 12 months, how many tugrugs of loan?

5

HERDERS' LOAN

(10.07)

4

Was/were this/these loan(s) received in the last 12 months?

AUTOMOBILE LOAN

3

HOUSING LOAN

HOUSEHOLD CONSUMPTION LOANOTHER

LEASING

2PENSION LOAN

BUSINESS LOAN

1

SALARY LOAN

Please indicate the loan type.
IF THE SAME TYPE OF LOAN IS MORE THAN ONE, COMBINE THEM.

DO NOT INCLUDE LOANS RECEIVED FOR EDUCATIONAL PURPOSES.

How many loans did your household or any member of your household repay during the last 12 months?

NO(10.06)(10.05)(10.04)

1

2

YES

Did your household or any member of your household receive or repay any loan during the last 12 months?

► (10.03)(10.03)NO

How much did you deposit in your savings during the last 12 months?

1

2

YES

Do you or does any member of your household have savings?

(10.02)(10.01)SECTION 12. SAVINGS AND LOAN

7

6

5

6

9

8

7

8

7

6

5

c.

b.

a.

23

LOAN №1

c.

b.

a.

LOAN №2

c.

b.

a.

LOAN №3

213

8►
9

NON-LIVING QUARTERS

OTHER

24

7

OTHER PUBLIC DWELLING

3

WOOD

(11.15)OTHER

2CEMENTOTHER

2ASPHALT ROOF SHINGLESManual Mongolia HSES 2012 Version 2.0►(11.15)(11.10) What is the total area your household occupies?

(11.09) Total useful area►

NON LIVING QUARTERS

OTHER

2

CEMENT(11.08) Living area

EARTH

1

WOOD

(11.07) Main material of the floor

TILE

1

METAL

(11.06) Main material of the roof

STONE

1

BRICKS(11.05) Main material of the walls

DO NOT INCLUDE KITCHEN, HALLWAYS AND BATHROOMS(SQUARE METERS)(SQUARE METERS)(SQUARE METERS)

4

3

4

3

5

6

PUBLIC DWELLING FOR EMPLOYEES45DORMITORY(11.04) Number of rooms in the dwelling

4

SEPARATE APARTMENT(11.10)

DOUBLE

NO

YES

2

1

(11.19) Did you borrow any money to acquire this dwelling?

4
BUILT BY OURSELVES

OTHER(11.20)3►

PRIVATIZED(11.20)2►
GIFT

PURCHASED(11.21)1►(11.20)RENTING3(11.20)NUMBER:INHERITED(11.18) How was this dwelling acquired?

PRIVATE

1►2►PRIVATE ORGANIZATIONGERSTATE-OWNED ORGANIZATION(11.17) Type of ownership of this dwelling(11.16) How long have you been living in this place?

IF DO NOT KNOW WRITE "99"(11.15) How old is this dwelling?

2
3

OTHER

1

2

1

2

1

EARTH

WOOD

(11.14) Main material of the floor

DOUBLESINGLE(11.13) Covering of the frame

SINGLE3(11.12) Covering of the ceiling

DETACHED HOUSE

2

2

NO

1►

(11.11)

1

APARTMENT

YES(11.11) Number of segments/walls in the ger

Ask about the dwelling where the household is living in now

GER(11.03) Type of this dwelling(11.02) Is this dwelling in which you are currenly living your main dwelling?

INCLUDE HOMES SET UP FOR CHILDREN TO ATTEND SCHOOL, AND SUMMER HOUSES.

(11.01) How many dwellings does your household own?

SECTION 11. HOUSING AND ENERGY

YEAR

YEAR

7

6

5

214

(11.22)

2
3

LOCAL SYSTEM/DIESEL STATIONSOLAR SYSTEM

Manual Mongolia HSES 2012 Version 2.0

1

2

3

4

CENTRALIZED: HOT & COLD WATER PIPE

CENTRALIZED: COLD WATER PIPE ONLYPROTECTED WELLUNPROTECTED WELL

(11.25) What is the source of water supply in your dwelling?

2

NO

TRANSPORTATION DISTRIBUTION

1

OTHER

SNOW, ICE

8

7

6

6
7

CANDLEYES

SPRING, RIVER

4
5

OTHER

SMALL GEN-SET(11.24) Does your dwelling have electricity source for functioning of home electronic appliances?

1

CENTRAL SYSTEM

55OTHERS

WIND SYSTEM

4

TRADITIONAL FIRE WOOD/COAL/ DUNG STOVE

23PRIVATE ELECTRICAL HEATERTUGROG:1(11.23) What is the main source of lighting for your dwelling ?

CENTRALIZEDPRIVATE LOW PRESSURE BOILER(11.22) What is the main source of heating system in this dwelling unit?

(11.21) th do you pay to rent the dwelling?

►

IF DON'T KNOW WRITE "99"(11.20) If you wanted to rent this dwelling to someone else, how much would be the monthly rent?

SECTION 13. HOUSING AND ENERGY

25

1
2

PUBLICNO

YES, BOTH LAND AND MOBILE PHONE

3 pharmacy

2 medical care center1 general education schoolNO► (11.33)

NO(11.36)INTERNET USAGE

NO

YES

2

1

At work
Internet Café

3

At home2

1(11.35) Where did you (your household member) use Internet during the last 3 months?

(11.34) How many members of the household use Internet?

1
2

YES

(11.33) Does any household member use Internet?

m2
m2

LAND OWNEDLAND USED(11.32) How much land do you (does s/he) own and/or use?

1
2

YES

(11.31) Does your household or a household member own and/or use land?

KM

3
4

Public Internet accesscentre5 Other

4

3

1

4

OUTSIDE THE DWELLINGNO TOILET

2(11.30) What is the distance, in km, to the nearest…..?

4 wellNO SPECIAL PLACEOTHER

YES, MOBILE PHONE

2

OPEN SEWAGE

IN A BOREHOLE?

YES, LAND LINE PHONE(11.29) Does your household have a telephone?

INSIDE THE DWELLING(11.28) What type of toilet do you have?
SEPARATE

THROUGH SERVICE ORGANIZATIONAT SPECIAL PLACE FOR WASTE

1

2

THROUGH DECENTRALIZED SYSTEM(11.27) How do you dispose waste?

1

THROUGH CENTRALIZED SYSTEM(11.26) How do you eject sewage?

3

NUMBER

4

4

3

215

2

NO

xxx

OTHER

Heating

Clean water

Hot water

Wastewater

Waste

Area usage payment

Other (elevator)

Other payment (plumbing maintenance/repair)

Drinking water, l (portable)

Rent: Ger

Rent: House/Apartment

Payment for renovation/repair of the dwelling

Other

02

03

04

05

06

07

08

09

10

11

12

13

1
2 ►NEXT SOURCE ITEM

01

YES
NO

(11.42)
Was any expense on …../ITEM, SERVICE/ incurred atyour household during the last 12 months?

ÑÓÓÖÍÛ ÒªËÁªÐlitre

GAS FUEL(11.39)(11.40)xx

TUGRUGSTUGRUGSTUGRUGS

(11.43)(11.44)
How many tugrugs did your household How many tugrugs did yourspend on ….. /ITEM/ in the last 1household spend on …..
month?
/ITEM/ in the last 12 months?

sack

ton

bag

ton

bag

cubic metre6ÍÝÐ ÒªÐËÈÉÍ ÄÓÃÀÀÐ

x

QUANTITY

5

x

DUNG

x

4

x

COAL

x

3

x

FIREWOOD

x

3
4

2

OTHER

2

BUY
PREPARE AND BUY(11.38)TUGRUGSTUGRUGS

What is the value/price of …..
/SOURCE ITEM/ that you received
for free from others in the last 12
months?

(11.41)(11.45)What is the value/price of …..
/ITEM/ that you received forfree from others in the last 12
months?

TUGRUGS

How much ….. /SOURCE How many tugrugs did your How many tugrugs did your
ITEM/ did you use in the household spend on …..
household spend on …..
last 12 months?
/SOURCE ITEM/ in the last /SOURCE ITEM/ in the last 12
1 month?
months?

ELECTRICITY► NEXT SOURCE ITEM

1

YES

1

PREPARE OURSELVES(11.37)

How do you prepare the fuel?

(11.36)

Did you use …../SOURCE/ inthe last 12 months?

1

SOURCE NUMBERSECTION 11. HOUSING, ENERGYFUEL AND ENERGY CONSUMPTION

216

Manual Mongolia HSES 2012 Version 2.0

DURABLE GOODS

Vacuum Cleaner

Washing machine

Sewing machineElectric or Gas Stove

Electric Heater

Electric Gen-set

Electric Iron

Oven

Boiler, Rice cooker

Water purifier

Iron Stove/Brick stove

Other

02

03

04

05

06

07

08

09

10

11

12

13

Manual Mongolia HSES 2012 Version 2.0

Other

24

Radio

Black & White TV

Color TV

Magnetophone/Tape player/Tape recorder

25

26

27

28

OTHER ELECTRONIC GOODS

Wooden Trunk

Carpet23

21

22

Wardrobe Closet

Wooden Table

20

Wall furniture

Iron Bed

17

Kitchen furniture set

Sofa

16

19

Bedroom furniture set

15

18

Traditional Style Bed, Wooden Bed

14

FURNITURE

Refrigerator

01

HOME APPLIANCES & ELECTRONIC GOODS

DURABLE GOOD'S NUMBER(12.02)

NUMBERIF YES PLEASE WRITE THE
NUMBERWRITE "0" IF NONE ►NEXT DURABLE GOOD

MONTHSTAKE AVERAGE IF
MORE THAN ONE OF
THIS GOODS WERE
USED

Does your household has How long have you
the following durable
used this good?
goods?

(12.01)SECTION 14: DURABLE GOODSTUGRUGS

TAKE AVERAGE IF
MORE THAN ONE OF
THIS GOODS ARE

Please value this goodin Tugrugs(12.03)

DURABLE GOOD'S NUMBER

NUMBERIF YES PLEASE WRITE THE
NUMBERWRITE "0" IF NONE ►NEXT DURABLE GOOD

44 Summer House

43 Garage

27* Please value the ger, house and dwelling in which you are residing.

42 House, Dwelling*

41 Ger*

DWELLING AND OTHER

40 Other

39 Tractor, Combine/Harvester

38 Bus37 Car36 Truck, Large truck

35 Motorcycle

34 Bicycle

MONTHSTAKE AVERAGE IF
MORE THAN ONE OF
THIS GOODS WEREUSED

HOUSEHOLD TRANSPORTATION & PRIVATE ENTERPRISE GOODS

33 Other

32 Computer

31 Camera

30 Video Camera

29 CD player, VCD player

DURABLE GOODS(12.02)

Does your household has How long have you
the following durable
used this good?
goods?

(12.01)(12.03)TUGRUGS

TAKE AVERAGE IF
MORE THAN ONE OF
THIS GOODS ARE

Please value this goodin Tugrugs

217

Winter coat, winter jacket

Other jackets, coats, raincoats, overcoats

Suit, costume

Wool and cashmere sweater

Other shirts (made of jeans, etc.)

Mongolian traditional deel

20104

20105

20106

20107

20108

20102

20103

Leather and suede jacket, deel

Sheepskin and furry jacket, deel

20101

Men's clothing

Socks

TightsOther men's clothing

20115

20116

20117

Socks

TightsOther women's clothing

20215

20216

20217

20218

20299

Undergarment (singlet, underwear, etc.)

Nightpant, nightshirt, nightdress, housecoat, dressing gowns

20214

Trousers

T-shirts

20213

20211

20212

Sportswear

Hat, scarf, neckcloth

20210

Mongolian raditional deel

Other shirts (made of jeans, etc.)

20207

Dress and skirts

Wool and cashmere sweater

20206

20209

Suit, costume

20205

20208

Winter coat, winter jacket

Other jackets, coats, raincoats, overcoats

20204

20202

20203

Leather and suede jacket, deel

Sheepskin and furry jacket, deel

20201

Women's clothing

20200

20199

Undergarment (singlet, underwear, etc.)

Nightpant, nightshirt, dressing gowns

20114

20112

20113

Trousers

T-shirts

20111

Sportswear

Hat, scarf

20110

Manual Mongolia HSES 2012 Version 2.0

20109

ITEMS

YES
1

Sub total 20201 - 20218

Sub total 20101 - 20117(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS28

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

20100

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

218

Winter coat, winter jacket

Other jackets, coats, raincoats, overcoats

Suit, costume

Wool and cashmere sweater

Other shirts (made of jeans, etc.)

20304

20305

20306

20307

20302

20303

Leather and suede jacket, deel

Sheepskin and furry jacket, deel

20301

Children's clothnig (aged 3-13)

All sorts of clothing for children aged 0-2

Wrapping and other articles for infants aged 0-2

20319

20320

Hat, scarf, variuos gloves /work/

Belt, suspenders, tie

Handkerchief

Thread, yarn

Other (button, press-stud, zip)

20401

20402

20403

20404

20405

Dry cleaning

Laundering

Dyeing of garments

Mending, repair

Cost for renting clothing

20501

20502

20503

20504

20505

20599

Repair, cleaning and lease of clothing

20500

20499

Other articles of clothing

20400

20399

TightsOther children's clothing

20316

20318

Socks

20315

20317

Undergarment (singlet, underwear, etc.)

Nightpant, nightshirt, nightdress, housecoat, dressing gowns

20314

Trousers

T-shirts

20313

20311

20312

Sportswear

Hat, scarf, neckcloth

20310

Mongolian raditional deel

Dress and skirts

20309

Manual Mongolia HSES 2012 Version 2.0

20308

ITEMS

YES
1

Sub total 20501 - 20505

Sub total 20401 - 20405

Sub total 20301 - 20320(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS

29

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

20300

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

219

Sport shoes

Mongolian traditional boots and buriad boots

Sandals, flip-flops

20605

20607

Women's shoes

20604

20606

Spring or autumn shoes

Summer shoes, boots

20603

Winter boots

20601

20602

Footwear, pairs

Footwear for children aged 0-2

20610

Cost for lease of shoes

20702

20703

Synthetic

CottonCarded wool

Other......

20807

20808

20809

20810

20899

Satin, m

All kinds of silk

20806

Cotton cloth

20804

20805

Drill ("Daalimba")

Tsagaan yambuu

20803

Woolen cloth

20801

20802

Cloth

20800

20799

Repair of footwear

Shoe polishing and cleaning

20701

Shoes repair and lease

20700

20699

Felt boots

Other footwear

20609

Manual Mongolia HSES 2012 Version 2.0

20608

ITEMS

YES
1

Sub total 20801 - 20810

Sub total 20701 - 20703

Sub total 20601 - 20610(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS30

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

20600

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

220

Metal beds

Closets and wardrobes

Kitchen furniture-set

20903

20904

20905

Furnished and wooden beds

Sofas, divans

20902

Furniture, appliancesHome furniture, appliances, carpets and oilcloth

Other furnitures and accessories/appliances

Cost for repair and services

20915

20916

Oilcloth for the floor

Other floor covering

Cost for repair and services

20922

Mat

20919

20921

Scatter/Area rug

20918

20920

Carpets

20917

Carpets and floor covering

MirrorCrib, playpen

20914

Bath room accessories/appliances

20912

20913

Painting and scultures

20909

MattressLamp, electric lamp

20908

20911

Chest

20907

20910

Bedroom furniture-set

Tables and chairs

20906

Manual Mongolia HSES 2012 Version 2.0

Cost for repair and services

21007

21008

21099

Tablecloth

Other sewn and knitted items, and cotton goods

21006

Towel

Bath towel

21003

21005

Bed covering

21002

21004

Curtains

Bedsheets

21001

Domestic cotton goods, sewn and knitted items

21000

20999

ITEMS

YES
1

Sub total 21001 - 21008

Sub total 20901 - 20922(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS

31

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

20901

20900

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

221

Sewing mashine

Electric and gas stove

Electric heating

21106

Washing mashine

21103

21105

Vacuum cleaner

21102

21104

Refrigerators

Domestic durable electric appliances

Domestic electric appliances

Cost for repair and services

21113

Cost for repair and services

21119

Metal and cast iron utensils

Other utensils

Cost for repair and services

21206

21207

21208

21299

Knife, spoon and fork

Plastic utensils

21203

21205

Vacuum flask

21202

21204

GlassesCeramic ware/china-ware

21201

Domestic glassware, utensils

21200

21199

Water boiler and electric tea pot

Other (Coffee mixer etc.)

Bread roaster

21116

21118

Rice cooker

21115

21117

Coffee pot

21114

Domestic minor electric appliances

Safe

Other (air conditioner etc)

21112

21110

21111

Electric ironElectric ring/Electric hob

21109

Generators

Electric fan

21108

Manual Mongolia HSES 2012 Version 2.0

21107

ITEMS

YES
1

Sub total 21201 - 21208

Sub total 21101 - 21119(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS32

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

21101

21100

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

222

Other (jack plane, drill, nipper, etc.)

Door accessories (hinge, etc.)

Small electric accessories (power outlet/socket, electric switch, cable/wire, etc.)

Flashlight/Torch

Lantern

Battery

21305

21306

21307

21308

21309

ITEMS

21304

Spade

Rake

21303

Saws

21301

21302

Domestic tools

Other

Cost of repair and service

21312

21313

Laundry soap

Washing powder/detergent

Match

Candle

21401

21402

21403

21404

Glue, scotch tape

Other tools

21414

21415

Cleaning, laundry and painting of domestic cotton goods, sewn and knitted items, and carpets

Cost for lease of domestic goods

21418

21419

Sub total 21401 - 21419

Cost for disinfection and sterilization

21417

21499

Cost for hiring a housekeeper

21416

House services:

Needle for sewing and weaving/knitting

Nail, screwdriver, bolt, nut

21413

21411

21412

Brush, polisher/rubstone

Clothes-hanger

21410

Broom/besom

Dustpan

Other cleaning products

21407

21409

Disinfectants

21406

21408

Shoe polish21405

Non-durable domestic goods

Domestic cleaning products and other inexpensive goods, home services

21400

21399

Bell

Signal accessories

21311

Manual Mongolia HSES 2012 Version 2.0

21310

YES
1

Sub total 21301 - 21313(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS33

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

21300

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

223

Other equipments/devices (hearing aids, artificial organs, etc.)

21505

21509

Transport:

Cost for transportation rent

21616

21699

Lease of garage

Other (Charge for using roads, driving license, etc.)

21613

21615

Technical inspection and diagnostics

21612

21614

Other fuel

Cost of repair and service (paid to an individual)

21611

Spare parts of auto mobile

Gasoline, diesel

21610

Wheels/Tires

21608

21609

Carting

21605

Repair and services of auto vehicles

Bicycle

21604

21607

Motorcycle

21603

21606

Bus

Trucks

21602

Car

21601

21600

Activities of private transportation

Inpatient care

21508

21599

Dental care

Other medical services (injection, medical test, X-ray etc)

21507

Outpatient's clinic examination

Manual Mongolia HSES 2012 Version 2.0

21506

Medical services:

Other (condoms, IUD, bandage, thermometer, syringe, etc.)

Eye glasses, contact lenses

21504

Injection

21502

21503

Tablets, vitamins

Medicines and other products:

Medicine, medical equipments/devices and services

ITEMS

YES
1

Sub total 21601 - 21616

Sub total 21501 - 21509(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS34

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

21501

21500

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

224

Railway freightTaxi cost: Inside the city

Road transportation service: inter-urban (microbus, taxi, etc.)

Road transport: Inside the city

21706

21707

21703

21705

Railway passenger service: International

21702

ITEMS

21704

Cost for bus and trolleybus

Railway passenger service: Domestic

21701

Transportation services:

Freight of water transport

Other transports

21712

21713

21714

Repair cost of telephone and fax mashine

21804

Calling card

Charge for internet service

21811

21812

21813

21899

Lease cost of telephone and fax

Installing charge of equipments

21810

Mobile/cell phone charge

Service charge of telegraph, telex and facimile

21809

21807

21808

Calling: International

Telephone charge (immovable)

21806

Calling: Inter-urban

21805

Telephone and Facimile

Telephone, fax mashine, mobile phone

21803

Telephone, fax mashine

Stamps, envelope (new)21802

Post services

Letters, parcel, post card

21801

21800

Communication

Cost for traveling by water transport

21711

21799

Air: International

Luggage cost of air

21710

Road freight : Inter-urban

Air: Domestic

21709

Manual Mongolia HSES 2012 Version 2.0

21708

YES
1

Sub total 21801 - 21813

Sub total 21701 - 21714(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS35

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

21700

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION225

ITEMS

Tape-recorderVideo player

21905

21906

Color TV

TV aerial

21904

Black-white TV

21902

21903

Radio

Sound, picture, photograph, data processing equipment, piece:

Equipment and durable goods for leisure

Films

Spare parts and repair cost of above equipments

21913

21914

Musical instruments (guitar, etc.)

Billiard board

Repair cost of above tools

21916

21917

21918

Services related to the pets (care, treatment, etc.)

22018

22099

Food for pets

Shelter, tie and bowl of pets

Pets

22015

22017

Christmas tree

22014

22016

Tent

Live and artificial flowers

22011

22013

Shotgun

22010

22012

Cassette and CD with games

Sport tools (skiing, etc.)

22009

Other toys and decoration

Collection (stamp-collection, etc.)

22008

Electric toys

22006

22007

Dolls

Toy car

22003

22005

Puzzle

22002

22004

Playing card

Chess

22001

Other goods for leisure, domestic animals (pets)

22000

21999

Travel tools (boat, hang-glider, etc.)

21915

Durable goods for leisureCalculator

Audio and video cassette, CD

Computer

21910

21912

Camera

21909

21911

Video camera

Binoculars

21908

Manual Mongolia HSES 2012 Version 2.0

21907

YES
1

Sub total 22001 - 22018

Sub total 21901 - 21918(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS36

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

21901

21900

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

226

Charge for radio and TV set (cabel TV)

Develop and print out photo films

Lottery

22106

22107

22108

Service charge at game centers/gaming houses/play centers

Performance fee (movie, drama/play, concert, museum)

22103

Renting for sport tools

Fee for sports course and class

22102

22105

Driving lessons

22101

22104

Leisure and cultural services

ITEMS

Manual Mongolia HSES 2012 Version 2.0

Other stationery (ink, eraser, folder, etc.)

22208

Tuition fee: secondary

Tuition fee: tertiary

Tuition fee: courses and classes

22403

22404

22405

22406

Accommodation services of boarding schools, universities

22505

22599

Accommodation services of hotels

Accommodation services of holiday villages

22504

22502

22503

At public eating places (restaurants, cafes, cafeterias)

At canteens in schools, works canteens

22501

Hotels, dormitories and restaurants

22500

22499

Tuition fee: primary

Tuition fee: literacy programmes for adults

22402

Education

Tuition fee: pre-primary

22401

Total cost for recreation and travel

22301

22400

Recreation and travel

22300

22299

Paper

Other printed matters (post card, calendar, etc)

22207

Books and dictionary

22205

22206

Pen, ballpoint pen

PencilNotebook

22202

22204

Newspapers and journals

22201

22203

Newspapers, books and stationery

22200

22199

YES
1

Sub total 22501 - 22505

Sub total 22401 - 22406

Sub total 22201 - 22208

Sub total 22101 - 22108(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

хххххххх

ххххххххTUGRUGSTUGRUGS37

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

22100

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

227

Toilet paper

Sanitary napkins

22604

22605

Hair dryier

Other electric appliances (beaty device/equipment/apparatus/machine, hair clipper, etc.)

Repair of such appliances

22609

22610

22611

22615

22616

Repair for valuables

Watch repair

22703

22704

Appliances for funeral (coffin, stone,etc.)

Repair of above appliances

22711

22712

22799

Tube, lighter, ash-tray

Sun glasses, umbrella

22708

22710

Baby's cart, chair

22707

22709

Bag

Wallet22706

Suitcase

22705

Other appliances:

Watches22702

Personal valuables:

Valuables

22701

22700

Personal valuables and appliances

PerfumeOther beauty products (llipstick, nail tools, lotion, shampoo, etc.)

22614

22699

Other sanitary products (comb, hair-roller, nailclipper, scale, etc.)

Beauty powder

22613

Non-electrical razors

22612

Other appliances for beauty:

Electric razors

22608

Electric appliances for beauty:

Beauty service (massage, sauna, public shower, manicure, pedicure)

22607

ITEMS

Hairdressing

Manual Mongolia HSES 2012 Version 2.0

22606

Hair cutting and beauty:

Toothpaste

Beauty soap

22603

Toothbrush

22601

22602

Personal care

YES
1

Sub total 22701 - 22712

Sub total 22601 - 22616(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS38

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

22600

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

228

Insurance

Health insuranceLife insurance

Dwelling insurance

Transport insurance

Other insurance

22901

22902

22903

22904

22905

Service fees for caring elders and disabled people

22801

22900

Social welfare

ITEMS

Manual Mongolia HSES 2012 Version 2.0

Fee for financial consultation

Service fees for banks and other financial institutions

23001

23002

Fees for legal services, employment agencies

Charges for leasing

Other services (advertisement, private detective, copying documents, etc.)

23102

23103

23104

23105

Other material

23205

23206

23299

Cement,

Glass

23204

Oil paint

Bricks23203

Wall paper, package

23201

23202

Materials for building repair

23200

23199

Fees for administrative documents for marriage, birth, death, etc.

Cost incurred in relation to purchase and sale of property

23101

Other services

23100

23099

Financial service

23000

22999

YES
1

Sub total 23201 - 23206

Sub total 23101 - 23105

Sub total 23001 - 23002

Sub total 22801 - 22905(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS39

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

22800

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

229

Yard

Stove

Other

24106

24107

24108

Tent frame

Tent covering

24103

24105

Ger (complete)

34102

24104

Apartment

House

24101

Cost related to housing and housing durable goods

ITEMS

Manual Mongolia HSES 2012 Version 2.0

Income tax

Cattle tax

Land tax

Other taxes

24201

24202

24203

24204

For institution

Other

24308

24309

24399

For church and temple

24307

Cost for celebration of tsagaan sar /white moon, lunar new year/

24304

Cost for celebration of birthday

Cost for celebration of new year

24303

Cost for other celebrations

Cost for wedding

24302

24306

Gifts, assistance, donation, and transfer to individuals

24301

24305

Cost for gifts, assistance and celebration

24400

24299

Tax collection

24200

s4199

YES
1

Sub total 24301 - 24309

Sub total 24201 - 24204

Sub total 24101 - 24108(13.01)
Did you or any member of your household buy following items for her/his own use during the past 12
months? Received from others without paying cash?

(13.02)

PURCHASED(13.03)

PURCHASED(13.04)(13.05)

RECEIVED FREE FROM OTHERSIF THE ITEM WAS PURCHASED FOR OTHERS OTHER THAN A MEMBER OF YOUR HOUSEHOLD, WRITE IN 24301.

TUGRUGSTUGRUGS40

TUGRUGSTUGRUGS

What is the value of all ..[ITEM]..
How much did all members of
How much did all members ofNOthat all members of your household What is the value of all ..[ITEM].. thatyour household spend on
your household spend on
2purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free from others during
all members of your household
the past 12 months?
past 12 months?
past 1 month?
received free from government andnon-government organizations
during the past 12 months?

ASK (13.01) FOR ALL ITEMS AND INDICATE IF ANY PURCHASE WAS MADE DURING THE PAST 12 MONTHS. IF
THE ANSWER IS "YES-1" , ASK QUESTIONS (13.02-13.05) ONLY FOR THE ITEMS THAT WERE PURCHASED.

34100

ITEM CODESECTION 13: NON-FOOD EXPENDITURE AND CONSUMPTION

230

AGE

SEX

CHECK PAGE

NAME

ID CODE
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15

41

231

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Database documentation for the HSES Mongolia 2012

HOUSEHOLD SOCIO ECONOMIC SURVEY

MONGOLIA 2012DATABASE DOCUMENTATION

Manual Mongolia HSES 2012 Version 2.0

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Database documentation for the HSES Mongolia 2012

Introduction

The database generated for the Mongolia Household Socio Economic Survey - 2012 is composed by the following 18 files:

STATA FORMAT

01_hhold.dta
02_indiv.dta
03_livestock.dta
04_livestock_exp.dta
05_by_product.dta
06_crop.dta
07_agric_exp.dta
08_enterprise.dta
09_other_income.dta
10_remittance.dta
11_savings_loan.dta
12_energy.dta
13_payment_serv.dta
14_durable.dta
15_non_food.dta
16_urb_diary.dta
17_rur_food_7d.dta
19_foodout.dta

This document contains the description of all those 18 files, including all the variables and its categories when applicable.

Manual Mongolia HSES 2012 Version 2.0

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Database documentation for the HSES Mongolia 201201_hhold

VariableNb.
Name
1 identif

household_id

2
3
4
5
6
7

8 Nb of hh members
HH_NO
Visit 1 DD
Visit 1 MM
Visit 1 YY
Visit 1 Result

q0008
hh_no
v1_dd
v1_mm
v1_yy
v1_res

Label

Code

8 v2_dd
9 v2_mm
10 v2_yy
11 v2_res

Visit 2 DD
Visit 2 MM
Visit 2 YY
Visit 2 Result

12 v3_dd
13 v3_mm
14 v3_yy
15 v3_res

Visit 3 DD
Visit 3 MM
Visit 3 YY
Visit 3 Result

16 v4_dd
17 v4_mm
18 v4_yy
19 v4_res

Visit 4 DD
Visit 4 MM
Visit 4 YY
Visit 4 Result

20 q0701

0701 Raised or Owned Herding,poultry or any animal?

21 q0707

0707 Has produced animal products past 12m?

22 q0715

0715 Agricultural land in past 12 m?

23 q0716
24 q0717

0716 What is total amount owned the past 12M
0717 Has vegetables, fruits in pas 12M

25 q0718
26 q0801

0518 What is total amount agricultural land HH members past
0601. Are there household enterprises?

27 q08020602. How many enterprises?

Categories
Label

1
2
3
4
5
6
7

COMPLETE
PARTIALLY COMPLETEDNO RESPONDENT IN THE HOUSEHOLDHOUSEHOLD TEMPERARILY NOT PRESENTPOSTPONEDREFUSED
HOUSEHOLD NOT FOUND

1
2
3
4
5
6
7

COMPLETE
PARTIALLY COMPLETEDNO RESPONDENT IN THE HOUSEHOLDHOUSEHOLD TEMPERARILY NOT PRESENTPOSTPONEDREFUSED
HOUSEHOLD NOT FOUND

1
2
3
4
5
6
7

COMPLETE
PARTIALLY COMPLETEDNO RESPONDENT IN THE HOUSEHOLDHOUSEHOLD TEMPERARILY NOT PRESENTPOSTPONEDREFUSED
HOUSEHOLD NOT FOUND

1
2
3
4
5
6
7

COMPLETE
PARTIALLY COMPLETEDNO RESPONDENT IN THE HOUSEHOLDHOUSEHOLD TEMPERARILY NOT PRESENTPOSTPONEDREFUSED
HOUSEHOLD NOT FOUND

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

Manual Mongolia HSES 2012 Version 2.0

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Database documentation for the HSES Mongolia 201201_hholdNb.
Name
28 q0907

VariableLabel
07-07 :Has any member received money or goods

29 q1001

30 q1002
31 q1003

Code

Categories
Label

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2
3
4
5
6
7
8
9

GER
DETACHED HOUSE
BUILDING(unauthorised but with access to some public service)
APPARTMENTSTUDENT'S DORMITORY
WORKER'S DORMITORYOTHER DORMITORY ACCOMODATIONNON-LIVING QUARTERS
OTHER

1
2
3
4
5

BRICKSCEMENT
WOOD
STONE
OTHER

1
2
3
4

METAL
ASPHALT ROOF SHINGLES
TILE
OTHER

1
2
3
4

WOOD
CEMENT
EARTH
OTHER

1
2

SINGLEDOUBLE

1
2

SINGLEDOUBLE

1
2
3

WOOD
EARTH
OTHER

99

***Undefined Label

1
2

STATE
ORGANIZATION'S

32 q1004
29 visitor
30 ndays
31 q1101
32 q1102

Number of visitors Cover Form 2
Number of days Cover Form 2
1101. Number of dwellings
1102. Is main dwelling?

33 q1103

1103. Type of Dwellings

34 q1104
35 q1105

1104. Number of rooms in the dwelling
1105. Main material of the walls

36 q11061106. Main material of the roof

37 q11071107. Main material of the floor

38 q1108
39 q1109
40 q1110
41 q1111
42 q11121108. Living area
1109. Total useful area
1110. What is the total area occupies
1111. Number of walls in the ger
1112. Covering of the ceiling

43 q11131113. Covering of the frame

44 q1114

1114. Main material of the floor

45 q11151115. How old is this dwelling

46 q1116
47 q11171116. How long have you been living
1117. Type of ownership

Manual Mongolia HSES 2012 Version 2.0

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Database documentation for the HSES Mongolia 201201_hholdNb.

Variable

Name

Label

Code
3 PRIVATE

48 q1118

1118. How was acquired

49 q11191119. Did you borrow any money to acquire

50 q11201120. If you wanted to rent, how much

51 q1121
52 q11221121. How much do you pay for rent
1122. What is the main source of heating

53 q11231123. Source of electricity

54 q1124

1124. Electricity resource adequate for operating electricd

55 q11251125. Water supply

56 q1126

57 q1127

Categories
Label

1
2
3
4
5
6
7

RENTINGINHERITEDGIFT
BUILT BY OURSELVESPURCHASEDPRIVATIZED
OTHER

1
2

YES
NO

99

***Undefined Label

1
2
3
4
5

CENTRALIZEDTRADITIONAL FIRE WOOD/COAL/ DUNG STOVEPRIVATE ELECTRICAL HEATERPRIVATE LOW PRESSURE BOILEROTHERS

1
2
3
4
5
6
7

CENTRAL SYSTEMLOCAL SYSTEM/DIESEL STATIONSOLAR SUSTEM
WIND SYSTEM
SMALL GEN-SETCANDEL
OTHER

1
2

YES
NO

1
2
3
4
5
6
7
8

CENTRALIZED: HOT & COLD WATER PIPE
CENTRALIZED: COLD WATER PIPE ONLYPROTECTED WELLUNPROTECTED WELL
TRANSPORTATION DISTRIBUTIONSPRING, RIVER
SNOW, ICE
OTHER

1
2
3
4

1127. Household waste disposal

58 q11281128. What type of toilet do you have59 q11291129. Has a telephone

60 q1130_1
62 q1130_2
63 q1130_3
64 q1130_4
65 q1131

1130. 3-Distance to the nearest medical care
1130. 4-Distance to the nearest pharmacy
1130. 5-Distance to the nearest well1131. Anybody from your household own or exploit land ?

1
2
3
4

NO SPECIAL PLACEOTHERS

12
3
4

SEPARATE
PUBLICOUTSIDE THE DWELLINGNO TOILET

1
2
3
4

YES, LAND LINE PHONE
YES, MOBILE PHONE
YES, BOTH LAND AND MOBILE PHONE
NO

1

YES

Manual Mongolia HSES 2012 Version 2.0

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Database documentation for the HSES Mongolia 201201_hhold

Nb.

Name

VariableLabel

66 q1132_a67 q1132_b68 q1133

1132. How many hectares does your household OWN?
1132. How many hectares does your household OPERATE?
1133. Use internet normally?

69 q1134
70 q1135_1

1134. How many household member
1135_1. Where used internet, at home

71 q1135_2

1135_2. Where used internet, at work

72 q1135_3

1135_3. Where used internet, internet café

73 q1135_4

1135_4. Where used interne, free public accesst

74 q1135_5

1135_5. Where used internet, other

Code
2 NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

Manual Mongolia HSES 2012 Version 2.0

Categories
Label

238

Database documentation for the HSES Mongolia 2012
02_indiv
VariableNb.
Name
1 identif
2 ind_id
3 q0102

household_id
Ind ID
102. Relationship to head

4 q0103103. Sex

56
7
8104. Year of birth105. Age Yrs
105. Age Mths
106. Marital Status

q0104
q0105yq0105m
q0106

Label

9 q0107107. Spouse ID CODE

10 q0108108. Father ID CODE

11 q0109109. Mother ID CODE

12 q0110a
13 q0110
14 q0111

110 A. Days away past month110. Months away
111. Is HH member?

15 q0207

207. Is 6 years or more?

16 q0208

208. Is answering personally?

17 q0209
18 q0210209. Respondent ID CODE
210. Highest certificate obtained

Code

Categories
Label

1
2
3
4
5
6
7
8
9
10
11

HEAD
WIFE / HUSBAND
SON / DAUGHTER
FATHER / MOTHER
BROTHER / SISTERFATHER / MOTHER IN LAWSON / DAUGHTER IN LAWGRAND PARENT
GRANDCHILDOTHER RELATIVE
OTHER

1
2

MALE
FEMALE

1
2
3
4
5
6

MARRIED
LIVING TOGETHERSEPARATEDDIVORCEDWIDOWED
NEVER MARRIED98***Undefined Label

98
99***Undefined Label***Undefined Label

98
99***Undefined Label***Undefined Label

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

NONE
PRIMARY

Manual Mongolia HSES 2012 Version 2.0

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Database documentation for the HSES Mongolia 2012
02_indiv
Nb.

Variable

Name

Label

19 q0211211. Can read a letter?

20 q0212

206. Are you attending School?

q0213
21 q0214214. Check age/ between 8-35 years

22 q0215

215. Reason never attended school

23 q0216t

216. Current education TYPE

24 q0216g
25 q0217

216. Current education GRADE
217. Type of School

26 q0218

211. School Location

27 q0219

212. Place where person lives during school

Categories
Code
Label
3 SECONDARY
4 COMPLETE SECONDARY
5 VOCATIONAL
6 DEGREE OR HIGHER EDUCATION DIPLOMA
7 BACHELOR
8 MASTER
9 PHD, DOCTOR DEGREE
10 OTHER
1
2
3

YES, EASILY
YES, WITH DIFFICULTY
NO

1
2
3
4

YES
NO, DROPPEDOUT
NO, NEVER ATTENDED
NO, COMPLETED

1
2

YES
NO

1
2
3
4
5
6
7
8
9
10
11
12
13

CHILD NOT INTRESTEDPARENTS NOT INTERESTEDDIFFICULT TRAINING
POOR TRAINING QUALITY
POOR SCHOOL CONDITIONSLACK OF BUDGETREQUIRED TO WORKSICK/DISABLED
HAD TO LOOK AFTER OTHERSSCHOOL TOO FARMIGRATIONSHORTAGE OF DORMITORYOTHERS

1
2
3
4

GENERAL
VOCATIONALCOLLEGE, UNIVERSITYOTHER (ECLE-SIASTICAL, NON FORMAL)

1
2
3

PUBLICPRIVATE
OTHER

1
2
3
4

CAPITAL CITY
AIMAG CENTER
SOUM CENTERABROAD

1
2
3
4
5

HOME
GER APPART FROM HH
DORMITORYRELATIVES
OTHER

q0220
q0221
28 q0222

222. Pay tuition?

Manual Mongolia HSES 2012 Version 2.0

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Database documentation for the HSES Mongolia 2012
02_indiv
Nb.

Name

VariableLabel

29 q0226_1

226_1. Expenditures during past 12 months in room rent

30 q0226_2

226_2. Expenditures during past 12 months in tuition paid by

32 q0226_3

226_3. Expenditures during past 12 months in books and suppl

33 q0226_4

226_4. Expenditures during past 12 months in uniforms

34 q0226_5

226_5. Expenditures during past 12 months in transport

35 q0226_6

226_6. Expenditures during past 12 months in others

36 q0226_7

226_7. Expenditures during past 12 months in TOTAL

37 q0301

301. Answering personally?

38 q0302
39 q0303

302. Respondent ID CODE
303. Any health problem during past month?

40 q0304a

304_A. Health problem (1)41 q0304b

304_B. Health problem (2)42 q0305

305. Did you seek treatment in past 1 M?

43 q0306

306. Why didn't seek treatment?

44 q0307307. Where was treatment provided?

Code
1 YES
2 NO

Categories
Label

1
2

YES
NO

1
2

YES
NO

1
2
3
4
5
6

RESPIRATORY SYSTEMDIGESTIVE SYSTEMURINARY AND SEXUAL ORGANBLOOD CIRCULATION SYSTEMDAMAGE OR INTOXICATION BY EXTERNAL IMPA
OTHER

0
1
2
3
4
5
6

NO MORERESPIRATORY SYSTEMDIGESTIVE SYSTEMURINARY AND SEXUAL ORGANBLOOD CIRCULATION SYSTEMDAMAGE OR INTOXICATION BY EXTERNAL IMPA
OTHER

1
2

YES
NO

1
2
3
4
5
6
7
8
9
10
11
12

NOT SERIOUS ENOUGHHEALTH FACILITY TOO FARNO TRANSPORTATIONHEALTH CARE TOO EXPENSIVE
TRANSPORT TOO EXPENSIVEHEALTH WORKERS NOT FRIENDLYHEALTH WORKERS NOT PRESENTHEALTH CARE NOT GOOD QUALITYNO MONEY
TREATED MYSELF
DIDN'T KNOW FROM WHERE TO GET TREATMENT
TRADITIONAL HEALER

Manual Mongolia HSES 2012 Version 2.0

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Database documentation for the HSES Mongolia 2012
02_indiv
Nb.

Name

VariableLabel

45 q0308

308. Who provided medical service for your treatment?

46 q309_1

309_1. Amount paid in facility or healt practitioner

47 q309_2

309_2. Amount paid in transportation or others

48 q0310

310. Have bought medicines in the past M ?

49 q0311
50 q0312

311. Amount spent in medicines
312. Have stayed at hospital in past 12 M?

51 q0313

313. What was the Hospital ?

52 q0314

314. How much did you pay for all costs

53 q0315

315. Amount spent in transportation

54 q0401

4.01 Respondent 10 yrs or more?

55 q0402

4.02 Answering by himself?

56 q0403
57 q0404

4.03 ID CODE of respondent
4.04 Did you any job for the past 7 days?

58 q0405

4.05 What kind of work was the main job you did?

59 q0406

4.06 Any permanent job despite you did no job in last 7 day

60 q0407

4.07 Main reasong for not doing job in last 7 days

Code

Categories
Label

1
2
3
4
5
6

CENTRAL HOSPITAL/CLINIC
AIMAG/DISTRICT CLINIC
SOUM CENTER FAMILY CLINICPRIVATEABROAD
OTHER

1
2
3
4
5
6

SPECIALISED DOCTORFAMILY DOCTORMEDSISTER
CHIROPRACTORTRADITIONAL HEALER
OTHER

1
2

YES
NO

1
2

YES
NO

1
2
3
4
5
6

CENTRAL HOSPITAL/CLINIC
AIMAG/DISTRICT CLINIC
SOUM CENTER FAMILY CLINICPRIVATEABROAD
OTHER

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2
3
4
5

WAGE JOBUNPAID WORKSELF EMPLOYED HERDING
SELF EMPLOYED AGRICULTURE
OTHER

1
2

YES
NO

1
2
3
4
5
6
7

SICK
PREGNANTCARING FOR OTHERSHOLIDAYTEMPORARY HALTSEASONAL WORKOTHERManual Mongolia HSES 2012 Version 2.0

242

Database documentation for the HSES Mongolia 2012
02_indiv
VariableNb.
Name
61 q0408

Label
4.08 Did you look for a job in last 7 days

62 q0409

4.09 Reasons for not looking for a job

63 q0410

4.10 Registered in labour and social welfare dep?

64 q0411c
65 q0412c
66 q0413
67 q0414

4.11 What is your main job? CODE
4.12 Economic branch? CODE
4.13 Nb of hours for a week on average
4.14 Type of your organisation

68 q0415

4.15 Do your receive any salary in cash and/or in kind

69 q0416a
70 q0416b
71 q0416c

4.16 Salary amount - past month
4.16 Salary amount - past 12 months
4.16 Bonuses and special allowances

Code

Categories
Label

1
2

YES
NO

1
2
3
4
5
6
7
8

STUDENTTOO OLDHOMEWORK, CARING FOR A BABYEXPECTING A JOBEMPLOYED IN SEASONAL JOBS
SICK/CARES OF SICK PERSONDISABLED
OTHER

1
2

YES
NO

1
2
3
4
5
6
7
8
9

Partnership
Cooperative
Corporation
LLC
State owned company
Local authority owned company
Government organisation
NGO
Other

1
2

YES
NO

Manual Mongolia HSES 2012 Version 2.0

243

Database documentation for the HSES Mongolia 201203_livestock

Variable
Nb.
Name
Label
1 household_id
2 ani_id
Animal Number

3
4
5
6
7
8

q0702_1
q0702_2
q0702_3
q0703
q0704
q0705

702-1. TOTAL
702-2. Number of female702-3. Number of young
703. Use for own food704. Number of sold705. Amount received

Categories
Label

Code
1
2
3
4
5
6

Manual Mongolia HSES 2012 Version 2.0

CattleHorsesCamels
Sheep
Goats
Other

244

Database documentation for the HSES Mongolia 201204_livestock_exp
Nb.
Name
1 household_id
2 exp_id
Exp number

3 q0706

VariableLabel

07 06: Expenditures on this [herding activity] in the last 1

Manual Mongolia HSES 2012 Version 2.0

Code
1
2
3
4
5
6
7

Categories
Label

Animal Feed
Drugs and veterinary costs
Gassoline /OilTaxes and Insurance
Wage, pay
Fence, machine
Other

245

Database documentation for the HSES Mongolia 2012
05_by_productNb.
Name
1 household_id
2 byprod_id
By-product number

Variable

Label

1
2
3
4
5
6

3 q0708
4
5
6
7
8
9

q0709
q0710
q0711
q0712
q0713
q0714

Code

709. Total Production
710. Quantity consumed by household
711. Quantity sold712. Total amount received from sales
713. Quantity produced and sold714. Total amount received from produced and sold

Manual Mongolia HSES 2012 Version 2.0

Categories
Label

Goat cashmere, kg
Wool, hair, cashmere, kg
Skins and hides, pieces
Milk, airag, liters
Eggs, (number)
Other by-products

246

Database documentation for the HSES Mongolia 2012
06_cropNb.
Name
1 household_id
2 crop_id
Crop Number

VariableLabel

3 q0719519. Did harvest during past 12 M?

4
5
6
7
8

520. Total harvest in past 12 M in KG
521. Quantity consumed by your HH
522. Quantity used for animal feed
523Q. Quantity sold (KG)
523T. Total amount sold (Tugrugs)

q0720
q0721
q0722
q0723qq0723tCategories
Label

Code
1
2
3
4
5
6
7
8
9
10
11
12
13

Potatoes
Carrots
Turnip
Cabbage
Beetroot
Onion
GarlicTomatoes
CucumberFruitsWheat
Haylage
Other…

1
2

YES
NO

Manual Mongolia HSES 2012 Version 2.0

247

Database documentation for the HSES Mongolia 2012
07_agric_exp

Variable
Nb.
Name
Label
1 household_id
2 exp_id
Expenditure Item

3 q0724

Code

Categories
Label

1
2
3
4
5
6
7
8
9
10
11
12
13

Seeds
Fertilizers
Extermination of vermin
Wages & salaries
Equipent & Tools
Spareparts
Repairs and services
Raw materials
Gasoline, fuelTaxes , insurances and fees
Transport
Rent
Others07-24: Total expenditures on item during past 12 mths

Manual Mongolia HSES 2012 Version 2.0

248

Database documentation for the HSES Mongolia 201208_enterpriseNb.
Name
1 household_id
2 en
3 q0803
4 q0804
5 q0805
6 q0806
7 q0807_01
8 q0807_02
9 q0807_03
10 q0807_04
11 q0807_05
12 q0807_06
13 q0807_07
14 q0807_08
15 q0807_09
16 q0807_10
17 q0807_11
18 q0807_99
19 q0808
20 q0809_1a
21 q0809_1b
22 q0809_2a
23 q0809_2bq0809_3aq0809_3b

Variable

LabelEnterprise Number (1-2-3)
0603. Activity Code0604. What % of this enterprise is owned by members
0605. How many members work in this enterprise0606. How many not members work in this enterprise past mont
0807_01: Wage of labor
0807_02: Expenditures in: Goods for resale
0807_03: Expenditures in: Raw materials
0807_04: Expenditures in: Gasoline, fuel0807_05: Expenditures in: water, steam
0807_06: Expenditures in: Equipment
0807_07: Expenditures in: Rental of facilities
0807_08: Expenditures in: Spare parts
0807_09: Expenditures in: Repair and maintenance
0807_10: Expenditures in: Tax, fees, patent, license, insura
0807_11: Expenditures in: Other expenses(labor, water, steam
0807_99: TOTAL EXPENSES
0808: Months in operation?
0809-1. Amount received in a average month (per mth)
0809-1. Number of average months
0809-2. Amount received in a bad month (per mth)
0809-2. Number of bad months
0809-3. Amount received in a good month (per mth)
0809-3. Number of good months

Manual Mongolia HSES 2012 Version 2.0

Code

Categories
Label

249

Database documentation for the HSES Mongolia 2012
09_other_income

Variable
Nb.
Name
Label
1 household_id
2 income_id
Source Number

3 q0901

09-01: Has anybody received ...

4
5
6
7
8
9
10
11
12
13

09_02: ID CODE 1
09_02: Amount during the past 12 mths (1)09_03: ID CODE 2
09_03: Amount during the past 12 mths (2)09_04: ID CODE 3
09_04: Amount during the past 12 mths (3)09_05: ID CODE 4
09_05: Amount during the past 12 mths (4)09_06: ID CODE 5
09_06: Amount during the past 12 mths (5)q0902_ic
q0902_tq0903_ic
q0903_tq0904_ic
q0904_tq0905_ic
q0905_tq0906_ic
q0906_t

Categories
Label

Code
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26

State pension
Special Pension
Unemployment benefit
Maternity benefits
Disability pension
Survivor pension
Illness payments
Funeral payments
Human development fund allowances (received in cash)
Human development fund allowances (transferred to account)
Human development fund allowances (student, superiority, other)
Mother benefit
Student benefit
Other social benefit
Rent of own assets (land, buildings, ve
Sale of assets
Inheritances and wedding presents
Loan repayments
Withdrawals from bank savings
Income from other sourses
savings?
Dividends?
Loan?
Treasury Bond?
Gambling, lottery and contest
Other income (from intellectual propert

1
2

YES
NO

Manual Mongolia HSES 2012 Version 2.0

250

Database documentation for the HSES Mongolia 2012
10_remittance

Variable
Nb.
Name
Label
1 household_id
2 lnLine Number
3 ind_id0908 ID CODE
4 q09090909. Who gave the gift

5 q09100910 Purpose of the receipt

6 q09110911. From where the gifts

7 q0912
8 q0913
9 q09140912. from wich country the gift (code)
0913. How much was received during the past 12 M (TUGR)
0914. Do receive it regularly?

10 q0915

0915. How do you receive it?

CodeCategories
Label

1
2
3
4
5
6
7

GOVERNMENTCOMPANIES AND ORGANIZATIONSNGOsPARENTS, CHILDREN, RELATIVESOTHER INDIVIDUALS (FRIENDS, NEIGHBORS,FOREIGN & INTERNATIONAL ORGANIZATIONS,OTHERS

1
2
3
4
5
6
7
8

HOUSEHOLD USEEDUCATION8 TUITION FEE
MEDICAL TREATMENT
PURCHASE OF DWELLINGHOLIDAY
FUNERAL
HOUDEHOLD ENTERPRISE
OTHER

1
2
3
4
5

Capital city
Aimag center
Soum center
Countrysideimmigration

1
2
3
4
5

YES, weekly
YES, monthly
YES, quarterly
YES, annualy
NO

1
2
3
4
5

CASH
BY ACCOUNTCASH REMITTANCE
IN KINDOTHERManual Mongolia HSES 2012 Version 2.0

251

Database documentation for the HSES Mongolia 201211_savings_loan
VariableNb.
Name
1 household_id
2 loan_id

Loan Number

3 q10051005. Kind of loans?

4 q1006

1006. Did you get this loan in the past 12 months?

q1007
5 q1008

1007. Total loan of past 12 months
1008. Is it possible for your household to repay the loan in time?

6 q10091009. Where do you or does any member of this household get this loans?

7 q10101010a-1010c. What was the loan purpose/function?

q1011
q1011

Label

1011. How much money do you repaid for this loan in the past 1 month?
How much money do you repaid for this loan in the past 12 month?

Code

Categories
Label

1
2
3
4
5
6
7
8
9

Salary loan
Retirement loan
Mortgage loan
Consumer loan
Stockman loan
Business loan
Financing solutions
Vehicle-car loan
Other

1
2

Yes
No

1
2
3

Yes
No
Don't know

1
2
3
4
5
6
7

Bank
Non bank financial institution
Savings and credit cooperatives
Employer or organization
Individual
Pawn shop
Others

1
2
3
4
5
6
7
8

HH expenses
Buy the car
Business
Buy the land
Buy the durable goods
Building a house
Send a HH member abroad
OthersManual Mongolia HSES 2012 Version 2.0

252

Database documentation for the HSES Mongolia 201212_energyNb.
Name
1 household_id
2 energy_id
Source Number

VariableLabel

3 q11361136. Have used the source?

4 q11371137. How do you mainly obtain [FUEL]?

5
6
7
8

1138. How much have you consumed for the past 12 motnths?
1139. Amount spend on purchases of ... in past month
1140. Amount spend on purchases of ... in past 12 months
1141. Value of ... received free in past 12 months

q1138
q1139
q1140
q1141

Manual Mongolia HSES 2012 Version 2.0

Code

Categories
Label

1
2
3
4
5
6
7
8
9

Electricity
Firewood, m3
Firewood, bag
Coal, ton
Coal, bagDung, tonDung, bagGas fuel, l
Other

1
2

YES
NO

1
2
3
4

Collect ourselves
PurchaseCollect and Purchase
Other

253

Database documentation for the HSES Mongolia 201213_payment_serv
Nb.

Variable

Name

Label

1 household_id
2 itemService Number

3 q11421142. Have bought or received free.. during past 12 m?

4 q1143
5 q1144
6 q1145

1143. Amount spend on purchases of .. during past month
1144. Amount spend on purchases of .. during past 12 months
1145. Value of .. received free during past 12 months

Manual Mongolia HSES 2012 Version 2.0

Code

Categories
Label

1
2
3
4
5
6
7
8
9
10
11
12
13

Heating fees
Water use fees
Hot water fees
Dirty water
Garbage disposal
Housing space fees
Other services (lift…)
Other fees (repair of plumbing)
Drinking water /transported/
House rent: Ger
House rent: Apartment, house
Charges of repair of dwelling
Other

1
2

YES
NO

254

Database documentation for the HSES Mongolia 2012
14_durable

Variable
Nb.
Name
Label
1 household_id
2 durable_id
GOOD NUMBER

3 q1201
4 q1202
5 q1203

Code
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44

1201 Number of durable good1202 How long have you used this good1203 Please value this good

Manual Mongolia HSES 2012 Version 2.0

Categories
Label

Refrigerator
Vacuum Cleaner
Washing machine
Sewing machineElectric or Gas Stove
Electric Heater
Electric Gen-set
Electric Iron
Oven
Rice cooker
Water purifier
Iron Stove/Brick stove
Other home appliances & equipment
Traditional Style Bed, Wooden Bed
Sofa
Iron Bed
Room divider
Bedroom furniture sets
Wardrobe Closet
Wooden Table
Wooden Trunk
CarpetOther furniture
Radio
Black & White TV
Color TV
Tape Player, CD Player
Video Cassette Player
Video Camera
CameraComputerOther electronic good
BicycleMotorcycle
Truck, Large truck
Car
Bus
Tractor, harvester
Other household transportation
Ger
House, Dwelling
GarageSummer House

255

Database documentation for the HSES Mongolia 2012
15_non_food
VariableNb.
Name
1 household_id
2 itemNon-food Item code

Label

Code

Categories
Label20101 Men: Leather jacket, deel20102 Men: Winter jacket, winter deel20103 Men: Overcoat
20104 Men: Other leather jacket, winter jacke
20105 Men: Suit, costume20106 Men: Wool and cashmere sweater
20107 Men: Other shirts
20108 Men: Traditional deel20109 Men: Sport wear
20110 Men: Hat, neckwear
20111 Men: Trousers
20112 Men: T-shirts
20113 Men: Underwear
20114 Men: pants (pyjamas ) and nightrobe
20115 Men: Socks
20116 Men: Tights
20117 Other men's clothing and footwear
20201 Women: Leather jacket, deel
20202 Women: Winter jacket, winter deel20203 Women: Overcoat
20204 Women: Other leather jacket, winter jac
20205 Women: Suit, costume20206 Women: Wool and cashmere sweater
20207 Women: Other shirts
20208 Women: Traditional deel20209 Women: Unlined dress and skirts
20210 Women: Sport wear
20211 Women: Hat, neckwear
20212 Women: Trousers
20213 Women: T-shirts
20214 Women: Underwear
20215 Women: pants (pyjamas ) and nightrobe
20216 Women: Socks
20217 Women: Tights
20218 Other women's clothing and footwear
20301 Children: Leather jacket, deel
20302 Children: Winter jacket, winter deel
20303 Children: Overcoat
20304 Children: Other leather jacket, winter20305 Children: Suit, costume20306 Children: Wool and cashmere sweater
20307 Children: Other shirts
20308 Children: Traditional deel
20309 Children: Unlined dress and skirts
20310 Children: Sport wear
20311 Children: Hat, neckwear
20312 Children: Trousers
20313 Children: T-shirts
20314 Children: Underwear
20315 Children: pants (pyjamas ) and nightrobe
20316 Children: Socks
20317 Children: Tights
20318 Other children's clothing and footwear

Manual Mongolia HSES 2012 Version 2.0

256

Database documentation for the HSES Mongolia 2012
15_non_food
Nb.

Name

Variable

Label

Categories
Code
Label
20319 All sorts of clothing for children aged
20320 Wrapping and other articles for infants
20401 Hat, neckwear, gloves
20402 Tie, belts
20403 Handkerchief
20404 Sewing treads
20405 Other (ribbons, press-studs, zip-fasten
20501 Dry cleaning
20502 Laundering
20503 Dyeing of garments
20504 Mending, repair
20505 Hire of garments
20601 Winter shoes
20602 Spring or autumn shoes
20603 Summer shoes, boot20604 Slippers
20605 Summer slippers
20606 Sport
20607 Traditional shoes and buriad shoes
20608 Felt
20609 Other footwear
20610 Footwear for children aged 0-2
20701 Repair of footwear
20702 Shoe cleaning services
20703 Cost for lease of shoes
20801 Woolen cloth, m
20802 Cloth Daalimba,m20803 Tsagaan yambuu, m20804 Cotton cloth, m
20805 Satin, m
20806 All kind of silk, m
20807 Synthetic, m
20808 Cotton, kg
20809 Carded wool
20810 Other......
20901 Furnished and wooden beds
20902 Sofas
20903 Metal beds
20904 Wall and wardrobes
20905 Kitchen furnitures
20906 Bedroom furnitures
20907 Table and chairs
20908 Chest
20909 Electric lamp
20910 Painting and scultures
20911 Mattress20912 Bath room accessories
20913 Mirror
20914 Beds for children
20915 Other furnitures and accessories
20916 Cost for repair and services
20917 Carpets
20918 Strip of carpet/mat
20919 Capping
20920 Oilcloth for the floor

Manual Mongolia HSES 2012 Version 2.0

257

Database documentation for the HSES Mongolia 2012
15_non_food
Nb.

Name

Variable

Label

Categories
Code
Label
20921 Other floor covering
20922 Cost for repair and services
21001 Curtains
21002 Bedsheets
21003 Bed covering
21004 Towel
21005 Bath towel
21006 Tablecloth
21007 Other woven, sewn and cloth appliances
21008 Cost for repair and services
21101 Refrigerators
21102 Vacuum cleaner
21103 Washing mashine
21104 Sewing mashine
21105 Electric and gas stove
21106 Electric heating
21107 Generators
21108 Electric fan
21109 Electric iron
21110 Electric ring/Electric hob
21111 Safe
21112 Other electric appliances (air conditio
21113 Cost for repair and services
21114 Coffee pot
21115 Rice cooker
21116 Bread roaster
21117 Water boiler and electric tea pot
21118 Other (Coffee mixer etc.)
21119 Cost for repair and services
21201 Glasses
21202 Ceramic ware/china-ware
21203 Vacuum flask
21204 Knife, spoon and fork
21205 Plastic utensils
21206 Metal and cast iron utensils
21207 Other utensils
21208 Cost for repair and services
21301 Saws
21302 Spade
21303 Rake
21304 Other (drill, nipper e.g)
21305 Door accessories (hinge e.g)
21306 Electric accessories (breaker, cable)
21307 Flashlight
21308 Lamp
21309 Battery
21310 Bell21311 Signal accessories
21312 Other
21313 Cost of repair and service
21401 Laundry soap, piece
21402 Washing powder/detergent, piece
21403 Match, piece
21404 Candle, piece
21405 Shoe polish, piece

Manual Mongolia HSES 2012 Version 2.0

258

Database documentation for the HSES Mongolia 2012
15_non_food
Nb.

Name

Variable

Label

Categories
Code
Label
21406 Sterilization materials, kg
21407 Other cleaning materials
21408 Brush, besom, piece
21409 Garbage basin, piece21410 Brush, polisher, piece21411 Clothes-hanger, piece
21412 Needle for sewing and woven, piece
21413 Nails, nut, screw
21414 Glue, scotch tape21415 Other tools
21416 House sweeper
21417 Cost disinfection and sterilization
21418 Dry cleaning
21419 Cost for lease of domestic goods
21501 Tablets, vitamins
21502 Injection
21503 Other(condoms,IUD, bandage, thermometer
21504 Eye glasses, contact lenses
21505 Other devices (hearing devices, artific21506 Outpatients clinic examination
21507 Dental care
21508 Other medical services (to give an inje
21509 In patient
21601 Car
21602 Bus
21603 Trucks
21604 Motorcycle
21605 Bicycle
21606 Carting
21607 Repair and services of auto vehicles
21608 Wheels
21609 Spare parts of auto mobile21610 Gasoline, diesel
21611 Other fuel21612 Cost of repair and service
21613 Technical inspection and diagnostics
21614 Lease of garage
21615 Other (Charge for using roads, driving
21616 Cost for transportation rent
21701 Cost for bus and trolleybus
21702 Railway passenger service: Domestic
21703 Railway passenger service: Internationa
21704 Railway freight21705 Taxi cost: Inside the city
21706 Road transportation service: inter-urba
21707 Road transport: Inside the city
21708 Road freight : Inter-urban
21709 Air: Domestic
21710 Air: International
21711 Luggage cost of air
21712 Cost for traveling by water transport
21713 Freight of water transport
21714 Other transports
21801 Letters, parcel, post card
21802 Stamps, envelope (new)Manual Mongolia HSES 2012 Version 2.0

259

Database documentation for the HSES Mongolia 2012
15_non_food
Nb.

Name

Variable

Label

Categories
Code
Label
21803 Telephone, fax mashine
21804 Repair cost of telephone and fax mashin
21805 Calling: Inter-urban
21806 Calling: International
21807 Telephone charge
21808 Mobile/cell phone
21809 Service charge of telegraph, telex and21810 Lease cost of telephone and fax
21811 Installing charge of equipments
21812 Calling card
21813 Charge for internet service
21901 Radio
21902 Black-white TV
21903 Color TV
21904 TV aerial
21905 Tape-recorder21906 Video player
21907 Video camer
21908 Binoculars
21909 Camera
21910 Computer
21911 Calculator
21912 Audio and video cassette, CD
21913 Films
21914 Repair cost of above equipments
21915 Travel tools (boat etc)
21916 Musical instruments (guitar etc)
21917 Billiard board
21918 Repair cost of above tools
22001 Playing card
22002 Chess
22003 Puzzle
22004 Dolls
22005 Car
22006 Electric toys
22007 Other toys
22008 Collection (stamp-collection etc)
22009 Cassette with games, CD
22010 Sport tools (skiing etc)
22011 Gun
22012 Tent
22013 Live and artificial flowers
22014 Xristmas tree
22015 Pets
22016 Food for pets
22017 Shelter, tie and bowl of pets
22018 Services related to the pets(care, trea
22101 Driving lessons
22102 Fee for sport s group study
22103 Performance fee (cinema, drama, concert
22104 Service charge for puppet places
22105 Renting for sport tools
22106 Charge for radio and TV set (cabel TV)
22107 Develop and print out photo films
22108 Lottery

Manual Mongolia HSES 2012 Version 2.0

260

Database documentation for the HSES Mongolia 2012
15_non_food
Nb.

Name

Variable

Label

Categories
Code
Label
22201 Newspapers and journals
22202 Notebook
22203 Pen
22204 Pencil
22205 Books and dictionary
22206 Paper
22207 Other printed matters (post card, calen
22208 Other stationary (ink, erassor, folder
22301 Total cost for recreation and travel
22401 Tuition fee: pre-primary
22402 Tuition fee: primary
22403 Tuition fee: literacy programmes for st
22404 Tuition fee: secondary
22405 Tertiary
22406 Course
22501 Restaurants, cafes
22502 Canteens in schools, works canteens
22503 Accommodation services of hotels
22504 Accommodation services of holidays vill22505 Accommodation services of boarding scho
22601 Toothbrush
22602 Tooth paste
22603 Beauty soap
22604 Toilet paper
22605 Sanitary nupkins
22606 Hairdressing
22607 Beauty salon
22608 Electric razors
22609 Hair dryier
22610 Other electric appliances
22611 Repair of such appliances
22612 Non-electrical razors
22613 Other non-electrical appliances
22614 Beauty powder
22615 Perfume22616 Other beauty products
22701 Valuables
22702 Watches
22703 Repair for valuables
22704 Watch repair
22705 Suitcase
22706 Bag
22707 Wallet
22708 Babys cart, chair
22709 Tube, lighter, ash-tray
22710 Sun glasses, umbrella
22711 Appliances for funeral (coffin, stone e
22712 Repair of above appliances
22801 Service fees for caring elders and disa
22901 Health insurance
22902 Life insurance
22903 Dwelling insurance
22904 Transport insurance
22905 Other
23001 Fee for financial consultation

Manual Mongolia HSES 2012 Version 2.0

261

Database documentation for the HSES Mongolia 2012
15_non_food
Nb.

Name

VariableLabel

3 q13011301. Have you bought or received for the last 12 Ms

4 q1302
5 q1303
6 q1304

1302. Purchased during the past month1303. Purchased during the past 12 months
1304. Received free during the past 12 months

Categories
Code
Label
23002 Service fees for banks and other financ
23101 Fees for administrative documents (for23102 Payment for the services of property ma
23103 Fees for legal services, employment age
23104 Charges for the leasing or rental
23105 Other services
23201 Wall paper, package
23202 Oil paint, l
23203 Bricks, piece
23204 Cement, kg
23205 Glass, m2
23206 Other......
24101 Apartment
24102 House
24103 Ger (complete)
24104 Tent frame
24105 Tent covering
24106 Yard
24107 Stove
24108 Other
24201 Income tax
24202 Cattle tax
24203 Land tax
24204 Other taxes
24301 Gifts for individual
24302 Cost for celebration and wedding
24303 For church and temple
24304 For institution
24305 Other

Manual Mongolia HSES 2012 Version 2.0

1
2

YES
NO

262

Database documentation for the HSES Mongolia 201216_urb_diary

Variable
Nb.
Name
Label
1 household_id
2 itemFood Item code

Code

Categories
Label

10101 Bread (1 piece = 670 gr) - piece
10102 Rice - Kg
10103 Flour, highest grade - Kg
10104 Flour, grade 1 - Kg
10105 Flour, grade 2 - Kg
10106 Other flour - Kg
10107 Noodle,domestic - Kg
10108 Noodle, import - Kg
10109 Bakery - Kg
10110 Biscuit - Kg
10111 Cake - Kg
10112 Millet - Kg
10113 Other rice (farina…) - Kg
10114 Pizza - Piece
10115 Other flour and flour products - Kg
10201 Mutton - Kg10202 Beef - Kg10203 Goat meat - Kg10204 Horse meat - Kg10205 Camel meat - Kg
10206 Dried meat - Kg10207 chicken - Kg10208 Pork - Kg10209 Bacon - Kg
10210 Game - Kg
10211 Other poultry - Kg
10212 Animal interior - Kg
10213 Sausage,salami kg - Kg10214 Sausage - Kg10215 Canned meat - Kg10216 Other meat, meat products - Kg
10301 Fish - Kg
10302 Dried, smoked, salted fish - Kg10303 Canned fish - Kg10304 Other fish and seafood - Kg
10401 Milk - Lt
10402 Youghurt - Lt
10403 Eggs - Nb
10404 Dried curds - Kg
10405 Horse milk, l - Lt
10406 Curds - Kg
10407 Cheese, national - Kg
10408 Cheese - Kg
10409 Curds - Kg
10410 Other milk products - Kg
10411 Dried and coffee milk - Kg
10412 Condensed milk - Lt
10413 Sour cream - Kg
10414 Dried eggs - Kg
10415 Other milk, cheese and eggs - N/A
10501 Butter - kg
10502 Margarine - kg

Manual Mongolia HSES 2012 Version 2.0

263

Database documentation for the HSES Mongolia 201216_urb_diary
Nb.

Name

Variable

Label

Categories
Code
Label
10503 Vegetable oil - Lt
10504 Edible animal fats - kg
10505 Cream - kg
10506 Melted butter - kg
10507 Olive oil - Lt
10508 Other oils and fats - kg
10601 Apple - Kg
10602 Mandarin - Kg
10603 Raisin,kg - Kg
10604 Other fresh fruit ,kg - Kg
10605 Wild fruit - Kg
10606 Dried fruit - Kg
10607 Wild nuts,kg - Kg
10608 Other nuts - Kg
10609 Other Fruits /watermelon etc./ - Kg
10701 Potato - Kg
10702 Cabbage - Kg10703 Carrot - Kg
10704 Turnip - Kg
10705 Onion - Kg
10706 Garlic - Gr
10707 Tomato - Kg
10708 Cucumber - Kg
10709 Jelly sticks - Kg
10710 Canned cucumber - Kg10711 Canned vegetable salad - Kg
10712 Pepper - Kg
10713 Mushrooms - Kg10714 Other vegetables - Kg
10801 Sugar - Kg
10802 Lump sugar - Kg10803 Sugar substitution - Gr
10804 Candy - Kg10805 Sweet - Kg
10806 Chocolate - Gr
10807 Honey - Gr
10808 Compotes - Gr
10809 Jam - Gr
10810 Icecream - Gr10811 Chewing gum - Piece
10812 Syrop - Gr
10813 Other (marmalades, sugar, jam) - N/A
10901 Salt - Gr
10902 Vinegar - Gr
10903 Ketchup - Gr
10904 Mayonnaise - kg
10905 Yeast - Gr
10906 Spice - Gr
10907 Babyfood - kg
10908 Other spices, other food - N/A
11001 Green tea - Gr
11002 Tea - Gr
11003 Coffee - Gr
11004 Cocoa - Gr

Manual Mongolia HSES 2012 Version 2.0

264

Database documentation for the HSES Mongolia 201216_urb_diary
Nb.

Name

3
4
5
6
7
8
9
10
11
12
13
14
15

q1401_1
q1401_2
q1401_3
q1401_4
q1402_1
q1402_2
q1402_3
q1402_4
q1403_1
q1403_2
q1403_3
q1403_4
q1404

Variable

Label

Categories
Code
Label
11005 Other tea, coffee - Gr
11101 Beverage - Lt
11102 Juice - Lt
11103 Pure water, bottled - Lt
11104 Other soft drinks - Lt
11201 Vodka, domestic - Lt
11202 Beer, domestic - Lt
11203 Vodka, imported - Lt
11204 Beer, imported - Lt
11205 Wine - Lt
11206 Other alcoholic beverages - Lt
11301 Cigarette, imported - Box
11302 Cigarette, domestic - Box
11303 Tobacco - Gr
11304 Snuff - Gr
11305 Other (tobacco) - Gr

1401_1 First 10 - Total consumed
1401_2 First 10 - Purchased
1401_3 First 10 - Reseived free
1401_4 First 10 - Own production
1402_1 Second 10 - Total consumed
1402_2 Second 10 - Purchased
1402_3 Second 10 - Reseived free
1402_4 Second 10 - Own production
1403_1 Third 10 - Total consumed
1403_2 Third 10 - Purchased
1403_3 Third 10 - Reseived free
1403_4 Third 10 - Own production
1404 Average unit price

Manual Mongolia HSES 2012 Version 2.0

265

Database documentation for the HSES Mongolia 201217_rur_food_7d

Variable
Nb.
Name
Label
1 household_id
2 itemFood Item code

Code

Categories
Label

10101 Bread (1 piece = 670 gr) - piece
10102 Rice - Kg
10103 Flour, highest grade - Kg
10104 Flour, grade 1 - Kg
10105 Flour, grade 2 - Kg
10106 Other flour - Kg
10107 Noodle,domestic - Kg
10108 Noodle, import - Kg
10109 Bakery - Kg
10110 Biscuit - Kg
10111 Cake - Kg
10112 Millet - Kg
10113 Other rice (farina…) - Kg
10114 Pizza - Piece
10115 Other flour and flour products - Kg
10201 Mutton - Kg10202 Beef - Kg10203 Goat meat - Kg10204 Horse meat - Kg10205 Camel meat - Kg
10206 Dried meat - Kg10207 chicken - Kg10208 Pork - Kg10209 Bacon - Kg
10210 Game - Kg
10211 Other poultry - Kg
10212 Animal interior - Kg
10213 Sausage,salami kg - Kg10214 Sausage - Kg10215 Canned meat - Kg10216 Other meat, meat products - Kg
10301 Fish - Kg
10302 Dried, smoked, salted fish - Kg10303 Canned fish - Kg10304 Other fish and seafood - Kg
10401 Milk - Lt
10402 Youghurt - Lt
10403 Eggs - Nb
10404 Dried curds - Kg
10405 Horse milk, l - Lt
10406 Curds - Kg
10407 Cheese, national - Kg
10408 Cheese - Kg
10409 Curds - Kg
10410 Other milk products - Kg
10411 Dried and coffee milk - Kg
10412 Condensed milk - Lt
10413 Sour cream - Kg
10414 Dried eggs - Kg
10415 Other milk, cheese and eggs - N/A
10501 Butter - kg
10502 Margarine - kg

Manual Mongolia HSES 2012 Version 2.0

266

Database documentation for the HSES Mongolia 201217_rur_food_7d
Nb.

Name

Variable

Label

Categories
Code
Label
10503 Vegetable oil - Lt
10504 Edible animal fats - kg
10505 Cream - kg
10506 Melted butter - kg
10507 Olive oil - Lt
10508 Other oils and fats - kg
10601 Apple - Kg
10602 Mandarin - Kg
10603 Raisin,kg - Kg
10604 Other fresh fruit ,kg - Kg
10605 Wild fruit - Kg
10606 Dried fruit - Kg
10607 Wild nuts,kg - Kg
10608 Other nuts - Kg
10609 Other Fruits /watermelon etc./ - Kg
10701 Potato - Kg
10702 Cabbage - Kg10703 Carrot - Kg
10704 Turnip - Kg
10705 Onion - Kg
10706 Garlic - Gr
10707 Tomato - Kg
10708 Cucumber - Kg
10709 Jelly sticks - Kg
10710 Canned cucumber - Kg10711 Canned vegetable salad - Kg
10712 Pepper - Kg
10713 Mushrooms - Kg10714 Other vegetables - Kg
10801 Sugar - Kg
10802 Lump sugar - Kg10803 Sugar substitution - Gr
10804 Candy - Kg10805 Sweet - Kg
10806 Chocolate - Gr
10807 Honey - Gr
10808 Compotes - Gr
10809 Jam - Gr
10810 Icecream - Gr10811 Chewing gum - Piece
10812 Syrop - Gr
10813 Other (marmalades, sugar, jam) - N/A
10901 Salt - Gr
10902 Vinegar - Gr
10903 Ketchup - Gr
10904 Mayonnaise - kg
10905 Yeast - Gr
10906 Spice - Gr
10907 Babyfood - kg
10908 Other spices, other food - N/A
11001 Green tea - Gr
11002 Tea - Gr
11003 Coffee - Gr
11004 Cocoa - Gr

Manual Mongolia HSES 2012 Version 2.0

267

Database documentation for the HSES Mongolia 201217_rur_food_7d
Nb.

Name

VariableLabel

3 q1501

1501. Have you consumed food during the 7 days

4
5
6
7
8

1502. Total consumed in the past 7 days
1503. Consumed from purchases
1504. Unit price1505. Consumed from Received free
1506. Consumed from Produced

q1502
q1503
q1504
q1505
q1506

Categories
Code
Label
11005 Other tea, coffee - Gr
11101 Beverage - Lt
11102 Juice - Lt
11103 Pure water, bottled - Lt
11104 Other soft drinks - Lt
11201 Vodka, domestic - Lt
11202 Beer, domestic - Lt
11203 Vodka, imported - Lt
11204 Beer, imported - Lt
11205 Wine - Lt
11206 Other alcoholic beverages - Lt
11301 Cigarette, imported - Box
11302 Cigarette, domestic - Box
11303 Tobacco - Gr
11304 Snuff - Gr
11305 Other (tobacco) - Gr
1
2

Manual Mongolia HSES 2012 Version 2.0

YES
NO

268

Database documentation for the HSES Mongolia 2012
19_foodout
Nb.

Name

1 household_id
2 itemService Number
3 q1507

Variable

Label

Code

Categories
Label

22501 Restaurants, cafes
22502 Canteens in schools, works canteens1
2

4 q1508
5 q1509

Manual Mongolia HSES 2012 Version 2.0

YESNO