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

Mongolia HSES 2010
(Version 1.0)

2017
The Institute of Statistical Mathematics (ISM)
andStatistical Information Institute for Consulting and Analysis (SINFONICA)

1

History of revision of the manualUVersion 1.0: Finalized in March 2017 based on the discussion during the Workshop in
December 2016.

Provisional version in November 2016 for the Workshop in December 2016.

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2

CONTENTS

Mongolia HSES 2010
1. About this Manual

Page 4

2. Outline of the survey

5Objective of the survey

Topics covered by the surveyFrequency of the survey

Survey period

Coverage of the survey

Sample designData collection methodData entry and data checkPublication

Technical and financial assistance

3. Data and metadata provided

7

4. Data import
4.1 Import STATA data files into R

94.2 Generated list of variable names in each data frame

10

4.3 Identifier

37

4.4 Weight39

5. Data check5.1 Structure of each data file41

5.2 Summary of each variable55

5.3 Frequency tables of categorical variables

66

5.4 Consistency check of identifier74

6. Household income
6.1 Outline of estimation of household income and expenditure75

6.2 Estimation of monthly household income

80

6.3 Wage income

82

6.4 Pension

86

6.5 Income from livestock89

6.6 Agricultural income

92

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6.7 Business income

95

6.8 Other income

99

6.9 Total household income

102

7. Household expenditure
7.1 Outline of estimation of monthly household expenditure103

7.2 Monetary expenditure
7.2.1 Urban food purchased

103

7.2.2 Rural food purchased

105

7.2.3 Non-food107

7.3 Non-monetary expenditure
7.3.1 Urban food110

7.3.2 Rural food118

7.3.3 Non-food

124

7.4 Total household expenditure125

9. Micro data to be provided

127

10. References: Imputed rent

131

Attachments:

142

1. The questionnaire
1.1 SES-1: Diary for the keeping in households (the first 10 days of a month)147

1.2 SES-2a: Consumption of food and other frequently purchased commodities (from diary)
for the households in the capital and aimag center

159

1.3 SES-2b: Consumption of food during the past 7 days (by recall)for the rural households /soum center and herders/165

1.4 SES-3: Section 0 to section 10

173

2. Data dictionary: Database documentation

207

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1. About this Manual
1. This manual was prepared for users to use the next 80% resampled micro data sets of Mongolia
U

U

Household Socio Economic Survey (HSES) 2010.

CSV format[1] "Household_80.csv""Individual_80.csv""Llivestock_80.csv"[4] "Llivestock Expenditure_80.csv""Product_80.csv""Crop_80.csv"[7] "Agriultural Expenditure_80.csv" "Enterprise_80.csv""Other income_80.csv"[10] "Remittance_80.csv""Energy_80.csv""Payment service_80.csv"[13] "Durable_80.csv""Non-Food_80.csv""Urban Diary_80.csv"[16] "Rural Food 7 day_80.csv""Basicvars_80.csv""HH_inc_exp_80.csv"

R format
The elements of the list object of “outfiles.80”correspond to;[1] "Household.80""Individual.80""Llivestock.80"[4] "Llivestock Expenditure.80""Product.80""Crop.80"[7] "Agriultural Expenditure.80" "Enterprise.80""Other income.80"[10] "Remittance.80""Energy.80""Payment service.80"[13] "Durable.80""Non-Food.80""Urban Diary.80"[16] "Rural Food 7 day.80""Basicvars.80""hhincexp.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 March 2017 by;
Hiroshige Furuta
Visiting Senior Research Fellow, Sinfonica

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2. Outline of Mongolia HSES 2010
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

surveythe basket and weights for consumer price index, and offer inputs to thenational accounts.

Topics covered byConsisted of 11 major modules: basic socio-economic information about thethe survey

members of households, education, health, employment, livestock, crop
production, household business and other income, housing and energy,
durable goods, non-food expenditures and 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 2010 to December 2010


Coverage of thesurvey

Geographical coverage: National

Survey target: Households and its members who live in territory ofMongolia while the survey is present, will participate in this survey.
 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 2010 HSES used the sampling frame which was developed by the
NSO based on 2005 population figures obtained from local registration
offices, because any frame based on the Census 2000 would not be
relevant anymore.

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.

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

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)
were selected with a probability proportional to their sizes and wererandomly 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 isslightly smaller: 3,572 households in Ulaanbaatar; 2,639 in aimag
centers; and 4,987 in rural areas and small towns. The difference is
explained by 60 households, for which complete information was
unavailable and were thus, excluded.

Data collectionSample size: 11,198 householdsFace-to-faceAll procedures were streamlined and centralized, which is likely to havemethodData entry anddata check

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 ofthis report. In all cases, it was possible to compare the listings used forconsistency checks against actual questionnaires filled out byhouseholds (in fact, during the first round of checks, some households
were visited again) and the data were revised whenever an error was
found.

Publication

POVERTY PROFILE IN MONGOLIA: Main Report (2011)

Technical and

Conducted HSES 2007-08 with support of World Bank.

financialNo description about World Bank in HSES 2010.

assistance

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3. Data and metadata provided
The following data and metadata are downloaded from Mongolian NSO’s website.
URL: http://web.nso.mn/nada/index.php/catalog/77

Household data files

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



Metadata

Codebook

HSES_Dbase_codebook_2010.pdf
Database documentation including variable labels and value labels

Survey report

HSES_2010.pdf
POVERTY PROFILE IN MONGOLIA: Main Report (2011)

Questionnaire

The questionnaire form was not available at the website. However, it was provided
by NSO upon request.

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IHSN
http://catalog.ihsn.org/index.php/catalog/4720

Survey report

The same as above

Codebook

The same as above(Accessed on 13 August 2016)

The survey report includes the followings in the annex;Overview of HSES and sampling design (in Annex A)Construction of consumption aggregate (in Annex B)

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9Chapter 4. Data import
4.1 Import STATA data files into R> STATA.files<-list.files()> STATA.files[1] "Household.dta""Individual.dta"[3] "Llivestock.dta""Llivestock Expenditure.dta"[5] "Product.dta""Crop.dta"[7] "Agriultural Expenditure.dta" "Enterprise.dta"[9] "Other income.dta""Remittance.dta"[11] "Energy.dta""Payment service.dta"[13] "Durable.dta""Non-Food.dta"[15] "Urban Diary.dta""Rural Food 7 day.dta"[17] "Basicvars.dta"# Imported STATA files into R> library(foreign)> outfiles<-list()> for(j in 1:17){+ outfiles<-c(outfiles,list(read.dta(STATA.files[j],convert.factors=F)))+ }> length(outfiles)[1] 17# 17 R data frames were stored in the list “outfiles”.
# Made list of data file names, number of records and variables> for(j in 1:17) cat(j,":",STATA.files[j],":",dim(outfiles[[j]]),"\n")1 : Household.dta : 11198 75
2 : Individual.dta : 43355 72
3 : Llivestock.dta : 13781 8
4 : Llivestock Expenditure.dta : 9273 3
5 : Product.dta : 25518 9
6 : Crop.dta : 2259 8
7 : Agriultural Expenditure.dta : 10044 3
8 : Enterprise.dta : 2051 23
9 : Other income.dta : 257393 13
10 : Remittance.dta : 22265 9
11 : Energy.dta : 67188 8
12 : Payment service.dta : 145574 6
13 : Durable.dta : 481514 5
14 : Non-Food.dta : 3964092 6
15 : Urban Diary.dta : 757720 16
16 : Rural Food 7 day.dta : 608408 8
17 : Basicvars.dta : 11198 13

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4.2 Generated list of variable names in each data frame
Summary
 Each file has household identifier “identif”.
 Area information and weight are found only in the data frame “Basicvars”.
 The variable of household total income and total expenditure are not found.


The variable of “29 cluster2” in the data frame “Household”is missing in the variable list of“hhold” in the attached “Database documentation”.

> for(k in 1:17){+ 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(length(cb[[j]])==3){ # including value labels+t<-cb[[j]]$vallabel+
for(k in 1:length(t)){+
cat(rep(" ",10),format(t[k],width=3),format(names(t)[k],width=30),"\n")+} # end of for+ } # end of if+ } # end of for j+ } # end of for k

1 ### Household.dta ###1 identif
group(identif)
2 q0008
8 Nb of hh members
3 hh_noHH_NO
4 v1_dd
Visit 1 DD
5 v1_mmVisit 1 MM
6 v1_yy
Visit 1 YY
7 v1_res
Visit 1 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
8 v2_dd
Visit 2 DD
9 v2_mmVisit 2 MM
10 v2_yy
Visit 2 YY
11 v2_res
Visit 2 Result
1 COMPLETE

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12 v3_dd
13 v3_mm
14 v3_yy
15 v3_res

16 v4_dd
17 v4_mm
18 v4_yy
19 v4_res

20 q0507

21 q0515

22 q0516
23 q0517

24 q0501

25 q0518
26 q0601

27 q0602
28 q0707

29 cluster2
30 visitor
31 ndays
32 q0801
33 q0802

2 PARTIALLY COMPLETED
3 NO RESPONDENT IN THE HOUSEHOLD
4 HOUSEHOLD TEMPERARILY NOT PRESENT
5 POSTPONED
6 REFUSED
7 HOUSEHOLD NOT FOUND
Visit 3 DD
Visit 3 MM
Visit 3 YY
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
Visit 4 DD
Visit 4 MM
Visit 4 YY
Visit 4 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
0507 Has produced animal products past 12m?
1 YES
2 NO
0515 Agricultural land in past 12 m?
1 YES
2 NO
0516 What is total amount owned the past 12M
0517 Has vegetables, fruits in pas 12M
1 YES
2 NO
05-01 Raised or Owned Herding,poultry or any animal?
1 YES
2 NO
0518 What is total amount agricultural land HH members past
0601. Are there household enterprises?
1 YES
2 NO
0602. How many enterprises?
07-07 :Has any member received money or goods
1 YES
2 NO
Cluster Cover Form 2
Number of visitors Cover Form 2
Number of days Cover Form 2
0801. Number of dwellings
0802. Is main dwelling?
1 YES
2 NO

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34 q0803

35 q0804
36 q0805

37 q0806

38 q0807

39 q0808
40 q0809
41 q0810
42 q0811
43 q0812

44 q0813

45 q0814

46 q0815
47 q0816
48 q0817

49 q08180803. Type of Dwellings
1 GER
2 BUILDING
3 DETACHED HOUSE
4 APARTMENT
5 STUDENT'S DORMITORY
6 WORKER'S DORMITORY
7 OTHER DORMITORY ACCOMODATION
8 NON-LIVING QUARTERS
9 OTHER
0804. Number of rooms in the dwelling
0805. Main material of the walls
1 BRICKS
2 CEMENT
3 WOOD
4 STONE
5 OTHER
0806. Main material of the roof
1 METAL
2 ASPHALT ROOF SHINGLES
3 TILE
4 OTHER
0807. Main material of the floor
1 WOOD
2 CEMENT
3 EARTH
4 OTHER
0808. Living area
0809. Total useful area
0810. What is the total area occupies
0811. Number of walls in the ger
0812. Covering of the ceiling
1 SINGLE
2 DOUBLE
0813. Covering of the frame
1 SINGLE
2 DOUBLE
0814. Main material of the floor
1 WOOD
2 EARTH
3 OTHER0815. How old is this dwelling99 ***Undefined Label
0816. How long have you been living
99 ***Undefined Label
0817. Type of ownership
1 STATE
2 ORGANIZATION'S
3 PRIVATE
0818. How was acquired
1 RENTING
2 INHERITED
3 GIFT
4 BUILT BY OURSELVES
5 PURCHASED
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50 q0819

51 q0820
52 q0821
53 q0822

54 q0823

55 q0824

56 q0825

57 q0826

58 q0827

59 q0828

60 q0829

61 q0830_1
62 q0830_2
63 q0830_3
64 q0830_4
65 q0830_5

7 OTHER0819. Did you borrow any money to acquire
1 YES
2 NO
0820. If you wanted to rent, how much
99 ***Undefined Label
0821. How much do you pay for rent
0822. 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
0823. Source of electricity
1 CENTRAL SYSTEM
2 LOCAL SYSTEM/DIESEL STATION
3 SOLAR SUSTEM
4 WIND SYSTEM
5 SMALL GEN-SET
6 CANDEL
7 OTHER0824. Electricity resource adequate for operating electric d
1 YES
2 NO
0825. 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
0826. Has the household a sewage system
1 YES
2 NO
0827. Household waste disposal
1 THROUGH TUBE
2 SPECIAL PLACE FOR WASTE
3 NO SPECIAL PLACE
4 OTHERS
0828. What type of toilet do you have
1 SEPARATE
2 PUBLIC
3 OUTSIDE THE DWELLING
4 NO TOILET
0829. Has a telephone
1 YES, LAND LINE PHONE
2 YES, MOBILE PHONE
3 YES, BOTH LAND AND MOBILE PHONE
4 NO
0830. 1-Distance to the nearest 8 GRADE school
0830. 2-Distance to the nearest 10 GRADE school
0830. 3-Distance to the nearest medical care
0830. 4-Distance to the nearest pharmacy
0830. 5-Distance to the nearest well

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66 q0831

67 q0832_a
68 q0832_b
69 q0833

70 q0834
71 q0835_1

72 q0835_2

73 q0835_3

74 q0835_4

75 q0835_5

0831. Anybody from your household own or exploit land ?
1 YES
2 NO
0832. How many hectares does your household OWN?
0832. How many hectares does your household OPERATE?
0833. Use internet normally?
1 YES
2 NO
0834. How many household member
0835_1. Where used internet, at home
1 YES
2 NO
0835_2. Where used internet, at work
1 YES
2 NO
0835_3. Where used internet, internet cafe
1 YES
2 NO
0835_4. Where used interne, free public accesst
1 YES
2 NO
0835_5. Where used internet, other
1 YES
2 NO

2 ### Individual.dta ###1 identif
group(identif)
2 ind_id
Ind ID
3 q0102102. 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
7 SON / DAUGHTER IN LAW
8 GRAND PARENT
9 GRANDCHILD
10 OTHER RELATIVE
11 SERVANT
12 OTHER
4 newhead
Head of the household
5 q0103103. Sex
1 MALE
2 FEMALE
6 q0104
104. Year of birth
7 q0105y105. Age Yrs
8 q0105m
105. Age Mths
9 q0106
106. Marital Status
1 MARRIED
2 LIVING TOGETHER
3 SEPARATED
4 DIVORCED
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10 q0107
11 q0108
12 q0109
13 q0110a
14 q0110
15 q0111

16 q0201

17 q0202

18 q0203
19 q0204

20 q0205

21 q0206

22 q0207

23 q0208

24 q0209t

6 NEVER MARRIED
107. Spouse ID CODE
108. Father ID CODE
109. Mother ID CODE
110 A. Days away past month110. Months away
111. Is HH member?
1 YES
2 NO
201. Is 6 years or more?
1 YES
2 NO
202. Is answering personally?
1 YES
2 NO
203. Respondent ID CODE
204. 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
205. Can read a letter?
1 YES, EASILY
2 YES, WITH DIFFICULTY
3 NO
206. Are you attending School?
1 YES
2 NO, DROPPEDOUT
3 NO, NEVER ATTENDED
4 NO, COMPLETED
207. Check age/ between 8-35 years
1 YES
2 NO
208. 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
209. Current education TYPE
1 GENERAL
2 VOCATIONAL

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25 q0209g
26 q0210

27 q0211

28 q0212

29 q0213

30 q0214_1
31 q0214_2
32 q0214_3
33 q0214_4
34 q0214_5
35 q0214_6
36 q0214_7
37 q0214_8
38 q0301

39 q0302
40 q0303

41 q0304a

42 q0304b

43 q0305

44 q0306

3 COLLEGE, UNIVERSITY
4 OTHER (ECLE-SIASTICAL, NON FORMAL)
209. Current education GRADE
210. Type of School
1 PUBLIC
2 PRIVATE
3 OTHER
211. School Location
1 CAPITAL CITY
2 AIMAG CENTER
3 SOUM CENTER
4 ABROAD
212. Place where person lives during school
1 HOME
2 GER APPART FROM HH
3 DORMITORY
4 RELATIVES
5 OTHER
213. Pay tuition?
1 YES
2 NO
214_1. Expenditures during past 12 months in room rent
214_2. Expenditures during past 12 months in tuition paid by
214_3. Expenditures during past 12 months in tuition paid fr
214_4. Expenditures during past 12 months in books and suppl
214_5. Expenditures during past 12 months in uniforms
214_6. Expenditures during past 12 months in transport
214_7. Expenditures during past 12 months in others
214_8. Expenditures during past 12 months in TOTAL
301. Answering personally?
1 YES
2 NO
302. Respondent ID CODE
303. Any health problem during past month?
1 YES
2 NO
304_A. Health problem (1)1 RESPIRATORY SYSTEM
2 DIGESTIVE SYSTEM
3 URINARY AND SEXUAL ORGAN
4 BLOOD CIRCULATION SYSTEM
5 DAMAGE OR INTOXICATION BY EXTERNAL IMPACT
6 OTHER
304_B. Health problem (2)0 NO MORE
1 RESPIRATORY SYSTEM
2 DIGESTIVE SYSTEM
3 URINARY AND SEXUAL ORGAN
4 BLOOD CIRCULATION SYSTEM
5 DAMAGE OR INTOXICATION BY EXTERNAL IMPACT
6 OTHER
305. Did you seek treatment in past 1 M?
1 YES
2 NO
306. Why didn't seek treatment?
1 NOT SERIOUS ENOUGH

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45 q0307

46 q0308

47 q309_1
48 q309_2
49 q0310

50 q0311
51 q0312

52 q0313

53 q0314
54 q0315
55 q0401

56 q0402

57 q0403
58 q0404

59 q0405

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
11 DIDN'T KNOW FROM WHERE TO GET TREATMENT
12 TRADITIONAL HEALER
307. Where was treatment provided?
1 CENTRAL HOSPITAL/CLINIC
2 AIMAG/DISTRICT CLINIC
3 SOUM CENTER FAMILY CLINIC
4 PRIVATE
5 ABROAD
6 OTHER
308. Who provided medical service for your treatment?
1 SPECIALISED DOCTOR
2 FAMILY DOCTOR
3 MEDSISTER
4 CHIROPRACTOR
5 TRADITIONAL HEALER
6 OTHER
309_1. Amount paid in facility or healt practitioner
309_2. Amount paid in transportation or others
310. Have bought medicines in the past M ?
1 YES
2 NO
311. Amount spent in medicines
312. Have stayed at hospital in past 12 M?
1 YES
2 NO
313. What was the Hospital ?
1 CENTRAL HOSPITAL/CLINIC
2 AIMAG/DISTRICT CLINIC
3 SOUM CENTER FAMILY CLINIC
4 PRIVATE
5 ABROAD
6 OTHER
314. How much did you pay for all costs
315. Amount spent in transportation
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
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

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60 q0406

61 q0407

62 q0408

63 q0409

64 q0410

65 q0411c
66 q0412c
67 q0413
68 q0414

69 q0415

70 q0416a
71 q0416b
72 q0416c

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 SICK
2 PREGNANT
3 CARING FOR OTHERS
4 HOLIDAY
5 TEMPORARY HALT
6 SEASONAL WORK
7 OTHER
4.08 Did you look for a job in last 7 days
1 YES
2 NO
4.09 Reasons for not looking for a job
1 STUDENT
2 TOO OLD
3 HOMEWORK, CARING FOR A BABY
4 EXPECTING A JOB
5 EMPLOYED IN SEASONAL JOBS
6 SICK/CARES OF SICK PERSON
7 DISABLED
8 OTHER
4.10 Registered in labour and social welfare dep?
1 YES
2 NO
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
1 Partnership
2 Cooperative
3 Corporation
4 LLC
5 State owned company
6 Local authority owned company
7 Government organisation
8 NGO
9 Other
4.15 Do your receive any salary in cash and/or in kind
1 YES
2 NO
4.16 Salary amount - past month
4.16 Salary amount - past 12 months
4.16 Bonuses and special allowances

3 ### Llivestock.dta ###1 identif
group(identif)
2 ani_id
Animal Number
1 Cattle
2 Horses
3 Camels

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19

3 q0502_1
4 q0502_2
5 q0502_3
6 q0503
7 q0504
8 q0505

4 Sheep
5 Goats
6 Other502-1. TOTAL
502-2. Number of female502-3. Number of young
503. Use for own food504. Number of sold505. Amount received

4 ### Llivestock Expenditure.dta ###1 identif
group(identif)
2 exp_id
Exp number
1 Animal Feed
2 Drugs and veterinary costs
3 Gassoline /Oil4 Taxes and Insurance
5 Other
3 q0506
05 06: Expenditures on this [herding activity] in the last 1

5 ### Product.dta ###1 identif
group(identif)
2 byprod_id By-product number
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 q0508508. In the past 12 months have your household produced ..?
1 YES
2 NO
4 q0509509. Total Production
5 q0510510. Quantity consumed by household
6 q0511511. Quantity sold
7 q0512512. Total amount received from sales
8 q0513513. Quantity produced and sold
9 q0514514. Total amount received from produced and sold6 ### Crop.dta ###1 identif
group(identif)
2 crop_id
Crop Number
1 Potatoes
2 Carrots
3 Turnip
4 Cabbage
5 Beetroot
6 Onion
7 Garlic
8 Tomatoes
9 Cucumber
10 Fruits
11

Mongolia HSES 2010 Manual (Version 1.0)

20

3 q0519

4 q0520
5 q0521
6 q0522
7 q0523q
8 q0523t

519. Did harvest during past 12 M?
1 YES
2 NO
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)

7 ### Agriultural Expenditure.dta ###1 identif
group(identif)
2 exp_id
Expenditure Item
1 Seeds
2 Fertilizers
3 Extermination of vermin
4 Equipent & Tools
5 Spareparts
6 Repairs and services
7 Raw materials
8 Gasoline, fuel9 Taxes , insurances and fees
10 Rent
11 Loan interest
12 Others
3 q052405-24: Total expenditures on item during past 12 mths

8 ### Enterprise.dta ###1 identif
group(identif)
2 enEnterprise Number (1-2-3)
3 q0603c
0603. Activity Code
4 q06040604. What % of this enterprise is owned by members
5 q06050605. How many members work in this enterprise
6 q06060606. How many not members work in this enterprise past mont
7 q0607_01
0607_01: Expenditures in: Goods for resale
8 q0607_02
0607_02: Expenditures in: Raw materials
9 q0607_03
0607_03: Expenditures in: Gasoline, fuel10 q0607_04
0607_04: Expenditures in: Equipment
11 q0607_05
0607_05: Expenditures in: Rental of facilities
12 q0607_06
0607_06: Expenditures in: Spare parts
13 q0607_07
0607_07: Expenditures in: Repair and maintenance
14 q0607_08
0607_08: Expenditures in: Tax, fees, patent, license, insura
15 q0607_09
0607_09: Expenditures in: Other expenses(labor, water, steam
16 q0607_10
0607_19: TOTAL EXPENSES
17 q0608
0608: Months in operation?
18 q0609_1a
0609-1. Amount received in a average month (per mth)19 q0609_1b
0609-1. Number of average months
20 q0609_2a
0612-2. Amount received in a bad month (per mth)
21 q0609_2b
0609-2. Number of bad months
22 q0609_3a
0609-3. Amount received in a good month (per mth)23 q0609_3b
0609-3. Number of good months

9 ### Other income.dta ###1 identif
group(identif)

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21

2 income_id

3 q0701

4 q0702_ic
5 q0702_t
6 q0703_ic
7 q0703_t
8 q0704_ic
9 q0704_t
10 q0705_ic
11 q0705_t
12 q0706_ic
13 q0706_t

Source Number
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 Baby care allowances
10 Child allowances (transferred to account)
11 Child allowances (received in cash)
12 Other social benefit
13 Rent of own assets (land, buildings, vehicles, equipment)
14 Sale of assets
15 Inheritances and wedding presents
16 Loan repayments
17 Withdrawals from bank savings
18 savings?
19 Dividends?
20 Loan?
21 Treasury Bond?
22 Gambling, lottery and contest
23 Other income (from intellectual property & other)
07-01: Has anybody received ...
1 YES
2 NO
07_02: ID CODE 1
07_02: Amount during the past 12 mths (1)07_03: ID CODE 2
07_03: Amount during the past 12 mths (2)07_04: ID CODE 3
07_04: Amount during the past 12 mths (3)07_05: ID CODE 4
07_05: Amount during the past 12 mths (4)07_06: ID CODE 5
07_06: Amount during the past 12 mths (5)10 ### Remittance.dta ###1 identif
group(identif)
2 ln
Line Number
3 ind_id
0708 ID CODE
4 q07090709. Who gave the gift
1 GOVERNMENT
2 COMPANIES AND ORGANIZATIONS
3 NGOs4 PARENTS, CHILDREN, RELATIVES
5 OTHER INDIVIDUALS (FRIENDS, NEIGHBORS, ETC)
6 FOREIGN & INTERNATIONAL ORGANIZATIONS, INDIVIDUALS
7 OTHERS
5 q07100710 Purpose of the receipt
1 HOUSEHOLD USE
2 EDUCATION8 TUITION FEE
3 MEDICAL TREATMENT
4 PURCHASE OF DWELLING

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22

6 q0711

7 q07128 q0713

9 q0714

5 HOLIDAY/FUNERAL
6 HOUDEHOLD ENTERPRISE
7 OTHER
0711. From where the gifts
1 URBAN
2 RURAL
3 KOREA
4 USA
5 ENGLAND
6 GERMANY
7 JAPAN
8 OTHER COUNTRY0712. How much was received uring the past 12 M (TUGR)
0713. Do receive it regularly?
1 YES, weekly
2 YES, monthly
3 YES, quarterly
4 YES, annualy
5 NO0714. How do you receive it?
1 CASH
2 BY ACCOUNT
3 CASH REMITTANCE
4 IN KIND
5 OTHER

11 ### Energy.dta ###1 identif
group(identif)
2 energy_id Source Number
1 Electricity
2 Firewood, m3
3 Coal, ton
4 Dung, ton
5 Gas fuel, l
6 Other
3 q08360836. Have used the source?
1 YES
2 NO
4 q08370837. How do you mainly obtain [FUEL]?
1 Collect ourselves
2 Purchase
3 Collect and Purchase
4 Other
5 q08380838. How much have you consumed for the past 12 motnths?
6 q08390839. Amount spend on purchases of ... in past month
7 q08400840. Amount spend on purchases of ... in past 12 months
8 q08410841. Value of ... received free in past 12 months

12 ### Payment service.dta ###1 identif
group(identif)
2 itemService Number
1 Heating fees
2 Water use fees
3 Hot water fees

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23

3 q0842

4 q0843
5 q0844
6 q0845

4 Dirty water
5 Garbage disposal
6 Housing space fees7
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 Other0842. Have bought or received free.. during past 12 m?
1 YES
2 NO
0843. Amount spend on purchases of .. during past month0844. Amount spend on purchases of .. during past 12 months
0845. Value of .. received free during past 12 months

13 ### Durable.dta ###1 identif
group(identif)
2 durable_id GOOD NUMBER
1 Refrigerator
2 Vacuum Cleaner
3 Washing machine
4 Sewing machine
5 Electric or Gas Stove
6 Electric Heater
7 Electric Gen-set
8 Electric Iron
9 Iron Stove/Brick stove
10 Other home appliances & equipment
11 Traditional Style Bed, Wooden Bed
12 Sofa
13 Iron Bed
14 Wardrobe Closet
15 Wooden Table
16 Wooden Trunk
17 Carpet
18 Other furniture
19 Radio
20 Black & White TV
21 Color TV
22 Tape Player, CD Player
23 Video Cassette Player
24 Video Camera
25 Camera
26 Computer
27 Other electronic good
28 Bicycle
29 Motorcycle
30 Truck, Large truck
31 Car32 Bus33 Tractor, harvester
34 Other household transportation
35 Gold jewelry

Mongolia HSES 2010 Manual (Version 1.0)

24

3 q0901
4 q0902
5 q090336 Silver Cup, Silver Products
37 Pipe, Heereg (Snuff Bottle)
38 Silver Products for Horses
39 Other Jewelry
40 Ger41 House, Dwelling
42 Garage
43 Summer House
0901 Number of durable good
0902 How long have you used this good0903 Please value this good

14 ### Non-Food.dta ###1 identif
group(identif)
2 itemNon-food Item code
20101 Men: Leather jacket, deel20102 Men: Winter jacket, winter deel20103 Men: Overcoat
20104 Men: Other leather jacket, winter jacket, deel20105 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: Socks
20115 Men: Tights
20116 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 jacket, deel
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: Socks
20216 Women: Tights
20217 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, winter jacket, deel
20305 Children: Suit, costume20306 Children: Wool and cashmere sweater
20307 Children: Other shirts

Mongolia HSES 2010 Manual (Version 1.0)

2520308 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: Socks
20316 Children: Tights
20317 Other children's clothing and footwear
20318 All sorts of clothing for children aged 0-2
20319 Wrapping and other articles for infants aged 0-2
20401 Hat, neckwear, gloves
20402 Tie, belts
20403 Handkerchief
20404 Sewing treads
20405 Other (ribbons, press-studs, zip-fasteners)
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 Mattress

Mongolia HSES 2010 Manual (Version 1.0)

2620912 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
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 conditioner etc)
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 Bell

Mongolia HSES 2010 Manual (Version 1.0)

27

21311 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
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, syringe etc)
21504 Eye glasses, contact lenses
21505 Other devices (hearing devices, artificial limbs etc)
21506 Outpatients clinic examination
21507 Dental care
21508 Other medical services (to give an injection, X-ray etc)
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 license etc)
21616 Cost for transportation rent
21701 Cost for bus and trolleybus
21702 Railway passenger service: Domestic
21703 Railway passenger service: International
21704 Railway freight21705 Taxi cost: Inside the city
21706 Road transportation service: inter-urban (microbus, taxi etc)
21707 Road transport: Inside the city
21708 Road freight : Inter-urban
21709 Air: Domestic

Mongolia HSES 2010 Manual (Version 1.0)

2821710 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)21803 Telephone, fax mashine
21804 Repair cost of telephone and fax mashine
21805 Calling: Inter-urban
21806 Calling: International
21807 Telephone charge
21808 Mobile/cell phone
21809 Service charge of telegraph, telex and facimile
21810 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, treatment etc)
22101 Driving lessons
22102 Fee for sport s group study

Mongolia HSES 2010 Manual (Version 1.0)

2922103 Performance fee (cinema, drama, concert, museum)
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
22201 Newspapers and journals
22202 Notebook
22203 Pen
22204 Pencil
22205 Books and dictionary
22206 Paper
22207 Other printed matters (post card, calendar etc)
22208 Other stationary (ink, erassor, folder etc)
22301 Total cost for recreation and travel
22401 Tuition fee: pre-primary
22402 Tuition fee: primary
22403 Tuition fee: literacy programmes for students too old
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 villages
22505 Accommodation services of boarding schools, universities
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 etc)
22712 Repair of above appliances
22801 Service fees for caring elders and disabled people
22901 Health insurance

Mongolia HSES 2010 Manual (Version 1.0)

30

3 q1001

4 q1002
5 q1003
6 q1004

22902 Life insurance
22903 Dwelling insurance
22904 Transport insurance
22905 Other
23001 Fee for financial consultation
23002 Service fees for banks and other financial institutions
23101 Fees for administrative documents (for birth, marriage ..)23102 Payment for the services of property managers and agents
23103 Fees for legal services, employment agencies
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
1001. Have you bought or received for the last 12 Ms
1 YES
2 NO
1002. Purchased during the past monthq1002
1004. Received free during the past 12 months

15 ### Urban Diary.dta ###1 identif
group(identif)
2 itemFood Item 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

Mongolia HSES 2010 Manual (Version 1.0)

3110112 Millet - Kg
10113
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
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

Mongolia HSES 2010 Manual (Version 1.0)

32

3 s11yn

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
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
Auxiliary 'Consumed? Y/N'

Mongolia HSES 2010 Manual (Version 1.0)

33

4 q1101_1
5 q1101_2
6 q1101_3
7 q1101_4
8 q1102_1
9 q1102_2
10 q1102_3
11 q1102_4
12 q1103_1
13 q1103_2
14 q1103_3
15 q1103_4
16 q1104

1 YES
2 NO
1101_1 First 10 - Total consumed
1101_2 First 10 - Purchased
1101_3 First 10 - Reseived free
1101_4 First 10 - Own production
1102_1 Second 10 - Total consumed
1102_2 Second 10 - Purchased
1102_3 Second 10 - Reseived free
1102_4 Second 10 - Own production
1103_1 Third 10 - Total consumed
1103_2 Third 10 - Purchased
1103_3 Third 10 - Reseived free
1103_4 Third 10 - Own production
1104 Average unit price16 ### Rural Food 7 day.dta ###1 identif
group(identif)
2 itemFood Item 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
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

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3410402 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
10804 Candy - Kg10805 Sweet - Kg
10806 Chocolate - Gr
10807 Honey - Gr
10808 Compotes - Gr
10809 Jam - Gr
10810 Icecream - Gr10811 Chewing gum - Piece

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3 q1201

4 q1202
5 q1203
6 q1204
7 q1205
8 q1206

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
1201. Have you consumed food during the 7 days
1 YES
2 NO
1202. Total consumed in the past 7 days
1203. Consumed from purchases
1204. Unit price1205. Consumed from Received free
1206. Consumed from Produced

17 ### Basicvars.dta ###1 identif
group(identif)
2 hhsize
Household size
3 cluster
Cluster
4 aimag
Aimag
1 Arhangai (01)2 Bayan-Ulgii (02)3 Bayanhongor (03)4 Bulgan (04)
5 Govi-Altai (05)
6 Dornogovi (06)7 Dornod (07)8 Dundgovi (08)9 Zavhan (09)10 Uvurhangai (10)11 Umnugovi (11)Mongolia HSES 2010 Manual (Version 1.0)

36

5 location

6 urban7 region

8 month
9 quarter
10 hhweight
11 strata
12 stratum
13 aimagsoum

12 Suhbaatar (12)13 Selenge (13)14 Tuv (14)15 Uvs (15)16 Hovd (16)17 Huvsgul (17)18 Hentii (18)19 Darhan-Uul (19)20 Ulaanbaatar (20)21 Orhon (21)22 Govisumber (22)Strata 4 locations
1 Ulaanbaatar
2 Aimagcenter
3 Soumcenter4 Countryside
Urban/rural
1 Urban
2 RuralRegion1 West2 Highlands
3 Central
4 East5 Ulaanbaatar
Calendar month of the interview
Calendar quarter of the interview
Strata 3
Combinations of aimags and soums

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4.3 Identifier
Household identifier> d<-outfiles[[17]]> dim(d)[1] 11198
13# Basicvars

The variable of “identif”is unique identifier and the number of unique “identif” is11,198.

> length(unique(d$identif))[1] 11198> sum(duplicated(d$identif))[1] 0Person identifierPerson identifier is the combination of “identif” and “ind_id” for data frames of“Individual”and “Remittance”.

# Generated person identifier “PID”.
02 Individual

PID in data frame “Individual” is unique.

> df<-outfiles[[2]]> dim(df)[1] 43355
72> df$PID<-df$identif*100+df$ind_id> head(df[,c(1:2,73)])
identif ind_id PID
1
1
1 101
2
1
2 102
3
1
3 103
4
1
4 104
5
2
1 201
6
2
2 202
> sum(duplicated(df$PID))[1] 0> outfiles[[2]]<-df

10 Remittance

There are 2,048 duplicated PID in data frame “Remittance”.

> df<-outfiles[[10]]> dim(df)[1] 22265
9> df$PID<-df$identif*100+df$ind_id> head(df)identif ln ind_id q0709 q0710 q0711 q0712 q0713 q0714

PID

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1
25 1
1
2
26 1
1
3
27 1
1
4
28 1
1
5
29 1
1
6
33 1
1
> outfiles[[10]]<-df

7
7
7
7
7
7

7
1
1
7
1
1

1 16000
1 16000
1 16000
1 16000
1 16000
1 16000

5
5
5
5
5
5

4 2501
4 2601
4 27014 28014 29014 3301> sum(duplicated(df$PID))[1] 2048
Example of duplicated PID> head(df[duplicated(df$PID),])
identif ln ind_id q0709 q0710 q0711 q0712 q0713 q0714
PID
29
130 2
1
1
1
1 70000
4
1 13001
63
138 2
4
1
4
1 500000
55 13804
74
142 2
2
4
1
2 130000
4
1 14202
110
162 3
1
1
1
2 30000
5
4 16201
116
164 1
1
1
1
1 70000
4
1 16401
125
166 2
1
4
1
2 500000
44 16601> df[df$identif==130,]
identif ln ind_id q0709 q0710 q0711 q0712 q0713 q0714
PID
26
130 3
2
1
1
1 70000
4
1 13002
27
130 1
1
1
1
1 20000
5
4 13001
28
130 4
7
1
1
1 70000
4
1 13007
29
130 2
1
1
1
1 70000
4
1 13001
Summary:
The person with PID=13001 received two kind of remittances.

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

The estimated number of household is 709,189.

> sum(d$hhweight)[1] 709189

The estimated number of household members is 2,696,378, based on “Basicvars” file.

> sum(d$hhweight*d$hhsize)[1] 2696378

The estimated number of household members is 2,696,489, based on “Individual” file.

> df<-outfiles[[2]]> dim(df)[1] 43355
72> df<-merge(df,d[,c("identif","hhweight")],by="identif",all.x=T)> dim(df)[1] 43355
73# Selected household members> df<-subset(df,q0111==1)> dim(df)[1] 42470
73> sum(df$hhweight)[1] 2696489> nrow(df)/nrow(d)[1] 3.792642> sum(d$hhweight*d$hhsize)/sum(d$hhweight)[1] 3.802059
Un-weighted
11,19842,470
3.79

Number of households
Number of household members
Household size

Weighted
709,189
2,696,489
3.80

Remarks: Differences of the number of household members within the household between “Basicvars”
and “Individual”
Generated household size from “Individual”.

> df<-outfiles[[2]]# Individual> df<-subset(df,q0111==1)> dim(df)[1] 42470
73> t<-tapply(df$PID,df$identif,length)> length(t)# Household size

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40

[1] 11198> head(t)1 2 3 4 5 6
4 7 2 5 4 5> d<-outfiles[[17]] # Baiscvars> table(t==d$hhsize,useNA="always")
FALSE TRUE <NA>
1 111970# There is one inconsistency!
> d[t!=d$hhsize,1:9] # Baiscvars
identif hhsize cluster aimag location urban region month quarter
5063
5063
1
1034
20
1
1
5
6
2
> df[df$identif==5063,1:15]# Individual
identif ind_id q0102 newhead q0103 q0104 q0105y q0105m q0106 q0107 q0108
19909
5063
1
1
1
1 1962
48
NA
1
2
98
19911
5063
3
3
0
2 198921NA
6NA1q0109 q0110a q0110 q0111
19909
99
30
1
1
19911
2
0
0
1

Summary
The household with identif=5063 seems to be composed of a father and a daughter. Therefore,
the hhsize should be read as 2 in “Basicvars”.
This error was confirmed by the delegates from Mongolia.

# Revised Basicvars file
> d[d$identif==5063,"hhsize"][1] 1> d[d$identif==5063,"hhsize"]<-2> d[d$identif==5063,"hhsize"][1] 2> sum(d$hhsize*d$hhweight)[1] 2696489

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Chapter 5. Data Check
5.1 Structure of each data file
> Rnames<-sub(".dta","",STATA.files)> for(j in 1:17){+ cat("##",j,"#### ",Rnames[j]," #########\n")+ print(str(outfiles[[j]]))+ cat("\n\n")+ }## 1 #### Household #########'data.frame':
11198 obs. of 75 variables:$ identif : int 1 2 3 4 5 6 7 8 9 10 ...
$ q0008 : int 4 7 2 5 4 5 4 5 4 5 ...
$ hh_no : int 3 4 5 6 7 8 12 13 1 2 ...
$ v1_dd : int 17 18 19 19 19 20 18 18 15 17 ...
$ v1_mm : int 2 2 2 2 2 2 2 2 3 3 ...
$ v1_yy : int 10 10 10 10 10 10 10 10 10 10 ...
$ v1_res : int 1 1 1 1 1 1 1 1 1 1 ...
$ v2_dd : int 17 18 19 19 19 20 18 18 15 17 ...
$ v2_mm : int 2 2 2 2 2 2 2 2 3 3 ...
$ v2_yy : int 10 10 10 10 10 10 10 10 10 10 ...
$ v2_res : int 1 1 1 1 1 1 1 1 1 1 ...
$ v3_dd : int 17 18 19 19 19 20 18 18 15 17 ...
$ v3_mm : int 2 2 2 2 2 2 2 2 3 3 ...
$ v3_yy : int 10 10 10 10 10 10 10 10 10 10 ...
$ v3_res : int 1 1 1 1 1 1 1 1 1 1 ...
$ v4_dd : int 17 18 19 19 19 20 18 18 15 17 ...
$ v4_mm : int 2 2 2 2 2 2 2 2 3 3 ...
$ v4_yy : int 10 10 10 10 10 10 10 10 10 10 ...
$ v4_res : int 1 1 1 1 1 1 1 1 1 1 ...
$ q0507 : int 1 1 1 1 1 1 1 1 1 1 ...
$ q0515 : int 2 2 2 2 2 2 2 2 2 2 ...
$ q0516 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0517 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0501 : int 1 1 1 1 1 1 1 1 1 1 ...
$ q0518 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0601 : int 2 2 2 2 2 2 2 2 2 2 ...
$ q0602 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0707 : int 2 2 2 2 2 2 2 2 2 2 ...
$ cluster2: int 1 1 1 1 1 1 1 1 8 8 ...
$ visitor : int 2 0 0 0 0 0 0 0 0 0 ...
$ ndays : int 60 0 0 0 0 0 0 0 0 0 ...
$ q0801 : int 1 1 1 1 1 1 1 1 1 2 ...
$ q0802 : int 1 1 1 1 1 1 1 1 1 1 ...
$ q0803 : int 1 1 1 1 1 1 1 1 1 2 ...
$ q0804 : int NA NA NA NA NA NA NA NA NA 3 ...
$ q0805 : int NA NA NA NA NA NA NA NA NA 3 ...
$ q0806 : int NA NA NA NA NA NA NA NA NA 1 ...
$ q0807 : int NA NA NA NA NA NA NA NA NA 1 ...
$ q0808 : int NA NA NA NA NA NA NA NA NA 56 ...
$ q0809 : int NA NA NA NA NA NA NA NA NA 56 ...
$ q0810 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0811 : int 5 5 5 5 5 5 5 5 5 NA ...

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$ q0812 : int 1 1 1 2 1 1 2 1 2 NA ...
$ q0813 : int 1 1 1 2 1 2 2 1 2 NA ...
$ q0814 : int 2 2 2 1 2 1 1 1 1 NA ...
$ q0815 : int 40 20 8 30 30 15 5 12 41 3 ...
$ q0816 : int 40 20 8 30 30 15 5 12 41 3 ...
$ q0817 : int 3 2 3 3 3 3 3 3 3 3 ...
$ q0818 : int 2 NA 2 2 3 2 2 2 4 4 ...
$ q0819 : int NA NA NA NA NA NA NA NA 2 2 ...
$ q0820 : int 99 99 99 99 99 99 99 99 99 99 ...
$ q0821 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0822 : int 2 2 2 2 2 2 2 2 2 2 ...
$ q0823 : int 6 3 3 3 6 2 1 3 6 1 ...
$ q0824 : int 2 2 2 2 2 2 2 2 2 1 ...
$ q0825 : int 7 6 6 6 6 6 6 6 6 3 ...
$ q0826 : int 2 2 2 2 2 2 2 2 2 1 ...
$ q0827 : int 3 3 3 3 3 3 3 3 3 2 ...
$ q0828 : int 3 4 4 4 3 4 3 3 3 3 ...
$ q0829 : int 4 1 2 3 3 3 1 1 4 3 ...
$ q0830_1 : num 0 0 0 0 14 30 0 0 0 0 ...
$ q0830_2 : num 33 46 50 47 45 40 32 2 28 1 ...
$ q0830_3 : num 31 15 40 12 14 35 6 3 28 1 ...
$ q0830_4 : num 31 15 40 12 14 35 6 3 28 1 ...
$ q0830_5 : num 0 0 0 0 0 0 0 0 0 1 ...
$ q0831 : int 2 2 2 2 2 2 2 2 2 2 ...
$ q0832_a : int NA NA NA NA NA NA NA NA NA NA ...
$ q0832_b : int NA NA NA NA NA NA NA NA NA NA ...
$ q0833 : int 2 2 2 2 2 2 2 2 2 2 ...
$ q0834 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0835_1 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0835_2 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0835_3 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0835_4 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0835_5 : int NA NA NA NA NA NA NA NA NA NA ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:26"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 251 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "group(identif)" "8 Nb of hh members" "HH_NO" "Visit 1 DD" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 39..$ 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" ...
..$ 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" ...
..$ 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" ...
..$ 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" ...
..$ q0507 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0515 : Named int 1 2

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43.. ..- attr(*, "names")= chr "YES" "NO"..$ q0517 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0501 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0601 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0707 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0802 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0803 : Named int 1 2 3 4 5 6 7 8 9.. ..- attr(*, "names")= chr "GER" "BUILDING" "DETACHED HOUSE" "APARTMENT" ...
..$ q0805 : Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "BRICKS" "CEMENT" "WOOD" "STONE" ...
..$ q0806 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "METAL" "ASPHALT ROOF SHINGLES" "TILE" "OTHER"..$ q0807 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "WOOD" "CEMENT" "EARTH" "OTHER"..$ q0812 : Named int 1 2.. ..- attr(*, "names")= chr "SINGLE" "DOUBLE"..$ q0813 : Named int 1 2.. ..- attr(*, "names")= chr "SINGLE" "DOUBLE"..$ q0814 : Named int 1 2 3.. ..- attr(*, "names")= chr "WOOD" "EARTH" "OTHER"..$ q0815 : Named int 99.. ..- attr(*, "names")= chr "***Undefined Label"..$ q0816 : Named int 99.. ..- attr(*, "names")= chr "***Undefined Label"..$ q0817 : Named int 1 2 3.. ..- attr(*, "names")= chr "STATE" "ORGANIZATION'S" "PRIVATE"..$ q0818 : Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "RENTING" "INHERITED" "GIFT" "BUILT BY OURSELVES" ...
..$ q0819 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0820 : Named int 99.. ..- attr(*, "names")= chr "***Undefined Label"..$ q0822 : Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "CENTRALIZED" "TRADITIONAL FIRE WOOD/COAL/ DUNG STOVE" "PRIVATE
ELECTRICAL HEATER" "PRIVATE LOW PRESSURE BOILER" ...
..$ q0823 : Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "CENTRAL SYSTEM" "LOCAL SYSTEM/DIESEL STATION" "SOLAR SUSTEM""WIND SYSTEM" ...
..$ q0824 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0825 : Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "CENTRALIZED: HOT & COLD WATER PIPE" "CENTRALIZED: COLD WATERPIPE ONLY" "PROTECTED WELL" "UNPROTECTED WELL" ...
..$ q0826 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0827 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "THROUGH TUBE" "SPECIAL PLACE FOR WASTE" "NO SPECIAL PLACE""OTHERS"..$ q0828 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "SEPARATE" "PUBLIC" "OUTSIDE THE DWELLING" "NO TOILET"..$ q0829 : Named int 1 2 3 4Mongolia HSES 2010 Manual (Version 1.0)

44.. ..- attr(*, "names")= chr
MOBILE PHONE" "NO"..$ q0831 : Named int 1 2.. ..- attr(*, "names")= chr..$ q0833 : Named int 1 2.. ..- attr(*, "names")= chr..$ q0835_1: Named int 1 2.. ..- attr(*, "names")= chr..$ q0835_2: Named int 1 2.. ..- attr(*, "names")= chr..$ q0835_3: Named int 1 2.. ..- attr(*, "names")= chr..$ q0835_4: Named int 1 2.. ..- attr(*, "names")= chr..$ q0835_5: Named int 1 2.. ..- attr(*, "names")= chr
NULL"YES, LAND LINE PHONE" "YES, MOBILE PHONE" "YES, BOTH LAND AND"YES" "NO""YES" "NO""YES" "NO""YES" "NO""YES" "NO""YES" "NO""YES" "NO"## 2 #### Individual #########'data.frame':
43355 obs. of 72 variables:$ identif: int 1 1 1 1 2 2 2 2 2 2 ...
$ ind_id : int 1 2 3 4 1 2 3 4 5 6 ...
$ q0102 : int 1 2 3 4 1 2 3 3 3 3 ...
$ newhead: int 1 0 0 0 1 0 0 0 0 0 ...
$ q0103 : int 1 2 1 2 1 2 1 1 1 1 ...
$ q0104 : int 1942 1954 1989 1927 1972 1972 1991 1997 1998 2002 ...
$ q0105y : int 67 55 20 82 37 37 18 12 11 7 ...
$ q0105m : int NA NA NA NA NA NA NA NA NA NA ...
$ q0106 : int 1 1 6 5 1 1 6 NA NA NA ...
$ q0107 : int 2 1 NA NA 2 1 NA NA NA NA ...
$ q0108 : int 99 99 1 99 98 98 1 1 1 1 ...
$ q0109 : int 99 4 2 99 98 99 2 2 2 2 ...
$ q0110a : int 0 0 10 0 0 0 20 20 20 20 ...
$ q0110 : int 0 0 3 0 0 0 2 9 9 9 ...
$ q0111 : int 1 1 1 1 1 1 1 1 1 1 ...
$ q0201 : int 1 1 1 1 1 1 1 1 1 1 ...
$ q0202 : int 1 1 1 2 2 1 1 2 2 2 ...
$ q0203 : int NA NA NA 2 2 NA NA 2 2 2 ...
$ q0204 : int 2 2 1 1 3 3 3 2 1 1 ...
$ q0205 : int 1 1 2 3 NA NA NA 1 1 1 ...
$ q0206 : int 4 4 2 3 4 4 4 1 1 1 ...
$ q0207 : int NA NA 1 2 NA NA NA NA NA NA ...
$ q0208 : int NA NA 7 NA NA NA NA NA NA NA ...
$ q0209t : int NA NA NA NA NA NA NA 1 1 1 ...
$ q0209g : int NA NA NA NA NA NA NA 70 20 10 ...
$ q0210 : int NA NA NA NA NA NA NA 1 1 1 ...
$ q0211 : int NA NA NA NA NA NA NA 3 3 3 ...
$ q0212 : int NA NA NA NA NA NA NA 4 4 4 ...
$ q0213 : int NA NA NA NA NA NA NA 2 2 2 ...
$ q0214_1: int NA NA NA NA NA NA NA 0 0 0 ...
$ q0214_2: int NA NA NA NA NA NA NA 0 0 0 ...
$ q0214_3: int NA NA NA NA NA NA NA 0 0 0 ...
$ q0214_4: int NA NA NA NA NA NA NA 15000 10000 8000 ...
$ q0214_5: int NA NA NA NA NA NA NA 0 0 0 ...
$ q0214_6: int NA NA NA NA NA NA NA 0 0 0 ...

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$ q0214_7: int NA NA NA NA NA NA NA 0 0 0 ...
$ q0214_8: int NA NA NA NA NA NA NA 15000 10000 8000 ...
$ q0301 : int 1 1 1 2 1 1 1 2 2 2 ...
$ q0302 : int NA NA NA 2 NA NA NA 2 2 2 ...
$ q0303 : int 2 1 1 1 2 2 2 2 2 2 ...
$ q0304a : int NA 4 1 1 NA NA NA NA NA NA ...
$ q0304b : int NA 0 0 0 NA NA NA NA NA NA ...
$ q0305 : int NA 1 2 2 NA NA NA NA NA NA ...
$ q0306 : int NA NA 1 1 NA NA NA NA NA NA ...
$ q0307 : int NA 2 NA NA NA NA NA NA NA NA ...
$ q0308 : int NA 1 NA NA NA NA NA NA NA NA ...
$ q309_1 : int NA 0 NA NA NA NA NA NA NA NA ...
$ q309_2 : int NA 0 NA NA NA NA NA NA NA NA ...
$ q0310 : int 2 2 2 2 2 2 2 2 2 2 ...
$ q0311 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0312 : int 2 1 2 2 2 1 2 2 2 2 ...
$ q0313 : int NA 2 NA NA NA 3 NA NA NA NA ...
$ q0314 : int NA 350000 NA NA NA 0 NA NA NA NA ...
$ q0315 : int NA 70000 NA NA NA 6000 NA NA NA NA ...
$ q0401 : int 1 1 1 1 1 1 1 1 1 2 ...
$ q0402 : int 1 1 2 2 2 1 1 2 2 NA ...
$ q0403 : int NA NA 2 2 2 NA NA 2 2 NA ...
$ q0404 : int 2 2 2 2 1 1 1 2 2 NA ...
$ q0405 : int NA NA NA NA 3 3 1 NA NA NA ...
$ q0406 : int 1 1 1 2 NA NA NA 2 2 NA ...
$ q0407 : int 3 1 3 NA NA NA NA NA NA NA ...
$ q0408 : int NA NA NA 2 NA NA NA 2 2 NA ...
$ q0409 : int NA NA NA 2 NA NA NA 1 1 NA ...
$ q0410 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0411c : int 612 612 612 NA 612 612 914 NA NA NA ...
$ q0412c : int 141 141 141 NA 144 141 8010 NA NA NA ...
$ q0413 : int 45 45 45 NA 56 30 40 NA NA NA ...
$ q0414 : int 9 9 9 NA 9 9 4 NA NA NA ...
$ q0415 : int 2 2 2 NA 2 2 1 NA NA NA ...
$ q0416a : int NA NA NA NA NA NA 200000 NA NA NA ...
$ q0416b : int NA NA NA NA NA NA 200000 NA NA NA ...
$ q0416c : int NA NA NA NA NA NA 0 NA NA NA ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:28"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 251 251 251 252 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "q0102" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Ind ID" "102. Relationship to head" "Head of
the household" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 38..$ q0102 : Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "HEAD" "WIFE / HUSBAND" "SON / DAUGHTER" "FATHER / MOTHER" ...
..$ q0103 : Named int 1 2.. ..- attr(*, "names")= chr "MALE" "FEMALE"..$ q0106 : Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "MARRIED" "LIVING TOGETHER" "SEPARATED" "DIVORCED" ...
..$ q0111 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0201 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"Mongolia HSES 2010 Manual (Version 1.0)

46..$ q0202 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0204 : Named int 1 2 3 4 5 6 7 8 9 10.. ..- attr(*, "names")= chr "NONE" "PRIMARY" "SECONDARY" "COMPLETE SECONDARY" ...
..$ q0205 : Named int 1 2 3.. ..- attr(*, "names")= chr "YES, EASILY" "YES, WITH DIFFICULTY" "NO"..$ q0206 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "YES" "NO, DROPPEDOUT" "NO, NEVER ATTENDED" "NO, COMPLETED"..$ q0207 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0208 : Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "CHILD NOT INTRESTED" "PARENTS NOT INTERESTED" "DIFFICULTTRAINING" "POOR TRAINING QUALITY" ...
..$ q0209t: Named int 1 2 3 4.. ..- attr(*, "names")= chr "GENERAL" "VOCATIONAL" "COLLEGE, UNIVERSITY" "OTHER (ECLESIASTICAL, NON FORMAL)"..$ q0210 : Named int 1 2 3.. ..- attr(*, "names")= chr "PUBLIC" "PRIVATE" "OTHER"..$ q0211 : Named int 1 2 3 4.. ..- attr(*, "names")= chr "CAPITAL CITY" "AIMAG CENTER" "SOUM CENTER" "ABROAD"..$ q0212 : Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "HOME" "GER APPART FROM HH" "DORMITORY" "RELATIVES" ...
..$ q0213 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0301 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0303 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0304a: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "RESPIRATORY SYSTEM" "DIGESTIVE SYSTEM" "URINARY AND SEXUALORGAN" "BLOOD CIRCULATION SYSTEM" ...
..$ q0304b: Named int 0 1 2 3 4 5 6.. ..- attr(*, "names")= chr "NO MORE" "RESPIRATORY SYSTEM" "DIGESTIVE SYSTEM" "URINARY ANDSEXUAL ORGAN" ...
..$ q0305 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ 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" "HEALTH CARE TOO EXPENSIVE" ...
..$ q0307 : Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "CENTRAL HOSPITAL/CLINIC" "AIMAG/DISTRICT CLINIC" "SOUM CENTERFAMILY CLINIC" "PRIVATE" ...
..$ q0308 : Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr"SPECIALISED DOCTOR" "FAMILY DOCTOR" "MEDSISTER""CHIROPRACTOR" ...
..$ q0310 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0312 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0313 : Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "CENTRAL HOSPITAL/CLINIC" "AIMAG/DISTRICT CLINIC" "SOUM CENTERFAMILY CLINIC" "PRIVATE" ...
..$ q0401 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0402 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"Mongolia HSES 2010 Manual (Version 1.0)

47..$ q0404 : 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" ...
..$ q0406 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0407 : Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "SICK" "PREGNANT" "CARING FOR OTHERS" "HOLIDAY" ...
..$ q0408 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0409 : Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "STUDENT" "TOO OLD" "HOMEWORK, CARING FOR A BABY" "EXPECTING A
JOB" ...
..$ q0410 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0414 : Named int 1 2 3 4 5 6 7 8 9.. ..- attr(*, "names")= chr "Partnership" "Cooperative" "Corporation" "LLC" ...
..$ q0415 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"NULL## 3 #### Llivestock #########'data.frame':
13781 obs. of 8 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 ...
$ q0502_1: int 10 5 30 10 40 5 112 90 20 10 ...
$ q0502_2: int 5 2 12 4 15 1 70 40 8 3 ...
$ q0502_3: int 2 0 0 2 0 0 20 12 3 1 ...
$ q0503 : int 1 1 6 4 2 0 13 5 1 0 ...
$ q0504 : int 0 0 0 0 0 0 2 23 0 0 ...
$ q0505 : int NA NA NA NA NA NA 60000 640000 NA NA ...
- 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 252 251 252 252 252 251 252 253- attr(*, "val.labels")= chr "" "ani_id" "" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Animal Number" "502-1. TOTAL" "502-2. Numberof female" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 1..$ ani_id: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "Cattle" "Horses" "Camels" "Sheep" ...
NULL## 4 #### Llivestock Expenditure #########'data.frame':
9273 obs. of 3 variables:$ identif: int 1 2 2 2 3 4 4 6 6 6 ...
$ exp_id : int 2 4 2 1 2 1 2 4 2 1 ...
$ q0506 : int 15000 30000 27000 24000 12000 9000 20000 14000 40000 26000 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:29"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g"- attr(*, "types")= int 252 251 253

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48

- attr(*, "val.labels")= chr "" "exp_id" ""- attr(*, "var.labels")= chr "group(identif)" "Exp number" "05 06: Expenditures on this[herding activity] in the last 1"- attr(*, "version")= int 8- attr(*, "label.table")=List of 1..$ exp_id: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "Animal Feed" "Drugs and veterinary costs" "Gassoline /Oil""Taxes and Insurance" ...
NULL## 5 #### Product #########'data.frame':
25518 obs. of 9 variables:$ identif : int 1 1 1 1 1 1 2 2 2 2 ...
$ byprod_id: int 1 2 3 4 5 6 1 2 3 4 ...
$ q0508: int 1 1 1 1 2 2 1 1 1 1 ...
$ q0509: num 3 30 12 750 NA NA 23 50 20 3500 ...
$ q0510: num 0 0 0 750 NA NA 0 0 0 2800 ...
$ q0511: num 3 30 12 0 NA NA 23 50 20 0 ...
$ q0512: int 54000 9000 62000 NA NA NA 529000 15000 82000 NA ...
$ q0513: int 0 0 0 0 NA NA 0 0 0 250 ...
$ q0514: int NA NA NA NA NA NA NA NA NA 300000 ...
- 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 252 251 251 255 255 255 253 252 253- attr(*, "val.labels")= chr "" "byprod_id" "q0508" "" ...
- attr(*, "var.labels")= chr "group(identif)" "By-product number" "508. In the past 12 months
have your household produced ..?" "509. Total Production" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 2..$ byprod_id: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "Goat cashmere, kg" "Wool, hair, cashmere, kg" "Skins and hides,
pieces" "Milk, airag, liters" ...
..$ q0508: Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"NULL## 6 #### Crop #########'data.frame':
2259 obs. of 8 variables:$ identif: int 58 79 82 85 89 89 97 103 104 110 ...
$ crop_id: int 1 1 1 1 1 11 1 1 1 1 ...
$ q0519 : int 1 1 1 1 1 1 1 1 1 1 ...
$ q0520 : int 240 200 10 20 4000 4000 40 80 75 50 ...
$ q0521 : int 160 80 10 20 500 0 40 80 75 50 ...
$ q0522 : int 0 0 0 0 1000 4000 0 0 0 0 ...
$ q0523q : int 80 0 0 0 2500 0 0 0 0 0 ...
$ q0523t : int 40000 NA NA NA 1250000 NA NA NA NA NA ...
- 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 252 251 251 253 252 252 253 253- attr(*, "val.labels")= chr "" "crop_id" "q0519" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Crop Number" "519. Did harvest during past 12
M?" "520. Total harvest in past 12 M in KG" ...

Mongolia HSES 2010 Manual (Version 1.0)

49

- attr(*, "version")= int 8- attr(*, "label.table")=List of 2..$ crop_id: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "Potatoes" "Carrots" "Turnip" "Cabbage" ...
..$ q0519 : Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"NULL## 7 #### Agriultural Expenditure #########'data.frame':
10044 obs. of 3 variables:$ identif: int 58 58 58 58 58 58 58 58 58 58 ...
$ exp_id : int 5 6 10 2 11 9 8 3 4 1 ...
$ q0524 : int 0 0 0 0 0 0 0 0 0 10000 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:29"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g"- attr(*, "types")= int 252 251 253- attr(*, "val.labels")= chr "" "exp_id" ""- attr(*, "var.labels")= chr "group(identif)" "Expenditure Item" "05-24: Total expenditureson item during past 12 mths"- attr(*, "version")= int 8- attr(*, "label.table")=List of 1..$ exp_id: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "Seeds" "Fertilizers" "Extermination of vermin" "Equipent &Tools" ...
NULL## 8 #### Enterprise #########'data.frame':
2051 obs. of 23 variables:$ identif : int 56 56 73 76 100 101 102 103 104 105 ...
$ en: int 1 2 1 1 1 1 1 1 1 1 ...
$ q0603c : int 1430 1520 4923 3100 4771 4921 3312 1610 4921 4620 ...
$ q0604 : int 100 100 100 100 100 100 100 100 100 100 ...
$ q0605 : int 1 1 1 1 1 1 1 1 1 1 ...
$ q0606 : int 0 0 0 0 0 0 0 0 0 0 ...
$ q0607_01: int 25000 0 0 0 5000000 0 0 0 0 0 ...
$ q0607_02: int 0 20000 0 400000 0 0 150000 300000 0 800000 ...
$ q0607_03: int 0 0 2000000 0 0 250000 0 0 400000 0 ...
$ q0607_04: int 0 0 0 0 0 0 0 0 0 0 ...
$ q0607_05: int 0 0 0 0 380000 0 0 0 0 0 ...
$ q0607_06: int 0 0 400000 0 0 80000 0 0 100000 0 ...
$ q0607_07: int 0 0 0 0 0 0 0 0 0 0 ...
$ q0607_08: int 0 0 60000 0 72000 15000 0 15000 38000 126000 ...
$ q0607_09: int 0 0 0 0 500000 0 180000 20000 0 0 ...
$ q0607_10: int 25000 20000 2460000 400000 5952000 345000 330000 335000 538000 926000 ...
$ q0608 : int 4 1 8 12 12 9 9 9 8 9 ...
$ q0609_1a: int 30000 0 350000 100000 850000 170000 150000 200000 150000 200000 ...
$ q0609_1b: int 1 0 2 3 6 3 3 3 2 3 ...
$ q0609_2a: int 10000 0 10000 20000 700000 90000 80000 100000 90000 150000 ...
$ q0609_2b: int 1 0 3 5 4 3 3 3 3 3 ...
$ q0609_3a: int 60000 40000 680000 400000 1000000 200000 250000 300000 180000 300000 ...
$ q0609_3b: int 2 1 3 4 2 3 3 3 3 3 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:29"

Mongolia HSES 2010 Manual (Version 1.0)

50

- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 253 253 253 253 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Enterprise Number (1-2-3)" "0603. Activity
Code" "0604. What % of this enterprise is owned by members" ...
- attr(*, "version")= int 8
NULL## 9 #### Other income #########'data.frame':
257393 obs. of 13 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 ...
$ q0701: int 1 2 2 2 2 2 2 2 2 2 ...
$ q0702_ic : int 1 NA NA NA NA NA NA NA NA NA ...
$ q0702_t : int 972000 NA NA NA NA NA NA NA NA NA ...
$ q0703_ic : int 2 NA NA NA NA NA NA NA NA NA ...
$ q0703_t : int 972000 NA NA NA NA NA NA NA NA NA ...
$ q0704_ic : int 4 NA NA NA NA NA NA NA NA NA ...
$ q0704_t : int 492000 NA NA NA NA NA NA NA NA NA ...
$ q0705_ic : int 0 NA NA NA NA NA NA NA NA NA ...
$ q0705_t : int NA NA NA NA NA NA NA NA NA NA ...
$ q0706_ic : int NA NA NA NA NA NA NA NA NA NA ...
$ q0706_t : int NA NA NA NA NA NA NA NA NA NA ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:31"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 251 251 253 251 253 251 253 251 ...
- attr(*, "val.labels")= chr "" "income_id" "q0701" "" ...
- attr(*, "var.labels")= chr"group(identif)" "Source Number" "07-01: Has anybody
received ..." "07_02: ID CODE 1" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 2..$ 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" ...
..$ q0701: Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"NULL## 10 #### Remittance #########'data.frame':
22265 obs. of 9 variables:$ identif: int 25 26 27 28 29 33 37 39 40 56 ...
$ ln: int 1 1 1 1 1 1 1 1 1 1 ...
$ ind_id : int 1 1 1 1 1 1 1 1 1 1 ...
$ q0709 : int 7 7 7 7 7 7 7 7 7 4 ...
$ q0710 : int 7 1 1 7 1 1 1 1 1 7 ...
$ q0711 : int 1 1 1 1 1 1 1 1 1 2 ...
$ q0712 : int 16000 16000 16000 16000 16000 16000 16000 16000 16000 80000 ...
$ q0713 : int 5 5 5 5 5 5 5 5 5 5 ...
$ q0714 : int 4 4 4 4 4 4 4 4 4 4 ...
- 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 252 251 251 251 251 251 253 251 251

Mongolia HSES 2010 Manual (Version 1.0)

51

- attr(*, "val.labels")= chr "" "" "" "q0709" ...
- attr(*, "var.labels")= chr "group(identif)" "Line Number" "0708 ID CODE" "0709. Who gave
the gift" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 5..$ q0709: Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "GOVERNMENT" "COMPANIES AND ORGANIZATIONS" "NGOs" "PARENTS,
CHILDREN, RELATIVES" ...
..$ q0710: Named int 1 2 3 4 5 6 7.. ..- attr(*, "names")= chr "HOUSEHOLD USE" "EDUCATION8 TUITION FEE" "MEDICAL TREATMENT""PURCHASE OF DWELLING" ...
..$ q0711: Named int 1 2 3 4 5 6 7 8.. ..- attr(*, "names")= chr "URBAN" "RURAL" "KOREA" "USA" ...
..$ q0713: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "YES, weekly" "YES, monthly" "YES, quarterly" "YES, annualy" ...
..$ q0714: Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "CASH" "BY ACCOUNT" "CASH REMITTANCE" "IN KIND" ...
NULL## 11 #### Energy #########'data.frame':
67188 obs. of 8 variables:$ identif : int 1 1 1 1 1 1 2 2 2 2 ...
$ energy_id: int 1 2 3 4 5 6 1 2 3 4 ...
$ q0836: int 2 1 2 1 2 2 2 1 2 2 ...
$ q0837: int NA 1 NA 1 NA NA NA 1 NA NA ...
$ q0838: num NA 16 NA 0.5 NA NA NA 10 NA NA ...
$ q0839: int NA 0 NA 0 NA NA NA 0 NA NA ...
$ q0840: int NA 0 NA 0 NA NA NA 0 NA NA ...
$ q0841: int NA 0 NA 0 NA NA NA 0 NA NA ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:33"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 251 251 255 253 253 253- attr(*, "val.labels")= chr "" "energy_id" "q0836" "q0837" ...
- attr(*, "var.labels")= chr "group(identif)" "Source Number" "0836. Have used the source?""0837. How do you mainly obtain [FUEL]?" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 3..$ energy_id: Named int 1 2 3 4 5 6.. ..- attr(*, "names")= chr "Electricity" "Firewood, m3" "Coal, ton" "Dung, ton" ...
..$ q0836: Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"..$ q0837: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Collect ourselves" "Purchase" "Collect and Purchase" "Other"
NULL## 12 #### Payment service #########'data.frame':
145574 obs. of 6 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ item : int 3 2 7 8 13 5 12 9 6 4 ...
$ q0842 : int 2 2 2 2 2 2 2 2 2 2 ...
$ q0843 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0844 : int NA NA NA NA NA NA NA NA NA NA ...
$ q0845 : int NA NA NA NA NA NA NA NA NA NA ...

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52

- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:34"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 251 253 253 253- attr(*, "val.labels")= chr "" "item" "q0842" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Service Number" "0842. Have bought or received
free.. during past 12 m?" "0843. Amount spend on purchases of .. during past month" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 2..$ 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" ...
..$ q0842: Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"NULL## 13 #### Durable #########'data.frame':
481514 obs. of 5 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ durable_id: int 1 2 3 4 5 6 7 8 9 10 ...
$ q0901: int 0 0 0 1 0 0 0 1 1 0 ...
$ q0902: int NA NA NA 480 NA NA NA 144 120 NA ...
$ q0903: num NA NA NA 18000 NA NA NA 3000 25000 NA ...
- 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 252 251 251 252 255- attr(*, "val.labels")= chr "" "durable_id" "" "" ...
- attr(*, "var.labels")= chr "group(identif)" "GOOD NUMBER" "0901 Number of durable good""0902 How long have you used this good" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 1..$ durable_id: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "Refrigerator" "Vacuum Cleaner" "Washing machine" "Sewing
machine" ...
NULL## 14 #### Non-Food #########'data.frame':
3964092 obs. of 6 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ item : int 20101 20102 20103 20104 20105 20106 20107 20108 20109 20110 ...
$ 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 NA NA NA NA NA NA NA NA NA NA ...
$ q1004 : int NA NA NA NA NA NA NA NA NA NA ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:49"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 253 253 253- attr(*, "val.labels")= chr "" "item" "q1001" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Non-food Item code" "1001. Have you bought or
received for the last 12 Ms" "1002. Purchased during the past month" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 2..$ item : Named int 20101 20102 20103 20104 20105 20106 20107 20108 20109 20110 ...

Mongolia HSES 2010 Manual (Version 1.0)

53.. ..- attr(*, "names")= chr "Men: Leather jacket, deel" "Men: Winter jacket, winter deel""Men: Overcoat" "Men: Other leather jacket, winter jacket, deel" ...
..$ q1001: Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"NULL## 15 #### Urban Diary #########'data.frame':
757720 obs. of 16 variables:$ identif: int 97 97 97 97 97 97 97 97 97 97 ...
$ item : int 10101 10102 10103 10104 10105 10106 10107 10108 10109 10110 ...
$ s11yn : int 1 1 2 1 2 2 2 2 1 2 ...
$ q1101_1: num 2 0.5 NA 3 NA NA NA NA 4.2 NA ...
$ q1101_2: num 2 0.5 NA 3 NA NA NA NA 4.2 NA ...
$ q1101_3: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1101_4: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1102_1: num 0 0 NA 5.1 NA NA NA NA 3.6 NA ...
$ q1102_2: num NA NA NA 5.1 NA NA NA NA 3.6 NA ...
$ q1102_3: num NA NA NA 0 NA NA NA NA 0 NA ...
$ q1102_4: num NA NA NA 0 NA NA NA NA 0 NA ...
$ q1103_1: num 2 2.3 NA 4.1 NA NA NA NA 3.6 NA ...
$ q1103_2: num 2 2.3 NA 4.1 NA NA NA NA 3.6 NA ...
$ q1103_3: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1103_4: num 0 0 NA 0 NA NA NA NA 0 NA ...
$ q1104 : num 500 1450 NA 700 NA NA NA NA 1900 NA ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:15"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 252 251 255 255 255 255 255 255 255 ...
- attr(*, "val.labels")= chr "" "item" "s11yn" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Food Item code" "Auxiliary 'Consumed? Y/N'""1101_1 First 10 - Total consumed" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 2..$ 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" ...
..$ s11yn: Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"NULL## 16 #### Rural Food 7 day #########'data.frame':
608408 obs. of 8 variables:$ identif: int 1 1 1 1 1 1 1 1 1 1 ...
$ item: int 10101 10102 10103 10104 10105 10106 10107 10108 10109 10110 ...
$ q1201 : int 2 2 2 1 2 2 2 2 1 2 ...
$ q1202 : num NA NA NA 10 NA NA NA NA 1 NA ...
$ q1203 : num NA NA NA 10 NA NA NA NA 1 NA ...
$ q1204 : num NA NA NA 580 NA NA NA NA 2000 NA ...
$ q1205 : num NA NA NA 0 NA NA NA NA 0 NA ...
$ q1206 : num NA NA NA 0 NA NA NA NA 0 NA ...
- 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 252 252 251 255 255 255 255 255

Mongolia HSES 2010 Manual (Version 1.0)

54

- attr(*, "val.labels")= chr "" "item" "q1201" "" ...
- attr(*, "var.labels")= chr "group(identif)" "Food Item code" "1201. Have you consumed foodduring the 7 days" "1202. Total consumed in the past 7 days" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 2..$ 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" ...
..$ q1201: Named int 1 2.. ..- attr(*, "names")= chr "YES" "NO"NULL## 17 #### Basicvars #########'data.frame':
11198 obs. of 13 variables:$ identif : int 1 2 3 4 5 6 7 8 9 10 ...
$ hhsize: int 4 7 2 5 4 5 4 5 4 5 ...
$ cluster : int 1 1 1 1 1 1 1 1 8 8 ...
$ aimag: int 1 1 1 1 1 1 1 1 1 1 ...
$ location : int 4 4 4 4 4 4 4 4 4 3 ...
$ 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 2 2 2 2 2 2 2 2 3 3 ...
$ quarter : int 1 1 1 1 1 1 1 1 1 1 ...
$ hhweight : num 47.4 47.4 47.4 47.4 47.4 ...
$ strata: int 3 3 3 3 3 3 3 3 3 3 ...
$ stratum : int 4 4 4 4 4 4 4 4 4 4 ...
$ aimagsoum: int 1 1 1 1 1 1 1 1 1 1 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "31 Jul 2013 08:27"- attr(*, "formats")= chr "%16.0g" "%16.0g" "%16.0g" "%16.0g" ...
- attr(*, "types")= int 252 251 252 251 251 251 251 251 251 255 ...
- attr(*, "val.labels")= chr "" "" "" "aimag" ...
- attr(*, "var.labels")= chr "group(identif)" "Household size" "Cluster" "Aimag" ...
- attr(*, "version")= int 8- attr(*, "label.table")=List of 4..$ aimag: Named int 1 2 3 4 5 6 7 8 9 10 ...
.. ..- attr(*, "names")= chr "Arhangai (01)" "Bayan-Ulgii (02)" "Bayanhongor (03)" "Bulgan(04)" ...
..$ location: Named int 1 2 3 4.. ..- attr(*, "names")= chr "Ulaanbaatar" "Aimagcenter" "Soumcenter" "Countryside"..$ urban: Named int 1 2.. ..- attr(*, "names")= chr "Urban" "Rural"..$ region : Named int 1 2 3 4 5.. ..- attr(*, "names")= chr "West" "Highlands" "Central" "East" ...
NULL

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55

5.2 Summary of each variable> for(j in 1:17){+ cat("##",j,"#### ",Rnames[j]," #########\n")+ print(summary(outfiles[[j]]))+ cat("\n\n")+ }## 1 #### Household #########
identif
q0008
Min.
:
1
Min.
: 1.000
1st Qu.: 2800
1st Qu.: 3.000
Median : 5600
Median : 4.000
Mean: 5600Mean: 3.793
3rd Qu.: 8399
3rd Qu.: 5.000
Max.
:11198Max.
:16.000
v1_yy
Min.
: 9.000
1st Qu.:10.000
Median :10.000
Mean: 9.978
3rd Qu.:10.000
Max.
:20.000

v1_resMin.
:1.000
1st Qu.:1.000
Median :2.000
Mean:1.591
3rd Qu.:2.000
Max.
:7.000v2_resMin.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.886
3rd Qu.:2.000
Max.
:7.000
NA's
:4288
v4_dd
Min.
: 0.00
1st Qu.:25.00
Median :30.00
Mean:25.62
3rd Qu.:30.00
Max.
:31.00
NA's
:4541
q0515
Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.906
3rd Qu.:2.000
Max.
:2.000v3_dd
Min.
: 0.00
1st Qu.:20.00
Median :21.00
Mean:20.79
3rd Qu.:21.00
Max.
:31.00
NA's
:4317
v4_mm
Min.
: 1.000
1st Qu.: 3.000
Median : 6.000
Mean: 6.423
3rd Qu.: 9.000
Max.
:12.000
NA's
:4543
q0516
Min.
:
0
1st Qu.:100
Median :500
Mean: 5568
3rd Qu.: 1000
Max.
:999000
NA's:10144q0602
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.102
3rd Qu.:1.000
Max.
:3.000q0601
Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.8343rd Qu.:2.000
Max.
:2.000hh_noMin.
: 1.00
1st Qu.: 3.00
Median : 6.00
Mean
: 5.96
3rd Qu.: 8.00
Max.
:13.00v1_dd
Min.
: 1.00
1st Qu.: 1.00
Median : 3.00
Mean
:10.55
3rd Qu.:22.00
Max.
:31.00v1_mm
Min.
: 1.000
1st Qu.: 4.000
Median : 6.000
Mean: 6.499
3rd Qu.: 9.000
Max.
:12.000

v2_dd
Min.
: 0.00
1st Qu.:10.00
Median :11.00
Mean:12.033rd Qu.:12.00
Max.
:31.00
NA's
:4283
v3_mm
Min.
: 1.000
1st Qu.: 3.000
Median : 6.000
Mean: 6.471
3rd Qu.: 9.000
Max.
:12.000
NA's
:4319
v4_yy
Min.
: 9.00
1st Qu.:10.00
Median :10.00
Mean: 9.97
3rd Qu.:10.00
Max.
:11.00
NA's
:4543
q0517
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.208
3rd Qu.:1.000
Max.
:2.000NA's:10144q0707
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.375
3rd Qu.:2.000
Max.
:2.000v2_mm
Min.
: 1.000
1st Qu.: 3.000
Median : 6.000
Mean: 6.469
3rd Qu.: 9.000
Max.
:12.000
NA's
:4288
v3_yy
Min.
: 9.000
1st Qu.:10.000
Median :10.000
Mean: 9.961
3rd Qu.:10.000
Max.
:11.000
NA's:4319
v4_resMin.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.035
3rd Qu.:1.000
Max.
:7.000
NA's
:4267
q0501
Min.
:1.000
1st Qu.:1.000
Median :2.000
Mean:1.625
3rd Qu.:2.000
Max.
:2.000v2_yy
Min.
: 9.000
1st Qu.:10.000
Median :10.000
Mean: 9.962
3rd Qu.:10.000
Max.
:11.000
NA's:4289
v3_resMin.
:1.00
1st Qu.:2.00
Median :2.00
Mean
:1.84
3rd Qu.:2.00
Max.
:6.00
NA's
:4319
q0507
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.0343rd Qu.:1.000
Max.
:2.000
NA's
:6994
q0518
Min.
:
0
1st Qu.:60
Median :240
Mean: 4360
3rd Qu.:800
Max.
:500000
NA's:10363
visitorMin.
: 0.000
1st Qu.: 0.000
Median : 0.000
Mean: 0.744
3rd Qu.: 0.000
Max.
:99.000

cluster2
Min.
:
1.0
1st Qu.: 328.2
Median : 660.0
Mean: 646.3
3rd Qu.: 967.0
Max.
:1248.0

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56

ndays
Min.
: 0.000
1st Qu.: 0.000
Median : 0.000
Mean: 4.693
3rd Qu.: 0.000
Max.
:270.000

NA's

:9336
q0801
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.147
3rd Qu.:1.000
Max.
:4.000q0802
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.072
3rd Qu.:1.000
Max.
:2.000q0830_1
Min.
: 0.000
1st Qu.: 0.100
Median : 0.500
Mean: 6.844
3rd Qu.: 1.500
Max.
:250.000

q0830_2
Min.
: 0.00
1st Qu.: 0.40
Median : 1.00
Mean
: 13.84
3rd Qu.: 3.50
Max.
:350.00

q0830_3
Min.
: 0.00
1st Qu.: 0.50
Median : 1.00
Mean
: 8.17
3rd Qu.: 3.00
Max.
:300.00

q0803
Min.
:1.000
1st Qu.:1.000
Median :2.000
Mean:2.235
3rd Qu.:3.000
Max.
:9.000q0804
Min.
:1.000
1st Qu.:1.000
Median :2.000
Mean:1.881
3rd Qu.:2.000
Max.
:9.000
NA's
:5211
q0805
q0806
q0807
q0808
q0809
Min.
:1.000Min.
:1.000Min.
:1.000
Min.
: 4.0
Min.
: 6.00
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.: 24.0
1st Qu.: 30.00
Median :2.000
Median :2.000
Median :1.000
Median : 30.0
Median : 40.00
Mean:2.283Mean:1.939Mean:1.353Mean: 37.3Mean: 45.17
3rd Qu.:3.000
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.: 44.0
3rd Qu.: 55.00
Max.
:5.000Max.
:4.000Max.
:4.000Max.
:500.0Max.
:500.00
NA's
:5211
NA's
:5211
NA's
:5211
NA's
:5211
NA's
:5211
q0810
q0811
q0812
q0813
q0814
Min.
: 4.00Min.
:3.000Min.
:1.000Min.
:1.000Min.
:1.00
1st Qu.:11.25
1st Qu.:4.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:1.00
Median :13.50
Median :5.000
Median :2.000
Median :2.000
Median :1.00
Mean:26.93Mean:4.939Mean:1.735Mean:1.734Mean:1.53
3rd Qu.:20.00
3rd Qu.:5.000
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:2.00
Max.
:99.00Max.
:8.000Max.
:2.000Max.
:2.000
Max.
:3.00
NA's
:11170
NA's
:6015
NA's
:6015
NA's
:6015
NA's
:6015
q0815
q0816
q0817
q0818
q0819
Min.
: 0.00Min.
: 0.00Min.
:1.000Min.
:1.000Min.
:1.000
1st Qu.: 8.00
1st Qu.: 4.00
1st Qu.:3.000
1st Qu.:4.000
1st Qu.:2.000
Median :20.00
Median :10.00
Median :3.000
Median :4.000
Median :2.000
Mean:32.93Mean:13.04Mean:2.942Mean:4.078Mean:1.911
3rd Qu.:40.00
3rd Qu.:20.00
3rd Qu.:3.000
3rd Qu.:5.000
3rd Qu.:2.000
Max.
:99.00Max.
:99.00Max.
:3.000Max.
:7.000Max.
:2.000
NA's
:412
NA's
:2998
q0820
q0821
q0822
q0823
q0824
Min.
:
99
Min.
:
0
Min.
:1.00
Min.
:1.000Min.
:1.000
1st Qu.:99
1st Qu.: 36250
1st Qu.:2.00
1st Qu.:1.000
1st Qu.:1.000
Median :99
Median :130000
Median :2.00
Median :1.000
Median :1.000
Mean: 25223
Mean:145773
Mean
:1.87
Mean
:1.627Mean:1.271
3rd Qu.:99
3rd Qu.:247500
3rd Qu.:2.00
3rd Qu.:2.000
3rd Qu.:2.000
Max.
:1000000
Max.
:600000
Max.
:5.00
Max.
:7.000Max.
:2.000
NA's
:270
NA's
:10928
q0825
q0826
q0827
q0828
q0829
Min.
:1.000Min.
:1.000
Min.
:1.00
Min.
:1.000Min.
:1.000
1st Qu.:3.000
1st Qu.:1.000
1st Qu.:2.00
1st Qu.:3.000
1st Qu.:2.000
Median :3.000
Median :1.000
Median :2.00
Median :3.000
Median :2.000
Mean:3.622Mean:1.465
Mean
:2.32
Mean
:2.765Mean:2.292
3rd Qu.:5.000
3rd Qu.:2.000
3rd Qu.:3.00
3rd Qu.:3.000
3rd Qu.:2.000
Max.
:8.000Max.
:2.000
Max.
:4.00
Max.
:4.000Max.
:4.000q0830_4
Min.
: 0.000
1st Qu.: 0.300
Median : 0.800
Mean: 8.104
3rd Qu.: 3.000
Max.
:300.000

Mongolia HSES 2010 Manual (Version 1.0)

57

NA's
:17
NA's
:10
NA's
:2
NA's
:2
q0830_5
q0831
q0832_aq0832_bMin.
: 0.000
Min.
:1.000
Min.
:
0.0
Min.
:
0
1st Qu.: 0.020
1st Qu.:1.000
1st Qu.:0.0
1st Qu.:0
Median : 0.250
Median :2.000
Median :575.0Median :0
Mean: 2.482
Mean:1.578
Mean
:
633.8
Mean
:
1690
3rd Qu.: 0.700
3rd Qu.:2.000
3rd Qu.:700.0
3rd Qu.:700
Max.
:300.000
Max.
:2.000Max.
:142211.0
Max.
:2000000
NA's
:13
NA's
:6465
NA's
:6465
q0833
q0834
q0835_1
q0835_2
q0835_3
Min.
:1.000Min.
:1.000Min.
:1.000Min.
:1.000Min.
:1.000
1st Qu.:2.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:1.000
Median :2.000
Median :2.000
Median :2.000
Median :2.000
Median :2.000
Mean:1.798Mean:1.926Mean:1.623Mean:1.604Mean:1.658
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:2.000
Max.
:2.000Max.
:7.000Max.
:2.000Max.
:2.000Max.
:2.000
NA's
:8938
NA's
:8938
NA's
:8938
NA's
:8938
q0835_4
q0835_5
Min.
:1.00
Min.
:1.000
1st Qu.:1.00
1st Qu.:2.000
Median :2.00
Median :2.000
Mean
:1.73
Mean
:1.945
3rd Qu.:2.00
3rd Qu.:2.000
Max.
:2.00
Max.
:2.000
NA's
:8938
NA's
:8938

## 2 #### Individual #########
identif
ind_id
Min.
:
1
Min.
: 1.000
1st Qu.: 2729
1st Qu.: 1.000
Median : 5509
Median : 3.000
Mean: 5536Mean: 2.807
3rd Qu.: 8298
3rd Qu.: 4.000
Max.
:11198Max.
:16.000

q0108
Min.
: 1.00
1st Qu.: 1.00
Median :98.00
Mean:59.25
3rd Qu.:99.00
Max.
:99.00newheadq0103
Min.
:0.0000
Min.
:1.000
1st Qu.:0.0000
1st Qu.:1.000
Median :0.0000
Median :2.000
Mean:0.2637
Mean:1.511
3rd Qu.:1.0000
3rd Qu.:2.000
Max.
:1.0000
Max.
:2.000NA's:885
q0105yq0105m
q0106
q0107
Min.
: 0.0
Min.
: 0.00Min.
:1.000Min.
: 1.000
1st Qu.:13.0
1st Qu.: 3.00
1st Qu.:1.000
1st Qu.: 1.000
Median :25.0
Median : 5.00
Median :1.000
Median : 2.000
Mean
:28.1
Mean
: 5.58Mean:3.149Mean: 3.224
3rd Qu.:41.0
3rd Qu.: 8.00
3rd Qu.:6.000
3rd Qu.: 2.000
Max.
:99.0
Max.
:11.00Max.
:6.000Max.
:98.000
NA's:42549NA's:11770NA's:26268q0109
q0110a
q0110
q0111
Min.
: 1.00Min.
: 0.000Min.
: 0.0000
Min.
:1.00
1st Qu.: 2.00
1st Qu.: 0.000
1st Qu.: 0.0000
1st Qu.:1.00
Median :98.00
Median : 0.000
Median : 0.0000
Median :1.00
Mean:50.49Mean: 2.631Mean: 0.8705
Mean:1.02
3rd Qu.:98.00
3rd Qu.: 0.000
3rd Qu.: 0.0000
3rd Qu.:1.00
Max.
:99.00Max.
:31.000Max.
:12.0000
Max.
:2.00

q0201
Min.
:1.000
1st Qu.:1.000
Median :1.000

q0202
Min.
:1.000
1st Qu.:1.000
Median :2.000

q0104
Min.
:1910
1st Qu.:1969
Median :1985
Mean
:1982
3rd Qu.:1996
Max.
:2010

q0102
Min.
: 1.000
1st Qu.: 1.000
Median : 3.000
Mean: 2.737
3rd Qu.: 3.000
Max.
:12.000q0203
Min.
: 1.000
1st Qu.: 1.000
Median : 2.000

q0204
Min.
: 1.000
1st Qu.: 2.000
Median : 4.000

Mongolia HSES 2010 Manual (Version 1.0)

q0205
Min.
:1.00
1st Qu.:1.00
Median :1.00

58

Mean
:1.113Mean:1.549Mean: 1.731Mean: 3.568
Mean:1.34
3rd Qu.:1.000
3rd Qu.:2.000
3rd Qu.: 2.000
3rd Qu.: 4.000
3rd Qu.:2.00
Max.
:2.000Max.
:2.000Max.
:13.000Max.
:10.000
Max.
:3.00
NA's
:885
NA's
:5703
NA's
:22689
NA's
:5703
NA's
:32406
q0206
q0207
q0208
q0209tq0209gMin.
:1.000
Min.
:1.00
Min.
: 1.00Min.
:1.000Min.
: 0.00
1st Qu.:1.000
1st Qu.:1.00
1st Qu.: 1.00
1st Qu.:1.000
1st Qu.: 20.00
Median :4.000
Median :2.00
Median : 5.00
Median :1.000
Median : 40.00
Mean:2.851
Mean
:1.51
Mean
: 4.89Mean:1.503Mean: 49.44
3rd Qu.:4.000
3rd Qu.:2.00
3rd Qu.: 7.00
3rd Qu.:2.000
3rd Qu.: 80.00
Max.
:4.000
Max.
:2.00
Max.
:13.00Max.
:4.000Max.
:120.00
NA's
:5703
NA's
:39724NA's:41590NA's:31098NA's:31098
q0210
q0211
q0212
q0213
q0214_1
Min.
:1.000Min.
:1.000Min.
:1.000
Min.
:1.00
Min.
:
0
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:1.00
1st Qu.:0
Median :1.000
Median :2.000
Median :1.000
Median :2.00
Median :0
Mean:1.094Mean:1.874Mean:1.739
Mean
:1.71
Mean
: 23972
3rd Qu.:1.000
3rd Qu.:3.000
3rd Qu.:3.000
3rd Qu.:2.00
3rd Qu.:0
Max.
:3.000Max.
:4.000Max.
:5.000
Max.
:2.00
Max.
:2160000
NA's:31098NA's:31098NA's:31098NA's:31098NA's:31099q0214_2
q0214_3
q0214_4
q0214_5
Min.
:
0
Min.
:
0
Min.
:
0
Min.
:
0
1st Qu.:0
1st Qu.:0
1st Qu.: 25000
1st Qu.:0
Median :0Median :0Median : 35000
Median :0
Mean: 169956
Mean
:
21274
Mean
: 44281
Mean: 12804
3rd Qu.: 70000
3rd Qu.:0
3rd Qu.: 50000
3rd Qu.: 18000
Max.
:11232000
Max.
:10000000
Max.
:1000000
Max.
:800000
NA's:31099NA's:31101NA's:31098NA's:31098q0214_6
q0214_7
q0214_8
q0301
Min.
:
0
Min.
:
0
Min.
:
0
Min.
:1.000
1st Qu.:0
1st Qu.:0
1st Qu.:43000
1st Qu.:1.000
Median :0Median :0Median :74000
Median :2.000
Mean: 23175
Mean: 24520Mean: 319934
Mean:1.597
3rd Qu.: 20000
3rd Qu.: 15000
3rd Qu.: 310000
3rd Qu.:2.000
Max.
:1400000
Max.
:2000000
Max.
:13432000
Max.
:2.000NA's:31099NA's:31099NA's:31098
NA's
:885
q0302
q0303
q0304aq0304bq0305
Min.
: 1.000
Min.
:1.000
Min.
:1.00
Min.
:0.00
Min.
:1.00
1st Qu.: 1.000
1st Qu.:2.000
1st Qu.:1.00
1st Qu.:0.00
1st Qu.:1.00
Median : 2.000
Median :2.000
Median :3.00
Median :0.00
Median :1.00
Mean: 1.732
Mean:1.929
Mean
:3.19
Mean
:0.32
Mean
:1.22
3rd Qu.: 2.000
3rd Qu.:2.000
3rd Qu.:5.00
3rd Qu.:0.00
3rd Qu.:1.00
Max.
:13.000
Max.
:2.000
Max.
:6.00
Max.
:6.00
Max.
:2.00
NA's
:18023
NA's
:885
NA's
:40354NA's:40354NA's:40354
q0306
q0307
q0308
q309_1Min.
: 1.00
Min.
:1.00
Min.
:1.00
Min.
:
0
1st Qu.: 1.00
1st Qu.:2.00
1st Qu.:1.00
1st Qu.:0
Median : 1.00
Median :2.00
Median :1.00
Median :9000
Mean: 4.42
Mean
:2.32
Mean
:1.27
Mean
:
45801
3rd Qu.:10.00
3rd Qu.:3.00
3rd Qu.:1.00
3rd Qu.:30000
Max.
:12.00
Max.
:6.00
Max.
:6.00
Max.
:10000000
NA's:42705NA's:41004NA's:41004NA's:41004q309_2
q0310
q0311
q0312
q0313
Min.
:
0
Min.
:1.00
Min.
:
150
Min.
:1.000Min.
:1.00
1st Qu.:0
1st Qu.:2.00
1st Qu.: 3000
1st Qu.:2.000
1st Qu.:2.00
Median :0Median :2.00
Median : 7000
Median :2.000
Median :2.00

Mongolia HSES 2010 Manual (Version 1.0)

59

Mean
: 15261
Mean
:1.91
Mean
: 16049
Mean:1.903Mean:2.21
3rd Qu.: 5000
3rd Qu.:2.00
3rd Qu.: 15000
3rd Qu.:2.000
3rd Qu.:3.00
Max.
:6000000
Max.
:2.00
Max.
:690000
Max.
:2.000
Max.
:6.00
NA's
:41004
NA's
:885
NA's
:39531
NA's
:885
NA's
:39252
q0314
q0315
q0401
q0402
Min.
:
0
Min.
:
0
Min.
:1.00
Min.
:1.000
1st Qu.:0
1st Qu.:0
1st Qu.:1.00
1st Qu.:1.000
Median : 20000
Median : 10000
Median :1.00
Median :2.000
Mean: 91906
Mean: 39717
Mean
:1.18
Mean
:1.519
3rd Qu.: 95000
3rd Qu.: 40000
3rd Qu.:1.00
3rd Qu.:2.000
Max.
:5000000
Max.
:5000000
Max.
:2.00
Max.
:2.000NA's:39252NA's:39252
NA's
:885
NA's
:8511
q0403
q0404
q0405
q0406
q0407
Min.
: 1.000
Min.
:1.000Min.
:1.000Min.
:1.000Min.
:1.00
1st Qu.: 1.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:2.000
1st Qu.:4.00
Median : 2.000
Median :2.000
Median :1.000
Median :2.000
Median :6.00
Mean: 1.749
Mean:1.563Mean:2.179Mean:1.942Mean:5.07
3rd Qu.: 2.000
3rd Qu.:2.000
3rd Qu.:3.000
3rd Qu.:2.000
3rd Qu.:6.00
Max.
:13.000
Max.
:2.000Max.
:5.000Max.
:2.000
Max.
:7.00
NA's
:25269
NA's
:8511
NA's
:28138NA's:23728NA's:42207
q0408
q0409
q0410
q0411cq0412cMin.
:1.000Min.
:1.000
Min.
:1.00
Min.
:111.0Min.
: 111
1st Qu.:2.000
1st Qu.:1.000
1st Qu.:2.00
1st Qu.:511.0
1st Qu.: 144
Median :2.000
Median :1.000
Median :2.00
Median :612.0
Median :4210
Mean:1.961Mean:2.477
Mean
:1.91
Mean
:563.7Mean:3677
3rd Qu.:2.000
3rd Qu.:3.000
3rd Qu.:2.00
3rd Qu.:712.0
3rd Qu.:6411
Max.
:2.000Max.
:8.000
Max.
:2.00
Max.
:997.0
Max.
:9900
NA's
:24876NA's:25601NA's:37735NA's:26990NA's:26990
q0413
q0414
q0415
q0416aMin.
: 1.00Min.
:1.000Min.
:1.000Min.
:
0
1st Qu.: 40.00
1st Qu.:7.000
1st Qu.:1.000
1st Qu.: 150000
Median : 48.00
Median :9.000
Median :1.000
Median : 220000
Mean: 50.25
Mean:7.324Mean:1.467Mean: 244919
3rd Qu.: 60.00
3rd Qu.:9.000
3rd Qu.:2.000
3rd Qu.: 300000
Max.
:130.00
Max.
:9.000Max.
:2.000Max.
:4200000NA's:26990NA's:26990NA's:26990NA's:34626q0416bq0416cMin.
: 10000
Min.
:0
1st Qu.: 1680000
1st Qu.:0
Median : 2500000
Median :0
Mean: 2834910
Mean
:
45249
3rd Qu.: 3600000
3rd Qu.:0
Max.
:30000000
Max.
:10000000
NA's:34626NA's:34625## 3 #### Llivestock #########
identif
ani_idq0502_1
Min.
:
1
Min.
:1.000Min.
:
0.00
1st Qu.: 1840
1st Qu.:2.000
1st Qu.:6.00
Median : 4894
Median :4.000
Median : 19.00
Mean: 5043Mean:3.169Mean: 48.79
3rd Qu.: 7319
3rd Qu.:5.000
3rd Qu.: 53.00
Max.
:11137Max.
:6.000Max.
:2950.00
q0502_3

q0503

q0504

q0502_2
Min.
: 0.00
1st Qu.: 2.00
Median : 7.00
Mean
: 20.29
3rd Qu.: 20.00
Max.
:800.00
NA's
:244
q0505

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60

Min.
: 0.00
1st Qu.: 0.00
Median : 3.00
Mean
: 10.03
3rd Qu.: 10.00
Max.
:485.00
NA's
:243

Min.
: 0.000
1st Qu.: 1.000
Median : 2.000
Mean: 4.335
3rd Qu.: 6.000
Max.
:52.000
NA's
:2

Min.
: 0.000
1st Qu.: 0.000
Median : 0.000
Mean: 4.375
3rd Qu.: 1.000
Max.
:900.000
NA's
:3

Min.
:
0
1st Qu.: 240000
Median : 400000
Mean: 761791
3rd Qu.: 800000
Max.
:64500000
NA's
:9656

## 4 #### Llivestock Expenditure #########
identif
exp_id
q0506
Min.
:
1
Min.
:1.000Min.
:300
1st Qu.: 1597
1st Qu.:1.000
1st Qu.:25000
Median : 4303
Median :2.000
Median :60000
Mean: 4800Mean:2.189Mean: 169846
3rd Qu.: 7091
3rd Qu.:3.000
3rd Qu.: 200000
Max.
:11137Max.
:5.000Max.
:15000000## 5 #### Product #########
identif
byprod_id
Min.
:
1
Min.
:1.0
1st Qu.: 1845
1st Qu.:2.0
Median : 4575
Median :3.5
Mean
: 5042Mean:3.5
3rd Qu.: 7342
3rd Qu.:5.0
Max.
:11137
Max.
:6.0
q0511
Min.
:
0.00
1st Qu.:1.00
Median : 12.00
Mean: 81.75
3rd Qu.: 31.00
Max.
:34349.00
NA's:13149

q0508
q0509
q0510
Min.
:0.000
Min.
:
0.2
Min.
:
0.0
1st Qu.:1.000
1st Qu.:12.0
1st Qu.:0.0
Median :1.000
Median :30.0Median :0.0
Mean:1.492Mean: 336.7
Mean: 236.5
3rd Qu.:2.000
3rd Qu.: 195.0
3rd Qu.:50.0
Max.
:2.000Max.
:36149.0
Max.
:22000.0
NA's
:1144
NA's
:13148NA's:13148
q0512
q0513
q0514
Min.
:
0
Min.
:
0.00
Min.
:
0
1st Qu.:45000
1st Qu.:0.00
1st Qu.: 200000
Median : 118000
Median :0.00
Median : 350000
Mean: 450060
Mean: 14.34
Mean: 453687
3rd Qu.: 495000
3rd Qu.:0.00
3rd Qu.: 600000
Max.
:20609400
Max.
:6400.00
Max.
:2900000NA's:16129NA's:13148NA's:25352## 6 #### Crop
identifMin.
: 58
1st Qu.: 2418
Median : 4530
Mean
: 5122
3rd Qu.: 7348
Max.
:11077
q0522
Min.
:
0.00
1st Qu.:0.00
Median :0.00
Mean: 96.01
3rd Qu.:0.00
Max.
:17500.00#########
crop_idMin.
: 1.000
1st Qu.: 1.000
Median : 3.000
Mean: 3.937
3rd Qu.: 6.000
Max.
:11.000

q0519
Min.
:1
1st Qu.:1
Median :1
Mean:1
3rd Qu.:1
Max.
:1q0523qMin.
:
0
1st Qu.:0
Median :0
Mean: 11033rd Qu.:50
Max.
:300000

q0520
Min.
:
1.0
1st Qu.:20.0
Median :100.0
Mean: 1906.1
3rd Qu.:432.5
Max.
:350000.0

q0523tMin.
:
0
1st Qu.:
85000
Median : 300000
Mean: 1361095
3rd Qu.: 900000
Max.
:75000000
NA's
:1625

Mongolia HSES 2010 Manual (Version 1.0)

q0521
Min.
:
0.0
1st Qu.: 10.0
Median : 50.0
Mean
: 152.7
3rd Qu.: 160.0
Max.
:5500.0

61## 7 #### Agriultural Expenditure #########
identif
exp_id
q0524
Min.
: 58
Min.
: 1.00Min.
:
0
1st Qu.: 2907
1st Qu.: 3.75
1st Qu.:0
Median : 4620
Median : 6.50
Median :0
Mean: 5184Mean: 6.50Mean:
37573
3rd Qu.: 7425
3rd Qu.: 9.25
3rd Qu.:0Max.
:11077Max.
:12.00Max.
:30000000## 8 #### Enterprise #########
identifenq0603c
q0604
q0605
Min.
: 56
Min.
:1.000
Min.
: 113
Min.
: 1.00Min.
:1.000
1st Qu.: 2609
1st Qu.:1.000
1st Qu.:2396
1st Qu.:100.00
1st Qu.:1.000
Median : 5247
Median :1.000
Median :4721
Median :100.00
Median :1.000
Mean: 5322Mean:1.096
Mean
:4275
Mean
: 97.74
Mean:1.262
3rd Qu.: 8063
3rd Qu.:1.000
3rd Qu.:4922
3rd Qu.:100.00
3rd Qu.:1.000
Max.
:11190Max.
:3.000
Max.
:9820
Max.
:100.00
Max.
:5.000
NA's
:4
q0606
q0607_01
q0607_02
q0607_03
Min.
: 0.0000
Min.
:
0
Min.
:
0
Min.
:
0
1st Qu.: 0.0000
1st Qu.:0
1st Qu.:0
1st Qu.:0
Median : 0.0000
Median :0Median :0Median :0Mean: 0.5076
Mean: 5315534
Mean:
741727
Mean:
932921
3rd Qu.: 0.0000
3rd Qu.: 3000000
3rd Qu.:0
3rd Qu.:500000Max.
:50.0000
Max.
:776000000
Max.
:215640000
Max.
:276000000
q0607_04
Min.
:0
1st Qu.:0
Median :0
Mean: 105381
3rd Qu.:0Max.
:35000000

q0607_05
Min.
:0
1st Qu.:0
Median :0
Mean: 340168
3rd Qu.:0Max.
:28800000

q0607_06
Min.
:0
1st Qu.:0
Median :0
Mean: 118640
3rd Qu.:0Max.
:11000000

q0607_07
Min.
:0
1st Qu.:0
Median :
0
Mean
:
51618
3rd Qu.:0
Max.
:20000000

q0607_08
Min.
:0
1st Qu.:0
Median :0
Mean: 152387
3rd Qu.: 72000
Max.
:25000000

q0607_09
Min.
:0.00e+00
1st Qu.:0.00e+00
Median :5.40e+04
Mean:1.17e+06
3rd Qu.:5.56e+05
Max.
:1.54e+08

q0607_10
Min.
:0.000e+00
1st Qu.:4.270e+05
Median :2.262e+06
Mean:8.928e+06
3rd Qu.:7.570e+06
Max.
:1.000e+09

q0608
Min.
: 1.000
1st Qu.: 6.000
Median :12.000
Mean: 9.355
3rd Qu.:12.000
Max.
:12.000

q0609_1aMin.
:0
1st Qu.: 170000
Median : 400000
Mean: 1979871
3rd Qu.: 1087500
Max.
:500000000
NA's:1q0609_3aMin.
:0
1st Qu.: 300000
Median : 650000

q0609_1bMin.
: 0.000
1st Qu.: 2.000
Median : 4.000
Mean: 3.515
3rd Qu.: 5.000
Max.
:12.000NA's:1q0609_3bMin.
: 0.000
1st Qu.: 2.000
Median : 3.000

q0609_2aMin.
:0
1st Qu.:90000
Median :250000Mean: 1447878
3rd Qu.:743500Max.
:400000000
NA's:6q0609_2bMin.
: 0.000
1st Qu.: 2.000
Median : 3.000
Mean: 2.687
3rd Qu.: 4.000
Max.
:10.000
NA's:6

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62

Mean
: 2858549
3rd Qu.: 1600000
Max.
:900000000
NA's
:4

Mean
: 3.121
3rd Qu.: 4.000
Max.
:12.000
NA's:4## 9 #### Other income #########
identif
income_id
q0701
Min.
:
1
Min.
: 1
Min.
:0.000
1st Qu.: 2802
1st Qu.: 6
1st Qu.:2.000
Median : 5600
Median :12
Median :2.000
Mean: 5600
Mean
:12
Mean
:1.931
3rd Qu.: 8398
3rd Qu.:18
3rd Qu.:2.000
Max.
:11198
Max.
:23
Max.
:2.000q0703_icMin.
: 0.00
1st Qu.: 0.00
Median : 1.00
Mean
: 1.66
3rd Qu.: 4.00
Max.
:12.00NA's:240662q0705_icMin.
: 0.00
1st Qu.: 0.00
Median : 4.00
Mean
: 2.55
3rd Qu.: 4.00
Max.
:14.00NA's:253659q0703_t
Min.
:2000
1st Qu.:
70000
Median :70000
Mean: 204008
3rd Qu.: 120000
Max.
:19044000
NA's:248992q0705_t
Min.
:1000
1st Qu.: 70000
Median : 70000
Mean: 79900
3rd Qu.: 80000
Max.
:1070000NA's:255325q0702_ic
q0702_tMin.
: 1.00Min.
:
2000
1st Qu.: 1.00
1st Qu.:
70000
Median : 2.00
Median : 100000
Mean: 2.36Mean: 421789
3rd Qu.: 3.00
3rd Qu.: 520000
Max.
:12.00Max.
:60000000
NA's:239522NA's:239522q0704_ic
q0704_tMin.
: 0.00Min.
:
2100
1st Qu.: 0.00
1st Qu.: 70000
Median : 3.00
Median : 70000
Mean: 2.11Mean: 81744
3rd Qu.: 3.00
3rd Qu.: 96000
Max.
:14.00Max.
:1560000NA's:249584
NA's:253344q0706_ic
q0706_tMin.
: 0.00Min.
:
3000
1st Qu.: 0.00
1st Qu.: 70000
Median : 0.00
Median : 70000
Mean: 2.68Mean: 112581
3rd Qu.: 5.00
3rd Qu.: 136000
Max.
:99.00Max.
:1400000NA's:255563NA's:256494## 10 #### Remittance #########
identifln
ind_id
Min.
: 25
Min.
:1.000Min.
: 1.000
1st Qu.: 4331
1st Qu.:1.000
1st Qu.: 1.000
Median : 6865
Median :2.000
Median : 2.000
Mean: 6552Mean:2.547Mean: 2.583
3rd Qu.: 8989
3rd Qu.:4.000
3rd Qu.: 4.000
Max.
:11185Max.
:6.000Max.
:98.000
q0711
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.178
3rd Qu.:1.000
Max.
:8.000
NA's
:4

q0712
Min.
:
2500
1st Qu.:
70000
Median :70000
Mean: 186967
3rd Qu.: 100000
Max.
:25000000
NA's:4## 11 #### Energy #########
identifenergy_id
Min.
:
1
Min.
:1.0
1st Qu.: 2800
1st Qu.:2.0

q0709
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.5343rd Qu.:1.000
Max.
:7.000
NA's
:3
q0713
q0714
Min.
:1.000Min.
:1.00
1st Qu.:5.000
1st Qu.:1.00
Median :5.000
Median :1.00
Mean:4.758Mean:1.28
3rd Qu.:5.000
3rd Qu.:1.00
Max.
:5.000
Max.
:5.00
NA's
:4
NA's
:4

q0836
Min.
:1.000
1st Qu.:1.000

q0837
Min.
:1.00
1st Qu.:1.00

Mongolia HSES 2010 Manual (Version 1.0)

q0710
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.2143rd Qu.:1.000
Max.
:7.000
NA's
:3

q0838
Min.
: 0.00
1st Qu.: 2.00

63Median : 5600
Mean
: 5600
3rd Qu.: 8399
Max.
:11198Median :3.5
Mean
:3.5
3rd Qu.:5.0
Max.
:6.0

q0839
Min.
:
0
1st Qu.:0
Median :0
Mean: 7270
3rd Qu.: 10000
Max.
:450000
NA's:42288

q0840
Min.
:
0
1st Qu.: 30000
Median : 85000
Mean: 110033
3rd Qu.: 160000
Max.
:2000000NA's:42245## 12 #### Payment service
identif
item
Min.
:
1
Min.
: 1
1st Qu.: 2800
1st Qu.: 4Median : 5600
Median : 7
Mean: 5600Mean: 7
3rd Qu.: 8399
3rd Qu.:10Max.
:11198Max.
:13Median :2.000
Mean:1.629
3rd Qu.:2.000
Max.
:2.000Median :2.00
Mean
:1.72
3rd Qu.:2.00
Max.
:4.00
NA's
:51029Median : 4.00
Mean
: 5.12
3rd Qu.: 6.00
Max.
:252.00
NA's:51001

q0841
Min.
:
0
1st Qu.:0
Median :0
Mean: 3961
3rd Qu.:0Max.
:560000
NA's:42242#########
q0842
Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.847
3rd Qu.:2.000
Max.
:2.000

q0843
Min.
:
0
1st Qu.:1200
Median :
2352
Mean
:
4887
3rd Qu.:4000
Max.
:2500000NA's:123359

q0844
Min.
:
0
1st Qu.:15120
Median :
30000
Mean
:
56847
3rd Qu.:50436
Max.
:34000000
NA's:123359

q0845
Min.
:
0.0
1st Qu.:0.0
Median :0.0
Mean: 720.6
3rd Qu.:0.0
Max.
:600000.0
NA's:123359## 13 #### Durable #########
identifdurable_id
q0901
Min.
:
1
Min.
: 1
Min.
: 0.0000
1st Qu.: 2800
1st Qu.:11
1st Qu.: 0.0000
Median : 5600
Median :22
Median : 0.0000
Mean: 5600
Mean
:22
Mean
: 0.3825
3rd Qu.: 8399
3rd Qu.:33
3rd Qu.: 1.0000
Max.
:11198
Max.
:43
Max.
:21.0000

q0902
Min.
: 0.0
1st Qu.: 36.0
Median : 72.0
Mean
:115.5
3rd Qu.:144.0
Max.
:999.0NA's:339925

q0903
Min.
:
555
1st Qu.:
30000
Median :70000
Mean: 1136829
3rd Qu.: 220000
Max.
:200000000
NA's:339926## 14 #### Non-Food #########
identif
item
Min.
:
1
Min.
:20101q1001:1.000

Min.

q1002
:

Min.

Mongolia HSES 2010 Manual (Version 1.0)064

1st Qu.: 2800
Median : 5600
Mean
: 5600
3rd Qu.: 8399
Max.
:11198
q1003
Min.
:
0
1st Qu.:6000
Median : 15000
Mean: 58573
3rd Qu.: 40000
Max.
:60000000
NA's:3430233

1st Qu.:20904
Median :21504
Mean:21579
3rd Qu.:22104
Max.
:24305

1st Qu.:2.000
Median :2.000
Mean:1.865
3rd Qu.:2.000
Max.
:2.000

1st Qu.:0
Median :
0
Mean
:
4105
3rd Qu.:800
Max.
:25000000
NA's:3430232

q1004
Min.
:
0
1st Qu.:0
Median :
0
Mean
:
2295
3rd Qu.:0
Max.
:25000000
NA's:3430240## 15 #### Urban Diary #########
identif
item
s11yn
Min.
: 97
Min.
:10101Min.
:1.000
1st Qu.: 2801
1st Qu.:10216
1st Qu.:2.000
Median : 5602
Median :10603
Median :2.000
Mean: 6006
Mean:10595Mean:1.778
3rd Qu.: 8403
3rd Qu.:10811
3rd Qu.:2.000
Max.
:11198Max.
:11305Max.
:2.000q1101_3
Min.
: 0.0
1st Qu.: 0.0
Median : 0.0
Mean
: 0.4
3rd Qu.: 0.0
Max.
:6500.0
NA's:622970q1102_3
Min.
: 0.0
1st Qu.: 0.0
Median : 0.0
Mean
: 0.4
3rd Qu.: 0.0Max.
:3150.0NA's:624915q1103_3
Min.
: 0.0
1st Qu.: 0.0
Median : 0.0
Mean
: 0.4
3rd Qu.: 0.0Max.
:3600.0
NA's:626630q1101_4
Min.
:0e+00
1st Qu.:0e+00
Median :0e+00
Mean:1e-01
3rd Qu.:0e+00
Max.
:1e+03NA's:622972q1102_4
Min.
:
0.0
1st Qu.:0.0
Median :
0.0
Mean
:
0.1
3rd Qu.:0.0
Max.
:3100.0NA's:624913q1103_4
Min.
:0e+00
1st Qu.:0e+00
Median :0e+00
Mean:1e-01
3rd Qu.:0e+00
Max.
:1e+03NA's:626633

q1101_1
q1101_2
Min.
:
0.0
Min.
:
0.0
1st Qu.:0.2
1st Qu.:0.5
Median :1.0
Median :1.5
Mean: 28.3Mean: 35.0
3rd Qu.:3.8
3rd Qu.:5.0
Max.
:6500.0Max.
:4400.0
NA's:588868
NA's:622969
q1102_1
q1102_2
Min.
:
0.0
Min.
:
0.0
1st Qu.:0.2
1st Qu.:0.5
Median :1.0
Median :1.5
Mean: 28.0Mean: 35.0
3rd Qu.:3.7
3rd Qu.:5.0
Max.
:4000.0
Max.
:4000.0
NA's:588875
NA's:624902q1103_1
q1103_2
Min.
:
0.0
Min.
:
0.0
1st Qu.:0.2
1st Qu.:0.5
Median :1.0
Median :1.5
Mean: 28.3Mean: 35.9
3rd Qu.:3.7
3rd Qu.:5.2
Max.
:3600.0Max.
:3000.0
NA's:588881NA's:626631
q1104
Min.
:
0
1st Qu.:600
Median : 1300
Mean
: 1800
3rd Qu.: 2500
Max.
:120000
NA's:589341## 16 #### Rural Food 7 day #########
identif
item
q1201
Min.
:
1
Min.
:10101Min.
:1.000
1st Qu.: 1846
1st Qu.:10216
1st Qu.:2.000
Median : 4649
Median :10603
Median :2.000

q1202
Min.
:
1st Qu.:Median :

0.0
0.5
2.0

Mongolia HSES 2010 Manual (Version 1.0)

q1203
Min.
:
1st Qu.:Median :

0.0
0.0
1.0

65

Mean
: 50933rd Qu.: 7450
Max.
:10248
q1204
Min.
:
0.0
1st Qu.: 12.8
Median : 900.0
Mean: 1377.4
3rd Qu.: 1800.0
Max.
:90000.0NA's:553726

Mean:10595
3rd Qu.:10811
Max.
:11305Mean:1.878
3rd Qu.:2.000
Max.
:2.000

q1205
Min.
:
0
1st Qu.:0
Median :0
Mean:
1
3rd Qu.:
0
Max.
:4000
NA's
:534439

Mean: 35.6
3rd Qu.:8.0
Max.
:7000.0NA's:534432

Mean: 33.9
3rd Qu.:6.0
Max.
:7000.0NA's:534436

q1206
Min.
: 0.0
1st Qu.: 0.0
Median : 0.0
Mean
: 0.7
3rd Qu.: 0.0
Max.
:600.0NA's:534434## 17 #### Basicvars #########
identif
hhsizecluster
Min.
:
1
Min.
: 1.000
Min.
:
1.0
1st Qu.: 2800
1st Qu.: 3.000
1st Qu.: 328.2
Median : 5600
Median : 4.000
Median : 659.0
Mean: 5600Mean: 3.793Mean: 646.3
3rd Qu.: 8399
3rd Qu.: 5.000
3rd Qu.: 967.0
Max.
:11198Max.
:16.000
Max.
:1248.0
urban
regionmonthMin.
:1.000Min.
:1.000Min.
: 1.000
1st Qu.:1.000
1st Qu.:2.000
1st Qu.: 3.000
Median :1.000
Median :3.000
Median : 6.000
Mean:1.445Mean:3.172Mean: 6.496
3rd Qu.:2.000
3rd Qu.:5.000
3rd Qu.: 9.000
Max.
:2.000Max.
:5.000Max.
:12.000
stratastratum
aimagsoumMin.
:1.000Min.
:1.000Min.
: 1.00
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:30.00
Median :2.000
Median :2.000
Median :59.00
Mean:2.126Mean:2.418Mean:53.87
3rd Qu.:3.000
3rd Qu.:4.000
3rd Qu.:80.00
Max.
:3.000Max.
:4.000Max.
:87.00

aimag
Min.
: 1.00
1st Qu.: 8.00
Median :15.00
Mean:13.48
3rd Qu.:20.00
Max.
:21.00quarterMin.
:1.000
1st Qu.:1.000
Median :2.000
Mean:2.499
3rd Qu.:3.000
Max.
:4.000

Mongolia HSES 2010 Manual (Version 1.0)

locationMin.
:1.000
1st Qu.:1.000
Median :2.000
Mean:2.382
3rd Qu.:4.000
Max.
:4.000hhweight
Min.
: 4.948
1st Qu.: 42.611
Median : 54.725
Mean: 63.332
3rd Qu.: 78.348
Max.
:246.901

66

5.3 Frequency tables of categorical variables
DATA CHECK OF CATEGORICAL VARIABLES>> for(k in 1:17){+ 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+ cat("\n\n","#### FREQUENCY OF VARIABLES IN ",k,":", Rnames[k],+ "#########################################\n\n")+ for(j in 1:length(cb)){+ if(k>=13&k<=16&j==2) {next}+ if(k==1&is.element(j,c(46,47,51,52))) {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 ####################################----- 7 : v1_res : Visit 1 Result -----------------------1
2
3
4
5
7
5581 5224 65 143 137
48----- 11 : v2_res : Visit 2 Result -----------------------1
2
3
4
5
6
7 <NA>
1328 5255 153 143
27
2
2 4288----- 15 : v3_res : Visit 3 Result -----------------------123456 <NA>
1606 4986 113 134
38
2 4319----- 19 : v4_res : Visit 4 Result -----------------------123
57 <NA>
6694 234
1
1
1 4267----- 20 : q0507 : 0507 Has produced animal products past 12m? -----------------------1
2 <NA>
4062 142 6994----- 21 : q0515 : 0515 Agricultural land in past 12 m? -----------------------1
2
1054 10144----- 23 : q0517 : 0517 Has vegetables, fruits in pas 12M -----------------------1
2 <NA>
835
219 10144----- 24 : q0501 : 05-01 Raised or Owned Herding,poultry or any animal? ----------------1
24204 6994----- 26 : q0601 : 0601. Are there household enterprises? -----------------------1
2

Mongolia HSES 2010 Manual (Version 1.0)

671862 9336----- 28 : q0707 : 07-07 :Has any member received money or goods -----------------------1
27004 4194----- 33 : q0802 : 0802. Is main dwelling? -----------------------1
2
10393
805
----- 34 : q0803 : 0803. Type of Dwellings -----------------------1
2
3
4
5
6
7
8
9
5183 1051 2644 2117
19
85
62
28
9
----- 36 : q0805 : 0805. Main material of the walls -----------------------12
3
45 <NA>
1650 1476 2591
59 211 5211----- 37 : q0806 : 0806. Main material of the roof -----------------------1
2
34 <NA>
2101 2660 717 509 5211----- 38 : q0807 : 0807. Main material of the floor -----------------------1
2
34 <NA>
4343 1345 126 173 5211----- 43 : q0812 : 0812. Covering of the ceiling -----------------------1
2 <NA>
1375 3808 6015----- 44 : q0813 : 0813. Covering of the frame -----------------------1
2 <NA>
1381 3802 6015----- 45 : q0814 : 0814. Main material of the floor -----------------------1
2
3 <NA>
2638 2341 204 6015----- 48 : q0817 : 0817. Type of ownership -----------------------1
2
3237
175 10786----- 49 : q0818 : 0818. How was acquired -----------------------1
2
3
4
5
6
7 <NA>
270 1521 795 4034 3139 728 299 412----- 50 : q0819 : 0819. Did you borrow any money to acquire -----------------------1
2 <NA>
729 7471 2998----- 53 : q0822 : 0822. What is the main source of heating -----------------------123452358 8453 21 220 146----- 54 : q0823 : 0823. Source of electricity -----------------------1
2
3
4
5
6
7
7860 822 2078
88
20 27852----- 55 : q0824 : 0824. Electricity resource adequate for operating electric d -----------1
28165 3033----- 56 : q0825 : 0825. Water supply -----------------------1
2
3
4
5
6
7
8
1929 352 3855 1272 1866 1589 267
68----- 57 : q0826 : 0826. Has the household a sewage system -----------------------1
25991 5207----- 58 : q0827 : 0827. Household waste disposal -----------------------1
2
3
4
772 7051 2396 979----- 59 : q0828 : 0828. What type of toilet do you have ------------------------

Mongolia HSES 2010 Manual (Version 1.0)

68

1
2
3
4
2149 137 7112 1800----- 60 : q0829 : 0829. Has a telephone -----------------------12
3
4
288 8621 1016 1273----- 66 : q0831 : 0831. Anybody from your household own or exploit land ? ----------------1
24729 6469----- 69 : q0833 : 0833. Use internet normally? -----------------------1
22260 8938----- 71 : q0835_1 : 0835_1. Where used internet, at home -----------------------1
2 <NA>
852 1408 8938----- 72 : q0835_2 : 0835_2. Where used internet, at work -----------------------1
2 <NA>
895 1365 8938----- 73 : q0835_3 : 0835_3. Where used internet, internet cafe -----------------------1
2 <NA>
774 1486 8938----- 74 : q0835_4 : 0835_4. Where used interne, free public accesst ----------------------1
2 <NA>
611 1649 8938----- 75 : q0835_5 : 0835_5. Where used internet, other -----------------------1
2 <NA>
125 2135 8938#### FREQUENCY OF VARIABLES IN

2 : Individual #########################################----- 3 : q0102 : 102. Relationship to head -----------------------1
2
3
4
5
6
7
8
9
10
12
11198 7835 19976
562
896
97
484
49 1879340
39----- 5 : q0103 : 103. Sex -----------------------1
2
21210 22145----- 9 : q0106 : 106. Marital Status -----------------------123456 <NA>
16707
380
483
565 2417 11033 11770----- 15 : q0111 : 111. Is HH member? -----------------------1
2
42470
885
----- 16 : q0201 : 201. Is 6 years or more? -----------------------1
2 <NA>
37652 4818
885----- 17 : q0202 : 202. Is answering personally? -----------------------1
2 <NA>
16986 20666 5703----- 19 : q0204 : 204. Highest certificate obtained -----------------------1
2
3
4
5
6
7
8
9
10 <NA>
4498 6451 7718 10669 2689 2037 3314
242
22
12 5703----- 20 : q0205 : 205. Can read a letter? -----------------------1
2
3 <NA>
7987 2175
787 32406----- 21 : q0206 : 206. Are you attending School? -----------------------1
2
34 <NA>

Mongolia HSES 2010 Manual (Version 1.0)

6912257 2862
769 21764 5703----- 22 : q0207 : 207. Check age/ between 8-35 years -----------------------1
2 <NA>
1765 1866 39724----- 23 : q0208 : 208. Reason never attended school -----------------------1
2
3
4
5
6
7
8
9
10
11
13 <NA>
509
312
51
6
9
100
341
222
55
7
19
134 41590----- 24 : q0209t : 209. Current education TYPE -----------------------1
2
34 <NA>
9033
323 2856
45 31098----- 26 : q0210 : 210. Type of School -----------------------1
2
3 <NA>
11158 1045
54 31098----- 27 : q0211 : 211. School Location -----------------------1
2
34 <NA>
5292 3297 3591
77 31098----- 28 : q0212 : 212. Place where person lives during school -----------------------12
3
45 <NA>
8613
429 1229 1774
212 31098----- 29 : q0213 : 213. Pay tuition? -----------------------1
2 <NA>
3558 8699 31098----- 38 : q0301 : 301. Answering personally? -----------------------1
2 <NA>
17138 25332
885----- 40 : q0303 : 303. Any health problem during past month? -----------------------1
2 <NA>
3001 39469
885----- 41 : q0304a : 304_A. Health problem (1) -----------------------123456 <NA>
993
322
200
582
430
474 40354----- 42 : q0304b : 304_B. Health problem (2) -----------------------0
1
2
3
4
5
6 <NA>
2709
86
38
27
51
26
64 40354----- 43 : q0305 : 305. Did you seek treatment in past 1 M? -----------------------1
2 <NA>
2351
650 40354----- 44 : q0306 : 306. Why didn't seek treatment? -----------------------1
2
3
4
5
6
8
9
10
11
12 <NA>
386
10
9
2
1
1
4
21
196
1
19 42705----- 45 : q0307 : 307. Where was treatment provided? -----------------------123456 <NA>
482
806
916
128
3
16 41004----- 46 : q0308 : 308. Who provided medical service for your treatment? ------------------123456 <NA>
1772
553
12
6
2
6 41004----- 49 : q0310 : 310. Have bought medicines in the past M ? -----------------------1
2 <NA>
3824 38646
885----- 51 : q0312 : 312. Have stayed at hospital in past 12 M? -----------------------1
2 <NA>
4103 38367
885----- 52 : q0313 : 313. What was the Hospital ? -----------------------123456 <NA>
1025 1668 1019
340
11
40 39252----- 55 : q0401 : 4.01 Respondent 10 yrs or more? ------------------------

Mongolia HSES 2010 Manual (Version 1.0)70

12 <NA>
34844 7626
885----- 56 : q0402
12 <NA>
16758 18086 8511----- 58 : q0404
12 <NA>
15217 19627 8511----- 59 : q0405
1
2
3
7887
552 4795----- 60 : q0406
12 <NA>
1148 18479 23728----- 61 : q0407
1
2
3
97
55
79
----- 62 : q0408
12 <NA>
725 17754 24876----- 63 : q0409
12
39543 3265 1521----- 64 : q0410
12 <NA>
525 5095 37735----- 68 : q0414
1
2
3
62
66
723
----- 69 : q0415
12 <NA>
8729 7636 26990: 4.02 Answering by himself? ------------------------: 4.04 Did you any job for the past 7 days? ------------------------: 4.05 What kind of work was the main job you did? -----------------------4
5 <NA>
138 1845 28138: 4.06 Any permanent job despite you did no job in last 7 day ------------: 4.07 Main reasong for not doing job in last 7 days ---------------------45
6
7 <NA>
123125
418
251 42207: 4.08 Did you look for a job in last 7 days ------------------------: 4.09 Reasons for not looking for a job -----------------------45678 <NA>
719
57
97
812 1740 25601: 4.10 Registered in labour and social welfare dep? -----------------------: 4.14 Type of your organisation -----------------------456789 <NA>
2890
241
67 3145224 8947 26990: 4.15 Do your receive any salary in cash and/or in kind ------------------#### FREQUENCY OF VARIABLES IN

3 : Llivestock #########################################----- 2 : ani_id : Animal Number -----------------------1
2
3
4
5
6
3101 2741 532 3604 3737
66#### FREQUENCY OF VARIABLES IN

4 : Llivestock Expenditure ##########################----- 2 : exp_id : Exp number -----------------------12
3
453396 2652 1754 1019 452#### FREQUENCY OF VARIABLES IN

5 : Product #########################################----- 2 : byprod_id : By-product number -----------------------1
2
3
4
5
6
4253 4253 4253 4253 4253 4253----- 3 : q0508 : 508. In the past 12 months have your household produced ..? -------------0
1
2 <NA>
1 12369 12004 1144

Mongolia HSES 2010 Manual (Version 1.0)

71#### FREQUENCY OF VARIABLES IN

6 : Crop #########################################----- 2 : crop_id : Crop Number -----------------------1
2 3
4
5
6
7
8
9 10 11711 341 233 186 120 197 29 130 178 44 90----- 3 : q0519 : 519. Did harvest during past 12 M? -----------------------1
2259#### FREQUENCY OF VARIABLES IN

7 : Agriultural Expenditure #############################----- 2 : exp_id : Expenditure Item -----------------------1
2 3
4
5
6
7
8
9 10 11 12
837 837 837 837 837 837 837 837 837 837 837 837#### FREQUENCY OF VARIABLES IN

8 : Enterprise ############################################# FREQUENCY OF VARIABLES IN

9 : Other income #########################################----- 2 : income_id : Source Number -----------------------1
2
3
4
5
6
7
8
9
10
11
12
13
11191 11191 11191 11191 11191 11191 11191 11191 11191 11191 11191 11191 11191
14
15
16
17
18
19
20
21
22
23
11191 11191 11191 11191 11191 11191 11191 11191 11191 11191----- 3 : q0701 : 07-01: Has anybody received ... -----------------------0
1
2
1 17871 239521#### FREQUENCY OF VARIABLES IN

10 : Remittance #########################################----- 4 : q0709 : 0709. Who gave the gift -----------------------1
2
3
4
5
6
7 <NA>
18191
935
60 2444
105
90
437
3
----- 5 : q0710 : 0710 Purpose of the receipt -----------------------1
2
3
4
5
6
7 <NA>
20733
575
184
83
250
39
398
3
----- 6 : q0711 : 0711. From where the gifts -----------------------1
2
3
4
5
6
7
8 <NA>
19344 2532
193
55
13
10
17
97
4
----- 8 : q0713 : 0713. Do receive it regularly? -----------------------12
3
45 <NA>
40603
191 3030 18397
4----- 9 : q0714 : 0714. How do you receive it? -----------------------12
3
45 <NA>
20027
171
291 1607165
4#### FREQUENCY OF VARIABLES IN

11 : Energy #########################################

Mongolia HSES 2010 Manual (Version 1.0)

72----- 2 : energy_id : Source Number -----------------------1
2
3
4
5
6
11198 11198 11198 11198 11198 11198----- 3 : q0836 : 0836. Have used the source? -----------------------1
224946 42242----- 4 : q0837 : 0837. How do you mainly obtain [FUEL]? -----------------------1
2
34 <NA>
5813 9578
230
538 51029#### FREQUENCY OF VARIABLES IN

12 : Payment service #########################################----- 2 : item : Service Number -----------------------1
2
3
4
5
6
7
8
9
10
11
12
13
11198 11198 11198 11198 11198 11198 11198 11198 11198 11198 11198 11198 11198----- 3 : q0842 : 0842. Have bought or received free.. during past 12 m? ------------------1
222215 123359#### FREQUENCY OF VARIABLES IN

13 : Durable ############################################# FREQUENCY OF VARIABLES IN

14 : Non-Food #########################################----- 3 : q1001
12533762 3430330: 1001. Have you bought or received for the last 12 Ms ---------------------#### FREQUENCY OF VARIABLES IN----- 3 : s11yn
12
168387 589333: Auxiliary 'Consumed? Y/N' ------------------------#### FREQUENCY OF VARIABLES IN----- 3 : q1201
1
273970 534438

15 : Urban Diary #########################################

16 : Rural Food 7 day #########################################: 1201. Have you consumed food during the 7 days ------------------------#### FREQUENCY OF VARIABLES IN

17 : Basicvars #########################################----- 4 : aimag : Aimag -----------------------1
2
3
4
5
6
7
8
9
10
11
12
13
14
504 408 408 312 312 312 312 312 408 600 312 312 408 504
16
17 18
19
20
21
312 504 407 336 3572 240----- 5 : location : Strata 4 locations -----------------------1
2
3
43572 2639 2129 2858

Mongolia HSES 2010 Manual (Version 1.0)

15
403

73

----- 6 : urban : Urban/rural -----------------------1
2
6211 4987----- 7 : region : Region -----------------------123451843 2568 2184 1031 3572

Mongolia HSES 2010 Manual (Version 1.0)

74

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

> HHID<-outfiles[[1]]$identif> length(HHID)[1] 11198> for(j in 1:17) cat("\n",j,":",sum(!is.element(outfiles[[j]]$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 : 0

Mongolia HSES 2010 Manual (Version 1.0)

75

Chapter 6. Household Income
6.1 Outline of estimation of household income and expenditure

The variables of total household income and total household expenditure were not provided.



Based on discussion with the delegates from Mongolia during the workshop 2016, the estimation
method of household income and expenditure is summarized as follows;

Total household expenditure is divided into monetary expenditure and non-monetary expenditure.
Non-monetary expenditure consists of “received free” and “own production”.

Monetary expenditure (A)Remarks

Food purchased

Urban + Rural

Non-foodfrom clothing up to materials for building repair

Non-food otherhousing durable goods, tax, assistance andcelebration

Non-food gift

gift for individuals

Non-monetary expenditure (B)Food received freeevaluated using median unit purchasing prices

Food own production

same as the aboveNon-food received freesame as the above

Total household expenditure (A+B)



Total household income is divided into monetary income and non-monetary income.
Here, non-monetary income is regarded as equivalent as non-monetary expenditure, therefore,
non-monetary income is not directly estimated from questionnaire.

Monetary income (C)Remarks

Wage
PensionLivestock
Agriculture
Business

Mongolia HSES 2010 Manual (Version 1.0)

76

Other income
Non-monetary income (D)Regarded as equivalent as (B)Total household income (C+B)



I have tried estimating monthly income and expenditure. The below table shows my trial
estimation of monetary income and comparison with the estimation by Mongolian delegates

IncomeFile

VariablessourceWage

Remarks(MO: Mongolian delegates)

02 Individual

q0416a (1M) wage amountCompletely consistent!

q0416b (12M) wage amountPension

09 Other income

sum of q0702_t to q0706_t (12M)

MO estimates = 68105

income_id: type of income

My trial = 67160 (excluded income_id =14 to 22)To clarify which income_id should be
included.

Livestock

03 livestock

q0505 (12M) amount received

04 livestock exp

q0506 (12M)

05 productq0512 (12M) sales
q0514 (12M) produced and soldMO estimates = 25796
My trial = 35642
Big gap!
Possible causes of treating outliers.

Agriculture

06 cropq0523t (12M) amount sold

(Crop)

07 crop exp

q0524 (12M)Completely consistent!
My trial = 3558 if negative crop income
at hh level is replaced with zero.

Business

08 enterpriseq0604: ownership rate
q0607_10: total expense

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77

sum of q0609_1b*q0609_1a,My trial = 54653 if outliers such as

q0609_2b*q0609_2a andincome<0 or revenue>7000000 are

q0609_3b*q0609_3a

replaced with zero.
Possible cause of not using ownershiprate in MO estimation?
To clarify treating of outliers

Other

10 remittanceq0712 (12M) amount received

MO estimates = 39956
My trial = 33444
To clarify the definition of “other”.

The above are the operational definitions of household income and expenditure.
However, the following income items seem not to be counted.


Imputed rent is not evaluated.

Compared with Section 8. Housing and Energy, house rent and dwelling fee are not included.

Compared with Section 9. Durable goods, some items are not covered in Section 10. Nonfood questionnaire sheets.



According to the survey report 2010, the different method is described for the purpose of poverty
analysis, as follows;

Item

Description

Principle

To estimate consumption contributing to people’s welfare

Five components

food, non-food, housing, durable goods and energy.

of consumption
FOODThe HSES 2010 records information on food consumption at thehousehold level for 122 items, organized in 13 categories: flour andflour products; meat and meat products; fish and seafood; dairy
products; eggs; oils and fat; fruits and berries; sugar and jam; otherfood; tea and coffee; mineral water and soft drinks; alcoholic
beverages; and tobacco and cigarettes.



The food component consists of not only expenditures on market
purchases or on meals eaten out but also food that was home-producedU

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or received in gifts.
UOnly food that was actually consumed was entered in the consumption
aggregate.

The value of non purchased food items was estimated and included in
the welfare measure.



The HSES used average prices to estimate the monetary value of nonUpurchased food. Median prices were computed at several levels by
U

Uhousehold, cluster, aimag, stratum and month. Hence if a householdUpurchased a food item, the same price would be used to value its self
produced and in kind consumption. If the household did not make any
Upurchase but consumed a food item, the average price from theimmediate upper level was used to estimate the value of that
consumption.
U

NON FOOD

371 items arranged in 38 different groups such as clothing andfootwear for men, women and children, jewelry and souvenirs, textiles,
education, health, recreation, beauty and toiletry products and services,
cultural expenses, household goods, durable goods, housing
expenditures, transportation, communication, insurance and taxes.



The HSES does not gather information on quantities consumed, withthe exception of durable goods, housing and energy.

Only items that contribute to the consumption are to be included.
Taxes, capital transactions, marriage, birth, funeral and remittancesU

given to other households are omitted.
U

Education and health are included. The HSES offers a second source ofUU

expenditure data for education and health. It was decided to use theUspecialized modules.
UThe HSES collects information with two reference periods: last monthand last year. A third option that can be seen as a compromise between
these two choices is to combine the information from both recall
periods. In this case information was taken from the last month if
Uavailable, and if the household did not purchase anything in the last 30
UU

days, information on the last year will be considered.
U

DURABLEGOODS

The right measure to estimate, for consumption purposes, is the streamof services that households derive from all durable goods in theirpossession over the relevant reference period.



It can be assumed to be proportional to the value of the good andU

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U79

determined by depreciation rates. A usual procedure involves
UU

calculating depreciation rates for each type of good based on theircurrent value and age, which in this case is provided by the HSES
along with the number of durables owned by the household.

HOUSINGThe estimation of this component involved three steps.

Very few households reported renting their dwellings although it isincreasingly common these days and rentals are too high. The
estimates may not always be credible.



Hedonic housing regressions were run with the imputed value of theUU

dwelling as the dependent variable.
ENERGYThe HSES collects information only on purchases and self-reported
Uvaluations of fuels and services obtained for free.
UGiven that no data on quantities of collected fuel are available, it is notpossible to impute a value to that consumption.

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6.2 Estimation of monthly household income

No aggregated data of household income is available in micro data set, and no income figures arein the survey report.



According to the delegates from Mongolia, the monthly total household income per household atnational average in 2010 is 448,027 MNT.



Data frames and variables related to household income are as the next;

IncomeFile

Variable

Description

Period02 Individual

q0416aWage amount – past month

1M

q0416b

Wage amount – past 12 months

12M

q0416cBonuses and special allowances

12M

q0702_t

Amount received by household member (1)12M

q0703_t

Amount received by household member (2)12M

q0704_t

Amount received by household member (3)12M

q0705_t

Amount received by household member (4)12M

q0706_t

Amount received by household member (5)12MsourceWage income

Pension

09 Other(Otherincomeincome)Income from

03 Llivestock

livestock

04 Livestock_

Revenueq0503

Quantity of own food

12M

q0504

Quantity of sold

12M

q0505

Amount received

12M

q0506

Expenditure (Cost)

q0510

Quantity of own consumption

12M

q0511

Quantity sold as raw material

12M

q0512

Amount of by-product sold as raw material

12M

q0514

Amount of by-product produced and sold

12M

Expenditure

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Agricultural

06 Crop

q0520

Total harvest in Kg

12M

incomeq0521

Quantity consumed by own hh in Kg

12M(Crop)

q0522

Quantity used for animal feed in Kg

12M

q0523qQuantity sold in Kg

12M

q0523tTotal amount sold

12M

Estimated amount of total harvest =(q0523t / q0523q) * q0520

07 Agricultural_q0524

Total expenditure

12M

q0604

Ownership rate (%)

q0607_10

Total expenses

12M

q0609_1a

Revenue in average month1M

q0609_1b

No. of months

q0609_2a

Revenue in bad monthq0609_2b

No. of months

q0609_3a

Revenue in good monthq0609_3b

No. of months

Expenditure

Business

08 EnterpriseincomeTotal revenue = q0609_1a * q0609_1b +

1M

1M

12M

q0609_2a * q0609_2b + q0609_3a * q0609_3b

Other income

10 Remittanceq0712

Amount received(Remittance)

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

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

6.3 Wage income
Data frame: 02 Individual
Variables from questionnaire/codebook
q0415: Have you receive salary by cash and/or in kind for the work in the last 12
months?
q0416a: The total amount of salary of the all jobs including main and double jobs inthe last monthq0416b: The total amount of salary of the all jobs including main and double jobs inthe last 12 months
q0416c: Additional wages, grants and bonuses in the last 12 months
Note: According to the delegates from Mongolia, q0416c is not included in theestimation of wage income, because it is covered in other income.

Note: The wage questions are different from questionnaire HSES 2007/08.
q0416a: Wage in cash – past 12 months
q0416b: Wage in-kind – past 12 months
q0416c: Bonuses and special allowances – past 12 months> d<-outfiles[[2]] # 02_indiv> dim(d)[1] 43355
73> colnames(d)[1] "identif" "ind_id" "q0102" "newhead" "q0103" "q0104" "q0105y"[8] "q0105m" "q0106""q0107" "q0108" "q0109" "q0110a" "q0110"[15] "q0111" "q0201""q0202" "q0203" "q0204" "q0205" "q0206"[22] "q0207" "q0208""q0209t" "q0209g" "q0210" "q0211" "q0212"[29] "q0213" "q0214_1" "q0214_2" "q0214_3" "q0214_4" "q0214_5" "q0214_6"[36] "q0214_7" "q0214_8" "q0301" "q0302" "q0303" "q0304a" "q0304b"[43] "q0305" "q0306""q0307" "q0308" "q309_1" "q309_2" "q0310"[50] "q0311" "q0312""q0313" "q0314" "q0315" "q0401" "q0402"[57] "q0403" "q0404""q0405" "q0406" "q0407" "q0408" "q0409"[64] "q0410" "q0411c" "q0412c" "q0413" "q0414" "q0415" "q0416a"[71] "q0416b" "q0416c" "PID"

8,729 household members received any salary.

> table(d$q0415,useNA="always")1
2 <NA>
8729 7636 26990

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The data shows that q0416a is monthly and q0416b is annual.

> d2<-subset(d,q0415==1)> dim(d2)[1] 8729 73> head(d2[,69:73])
q0415 q0416a q0416b q0416c PID
7
1 200000 200000
0 203
19
1 25000 200000
0 501
22
1 80000 480000
0 504
41
1 120000 950000
0 100142
1 180000 2160000
0 100254
1 265000 3180000
0 1401> round(mean(d2$q0416a)/1000)[1] 245> round(mean(d2$q0416b)/1000)[1] 2835> round(mean(d2$q0416c)/1000)[1] 45Out of 8,729 wage earners, 647 persons did not responded to monthly wage, butreported yearly wage.

> m<-table(d2$q0416a>0,d2$q0416b>0)> rownames(m)<-c("Monthly NA","Monthly filled")> colnames(m)<-c("Yearly filled")> addmargins(m)Yearly filled Sum
Monthly NA
647 647
Monthly filled
8082 8082
Sum
8729 8729



Twelvefold monthly wage is not equal to yearly wage for 2,104 persons.

> d3<-subset(d2,q0416a>0)> dim(d3)[1] 8082 74> table(d3$q0416a*12==d3$q0416b)
FALSE TRUE
2104 5978

Regarding two reference periods: last month and last year, the 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 lastyear will be considered.”

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

Estimated annual wage as;
q0416a*12 (if q0416a>0)
q0416b(otherwise)> d2$wage<-ifelse(d2$q0416a>0, d2$q0416a*12, d2$q0416b)> head(d2[,c(73,69,70,71,74)])
PID q0415 q0416a q0416b
wage
7 203
1 200000 200000 2400000
19 501
1 25000 200000 300000
22 504
1 80000 480000 960000
41 1001
1 120000 950000 1440000
42 1002
1 180000 2160000 2160000
54 1401
1 265000 3180000 3180000> head(d2[d2$q0416a==0,c(73,69,70,71,74)])
PID q0415 q0416a q0416b
wage
416 11502
1
0 2000000 2000000
608 15301
10 700000 700000
609 15302
1
0 750000 750000
635 15701
10 100000 100000
655 16103
1
0 1500000 1500000
671 16401
1
0 2000000 2000000


Aggregated at household level# Number of wage earners within the household> table(tapply(d2$PID,d2$identif,length))
1
2
3
4
5
3547 2058 279 46
9 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)

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+ }
+ y[is.na(y)]<-0+ return (y)+ }> HHID<-outfiles[[1]]$identif # 1-11198> df<-CollapseBy(d2,"identif","wage",HHID)> dim(df)[1] 11198
2> df$mwage<-round(df$wage/12) # Monthly wage
> df$hhweight<-outfiles[[17]]$hhweight> head(df)identifwage mwage hhweight1
1
0
0 47.39788
2
2 2400000 200000 47.39788
330
0 47.39788
440
0 47.39788
5
5 1260000 105000 47.39788
660
0 47.39788> round(weighted.mean(df$mwage,df$hhweight))[1] 223584> hhinc<-df

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6.4 Pension (OTHER INCOME)
Data frame: 09 other income
Income source (income_id)
Pension, benefits and social welfare
01 State pension
02 Special pension
03 Unemployment benefit
04 Maternity benefits
05 Civil care of disabled
06 Survivor’s pension
07 Illness payment
08 Funeral payments
09 Baby care allowances
10 Child allowances (transferred to account)
11 Child allowances (received in cash)
12 Other social benefit
Other ources
13 Rent of own assets (land, buildings, vehicles, equipment)
14 Sale of assets
15 Inheritances and wedding presents
16 Loan repayments
17 Withdrawals from bank savings
Interests and dividends from …
18 Savings?
19 Dividends?
20 Loan?
21 Treasury bond?
22 Gambling, lottery and contest
23 Other income (from intellectual property & other)

Remarks;
According to the delegates from Mongolia, 15 (Inheritances and wedding presents), 21 (Treasurybond) and 22 (Gambling, lottery and contest) are excluded from household income.

> d<-outfiles[[9]]> dim(d)[1] 257393
13> head(d[d$q0701==1,])
identif income_id q0701 q0702_ic q0702_t q0703_ic q0703_t q0704_ic q0704_t q0705_ic q0705_t
1
1
1
1 972000
2 972000
4 492000
0
NA
1
12
1
1
70000
2
70000
4
70000
0
NA
2
10
1
4 130000
5 130000
6 130000
7 130000
2
12
1
4
70000
5
70000
6
70000
7
70000
3
10
1
2 130000
0
NA
NA
NA
NA
NA
3
12
1
2
70000
0
NA
NA
NA
NA
NA
q0706_ic q0706_t
1
NA
NA
12
NA
NA
1
12
33
35
56
58

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33
35
56
58

0
0
NA
NA

NA
NA
NA
NA

###################################################################> d2<-subset(d,q0701==1&!is.element(d$income_id,c(14:17,18:22)))> dim(d2)[1] 17505
13



Remarks: To decide which income_id should be included in the concept of householdincome.



Generated the variable of monthly total amount received by household members.

> d2$pension<-round(rowSums(d2[,seq(5,13,by=2)],na.rm=T)/12)> head(d2)identif income_id q0701 q0702_ic q0702_t q0703_ic q0703_t q0704_ic
1
1
1
1
1 972000
2 972000
4
12
1
12
1
1 70000
2 70000
433
2
10
1
4 130000
5 130000
6
35
2
12
1
4 70000
5 70000656
3
10
1
2 130000
0
NA
NA
58
3
12
1
2 700000NANAq0704_t q0705_ic q0705_t q0706_ic q0706_t pension
1 492000
0NANA
NA 203000
12 70000
0NANA
NA 17500
33 130000
7 1300000NA 43333
35 70000
770000
0NA 23333
56
NA
NA
NA
NA
NA 10833
58
NA
NA
NA
NA
NA
5833

> df<-CollapseBy(d2,"identif","pension",HHID)> dim(df)[1] 11198
2> head(df)identif pension
1
1 220500
22 66666
3
3 16666
44 81000
550
6
6 50000> df$hhweight<-outfiles[[17]]$hhweight> head(df)identif pension hhweight1
1 220500 47.39788

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2
2 66666 47.39788
3
3 16666 47.39788
44 81000 47.39788
550 47.39788
66 50000 47.39788> round(weighted.mean(df$pension,df$hhweight))[1] 67160> pension<-df

For reference: HSES 2010 Questionnaire

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6.5 Income from livestock
Data frame: 03 Livestockq0502_1: total number of animals
q0502_2: number of female
q0502_3: number of young
q0503: use for own foodq0504: number of sold
q0505: amount received> d<-outfiles[[3]]> dim(d)[1] 13781
8> head(d[!is.na(d$q0505),])
identif ani_id q0502_1 q0502_2 q0502_3 q0503 q0504 q0505
7
2
4
112
70
20
13
2 60000
8
2
5
90
40
12
5
23 640000
27
8
1
16
10
0
1
3 540000
40
12
1
40
10
9
1
2 600000
50
17
1
25
10
5
1
3 1200000
61
20
1
176
60
36
1
10 4000000> table(d$ani_id)
1
2
3
4
5
6
3101 2741 532 3604 3737 66

The number of households with animals is 4,160.

> nrow(subset(d,q0502_1>0))[1] 13538> length(unique(subset(d,q0502_1>0)$identif))[1] 4160



Number of sample households by herding animal> t<-table(d$ani_id,useNA="ifany")> names(t)<-c("Cattle","Horse","Camel","Sheep","Goat","Other")> tCattle Horse Camel Sheep Goat Other
3101 2741
532 3604 3737
66

Aggregated q0505 at household-level.

> df<-CollapseBy(d,"identif","q0505",HHID)> df$revenue<-round(df$q0505/12) # Monthly revenue> dim(df)[1] 11198
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90

1
2
3
4
5
6

identif q0505 revenue
1 0e+00
0
2 7e+05 58333
3 0e+000
4 0e+000
5 0e+000
6 0e+00
0

Data frame: 04 Livestock_exp
exp_id: exp code
q0506: expenditure on this herding activity in the last 12 months> d<-outfiles[[4]]> dim(d)[1] 9273
3> head(d)identif exp_id q0506
1
1
2 15000
2
2
4 30000
3
2
2 27000
4
2
1 24000
5
3
2 12000
6
4
1 9000> table(d$exp_id)
1
2
3
4
5
3396 2652 1754 1019 452> df<-merge(df, CollapseBy(outfiles[[4]],"identif","q0506",HHID),by="identif")> df$cost<-round(df$q0506/12) # Monthly cost> head(df)identif q0505 revenue q0506 cost1
1 0e+00
0 15000 1250
2
2 7e+05 58333 81000 6750
33 0e+00
0 12000 1000
44 0e+00
0 29000 2417
55 0e+00000
6
6 0e+00
0 80000 6667
Remarks:
There are cases without revenue but with positive cost.

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Data frame: 05 Product (by-product)q0509: total quantity of production
q0510: quantity consumed by household
q0511: quantity sold as raw materialq0512: total amount received from sales
q0513: quantity produced and soldq0514: total amount received from produced and sold> d<-outfiles[[05]]> dim(d)[1] 25518
9> head(d)identif byprod_id q0508 q0509 q0510 q0511 q0512 q0513 q0514
1
1
1
1
3
0
3 54000
0
NA
2
1
2
1
30
0
30 9000
0
NA
3
1
3
1
12
0
12 62000
0
NA
4
1
4
1
750
750
0
NA
0
NA
5
1
5
2
NA
NA
NA
NA
NA
NA
6
1
6
2
NA
NA
NA
NA
NA
NA
> df<-merge(df, CollapseBy(outfiles[[5]],"identif",c("q0512","q0514"),HHID),+ by="identif")> df$byprod<-round((df$q0512+df$q0514)/12) # Monthly by-product> df$livestock<-df$revenue-df$cost+df$byprod # Monthly livestock income> head(df)identif q0505 revenue q0506 cost q0512 q0514 byprod livestock
1
1 0e+00
0 15000 1250 125000
0 104179167
2
2 7e+05 58333 81000 6750 626000 300000 77167
1287503
3 0e+00
0 12000 1000 16000
0 1333333
4
4 0e+00
0 29000 2417 780000 270000 87500
85083
55 0e+00
000 67000
0 55835583
6
6 0e+00
0 80000 6667 106000 1200000 108833
102166> livestock<-df> apply(livestock,2,function(x) round(weighted.mean(x,hhinc$hhweight)))
identifq0505
revenue
q0506
cost
q0512
q0514
5707
231050
19254
1180439837
3095405156
byprod livestock
26225
35642

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6.6 Agricultural (Crop) income
Data frame: 06 cropq0519: Did harvest during past 12 months
q0520: total harvest during past 12 months
q0521: quantity consumed by own household
q0522: quantity used for animal feedq0523q: quantity sold (kg)q0523t: total amount sold (MNT)> d<-outfiles[[6]]> dim(d)[1] 22598> head(d)identif crop_id q0519 q0520 q0521 q0522 q0523q q0523t
1
58
1
1 240 160
080 40000
2
79
1
1 200
80
0
0
NA
3
82
1
1
10
10
0
0
NA
4
85
1
1
20
20
0
0
NA
5
89
1
1 4000 500 1000 2500 1250000
689
11
1 40000 40000NAThe data set is only for harvesting crops.

> table(d$q0519)
1
2259



The number of sample households harvesting crops is 805.

> length(unique(d$identif))[1] 805



The number of households by harvesting crop

> t<-table(d$crop_id)> names(attributes(d)$label.table["crop_id"][[1]])[1] "Potatoes" "Carrots" "Turnip""Cabbage" "Beetroot" "Onion"[7] "Garlic""Tomatoes" "Cucumber" "Fruits""Other\x85"> names(t)<-names(attributes(d)$label.table["crop_id"][[1]])> names(t)[11]<-"Other"> t
Potatoes Carrots Turnip Cabbage BeetrootOnion Garlic Tomatoes
711
341
233
186
120
197
29
130
Cucumber Fruits
Other
178
44
90

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Aggregated q0523t at household level.

> df<-CollapseBy(d,"identif","q0523t",HHID)> dim(df)[1] 11198
2> df$revenue<-round(df$q0523t/12) # Monthly revenue> head(df[df$revenue>0,])
identif q0523t revenue
58
58 400003333
89
89 1250000 104167
136
136 300000
25000
143
143 60000
5000
159
159 128000
10667
161
161 490000 40833

Data frame: 07 agric_exp
q0524: total expenditure on item during past 12 months> d<-outfiles[[7]]> dim(d)[1] 10044
3> head(d)identif exp_id q0524
1
58
5
0
2
58
6
0
3
58
10
0
4
58
2
0
5
58
11
0
6
58
9
0
> table(d$exp_id)
1 2
3 4 5
6 7 8
9 10 11 12
837 837 837 837 837 837 837 837 837 837 837 837


The number of unique household is 837.

> length(unique(d$identif))[1] 837
The number of records with positive value of q0524 is 1,597.

> table(d$q0524>0)
FALSE TRUE
8447 1597
Aggregated q0524 at household level.

> df<-merge(df,CollapseBy(d,"identif","q0524",HHID),by="identif")> dim(df)Mongolia HSES 2010 Manual (Version 1.0)

94[1] 11198
4> df$cost<-round(df$q0524/12) # Monthly cost
> df$crop<-df$revenue-df$cost # Monthly crop income> head(df[df$revenue>0,])
identif q0523t revenue q0524 cost crop
58
58 40000
3333 10000
833 2500
89
89 1250000 104167 1260000 105000 -833
136
136 300000
25000 50000 4167 20833
143
143 60000
5000 40000 3333 1667
159
159 128000
10667 49000 4083 6584
161
161 490000
40833 60000 5000 35833


Replaced negative crop income with zero.

> df$crop2<-ifelse(df$crop<0,0,df$crop)> head(df[df$revenue>0,])
identif q0523t revenue q0524 cost crop crop2
58
58 40000
3333 10000
833 2500 2500
89
89 1250000 104167 1260000 105000 -833
0
136
136 300000
25000 50000 4167 20833 20833
143
143 60000
5000 40000 3333 1667 1667
159
159 128000
10667 49000 4083 6584 6584
161
161 490000
40833 60000 5000 35833 35833> crop<-df> apply(crop,2,function(x) round(weighted.mean(x,hhinc$hhweight)))
identif q0523t revenue q0524
cost
crop crop2
5707
71062
5922 33948
2829
3093
3558

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6.7 BUSINESS INCOME
Data frame: 08 enterpriseq0604: percentage owned by household members (%)
q0607_10: total expenses
q0608: months in operation
q0609_1a: amount received in an average month (per month)q0609_1b: number of average months
q0609_2a: amount received in a bad month (per month)q0609_2b: number of bad months
q0609_3a: amount received in a good month (per month)q0609_3b: number of good months> d<-outfiles[[8]]> dim(d)[1] 2051 23> head(d)identif en q0603c q0604 q0605 q0606 q0607_01 q0607_02 q0607_03 q0607_04
1
56 1 1430
100
1
0
25000
0
0
0
2
56 2 1520
100
1
0
0
20000
0
0
3
73 1 4923
100
1000 2000000
0476 1 3100
100
1
00 400000005100 1 4771
100
1
0 5000000
0006101 1 4921
100
1
0
0
0 2500000q0607_05 q0607_06 q0607_07 q0607_08 q0607_09 q0607_10 q0608 q0609_1a
1
0
0
0
0
0
25000
4
30000
2
0
0
0
0
0
20000
1
0
3
0
400000060000
0 2460000
8 350000
400000 400000
12 100000
5 3800000072000 500000 5952000
12 850000
6
0
80000
0
15000
0 345000
9 170000
q0609_1b q0609_2a q0609_2b q0609_3a q0609_3b
1
1
10000
1
60000
2
2
0
0
0
40000
1
3
2
10000
3
680000
3
4
3
20000
5
4000004567000004 1000000
2
6
3
90000
3
2000003There are 9 cases where total expenses are positive but no revenue are written.

> table(d$q0608==(d$q0609_1b+d$q0609_2b+d$q0609_3b))
FALSE TRUE
9 2036> d2<-subset(d,d$q0608!=(d$q0609_1b+d$q0609_2b+d$q0609_3b))> dim(d2)[1] 9 23

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> d2[,c("identif","q0607_10","q0608","q0609_1b","q0609_2b","q0609_3b")]identif q0607_10 q0608 q0609_1b q0609_2b q0609_3b
98
564 42708700
12
0
0
0
103
578 23826000
12
0
0
0
109
592 22150000
12
0
0
0
110
593 14730000
12
0
0
0
182
985 1400000
3
0
0
0
275
1418 32468000
12
0
0
0
310
1621 4804000
12
0
0
0
356
1831 18762000
12
0
0
0
357
1833 16080000
12
0
0
0



Generated variable of total monthly revenue as;(q0609_1b*q0609_1a + q0609_2b*q0609_2a + q0609_3b*q0609_3a)/12> d[is.na(d)]<-0> d$revenue<-round((d$q0609_1b*d$q0609_1a + d$q0609_2b*d$q0609_2a ++ d$q0609_3b*d$q0609_3a)/12)> head(d[,c(1,2,18:24)])
identif en q0609_1a q0609_1b q0609_2a q0609_2b q0609_3a q0609_3b revenue
1
56 1
30000
1
1e+04
1
60000
2 13333
2
56 2
0
0
0e+00
0
40000
1
3333
3
73 1 350000
2
1e+04
3 680000
3 230833
4
76 1 100000
32e+04
5 400000
4 166667
5
100 1 850000
6
7e+05
4 1000000
2 825000
6
101 1 170000
39e+04
3 200000
3 115000Generated variable of monthly business income as;(revenue-q0607_10/12)*q0604/100> d$cost<-round(d$q0607_10/12)> d$business<-round((d$revenue-d$cost)*d$q0604/100)> head(d[,c(1:2,4,16,24:26)])
identif en q0604 q0607_10 revenue cost business1
56 1 100
25000 13333 2083
11250
2
56 2 100
20000
3333 1667
1666
3
73 1 100 2460000 230833 205000
25833
4
76 1 100 400000 166667 33333 133334
5
100 1 100 5952000 825000 496000 329000
6
101 1 100 345000 115000 28750
86250> head(d[d$q0604<100,c(1:2,4,16,24:26)])
identif en q0604 q0607_10 revenue
cost business
81
519 1
15 21100000 3166667 1758333 211250
99
566 1
10
40000 16667
3333
1333
104
579 1
10
10000 10000
833
917
159
897 1
3 140000 98333 11667
2600
173
955 1
95 7539600 825000 628300 186865
180
971 1
20 1630000 110833 135833-5000

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business2: replace negative income at firm level with zero.

> d$business2<-ifelse(d$business<0,0,d$business)> head(d[d$q0604<100,c(1:2,4,16,24:27)])
identif en q0604 q0607_10 revenue
cost business business2
81519 1
15 21100000 3166667 1758333 211250
21125099566 1
1040000 16667
3333
1333
1333
104
579 1
10
10000 10000
833
917
917
159
897 1
3 140000 98333 11667
2600
2600
173
955 1
95 7539600 825000 628300 186865
186865180971 1
20 1630000 110833 135833
-5000
0



Aggregated at household level> df<-CollapseBy(d,"identif",c("revenue","cost","business","business2"),HHID)> dim(df)[1] 11198
5> head(df[df$business>0,])
identif revenue
cost business business2
56
56 16666
3750
12916
12916
73
73 230833 205000
25833
25833
76
76 166667 33333 133334
133334100
100 825000 496000 329000
329000101
101 115000 28750
86250
86250
102
102 120000 27500
92500
92500
> head(df[df$business<0,])identif revenue
cost business business2
135
135 141667 185417 -43750
0
152
152 110000 176800 -66800
0
160
160 179167 235000 -55833
0
396
396
8333
31333 -23000
0
564
564
0 3559058 -3559058
0
578
578
0 1985500 -1985500
0> head(df[df$business<0&df$business2>0,])
identif revenue
cost business business2
592
592 633333 2219166 -1585833
2600002412
2412
89166 333333 -244167
7500
7387
7387 1703333 1760000 -56667
13333
9430
9430 510000 530083 -20083
19500
10783 10783 1646666 1809166 -162500
112500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

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592
2412
7387
9430
10783

592 633333 2219166 -1585833
2412
89166 333333 -244167
7387 1703333 1760000 -56667
9430 510000 530083 -20083
10783 1646666 1809166 -162500

260000
7500
13333
19500
11250000000> apply(df,2,function(x) round(weighted.mean(x,hhinc$hhweight)))
identif revenue
cost business business2 business3
5707
364483145398218141223071222990business4: replace outlier revenue > 7,000,000 with zero

# Assumption of outlier revenue, considering;# > range(df$mo_business)# [1]0 6936666> range(df$revenue)[1]
0 433333333> nrow(subset(df,revenue>7000000))[1] 54> df$business4<-ifelse(df$revenue>7000000,0,df$business3)> apply(df,2,function(x) round(weighted.mean(x,hhinc$hhweight)))
identif revenue
cost business business2 business3 business4
5707
36448314539821814122307122299054653> range(df$business4)[1]
0 6283334> business<-df

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6.8 Other (REMITTANCE) income
Data frame: 10 remittance # Section 7
q0709: Who gave the giftq0710: Purpose of the receipt
q0711: From where the gifts
q0712: Amount received during the past 12 months
q0713: Do receive it regularly?
q0714: How do you receive it?

> d<-outfiles[[10]]> dim(d)[1] 22265
10> head(d)identif ln ind_id q0709 q0710 q0711 q0712 q0713 q0714 PID
1
25 1
1
7
7
1 16000
5
4 2501226 1
17
1
1 16000
5
4 2601327 1
171
1 16000
5
4 2701428 1
177
1 16000
5
4 2801529 1
1711 16000
5
4 2901633 1
171
1 16000
54 3301

Who gave the gift?

> t<-table(d$q0709)> names(t)<-names(attributes(d)$label.table["q0709"][[1]])> t
GOVERNMENT
18191
COMPANIES AND ORGANIZATIONS
935
NGOs
60
PARENTS, CHILDREN, RELATIVES
2444
OTHER INDIVIDUALS (FRIENDS, NEIGHBORS, ETC)
105
FOREIGN & INTERNATIONAL ORGANIZATIONS, INDIVIDUALS
90
OTHERS
437



Purpose of the receipt> t<-table(d$q0710)> names(t)<-names(attributes(d)$label.table["q0710"][[1]])> tMongolia HSES 2010 Manual (Version 1.0)

100

HOUSEHOLD USE EDUCATION8 TUITION FEE
20733
575
PURCHASE OF DWELLINGHOLIDAY/FUNERAL
83
250
OTHER
398



MEDICAL TREATMENT184
HOUDEHOLD ENTERPRISE
39

From where the gifts?

> t<-table(d$q0711)> names(t)<-names(attributes(d)$label.table["q0711"][[1]])
> t
URBAN
RURAL
KOREA
USA
19344
2532
193
55
GERMANY
JAPAN OTHER COUNTRY
10
17
97



ENGLAND
13

Do receive it regularly?

> t<-table(d$q0713)> names(t)<-names(attributes(d)$label.table["q0713"][[1]])> t
YES, weekly YES, monthly YES, quarterly YES, annualy
40
603
191
3030



How do you receive it?

> t<-table(d$q0714)> names(t)<-names(attributes(d)$label.table["q0714"][[1]])> t
CASH
BY ACCOUNT CASH REMITTANCE
IN KIND
20027
171
291
1607



NO
18397

Aggregated at household level> df<-CollapseBy(d,"identif","q0712",HHID)> dim(df)[1] 11198
2> df$other<-round(df$q0712/12)> head(df[df$q0712>0,])
identif q0712 other25
25 16000 1333
26
26 16000 1333
27
27 16000 1333
28
28 16000 1333

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OTHER
165

101

29
33

29 16000 1333
33 16000 1333

> weighted.mean(df$other,hhinc$hhweight)[1] 33444.35> other<-df

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

> hhinc.old<-hhinc> hhinc<-hhinc[,c(1,3)]> colnames(hhinc)[2]<-"wage"> hhinc<-merge(hhinc,pension[,c("identif","pension")],by="identif")> hhinc<-merge(hhinc,livestock[,c("identif","livestock")],by="identif")> hhinc<-merge(hhinc,crop[,c("identif","crop2")],by="identif")> colnames(hhinc)[5]<-"agriculture"> hhinc<-merge(hhinc,business[,c("identif","business4")],by="identif")> colnames(hhinc)[6]<-"business"> hhinc<-merge(hhinc,other[,c("identif","other")],by="identif")> head(hhinc)identif wage pension livestock agriculture business other1
1
0 220500
9167
0
0
0
2
2 200000
66666
128750
0
0
0
3
3
0
16666
333
0
0
0
4
4
0
81000
85083
0
0
0
5
5 105000
0
5583
0
0
0
6
6
0
50000
102166000> hhinc$ttinc<-rowSums(hhinc[,-1])> head(hhinc)identif wage pension livestock agriculture business other ttinc
1
1
0 2205009167
000 229667
22 200000
66666
128750000 395416
3
3
0
16666
333
0
0
0 16999
4
4
0
81000
85083
0
0
0 166083
5
5 10500005583
000 110583
6
6
0
50000
102166000 152166> t<-apply(hhinc,2,function(x) round(weighted.mean(x,hhinc.old$hhweight)))> data.frame(item=names(t),mean=t,row.names=NULL)
item
mean
1
identif
5707
2
wage 223584
3
pension 67160
4 livestock 35642
5 agriculture3558
6business 54653
7other 33444
8
ttinc 418041

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Chapter 7. Household Expenditure
7.1 Outline of estimation of monthly household expenditure

As described in Chapter 6, the total household expenditure is divided into monetary expenditureand non-monetary expenditure. Non-monetary expenditure consists of “received free” and “ownproduction”.

Monetary expenditure (A)Remarks

Questionnaire

Food purchased

Urban + RuralSES 2a, SES 2b

Non-foodfrom clothing up to materials for building

Section 10, SES 3

repairNon-food otherhousing durable goods, tax, assistance andSection 10, SES 3

celebration
Non-food gift

gift for individuals

Section 10, SES 3

evaluated using median unit purchasing

SES 2a, SES 2b

Non-monetary expenditure (B)Food received free

pricesFood own production

same as the above

SES 2a, SES 2b

Non-food received freesame as the above

Section 10, SES 3

Total household expenditure(A+B)

7.2 MONETARY EXPENDITURE

7.2.1 Urban Food Purchased
data frame: 15 Urban diary (Questionnaire SES-2a)> d<-outfiles[[15]]> dim(d)[1] 757720
16> head(d)identif item s11yn q1101_1 q1101_2 q1101_3 q1101_4 q1102_1 q1102_2 q1102_3
1
97 10101
1
2.0
2.0
0
0
0.0
NA
NA
2
97 10102
1
0.5
0.5
0
0
0.0
NA
NA
3
97 10103
2
NA
NA
NA
NA
NA
NA
NA
4
97 10104
1
3.0
3.0
0
0
5.1
5.1
0

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5
6

97 101052NANANA
97 101062
NANA
NAq1102_4 q1103_1 q1103_2 q1103_3 q1103_4 q1104
1
NA
2.0
2.0
0
0 500
2
NA
2.3
2.3
0
0 1450
3
NA
NA
NA
NA
NA
NA
4
0
4.1
4.1
0
0 700
5
NA
NA
NA
NA
NA
NA
6
NA
NA
NA
NA
NA
NA

NA
NA

NA
NA

# q110i_2: quantity purchased during the i-th 10 days (i=1,2,3)# q1104: average unit price# quantity purchased during a month> d$qpur<-rowSums(d[,c("q1101_2","q1102_2","q1103_2")],na.rm=T)# amount purchased during a month> d$u_pur<-d$qpur*d$q1104> head(d[,c(1:3,5,9,13,16:18)])
identif item s11yn q1101_2 q1102_2 q1103_2 q1104 qpur u_pur1
97 1010112.0
NA
2.0 500 4.0 2000
2
97 101021
0.5
NA
2.3 1450 2.8 4060
3
97 101032
NANANA
NA 0.0NA
497 101041
3.0
5.1
4.1 700 12.2 85405
97 101052
NANANA
NA 0.0NA
697 101062
NANANA
NA 0.0NA# Aggregated u_pur at household level> df<-CollapseBy(d,"identif","u_pur",HHID)> dim(df)[1] 11198
2> head(df[df$u_pur>0,])
identifu_pur
97
97 162387.5
98
98 264962.5
99
99 157440.7
100
100 158402.0
101
101 200634.0
102
102 60287.0> food<-df

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NA

NA
NA

105

7.2.2 Rural Food Purchased
data frame: 16 Rural Food 7 days

(Questionnaire SES-2b)> d<-outfiles[[16]]> dim(d)[1] 608408
8> head(d[!is.na(d$q1202)&d$q1202>0,])
identif item q1201 q1202 q1203 q1204 q1205 q1206
4
1 10104
1 10.0
10
580
0 0.0
9
1 10109
1 1.0
1 20000 0.0
16
1 10201
1
2.0
0
NA
0 2.0
17
1 10202
1
4.0
0
NA
0 4.0
18
1 10203
1
1.5
0
NA
0 1.5
31
1 10216
1
2.0
0
NA
0
2.0
# q1203: quantity purchased in the last 7 days
# q1204: unit price# Conversion multiplier from weekly to monthly is 4.3.
# amount purchased during a month> d$r_pur<-d$q1203*d$q1204*4.3> head(d[!is.na(d$q1202)&d$q1202>0,])
identif item q1201 q1202 q1203 q1204 q1205 q1206 r_pur
4
1 10104
1 10.010580
0 0.0 24940
9
1 101091
1.0
1 20000 0.0 8600
16
1 10201
1
2.0
0
NA
0
2.0
NA
17
1 10202
1
4.0
0
NA
0 4.0
NA
18
1 10203
1
1.5
0
NA
0
1.5
NA
31
1 10216
1
2.0
0
NA
0
2.0
NA

# Aggregated r_pur at household level> df<-CollapseBy(d,"identif","r_pur",HHID)> dim(df)[1] 11198
2> head(df[df$r_pur>0,])
identif r_pur
1
1 715092
2 826033
3 216724
4 5082655 648446
6 94170> food.old<-food> food$r_pur<-df$r_pur

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> head(food)
identif u_pur r_pur
1
1
0 715092
2
0 826033
3
0 216724
4
0 508265
50 648446
6
0 94170

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7.2.3 Non-food
Data frame: 14 Non-Food (Section 10)> d<-outfiles[[14]]> dim(d)[1] 3964092
6> d[is.na(d)]<-0#> d<-subset(d,q1001==1)#> dim(d)[1] 533762
6> head(d)identif item q1001 q1002 q1003 q1004
11
1 20111
1 6000 18000
0121 201121
0 3000013
1 201131
0 4000014
1 201141
0 1000029
1 202131
0 1500030
1 202141
0 35000q1002: Amount purchased during the past monthq1003: Amount purchased during the past 12 months
q1004: Amount received free during the past 12 months
item: item code, excluding sub-total> range(d$item)[1] 20101 24305> length(unique(d$item))[1] 353

Generated monthly expenditure variables of nfood, nfoodother, nfoodgifts andnfoodfree.
nfood, nfoodother, nfoodgifts are monetary expenditure, and nfoodfree is nonmonetary expenditure.

Monetary

Variables

Value

Conditions

nfood

q1002 or q1003/12

item 20101-23299, excluding
22501(restaurant) and 22502(canteen)nfoodotherq1002 or q1003/12

item 24101-24305, excluding 24301
housing durable goods, tax,
assistance, celebration

Non-monetarynfoodgifts

q1002 or q1003/12

item 24301(gifts)

nfoodfreeq1004/12

item 20101-24305

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> d$nfood<-ifelse(d$item>=20101&d$item<=23299&d$item!=22501&d$item!=22502,+ ifelse(d$q1002>0,d$q1002,round(d$q1003/12)),0)> d$nfoodother<-ifelse(d$item>=24101&d$item<=24305&d$item!=24301,+ ifelse(d$q1002>0,d$q1002,round(d$q1003/12)),0)> d$nfoodgifts<-ifelse(d$item==24301,+ ifelse(d$q1002>0,d$q1002,round(d$q1003/12)),0)> d$nfoodfree<-round(d$q1004/12)> head(d)identif item q1001 q1002 q1003 q1004 nfood nfoodother nfoodgifts nfoodfree
11

1 20111

1 6000 18000

0 6000

0

0

0

12

1 201121

0 3000

0

250

0

0

0

13

1 201131

0 4000

0

333

0

0

0

14

1 201141

0 1000

0

83

0

0

0

29

1 202131

0 1500

0

125

0

0

0

30

1 202141

0 3500

0

292

0

0

0

> head(d[d$nfoodother>0,])
identif item q1001 q1002 q1003 q1004 nfood nfoodother nfoodgifts nfoodfree347

1 24202

1 0e+00

5500

0

0

458

0

0

349

1 24204

1 0e+00 19500

0

0

1625

0

0

351

1 24302

1 1e+05 120000

0010000000352

1 24303

1 0e+00 30000

0

0

2500

0

0

696

2 24105

1 0e+00 115000

0

0

9583

0

0

703

2 24204

1 0e+00 40000

0

0

3333

0

0

> head(d[d$nfoodgifts>0,])
identif item q1001 q1002 q1003 q1004 nfood nfoodother nfoodgifts nfoodfree1412

4 2430110 3e+04

0

0

0

2500

0

2120

6 2430110 3e+04

0

0

0

2500

0

6014

17 24301

1

0 6e+04

0

0

0

5000

0

7076

20 24301

10 1e+05

0

0

0

8333

0

7784

22 24301

1

0 6e+04

0

0

0

5000

0

8138

23 24301

1

0 4e+04

0

0

0

3333

0

> head(d[d$nfoodfree>0,])

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identif item q1001 q1002 q1003 q1004 nfood nfoodother nfoodgifts nfoodfree
7086

21 20106100 10000

0

0

0

833

7088

21 201081

00 40000

0

0

0

3333

7091

21 20111

10

0 15000

0

0

0

1250

7092

21 20112100 6000

0

0

0

500

7143

21 20601

100 30000

0

0

0

2500

7144

21 20602

100 25000

0

0

0

2083

# Aggregated at household level> df<-CollapseBy(d,"identif",c("nfood","nfoodother","nfoodgifts","nfoodfree"),HHID)> dim(df)[1] 11198

5> head(df)identif nfood nfoodother nfoodgifts nfoodfree
1

1 82033

10458300

22 86983362916

0

0

3

3

2342

15167

0

0

4

4 54676

1000002500

055 57951

51917

0

0

6

6 123475

2064342500

0# Mean monthly expenditure including q1001=1> round(apply(df,2,function(x) weighted.mean(x,d13$hhweight)))
identif

nfood nfoodother nfoodgifts nfoodfree

5707

279650

59312

12285

9402

> nfood<-df[,1:5]> head(nfood)
identif nfood nfoodother nfoodgifts nfoodfree
1

1 82033

10458300

22 86983362916

0

0

3

3

2342

15167

0

0

4

4 54676

1000002500

055 57951

51917

0

0

6

6 123475

206434

2500

0

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7.3 NON-MONETARY EXPENDITURE

7.3.1 Urban fooddata frame: 15 Urban Diary(Questionnaire SES-2a)> d<-outfiles[[15]]> dim(d)[1] 757720
16> head(d)identif item s11yn q1101_1 q1101_2 q1101_3 q1101_4 q1102_1 q1102_2
1
97 10101
1
2.0
2.0
0
0
0.0
NA
2
97 10102
1
0.5
0.5
0
0
0.0
NA
3
97 10103
2
NA
NA
NA
NA
NA
NA
4
97 10104
1
3.0
3.0
0
0
5.1
5.1
5
97 10105
2
NA
NA
NA
NA
NA
NA
6
97 10106
2
NA
NA
NA
NA
NA
NA
q1102_3 q1102_4 q1103_1 q1103_2 q1103_3 q1103_4 q1104
1
NA
NA
2.0
2.0
0
0 500
2
NA
NA
2.3
2.3
0
0 1450
3
NA
NA
NA
NA
NA
NA
NA
4
0
0
4.1
4.1
0
0 700
5
NA
NA
NA
NA
NA
NA
NA
6
NA
NA
NA
NA
NA
NA
NA
s11yn: Consumed? Y/N
q110i_3: Quantity received free during the i-th 10 days (i=1,2,3)
q1102_4: Quantity own-produced during second 10 days (i=1,2,3)
q1104: average unit price
item: food item code, excluding sub-total.
> range(d$item)[1] 10101 11305> length(unique(d$item))[1] 122

There are 4,248 records without unit price data, which should be imputed.

> t<-addmargins(table(d$s11yn,is.na(d$q1104)|+ !is.na(d$q1104)&d$q1104==0,useNA="ifany"))> rownames(t)<-c("Consumed","Not consumed","Sum")> colnames(t)<-c("With unit price","Need imputation","Sum")> t
With unit price Need imputation
Sum
Consumed
1641394248 168387
Not consumed
6589327 589333
Sum
164145593575 757720

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111########################################################################################### Estimation of unit price ################################################################################################################################ data frame: 15 Urban Diary (Questionnaire SES-2a)> d<-outfiles[[15]]> dim(d)[1] 757720
16# Generated the variable of monthly quantity consumed# quantity received free
> d$q_3<-rowSums(d[,c("q1101_3","q1102_3","q1103_3")],na.rm=T)# quantity own-produced> d$q_4<-rowSums(d[,c("q1101_4","q1102_4","q1103_4")],na.rm=T)> sum(is.na(d$quantity))[1] 0> sum(is.na(d$q_3==0))[1] 0> sum(is.na(d$q_4==0))[1] 0> head(d[d$q_3>0,c(1,2,6,10,14,17:18)])
identif item q1101_3 q1102_3 q1103_3 q_3 q_4
1256
107 10401
12.5
11.0
9.5 33.0 0
1261
107 10406
1.0
1.0
1.5 3.5 0
1276
107 10506
0.4
0.5
0.3 1.2 0
1397
108 105050.8
NANA 0.8 03821
200 10404
0.5
NANA 0.5 04470
205 10711
0.5
NA
NA 0.5 0> head(d[d$q_4>0,c(1,2,7,11,15,17:18)])
identif item q1101_4 q1102_4 q1103_4 q_3 q_4
2471
117 10216
1.5
5.0
1.5 0 8.0
2593
118 10216
NA4.0
NA 0 4.0
2715
119 10216
NA5.0
NA 0 5.0
2837
120 10216
NA4.5
NA 0 4.5
3081
122 10216
NA4.6
0.5 0 5.1
3203
123 10216
NA5.0
0.5 0 5.5

# Generated data frame with records consumed the item at least in the last month, andvariables of identif, item, q_3, q_4 and q1104 (unit price).
> d<-subset(d,s11yn==1,select=c(identif, item, q_3, q_4, q1104))> dim(d)[1] 168387
5> table(is.na(d$q1104))
FALSE TRUE
167909478> colnames(d)[5]<-"up0" # Original unit price filled-in the questionnaire

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# Peplaced up0=0 with NA.
# Note: There are cases with up0 being zero even though quantity consumed is
positive, for example;> head(d[!is.na(d$q1104)&d$q1104==0,1:16])
identif item s11yn q1101_1 q1101_2 q1101_3 q1101_4 q1102_1 q1102_2
1256
107 10401
1
12.5
0
12.5
0.0
11.0
0
1261
107 10406
1
1.0
0
1.0
0.0
1.0
0
1276
107 10506
1
0.4
0
0.4
0.0
0.5
0
1397
108 10505
1
0.8
0
0.8
0.0
0.0
NA
2471
117 10216
1
1.5
0
0.0
1.5
5.0
0
2593
118 10216
1
0.0
NA
NA
NA
4.0
0
q1102_3 q1102_4 q1103_1 q1103_2 q1103_3 q1103_4 q1104
1256
11.0
0
9.5
0
9.5
0.0
0
1261
1.0
0
1.5
0
1.5
0.0
0
1276
0.5
0
0.3
0
0.3
0.0
0
1397
NA
NA
0.0
NA
NA
NA
0
2471
0.0
5
1.5
0
0.0
1.5
0
2593
0.0
4
0.0
NA
NA
NA
0

> sum(!is.na(d$up0)&d$up0==0)[1] 3770> d$up0<-ifelse(!is.na(d$up0)&d$up0==0,NA,d$up0)> sum(is.na(d$up0))[1] 4248# Generated data frame with regional information from “17 Basicvars”.
> df<-outfiles[[17]]> df<-subset(df,select=c(identif,cluster,aimag,location,month))> colnames(df)[2:4]<-c("psu","dist","strata")> head(df)identif psu dist strata month
1
1 1
1
4
2
2
2 1
1
4
2
3
3 1
1
4
2
4
4 1
1
4
2
5
5 1
1
4
2
6
6 1
1
4
2
# Merged d with df and appended regional information to d.
> d<-merge(d,df,by="identif",all.x=T)> dim(d)[1] 168387
9# Variable up: to be filled-in with the value of unit price used for estimation> d$up<-d$up0

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> head(d)identif item q_3 q_4 up0 psu dist strata month up
1
97 10101 00 500 52
1
2
3 500
2
97 10102 00 1450 52
12
3 14503
97 10104 00 700 52
1
2
3 700
4
97 10109 0
0 1900 52
12
3 19005
97 10111 00 8500 52
12
3 85006
97 10201 00 3300 52
1
2
3 3300#### Estimation of unit price ##### Specification: To compute median unit price of the available unit price "up0"# within the domain specified by the below control parameters, and# update the variable of unit price "up" with the value being NA.
# Then, the variable "up" will be used for estimating in-kind consumption# Control parameters> lbl<-list()> lbl[[1]]<-c("item","psu","up1")> lbl[[2]]<-c("item","dist","strata","month","up2")> lbl[[3]]<-c("item","strata","month","up3")> lbl[[4]]<-c("item","month","up4")> lbl[[5]]<-c("item","up5")# Scripts for estimating unit price> for(j in 1:length(lbl)){+ cmd<-paste("m<-aggregate(d$up0,list(d$",lbl[[j]][1],sep="")+ if(length(lbl[[j]])>2){+ for(k in 2:(length(lbl[[j]])-1)){+ cmd<-paste(cmd,",d$",lbl[[j]][k],sep="")+ }}+ cmd<-paste(cmd,"),FUN=median,na.rm=T)",sep="")+ eval(parse(text=cmd))+ colnames(m)<-lbl[[j]]+ d<-merge(d,m,by=lbl[[j]][-length(lbl[[j]])],all.x=T)+ cmd<-paste("d$up<ifelse(is.na(d$up),d$",lbl[[j]][length(lbl[[j]])],",d$up)",sep="")+ eval(parse(text=cmd))+ }# The final unit price "up" for urban food> head(d)item month strata dist psu identif q_3 q_4 up0 up up1 up2 up3 up4 up5
1 101011
1 20 1078
2390 0 0 600 600 600 650 650 650 650
2 101011
1 20 1078
2391 0 0 600 600 600 650 650 650 650
3 101011
1 20 964
2077 0 0 650 650 625 650 650 650 650
4 101011
1 20 9342015 0 0 610 610 610 650 650 650 650
5 101011
1 20 972
2108 0 0 750 750 660 650 650 650 650
6 101011
1 20 1158
2574 0 0 650 650 600 650 650 650 650

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> sum(is.na(d$up))[1] 0# Estimated the consumption in the last one month> d$u_free<-d$q_3*d$up> d$u_own<-d$q_4*d$up> head(d[d$u_free>0,c(1:8,10,16:17)])
item month strata dist psu identif q_3 q_4
up u_free u_own
302 10101
1
2
11 4881037 1 0 650.0 650.00414 10101
1
2
4 185
385 7 0 512.5 3587.5
0
422 10101
1
2
16 7121515 2 0 600.0 1200.00429 10101
1
2
19 8441813 11 0 600.0 6600.00458 10101
1
2
2 100
207 2 5 600.0 1200.0 3000
809 10101
102
19 83710186 6 0 500.0 3000.00> head(d[d$u_own>0,c(1:8,10,16:17)])
item month strata dist psu identif q_3 q_4 up u_free u_own
298 10101
1
1
20 894
1922 0 53 760
0 40280
318 10101
1
2
2 100
200 0 9 600
0 5400329 10101
1
2
2 100
206 0 7 600
0 4200330 10101
1
2
2 100
205 0 5 600
0 3000332 10101
1
2
2 100
203 0
8 600
0 4800357 10101
1
2
4 185
387 0
2 600
0 1200# Summarized exp at household level> t<-tapply(d$exp,d$identif,sum)> exp15<-data.frame(identif=names(t),mexp=t,row.names=NULL)> dim(exp15)[1] 62112> head(exp15)
identifmexp
1
97 162387.5
2
98 264962.5
3
99 157440.7
4100 158402.0
5
101 200634.06
102 60287.0> round(apply(df,2,function(x) weighted.mean(x,d13$hhweight)))
identif u_free u_own
5707
2516
2997

> food.old<-food> food<-cbind(food,df[,2:3])> head(food)
identif u_pur r_pur u_free u_own
1
1
0 71509
0
0

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2
3
4
5
6



2
3
4
5
6

0 82603
0 21672
0 50826
0 64844
0 94170

0
0
0
0
0

0
0
0
0
0

Results of imputation of unit price
Original q1104
Imputed price
NA
>0
=0
>0

Cases
478
3770

> table(d$s11yn==1&is.na(d$q1104),!is.na(d$up)&d$up>0)
FALSE TRUE
FALSE 589333 167909
TRUE
0
478
> table(d$s11yn==1&!is.na(d$q1104)&d$q1104==0,!is.na(d$up)&d$up>0)
FALSE TRUE
FALSE 589333 164617
TRUE
0 3770> head(d[is.na(d$q1104)&!is.na(d$up),])identif item s11yn q1101_1 q1101_2 q1101_3 q1101_4 q1102_1 q1102_2
25626
691 10201
1
18.5
0
0
18.5
16.5
0
25748
692 10201
1
5.8
0
0
5.8
3.6
0
25870
693 10201
1
5.2
0
0
5.2
6.5
0
25992
694 10201
1
9.1
0
0
9.1
6.5
0
25994
694 10203
1
0.0
NA
NA
NA
0.0
NA
25995
694 10204
1
0.0
NA
NA
NA
1.5
0
q1102_3 q1102_4 q1103_1 q1103_2 q1103_3 q1103_4 q1104 up
25626
0
16.5
16.5
0
0
16.5
NA 2000
25748
0
3.6
5.6
0
0
5.6
NA 2000
25870
0
6.5
4.6
0
0
4.6
NA 2000
25992
0
6.5
2.6
0
0
2.6
NA 2000
25994
NA
NA
0.8
0
0
0.8
NA 2500
25995
0
1.5
0.0
NA
NA
NA
NA 2500> head(d[!is.na(d$q1104)&d$q1104==0,])
identif item s11yn q1101_1 q1101_2 q1101_3 q1101_4 q1102_1 q1102_2
1256
107 10401
1
12.5
0
12.5
0.0
11.0
0
1261
107 10406
1
1.0
0
1.0
0.0
1.0
0
1276
107 10506
1
0.4
0
0.4
0.0
0.5
0
1397
108 10505
1
0.8
0
0.8
0.0
0.0
NA
2471
117 10216
1
1.5
0
0.0
1.5
5.0
0
2593
118 10216
1
0.0
NA
NA
NA
4.0
0
q1102_3 q1102_4 q1103_1 q1103_2 q1103_3 q1103_4 q1104 up
1256
11.0
0
9.5
0
9.5
0.0
0 1650

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1261
1276
1397
2471
2593



1.0
0.5
NA
0.0
0.0

0
0
NA
5
4

1.5
0.3
0.0
1.5
0.0

0
0
NA
0
NA

1.5
0.3
NA
0.0
NA

0.0
0.0
NA
1.5
NA

0 20000 45000 16500 25000 2500Strategy of generating resampled micro data:
To append up (imputed unit price) to outfiles[[15]] by merging keys being identif and item.

> up<-d[,c("identif","item","up")]> dim(up)[1] 168387
3> head(up)identif item up
12390 10101 600
22391 10101 600
32077 10101 650
42015 10101 610
52108 10101 750
62574 10101 650> d<-outfiles[[15]]> dim(d)[1] 757720
16> d<-merge(d,up,by=c("identif","item"),all.x=T)> dim(d)[1] 757720
17> head(d)identif item s11yn q1101_1 q1101_2 q1101_3 q1101_4 q1102_1 q1102_2 q1102_3
1
97 10101
1
2.0
2.0
0
0
0.0
NA
NA
2
97 10102
1
0.5
0.5
0
0
0.0
NA
NA
3
97 10103
2
NA
NA
NA
NA
NA
NA
NA
4
97 10104
1
3.0
3.0
0
0
5.1
5.1
0
5
97 10105
2
NA
NA
NA
NA
NA
NA
NA
6
97 10106
2
NA
NA
NA
NA
NA
NA
NA
q1102_4 q1103_1 q1103_2 q1103_3 q1103_4 q1104 up
1
NA
2.0
2.0
0
0 500 500
2
NA
2.3
2.3
0
0 1450 1450
3
NA
NA
NA
NA
NA
NA NA
4
0
4.1
4.1
0
0 700 700
5
NA
NA
NA
NA
NA
NA NA
6
NA
NA
NA
NA
NA
NA NA
# imputed_up: imputed unit price computed by the author.
> d$up<-ifelse(!is.na(d$q1104)&d$q1104>0,NA,d$up)> colnames(d)[17]<-"imputed_up"> sum(!is.na(d$imputed_up))

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[1] 4248> outfile15.old<-outfiles[[15]]> outfiles[[15]]<-dMongolia HSES 2010 Manual (Version 1.0)

118

7.3.2 Rural food
Data frame: 16 Rural Food 7 days

(Questionnaire SES-2b)> d<-outfiles[[16]]> dim(d)[1] 608408
8> head(d[!is.na(d$q1202)&d$q1202>0,])
identif item q1201 q1202 q1203 q1204 q1205 q1206
4
1 10104
1 10.0
10
580
0 0.0
9
1 10109
1 1.0
1 20000 0.0
16
1 10201
1
2.0
0
NA
0 2.0
17
1 10202
1
4.0
0
NA
0 4.0
18
1 10203
1
1.5
0
NA
0 1.5
31
1 10216
1
2.0
0
NA
0 2.0
q1201: Have you consumed in the last 7days
q1202: Total quantity consumed in the last 7 days
q1203: Quantity purchased
q1204: Unit priceq1205: Quantity received freeq1206: Quantity of own production

item: food item code, excluding sub-total.
> range(d$item)[1] 10101 11305> length(unique(d$item))[1] 122

There are 19,357 records without unit price data, which should be imputed.

> t<-addmargins(table(d$q1201,is.na(d$q1204)|!is.na(d$q1204)&d$q1204==0,+ useNA="ifany"))> rownames(t)<-c("Consumed","Not consumed","Sum")> colnames(t)<-c("With unit price","Need imputation","Sum")> t

ConsumedNot consumed
Sum

With unit price Need imputation
Sum
54613
19357 73970
1534437 534438
54614
553794 608408

 The conversion multiplier from weekly to monthly is set as 4.3.
> round(52/12,1)[1] 4.3

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119########################################################################################### Estimation of unit price ################################################################################################################################ Data frame: 16 Rural Food 7 days (Questionnaire SES-2b)> d<-outfiles[[16]]> dim(d)[1] 608408
8# Generated the variable of quantity consumed in the last 7 days
> d$quantity<-d$q1202> sum(is.na(d$quantity))[1] 534432> sum(d$quantity==0)[1] NA> head(d)identif item q1201 q1202 q1203 q1204 q1205 q1206 quantity
1
1 10101
2
NA
NA
NA
NA
NA
NA
2
1 10102
2
NA
NA
NA
NA
NA
NA
3
1 10103
2
NA
NA
NA
NA
NA
NA
4
1 10104
1
10
10 5800
010
51 10105
2
NA
NA
NA
NA
NA
NA
6
1 10106
2
NA
NA
NA
NA
NA
NA

# Generated data frame with records consumed the item at least in the last month, andvariables of identif, item, q1205 (quantity received free), q1206 (quantity own
produced) and q1204 (unit price).
> d<-subset(d,q1201==1,select=c(identif, item, q1205, q1206, q1204))> dim(d)[1] 73970
5> table(is.na(d$q1204))
FALSE TRUE
54678 19292> colnames(d)[5]<-"up0" # Original unit price filled-in the questionnaire> head(d)identif item q1205 q1206 up0
4
1 10104
0 0.0 580
9
1 101090
0.0 2000
16
1 1020102.0NA171 1020204.0
NA18
1 1020301.5NA31
1 102160
2.0
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# Peplaced up0=0 with NA.
> sum(!is.na(d$up0)&d$up0==0)[1] 65> d$up0<-ifelse(!is.na(d$up0)&d$up0==0,NA,d$up0)> sum(is.na(d$up0))[1] 19357# Generated data frame with regional information from “17 Basicvars”.
> df<-outfiles[[17]]> df<-subset(df,select=c(identif,cluster,aimag,location,month))> colnames(df)[2:4]<-c("psu","dist","strata")> head(df)identif psu dist strata month
1
1 1
1
4
2
2
2 1
1
4
2
3
3 1
1
4
2
4
4 1
1
4
2
5
5 1
1
4
2
6
6 1
1
4
2
# Merged d with df and appended regional information to d.
> d<-merge(d,df,by="identif",all.x=T)> dim(d)[1] 73970
9# Variable up: to be filled-in with the value of unit price used for estimation> d$up<-d$up0> head(d)identif item q1205 q1206 up0 psu dist strata month up
1
1 10104
0 0.0 580 1
1
4
2 580
2
1 10109
0 0.0 2000 1
1
4
2 20003
1 10201
0 2.0 NA 1
1
4
2 NA
4
1 102020 4.0 NA 1
1
4
2 NA
5
1 10203
0 1.5 NA 1
1
4
2 NA
6
1 102160 2.0 NA 1
1
4
2 NA

#### Estimation of unit price ##### Specification: To compute median unit price of the available unit price "up0"# within the domain specified by the below control parameters, and# update the variable of unit price "up" with the value being NA.
# Then, the variable "up" will be used for estimating in-kind consumption# Control parameters> lbl<-list()> lbl[[1]]<-c("item","psu","up1")

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> lbl[[2]]<-c("item","dist","strata","month","up2")> lbl[[3]]<-c("item","strata","month","up3")> lbl[[4]]<-c("item","month","up4")> lbl[[5]]<-c("item","up5")# Scripts for estimating unit price> for(j in 1:length(lbl)){+ cmd<-paste("m<-aggregate(d$up0,list(d$",lbl[[j]][1],sep="")+ if(length(lbl[[j]])>2){+ for(k in 2:(length(lbl[[j]])-1)){+ cmd<-paste(cmd,",d$",lbl[[j]][k],sep="")+ }}+ cmd<-paste(cmd,"),FUN=median,na.rm=T)",sep="")+ eval(parse(text=cmd))+ colnames(m)<-lbl[[j]]+ d<-merge(d,m,by=lbl[[j]][-length(lbl[[j]])],all.x=T)+ cmd<-paste("d$up<-ifelse(is.na(d$up),d$",lbl[[j]][length(lbl[[j]])],",d$up)",sep="")+ eval(parse(text=cmd))+ }# The final unit price "up" for rural food> head(d)item month strata dist psu identif q1205 q1206 up0 up up1 up2 up3 up4 up5
1 101011
3 15 6371359
00 700 700 700 700 700 650 700
2 101011
3 13 562
1192
00 650 650 650 600 700 650 700
3 101011
3 13 552
1173
0
3 NA 600 600 600 700 650 700
4 101011
3 18 8021709
00 750 750 750 750 700 650 700
5 101011
3 13 562
1191
0
7 NA 650 650 600 700 650 700
6 10101
1
3
6 233
499
0
0 650 650 650 650 700 650 700> sum(is.na(d$up))[1] 6

Remarks:
There are 6 un-imputed records. These are all “10211 Other poultry”.
These are ignored, that is, up is set with zero.
> d[is.na(d$up),1:10]
item month strata dist psu identif q1205 q1206 up0 up
20828 10211
10
3 13 546
9562 0.0 2.00 NA NA
20829 10211
12
4 14 586
9652 0.0 2.00 NA NA
20830 10211
2
4
4 157
334 0.0 0.05 NA NA
20831 10211
3
4 18 793
1690 0.0 1.00 NA NA
20832 10211
9
3 14 588
6854 0.1 0.00 NA NA
20833 10211
9
4 14 588
6856 0.0 3.00 NA NA> d$up<-ifelse(is.na(d$up),0,d$up)> sum(is.na(d$up))[1] 0

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# Estimated the consumption in the last one month# Monthly expenditure variables> d$r_free<-d$q1205*d$up*4.3> d$r_own<-d$q1206*d$up*4.3> head(d)item month strata dist psu identif q1205 q1206 up0 up up1 up2 up3 up4 up5
1 101011
3 15 6371359
00 700 700 700 700 700 650 700
2 101011
3 13 562
1192
00 650 650 650 600 700 650 700
3 101011
3 13 552
1173
0
3 NA 600 600 600 700 650 700
4 101011
3 18 8021709
00 750 750 750 750 700 650 700
5 101011
3 13 562
1191
0
7 NA 650 650 600 700 650 700
6 10101
1
3
6 233
499
0
0 650 650 650 650 700 650 700
r_free r_own
1
0
0
2
0
0
3
0 7740400
5
0 19565600> sum(!is.na(d$q1205)&is.na(d$r_free))[1] 0> sum(!is.na(d$q1206)&is.na(d$r_own))
[1] 0



Results of imputation of unit price
Original q1104
Imputed price
NA
>0
=0
>0

Cases
19286
65

> table(d$s11yn==1&is.na(d$q1104),!is.na(d$up)&d$up>0)
FALSE TRUE
FALSE 589333 167909
TRUE
0
478
> table(d$s11yn==1&!is.na(d$q1104)&d$q1104==0,!is.na(d$up)&d$up>0)
FALSE TRUE
FALSE 589333 164617
TRUE
0 3770# Summarized at household level> df<-CollapseBy(d,"identif",c("r_free","r_own"),HHID)> dim(df)Mongolia HSES 2010 Manual (Version 1.0)

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[1] 11198
3> head(df)identif r_free r_own
1
1
0.0 193715
2
2
0.0 329595
3
3
0.0 143620
44
0.0 332820
55 8922.5 129817
6
6 10320.0 241015> round(apply(df,2,function(x) weighted.mean(x,d13$hhweight)))
identif r_free r_own
5707
5519 31619> food.old<-food> food<-cbind(food,df[,2:3])> head(food)
identif u_pur r_pur u_free u_own r_free r_own
1
1
0 7150900
0.0 193715
2
2
0 8260300
0.0 329595
3
30 2167200
0.0 143620
440 50826
00
0.0 332820
550 6484400 8922.5 129817
6
60 9417000 10320.0 241015



Strategy of generating resampled micro data:
To append up (imputed unit price) to outfiles[[15]] by merging keys being identif and item.

> up<-d[,c("identif","item","up")]> dim(up)[1] 73970
3> head(up)identif item up
11359 10101 700
21192 10101 650
31173 10101 600
41709 10101 750
51191 10101 650
6499 10101 650> d<-outfiles[[16]]> dim(d)[1] 608408
8> d<-merge(d,up,by=c("identif","item"),all.x=T)> dim(d)[1] 608408
9> head(d)Mongolia HSES 2010 Manual (Version 1.0)

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1
2
3
4
5
6

identif item q1201 q1202 q1203 q1204 q1205 q1206 up
1 10101
2
NA
NA
NA
NA
NA NA
1 10102
2
NA
NA
NA
NA
NA NA
1 10103
2
NA
NA
NA
NA
NA NA
1 10104
1
10
10 5800
0 580
1 10105
2
NA
NA
NA
NA
NA NA
1 10106
2
NA
NA
NA
NA
NA NA

# imputed_up: imputed unit price computed by the author.
> d$up<-ifelse(!is.na(d$q1204)&d$q1204>0,NA,d$up)> colnames(d)[9]<-"imputed_up"> sum(!is.na(d$imputed_up))[1] 19357> outfile16.old<-outfiles[[16]]> outfiles[[16]]<-d7.3.3 Non-foodNon-food received free is already discussed in 7.2.3 Non-food, MONETARY EXPENDITURE.

# Variable of nfoodfree in data frame nfood.
> head(nfood[nfood$nfoodfree>0,])
identif nfood nfoodother nfoodgifts nfoodfree
21
21 1800
0
0
10499
44
44 23332
6667
3333
833
55
55 32642
15083
029166660
60 18208
0
0
1708
74
74 29475
30417
0
333
120
120 60737
32000002375

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7.4 Total household expenditureDefined summary file of household expenditure> hhexp<-cbind(food[,c(1:2,4:5,3,6:7)],nfood[-1])> head(hhexp)
identif u_pur u_free u_own r_pur r_free r_own nfood nfoodother nfoodgifts
11
000 71509
0.0 193715 82033
10458302
2000 82603
0.0 329595 86983
3629160
3
3
0
0
0 21672
0.0 143620 2342
15167
0
4
4
0
0
0 50826
0.0 332820 54676
1000002500
550
00 64844 8922.5 129817 57951
51917
0
6
6
0
0
0 94170 10320.0 241015 123475
2064342500
nfoodfree
1
0
2
0
3
0
4
0
5
0
6
0
> hhexp$food<-round(rowSums(hhexp[,c(2:7)]))> hhexp$monetary_exp<-rowSums(hhexp[,c(2,5,8:10)])> hhexp$ttexp<-round(rowSums(hhexp[,2:11]))> head(hhexp)
identif u_pur u_free u_own r_pur r_free r_own nfood nfoodother11000 71509
0.0 193715 82033
1045832
20
00 82603
0.0 329595 86983
3629163
3
0
0
0 21672
0.0 143620 2342
15167
4
4
0
0
0 50826
0.0 332820 54676
10000055000 64844 8922.5 129817 57951
51917
6
6
0
0
0 94170 10320.0 241015 123475
206434
nfoodgifts nfoodfree
food monetary_exp ttexp
100 265224
258125 451840
200 412198
532502 862097
300 165292
39181 182801
42500
0 383646
208002 540822
500 203584
174712 313452
62500
0 345505
426579 677914

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 Mean monthly expenditure per household by item
> t<-apply(hhexp[,-1],2,function(x) weighted.mean(x,hhinc.old$hhweight))> data.frame(item=names(t),mean=round(t),row.names=NULL)
item mean1
u_pur 107748
2
u_free 2516
3
u_own 2997
4
r_pur 33054
5
r_free 5519
6
r_own 31619
7nfood 279650
8nfoodother 59312
9nfoodgifts 12285
10nfoodfree 9402
11
food 183452
12 monetary_exp 492049
13
ttexp 544101



Generated data frame of trial estimation of household income and expenditure.

> hhincexp<-merge(hhinc,hhexp,by="identif")> dim(hhincexp)[1] 11198
21> head(hhincexp)
identif wage pension livestock agriculture business other ttinc u_pur
1
1
0 2205009167
000 229667
02
2 200000
66666
128750000 395416
0
3
3
0
16666
333
0
0
0 16999
0
4
4
0
81000
85083
0
0
0 166083055 10500005583
000 110583
0
6
6
0
50000
102166000 1521660u_free u_own r_pur r_free r_own nfood nfoodother nfoodgifts nfoodfree
10
0 71509
0.0 193715 82033
10458300
200 82603
0.0 329595 86983
36291600
3
0
0 21672
0.0 143620 2342
15167
0
0
4
0
0 50826
0.0 332820 54676
1000002500
05
00 64844 8922.5 129817 57951
51917
0
0
6
0
0 94170 10320.0 241015 123475
2064342500
0food monetary_exp ttexp
1 265224
258125 451840
2 412198
532502 862097
3 165292
39181 182801
4 383646
208002 540822
5 203584
174712 313452
6 345505
426579 677914> outfiles[[18]]<-hhincexp> Rnames[18]<-"HH_inc_exp"

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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 17 Basicvars will be adjusted by dividing by 0.8.

3. Resampled data files will be provided in CSV and R format.

4. Others
1) The imputed price data estimated by the author will be appended to data files; “Urban Diary”
and “Rural Food 7 days”.
2) The household-level income and expenditure data estimated by the author will be included.

Resampling# Selected 80% of hhid
> hhid<-outfiles[[17]]$identif # Basicvars> length(hhid)[1] 11198> range(hhid)[1]

1 11198> Int<-5> (St<-sample(1:5,1))[1] 4> hhid.selected<-hhid[(1:length(hhid))%%Int!=(St-1)]> length(hhid.selected)/length(hhid)[1] 0.7999643> hhid.selected<-hhid.selected[order(hhid.selected)]

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> head(hhid.selected)[1] 1 2 4 5 6 7# Resampled at the rate of 80%# outfiles[[1]] to outfiles[[18]]> Rnames.80<-paste(Rnames,".80",sep="")> Rnames.80[1] "Household.80""Individual.80"[3] "Llivestock.80""Llivestock Expenditure.80"[5] "Product.80""Crop.80"[7] "Agriultural Expenditure.80" "Enterprise.80"[9] "Other income.80""Remittance.80"[11] "Energy.80""Payment service.80"[13] "Durable.80""Non-Food.80"[15] "Urban Diary.80""Rural Food 7 day.80"[17] "Basicvars.80""HH_inc_exp.80"> outfiles.80<-list()> for(j in 1:18){+ d<-outfiles[[j]]+ outfiles.80[[j]]<-subset(d,is.element(d$identif,hhid.selected))+ }> length(outfiles.80)[1] 18> for(j in 1:18){+ cat(format(Rnames.80[j],width=26),": ",+ format(nrow(outfiles.80[[j]]),width=7),",",+ format(ncol(outfiles.80[[j]]),width=3),"\n")+ }Household.80:8958 , 75

Individual.80:

34719 , 73

Llivestock.80:

11023 ,

8

Llivestock Expenditure.80 :7387 ,

3

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Product.80:

20376 ,

9

Crop.80:1809 ,

8

Agriultural Expenditure.80 :8100 ,

3Enterprise.80:

1605 , 23

Other income.80:

205896 , 13Remittance.80:

17792 , 10

Energy.80:

53748 ,

8

Payment service.80:

116454 ,6

Durable.80:

385194 ,5

Non-Food.80: 3171132 ,6

Urban Diary.80:

606074 , 17

Rural Food 7 day.80:

486774 ,Basicvars.80:

8958 , 13

HH_inc_exp.80:8958 , 21

9# Adjusted weight in Basicvars> d<-outfiles.80[[17]]> d$WT<-d$hhweight/0.8> outfiles.80[[17]]<-d> sum(d$WT)[1] 709014.9> sum(outfiles[[17]]$hhweight)[1] 709189> save(outfiles.80,file="Resampled_80%.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""Llivestock Expenditure_80.csv"[5] "Product_80.csv""Crop_80.csv"[7] "Agriultural Expenditure_80.csv" "Enterprise_80.csv"

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130[9] "Other income_80.csv""Remittance_80.csv"[11] "Energy_80.csv""Payment service_80.csv"[13] "Durable_80.csv""Non-Food_80.csv"[15] "Urban Diary_80.csv""Rural Food 7 day_80.csv"[17] "Basicvars_80.csv""HH_inc_exp_80.csv"> for(j in 1:18){+ cmd<-paste("write.csv(outfiles.80[[",j,"]],'",CSVnames[j],"',row.names=F)",sep="")+ eval(parse(text=cmd))+ }# Resampled data set in csv format> 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] "HH_inc_exp_80.csv""Household_80.csv"[9] "Individual_80.csv""Llivestock Expenditure_80.csv"[11] "Llivestock_80.csv""Non-Food_80.csv"[13] "Other income_80.csv""Payment service_80.csv"[15] "Product_80.csv""Remittance_80.csv"[17] "Rural Food 7 day_80.csv""Urban Diary_80.csv"

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Chapter 10. References: Imputed Rent
[REFERENCE]
As described, imputed rent was not evaluated in Chapter 8. Here, imputed rent was discussed, but
yet finalized.
Imputed rent
data frame: 01 Household
q0818: How was acquired (RENT or not)q0820: If you wanted to rent, how much
If don’t know write “99”q0821: How much do you pay for rent
> d<-outfiles[[1]]> dim(d)[1] 1119875


If q0818 is RENTING, q0821 should be answered. If q0818 is not RENTING, q0820
should be answered.



Among 270 RENTING, the amount of rent is positive for 262 cases. In case that theamount of rent is zero, imputed rent should be estimated.

> m1<-table(d$q0818,d$q0821==0,useNA="ifany")> colnames(m1)<-c("q0821>0","q0821=0","NA")> rownames(m1)<-c(names(attributes(d)$label.table["q0818"][[1]]),"<NA>")> addmargins(m1)q0821>0 q0821=0
NA SumRENTING262
8
0 270
INHERITED
00 1521 1521
GIFT
00 795 795
BUILT BY OURSELVES
00 4034 4034
PURCHASED
00 3139 3139
PRIVATIZED
0
0 728
728
OTHER
0
0 299 299<NA>0
0 412 412Sum
262
8 10928 11198



Out of eight households with rent being zero, three are ger, four are detachedhouse, and the other one is “other dormitory accommodation”, while all are owned
by private.

> table(d[!is.na(d$q0818)&d$q0818==1&d$q0821==0, "q0803"])
1 3 7
3 4 1
> table(d[!is.na(d$q0818)&d$q0818==1&d$q0821==0, "q0817"])

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3
8



Out of 11,198 records, 412 NAs found in q0818. However, they are regarded as NonRENTING, because q0820 is responded. Consequently, imputed rent q0820 is filled
in 2,528 cases, and 8,400 cases should be imputed.

> m2<-table(d$q0818,d$q0820==99,useNA="ifany")> colnames(m2)<-c("q0820 filled","Don't know","<NA>")> rownames(m2)<-c(names(attributes(d)$label.table["q0818"][[1]]),"<NA>")> addmargins(m2)

RENTINGINHERITEDGIFT
BUILT BY OURSELVESPURCHASEDPRIVATIZED
OTHER
<NA>
Sum



q0820 filled Don't know <NA> Sum
00 270 2702301291
0 1521
103
692
0 795
605
3429
0 40341081
2058
0 3139
365
363
0 728
54
245
0 299
90
322
0 412
2528
8400 270 11198

The type of ownership of 8,400 households to be imputed is as follows;> t1<-table(d[(is.na(d$q0818)|d$q0818!=1)&d$q0820==99, "q0817"])> names(t1)<-c(names(attributes(d)$label.table["q0817"][[1]]))> addmargins(t1)STATE ORGANIZATION'SPRIVATE
Sum
177
145
8078
8400



The type of dwellings of 8,400 households to be imputed is as follows;> t2<-table(d[(is.na(d$q0818)|d$q0818!=1)&d$q0820==99, "q0803"])> names(t2)<-c(names(attributes(d)$label.table["q0803"][[1]]))> addmargins(t2)GER
BUILDING
4506
803
DETACHED HOUSE
APARTMENT1943
989
STUDENT'S DORMITORY
WORKER'S DORMITORY
1466
OTHER DORMITORY ACCOMODATIONNON-LIVING QUARTERS
50
22
OTHER
Sum
7
8400

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133#####################################################################SUMMARY
Estimation of imputed rent for 8,400 sample household is essential.
# Data frame of records with rent or imputed rent
> d2<-subset(d,(!is.na(d$q0820)&d$q0820!=99)|(!is.na(d$q0821)&d$q0821>0))> dim(d2)[1] 2790 75
Depended variable: y = q0820 + q0821
q0820: imputed rent
q0821: rent
> d2$y<-rowSums(d2[,c("q0820","q0821")],na.rm=T)> head(d2[,c("q0820","q0821","y")])q0820 q0821
y
189 10000
NA 10000
229 15000
NA 15000
232 35000
NA 35000
233 30000
NA 30000
234 25000
NA 25000
235 50000
NA 50000> head(d2[is.na(d2$q0820),c("q0820","q0821","y")])q0820 q0821
y328
NA 30000 30000
514
NA 50000 50000
589
NA 30000 30000
590
NA 100000 100000
594
NA 150000 150000
634
NA 30000 30000

Possible independent variable:
q0803: type of dwellings# No missing value for q0803# Median of rent by type of dwellings> t<-tapply(d2$y,d2$q0803,median)> names(t)<-c(names(attributes(d)$label.table["q0803"][[1]]))> t
GER
BUILDING
20000
50000
DETACHED HOUSE
APARTMENT
50000
200000STUDENT'S DORMITORY
WORKER'S DORMITORY
20000
30000
OTHER DORMITORY ACCOMODATIONNON-LIVING QUARTERS
62000
32500

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OTHER
150000q0804: number of rooms# q0804 is available in 680 cases.
> table(is.na(d2$q0804))
FALSE TRUE
2110 680# Median of rent by number of rooms> t<-tapply(d2$y,d2$q0804,median)
> t
1
2
3
4
5
6
50000 120000 200000 200000 225000 150000

78980000 1000000 100000

q0808: living area
# q0808 is available in 680 cases.
> table(is.na(d2$q0808))
FALSE TRUE
2110 680

q0817: type of ownership# No missing value for q0803> table(d2$q0817,useNA="ifany")
12
3
60 30 2700
# Median of rent by type of ownership> t<-tapply(d2$y,d2$q0817,median)> names(t)<-c(names(attributes(d)$label.table["q0817"][[1]]))> t
STATE ORGANIZATION'SPRIVATE
45000
45000
60000



Hedonic approach for estimating imputed rent should be applied.

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

According to the delegates from Mongolia, the process of estimating imputed rent is asfollows;

Step 1: Hedonic approach using multiple regression to estimate selling price of dwelling.

Four models for the four different dwelling types;
1 GER
2 Apartment
3 House4 Others(To clarify the four dwelling types!)

Dependent variable: selling price(To clarify the variable!)

Independent variables as the next;
No

Dwelling

Independent variables

type
1

GER

the number of walls, roof, and floor conditions, how long living in, heating,electricity, water supply and sewage systems, toilets, phone, province andmonths2

Apartment

number of rooms, walls, roof. floor conditions, the total area of apartment, living
area of apartment, how long living in the apartment, heating, electricity, watersupply, sewage systems, toilets, phone, province location and months

3

House

number of rooms, walls, roof and floor conditions, the total area of house, living
area of house, heating, electricity, water supply. sewage systems, toilets, phone
and province location and months

4

Othersa very small percentage of households accounts for in this dwelling type (around1%). Generally, hostels are considered in this group and median value isestimated based on collected rent information for hh whose information is not
valid.

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Step 2: Results of median regression

Note: The blow tables are the results of median regression by STATA.

dwe==1
Median regression

Number of obs =4746

Raw sum of deviations 1718.622 (about 6.3801241)
Min sum of deviations 1346.963

lnvaluedwe

Pseudo R2

Coef.

Std. Err.

=t

0.2163P>t[95% Conf.

Interval]

gwalls0.1885615

0.0112428

16.77

0

0.1665203

0.210603

groof

0.0351366

0.0292267

1.2

0.229

-0.0221615

0.092435

gframe0.013976

0.0291815

0.48

0.632

-0.0432334

0.071185_Igfloor_2-0.0456944

0.0157741

-2.9

0.004

-0.0766191-0.01477_Igfloor_3-0.0935462

0.0361376

-2.59

0.01

-0.1643928-0.0227agex-0.006825

0.0004812-14.180-0.0077684-0.00588_Iheating_2

0.0138355

0.0457945

0.3

0.763

-0.0759431

0.103614_Iheating_3

0.1179499

0.1543638

0.76

0.445

-0.1846757

0.420576_Iheating_5

0.0376877

0.0646191

0.58

0.56

-0.0889962

0.164372_Ilight_2-0.0466428

0.0287494

-1.62

0.105

-0.1030052

0.00972_Ilight_3

0.052817

0.0248093

2.13

0.033

0.0041791

0.101455_Ilight_4-0.0338924

0.061295

-0.55

0.58

-0.1540595

0.086275_Ilight_5-0.1549281

0.112692

-1.37

0.169

-0.3758573

0.066001_Ilight_6-0.0705137

0.0357543

-1.97

0.049

-0.1406089-0.00042_Ilight_7-0.0682043

0.0685604

-0.99

0.32

-0.2026149

0.066206_Iwater_2-0.1070218

0.1346574

-0.79

0.427

-0.3710135

0.15697_Iwater_3-0.119645

0.1040153

-1.15

0.25

-0.3235638

0.084274_Iwater_4-0.1012666

0.105461

-0.96

0.337

-0.3080198

0.105487_Iwater_5-0.1994121

0.1048443

-1.9

0.057

-0.4049563

0.006132_Iwater_6-0.1358363

0.1050804

-1.29

0.196

-0.3418433

0.070171_Iwater_7-0.0995617

0.1085101

-0.92

0.359

-0.3122926

0.113169_Isewage_2-0.1060924

0.0170491

-6.22

0

-0.1395166-0.07267_Itoilet_2-0.0387083

0.081499

-0.47

0.635

-0.1984847

0.121068_Itoilet_3

0.176141

0.0629151

2.8

0.005

0.0527978

0.299484_Itoilet_4

0.1991171

0.0658506

3.02

0.003

0.0700189

0.328215

phone-0.1186198

0.0380601

-3.12

0.002

-0.1932355-0.044_Iaimag_2-0.4661354

0.0582544-80-0.5803413-0.35193_Iaimag_3-0.0621969

0.039964

-1.56

0.12

-0.1405451

0.016151_Iaimag_4-0.1488411

0.0444382

-3.35

0.001

-0.2359609-0.06172_Iaimag_5-0.0824533

0.04146

-1.99

0.047

-0.1637345-0.00117_Iaimag_6-0.3326422

0.0572904

-5.81

0

-0.4449583-0.22033_Iaimag_7-0.2739833

0.0519195

-5.28

0

-0.3757699-0.1722_Iaimag_8

0.2461214

0.0416742

5.91

00.1644204

0.327823

Mongolia HSES 2010 Manual (Version 1.0)

137

_Iaimag_9-0.279529

0.0430994

-6.49

0

-0.3640241_Iaimag_10_Iaimag_11-0.3513508

0.035401

0.1083414

0.0445406_Iaimag_12-0.059846_Iaimag_13_Iaimag_14_Iaimag_15

-9.92

0

-0.4207534-0.28195

2.43

0.015

0.0210208

0.195662

0.0441308

-1.36

0.175

-0.146363

0.026671-0.308157

0.0584383

-5.27

0

-0.4227235-0.19359-0.1533168

0.0411719

-3.72

0

-0.234033-0.0726-0.2511763

0.0428187

-5.87

0

-0.3351211-0.16723_Iaimag_16-0.4179453

0.0420522

-9.94

0

-0.5003875-0.3355_Iaimag_17-0.7043658

0.0384852

-18.3

0

-0.779815-0.62892_Iaimag_18-0.0667636

0.0414663

-1.61

0.107

-0.1480571

0.01453_Iaimag_19

0.0342872

0.0808673

0.42

0.672

-0.1242507

0.192825_Iaimag_20-0.3034644

0.0327211

-9.27

0

-0.3676133-0.23932_Iaimag_21-0.5192496

0.0744049

-6.98

0

-0.6651182-0.37338_Imonth2_2

0.0602147

0.0314923

1.91

0.056

-0.0015249

0.121954_Imonth2_3-0.0134153

0.0308574

-0.43

0.664

-0.0739103

0.04708_Imonth2_4-0.0210.0316429

-0.66

0.507

-0.083035

0.041035_Imonth2_5-0.0349979

0.0321451

-1.09

0.276

-0.0980174

0.028022_Imonth2_6-0.0195975

0.0313093

-0.63

0.531

-0.0809785

0.041784_Imonth2_7

0.0349003

0.0315626

1.11

0.269

-0.0269773

0.096778_Imonth2_8

0.0090852

0.0313866

0.29

0.772

-0.0524472

0.070618_Imonth2_9-0.0173485

0.030964

-0.56

0.575

-0.0780526

0.043356_Imonth2_10

0.0138717

0.0313057

0.44

0.658

-0.0475022

0.075246_Imonth2_11

0.0085196

0.0319572

0.27

0.79

-0.0541316

0.071171_Imonth2_12-0.0381905

0.0313511

-1.22

0.223

-0.0996534

0.023273

5.639698

0.1444908

39.03

0

5.356428

5.922968_cons

dwe==2FLATMedian regression

Number of obs =1933

Raw sum of deviations 1223.058 (about 10.158616)
Min sum of deviations 611.5788

lnvaluedwe

Coef.

Std. Err.

Pseudo R2

=

t

P>t

0.5000[95% Conf.

Interval]rooms

0.199610.020006

9.98

00.160374

0.238847_Iwalls_2

0.019504

0.028779

0.68

0.498

-0.03694

0.075946_Iwalls_3-0.33921

0.065994-5.14

0-0.46864-0.20978_Iwalls_4

0.022355

0.128872

0.17

0.862

-0.23039

0.275104_Iwalls_5-0.02177

0.10898

-0.2

0.842

-0.2355

0.191965_Iroof_2

0.060397

0.031169

1.94

0.053

-0.00073

0.121527_Iroof_3

0.038684

0.052586

0.74

0.462

-0.06445

0.141817_Iroof_4

0.114858

0.052343

2.19

0.028

0.0122010.217515_Ifloor_2-0.00191

0.027545

-0.07

0.945

-0.05594

0.052109

Mongolia HSES 2010 Manual (Version 1.0)

-0.19503

138_Ifloor_3

0.844688

0.276418

3.06

0.002

0.302568

1.386809_Ifloor_4

0.111509

0.056349

1.98

0.048

0.000995

0.222022

livarea0.001309

0.001685

0.78

0.437

-0.0020.004613

totarea

0.003798

0.001463

2.6

0.01

0.000929

0.006668

agex

0.001684

0.000847

1.99

0.047

2.26E-05

0.003345_Iheating_2-0.40311

0.095768-4.21

0-0.59093-0.21529_Iheating_3-0.31216

0.162536

-1.92

0.055

-0.63093

0.006608_Iheating_5-0.98302

0.141783-6.93

0-1.26109-0.70496_Ilight_2

0.023036

0.07512

0.31

0.759

-0.12429

0.170364_Ilight_3-2.35961

0.488654-4.83

0-3.31797-1.40124_Ilight_4-0.00642

0.469456

-0.01

0.989

-0.92713

0.914295_Ilight_6-1.84803

0.477993-3.87

0-2.78549-0.91057_Iwater_2-0.28781

0.044217-6.51

0-0.37453-0.20109_Iwater_3-0.42833

0.110657-3.87

0-0.64535-0.21131_Iwater_4-0.62150.205321

-3.03

0.003

-1.02419-0.21882_Iwater_5-0.36317

0.123695

-2.94

0.003

-0.60577-0.12058_Iwater_6-1.98170.301384-6.58

0-2.57279-1.39062_Iwater_7-1.28385

0.198123-6.48

0-1.67242-0.89529_Isewage_2-0.32839

0.053325-6.16

0-0.43297-0.22381_Itoilet_2-0.612650.087882-6.97

0-0.78501-0.44029_Itoilet_3-0.4205

0.07024-5.99

0-0.55826-0.28275_Itoilet_4-0.501040.25478

-1.97

0.049

-1.00072-0.00135

phone

0.035818

0.023916

1.5

0.134

-0.011090.082723_Iaimag_2-0.66072

0.370014

-1.79

0.074

-1.38641

0.06496_Iaimag_3-0.13636

0.231522

-0.59

0.556

-0.59043

0.317708_Iaimag_4-0.77724

0.373211

-2.08

0.037

-1.50919-0.04528_Iaimag_5-0.15526

0.183852

-0.84

0.398

-0.51584

0.205311_Iaimag_6-0.46521

0.1699

-2.74

0.006

-0.79842-0.13199_Iaimag_7-0.59793

0.170688-3.5

0-0.93269-0.26318_Iaimag_8-0.27226

0.187293

-1.45

0.146

-0.63958

0.095067_Iaimag_9

0.009597

0.208285

0.05

0.963

-0.3989

0.418092_Iaimag_10-0.03334

0.213289

-0.16

0.876

-0.45165

0.38497_Iaimag_11-0.031290.190986

-0.16

0.87

-0.40586

0.343277_Iaimag_12-0.10238

0.188205

-0.54

0.587

-0.47149

0.266739_Iaimag_13-0.55688

0.173598

-3.21

0.001

-0.89735-0.21642_Iaimag_14-0.14388

0.173794

-0.83

0.408

-0.48473

0.196969_Iaimag_15-0.7686

0.23997

-3.2

0.001

-1.23924-0.29796_Iaimag_16-0.16712

0.206773

-0.81

0.419

-0.57265

0.238413_Iaimag_17-0.42856

0.225134

-1.9

0.057

-0.8701

0.012978_Iaimag_18-0.49959

0.183193

-2.73

0.006

-0.85887-0.1403_Iaimag_19-0.63368

0.170259-3.72

0-0.9676-0.29976_Iaimag_20

0.244196

0.161713

1.51

0.131

-0.07296

0.561353_Iaimag_21-0.18442

0.168968

-1.09

0.275

-0.51581

0.146963_Imonth2_2-0.03007

0.052211

-0.58

0.565

-0.13247

0.072329_Imonth2_3-0.01888

0.060783

-0.31

0.756

-0.13809

0.10033_Imonth2_4

0.01190.051806

0.23

0.818

-0.0897

0.113503_Imonth2_5

0.090297

0.055272

1.63

0.102

-0.01811

0.198699_Imonth2_6

0.05668

0.055723

1.02

0.309

-0.05261

0.165965

Mongolia HSES 2010 Manual (Version 1.0)

139

_Imonth2_7

0.046116

0.054052_Imonth2_8

0.09897_Imonth2_9

0.052618_Imonth2_10

0.029813_Imonth2_11_Imonth2_12_cons

dwe==3

0.85

0.394

-0.05989

0.152125

0.055064

1.8

0.072

-0.00902

0.206963

0.055651

0.95

0.345

-0.05653

0.161764

0.056511

0.53

0.598

-0.081020.140644

0.067342

0.05343

1.26

0.208

-0.03745

0.172130.050397

0.054806

0.92

0.358

-0.05709

0.157884

9.449944

0.169124

55.88

09.118253

9.781635

HOUSEMedian regression
Raw sum of deviations

Number of obs =Min sum of deviations 2075.186

lnvaluedwe
rooms

3559

2883.78 (about 8.5491781)

Coef.

Std. Err.

Pseudo R2

=

t

P>t

0.2804[95% Conf.

Interval]

0.091462

0.0199784.58

00.052291

0.130632_Iwalls_2-0.0595

0.065985

-0.9

0.367

-0.18888

0.069868_Iwalls_3-0.12921

0.040445

-3.19

0.001

-0.20851-0.04991_Iwalls_4-0.32455

0.159199

-2.04

0.042

-0.63668-0.01241_Iwalls_5-0.22879

0.076954

-2.97

0.003

-0.37966-0.07791_Iroof_2-0.05308

0.03608

-1.47

0.141

-0.12382

0.017659_Iroof_3-0.10386

0.04657

-2.23

0.026

-0.19517-0.01256_Iroof_4-0.53917

0.072339-7.45

0-0.681-0.39734_Ifloor_2

0.029805

0.049814

0.6

0.55

-0.06786

0.127473_Ifloor_3

0.051475

0.109103

0.47

0.637

-0.16244

0.265387_Ifloor_4

0.075637

0.103841

0.73

0.466

-0.12796

0.279232

livarea-0.00525

0.001263-4.15

0-0.00772-0.00277

totarea

0.013376

0.00126510.57

00.010896

0.015856

agex-0.001790.001541

-1.16

0.246

-0.00481

0.001235_Iheating_2-0.34248

0.077312-4.43

0-0.49406-0.1909_Iheating_3

0.170914

0.098772

1.73

0.084

-0.02274

0.364571_Iheating_5-0.43423

0.279687

-1.55

0.121

-0.9826

0.114133_Ilight_2-0.05067

0.071352

-0.71

0.478

-0.19056

0.089227_Ilight_3-0.30242

0.094896

-3.19

0.001

-0.48848-0.11637_Ilight_4-0.41103

0.353269

-1.16

0.245

-1.10366

0.281607_Ilight_5-0.48074

0.855126

-0.56

0.574

-2.15733

1.19586_Ilight_6-0.63502

0.252992

-2.51

0.012

-1.13104-0.13899_Ilight_7

0.106271

0.60832

0.17

0.861

-1.08643

1.29897_Iwater_2-0.52493

0.148121-3.54

0-0.81534-0.23452_Iwater_3-0.56502

0.11462-4.93

0-0.78975-0.34029_Iwater_4-0.64628

0.12331-5.24

0-0.88805-0.40452

Mongolia HSES 2010 Manual (Version 1.0)

140

_Iwater_5-0.39988

0.116434

-3.43

0.001

-0.62817-0.1716_Iwater_6-0.76808

0.131757-5.83

0-1.02641-0.50976_Iwater_7-0.69284

0.168579-4.11

0-1.02336-0.36232_Isewage_2-0.1379

0.032282-4.27

0-0.20119-0.0746_Itoilet_2-0.56941

0.179466

-3.17

0.002

-0.92128-0.21754_Itoilet_3-0.37884

0.106447-3.56

0-0.58755-0.17014_Itoilet_4-0.09309

0.157196

-0.59

0.554

-0.40130.215111

phone

0.182302

0.058673

3.11

0.002

0.067265

0.297338_Iaimag_2-0.35909

0.10493

-3.42

0.001

-0.56482-0.15336_Iaimag_3

0.388996

0.172416

2.26

0.024

0.050949

0.727043_Iaimag_4-0.07856

0.110894

-0.71

0.479

-0.29598

0.138861_Iaimag_5

0.254211

0.193905

1.31

0.19

-0.12597

0.634388_Iaimag_6

0.50757

0.124835

4.07

00.262814

0.752327_Iaimag_7-0.54767

0.11412-4.8

0-0.77141-0.32392_Iaimag_8

0.099079

0.171973

0.58

0.565

-0.23810.436256_Iaimag_9

0.239067

0.128823

1.86

0.064

-0.01351

0.491643_Iaimag_10

0.627154

0.137274.57

00.358017

0.896291_Iaimag_11

0.628868

0.1547014.07

00.325555

0.932181_Iaimag_12

0.470303

0.128144

3.67

00.219059

0.721548_Iaimag_13-0.03457

0.091731

-0.38

0.706

-0.21442

0.145286_Iaimag_14-0.29076

0.098696

-2.95

0.003

-0.48426-0.09725_Iaimag_15-0.29738

0.118975

-2.5

0.012

-0.53065-0.06411_Iaimag_16

0.104317

0.13853

0.75

0.451

-0.16729

0.375925_Iaimag_17

0.014869

0.09572

0.16

0.877

-0.17280.202542_Iaimag_18-0.10296

0.109649

-0.94

0.348

-0.31794

0.112023_Iaimag_19-0.12085

0.1169

-1.03

0.301

-0.35005

0.108348_Iaimag_20

0.686429

0.078664

8.73

00.532196

0.840661_Iaimag_21

0.319251

0.124334

2.57

0.01

0.075476

0.563025_Imonth2_2

0.150358

0.071883

2.09

0.037

0.009422

0.291295_Imonth2_3

0.052999

0.067332

0.79

0.431

-0.07901

0.185013_Imonth2_4

0.024323

0.073479

0.33

0.741

-0.11974

0.168389_Imonth2_5

0.085828

0.068438

1.25

0.21

-0.04835

0.220011_Imonth2_6

0.105587

0.070912

1.49

0.137

-0.03345

0.244619_Imonth2_7

0.204081

0.07146

2.86

0.004

0.063974

0.344189_Imonth2_8

0.150354

0.071019

2.12

0.034

0.011112

0.289597_Imonth2_9

0.079974

0.071806

1.11

0.265

-0.06081

0.220761_Imonth2_10

0.246048

0.0694293.54

00.109923

0.382173_Imonth2_11

0.113435

0.070065

1.62

0.106

-0.02394

0.250807_Imonth2_12

0.242518

0.069675

3.48

0.001

0.105911

0.379125_cons

8.979551

0.135583

66.23

08.713722

9.24538

Mongolia HSES 2010 Manual (Version 1.0)141

dwe==4

OTHER

scalar usd = 1355.93
count if dwe==4
tab q0820 if dwe==4, m
gen x = q0820/scalar(usd) if dwe==4
replace x=. if q0820==99
tab xegen y = median(x) if dwe==4, by(dwelling)
replace valuex = x if dwe==4 & x!=.
replace valuex = y if dwe==4 & x==.
summ dwe value* if dwe==4
drop x y

Step 3: Estimation of imputed rent by using the estimated coefficients of independent
variables, as the next;

Monthly imputed rent = estimated value of dwelling * r / 12

where, r is the depreciation rate;
Dwelling type

Depreciation period

Depreciation rate (r)GER

17 years

0.06 (= 1/ 17)

Apartment, House

33 years

0.03 (= 1/ 33)

Mongolia HSES 2010 Manual (Version 1.0)

142

Attachments
1. The questionnaire
Four types of questionnaire are attached.

1.1 SES-1: Diary for the keeping in households (the first 10 days of a month) for the households inthe capital and aimag center.
Note: The diary sheets for the second 10 days of a month and the third 10 days of a month areomitted.

1.2 SES-2a: Consumption of food and other frequently purchased commodities (from diary) for thehouseholds in the capital and aimag center (Section 11)

1.3 SES-2b: Consumption of food during the past 7 days (by recall) for the rural households /soumcenter and herders/ (Section 12)

1.4 SES-3: Section 0 to section 10

2. Data dictionary: Database documentation

Errors in data dictionary

Next to 28 q0707 in hhold

Variable of cluster2 is missing.

3 q0102 in 02_indiv“7 Brother/sister in law” should be read as “7 son/daughter in law”.

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Translation mistake
Category 7 “Brother/sister in law” in relationship to head should be read as“Son/daughter in law”.
Three evidences for this are shown below.
Evidence 1: Comparison of distribution by categories between HSES and Census.
Mongolia - HSES 2010

http://catalog.ihsn.org/index.php/catalog/4720/data_dictionary#page=F2&tab=datadictionary(Accessed on 13 August 2016)

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Mongolia PHC 2010: Population and housing census

http://web.nso.mn/nada/index.php/catalog/89/datafile/F3 (Accessed on 13 August 2016)

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Evidence 2: Translation from local language

The right side is the results of Google Translate from Mongolian to English.
The left side is the response categories of relationship to head in the Mongolian
questionnaire of HSES 2007/08, which is the same as HSES 2010.

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Evidence 3: Micro data
q0102 q0103 q0105y q0106 q0107

q0108

q0109

identif ind_id relation sex age marital spouseID fatherID motherID
620

155

1

1

1 68

1

2

99

99

621

155

2

2

2 67

1

1

99

99

622

155

3

3

1 33

1

4

1

2

623

155

4

7

2 31

1

3

98

98

624

155

5

9

1

NA

NA

3

4

4

The above is the sample household with the identifier being 155, which has fivehousehold members. There are two couples in the household; one is the head (theind_id=1) and his spouse (2), and the other is their son (3) and his wife (4),that is, their daughter in law, whose relationship code to the head is 7.

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NSO, Mongolia

SES-1

All staffs at the all level of NSO should keep your responses confidential in accordance with Mongolian Legislation on "Statistics" and"Confidentiality of private information".

SOCIO-ECONOMIC SURVEYDIARY FOR THE KEEPING IN HOUSEHOLDSThe first 10 days of a month

Quarter

Cluster number

NAME OF HOUSEHOLD HEAD

ADDRESSNAME OF INTERVIEWER

CodeDATE OF VISITS

YEAR

MONTH

DAY

RESULT*

VISIT 1:VISIT 2:

Result code*

VISIT 3:

Filled sufficiently -1

VISIT 4:

Filled insufficiently -2

NOTE:

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Instruction to fill up dairy in households
Record 1: Food consumption of the households
The monthly food consumption of household members shall be recording by following times dividedinto 3 groups. Namely,- First ten days /1-10/- Second ten days /11-20/- Third ten days /21 to the end of month/
Record 1 consists following sections:
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. Every row has number ed following 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 be recorded consumed food items of the particular day on appropriate page as follows.
1) Household member shall be specified name of the consumed food items in (12.01). Interviewer will be coded them later on. For example, mutton, imported rice, big red apple andvegetable oil etc.
2) Household member will be recorded quantities and units of consumed food items in (12.02). Although the standard units as kilogram, liter, piece etc. have using to measure sometimes
any member of the particular household could purchase certain food items by non-standard units from the local market. In this case, household members should be certainly recorded units as
own possible ways. For instance, 1 kilogram, 350 grams, 4 apple, half bottle or one packet, etc.
Note: Interviewers should convert each food items measured by non-standard units to the standard units and identify total quantities. In the 11th section, the standard units should record all fooditems. For example, if respondent recorded half sack rice, in this case interviewer should convert to the kilogram.
3) The main sources of consumed food items would record in (12.03). The household member would record correspond code from the given codes in the column, if it purchased should
record its unit price. For example, suppose that member has puchased 3 kg potatoes and its unit price is 350 tugrigs, and total cost was 1050 tugrigs. In this case. he/she should record unit
price is 350 tugrigs.
- The Interviewers should fill up last two columns.
- (12.04) Codes for food items: Should record correspond codes have taken from detailed lists of food items.
- (12.05) Converted quantities into the standard units: Interviewers (12.02) should convert each food items measured by non-standard units to the standard units. Explain it above. If
those items have recorded by standard units, interviewers directly copied from the (12.02) column.
Record 2: Purchased non-food items of the household
Household should record purchased non-food items in particular day. They can be having nothing purchased in some days. They can be having purchased many items in some days. In thiscase, there is not adequate space to record them in the particular page; it can be proceeding in the page for next day.

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

1

5

Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

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

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

2

5

Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

0201
0202
0203
0204
0205
0206
0207
0208
0209
0210
0211
0212
0213
0214
0215
0216
0217
0218
0219
0220
0221
0222
0223
0224
0225
0226
0227
0228
0229
0230

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

3

5

Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

0301
0302
0303
0304
0305
0306
0307
0308
0309
0310
0311
0312
0313
0314
0315
0316
0317
0318
0319
0320
0321
0322
0323
0324
0325
0326
0327
0328
0329
0330

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

45

Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

0401
0402
0403
0404
0405
0406
0407
0408
0409
0410
0411
0412
0413
0414
0415
0416
0417
0418
0419
0420
0421
0422
0423
0424
0425
0426
0427
0428
0429
0430

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

55

Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

0501
0502
0503
0504
0505
0506
0507
0508
0509
0510
0511
0512
0513
0514
0515
0516
0517
0518
0519
0520
0521
0522
0523
0524
0525
0526
0527
0528
0529
0530

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

6

5

Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

0601
0602
0603
0604
0605
0606
0607
0608
0609
0610
0611
0612
0613
0614
0615
0616
0617
0618
0619
0620
0621
0622
0623
0624
0625
0626
0627
0628
0629
0630

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

7

5

Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

0701
0702
0703
0704
0705
0706
0707
0708
0709
0710
0711
0712
0713
0714
0715
0716
0717
0718
0719
0720
0721
0722
0723
0724
0725
0726
0727
0728
0729
0730

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

8

5

Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

0801
0802
0803
0804
0805
0806
0807
0808
0809
0810
0811
0812
0813
0814
0815
0816
0817
0818
0819
0820
0821
0822
0823
0824
0825
0826
0827
0828
0829
0830

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

95

Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

0901
0902
0903
0904
0905
0906
0907
0908
0909
0910
0911
0912
0913
0914
0915
0916
0917
0918
0919
0920
0921
0922
0923
0924
0925
0926
0927
0928
0929
0930

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FOOD CONSUMPTION
DAY

1

3

2

FOR OFFICE USE

Write sources
LINE NUMBER

4
Write the full description of
the item consumed

Write the quantity
consumed and thename of the unit ofmeasurement

10

5Purchased - 1 Received
free - 2
Own production - 3

Code

ITEM CODECONSUMEDQUANTITYCODE

QUANTITY

If purchased, write
unit price

QUANTITY, UNITITEMSTUGRIG

1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030

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Ху

NSO, MONGOLIA

SES-2aAll staffs at the all level of NSO should keep your responses confidential in accordance with Mongolian Legislation on "Statistics" and "Confidentiality of private information".

THE SOCIO-ECONOMIC SURVEY

HOUSEHOLD ID
Quarter

NAME OF HOUSEHOLD HEADINTERVIEWER

Cluster number

HHNo

ADDRESS

Code

SUPERVISOR

Code

Did any visitor stay here with your household for the last month?

Number(Specify number of visitors)
How many days?

person/day(Number of visitors multiple by days stayed here)

For the households in the capital and aimag center
NOTE:

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SECTION 11: CONSUMPTION OF FOOD AND OTHER FREQUENTY PURCHASED COMMODITIES (FROM DIARY)
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGFIRST 10 DAYS /1-10
1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
FIRST 10 DAYS

ITEMS

UNIT

SECOND 10 DAYS /11- 20(11.01)
MAIN SOURCES OF CONSUMED ITEMS 1.TOTAL ..[ITEM]..
CONSUMED
2.
3.4.DURING THE
Purchased
Received
Own
SECOND 10 DAYS
free
production

QUANTITY

THIRD 10 DAYS /21-30, 31(11.02)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

3.Received
free

QUANTITY

4.Own
production

1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
THIRD 10 DAYSMONTHLY AVERAGE(11.03)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

QUANTITY

3.Received
free

4.Own
production(11.04)
OF UNIT
Write to strike an average
unit prices of 30 days/

TUGRUGS / [UNIT]

10100 FLOUR AND FLOUR PRODUCTS
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

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 Pizza

N/A

/ N/A

N/A

/ N/A

10201 Mutton

Kg

/ Kg

10202 Beef

Kg

/ Kg

10203 Goat meat

Kg

/ Kg

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

10115 Other flour and flour products
10199

Sub total 10102 - 10115

10200 MEAT, MEAT PRODUCTS

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SECTION 11: CONSUMPTION OF FOOD AND OTHER FREQUENTY PURCHASED COMMODITIES (FROM DIARY)
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGFIRST 10 DAYS /1-10
1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
FIRST 10 DAYS

ITEMS

UNIT

SECOND 10 DAYS /11- 20(11.01)
MAIN SOURCES OF CONSUMED ITEMS 1.TOTAL ..[ITEM]..
CONSUMED
2.
3.4.DURING THE
Purchased
Received
Own
SECOND 10 DAYS
free
production

QUANTITY

THIRD 10 DAYS /21-30, 31(11.02)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

3.Received
free

QUANTITY

4.Own
production

1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
THIRD 10 DAYSMONTHLY AVERAGE(11.03)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

QUANTITY

3.Received
free

4.Own
production(11.04)
OF UNIT
Write to strike an average
unit prices of 30 days/

TUGRUGS / [UNIT]

10215 Canned meat

Kg

/ Kg

10217 Other meat, meat products

N/A

/ N/A

10301 Fish

Kg

/ Kg

10302 Dried, smoked, salted fish

Kg

/ Kg

10303 Canned fish

Kg

/ Kg

10304 Other fish and seafood

Kg

/ Kg

10401 Milk

Lt

/ Lt

10402 Youghurt

Lt

/ Lt

10403 Eggs

Nb

/ Nb

10404 Dried curds

Kg

/ Kg

10405 Horse milk, l

Lt

/ Lt

10406 Curds

Kg

/ Kg

10407 Cheese, national

Kg

/ Kg

10408 Cheese

Kg

/ Kg

10409 Curds

Kg

/ Kg

10410 Other milk products

Kg

/ Kg

10411 Dried and coffee milk

Kg

/ Kg

10412 Condensed milk

Lt

/ Lt

10413 Sour cream

Kg

/ Kg

10299

Sub total 10201 - 10217

10300 FISH AND SEAFOOD

10399

Sub total 10301 - 10304

10400 MILK, CHEESE AND EGGS

10414 Dried eggs

Kg

/ Kg

10415 Other milk, cheese and eggs

N/A

/ N/A

10499

Sub total 10401 - 10415

10500 OILS AND FAT
10501 Butter

kg

/ kg

10502 Margarine

kg

/ kg

10503 Vegetable oil

Lt

/ Lt

10504 Edible animal fats

kg

/ kg

10505 Cream

kg

/ kg
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SECTION 11: CONSUMPTION OF FOOD AND OTHER FREQUENTY PURCHASED COMMODITIES (FROM DIARY)
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGFIRST 10 DAYS /1-10
1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
FIRST 10 DAYS

ITEMS

UNIT

SECOND 10 DAYS /11- 20(11.01)
MAIN SOURCES OF CONSUMED ITEMS 1.TOTAL ..[ITEM]..
CONSUMED
2.
3.4.DURING THE
Purchased
Received
Own
SECOND 10 DAYS
free
production

QUANTITY

THIRD 10 DAYS /21-30, 31(11.02)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

3.Received
free

QUANTITY

4.Own
production

1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
THIRD 10 DAYSMONTHLY AVERAGE(11.03)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

QUANTITY

3.Received
free

4.Own
production(11.04)
OF UNIT
Write to strike an average
unit prices of 30 days/

TUGRUGS / [UNIT]

10506 Melted butter

kg

/ kg

10507 Olive oil

kg

/ kg

kg

/ kg

10601 Apple

Kg

/ Kg

10602 Mandarin

Kg

/ Kg

10603 Raisin,kg

Kg

/ Kg

10604 Other fresh fruit ,kg

Kg

/ Kg

10605 Wild fruit

Kg

/ Kg

10606 Dried fruit

Kg

/ Kg

10607 Wild nuts,kg

Kg

/ Kg

10608 Other nuts

Kg

/ Kg

10609 Other Fruits /watermelon etc./

N/A

/ N/A

10701 Potato

Kg

/ Kg

10702 Cabbage

Kg

/ Kg

10703 Carrot

Kg

/ Kg

10704 Turnip

Kg

/ Kg

10705 Onion

Kg

/ Kg

10706 Garlic

Kg

/ Kg

10707 Tomato

Kg

/ Kg

10708 Cucumber

Kg

/ Kg

10709 Jelly sticks

Kg

/ Kg

10710 Canned cucumber

Kg

/ Kg

10711 Canned vegetable salad

Kg

/ Kg

10712 Pepper

N/A

/ N/A

10508 Other
10599

Sub total 10501 - 10508

10600 FRUITS

10699

Sub total 10601 - 10609

10700 VEGETABLES

10713 Mushrooms

Kg

/ Kg

10714 Other vegetables

N/A

/ N/A

10799

Sub total 10701 - 10714

10800 SUGAR AND JAM
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SECTION 11: CONSUMPTION OF FOOD AND OTHER FREQUENTY PURCHASED COMMODITIES (FROM DIARY)
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGFIRST 10 DAYS /1-10
1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
FIRST 10 DAYS

ITEMS

UNIT

SECOND 10 DAYS /11- 20(11.01)
MAIN SOURCES OF CONSUMED ITEMS 1.TOTAL ..[ITEM]..
CONSUMED
2.
3.4.DURING THE
Purchased
Received
Own
SECOND 10 DAYS
free
production

QUANTITY

THIRD 10 DAYS /21-30, 31(11.02)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

3.Received
free

QUANTITY

4.Own
production

1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
THIRD 10 DAYSMONTHLY AVERAGE(11.03)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

QUANTITY

3.Received
free

4.Own
production(11.04)
OF UNIT
Write to strike an average
unit prices of 30 days/

TUGRUGS / [UNIT]

10801 Sugar

Kg

/ Kg

10802 Lump sugar

Kg

/ Kg

10803 Sugar substitution

Kg

/ Kg

10804 Candy

Kg

/ Kg

10805 Sweet

Kg

/ Kg

10806 Chocolate

Kg

/ Kg

10807 Honey

Kg

/ Kg

10808 Compotes

Kg

/ Kg

10809 Jam

Kg

/ Kg

10810 Icecream

Kg

/ Kg

10811 Chewing gum

N/A

/ N/A

10812 Syrop

Kg

/ Kg

10813 Other (marmalades, sugar, jam)

N/A

/ N/A

10901 Salt

gr

/ gr

10902 Vinegar

gr

/ gr

10903 Ketchup

gr

/ gr

10904 Mayonnaise

kg

/ kg

10905 Yeast

gr

/ gr

10906 Spice

gr

/ gr

10907 Babyfood

kg

/ kg

10908 Other spices, other food

N/A

/ N/A

11001 Green tea

gr

/ gr

11002 Tea

gr

/ gr

11003 Coffee

gr

/ gr

11004 Cocoa

gr

/ gr

11005 Other tea, coffee

N/A

/ N/A

10899

Sub total 10801 - 10813

10900 OTHER FOOD

10999

Sub total 10901 - 10908

11000 TEA AND COFFEE

11099

Sub total 11001 - 11005

11100 MINERAL WATER AND SOFT DRINKS
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SECTION 11: CONSUMPTION OF FOOD AND OTHER FREQUENTY PURCHASED COMMODITIES (FROM DIARY)
INTERVIEWER: SUMMARIZE THE FOLLOWING INFORMATION FROM THE DIARY WRITE ZERO IF NOTHINGFIRST 10 DAYS /1-10
1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
FIRST 10 DAYS

ITEMS

UNIT

SECOND 10 DAYS /11- 20(11.01)
MAIN SOURCES OF CONSUMED ITEMS 1.TOTAL ..[ITEM]..
CONSUMED
2.
3.4.DURING THE
Purchased
Received
Own
SECOND 10 DAYS
free
production

QUANTITY

THIRD 10 DAYS /21-30, 31(11.02)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

3.Received
free

QUANTITY

4.Own
production

1.TOTAL ..[ITEM]..
CONSUMEDDURING THE
THIRD 10 DAYSMONTHLY AVERAGE(11.03)
MAIN SOURCES OF CONSUMED
ITEMS
2.
Purchased

QUANTITY

3.Received
free

4.Own
production(11.04)
OF UNIT
Write to strike an average
unit prices of 30 days/

TUGRUGS / [UNIT]

11101 Beverage

Lt

/ Lt

11102 Juice

Lt

/ Lt

11103 Pure water, bottled

Lt

/ Lt

11104 Other soft drinks

Lt

/ Lt

11201 Vodka, domestic

Lt

/ Lt

11202 Beer, domestic

Lt

/ Lt

11203 Vodka, imported

Lt

/ Lt

11204 Beer, imported

Lt

/ Lt

11205 Wine

Lt

/ Lt

11206 Other alcoholic beverages

Lt

/ Lt

11301 Cigarette, imported

Box

/ Box

11302 Cigarette, domestic

Box

/ Box

11303 Tobacco

Kg

/ Kg

11304 Snuff

Kg

/ Kg

11305 Other (tobacco)

Kg

/ Kg

11199

Sub total 11101 - 11104

11200 ALCOHOLIC BEVERAGES

11299

Sub total 11201 - 11206

11300 TOBACCO AND CIGARETTES

11399

Sub total 11301 -Mongolia HSES 2010 Manual (Version 1.0)

165

NSO, MONGOLIA

SES-2bAll staffs at the all level of NSO should keep your responses confidential in accordance with Mongolian Legislation on "Statistics" and "Confidentiality of private information".

THE SOCIO-ECONOMIC SURVEY

HOUSEHOLD ID
Quarter

NAME OF HOUSEHOLD HEADINTERVIEWER

Cluster number

HHNo

ADDRESS

Code

SUPERVISOR

Code

Did any visitor stay here with your household for the last month?

Number(Specify number of visitors)
How many days?

person/day(Number of visitors multiple by days stayed here)

For the rural households /soum center and herders/
NOTE:

Mongolia HSES 2010 Manual (Version 1.0)

166

SECTION 12: CONSUMPTION OF FOOD DURING THE PAST 7 DAYS (BY RECALL )ITEM CODEASK (12.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX
OR "2" FOR "NO" IN THE SECOND BOX.. THEN ASK (12.02) to (12.06) ONLYFOR THE ITEMS THAT WERE ACQUIRED(12.01)Have you consumed ..[ITEM].. during the 7 days?

ITEMS
10100

UNIT

FLOUR AND FLOUR PRODUCTS

YES

NO

1

2

FOOD CONSUMPTION BY RECALL - RURAL HOUSEHOLDSCONSUMPTION DURING THE PAST 7 DAYSSOURCES OF CONSUMPTIONRECEIVED FREE
FROM PURCHASES(12.02)
How much ..[ITEM] have you (12.03)(12.04)(12.05)
consumed in total during the From that quantity
And what was the unit price From that quantity
past 7 days?
consumed, how much came of that quantity consumed
consumed, how much camefrom purchases?
during the past 7 days?
from gifts or was received
free?
TOTAL

QUANTITYQUANTITYTUGRUGS / Unit

QUANTITYpiece/ 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

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 Pizza

N/A

/ N/A

N/A

/ N/A

10201 Mutton

Kg

/ Kg

10202 Beef

Kg

/ Kg

10203 Goat meat

Kg

/ Kg

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

Kg

/ Kg

10199

Sub total 10102 - 10115

10200 MEAT, MEAT PRODUCTS

10214

Sausage

10215 Canned meat
10217 Other meat, meat products

Kg

N/A

From that quantity
consumed, how much camefrom own production?

(12.02) = (12.03) + (12.05) +(12.06)10101 Bread (1 piece = 670 gr)

10115 Other flour and flour products

PRODUCED(12.06)/ Kg

Mongolia HSES 2010 Manual (Version 1.0)

/ N/A

QUANTITY167

SECTION 12: CONSUMPTION OF FOOD DURING THE PAST 7 DAYS (BY RECALL )ITEM CODEASK (12.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX
OR "2" FOR "NO" IN THE SECOND BOX.. THEN ASK (12.02) to (12.06) ONLYFOR THE ITEMS THAT WERE ACQUIRED(12.01)Have you consumed ..[ITEM].. during the 7 days?

ITEMS
10299

UNIT

YES

NO

1

2

FOOD CONSUMPTION BY RECALL - RURAL HOUSEHOLDSCONSUMPTION DURING THE PAST 7 DAYSSOURCES OF CONSUMPTIONRECEIVED FREE
FROM PURCHASES(12.02)
How much ..[ITEM] have you (12.03)(12.04)(12.05)
consumed in total during the From that quantity
And what was the unit price From that quantity
past 7 days?
consumed, how much came of that quantity consumed
consumed, how much camefrom purchases?
during the past 7 days?
from gifts or was received
free?
TOTAL

QUANTITYQUANTITYTUGRUGS / Unit

QUANTITY

Sub total 10201 - 10217

10301 Fish

Kg

/ Kg

10302 Dried, smoked, salted fish

Kg

/ Kg

10303 Canned fish

Kg

/ Kg

10304 Other fish and seafood

Kg

/ Kg

10401 Milk

Lt

/ Lt

10402 Youghurt

Lt

/ Lt

10403 Eggs

Nb

/ Nb

10404 Dried curds

Kg

/ Kg

10405 Horse milk, l

Lt

/ Lt

10406 Curds

Kg

/ Kg

10407 Cheese, national

Kg

/ Kg

10408 Cheese

Kg

/ Kg

10409 Curds

Kg

/ Kg

10410 Other milk products

Kg

/ Kg

10411 Dried and coffee milk

Kg

/ Kg

Sub total 10301 - 10304

10400 MILK, CHEESE AND EGGS

10412 Condensed milk

Lt

/ Lt

10413 Sour cream

Kg

/ Kg

10414 Dried eggs

Kg

/ Kg

10415 Other milk, cheese and eggs

N/A

/ N/A

10499

Sub total 10401 - 10415

10500 OILS AND FAT
10501 Butter

kg

/ kg

10502 Margarine

kg

/ kg

10503 Vegetable oil

Lt

/ Lt

10504 Edible animal fats

kg

/ kg

10505 Cream

kg

/ kg

10506 Melted butter

kg

/ kg

10507 Olive oil

kg

/ kg

10508 Other

kg

/ kg

10599

From that quantity
consumed, how much camefrom own production?

(12.02) = (12.03) + (12.05) +(12.06)10300 FISH AND SEAFOOD

10399

PRODUCED(12.06)

Sub total 10501 - 10508
Mongolia HSES 2010 Manual (Version 1.0)

QUANTITY168

SECTION 12: CONSUMPTION OF FOOD DURING THE PAST 7 DAYS (BY RECALL )ITEM CODEASK (12.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX
OR "2" FOR "NO" IN THE SECOND BOX.. THEN ASK (12.02) to (12.06) ONLYFOR THE ITEMS THAT WERE ACQUIRED(12.01)Have you consumed ..[ITEM].. during the 7 days?

ITEMS

UNIT

YES

NO

1

2

FOOD CONSUMPTION BY RECALL - RURAL HOUSEHOLDSCONSUMPTION DURING THE PAST 7 DAYSSOURCES OF CONSUMPTIONRECEIVED FREE
FROM PURCHASES(12.02)
How much ..[ITEM] have you (12.03)(12.04)(12.05)
consumed in total during the From that quantity
And what was the unit price From that quantity
past 7 days?
consumed, how much came of that quantity consumed
consumed, how much camefrom purchases?
during the past 7 days?
from gifts or was received
free?
TOTAL

QUANTITYQUANTITYTUGRUGS / Unit

QUANTITY

10601 Apple

Kg

/ Kg

10602 Mandarin

Kg

/ Kg

10603 Raisin,kg

Kg

/ Kg

10604 Other fresh fruit ,kg

Kg

/ Kg

10605 Wild fruit

Kg

/ Kg

10606 Dried fruit

Kg

/ Kg

10607 Wild nuts,kg

Kg

/ Kg

10608 Other nuts

Kg

/ Kg

10609 Other Fruits /watermelon etc./

N/A

/ N/A

10701 Potato

Kg

/ Kg

10702 Cabbage

Kg

/ Kg

10703 Carrot

Kg

/ Kg

10704 Turnip

Kg

/ Kg

10705 Onion

Kg

/ Kg

10706 Garlic

Kg

/ Kg

10707 Tomato

Kg

/ Kg

10708 Cucumber

Kg

/ Kg

10709 Jelly sticks

Kg

/ Kg

10710 Canned cucumber

Kg

/ Kg

10711 Canned vegetable salad

Kg

/ Kg

10712 Pepper

N/A

/ N/A

Sub total 10601 - 10609

10700 VEGETABLES

10713 Mushrooms

Kg

/ Kg

10714 Other vegetables

N/A

/ N/A

10801 Sugar

Kg

/ Kg

10802 Lump sugar

Kg

/ Kg

10803 Sugar substitution

Kg

/ Kg

10804 Candy

Kg

/ Kg

10805 Sweet

Kg

/ Kg

10806 Chocolate

Kg

/ Kg

10799

From that quantity
consumed, how much camefrom own production?

(12.02) = (12.03) + (12.05) +(12.06)10600 FRUITS

10699

PRODUCED(12.06)

Sub total 10701 - 10714

10800 SUGAR AND JAM

Mongolia HSES 2010 Manual (Version 1.0)

QUANTITY169

SECTION 12: CONSUMPTION OF FOOD DURING THE PAST 7 DAYS (BY RECALL )ITEM CODEASK (12.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX
OR "2" FOR "NO" IN THE SECOND BOX.. THEN ASK (12.02) to (12.06) ONLYFOR THE ITEMS THAT WERE ACQUIRED(12.01)Have you consumed ..[ITEM].. during the 7 days?

ITEMS

UNIT

YES

NO

1

2

FOOD CONSUMPTION BY RECALL - RURAL HOUSEHOLDSCONSUMPTION DURING THE PAST 7 DAYSSOURCES OF CONSUMPTIONRECEIVED FREE
FROM PURCHASES(12.02)
How much ..[ITEM] have you (12.03)(12.04)(12.05)
consumed in total during the From that quantity
And what was the unit price From that quantity
past 7 days?
consumed, how much came of that quantity consumed
consumed, how much camefrom purchases?
during the past 7 days?
from gifts or was received
free?
TOTAL

QUANTITYQUANTITYTUGRUGS / Unit

QUANTITYKg/ Kg

10808 Compotes

Kg

/ Kg

10809 Jam

Kg

/ Kg

10810 Icecream

Kg

/ Kg

10811 Chewing gum

N/A

/ N/A

10812 Syrop

Kg

/ Kg

10813 Other (marmalades, sugar, jam)

N/A

/ N/A

10901 Salt

gr

/ gr

10902 Vinegar

gr

/ gr

10903 Ketchup

gr

/ gr

10904 Mayonnaise

kg

/ kg

10905 Yeast

gr

/ gr

10906 Spice

gr

/ gr

10907 Babyfood

kg

/ kg

N/A

/ N/A

11001 Green tea

gr

/ gr

11002 Tea

gr

/ gr

11003 Coffee

gr

/ gr

11004 Cocoa

gr

/ gr

11005 Other tea, coffee

N/A

/ N/A

11101 Beverage

Lt

/ Lt

11102 Juice

Lt

/ Lt

11103 Pure water, bottled

Lt

/ Lt

11104 Other soft drinks

Lt

/ Lt

11201 Vodka, domestic

Lt

/ Lt

11202 Beer, domestic

Lt

/ Lt

Sub total 10801 - 10813

10900 OTHER FOOD

10908 Other spices, other food10999

Sub total 10901 - 10908

11000 TEA AND COFFEE

11099

Sub total 11001 - 11005

11100 MINERAL WATER AND SOFT DRINKS

11199

From that quantity
consumed, how much camefrom own production?

(12.02) = (12.03) + (12.05) +(12.06)10807 Honey

10899

PRODUCED(12.06)

Sub total 11101 - 11104

11200 ALCOHOLIC BEVERAGES

Mongolia HSES 2010 Manual (Version 1.0)

QUANTITY170

SECTION 12: CONSUMPTION OF FOOD DURING THE PAST 7 DAYS (BY RECALL )ITEM CODEASK (12.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX
OR "2" FOR "NO" IN THE SECOND BOX.. THEN ASK (12.02) to (12.06) ONLYFOR THE ITEMS THAT WERE ACQUIRED(12.01)Have you consumed ..[ITEM].. during the 7 days?

ITEMS

UNIT

YES

NO

1

2

FOOD CONSUMPTION BY RECALL - RURAL HOUSEHOLDSCONSUMPTION DURING THE PAST 7 DAYSSOURCES OF CONSUMPTIONRECEIVED FREE
FROM PURCHASES(12.02)
How much ..[ITEM] have you (12.03)(12.04)(12.05)
consumed in total during the From that quantity
And what was the unit price From that quantity
past 7 days?
consumed, how much came of that quantity consumed
consumed, how much camefrom purchases?
during the past 7 days?
from gifts or was received
free?
TOTAL

QUANTITYQUANTITYTUGRUGS / Unit

QUANTITY

Lt/ Lt

11204 Beer, imported

Lt

/ Lt

11205 Wine

Lt

/ Lt

11206 Other alcoholic beverages

Lt

/ Lt

Sub total 11201 - 11206

11300 TOBACCO AND CIGARETTES
11301 Cigarette, imported

Box

/ Box

11302 Cigarette, domestic

Box

/ Box

11303 Tobacco

Kg

/ Kg

11304 Snuff

Kg

/ Kg

11305 Other (tobacco)

Kg

/ Kg

11399

From that quantity
consumed, how much camefrom own production?

(12.02) = (12.03) + (12.05) +(12.06)11203 Vodka, imported

11299

PRODUCED(12.06)

Sub total 11301 -Mongolia HSES 2010 Manual (Version 1.0)

QUANTITYFOOD ITEMS
CodeFOOD ITEMS
Unit

10100 FLOUR AND FLOUR PRODUCTS

Code

171
Unit

10400 MILK, CHEESE AND EGGS

FOOD ITEMSFOOD ITEMS

Code

Unit

Code

10704 Turnip

Kg

11100 MINERAL WATERS, SOFT DRINKS

Unit

10101 Bread (1 piece = 670 gr)

piece

10401 Milk

Lt

10705 Onion

Kg

11101 BeverageLt

10102 RiceKg

10402 Youghurt

Lt

10706 Garlic

Kg

11102 Juice

Lt

10103 Flour, highest gradeKg

10403 Eggs

Nb

10707 Tomato

Kg

11103 Pure water, bottled

Lt

10104 Flour, grade 1

Kg10404 Dried curds

Kg

10708 Cucumber

Kg

11104 Other soft drinks

Lt

10105 Flour, grade 2

Kg10405 Horse milk, lLt10709 Jelly sticks

Kg

11200 ALCOHOLIC BEVERAGES

10106 Other flourKg

10406 Curds

Kg

10710 Canned cucumber

Kg

11201 Vodka, domestic

Lt

10107 Noodle,domestic

Kg

10407 Cheese, nationalKg10711 Canned vegetable salad

Kg11202 Beer, domestic

Lt

10108 Noodle, import

Kg

10408 CheeseKg

10712 Pepper

N/A

11203 Vodka, imported

Lt

10109 BakeryKg

10409 Curds

Kg

10713 Mushrooms

Kg

11204 Beer, imported

Lt

10110 BiscuitKg

10410 Other milk products

Kg

10714 Other vegetables

N/A

11205 Wine

Lt

10111 CakeKg10411 Dried and coffee milk

Kg

10800 SUGAR, JAM

11206 Other alcoholic beverages

Lt

10112 Millet

Kg

10412 Condensed milk

Lt

10801 Sugar

Kg

11300 TOBACCO

10113 Other rice (farina…)

Kg

10413 Sour creamKg

10802 Lump sugar

Kg11301 Cigarette, imported

Box10114 Pizza

N/A

10414 Dried eggs

Kg

10803 Sugar substitution

Kg

11302 Cigarette, domestic

Box10115 Other flour and flour products

N/A

10415 Other milk, cheese and eggs

N/A

10804 Candy

Kg

11303 Tobacco

Kg10805 Sweet

Kg

11304 Snuff

Kg

11305 Other (tobacco)Kg

10200 MEAT, MEAT PRODUCTS

10500 OILS AND FATS

10201 Mutton

Kg

10501 Butter

Kg

10806 Chocolate

Kg10202 Beef

Kg

10502 Margarine

Kg

10807 HoneyKg

10203 Goat meat

Kg

10503 Vegetable oil

Lt

10808 Compotes

Kg

10204 Horse meat

Kg

10504 Edible animal fats

Kg10809 Jam

Kg

10205 Camel meat

Kg

10505 CreamKg

10810 IcecreamKg

10206 Dried meat

Kg

10506 Melted butterKg10811 Chewing gum

N/A

10207 chicken

Kg

10507 Olive oil

Kg

10812 SyropKg

10208 Pork

Kg

10508 Other oils and fats

N/A10813 Other (marmalades, sugar, jam)N/A10209 Bacon

Kg

10600 FRUIT

10210 GameKg

10601 AppleKg

10901 Salt

Kg

10211 Other poultry

Kg

10602 Mandarin

Kg

10902 Vinegar

Kg

10212 Animal interiorKg

10603 Raisin,kg

Kg

10903 KetchupKg10213 Sausage,salami kg

Kg

10604 Other fresh fruit ,kg

Kg

10904 Mayonnaise

N/A

10214 Sausage,kg

Kg

10605 Wild fruit

Kg

10905 YeastKg

10215 Canned meat

Kg

10606 Dried fruit

Kg

10906 SpiceKg

10216 Other meat, meat products

N/A10607 Wild nuts,kg

Kg

10907 Babyfood

Kg10608 Other nuts

Kg

10908 Other spices, other food

N/A

N/A

11000 TEA, COFFEE

10300 FISH AND SEAFOOD
10301 Fish

Kg

10609 Other Fruits

10302 Dried, smoked, salted fishKg

10700 VEGETABLES

10303 Canned fishKg10701 Potato

10304 Other fish and seafood

Kg

10702 Cabbage
10703 Carrot

10900 OTHER FOOD

11001 Green tea

Kg

Kg

11002 Tea

Kg

Kg

11003 Coffee

Kg

Kg

11004 Cocoa

Kg

11005 Other tea, coffee

N/A

Mongolia HSES 2010 Manual (Version 1.0)

ID CODE172

CHECK PAGE

AGE

SEX

NAME

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
Mongolia HSES 2010 Manual (Version 1.0)

173

Aproved by the National Statistical Office
2010. Decree….

HSES-3

SOCIO-ECONOMIC SURVEY

The officials at all levels of the National Statistical Office system will keep your family's private data strictly confidential, according to the
Mongolian Laws on the individual's right to confidentiality and provision 22.3 of the Law on Statistics

SECTION 0. GENERAL QUESTIONS
DATE

1. HOUSEHOLD ID

Cluster number

VISITSHH No

RESULT*
DAY

MONTH

YEAR

1

2. AIMAG/CAPITAL

Code

2

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

Code

3

..........................................................
4. LOCATIONCAPITAL - 1 AIMAG CENTER -2

Code

4

SOUM CENTER - 3 RURAL - 4

5. ENUMERATOR

Code..........................................................

*

6. SUPERVISOR

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

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

Code(Equal to the sum of members answered "a right person to continue
asking questions" against Question 11, Section I. )NAME OF HOUSEHOLD HEAD ..................................................................

COMPLETE

1

PARTIALLY COMPLETED

2NO RESPONDENT IN THE HOUSEHOLD

3HOUSEHOLD TEMPERARILY NOT PRESENT4

POSTPONED

5

REFUSED

6

HOUSEHOLD NOT FOUND

7

ADDRESS.....................................................................................
Day…… month…… year……….. Mongolia HSES 2010 Manual (Version 1.0)

174

SECTION 1: HOUSEHOLD ROSTER(1.01)ID CODE

NAME(1.03)(1.02)
What is ..[NAME]'s..
SEX
relationship to the household
head?

BEFORE GOING ON TO
QUESTIONS 4-10,
HEAD
PLEASE FILL IN
QUESTIONS 1-3 ON THE WIFE / HUSBAND
NAME, RELATION TO
SON / DAUGHTER
THE HEAD OF HH AND
FATHER / MOTHER
THE SEX FOR EACH
HOUSEHOLD MEMBER. BROTHER / SISTERFATHER / MOTHER IN
LAW

ONLY FOR HOUSEHOLD MEMBERS AGED 15 AND (1.08)(1.09)(1.10)ABOVE
FATHER'S ID MOTHER'S ID For how many
CODE
CODE
months during(1.06)(1.07)
the past 12
What ismonths (since
Marital status..[NAME]..
..[MONTH] /spouse's ID..[YEAR].. ) has
IF
FATHERIS
IF
MOTHERIS
CODE?
DEAD WRITE DEAD WRITE he/she been
away from this
'99'
'99'
(FOR CHILDREN
household?
LESS THAN ONE
MARRIED1
YEAR, WRITE
LIVINGIF SPOUSE IS
THE AGE IN
2
TOGETHERNOT AIF FATHER IS IF MOTHER ISMONTHS).
HOUSEHOLD
NOT A
NOT A
►
(1.08)SEPARATED3
MEMBER CODE HOUSEHOLD HOUSEHOLDDIVORCED
4 ► (1.08) 98
MEMBERMEMBERWRITE '98'
WRITE '98'
WIDOWED5 ► (1.08)(1.04)(1.05)
What is theAGEyear of birth of..[NAME]..?
AGE INCOMPLETED
YEARS

01
02
03
04 MALE

1

05
06 FEMALE
2

BROTHER / SISTER IN
LAW

07

GRAND PARENT

08

GRANDCHILD

09

OTHER RELATIVE10SERVANT

11

OTHER

12

NEVER MARRIEDYEAR OF
BIRTH

AGE
YEARS

MTHS

6

► (1.08)(1.11)USING QUESTION (1.10) PLEASE
DEFINE S HE/SHE A RIGHTPERSON TO CONTINUE ASKINGQUESTIONS?

DO NOT INCLUDE A HOUSEHOLDHEAD OR ANY HOUSEHOLDSTUDENT MEMBERS AWAY FROMHOME 11 MONTHS OR MORE AND
ANY ONE ELSE AWAY FROMHOME 6 MONTHS OR MOREYESNO
SPOUSE'S ID
CODE

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
Mongolia HSES 2010 Manual (Version 1.0)

FATHER'S ID MOTHER'S ID
MONTHS
CODE
CODE

1
2
► NEXT PERSON175

SECTION 2: EDUCATION For household members 6 years or more
HOUSEHOLD MEMBERS WHO DROPPED OUT AND NEVER ATTENDEDSCHOOLХУВИЙН ДУГААР

FOR ALL HOUSEHOLD MEMBERS 6 YEARS OR MORE
(2.01)(2.02)

LOOK AT SECTION 1,
QUESTION (1.05):..[NAME]..'S AGE. IS 6YEARS OR MORE ?

IS THIS MEMBERANSWERINGPERSONALLY?

YES

1

NO

2 ► NEXTPERSON

YES
NO

1
2

(2.07)(2.03)(2.04)(2.05)(2.06)(2.08)WRITE THE ID
What is highest education/qualification level Can you / [NAME] read a Are you currently attending
CHECK..[NAME]..'S
Why did you / [NAME] never attend school?
CODE OFachieved?
letter? Or Are you literate? school? ( If not, please ask has AGE. IS 8 or BETWEEN
he/she ever attended school) 8-35 YEARS.
RESPONDENT.
1
CHILD NOT INTERESTED
1CHECK FROM THE NONEPRIMARYCHECK PAGE
2
PARENTS NOT INTERESTED
2
SECONDARY
3
DIFFICULTY OF SCHOOL
3COMPLETE SECONDARY

4►

VOCATIONAL(2.04)

DEGREE OR HIGHEREDUCATION DIPLOMA

5
6►

YES, EASILY
YES, WITH
DIFFICULTY

1

YES
NO. DROPPED
OUT

2
3
4

7

ÌÀÃÈÑÒÐ

8

Ph ÄÎÊÒÎÐOTHER

9NO, NEVER
ATTENDED

10NO, COMPLETED

3EDUCATION LEVEL IS DETERMINED BY
THE HIGHEST EDUCATION LEVELRESPONDENT'S ID
OBTAINED
CODE
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15

► YES
(2.09)

2

BACHELOR(2.06) NO

1

Mongolia HSES 2010 Manual (Version 1.0)►

NEXT
PERSONNO

1
2 ► NEXTPERSONLOOK FROM THE
CHECK PAGEÑÓÐÃÀËÒÛÍ ×ÀÍÀÐ ÌÓÓ

4

POOR SCHOOL CONDITION

5LACK OF BUDGET

6

REQUIRED TO WORK

7

SICK/DISABLED

8

HAD TO LOOK AFTER OTHERS9SCHOOL TOO FAR

10MIGRATION

11

LACK OF DORMITORY

12OTHERS

13► NEXT PERSON

176

SECTION 2: EDUCATION For household members 6 years or more
FOR ALL MEMBERS CURRENTLY ATTENDING SCHOOL AND ANSWERED "YES" TO QUESTION 2.06

ХУВИЙН ДУГААР

(2.09)(2.10)
Which school are you attending and What is thewhat grade are you in now??
ownership ofyour /.[[NAME]..'s
school?

TYPE(2.11)
Where is your /..[NAME]..'s school
located?

1

1 TO 12 PUBLIC

VOCATIONALCOLLEGE,UNIVERSITY

2

1 TO 3.5 PRIVATE

2 AIMAG CENTER

3

1 TO 6

3 SOUM CENTERSCHOOL(2.14)
Do you/Does … How much has your household spent during the last 12 months on your education?
[NAME]... pay
any tuition?
IF NOTHING WRITE ZERO.

GENERAL

OTHER ( ECLESIASTICAL,NON FORMAL)(2.13)(2.12)
Where do you / does..[NAME]..live while
attending school?

GRADE

OTHER

1 CAPITAL CITYABROAD40

GRADE

FOR ALL MEMBERS CURRENTLY ATTENDING SCHOOL

1 HOME
2 GER APPARTFROM HH
3 DORMITORY

1 YES 12 NO

FOR TUITION FEE PAYMENTS EXCEPT FOR AID AND GRANTS AFTER ASKING THE INDIVIDUAL AMOUNTS,
CALCULATE TOTAL. PROBE AND RECONCILE.
► NEXT PERSON

2

3

4 RELATIVES

4

OTHER

5

1
2
3
4
For room rent / For tuition paid
For books anddormitory
by household For tuition paid
suppliesby grants andaid
TUGRUGTUGRUG

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

Mongolia HSES 2010 Manual (Version 1.0)

TUGRUGTUGRUG5
For uniform

6
Transport

7
OthersTotal

8

TUGRUGTUGRUGTUGRUGTUGRUG177

SECTION 3: HEALTHFOR ALL HOUSEHOLD MEMBERS(3.02)(3.03)COPY THE Did you / [NAME]
ID CODE have any healthOFcomplaints in the
RESPOND past month?
ENT
FROM
THE
ROSTER

ID CODE(3.01)IS THISPERSONPRESENTANDANSWERINGFORHIMSELF/HE
RSELF/?

YES
►
NO

1

YES

(3.03)

NO

2

1
2
►

(3.04)(3.05)(3.06)(3.07)(3.08)
What health complaints did you / Did you seek treatment at Why did you not get any treatment at a health facility or health provider for your Where was the treatment provided? Under whose control
have you treated?
[NAME] have?
a health facility or health health problems?
(The last time)
provider for your healthproblems?
1
RESPIRATORYSYSTEM
01
NOT SERIOUS ENOUGHDIGESTIVE SYSTEM
2
02
HEALTH FACILITY TOO FARURINARY ANDSEXUAL ORGAN

3NO TRANSPORTATION

03
04

BLOOD CIRCULATIONSYSTEM

4

HEALTH CARE TOO EXPENSIVE
TRANSPORT TOO EXPENSIVE

05

HEALTH WORKERS NOT FRIENDLY

06

FOR ALL
ALTERNATIVES,SKIP TO(3.10)DAMAGE OR
INTOXICATION BY
EXTERNAL IMPACT(3.10) OTHERFIRSTONLY OUT PATIENT
CARE
5
YES
►
6

SECOND

1

NO

2

1

AIMAG/DISTRICT CLINIC
SOUM CENTER FAMILY
CLINIC

3

PROFFESIONAL
DOCTOR

1

2 FAMILY DOCTOR 2
NURSE

3

HEALTH WORKERS NOT PRESENT

07

chiropractor

4

HEALTH CARE NOT GOOD QUALITY

08

PRIVATE HOSPITAL

4 medicaster5

NO MONEY

09

ABROAD
OTHER

5
6

6

(3.07) TREATED MYSELF
DID`T KNOW FROM WHERE TO GETTREATMENT
TRADITIONAL HEALER

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

CENTRALHOSPITAL/CLINIC

Mongolia HSES 2010 Manual (Version 1.0)

10
11
12

OTHER

178

SECTION 3: HEALTHFOR ALL HOUSEHOLD MEMBERS GOT SICK IN LAST MONTH(3.09)ID CODEOUTPATIENT EXPENSES

FOR HOUSEHOLD MEMBERS WHO HAVE STAYED AT HOSPITAL THE PAST 12 MONTHS(3.10)(3.11)(3.13)(3.12)
During the past month, How much did you pay for During the past 12
What was the hospital?
have you purchased all medicines purchased months, have you stayed
any medicines on your on your own in the past
at a hospital or clinic
own, that is without a month?
overnight?
prescription, to treat
any health problems?

2.1.How much did you
How much did you pay for
pay, either in money or transportation for thesein kind, for all costs
visits to a facility or healthassociated with thecare provider including cost
outpatient visits to a for gifts for health carefacility or healthworkers and practitioners
practitioner during the during the past month?
past month? Include Include the transportation
any medicines
costs of anyone who
prescribed duringaccompanied you.
MEDICINE USED IN
these visits, even if
For food and other goods
purchased elsewhere please include the value in HOSPITAL WILL BE
FILLED IN
tugrugs.
QUESTIONS 3.14

TUGRUGSOUM CENTER FAMILY
CLINICPRIVATEABROAD
OTHER

YES

1

YES

1

NO

2

NO

2

►
TUGRUGCENTRAL
CLINIC/SPECIALIZEDHOSPITALAIMAG/DISTRICT CLINIC(3.12)NEXT► PERSONTUGRUG

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

Mongolia HSES 2010 Manual (Version 1.0)

(3.14)How much did you pay for all
costs associated with hospipal
stays, in cash or in kind, for past
12 months?

(3.15)How much did you spend fortransportation and other medical
expenses, including cost for gifts
for health care workers andpractitioners during the past 12
months?

1
2
INCLUDE THE COST FOR
MEDICINE PRESCRIBED AND
4
PURCHASED BY HOUSEHOLD
5MEMBERS
6
3

WRITE ZERO IF NOTHINGWRITE ZERO IF NOTHINGTUGRUGSTUGRUGS

179

SECTION 4: JOBSSECTION 4: JOBS

FOR ALL HOUSEHOLD MEMBERS 10 YEARS OLD AND ABOVE

FOR ALL HOUSEHOLD MEMBERS 10 YEARS OLD AND ABOVE(4.01)(4.02)(4.03)COPY THE ID
CODE OF ALL
HOUSEHOLD
MEMBERS 10YEARS OLD ANDABOVE FROM
THE FLAP

COPY THE ID
CODE OF ALL
HOUSEHOLD
MEMBERS 10YEARS OLD
AND ABOVEFROM
SECTION 1

COPY THE ID Do you work
CODE OF THE during past 7
RESPONDENT days?
FROM THE
ROSTER(4.04)

NO

1

YES

2

► NEXT PERSON NO(4.06)(4.07)(4.08)(4.09)

However you were
unemployed in last 7
days, have you
worked forsomething?

WHAT IS THE REASON THATYOU DIDN'T WORK IN THE
LAST WEEK?

HAVE YOULOOKED FOR
WORK IN THE
LAST WEEK?

Ñ¿¿ëèéí 7 õîíîãò àæèë õàéãààã¿é øà DID YOU
WHAT IS YOUR OCCUPATION?
ëòãààíàà õýëíý ¿¿?
REGISTER AT THE
EMPLOYMENTAND SOCIALWELFAREOFFICE?
STUDENT1(4.10)(4.11)► NEXT PERSONID CODE
YES(4.05)
What was your main work in last 7
days?

1

SICK

1

PREGNANCY

2

TAKE CARE OTHERS

3

WAGE JOB

1RESTED

4

UNPAID

2

TEMPORARY STOPPED5

WAITING FOR WORK

4SEASONEL EMPLOYED5

SEASONAL

6► (4.04)YES

1

HERDER

3

YES

1

2

NO

2

FARMER

4NO

2 OTHEROTHER

5ID CODE

2► NEXT PERSONHOUSEWIFE,
CHILDCARE LEAVE FROMWORKOWN ACCOUNT:► (4.06)

TOO OLD► (4.11)

YES

NO

3
If family member is unemployed in last 7 days, use the main occupation in last 12
months

1

YES

1

6

NO

2

2 DISABLED

7► NEXT PERSON

OTHER

8

► (4.10) LOOK AFTER SICK PERSON

7► (4.08)

IF FAMILY MEMBER IS DOUBLE EMPLOYED, RECORD ONLY MAIN
OCCUPATION.

► (4.11)DESCRIPTION OF THE OCCUPATION

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

Mongolia HSES 2010 Manual (Version 1.0)

OCCUPATION CODE180

SECTION 4: JOBS
FOR ALL HOUSEHOLD MEMBERS 10 YEARS OLD AND ABOVE(4.12)(4.13)ECONOMIC ACTIVITY

When you
Is your employer for this work…
conducted thisactivity during thepast 12 months,
how many hours
per week did you
work onaverage?

(4.14)(4.15)(4.16)Have you received How much salary did you get totally for all works you engaged in?
salary by cash and How much was your last 12 month payment?
in kind for the workin the last 12
months?
the total amount of salary of the all jobs including main and double jobs.

FOR IN KIND PAYMENTS ESTIMATE THE VALUE USING THE MARKET PRICEDESCRIPTION OF THE ECONOMIC ACTIVITY

ISIC CODE

HOURS / WEEKPARTNERSHIPS

1COOPERATIVE

2CORPORATION

3

LLC

4

STATE OWNED5LOCAL ADMINISTRATION OWNED

6 YES

1

GOVERNMENT ORGANIZATION

7 NO

2

NON-GOVERNMENT ORGANIZATION

8

OTHER

9

►NEXT PERSON

Payroll

Additional wages, grants and bonusesin last 12 months

Last months

Last 12 months

TUGRUGSTUGRUGS

Mongolia HSES 2010 Manual (Version 1.0)

TUGRUGS

181

SECTION 5: AGRICULTURAL PRODUCTION(5.01)

A: HERDING

In the last 12 months, have your household raised or owned herding, poultry or any other animal ?
Please make sure that whether it is answered as "3" in question № 4.05. Households who have private livestock should be answered in this question eventhough it is answered as "doesn't engagin in the animal husbandry" In Chapter 4.
YES

1

NO

2

►

PART B

Name of animals

WRITE ZERO IF NONE AND SKIP TO NEXTANIMAL(5.03)
Use for own foodfemale(5.05)
Amount received

INCLUDING SOLD
AS ALIVE ANDSLAUGTHERED

Of which…
TOTAL(5.04)
Sold

Expenditures

NUMBER OF ROWNUMBERS(5.02)In the past 12 months, how many ..[ANIMALS].. did the household….
How many ..[ANIMAL].. does the HH own now?

young

NUMBERNUMBER(5.06)
Expenditures on herding
activities in the last 12
monthsExpenditure item

WRITE ZERO IFNOTHINGTUGRUGSTUGRUGS

1 Cattle

01

Animal Feed

2 Horses

02

Drugs and veterinary costs
Gassoline /Oil3 Camels

03

4 Sheep

04

Taxes and Insurance

5 Goats

05

Other (Hired labour costs, Maintenance of fences &Equipment, Repair of equipment, Steam, water, electricity& Heat, Rent, Loan's interest)

99

Total

6 Other (hive, pig)
9 TOTAL(5.07)In the last 12 months, have your household produce any wool, cashmere, leather, milk and other livestock products?
YES
NO

1
2

►

ANIMAL NUMBER(5.08)

YES

1

NO

2
► NEXT ANIMAL

02 Wool, Horse, Cattle's hair
03 Sking and hides

Of which…

(5.09)In last 12 months,
Total production
have your householdproduced[PRODUCTS]?

PRODUCT

01 Cashmere

PART B(5.10)
Consumed byhouseholdSOLD(5.11)PRODUCED AND SOLD

(5.12)

Quantity sold as
raw material

Total amountreceived

QUANTITYQUANTITYQUANTITYTUGRUGS

Kg
PiecesLiters

05 Eggs

PiecesQuantity sold as
raw material(5.14)
Total amounti d

WRITE ZERO IF NOTHING

Kg

04 Mare milk, airag(5.13)

06 Others

Mongolia HSES 2010 Manual (Version 1.0)

QUANTITYTUGRUGS

182

SECTION 5: AGRICULTURE, HERDING AND BY-PRODUCTS(5.15)(5.16)

Does any member of your household own or has operated any agriculturalland in the past 12 months?

YES

1

NO

2

B: CROPS(5.17)Has your household harvested any vegetables, fruits or cereals in the past 12 months?

► SECTION 6

What is the total amount of agricultural land owned or operated
by the household during the past 12 months?

M2(5.18)

YES

1

NO

2

►

SECTION 6

What is the total amount of agricultural land operated by the household members during the past
12 months?

EXPENDITURES(5.20)Of which…
(5.19)
Did you harvest ..[CROP].. Total harvest of ..[CROP].. (5.21)(5.22)(5.23)
during the past 12
in last 12 months
Quantity consumed Quantity used for Sold as raw material
months?
by your household animal feed
NAME OF THE CROP
YES

1

NO
2
►ASK NEXT CROPKILOGRAMSKILOGRAMSKILOGRAMSQUANTITYTOTALAMOUNTRECEIVEDKILOGRAMSTUGRUGS

EXPENDITURE ITEMNUMBER OF ROWNUMBERSPRODUCTION OF CROPS

M2

WRITE ZERO IF NOTHINGTUGRUGS01

Seeds

01 Potatoes

02

Fertilizers

02 Carrots

03

Extermination of vermin

03 Turnip

04

Equipent & Tools

04 Cabbage

05

Routine repairs, constructions

05 Beetroot06

Raw materials

06 Onion

07

Firewood, dung

07 Garlic

08

Gasoline, fuel08 Tomatoes

09

Taxes

09 Cucumber

10

Rent

10 Fruits

11Interest rate

12

Other (Hired labour, Electricity & heat, Steam heating, water
expenditure, Transportation, Communication)

99

TOTAL (01-12)

11

Other (Wheat, Barley,
Oats, Grain)

99 TOTAL

Mongolia HSES 2010 Manual (Version 1.0)

(5.24)
What was the expenditure on..[ITEM].. in the past 12
months?

183

SECTION 6: Non-Farm household enterprises(6.01) In last 12 months, has you household engage in Non-farming production, trade and service?
YES

1

NO

2

(6.02) How many types of productiion and services has your household engaged in?

PRODUCTION, TRADE ANDSERVICES №1PRODUCTION, TRADE ANDSERVICES №2PRODUCTION, TRADE ANDSERVICES №3

ISIC CODE:

ISIC CODE:

ISIC CODE:

%

%

%

(6.05) How many members of your household work in this enterprise?

NUMBERNUMBERNUMBER(6.06) During the past month, how many people did this enterprise employ who are not members of this household?

NUMBERNUMBERNUMBER► SECTION 7

PLEASE WRITE THE NAME OF PRODUCTION AND SERVICES.
(6.03) FULL WRITTEN DESCRIPTION?
PLEASE WRITE THE RELATED CODE OF "ISIC" .
(6.04) What percentage of this enterprise is owned by members of this household?

TUGRUGS(6.07) How much did this enterprise spend during the past 12 months in …?
01

Goods for resale02

Raw materials

03

Gasoline, fuel04

Equipment

05

housing rents

06

Spare parts

07

Repair and maintenance of facilities and equipment

08

Taxes, order, patent license, Insurance

09

Other expenses (Wages and salaries for employees, Water and steam heating,Electricity, Heat, Transportation cost, Post, communications,internet, Interest on
business loans)

10

TOTAL EXPENSES(6.08) For how many of the past 12 months has this enterprise been in operation?
(6.09)(a) How much does this enterprisereceive from its clients…
(á)How many of the past 12 months
were…

TUGRUGS

The number of months(a) tugrugs/month1...in an average month?

2...in a bad month?

3...in a good month?

Mongolia HSES 2010 Manual (Version 1.0)

TUGRUGS

The number of months(á) months(a) tugrugs/month

The number of months(á) months(a) tugrugs/month(á) months

184

SOURCE NUMBERSECTION 7: OTHER INCOME

PART A. PENSION, BENEFITS AND SOCIAL WELFARE AND INCOME FROM OTHER SOURCES(7.01)
Has any of the household members received income from...[SOURCE]... during the last 12 months?

Who of the household members got income from ...[SOURCE]... and what was the total he/she received during the last 12 months?

YES

1

NO

2

► NEXT(7.02)(7.03)(7.04)(7.05)(7.06)PERSON # 1

PERSON # 2

PERSON # 3

PERSON # 4

PERSON # 5#1
ID CODE#2
TUGRUGS

ID CODE#3
TUGRUGS

ID CODEPENSION, BENEFITS AND SOCIAL WELFARE
01 State pension
02 Special Pension
03 Unemployment benefit
04 Maternity benefits
05 Civil care of disabled
06 Survivor's pension
07 Illness payments
08 Funeral payments
09 Baby care allowances
10 Child allowances (transferred to account)
11 Child allowances (received in cash)
12 Other social benefit
OTHER SOURCES
13

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

14 Sale of assets
15 Inheritances and wedding presents
16 Loan repayments
17 Withdrawals from bank savings
Interests and in dividends from ….
18

savings?

19

Dividends?

20

Loan?

21

Treasury Bond?

22 Gambling, lottery and contest
23 Other income (from intellectual property & other)

Mongolia HSES 2010 Manual (Version 1.0)

#4
TUGRUGS

ID CODE#5
TUGRUGS

ID CODETUGRUGS

185

SECTION 7: OTHER INCOME(7.07)

B: INCOME FROM REMITTANCES AND AID

In the last 12 months, has any member of the household received money or goods from individuals, relatives, friends, government or an aid organization.
DO NOT INCLUDE EDUCATIONAL GIFTS OR GRANTS, AND AMOUNTS OR GOODS THAT HAVE TO BE REPAID

YES

1

NO

2

►

SECTION - 8(7.09)(7.08)(7.10)(7.11)(7.12)

What for have you spend the gift or grants?

From where the gifts, remittances oraids were sent or given?

How much was received during the past Do you receive this gifts By which type do you
receive the gifts or grants?
12 months? ( Include every non-currency or granst in regularones through converting into currency) period?

1

Household consumption

1

URBAN

1

COMPANIES AND ORGANIZATIONS

2

Education and training fees

2

RURAL

2

NGOs

3

Treatment

3 ABROAD

RELATIVES

4

ÑÓÓÖÒÀÉ ÁÎËÎÕ

4

KOREA

3

OTHER INDIVIDUALS (FRIENDS, NEIGHBORS, ETC)

5celebration/ burial

5

USA

4

FOREIGN & INTERNATIONAL ORGANIZATIONS, AND
FOREIGHN INDIVIDUALS

6household production and business

6

ENGLAND

5

other

7

GERMANY

LINE NUMBER

COPY THE CODE OF
Who gave the gift, remittance or aid?
ANY HH MEMBER WHO
RECEIVED MONEY OR
IN-KIND ASSISTANCE(THE RECEIVER) .
GOVERNMENT/ TRAINING FUNDOTHERS7(7.13)(7.14)

cash

1

7 days even

1 accounts

2monthly

2 remittance3

6

every season

3 non-cash

4

JAPAN

7

each year

4 other

5

OTHER COUNTRY

8YES:FOR GOODS RECEIVED, ASK FOR
THE IMPUTED VALUENOTUGRUGID CODE
01
02
03
04
05
06
07
08

Mongolia HSES 2010 Manual (Version 1.0)

5

186

SECTION 8. HOUSING AND ENERGY(8.01) How many dwellings does your household own?
INCLUDE HOMES SET UP FOR CHILDREN TO ATTEND SCHOOL. DON'T INCLUDE DACHAS(8.02) Is this dwelling that you live is your main dwelling ?

GER(8.11) Number of segments in the ger
YES

1

NO

2

(8.12) Covering of the ceiling(8.03) Type of this dwelling
GER

1►(8.11)

2

SEPARATE APARTMENT

3

HOUSE LOCATED INSIDE OF THE COMMUNIALAPPARTMENT BUILDING

4

DORMITORY

5

WORKERS APARTMENT

6

OTHER PUBLIC HOUSE

7

NON-LIVING QUARTERS

8►

OTHER

9

SINGLE

1

DOUBLE2(8.13) Covering of the frame

HOUSE:
separate single family housing

NUMBER:SINGLE

1

DOUBLE2(8.14) Main material of the floor(8.10)

WOOD

1

EARTH

2

OTHER

3

(8.15) How old is this dwelling?
YEAR

IF DO NOT KNOW WRITE "99"(8.04) Number of rooms in the dwelling(8.16) How long have you been living in this place?

DO NOT INCLUDE KITCHEN, HALLWAYS AND BATHROOMS

YEAR(8.17) Type of ownership of this dwelling(8.05) Main material of the walls

STATE OWNED ENTERPRISES

1►(8.20)(8.20)

BRICKS

1

STONE

4

PRIVATE OWNED ENTERPRISES

2►

CEMENT

2

OTHER

5

PRIVATE

3

WOOD

3(8.18) How was this dwelling acquired?
RENTING1►(8.21)

PURCHASED

METAL

1

TILE

3

INHERITED

2►(8.20)PRIVATIZED

6

ASPHALT ROOF SHINGLES

2

OTHER

4

GIFT

3►

(8.20)OTHER

7

BUILT BY OURSELVES

4(8.06) Main material of the roof

5(8.07) Main material of the floor
WOOD

1

EARTH

3

CEMENT

2

OTHER

4

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

What is size of living area in your dwelling?
(8.08) Living area

YES

1

NO

2

(SQUARE METERS)(8.20) IF YOU RENT YOUR DWELLING HOW MUCH

What is size of total living area in your dwelling?
(8.09) Total useful area
(SQUARE METERS)►(8.15)►NON LIVING QUARTERS(8.10) What is the total area your household occupies?
►

TUGROG:RENT DO YOU REQUIRE FOR A MONTH?
If you do not know please write as '99'.

(SQUARE METERS)(8.15)

Mongolia HSES 2010 Manual (Version 1.0)

(8.22)

187

SECTION 8. HOUSING AND ENERGY(8.21) How much do you rent your housing in a month?

TUGROG:(8.30)

КМ

Distance to the nearest school:
1 8 grade school(8.22) What is the main source of heating system in this dwelling unit?
CENTRALIZEDTRADITIONAL FIRE WOOD/COAL/DUNG STOVE

2 10 grade school

1

PRIVATE ELECTRICAL HEATER

32PRIVATE LOW PRESSURE BOILER

4

4 Distance to the nearest pharmacy

OTHERS

5

5 Well

3 Distance to the nearest place to receive medical care

(8.23) Source of electricity(8.31) Do you or any member of your household owns any land for forever and certain period?

CENTRAL SYSTEM

1SMALL GEN-SET

5LOCAL SYSTEM/DIESEL STATION2CANDLES

6

YES

1

SOLAR SYSTEM

3

OTHER

7

NO

2

WIND SYSTEM

4►(8.33)(8.32) What is total land area owned by?
(8.24) Do your house have enegy sources to run household appliance?

land area owned by for ì2land are owned by certaì2
YES

1

NO

2

INTERNET USE(8.25) Water supply(8.33) Does ay household member normally use Internet?

CENTRALIZED: HOT & COLD WATER PIPE

1 TRANSPORTATION DISTRIBUTION

5CENTRALIZED: COLD WATER PIPE ONLY

2 SPRING, RIVER

6

YES

1

PROTECTED WELL

3 SNOW, ICE

7

NO

2

UNPROTECTED WELL

4 OTHER

8► (8.36)(8.34) HowHow many household members normally use Internet?
(8.26) Has the household have you a sewage system?

NUMBER
YES

1

NO

2

(8.35) Where do household members have used Internet during the past 3 months?

(8.27) What's the main method used for waste disposal?
THROUGH TUBE

1

NO SPECIAL PLACE

3

SPECIAL PLACE FOR WASTE

2OTHERS

4

YES

1

NO

2

1 At home(8.28) What type of toilet do you have?
INSIDE THE DWELLING

2 At work
SEPARATE

1OUTSIDE THE DWELLING

33 Internet Café

PUBLIC2NO TOILET

44 Free public Internet access centre
5 Other(8.29) Does your household have a telephone?
YES, LAND LINE PHONE

1

YES, MOBILE PHONE

2

YES, BOTH LAND AND MOBILE PHONE

3

NO

4

SECTION 8:HOUSING AND ENERGYE NUMBER

FUEL AND ENERGY CONSUMPTION(8.36)(8.37)(8.38)(8.39)Have you use the / ITEM / in last 12
months ?

How do you prepare your /FUELS/?

How manydiffererent kinds ofsource have you
used in last 12

How much did you spend How much money havefor ITEM in a last month? your household spend for/ITEM/ in last 12 months?

OWN MADE

1(8.40)

Mongolia HSES 2010 Manual (Version 1.0)

(8.41)
What is the price of the/ITEM/ that you borrowed
from others for free in last
12 months?

SOURCE

188

YES

1

NO

2

months?

2

PURCHASE
OWND MADE AND PURCHAGE

3

OTHER

4

► NEXT SOURCE
x

x

x

x

x

x

x

x

PHYSICAL AMOUNT
x

x

x

1

Electric power

2

Firewood

ì

3

COAL

ton

4

DUNG

ton

x

TUGRUGTUGRUGTUGRUG

x

3

5

GAS

L

6

OTHER

xxx

(8.42)
have you paid for the /ITEM/ in last 12 months? Used free?

ITEM

CODE

DWELLING FEE

YESNO(8.43)How much did you paind in latst
month?

(8.44)How much have you paid inlast 12 months?

(8.45)How much have you borrowed from others forfree in last 12 month?

1
2 ►NEXT ITEMTUGRUG

01

Heating fees

02

Water use fees

03

Hot water fees04

Dirty water05

Garbage disposal

06

Housing space fees

07

Other services (lift…)

08

Other services fees(repair of plumbing)09

Water, /brought by transport/

10

House rent: Ger

11

House rent: Apartment, house

12

Charges of repair of dwelling

13

Other

TUGRUG

Mongolia HSES 2010 Manual (Version 1.0)

TUGRUG

189

DURABLE GOODS(9.01)(9.02)(9.03)(9.01)(9.02)(9.03)

Does your household
has the following
durable goods?

How long have you
used this good?

Please value thisgood in Tugrugs

Does your household
has the following
durable goods?

How long have you
used this good?

Please value thisgood in Tugrugs

TAKE AVERAGE IF
MORE THAN ONE OF
THIS GOODS WEREUSEDTAKE AVERAGE IF
MORE THAN ONE OF
THIS GOODS AREMONTHSTUGRUGSIF YES PLEASE WRITE
THE NUMBER
WRITE "0" IF NONE ►NEXT DURABLE GOOD

NUMBER

TAKE AVERAGE IF
TAKE AVERAGE IF
MORE THAN ONE OF
MORE THAN ONE OF
THIS GOODS WERE
THIS GOODS AREUSEDMONTHSDURABLE GOOD'S NUMBER

DURABLE GOOD'S NUMBERSECTION 9: DURABLE GOODS

DURABLE GOODSIF YES PLEASE WRITE
THE NUMBER
WRITE "0" IF NONE ►NEXT DURABLE GOOD

TUGRUGS

NUMBERHOME APPLIANCES & EQUIPMENT

23 Video Cassette Player

01 Refrigerator

24 Video Camera

02 Vacuum Cleaner

25 Camera

03 Washing machine

26 Computer

04 Sewing machine

27 Other

05 Electric or Gas Stove

HOUSEHOLD TRANSPORTATION & PRIVATE ENTERPRISE GOODS

06 Electric Heater

28 Bicycle

07 Electric Gen-set

29 Motorcycle

08 Electric Iron

30 Truck, Large truck

09 Iron Stove/Brick stove

31 Car10 Other

32 BusFURNITURE

33 Tractors, Combine harvesters

11 Traditional Style Bed, Wooden Bed

34 Other

12 Sofa

JEWELRY

13 Iron Bed

35 Gold jewelry

14 Wardrobe Closet

36 Silver Cup, Silver Products

15 Wooden Table

37 Pipe, Heereg (Snuff Bottle)

16 Wooden Trunk

38 Silver Products for Horses

17 Carpet

39 Other Jewelry

18 Other

DWELLING AND OTHER

ELECTRONIC GOODS, CAMERAS

40 Ger*

19
20
21
22

41 House, Dwelling*
42 Garage
43 Summer House

Radio
Black & White TV
Color TV
Tape Player, CD Player* Please value your dwelling in tugrugs

Mongolia HSES 2010 Manual (Version 1.0)

190

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)

Men's clothing and footwear

20101

Leather jacket, deel

20102

Winter jacket, winter deel

20103

Overcoat

20104

Other leather jacket, winter jacket, deel

20105

Suit, costume

20106

Wool and cashmere sweater

20107

Other shirts

20108

Traditional deel

20110

Sport wear

20111

Hat, neckwear

20112

Trousers

20113

T-shirts

20114

Underwear

20115

Socks

20116

Tights20117

Other men's clothing and footwear(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 20101 - 20117

20199
20200

Women's clothing and footwear

20201

Leather jacket, deel

20202

Winter jacket, winter deel

20203

Overcoat

20204

Other leather jacket, winter jacket, deel

20205

Suit, costume

20206

Wool and cashmere sweater

20207

Other shirts

20208

Traditional deel

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
20100

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

191

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)

Unlined dress and skirts

20210

Sport wear

20211

Hat, neckwear

20212

Trousers

20213

T-shirts

20214

Underwear

20215

Socks

20216

Tights20217

Other women's clothing and footwear(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 20201 - 20217

20299
20300

Children's clothig and footwear (aged 3-13)

20301

Leather jacket, deel

20302

Winter jacket, winter deel

20303

Overcoat

20304

Other leather jacket, winter jacket, deel

20305

Suit, costume20306

Wool and cashmere sweater

20307

Other shirts

20308

Traditional deel

20309

Unlined dress and skirts

20310

Sport wear

20311

Hat, neckwear

20312

Trousers

20313

T-shirts

20314

Underwear

20315

Socks

20316

TightsRECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
20209

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

192

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)Other children's clothing and footwear

20318

All sorts of clothing for children aged 0-2

20319

Wrapping and other articles for infants aged 0-2(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 20301 - 20319

20399
20400

Other articles of clothing

20401

Hat, neckwear, gloves

20402

Tie, belts

20403

Handkerchief

20404

Sewing treads

20405

Other (ribbons, press-studs, zip-fasteners)
Sub total 20401 - 20405

20499
20500

Repair, cleaning and lease of clothing

20501

Dry cleaning

20502

Laundering

20503

Dyeing of garments

20504

Mending, repair

20505

Hire of garments
Sub total 20501 - 20505

20599
20600

Footwear, pairs

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

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
20317

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

193

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)Other footwear

20610

Footwear for children aged 0-2

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 20601 - 20610

20699
20700

Shoes repair and lease

20701

Repair of footwear

20702

Shoe cleaning services

20703

Cost for lease of shoes
Sub total 20701 - 20703

20799
20800

Cloth

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......
Sub total 20801 - 20810

20899
20900

(10.03)

Furnitures, carpets and oilcloth
Furnitures

20901

Furnished and wooden beds

20902

Sofas

20903

Metal beds

20904

Wall and wardrobes

20905

Kitchen furnitures

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
20609

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

194

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)

Bedroom furnitures

20907

Table and chairs

20908

Chest

20909

Electric lamp

20910

Painting and scultures

20911

Mattress

20912

Bath room accessories

20913

Mirror20914

Beds for children

20915

Other furnitures and accessories

20916

Cost for repair and services(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Carpets and floor covering, sq.m
20917

Carpets

20918

Strip of carpet/mat

20919

Capping

20920

Oilcloth for the floor

20921

Other floor covering

20922

Cost for repair and services
Sub total 20901 - 20922

20999
21000

Domestic woven and sewn appliances, piece

21001

Curtains

21002

Bedsheets

21003

Bed covering

21004

Towel

21005

Bath towel

21006

Tablecloth

21007

Other woven, sewn and cloth appliances

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
20906

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

195

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)WRITE ZERO IF NOTHINGTUGRUGS

Cost for repair and services
Sub total 21001 - 21008

21099
21100

(10.03)

Domestic electric appliances, piece
Domestic durable electric appliances

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 conditioner etc)

21113

Cost for repair and services
Domestic minor electric appliances

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
Sub total 21101 - 21119

21199
21200

Domestic utensils, piece

21201

Glasses

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
21008

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

196

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)

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(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 21201 - 21208

21299
21300

Domestic tools, piece

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

Bell

21311

Signal accessories

21312

Other

21313

Cost of repair and service
Sub total 21301 - 21313

21399
21400

Domestic sanitary and cleaning materials

21401

Laundry soap, piece

21402

Washing powder/detergent, piece

21403

Match, piece

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
21202

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

197

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Candle, pieceNon-durable domestic goods

21405

Shoe polish, piece

21406

Sterilization materials, kg

21407

Other cleaning materials

21408

Brush, besom, piece

21409

Garbage basin, piece

21410

Brush, polisher, piece

21411

Clothes-hanger, piece

21412

Needle for sewing and woven, piece

21413

Nails, nut, screw

21414

Glue, scotch tape21415

Other tools
House services:

21416

House sweeper

21417

Cost disinfection and sterilization

21418

Dry cleaning

21419

Cost for lease of domestic goods
Sub total 21401 - 21419

21499
21500

Medicine, medical care and services
Medicines and other products:

21501

Tablets, vitamins

21502

Injection

21503

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

21504

Eye glasses, contact lenses

21505

Other devices (hearing devices, artificial limbs etc)

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
21404

PURCHASED

Medical care:
Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

198

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)Outpatient's clinic examination

21507

Dental care

21508

Other medical services (to give an injection, X-ray etc)

21509

In patient

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 21501 - 21509

21599
21600

(10.03)

Activities of private transportation
Transport:

21601

Car

21602

Bus

21603

Trucks21604

Motorcycle

21605

Bicycle21606

Carting

21607

Repair and services of auto vehicles

21608

Wheels21609

Spare parts of auto mobile

21610

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 license etc)

21616

Cost for transportation rent
Sub total 21601 - 21616

21699
21700

Transportation services:

21701

Cost for bus and trolleybus

21702

Railway passenger service: Domestic

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
21506

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

199

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)

Railway passenger service: International

21704

Railway freight

21705

Taxi cost: Inside the city

21706

Road transportation service: inter-urban (microbus, taxi etc)

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

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 21701 - 21714

21799
21800

(10.03)

Communication
Post services

21801

Letters, parcel, post card

21802

Stamps, envelope (new)Telephone, fax mashine

21803

Telephone, fax mashine

21804

Repair cost of telephone and fax mashine
Telephone and Facimile

21805

Calling: Inter-urban

21806

Calling: International

21807

Telephone charge

21808

Mobile/cell phone

21809

Service charge of telegraph, telex and facimile

21810

Lease cost of telephone and fax

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
21703

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

WRITE ZERO IF NOTHINGTUGRUGS

WRITE ZERO IF NOTHINGTUGRUGS

200

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)

Installing charge of equipments

21812

Calling card

21813

Charge for internet service

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 21801 - 21813

21899
21900

(10.03)Equipment for leisure and durable goods
Sound, picture, photograph, data processing equipment, piece:

21901

Radio

21902

Black-white TV

21903

Color TV

21904

TV aerial

21905

Tape-recorder

21906

Video player

21907

Video camer

21908

Binoculars

21909

Camera21910

Computer

21911

Calculator

21912

Audio and video cassette, CD

21913

Films

21914

Repair cost of above equipments
Durable goods for leisure21915

Travel tools (boat etc)

21916

Musical instruments (guitar etc)

21917

Billiard board

21918

Repair cost of above tools
Sub total 21901 - 21918

21999
22000

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
21811

PURCHASED

Other goods for leisure, domestic animals (pets)
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SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)

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, treatment etc)

(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 22001 - 22018

22099
22100

Leisure and cultural services

22101

Driving lessons

22102

Fee for sport 's group study

22103

Performance fee (cinema, drama, concert, museum)

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

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
22001

PURCHASED

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SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Lottery
Sub total 22101 - 22108

22199
22200

Newspapers, books and stationary

22201

Newspapers and journals

22202

Notebook

22203

Pen

22204

Pencil22205

Books and dictionary

22206

Paper

22207

Other printed matters (post card, calendar etc)

22208

Other stationary (ink, erassor, folder etc)
Sub total 22201 - 22208

22299
22300

Recreation and travel

22301

Total cost for recreation and travel

22400

Education

22401

Tuition fee: pre-primary

22402

Tuition fee: primary

22403

Tuition fee: literacy programmes for students too old

22404

Tuition fee: secondary

22405

Tertiary

22406

CourseSub total 22401 - 22406

22499
22500

Hotels, dormitories and restaurants

22501

Restaurants, cafes

22502

Canteens in schools, works canteens

22503

Accommodation services of hotels

22504

Accommodation services of holidays villages

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
22108

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

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SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Accommodation services of boarding schools, universities
Sub total 22501 - 22505

22599
22600

Personal care

22601

Toothbrush

22602

Tooth paste

22603

Beauty soap

22604

Toilet paper

22605

Sanitary nupkins
Hair cutting and beauty:

22606

Hairdressing

22607

Beauty salon
Electric appliances for beauty:

22608

Electric razors

22609

Hair dryier

22610

Other electric appliances

22611

Repair of such appliances
Other appliances for beauty:

22612

Non-electrical razors

22613

Other non-electrical appliances

22614

Beauty powder

22615

Perfume22616

Other beauty products
Sub total 22601 - 22616

22699
22700

Valuables
Valuables:

22701

Valuables

22702

Watches

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
22505

PURCHASED

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204

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)

Repair for valuables

22704

Watch repair(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Other appliances:
22705

Suitcase

22706

Bag

22707

Wallet22708

Baby's cart, chair

22709

Tube, lighter, ash-tray

22710

Sun glasses, umbrella

22711

Appliances for funeral (coffin, stone etc)

22712

Repair of above appliances
Sub total 22701 - 22712

22799
22800

Social welfare

22801

Service fees for caring elders and disabled people

22900

Insurance

22901

Health insurance

22902

Life insurance

22903

Dwelling insurance

22904

Transport insurance

22905

Other
Sub total 22901 - 22905

22999
23000

Financial service

23001

Fee for financial consultation

23002

Service fees for banks and other financial institutions
Sub total 23001 - 23002

23099
23100

Other services

23101

Fees for administrative documents (for birth, marriage ..)RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
22703

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

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205

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)

Payment for the services of property managers and agents

23103

Fees for legal services, employment agencies

23104

Charges for the leasing or rental

23105

Other services(10.03)

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 23101 - 23105

23199
23200

Materials for building repair

23201

Wall paper, package

23202

Oil paint, l

23203

Bricks, piece

23204

Cement, kg

23205

Glass, m2

23206

Other......
Sub total 23201 - 23206

23299
24100

Cost related to housing durable goods

24101

Apartment

24102

House

24103

Ger (complete)

24104

Tent frame

24105

Tent covering

24106

Yard

24107

Stove

24108

Other
Sub total 24101 - 24107

24199
24200

Tax

24201

Income tax

24202

Cattle tax

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
23102

PURCHASED

Mongolia HSES 2010 Manual (Version 1.0)

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206

SECTION 10: NON-FOOD EXPENDITURE AND CONSUMPTIONPURCHASEDITEM CODERESPONDENT: MOST INFORMED HOUSEHOLD MEMBER
ASK (10.01) FOR ALL ITEMS FIRST, PUTTING "1" FOR YES IN THE FIRST BOX OR "2" FOR "NO" IN THE
SECOND BOX. THEN ASK (10.02, (10.03)) AND (10.04) ONLY FOR THE ITEMS THAT WERE ACQUIRED(10.01)YES

Have you or any member of your household bought or received without paying cash for any [..[ITEM]..] forthe last 12 months?

1(10.02)Land tax

24204

Other taxes

WRITE ZERO IF NOTHINGTUGRUGS

Sub total 24201 - 24204

24299
24300

Cost for gifts, assistance and celebration

24301

Gifts for individual

24302

Cost for celebration and wedding

24303

For church and temple

24304

For institution

24305

Other

24399

(10.03)

RECEIVED FREE
(10.04)

How much did all members of
How much did all members ofWhat is the value of all ..[ITEM]..
your household spend on
your household spend onthat all members of your household
NO purchases of ..[ITEM].. during the purchases of ..[ITEM].. during the received free during the past 12
past month?
past 12 months?
months?
2

ITEMS
24203

PURCHASED

Sub total 24301 - 24305

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Database documentation for the HSES Mongolia 2010

HOUSEHOLD SOCIO ECONOMIC SURVEY

MONGOLIA 2010DATABASE DOCUMENTATION

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Database documentation for the HSES Mongolia 2010

Introduction

The database generated for the Mongolia Household Socio Economic Survey - 2010 is composed by the following 16
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_energy.dta
12_payment_serv.dta
13_durable.dta
14_non_food.dta
15_urb_diary.dta
16_rur_food_7d.dta

This document contains the description of all those 16 files, including all the variables and its categories when applicable.

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abase documentation for the HSES Mongolia 201001_hholdNb.

VariableName
1 household_id

2
3
4
5
6
7

q0008
hh_no
v1_dd
v1_mm
v1_yy
v1_res8 v2_dd
9 v2_mm
10 v2_yy
11 v2_res

12 v3_dd
13 v3_mm
14 v3_yy
15 v3_res

16 v4_dd
17 v4_mm
18 v4_yy
19 v4_res

20 q0507

Label

Categories
Code

Label

8 Nb of hh members
HH_NO
Visit 1 DD
Visit 1 MM
Visit 1 YY
Visit 1 Result
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

Visit 2 DD
Visit 2 MM
Visit 2 YY
Visit 2 Result

Visit 3 DD
Visit 3 MM
Visit 3 YY
Visit 3 Result

Visit 4 DD
Visit 4 MM
Visit 4 YY
Visit 4 Result

0507 Has produced animal
products past 12m?

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abase documentation for the HSES Mongolia 201001_hholdNb.

VariableName

21 q0515

22 q0516
23 q0517

24 q0501

25 q0518
26 q0601

27 q0602
28 q0707

Label
0515 Agricultural land in past 12m?

33

34 q080435

36 q0806

Label

1
2

YES
NO

1
2

YES
NO

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

METAL
ASPHALT ROOF SHINGLES

0516 What is total amount owned
the past 12M
0517 Has vegetables, fruits in pas
12M

05-01 Raised or Owned
Herding,poultry or any animal?
0518 What is total amountagricultural land HH members
past0601. Are there household
enterprises?

0602. How many enterprises?
07-07 :Has any member received
money or goods

29 cluster2 missing

29 visitor
30 ndays
31 q0801
32 q0802

Categories
Code

Number of visitors Cover Form 2
Number of days Cover Form 2
0801. Number of dwellings
0802. Is main dwelling?

0803. Type of Dwellings

0804. Number of rooms in thedwelling
0805. Main material of the walls

0806. Main material of the roof

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abase documentation for the HSES Mongolia 201001_hholdNb.

VariableName

37 q0807

38 q0808
39 q0809
40 q0810
41 q0811
42 q0812

43 q0813

44 q0814Label

52 q0822

1
2

SINGLEDOUBLE

1
2

SINGLEDOUBLE

1
2
3

WOOD
EARTH
OTHER

99

***Undefined Label

1
2
3

STATE
ORGANIZATION'SPRIVATE

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 BOILEROTHERS0814. Main material of the floor

46 q0816
47 q0817

51 q0821

WOOD
CEMENT
EARTH
OTHER

0813. Covering of the frame

0816. How long have you been
living0817. Type of ownership

50 q0820

12
3
40808. Living area
0809. Total useful area
0810. What is the total area
occupies
0811. Number of walls in the ger
0812. Covering of the ceiling

0815. How old is this dwelling

49 q0819Label

0807. Main material of the floor

45 q0815

48 q0818

Categories
Code
3 TILE
4 OTHER0818. How was acquired

0819. Did you borrow any money
to acquire

0820. If you wanted to rent, how
much
If don't know, write 99.

0821. How much do you pay forrent
0822. What is the main source ofheating

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abase documentation for the HSES Mongolia 201001_hholdNb.

VariableName
53 q0823

54 q0824

55 q0825

56 q0826

57 q0827

58 q0828

59 q0829

60 q0830_1
61 q0830_2
62 q0830_3
63 q0830_4
64 q0830_5
65 q0831

Label
0823. Source of electricity

Categories
Code

Label

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

YES
NO

1
2
3
4

THROUGH TUBE
SPECIAL PLACE FOR WASTENO 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 PHONENO

0824. Electricity resource
adequate for operating electricd

0825. Water supply

0826. Has the household asewage system

0827. Household waste disposal

0828. What type of toilet do you
have

0829. Has a telephone

0830. 1-Distance to the nearest 8
GRADE school
0830. 2-Distance to the nearest
10 GRADE school
0830. 3-Distance to the nearest
medical care
0830. 4-Distance to the nearest
pharmacy
0830. 5-Distance to the nearest
well
0831. Anybody from yourhousehold own or exploit land ?

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abase documentation for the HSES Mongolia 201001_hholdNb.

VariableName

66 q0832_a
67 q0832_b
68 q0833

69 q0834
70 q0835_1

71 q0835_2

72 q0835_3

73 q0835_4

74 q0835_5

Label

Categories
Code
1 YES
2 NO

0832. How many hectares does
your household OWN?
0832. How many hectares does
your household OPERATE?
0833. Use internet normally?
1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

1
2

YES
NO

0834. How many household
member0835_1. Where used internet, at
home

0835_2. Where used internet, at
work

0835_3. Where used internet,
internet café

0835_4. Where used interne, freepublic accesst

0835_5. Where used internet,
other

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Database documentation for the HSES Mongolia 2010
02_indiv
Variable
Label
Nb.
Name
1 household_id
Ind ID
2 ind_id102. Relationship to head
3 q0102

Categories
Label

Code

1 HEAD
2 WIFE / HUSBAND
3 SON / DAUGHTER
4 FATHER / MOTHER
5 BROTHER / SISTER
6 FATHER / MOTHER IN LAW
7--------------------------------------------BROTHER / SISTER IN LAW 7 SON / DAUGHTER IN LAW
8 GRAND PARENT
9 GRANDCHILD
10 OTHER RELATIVE
11 SERVANT
12 OTHER
4 q0103

5
6
7
8

q0104
q0105yq0105mq0106

103. Sex

107. Spouse ID CODE

10 q0108108. Father ID CODE

12 q0110a
13 q0110
14 q0111

15 q0201

16 q0202

17 q0203
18 q0204

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
3
4
5

NONE
PRIMARY
SECONDARYCOMPLETE SECONDARYVOCATIONAL

104. Year of birth105. Age Yrs
105. Age Mths
106. Marital Status

9 q0107

11 q01091
2

109. Mother ID CODE

110 A. Days away past month110. Months away
111. Is HH member?

201. Is 6 years or more?

202. Is answering personally?

203. Respondent ID CODE
204. Highest certificate obtained

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Database documentation for the HSES Mongolia 2010
02_indiv
Variable
Nb.

Label

Name

19 q0205

20 q0206

21 q0207

22 q0208

23 q0209t

24 q0209g
25 q0210

26 q0211

27 q0212

28 q0213

Categories
Code
Label
6 DEGREE OR HIGHER EDUCATION DIPLOMA
7 BACHELOR
8 MASTER
9 PHD, DOCTOR DEGREE
10 OTHER

205. Can read a letter?
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

206. Are you attending School?

207. Check age/ between 8-35 years

208. Reason never attended school

209. Current education TYPE

209. Current education GRADE
210. Type of School

211. School Location

212. Place where person lives during
school213. Pay tuition?

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Database documentation for the HSES Mongolia 2010
02_indiv
Variable
Nb.

Name

Label

29 q0214_1

214_1. Expenditures during past 12
months in room rent

30 q0214_2

214_2. Expenditures during past 12
months in tuition paid by

31 q0214_3

214_3. Expenditures during past 12
months in tuition paid fr

32 q0214_4

214_4. Expenditures during past 12
months in books and suppl

33 q0214_5

214_5. Expenditures during past 12
months in uniforms

34 q0214_6

214_6. Expenditures during past 12
months in transport

35 q0214_7

214_7. Expenditures during past 12
months in others

36 q0214_8

214_8. Expenditures during past 12
months in TOTAL

37 q0301

301. Answering personally?

38 q0302
39 q0303

40 q0304a

41 q0304b

42 q0305

43 q0306

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

302. Respondent ID CODE
303. Any health problem during pastmonth?

304_A. Health problem (1)304_B. Health problem (2)305. Did you seek treatment in past 1 M?

306. Why didn't seek treatment?

Mongolia HSES 2010 Manual (Version 1.0)

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Database documentation for the HSES Mongolia 2010
02_indiv
VariableNb.

Name

44 q0307

45 q0308Label

307. Where was treatment provided?

309_1. Amount paid in facility or healt
practitioner

47 q309_2

309_2. Amount paid in transportation orothers

48 q0310

310. Have bought medicines in the past M?

50 q0312

51 q0313

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 CLINICPRIVATEABROADOTHER

308. Who provided medical service foryour treatment?

46 q309_1

49 q0311

Categories
Code
Label
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
11 DIDN'T KNOW FROM WHERE TO GET TREATMENT
12 TRADITIONAL HEALER

311. Amount spent in medicines
312. Have stayed at hospital in past 12
M?

313. What was the Hospital ?

52 q0314

314. How much did you pay for all costs

53 q0315

315. Amount spent in transportation

Mongolia HSES 2010 Manual (Version 1.0)

218

Database documentation for the HSES Mongolia 2010
02_indiv
VariableNb.
Name
54 q0401

55 q0402

Label
4.01 Respondent 10 yrs or more?

4.03 ID CODE of respondent

57 q0404

4.04 Did you any job for the past 7 days?

59 q0406

60 q0407

61 q0408

62 q0409

63 q0410

64 q0411c
65 q0412c
66 q0413
67 q0414

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 WORK
OTHER

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

Partnership
Cooperative
Corporation

4.02 Answering by himself?

56 q0403

58 q0405

Categories
Label

Code

4.05 What kind of work was the main job
you did?

4.06 Any permanent job despite you did
no job in last 7 day

4.07 Main reasong for not doing job in last
7 days

4.08 Did you look for a job in last 7 days

4.09 Reasons for not looking for a job

4.10 Registered in labour and social
welfare dep?

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

Mongolia HSES 2010 Manual (Version 1.0)

219

Database documentation for the HSES Mongolia 2010
02_indiv
VariableNb.

Name

68 q0415

Label

Categories
Code
Label
4 LLC
5 State owned company
6 Local authority owned company
7 Government organisation
8 NGO
9 Other

4.15 Do your receive any salary in cash
and/or in kind1
2

69 q0416a
70 q0416b
71 q0416c

YESNO

4.16 Salary amount - past month
4.16 Salary amount - past 12 months
4.16 Bonuses and special allowances

Mongolia HSES 2010 Manual (Version 1.0)

220

Database documentation for the HSES Mongolia 201003_livestock
Variable
Nb.
Name
Label
1 household_id
2 ani_id
Animal Number

3
4
5
6
7
8

q0502_1
q0502_2
q0502_3
q0503
q0504
q0505

502-1. TOTAL
502-2. Number of female502-3. Number of young
503. Use for own food504. Number of sold505. Amount received

Categories
Label

Code

1
2
3
4
5
6

Mongolia HSES 2010 Manual (Version 1.0)

CattleHorsesCamels
Sheep
Goats
Other

221

Database documentation for the HSES Mongolia 201004_livestock_exp
VariableNb.
Name
1 household_id
2 exp_id
Exp number

Label

Code

1
2
3
4
5
3 q0506

05 06: Expenditures on this [herding activity] in the last 1

Mongolia HSES 2010 Manual (Version 1.0)

Categories
Label

Animal Feed
Drugs and veterinary costs
Gassoline /OilTaxes and Insurance
Other

222

Database documentation for the HSES Mongolia 201005_by_product
Variable
Label
Nb.
Name
1 household_id
By-product number
2 byprod_id

3 q0508

4
5
6
7
8

q0509
q0510
q0511
q0512
q0513

9 q0514

Categories
Label

Code

1
2
3
4
5
6

Goat cashmere, kg
Wool, hair, cashmere, kg
Skins and hides, pieces
Milk, airag, liters
Eggs, (number)
Other by-products

1
2

YES
NO

508. In the past 12 months have yourhousehold produced ..?

509. Total Production
510. Quantity consumed by household
511. Quantity sold
512. Total amount received from sales
513. Quantity produced and sold514. Total amount received from produced
and sold

Mongolia HSES 2010 Manual (Version 1.0)

223

Database documentation for the HSES Mongolia 201006_crop
VariableNb.
Name
1 household_id
2 crop_id
Crop Number

3 q0519

4
5
6
7
8

q0520
q0521
q0522
q0523qq0523tLabel

Categories
Label

Code

1
2
3
4
5
6
7
8
9
10
11

Potatoes
Carrots
Turnip
Cabbage
Beetroot
Onion
GarlicTomatoes
CucumberFruitsOther…

1
2

YES
NO

519. Did harvest during past 12 M?

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)

Mongolia HSES 2010 Manual (Version 1.0)

224

Database documentation for the HSES Mongolia 201007_agric_exp
Variable
Nb.
Name
Label
1 household_id
2 exp_id
Expenditure Item

3 q0524

Code

Categories
Label

1
2
3
4
5
6
7
8
9
10
11
12

Seeds
Fertilizers
Extermination of vermin
Equipent & Tools
Spareparts
Repairs and services
Raw materials
Gasoline, fuelTaxes , insurances and fees
Rent
Loan interest
Others05-24: Total expenditures on item during past 12 mths

Mongolia HSES 2010 Manual (Version 1.0)

225

Database documentation for the HSES Mongolia 201008_enterprise
Variable
Label
Nb.
Name
1 household_id
Enterprise Number (1-2-3)
2 en0603. Activity Code
3 q0603c
0604. What % of this enterprise is owned bymembers
4 q06040605. How many members work in this enterprise
5 q06050606. How many not members work in thisenterprise past mont
6 q0606
0607_01: Expenditures in: Goods for resale
7 q0607_01
0607_02: Expenditures in: Raw materials
8 q0607_02
0607_03: Expenditures in: Gasoline, fuel9 q0607_03
0607_04: Expenditures in: Equipment
10 q0607_04
0607_05: Expenditures in: Rental of facilities
11 q0607_05
0607_06: Expenditures in: Spare parts
12 q0607_06

18 q0609_1a19 q0609_1b

0607_07: Expenditures in: Repair and maintenance
0607_08: Expenditures in: Tax, fees, patent,
license, insura
0607_09: Expenditures in: Other expenses(labor,water, steam
0607_19: TOTAL EXPENSES
0608: Months in operation?
0609-1. Amount received in a average month (permth)
0609-1. Number of average months

20 q0609_2a
21 q0609_2b

0612-2. Amount received in a bad month (per mth)
0609-2. Number of bad months

22 q0609_3a
23 q0609_3b

0609-3. Amount received in a good month (per mth)
0609-3. Number of good months

13 q0607_07
14 q0607_08
15 q0607_09
16 q0607_10
17 q0608

Code

Mongolia HSES 2010 Manual (Version 1.0)

Categories
Label

226

Database documentation for the HSES Mongolia 2010
09_other_income
Variable
Nb.
Name
Label
1 household_id
2 income_id
Source Number

3 q0701

4 q0702_ic
5 q0702_t
6 q0703_ic
7 q0703_t
8 q0704_ic
9 q0704_t
10 q0705_ic
11 q0705_t
12 q0706_ic
13 q0706_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

State pension
Special Pension
Unemployment benefit
Maternity benefits
Disability pension
Survivor pension
Illness payments
Funeral payments
Baby care allowancesChild allowances (transferred to accoun
Child allowances (received in cash)
Other social benefit
Rent of own assets (land, buildings, ve
Sale of assets
Inheritances and wedding presents
Loan repayments
Withdrawals from bank savings
savings?
Dividends?
Loan?
Treasury Bond?
Gambling, lottery and contest
Other income (from intellectual propert

1
2

YES
NO

07-01: Has anybody received ...

07_02: ID CODE 1
07_02: Amount during the past 12 mths (1)07_03: ID CODE 2
07_03: Amount during the past 12 mths (2)07_04: ID CODE 3
07_04: Amount during the past 12 mths (3)07_05: ID CODE 4
07_05: Amount during the past 12 mths (4)07_06: ID CODE 5
07_06: Amount during the past 12 mths (5)Mongolia HSES 2010 Manual (Version 1.0)

227

Database documentation for the HSES Mongolia 2010
10_remittance
Variable
Label
Nb.
Name
1 household_id
Line Number
2 ln
0708 ID CODE
3 ind_id
0709. Who gave the gift
4 q0709

5 q0710

6 q0711

7 q07128 q0713

9 q0714

Code

Categories
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

HOUSEHOLD USEEDUCATION8 TUITION FEE
MEDICAL TREATMENT
PURCHASE OF DWELLINGHOLIDAY/FUNERALHOUDEHOLD ENTERPRISE
OTHER

1
2
3
4
5
6
7
8

URBAN
RURAL
KOREA
USA
ENGLANDGERMANYJAPANOTHER COUNTRY

1
2
3
4
5

YES, weekly
YES, monthly
YES, quarterly
YES, annualy
NO

1
2
3
4
5

CASH
BY ACCOUNTCASH REMITTANCE
IN KIND
OTHER

0710 Purpose of the receipt

0711. From where the gifts

0712. How much was received during
the past 12 M (TUGR)
0713. Do receive it regularly?

0714. How do you receive it?

Mongolia HSES 2010 Manual (Version 1.0)

228

Database documentation for the HSES Mongolia 201011_energy
Variable
Label
Nb.
Name
1 household_id
Source Number
2 energy_id

3 q0836

4 q0837

Electricity
Firewood, m3
Coal, tonDung, ton
Gas fuel, l
Other

1
2

YES
NO

1
2
3
4

Collect ourselves
PurchaseCollect and Purchase
Other0837. How do you mainly obtain [FUEL]?

7 q0840
8 q08410841. Value of ... received free in past 12 months

6 q0839

1
2
3
4
5
6
0836. Have used the source?

0838. How much have you consumed for the past
12 motnths?
0839. Amount spend on purchases of ... in pastmonth0840. Amount spend on purchases of ... in past
12 months

5 q0838

Categories
Label

Code

Mongolia HSES 2010 Manual (Version 1.0)

229

Database documentation for the HSES Mongolia 201012_payment_serv
Variable
Nb.

Label

Name

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

1 household_id
Service Number
2 item

3 q0842

4 q0843
5 q0844
6 q08450842. Have bought or received free.. during past
12 m?

0843. Amount spend on purchases of .. during
past month0844. Amount spend on purchases of .. during
past 12 months
0845. Value of .. received free during past 12
monthsMongolia HSES 2010 Manual (Version 1.0)

230

Database documentation for the HSES Mongolia 2010
13_durable
Variable
Nb.
Name
Label
1 household_id
2 durable_id
GOOD NUMBER

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
3 q0901
4 q0902
5 q0903

0901 Number of durable good
0902 How long have you used this good0903 Please value this good

Mongolia HSES 2010 Manual (Version 1.0)

Categories
Label

Refrigerator
Vacuum Cleaner
Washing machine
Sewing machineElectric or Gas Stove
Electric Heater
Electric Gen-set
Electric Iron
Iron Stove/Brick stove
Other home appliances & equipment
Traditional Style Bed, Wooden Bed
Sofa
Iron Bed
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
Gold jewelry
Silver Cup, Silver Products
Pipe, Heereg (Snuff Bottle)
Silver Products for Horses
Other Jewelry
Ger
House, Dwelling
GarageSummer House

231

Database documentation for the HSES Mongolia 2010
14_non_food
Variable
Label
Nb.
Name
1 household_id
Non-food Item code
2 itemCode

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: Socks
20115 Men: Tights
20116 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: Socks
20216 Women: Tights
20217 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: Socks
20316 Children: Tights
20317 Other children's clothing and footwear
20318 All sorts of clothing for children aged
20319 Wrapping and other articles for infants

Mongolia HSES 2010 Manual (Version 1.0)

232

Database documentation for the HSES Mongolia 2010
14_non_food
Variable
Nb.

Name

Label

Categories
Code
Label
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
20921 Other floor covering

Mongolia HSES 2010 Manual (Version 1.0)

233

Database documentation for the HSES Mongolia 2010
14_non_food
Variable
Nb.

Name

Label

Categories
Code
Label
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

Mongolia HSES 2010 Manual (Version 1.0)

234

Database documentation for the HSES Mongolia 2010
14_non_food
Variable
Nb.

Name

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

Mongolia HSES 2010 Manual (Version 1.0)

235

Database documentation for the HSES Mongolia 2010
14_non_food
Variable
Nb.

Name

Label

Categories
Code
Label
21802 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)

Mongolia HSES 2010 Manual (Version 1.0)

236

Database documentation for the HSES Mongolia 2010
14_non_food
Variable
Nb.

Name

Label

Categories
Code
Label
22107 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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Database documentation for the HSES Mongolia 2010
14_non_food
VariableNb.

Name

3 q1001

Label

Categories
Code
Label
22904 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

1001. Have you bought or received for thelast 12 Ms
1
2

4 q10021002. Purchased during the past month

5 q10031003. Purchased during the past 12 months
1004. Received free during the past 12
months

6 q1004

YES
NO

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Database documentation for the HSES Mongolia 201015_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

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Database documentation for the HSES Mongolia 201015_urb_diary
Variable
Nb.

Name

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

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Database documentation for the HSES Mongolia 201015_urb_diary
VariableNb.

Name

3 s11yn

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

Auxiliary 'Consumed? Y/N'
1
2

4 q1101_1
5 q1101_2
6 q1101_3
7 q1101_4
8 q1102_1
9 q1102_2
10 q1102_3
11 q1102_4
12 q1103_1
13 q1103_2
14 q1103_3
15 q1103_4
16 q1104
17

imputed_up

1101_1 First 10 - Total consumed
1101_2 First 10 - Purchased
1101_3 First 10 - Reseived free
1101_4 First 10 - Own production
1102_1 Second 10 - Total consumed
1102_2 Second 10 - Purchased
1102_3 Second 10 - Reseived free
1102_4 Second 10 - Own production
1103_1 Third 10 - Total consumed
1103_2 Third 10 - Purchased
1103_3 Third 10 - Reseived free
1103_4 Third 10 - Own production
1104 Average unit priceimputed unit price computed by the author

Mongolia HSES 2010 Manual (Version 1.0)

YES
NO

241

Database documentation for the HSES Mongolia 201016_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

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Database documentation for the HSES Mongolia 201016_rur_food_7d
Variable
Nb.

Name

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

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Database documentation for the HSES Mongolia 201016_rur_food_7d
VariableNb.

Name

3 q1201

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) - Gr1901. Have you consumed food during the 7 days
1
2

4
5
6
7
8

q1202
q1203
q1204
q1205
q1206

1202. Total consumed in the past 7 days
1203. Consumed from purchases
1204. Unit price1205. Consumed from Received free
1206. Consumed from Produced

9

imputed_up

imputed unit price computed by the author

Mongolia HSES 2010 Manual (Version 1.0)

YES
NO

244

17 Basicvar
1 identif
2 hhsize
3 cluster
4 aimag

5 location

6 urban7 region

8 month
9 quarter
10 hhweight
11 strata
12 stratum
13 aimagsoumgroup(identif)
Household size
ClusterAimag
1 Arhangai (01)2 Bayan-Ulgii (02)3 Bayanhongor (03)4 Bulgan (04)
5 Govi-Altai (05)
6 Dornogovi (06)7 Dornod (07)8 Dundgovi (08)9 Zavhan (09)10 Uvurhangai (10)11 Umnugovi (11)12 Suhbaatar (12)13 Selenge (13)14 Tuv (14)15 Uvs (15)16 Hovd (16)17 Huvsgul (17)18 Hentii (18)19 Darhan-Uul (19)20 Ulaanbaatar (20)21 Orhon (21)22 Govisumber (22)Strata 4 locations
1 Ulaanbaatar
2 Aimagcenter
3 Soumcenter4 Countryside
Urban/rural
1 Urban
2 RuralRegion1 West2 Highlands
3 Central
4 East5 Ulaanbaatar
Calendar month of the interview
Calendar quarter of the interview
Strata 3
Combinations of aimags and soums

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18 HH_inc_exp

This is the author’s trial estimation of household-level monthly income and expenditure.
No

Variable

Description

1

identif2

wage

wage income

3

pensionpension4

livestock

income from livestock

5

agriculture

agricultural income

6businessbusiness income

7

other

other income (remittance)

8

ttinc

monthly total household income

9

u_pur

urban food purchased10

u_freeurban food received free

11

u_own

urban food own production

12

r_pur

rural food purchased

13

r_freerural food received free

14

r_own

rural food own production

15

nfood

non-food from clothing up to materials for building repair

16

nfoodotherhousehold durable goods, tax, assistance and celebration

17

nfoodgifts

gift for individuals

18

nfoodfree

non-food received free

19

food

sum of food (9 to 14)

20

monetary_exp

sum of monetary expenditure

21

ttexp

monthly total household expenditure

Mongolia HSES 2010 Manual (Version 1.0)