Users’ Manual for Handling Resampled Micro Data of
Cambodia Socio-Economic Survey (CSES)
CSES 2012

Version 2.0

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

1

History of revision of the manualSecond version 2.0 in March 2019
- Revised based on the discussion during the workshop in December 2018

First draft version 1.0 in December 2018

Manual Cambodia CSES 2012 Version 2.0

2

CONTENTSCSES 2012
Chapter 1. About this Manual

Page 4

Chapter 2. Outline of CSES 2009

6

Chapter 3. Data and metadata provided

17

Chapter 4. Data import
4.1 Import STATA files into R

22

4.2 Structure of data files

25

4.3 Names and types of variables

32

Chapter 5. Data check5.1 Summary of each data file53

5.2 Frequency of categorical variables

80

5.3 Relationship among data files and identifiers

101

Chapter 6. Household expenditure112

6.1 Food items

114

6.2 Non-food items

118

6.3 Housing

121

6.4 Total expenditure

124

Chapter 7. Household income
7.0 Provided summary file of housheold income

130

7.1 Wage and salary136

7.2 Agricultural income

138

7.3 Non-agricultural income

144

7.4 Income Own House

146

7.5 Property income

149

7.6 Transfers received

153

7.7 Negative transfers

159

Chapter 8. Resampled micro data to be provided

166

Manual Cambodia CSES 2012 Version 2.0

3Appendix:
1. Diary form172

2. Household questionnaire

174

3. Rules for income composition

229

Manual Cambodia CSES 2012 Version 2.0

4Chapter 1. About this Manual
1. This manual was prepared for users to use the next 80% resampled micro data sets of Cambodia
Socio-Economic Survey 2012.
80% resampled micro data set (38 files)
In CSV format[1] "Households_80.csv""HHMembers_80.csv"[3] "HHFoodConsumption_80.csv""HHRecallNonFood_80.csv"[5] "HHVulnerability_80.csv""PersonEducation_80.csv"[7] "HHHousing_80.csv""HHLandOwnership_80.csv"[9] "HHProductionCrops_80.csv""HHCostCultivationCrops_80.csv"[11] "HHInventoryCrops_80.csv""HHSalesCrops_80.csv"[13] "HHLivestock1_80.csv""HHLivestock2_80.csv"[15] "HHFishCultivation1_80.csv""HHFishCultivation2_80.csv"[17] "HHFishCultivation3_80.csv""HHForestryHunting1_80.csv"[19] "HHForestryHunting2_80.csv""HHNonAgriculture1_80.csv"[21] "HHNonAgriculture2_80.csv""HHNonAgriculture3_80.csv"[23] "HHLiabilities_80.csv""HHIncomeOtherSource_80.csv"[25] "HHConstruction_80.csv""HHDurableGoods_80.csv"[27] "PersonMaternalHealth_80.csv""PersonHealthU2_80.csv"[29] "PersonIllness_80.csv""PersonDisability_80.csv"[31] "PersonEcoCurrent_80.csv""PersonviolenceA_80.csv"[33] "PersonViolenceB_80.csv""HHOtherInfo_80.csv"[35] "PSUListing_80.csv""weighthouseholds_80.csv"[37] "weightpersons_80.csv""hhexp_80.csv"[39] "hhinc_80.csv"
In R format[1] "Households.80""HHMembers.80"[3] "HHFoodConsumption.80""HHRecallNonFood.80"[5] "HHVulnerability.80""PersonEducation.80"[7] "HHHousing.80""HHLandOwnership.80"[9] "HHProductionCrops.80""HHCostCultivationCrops.80"[11] "HHInventoryCrops.80""HHSalesCrops.80"[13] "HHLivestock1.80""HHLivestock2.80"

Manual Cambodia CSES 2012 Version 2.0

5[15] "HHFishCultivation1.80""HHFishCultivation2.80"[17] "HHFishCultivation3.80""HHForestryHunting1.80"[19] "HHForestryHunting2.80""HHNonAgriculture1.80"[21] "HHNonAgriculture2.80""HHNonAgriculture3.80"[23] "HHLiabilities.80""HHIncomeOtherSource.80"[25] "HHConstruction.80""HHDurableGoods.80"[27] "PersonMaternalHealth.80""PersonHealthU2.80"[29] "PersonIllness.80""PersonDisability.80"[31] "PersonEcoCurrent.80""PersonviolenceA.80"[33] "PersonViolenceB.80""HHOtherInfo.80"[35] "PSUListing.80""weighthouseholds.80"[37] "weightpersons.80""hhexp.80"[39] "hhinc.80"

2. The original micro data sets composed of all the samples of CSES were provided by National
Institute of Statistics (NIS), Cambodia in 2015 based on the Charter for Experimental
Laboratory for Research Purpose Statistical Use of Micro Data, and resampled at the rate of
80% by Sinfonica.

3. The above resampled data sets are available through the Institute of Statistical Mathematics(ISM) both in CSV and R format.

4. This manual was first compiled in November 2018 by;
Hiroshige Furuta
Visiting Senior Research Fellow, Sinfonica

Manual Cambodia CSES 2012 Version 2.0

6Chapter 2. Outline of CSES 2012
Summary
Objectives of the

The main objective of the survey is to collect statistical information about thesurveyliving conditions of the Cambodian population and the extent of poverty. The
survey results can be used for identifying problems and making decisions
based on statistical data.

Topicscoveredby the survey

The next eight topics;• Demographic characteristics• Housing• Agriculture• Education• Labour Force• Health and Nutrition• Victimization• Household Income and Consumption

Frequency of theAnnually since2007.

surveyCSES 2004 and CSES 2009 were large sample surveys (12,000 households),
whereas the years between have small samples (3,600 households for CSES
2010 and 2011, then 3,840 households in CSES 2012).

Survey periodThe annual sample was divided into 12 monthly samples. Data collection
was carried out from January 2012 to December 2012.

For a household, survey period was one month. Recall data on income
and expenditure was collected in the household questionnaire. Reference
period of food was 7 days. That of non-food was from a month to 12
months depending on items. Also, the diary questionnaire on income andexpenditure was requested to record during the survey month.

Coverage of the

Geographically, the survey covered the whole country. Cambodia
consisted of 24 provinces.

survey

Private households with one or more persons, including nomadic
households. Institutional households such as long term hospitals, prisons,monasteries, military quarters were excluded.

Sample designFor CSES 2012 a new CSES survey sample and questionnaire design was
implemented.

Three-stage stratified sample selection
Sampling frame: General Population Census 2008 for sampling of

Manual Cambodia CSES 2012 Version 2.0

7villages (14,073 villages) ?
Strata: province and urban/rural (48 strata) ?
Stage 1: A random sample of PSUs was selected from each stratum using
systematic PPS.
Stage 2: One EA was selected by SRS, in each villege selected in stage 1.
Stage 3: In each selected EA a sample of 10 households was selected.
Sample size
In total 3,840 households
Response rate
Almost a 100 percent response rate.

WeightDatacollection

method

Two kind of weights: household weight and person weightFace to faceIn total 50 teams for field work.
four enumerators.

A team consisted of a supervisor andIn urban one enmerator was in charge of 10

household during each month, while in rural two enumerators were
responsible for one PSU and for interviewing 20 households..


During a survey month, different questions were asked during the first
visit and in the following four weeks.

Data entry anddata check
Publication anddissemination

Supervisors from the field delivered questionnaires to NIS.

Data editing

and coding was implemented in NIS.
Reports and tables are available at NIS website.
available at NADA.

Manual Cambodia CSES 2012 Version 2.0

Metadata is also

8The below describes based on the study description on NADA.


Series Information

The Cambodian Socio-Economic Survey 2012 (CSES) is the eleventh survey collecting data fromhousehold and individuals in Cambodia on different areas relating to poverty. The survey isconducted by the National Institute of Statistics (NIS) of the Ministry of Planning (MOP). The first
Socio-Economic Survey was conducted in 1994 (CSES 1994). Since then the CSES has been
conducted in 1996, 1997, 1999 and 2004. Since 2007 NIS conducts the CSES annually.

The CSES2004 was the fifth survey that was conducted and as a countrywide sample survey ofvillages and households in Cambodia. CSES2004 was the first survey with a collection of income
and receipts, expenditure and consumption of own production in a diary were daily transactions arereported. The sample size in CSES2004 was 1,000 households every month. Since 2007 theSocio-Economic Survey is conducted every year with a sample size of 300 households every month(3,600 household annually). The annual surveys are undertaken as a part of the project, “Capacity
Development for Socio-Economic Surveys and Planning” of the Royal Government of Cambodia.
This project is supported and financed by Sida (The Swedish International Development
Cooperation Agency). In 2009 the CSES was similar to CSES 2004 with a sample size of 1,000
households every month (12,000 households on annual basis).

For 2010 and 2011 the sample size was again brought down to 3,600. CSES 2012 had a slightly
bigger sample size of 3,840.

The earlier CSES rounds have all made it possible to report sets of indicators on 8 main areas ofsocial concern• Demographic characteristics• Housing• Agriculture• Education• Labour Force• Health and Nutrition• Victimization• Household Income and Consumption

In CSES 2010 some changes have been introduced in the household questionnaire. Most changes
were minor except for the questions on current economic activity.

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For the CSES 2012 a new CSES survey sample and questionnaire design was implemented.

Overview

The Cambodia Socio-Economic Survey (CSES) asks questions to a country wide sample ofhouseholds and household members about housing conditions, education, economic activities,
household production and income, household level and structure of consumption, health,victimization, etc. There are also questions related to people in the labour force, e.g. labour force
participation.

Poverty reduction is a major commitment by the Royal Government of Cambodia. Accurate
statistical information about the living standards of the population and the extent of poverty is an
essential instrument to assist the Government in diagnosing the problems, in designing effective
policies for reducing poverty and in monitoring and evaluating the progress of poverty reduction.
The Millennium Development Goals (MDG) has been adopted by the Royal Government of
Cambodia and a National Strategic Development Plan (NSDP) has been developed. The MDGs arealso incorporated into the “Rectangular Strategy of Cambodia”.

Cambodia is still a predominantly rural and agricultural society. The vast majority of the population
get their subsistence in households as self-employed in agriculture. The level of living is determinedby the household's command over labour and resources for own-production in terms of land andlivestock for agricultural activities, equipments and tools for fishing, forestry and construction
activities and income-earning activities in the informal and formal sector. The CSES aims toestimate household income and consumption/expenditure as well as a number of other household
and individual characteristics.

The main objective of the survey is to collect statistical information about living conditions of theCambodian population and the extent of poverty. The survey can be used for identifying problems
and making decisions based on statistical data.

The main user is the Royal Government of Cambodia (RGC) as the survey supports monitoring the
National Strategic Development Plan (NSDP) by different socio-economic indicators. Other users
are university researchers, analysts, international organizations e.g. the World Bank and NGO’s. The
World Bank has published a report on poverty profile and social indicators using CSES 2007 data .
In this regard, the CSES continues to serve all stakeholders involved as essential instruments in order

Manual Cambodia CSES 2012 Version 2.0

10

to assist in diagnosing the problems and designing their most effective policies. The CSES micro
data at NIS is available for research and analysis by external researchers after approval by Senior
Minister of Planning. The interesting research questions that could be put to the data are many; NIS
welcomes new research based on CSES data.
Objectives

General Objectives:
CSES 2012 will continue the work started through CSES 2004 and the annual CSES 2007 and 2008
and would primarily aim at producing information needed for planning and policy making for
reduction of poverty in Cambodia. Reduction of poverty has been given high priority in Cambodia's
National Strategic Development Plan (NSDP 2009-2013). In addition to this, the survey data help invarious other ways in developmental planning and policy making in the country. They would also
prove useful for the production of National Accounts in Cambodia.

A long-term objective of the entire project is to build national capability in NIS for conducting
socio-economic surveys and for utilizing survey data for planning for national development andsocial welfare.

Specific Objectives:
Among specific objectives, the following deserve special mention:1) Obtain data on infrastructural facilities in villages, especially facilities for schooling and healthcare and associated problems.
2) Obtain data on retail prices of selected food, non-food and medicine items prevailing in thevillages.
3) Collect data on utilization of education, housing and land ownership
4) Collect data on household assets and outstanding loans.
5) Collect data on household's construction activities.
6) Collect information on maternal health, child health/care.
7) Collect information on health care seeking and expenditure of the household members related toillness, injury and disability.
8) Collect information on economic activities including the economic activities for children aged
between 5 and 17 years.
9) Collect information on victimization by the household10) Collect information on the presence of the household members.

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

Scope

Briefly the CSES rounds have all made it possible to report sets of indicators on 8 main areas ofsocial concern:
1. Demographic characteristics
2. Housing
3. Agriculture
4. Education
5. Labour Force
6. Health and Nutrition
7. Victimization
8. Household Income and ConsumptionSampling

Sampling Procedure:
The sampling design in the CSES 2012 survey is a three-stage design. In stage one a sample ofvillages is selected, in stage two an Enumeration Area (EA) is selected from each village selected instage one, and in stage three a sample of households is selected from each EA selected in stage two.

Stage 1: A random sample of PSUs was selected from each stratum. The sampling method was
systematic PPS (PPS=sampling with probability proportional to size). The size measure used was thenumber of households in the PSU according to the sampling frame.
Stage 2. One EA was selected by Simple Random Sampling (SRS), in each village selected in stage
1.
Stage 3. In each selected EA a sample of 10 households was selected. The selection of households
was done in the field by the supervisors/interviewers. All households in selected EAs were listed by
the enumerator. The sample of households was then selected from the list by systematic samplingwith a random start (the start value controlled by NIS).

Response Rate

The CSES 2012 enjoyed almost a 100 percent response rate. The high response rate together withclose and systematic fieldwork supervision by the core group members were a major contribution forachieving high quality survey results.

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12

Weighting

Sampling weights were computed for every stage. First stage weights (W1) were assigned to
selected villages. With the PPS procedure employed villages were selected with different
probabilities. Large villages are over-represented in the sample and, small villages areunder-represented. In the calculattion of results (estimates) from the sample it must be ensured that
there is compensate for this misrepresentation. The way to do that is to assign sampling weights tothe selected villages (PSUs). The over-represented large villages should be down-weighted and theunder-represented small villages should be up-weighted.
The second stage sampling weights W2 are calculated as the number of households in the village(according to the chairman) over the number of sampled households (10).
The household sampling weights (Wprel) are calculated by multiplying W1 by W2. All the sampled
households in the village get the same household weight. These weights were then calibrated.

Data Collection

Data Collection Dates:
From 1 January 2012 to 29 December 2012

Data Collection Mode:
Face-to-face

Data Collection Notes:
For the CSES 2012 a new CSES survey sample and questionnaire design was implemented. The
data collection and field work have therefore been monitored closely. especially in the beginning of
the year. The changes caused only minor problems in the data collection. The fieldwork operations
and logistics have been running very well. A training on sub-national level for all supervisors andenumerators was held in the beginning of the year. The training was paid for by local cost. Now NIS
has its own capacity to carry out the out the data collection process, but is financially supported
diretly by Sida. The L T As have participated in a few fieldtrips to learn more about the datacollection and to check whether the work is carried out as planned. The Subject Matter Staff (SMS)
have also participated more in the field work than previous years. As a result, the enumerators'
undrstanding of the questions has improved and at the same time tha SMS has received information
about possible questionnaire improvements. All these activities will lead to better quality in the datacollection.
Interviewers and supervisors were initially divided into teams of five persons (one supervisor andfour interviewers), making in total 50 teams for the fieldwork. Each month, 25 teams were working

Manual Cambodia CSES 2012 Version 2.0

13

in the field with a workload of 10 households per interviewer. In urban areas, 4 PSUs were allocatedto one team while in rural areas, 2 PSUs were allocated. The fieldwork plan was designed in order togather around 60 households monthly per team.
For a given month, the team arrived in the village three days before the first day of the month to tend
to preparatory tasks like discussing with village authorities, filling out the Household Listing Form,and thereafter sample those households to be interviewed.

The Village Form was filled out by the supervisor.
The Household Questionnaire had 16 sections that were filled out by the interviewer during the first
visit to the household, and in the following four weeks according to the following scheme:
FIRST VISIT: Initial visit
WEEK 1: Education and literacy, Housing
WEEK 2: Household economic activities, Household liabilities, Household income from othersources, and other expenditures (partial non-food recall)
WEEK 3: Durable goods and other expenses, Construction activities in the past 12 months, Nutrition,
Fertility and child care, Mortality
WEEK 4: Health check of children, Current economic activity, Health, HIV/AIDS, Victimization

Once the month ended, the team went back to the NIS headquarters in Phnom Penh.
Questionnaires from the same PSU was delivered to the Data Management team by the supervisor ina packet including all of the documents used and produced in the fieldwork, including maps,
enumeration lists, questionnaires, diaries, etc. Before going to the villages, teams were briefed andintroduced to minor adjustments of the interviewing procedure that had to be made as a result ofmonitoring activities and feed-back from the data processing.

The fieldwork started in Janury 2010 and was scheduled to end in December 2010.
Fifty (50) supervisors and 200 enumerators were recruited by NIS and trained for the fieldwork. The
training took place in Phnom Penh and lasted three weeks for supervisors and two weeks forenumerators. Before the start of each fieldwork month, there were briefing and retraining sessions.
Each fieldwork team included one supervisor and four enumerators. In urban areas one enumerator
was responsible for one PSU and for interviewing 10 households, while in rural areas twoenumerators were responsible for one PSU and for interviewing 20 households. In all, 125
enumerators and supervisors, divided into 25 teams, were carrying out the fieldwork at the sametime. Two such team groups were formed and each team group alternated monthly.

Enumerator and Supervisor training:

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14Initial training was provided during nine days for a group of 20-30 staff (not all were attending all
the time). This training included a translation into Khmer of selected parts of the questionnaire, and afield test in a village outside Phnom Penh where the participants performed test interviews in 16
households. The experiences from this exercise were followed up during the course. The course also
included general aspects on survey methodology and ways of controlling for errors. Many of thefindings from this training served as input to later stages.
Prior to the start of the fieldwork intensive interviewer and supervisor training was carried out. The
200 interviewers and 50 supervisors recruited were split into two groups, each consisting of 100
interviewers and 25 supervisors. The two groups later alternated so that the first group did theirfieldwork during odd survey months (i.e. November, January, March …) while the second group
covered the even survey months (i.e. February, April …).
The training was designed with this in mind. Training of the first group was provided in English by a
WB consultant and simultaneously interpreted in Khmer by the appointed NIS officer. The second
group was trained by NIS only.
Common was that the supervisors were first trained during one week, and then jointly with theirinterviewers for two weeks. Before all fieldwork months the group in turn was gathered at the NIS towalk through the questionnaire and manuals in order to correct errors that were detected during thebriefing sessions or the monitoring operations, and to learn how to handle any changes that wereintroduced to the survey instruments.


Questionnaires

Three different questionnaires or forms were used in the survey:
Form 1: Household listing sheets to be used in the sampling procedure in the enumeration areas.
Form 2: Village questionnaire answered by the village leader about economy and infrastructure, crop
production, health, education, retail prices and sales prices of agriculture, employment and wages,
and recruitment of children for work outside the village.
Form 3: Household questionnaire with questions for each household member, including modules on
migration, education and literacy, housing conditions, crop production, household liabilities, durable
goods, construction activities, nutrition, fertility and child care, child feeding and vaccination, healthof children, mortality, current economic activity, health and illness, smoking, HIV/AIDS awareness,and victimization.
The interviewer is responsible for filling up Form 1 and Form 3 to respondents. . For Form 2, thesupervisors will be asked to canvass this form. In case that the supervisors are absent for any reason,
the interviewers may be also asked to help fill up this form (Form 2).

Supervision:

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15

Any survey of the CSES dimensions needs a comprehensive system for quality management andmonitoring. Only then can deviations from the target be tended to in time to avoid shortfalls.
Interviewers and supervisors were initially divided into teams of five persons (one supervisor andfour interviewers), making in total 50 teams for the fieldwork.
The CSES management group within NIS therefore set up a meticulous monitoring scheme to be
implemented from the very beginning. The monitoring team did include at least five NIS staff.
Commonly the DG of NIS has spent one week monthly while other top ranked NIS officers havebeen out for two weeks on average. At times other officials from NIS or the Ministry haveparticipated.
Inspections entailed both announced and unannounced visits. Every team was visited at least twice
during their fieldwork periods. The pur­poses of these visits were several. One important purpose
was to get a disciplinary effect on supervisors and enumerators from their knowledge that suchinspections must be ex­pected throughout the fieldwork month, including also at the very end of thediary month. Also important was to give feedback and encouragement to fieldworkers and tocomplement training by advice and suggestions and to sort out any problem that had arisen in thecourse of fieldwork in the village. Another area of concern was to ensure that the household listingand sampling was done in accordance with the procedures that were devised.
In general, a supervisor is assigned to supervise several enumerators during the field operations. The
major duties and responsibilities of a supervisor in relation to your work as enumerator are thefollowing:
1. Your supervisor is responsible for ensuring that all the enumerators under him/her do the listingand enumeration work satisfactorily in time. He/she plans and organises the work in his/her area ofsupervision and sees to it that everything is conducted efficiently and completely.
2. Your supervisor is required to check your work as enumeration proceeds to make sure that you
have done your work correctly and have followed the standard procedures laid down by the NIS. He
will check all the questionnaires filled by you. You must show and submit your work to him/her andreport to him/her the progress of your work and avoid committing the same errors again.
3. As part of his/her supervisory functions, your supervisor will visit the enumeration area assigned
to you to check that you have completely covered your area in the listing operation. He may observe
you when you are interviewing some respondents. He/she will also re-interview some of thehouseholds you have interviewed to check whether the information you have obtained are valid.
4. The supervisor may provide to you all necessary field supplies and questionnaires etc. As soon as
you complete the enumeration, you must return all unused supplies and materials to him/her.
Otherwise, you will not be given clearance to collect your final service fee payment at the end ofyour work.

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16

The supervisor serves as a link between you and higher officials of the NIS. Just as he/she informs
you of the instructions from NIS officials, you must inform him/her of any problem or difficulty thatyou experience. Seek his/her advice on how to deal with problems in the field as often as needed. He
may help you establish contact with village leaders, commune leaders, and other representatives ofthe village.

Manual Cambodia CSES 2012 Version 2.0

17Chapter 3. Data and metadata provided

CSES 2012 micro data sets were provided to Sinfonica in March 2015 by NIS.

Data set provided
Household data in STATA format

File names in STATA format (37 files)[1] "HHConstruction.dta""HHCostCultivationCrops.dta"[3] "HHDurableGoods.dta""HHFishCultivation1.dta"[5] "HHFishCultivation2.dta""HHFishCultivation3.dta"[7] "HHFoodConsumption.dta""HHForestryHunting1.dta"[9] "HHForestryHunting2.dta""HHHousing.dta"[11] "HHIncomeOtherSource.dta""HHInventoryCrops.dta"[13] "HHLandOwnership.dta""HHLiabilities.dta"[15] "HHLivestock1.dta""HHLivestock2.dta"[17] "HHMembers.dta""HHNonAgriculture1.dta"[19] "HHNonAgriculture2.dta""HHNonAgriculture3.dta"[21] "HHOtherInfo.dta""HHProductionCrops.dta"[23] "HHRecallNonFood.dta""HHSalesCrops.dta"[25] "HHVulnerability.dta""Households.dta"[27] "PersonDisability.dta""PersonEcoCurrent.dta"[29] "PersonEducation.dta""PersonHealthU2.dta"[31] "PersonIllness.dta""PersonMaternalHealth.dta"[33] "PersonviolenceA.dta""PersonViolenceB.dta"[35] "PSUListing.dta""weighthouseholds.dta"[37] "weightpersons.dta"



Metadata

Questionnaire
CSES2012 Diary ENG.xls

Diary questionnaire

CSES2012 Village ENG.xls

Village questionnaire

CSES2012 HH Questionnaire.xls

Household questionnaire

Manual Cambodia CSES 2012 Version 2.0

18Survey Report
Report CSES2012.pdf
ManualCSES2012 field manual ENG.pdf
Data dictionary
None
Code

(Note) Data dictionary was not provided.



In addition, summary file of household income, “IncomeHousehold_2012.sav” was provided
upon request on the occasion of the workshop in December 2018.
It will be discussed in Section 7.0.

Manual Cambodia CSES 2012 Version 2.0

19

Other source of metadata


ILO Microdata Repository
http://www.ilo.org/surveydata/index.php/catalog/341/related_materials(Accessed on 1 May 2018)

Questionnaire form and Field Manual in English are available.

Manual Cambodia CSES 2012 Version 2.0

20

Cambodia-NADA (Microdata)
https://nada-nis.gov.kh/index.php/catalog/17/data_dictionary(Accessed on 1 May 2018)

Data discription in English is available.

Manual Cambodia CSES 2012 Version 2.0

21

Homopage of NIS
https://www.nis.gov.kh/index.php/en/14-cses/12-cambodia-socio-economic-survey-reports(Accessed on 1 May 2018)

Survey Reports of CSES are available.

Manual Cambodia CSES 2012 Version 2.0

22Chapter 4.

Data Import

4.1 Import STATA data files into RImported the following 37 STATA files into R> infiles<-list.files()> infiles<-infiles[-27]> infiles[1] "HHConstruction.dta""HHCostCultivationCrops.dta"[3] "HHDurableGoods.dta""HHFishCultivation1.dta"[5] "HHFishCultivation2.dta""HHFishCultivation3.dta"[7] "HHFoodConsumption.dta""HHForestryHunting1.dta"[9] "HHForestryHunting2.dta""HHHousing.dta"[11] "HHIncomeOtherSource.dta""HHInventoryCrops.dta"[13] "HHLandOwnership.dta""HHLiabilities.dta"[15] "HHLivestock1.dta""HHLivestock2.dta"[17] "HHMembers.dta""HHNonAgriculture1.dta"[19] "HHNonAgriculture2.dta""HHNonAgriculture3.dta"[21] "HHOtherInfo.dta""HHProductionCrops.dta"[23] "HHRecallNonFood.dta""HHSalesCrops.dta"[25] "HHVulnerability.dta""Households.dta"[27] "PersonDisability.dta""PersonEcoCurrent.dta"[29] "PersonEducation.dta""PersonHealthU2.dta"[31] "PersonIllness.dta""PersonMaternalHealth.dta"[33] "PersonviolenceA.dta""PersonViolenceB.dta"[35] "PSUListing.dta""weighthouseholds.dta"[37] "weightpersons.dta"> library(foreign)> outfiles<-list()> for(j in 1:length(infiles)){+ df<-read.dta(infiles[j],convert.factors=F)+ outfiles<-c(outfiles,list(df))+ }> length(outfiles)[1] 37Manual Cambodia CSES 2012 Version 2.0

23# 37 R data frames were stored in the list “outfiles”.
# Made list of data file name, number of records and variables> Rnames<-sub(".dta","",infiles)> for(j in 1:length(infiles)){+ if(j==1) cat("data frame

nrow

ncol \n")+ cat(j,": ",format(Rnames[j],width=27),": ",+ format(nrow(outfiles[[j]]),width=6),",",+ format(ncol(outfiles[[j]]),width=3),"\n")+ }data frame

nrow

ncol

1 :

HHConstruction:

3576 ,

27

2 :HHCostCultivationCrops:

4034 ,21

3 :HHDurableGoods:

34809 ,

14

4 :HHFishCultivation1

:

82 ,

9

5 :

HHFishCultivation2:

2614 ,

6

6 :HHFishCultivation3:3683 ,

6

7 :HHFoodConsumption:

57784 ,

8

8 :HHForestryHunting1:

5851 ,

99 :HHForestryHunting2:6645 ,

6

10 :HHHousing:3841 ,

51

11 :HHIncomeOtherSource:

4220 ,

8

12 :HHInventoryCrops:

1916 ,

8

13 :HHLandOwnership:3781 ,37

14 :HHLiabilities:

1365 ,12

15 :HHLivestock1:

20526 ,19

16 :HHLivestock2:

3898 ,

6

17 :HHMembers:

17644 ,

23

18 :HHNonAgriculture1:

1703 ,

15

19 :HHNonAgriculture2:

7418 ,

11

20 :HHNonAgriculture3:

2604 ,11

21 :HHOtherInfo:

3840 ,

47

22 :HHProductionCrops:

4036 ,

15

Manual Cambodia CSES 2012 Version 2.0

24

23 :

HHRecallNonFood:

40135 ,

824 :HHSalesCrops:

1625 ,

825 :HHVulnerability:

3843 ,

20

26 :Households:

3840 ,

1027 :PersonDisability:

17644 ,

18

28 :PersonEcoCurrent:

16086 ,

47

29 :PersonEducation:

16754 ,

29

30 :PersonHealthU2

:

585 ,

19

31 :

PersonIllness:

17644 ,

23

32 :PersonMaternalHealth:1245 ,

15

33 :PersonviolenceA:

17588 ,

834 :PersonViolenceB

:

44 ,

14

35 :

PSUListing

:

384 ,

16

36 :

weighthouseholds:

3840 ,

737 :weightpersons:

17644 ,

8

Manual Cambodia CSES 2012 Version 2.0

25

4.2 Structure of data files
The next table is based on the data description in Cambodia-NADA.

Note:
OLD No represents the alphabetical order of file names.
NEW No represents the structural order of data file, as the next table.
CSES 2012: Data files and corresponding part of questionnaire
OLD

NEW

File name

Description

Cases

Variables

No

No

26

1

Households

Cover page

3840

10

17

2

HHMembers

01.

of

17644

20

01. Initial Visit: B. Food, Beverages

57784

5

InitialVisit:A.

List

Household Members.
7

3

HHFoodConsumption

and Tobacco Consumption during theLast 7 Days.
23

4

HHRecallNonFood

01. C. RECALL NON-FOOD EXPENDITURES

40135

5

25

5

HHVulnerability

01. D. VULNERABILITY

3843

17

29

6

PersonEducation

02. Education and Literacy

16754

25

10

7

HHHousing04. Housing.

3841

48

13

8

HHLandOwnership

05. Household Economic Activities, A.

3781

34

4036

12

4034

18

1916

5

1625

5

20526

16

Land Ownership
22

9

HHProductionCrops

05, B. Production of Crops (Including
Fruits and Vegetables, etc.)

2

10

HHCostCultivationCrops

05. C. Cost of Cultivation of Crops
including Fruits and Vegetables, etc.

12

11

HHInventoryCrops

05.D.1 Inventory of Crops (Including
Fruits and Vegetables, etc.)

24

12

HHSalesCrops

05.D.2

SALES

OF

CROPS

(INCLUDINGFRUITS AND VEGETABLES ETC.).
15

13

HHLivestock1

05. Household Economic Activities, E.
INPUTS AND OUTPUTS OF LIVESTOCK AND
POULTRYRAISINGACTIVITIES,

table, Columns 1-15

Manual Cambodia CSES 2012 Version 2.0

First

26

16

14

HHLivestock2

05. Household Economic Activities, E.

3898

3

82

6

2614

3

3683

3

from

5851

6

from

6645

3

Non-

1703

12

7418

8

2604

8

1365

9

Other

4220

5

08. Construction Activities in the

3576

24

Inputs and Outputs of Livestock andPoultry

Raising

Activities,

Second

table
4

15

HHFishCultivation1

05. F. Inputs and Outputs From Fish
Cultivation and Fishing/Trapping ofAquatic ProductS, Table 1

5

16

HHFishCultivation2

05. F. Inputs and Outputs From Fish
Cultivation and Fishing/Trapping ofAquatic Products, Table 2

6

17

HHFishCultivation3

05. F. Inputs and Outputs from Fish
Cultivation and Fishing/Trapping ofAquatic Products, Table 3.

818

HHForestryHunting1

05.G.

InputsandOutputs

Forestry and Hunting, Table 1
919

HHForestryHunting2

05.

G.

InputsandOutputs

Forestry and Hunting, Table 2.
18

20

HHNonAgriculture1

05.H.

List

agriculturalofHouseholds

Economic

Activities

during the Past 12 Months, Table 1
19

21

HHNonAgriculture2

05.

H.

List

AgriculturalofHouseholdEconomic

Non-

Activities

during the Past 12 Months, Table 2.
20

22

HHNonAgriculture3

05.

H.

List

AgriculturalofHouseholdEconomic

Non-

Activities

during the Past 12 Months, Table 3
14

23

HHLiabilities

06. Household Liabilities

11

24

HHIncomeOtherSource

07.

HouseholdIncomefrom

Sources1

25

HHConstruction

Past 12 Months.
326

HHDurableGoods

09. Durable Goods

34809

11

32

27

PersonMaternalHealth

10. Maternal Health: Last pregnancy

1245

11

585

14

and delivery
30

28

PersonHealthU2

11. Child Health - YOUNGEST CHILD &AND ALL CHILDREN UNDER 2

Manual Cambodia CSES 2012 Version 2.0

27

31

29

PersonIllness

13.

HealthCare

Seeking

and

17644

19

Expenditures, Section B
27

30

PersonDisability

14. Disability.

17644

14

28

31

PersonEcoCurrent

15. Current Economic Activity.

16086

43

33

32

PersonviolenceA

17. Vicitmization, Victim of Violence

17588

4

44

10

3840

29

section, Table 1
34

33

PersonViolenceB

17. Victimization, Victim of Violence
section, Table 2

21

34

HHOtherInfo

Data

contained

in

this

file

are

questions from various sections of the
2012

CSES

questionnaire.

These

include: 01. B. Food, Beverages andTobacco Consumption during the Last 7
Days:

Q1

03.

B.

Informationon

Migration: Current Migrants: Q1 05. A.
Household Economic Activities: Land
Ownership: Q1A - Q3 05. B. Production
of

Crops

(Including

FruitsandVegetables, etc.): Q1 05. D. Inventory
of

Crops

(Including

FruitsandVegetables, etc.): Q1 05. D. 1. Sales
of

Crops

(Including

FruitsandVegetables, etc.): Q1 05. E. Inputs
and Outputs of Livestock and Poultry
Raising Activities: Q1 05. F. Inputs
and Ouputs from Fish Cultivation andFishing/ Trapping pf Aquatic Products;
Q1 - Q2 05. G. Inputs and Outputs from
Forestry and Hunting: Q1 - Q2 05. H.
List

of

Household

Non-Agricultural

Economic Activities during the Past 12
Months 06. Household Liabilities: Q1
08. Construction Activities in the
Past 12 Months 10. Maternal Health: Q1
11. Child Health: Q1 13. A. Health Care
Seeking and Expenditure: Subsidized

Manual Cambodia CSES 2012 Version 2.0

28Household Health Care: Q1 - Q4 17. A.
Victimization: Q1 - Q3

35

35

PSUListing

Information about the PSUs.

384

15

36

36

WeightHouseholds

Household weights

3840

7

37

37

Weightpersons

Person weight

17644

8

Manual Cambodia CSES 2012 Version 2.0

29

Rearrangement of Rfiles and outfiles> file.order<-c(26,17,7,23,25,29,10,13,22,2,12,24,15,16,4,5,6,8,9,+ 18,19,20,14,11,1,3,32,30,31,27,28,33,34,21,35,36,37)> Rnames.old<-Rnames> Rnames<-Rnames[file.order]> Rnames[1] "Households""HHMembers"[3] "HHFoodConsumption""HHRecallNonFood"[5] "HHVulnerability""PersonEducation"[7] "HHHousing""HHLandOwnership"[9] "HHProductionCrops""HHCostCultivationCrops"[11] "HHInventoryCrops""HHSalesCrops"[13] "HHLivestock1""HHLivestock2"[15] "HHFishCultivation1""HHFishCultivation2"[17] "HHFishCultivation3""HHForestryHunting1"[19] "HHForestryHunting2""HHNonAgriculture1"[21] "HHNonAgriculture2""HHNonAgriculture3"[23] "HHLiabilities""HHIncomeOtherSource"[25] "HHConstruction""HHDurableGoods"[27] "PersonMaternalHealth""PersonHealthU2"[29] "PersonIllness""PersonDisability"[31] "PersonEcoCurrent""PersonviolenceA"[33] "PersonViolenceB""HHOtherInfo"[35] "PSUListing""weighthouseholds"[37] "weightpersons"> outfiles.old<-outfiles> for(j in 1:37) outfiles[[j]]<-outfiles.old[[file.order[j]]]> for(j in 1:length(infiles)){+ if(j==1) cat("data frame+ cat(j,": ",format(Rnames[j],width=27),": ",+ format(nrow(outfiles[[j]]),width=6),",",+ format(ncol(outfiles[[j]]),width=3),"\n")+ }data frame
nrow
ncol
1 : Households:
3840 , 10
2 : HHMembers:
17644 , 23
3 : HHFoodConsumption:
57784 ,
8
4 : HHRecallNonFood:
40135 ,
8
5 : HHVulnerability:
3843 , 20
6 : PersonEducation:
16754 , 29
7 : HHHousing:
3841 , 51
8 : HHLandOwnership:3781 , 37
9 : HHProductionCrops:
4036 , 15
10 : HHCostCultivationCrops:
4034 , 21
11 : HHInventoryCrops:
1916 ,
8
12 : HHSalesCrops:
1625 ,
8
13 : HHLivestock1:
20526 , 19
14 : HHLivestock2:
3898 ,
6
15 : HHFishCultivation1:82 ,916 : HHFishCultivation2:
2614 ,
6
17 : HHFishCultivation3:3683 ,
6
18 : HHForestryHunting1:
5851 ,
9nrow

ncol \n")Manual Cambodia CSES 2012 Version 2.0

30

19 :
20 :
21 :
22 :
23 :
24 :
25 :
26 :
27 :
28 :
29 :
30 :
31 :
32 :
33 :
34 :
35 :
36 :
37 :

HHForestryHunting2
HHNonAgriculture1
HHNonAgriculture2
HHNonAgriculture3
HHLiabilities
HHIncomeOtherSource
HHConstruction
HHDurableGoods
PersonMaternalHealth
PersonHealthU2
PersonIllness
PersonDisability
PersonEcoCurrent
PersonviolenceA
PersonViolenceB
HHOtherInfo
PSUListing
weighthouseholds
weightpersons

:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:

6645 ,
1703 ,
7418 ,
2604 ,
1365 ,
4220 ,
3576 ,
34809 ,
1245 ,
585 ,
17644 ,
17644 ,
16086 ,
17588 ,
44 ,
3840 ,
384 ,
3840 ,
17644 ,

6
15
11
11
12
8
27
14
15
19
23
18
47
8
14
47
16
7
8

Manual Cambodia CSES 2012 Version 2.0

31

Naming rule of the variable

For example: the variable of Q01BC05,
Q01B represents the questionnaire form, and C05 represents the column number of the questions.

01. B. FOOD, BEVERAGES AND TOBACCO CONSUMPTION DURING THE LAST 7 DAYS
Respondent: The household member who knows most about food, beverage, tobacco consumption in the last 7 days
Q1 Did your household have any economic activity, e.g. agriculture production (farming), producing goods, service etc. during the last 7days?

INITIAL VISIT
1 = Yes
2 = NoITEM NUMBER

Only expenditure/value of own production for household consumption!
Note that any household´s expenditure on economic activity shall not be included in this section, because it will be asked in the sections on theeconomic activities (Section 5B-H).
Value of consumption in Riels
Write '0' if nothing

For each item group try to estimate quantity of items consumed and then how
much of the consumed quantity had been purchased in cash and how much wasfrom own production or received as payment in kind for work, or as gift, or freecollection.

Purchased in cash

Own production, wages
in kind, gifts, free

Total consumption( Col 3 + Col 4)collections (imputed
FOOD/BVERAGE/TOBACCO ITEMS

RIELS

RIELS

RIELS

(2)

(3)

(4)

(5)

Q01BC03

Q01BC04

Q01BC05(1)

Q01BC01
01

Rice (All kind of rice to be included)

Manual Cambodia CSES 2012 Version 2.0

32

4.3 Names and types of variables

Displayed the names and types of variables> for(j in 1:37){+ cat("##",j,"#### ",Rnames[j]," ##########\n")+ print(str(outfiles[[j]]))+ cat("\n\n")+ }## 1 #### Households ##########'data.frame':
3840 obs. of 10 variables:$ HHID: chr "0100301" "0100302" "0100303" "0100304" ...
$ PSU: chr "01003" "01003" "01003" "01003" ...
$ HHnumber: chr "01" "02" "03" "04" ...
$ Males: int 1 3 3 2 3 0 4 1 4 3 ...
$ Females: int 1 2 5 3 2 3 2 2 1 4 ...
$ Total: int 2 5 8 5 5 3 6 3 5 7 ...
$ SupervisorId: chr "011" "011" "011" "011" ...
$ RowDiff: int 0 0 0 0 0 0 0 0 0 0 ...
$ SignOut: POSIXct, format: "2013-01-18 18:07:00" "2013-01-18 18:31:00" ...
$ Operator: chr "zada" "zada" "zada" "zada" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:11"- attr(*, "formats")= chr "%9s" "%9s" "%9s" "%8.0g" ...
- attr(*, "types")= int 7 5 2 251 251 251 3 253 255 15- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 2 #### HHMembers ##########'data.frame':
17644 obs. of 23 variables:$ pkid: int 2 3 4 5 6 7 8 9 10 11 ...
$ hhid: chr "2101910" "2101910" "2101910" "2101910" ...
$ Q01AC01: int 1 2 3 4 5 1 2 3 4 5 ...
$ Q01AC03: int 1 2 1 1 2 1 2 1 1 2 ...
$ Q01AC04A : int 23 4 29 20 20 10 20 25 12 24 ...
$ Q01AC04B : int 3 6 11 11 8 9 1 4 5 10 ...
$ Q01AC04C : int 1972 1974 1992 1995 2008 1983 1985 2003 2006 2011 ...
$ Q01AC05: int 39 37 19 16 3 28 26 8 5 0 ...
$ Q01AC06: int 1 2 3 3 3 1 2 3 3 3 ...
$ Q01AC07: int NA NA 1 1 1 NA NA 1 1 1 ...
$ Q01AC08: int NA NA 2 2 2 NA NA 2 2 2 ...
$ Q01AC09: int 1 1 4 4 NA 1 1 NA NA NA ...
$ Q01AC10: int 2 1 NA NA NA 2 1 NA NA NA ...
$ Q01AC11A : int 1 1 1 1 1 1 1 1 1 1 ...
$ Q01AC11B : int 1 1 1 1 1 1 1 1 1 1 ...
$ Q01AC12A : int 2 0 0 2 0 0 0 0 0 0 ...
$ Q01AC12B : int 0 NA NA 0 NA NA NA NA NA NA ...
$ Q01AC12C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01AC13: int 1 1 1 2 1 1 1 1 1 1 ...
$ Q01AC14: int NA NA NA 30 NA NA NA NA NA NA ...
$ EntryUser : chr "riya" "riya" "riya" "riya" ...

Manual Cambodia CSES 2012 Version 2.0

33$ ChangeDate: POSIXct, format: "2012-02-21 19:17:00" "2012-02-21 19:17:00" ...
$ Persid: chr "210191001" "210191002" "210191003" "210191004" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 252 252 252 252 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 3 #### HHFoodConsumption ##########'data.frame':
57784 obs. of 8 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "2101910" "2101910" "2101910" "2101910" ...
$ Q01BC01: int 1 2 3 4 5 6 7 8 11 12 ...
$ Q01BC03: int 0 5000 18000 30000 5000 2000 3500 7000 2500 15000 ...
$ Q01BC04: int 21000 0 10000 0 0 0 0 3000 0 0 ...
$ Q01BC05: int 21000 5000 28000 30000 5000 2000 3500 10000 2500 15000 ...
$ EntryUser : chr "riya" "riya" "riya" "riya" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:18:00" "2012-02-21 19:18:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:15"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 253 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 4 #### HHRecallNonFood ##########'data.frame':
40135 obs. of 8 variables:$ pkid: int 17 32 44 45 47 49 51 54 55 56 ...
$ HHID: chr "0803010" "0803010" "0803010" "0803010" ...
$ Q01CC01: int 1 4 5 6 8 10 12 2 3 4 ...
$ Q01CC04: int 40000 13000 120000 600000 300000 150000 20000 90000 40000 10000 ...
$ Q01CC05: int 0 0 60000 0 0 0 0 0 0 0 ...
$ Q01CC06: int 40000 13000 180000 600000 300000 150000 20000 90000 40000 10000 ...
$ EntryUser : chr "morokat" "morokat" "morokat" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:27:00" "2012-02-21 19:29:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:13"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 253 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 5 #### HHVulnerability ##########'data.frame':
3843 obs. of 20 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "2101910" "0803010" "2101801" "1209101" ...

Manual Cambodia CSES 2012 Version 2.0

34$ Q01DQ1: int 1 1 1 1 1 1 1 1 1 1 ...
$ Q01DQ2: int 1 1 1 1 1 1 1 1 1 1 ...
$ Q01DQ3: int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_1 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_2 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_3 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_4 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_5 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_6 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_7 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_8 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_9 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_10 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_11 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ4_12 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q01DQ5: int NA NA NA NA NA NA NA NA NA NA ...
$ EntryUser : chr "riya" "morokat" "buntha" "Buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:25:00" "2012-02-21 19:33:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:13"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 6 #### PersonEducation ##########'data.frame':
16754 obs. of 29 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "2101910" "2101910" "2101910" "0803010" ...
$ Q02C01: int 1 2 3 1 2 3 4 4 5 1 ...
$ Q02C1b: int 2 2 2 1 2 2 2 4 2 1 ...
$ Q02C02: int 1 1 1 1 1 1 1 1 1 1 ...
$ Q02C03: int 1 1 1 1 2 2 2 1 2 2 ...
$ Q02C04: int 1 1 1 1 1 1 2 1 2 2 ...
$ Q02C05: int 14 7 12 4 2 2 NA 9 NA NA ...
$ Q02C06: int 15 7 14 4 2 1 NA 13 NA NA ...
$ Q02C07: int 2 2 2 2 2 1 NA 1 NA NA ...
$ Q02C08: int NA NA NA NA NA 2 NA 10 NA NA ...
$ Q02C09: int NA NA NA NA NA 1 NA 1 NA NA ...
$ Q02C10: int NA NA NA NA NA 2 NA 1 NA NA ...
$ Q02C11: int NA NA NA NA NA NA 11 NA 11 NA ...
$ Q02C12: int 2 2 2 2 2 2 2 2 2 2 ...
$ Q02C13: int NA NA NA NA NA NA NA NA NA NA ...
$ Q02C14: int NA NA NA NA NA NA NA NA NA NA ...
$ Q02C15: int 2 2 1 2 2 1 2 1 2 2 ...
$ Q02C16A: int NA NA 0 NA NA 0 NA 0 NA NA ...
$ Q02C16B: int NA NA 1200000 NA NA 0 NA 120000 NA NA ...
$ Q02C16C: int NA NA 50000 NA NA 10000 NA 23000 NA NA ...
$ Q02C16D: int NA NA 35000 NA NA 4000 NA 30000 NA NA ...
$ Q02C16E: int NA NA 370000 NA NA 130000 NA 150000 NA NA ...
$ Q02C16F: int NA NA 750000 NA NA 0 NA 20000 NA NA ...
$ Q02C16G: int NA NA 20000 NA NA 4000 NA 2000 NA NA ...
$ Q02C16H: int NA NA 2425000 NA NA 148000 NA 345000 NA NA ...

Manual Cambodia CSES 2012 Version 2.0

35$ EntryUser : chr "riya" "riya" "riya" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:25:00" "2012-02-21 19:25:00" ...
$ Persid: chr "210191001" "210191002" "210191003" "080301001" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:13"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 7 #### HHHousing ##########'data.frame':
3841 obs. of 51 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "2101910" "2101801" "1209101" ...
$ Q04_01: int 1 1 1 2 1 1 1 1 1 2 ...
$ Q04_02: int 20 56 42 30 30 40 48 30 20 35 ...
$ Q04_03: int 1 1 1 1 1 1 1 1 1 2 ...
$ Q04_04: int 1 2 2 2 2 2 2 2 2 2 ...
$ Q04_05: int 4 2 2 4 3 4 2 4 4 4 ...
$ Q04_06: int 3 2 2 2 2 2 2 1 3 2 ...
$ Q04_07: int 1 3 3 1 1 3 3 1 3 1 ...
$ Q04_08: int 3 9 9 9 1 3 9 9 3 1 ...
$ Q04_09: int 50 NA NA NA NA 3 NA NA 7 NA ...
$ Q04_10M1 : int 1 NA NA NA NA 2 NA NA 3 NA ...
$ Q04_10M2 : int 2 NA NA NA NA 1 NA NA 2 NA ...
$ Q04_10M3 : int 3 NA NA NA NA NA NA NA NA NA ...
$ Q04_11: int 10 NA NA NA NA 5 NA NA 3 NA ...
$ Q04_12: int 3 10 5 10 1 3 10 10 3 1 ...
$ Q04_13: int 50 0 120 0 NA 3 0 0 7 NA ...
$ Q04_14M1 : int 1 NA 1 NA NA 1 NA NA 3 NA ...
$ Q04_14M2 : int 2 NA 2 NA NA 2 NA NA 2 NA ...
$ Q04_14M3 : int NA NA NA NA NA NA NA NA 1 NA ...
$ Q04_15: int 12 NA 30 NA NA 5 NA NA 5 NA ...
$ Q04_16: int 0 40000 0 5000 27700 0 40000 14000 0 15000 ...
$ Q04_17: int 3 1 3 1 1 1 1 1 1 1 ...
$ Q04_18A: int NA 1 NA 1 1 2 1 1 1 1 ...
$ Q04_18B: int NA 2 NA 2 2 1 2 2 2 2 ...
$ Q04_18C: int NA 2 NA 2 2 2 2 2 2 2 ...
$ Q04_18D: int NA 2 NA 2 2 2 2 2 2 2 ...
$ Q04_18E: int NA 2 NA 2 2 2 2 2 2 2 ...
$ Q04_19A: int 2 7 7 2 2 2 6 2 7 2 ...
$ Q04_19B: int 2 3 3 2 1 1 3 1 3 1 ...
$ Q04_20: int 0 0 0 0 0 0 0 0 0 0 ...
$ Q04_21: int 0 0 0 0 0 0 0 0 0 0 ...
$ Q04_22A: int 1 2 1 1 1 1 1 1 1 1 ...
$ Q04_22B: int 1 2 2 1 1 1 2 2 1 2 ...
$ Q04_22C1 : int NA 1 1 NA NA NA 2 2 NA 2 ...
$ Q04_22C2 : int NA 2 2 NA NA NA 3 4 NA NA ...
$ Q04_22C3 : int NA 3 NA NA NA NA NA NA NA NA ...
$ Q04_22D: int NA 3 6 NA NA NA 3 5 NA 1 ...
$ Q04_23A: int 14000 0 0 8000 38500 0 0 35000 0 16000 ...
$ Q04_23B: int 0 10000 0 0 12000 0 0 0 0 2600 ...
$ Q04_23C: int 0 0 0 0 0 0 0 0 0 0 ...

Manual Cambodia CSES 2012 Version 2.0

36$ Q04_23D: int 10000 20000 45000 15000 21000 40000 45000 35000 40000 30000 ...
$ Q04_23E: int 0 0 0 2000 0 0 0 0 0 2400 ...
$ Q04_23F: int 6000 30000 10000 0 0 11000 10000 0 6000 0 ...
$ Q04_23G: int 0 0 0 0 0 0 0 0 0 2000 ...
$ Q04_24: int 1 1 1 1 1 2 1 1 1 1 ...
$ Q04_25A: int NA NA NA NA NA NA NA NA NA NA ...
$ Q04_25B: int 50000 100000 70000 120000 280000 160000 100000 60000 100000 200000 ...
$ Q04_26: int 0 0 0 0 0 0 0 0 0 0 ...
$ EntryUser : chr "morokat" "riya" "buntha" "Buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:36:00" "2012-02-21 19:39:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:15"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 252 252 252 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 8 #### HHLandOwnership ##########'data.frame':
3781 obs. of 37 variables:$ pkid: int 4 5 6 7 8 9 10 11 12 13 ...
$ hhid: chr "2101801" "2101801" "2101801" "2101801" ...
$ Q05AC01: int 1 2 3 4 1 2 1 1 2 1 ...
$ Q05AC02: num 3000 1300 1000 1000 30000 ...
$ Q05AC03: int 1 1 1 1 1 1 1 1 1 1 ...
$ Q05AC04A : int 300 100 70 70 4500 1200 250000 1000 700 500 ...
$ Q05AC04B : int 2 2 2 2 2 2 1 2 2 2 ...
$ Q05AC04C : int 2 2 2 2 2 2 2 3 3 2 ...
$ Q05AC05A : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC05B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC05C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC06A : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC06B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC06C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC07: int 1 1 1 1 2 1 1 1 1 1 ...
$ Q05AC08: int 1999 1999 1999 1999 2009 1991 2009 1980 1980 1983 ...
$ Q05AC09: int 2 2 2 2 4 2 2 1 1 1 ...
$ Q05AC10: int NA NA NA NA 60000000 NA NA NA NA NA ...
$ Q05AC11: int 3200000 2000000 2000000 2000000 100000000 20000000 8000000 28000000 21000000
57840000 ...
$ Q05AC12: int 1 1 1 1 1 1 1 2 2 1 ...
$ Q05AC13A : int 3 3 3 3 4 4 3 NA NA 3 ...
$ Q05AC13B : int 8 8 8 8 8 8 3 NA NA 3 ...
$ Q05AC14: int 3 3 3 3 3 2 3 NA NA 3 ...
$ Q05AC15: int 6 6 6 6 1 2 2 1 1 2 ...
$ Q05AC16A : int 1 1 1 1 1 1 1 1 1 1 ...
$ Q05AC16B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC16C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC17: int 1 1 1 1 2 1 1 4 4 1 ...
$ Q05AC18A : int 1 1 1 1 2 1 1 1 1 1 ...
$ Q05AC18B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC18C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AC19: int NA NA NA NA 2010 NA NA NA NA NA ...
$ Q05AC20: int 1 1 1 1 1 1 1 1 1 1 ...

Manual Cambodia CSES 2012 Version 2.0

37$ Q05AC21: int 1999 1999 1999 1999 2009 1991 2009 1980 1980 1983 ...
$ Q05AC22: int 3 3 3 3 3 3 3 3 3 3 ...
$ EntryUser : chr "buntha" "buntha" "buntha" "buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:44:00" "2012-02-21 19:45:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%10.0g" ...
- attr(*, "types")= int 253 7 251 255 251 253 251 251 253 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 9 #### HHProductionCrops ##########'data.frame':
4036 obs. of 15 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "2101910" "2101910" "2101910" "2101801" ...
$ WetDry: int 1 1 2 1 1 1 1 1 1 1 ...
$ Q05BC01: int 1 2 1 1 2 3 4 1 1 2 ...
$ Q05BC02: int 2 2 1 1 2 3 4 1 1 2 ...
$ Q05BC03B : chr "102" "103" "101" "102" ...
$ Q05BC04: num 4300 700 30000 3000 1300 1000 1000 2000 7550 5550 ...
$ Q05BC05: num 4300 700 30000 3000 1300 1000 1000 2000 7550 5550 ...
$ Q05BC06: num 2250 200 21150 720 240 ...
$ Q05BC07: num 50 10 150 0 0 0 0 5 20 15 ...
$ Q05BC08: num 90 0 0 0 0 0 0 0 0 0 ...
$ Q05BC09: int 950 1400 950 1000 1000 1000 1000 1700 820 820 ...
$ PastYear : int 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 ...
$ EntryUser : chr "riya" "riya" "riya" "buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:45:00" "2012-02-21 19:45:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:13"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 3 255 255 255 255 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 10 #### HHCostCultivationCrops ##########'data.frame':
4034 obs. of 21 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "2101910" "2101910" "2101910" "2101801" ...
$ WetDry: int 1 1 2 1 1 1 1 1 1 1 ...
$ Q05CC01: int 1 2 1 1 2 3 4 1 1 2 ...
$ Q05CC02: int 2 2 1 1 2 3 4 1 1 2 ...
$ Q05CC03: int 30000 7500 1000000 60000 25000 22000 22000 17000 100000 80000 ...
$ Q05CC04: int 240000 20000 4300000 68000 26000 24000 24000 100000 364000 260000 ...
$ Q05CC05: int 180000 20000 0 30000 20000 15000 15000 0 100000 80000 ...
$ Q05CC06: int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05CC07: int 22500 0 845000 2000 2000 2000 2000 60000 0 0 ...
$ Q05CC08: int 30000 0 23000 0 0 0 0 7000 96000 0 ...
$ Q05CC09: int 270000 30000 1000000 0 0 0 0 0 150000 100000 ...
$ Q05CC10: int 180000 20000 1050000 0 0 0 0 0 200000 150000 ...

Manual Cambodia CSES 2012 Version 2.0

38$ Q05CC11: int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05CC12: int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05CC13: int 0 0 460000 0 0 0 0 0 0 0 ...
$ Q05CC14: int 0 0 0 20000 10000 10000 5000 100000 0 0 ...
$ Q05CC15: int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05CC16: int 952500 97500 8678000 180000 83000 73000 68000 284000 1010000 670000 ...
$ EntryUser : chr "riya" "riya" "riya" "buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:46:00" "2012-02-21 19:46:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:12"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 253 253 253 253 253 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 11 #### HHInventoryCrops ##########'data.frame':
1916 obs. of 8 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "2101910" "2101910" "2101910" "2101801" ...
$ Q05DC01: int 1 2 3 1 2 3 4 1 1 2 ...
$ Q05DC02B : chr "102" "103" "101" "102" ...
$ Q05DC03: num 2290 190 1000 720 240 150 50 2600 1000 300 ...
$ Q05DC04: int 950 1400 950 1000 1000 1000 1000 800 1000 1000 ...
$ EntryUser : chr "riya" "riya" "riya" "buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:47:00" "2012-02-21 19:47:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%9s" ...
- attr(*, "types")= int 253 7 251 3 255 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 12 #### HHSalesCrops ##########'data.frame':
1625 obs. of 8 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "2101910" "2101909" "2101802" "0803008" ...
$ Q05D1C1: int 1 1 1 1 1 1 2 1 1 2 ...
$ Q05D1C2: chr "101" "102" "102" "102" ...
$ Q05D1C3: num 20000 4300 200 140 2600 500 1000 2000 1200 1850 ...
$ Q05D1C4: int 950 820 1000 1200 1000 1000 1000 1000 1000 1500 ...
$ EntryUser : chr "riya" "riya" "buntha" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:48:00" "2012-02-21 22:57:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:13"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%9s" ...
- attr(*, "types")= int 253 7 251 3 255 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL

Manual Cambodia CSES 2012 Version 2.0

39## 13 #### HHLivestock1 ##########'data.frame':
20526 obs. of 19 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "0803010" "0803010" "0803010" ...
$ Q05E1C01 : int 1 2 3 4 5 6 7 8 9 10 ...
$ Q05E1C03 : int 2 2 2 2 2 2 1 2 2 2 ...
$ Q05E1C04 : int NA NA NA NA NA NA 22 NA NA NA ...
$ Q05E1C05 : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05E1C06 : int NA NA NA NA NA NA 70000 NA NA NA ...
$ Q05E1C7a : int NA NA NA NA NA NA 30 NA NA NA ...
$ Q05E1C7b : int NA NA NA NA NA NA 25 NA NA NA ...
$ Q05E1C08 : int NA NA NA NA NA NA 140000 NA NA NA ...
$ Q05E1C09 : int NA NA NA NA NA NA 0 NA NA NA ...
$ Q05E1C10 : int NA NA NA NA NA NA 0 NA NA NA ...
$ Q05E1C11 : int NA NA NA NA NA NA 70000 NA NA NA ...
$ Q05E1C12 : int NA NA NA NA NA NA 0 NA NA NA ...
$ Q05E1C13 : int NA NA NA NA NA NA 0 NA NA NA ...
$ Q05E1C14 : int NA NA NA NA NA NA 0 NA NA NA ...
$ Q05E1C15 : int NA NA NA NA NA NA 0 NA NA NA ...
$ EntryUser : chr "morokat" "morokat" "morokat" "morokat" ...
$ Changedate: POSIXct, format: "2012-02-21 19:36:00" "2012-02-21 19:36:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 253 253 253 253 253 253 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 14 #### HHLivestock2 ##########'data.frame':
3898 obs. of 6 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "0803010" "2101910" "2101910" ...
$ Q05E2C01 : int 1 2 1 2 2 4 1 1 2 2 ...
$ Q05E2C03 : int 20000 20000 1380000 200000 800000 40000 5000 20000 70000 40000 ...
$ EntryUser : chr "morokat" "morokat" "riya" "riya" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:38:00" "2012-02-21 19:38:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 15 #### HHFishCultivation1 ##########'data.frame':
82 obs. of 9 variables:$ pkid: int 1 2 3 4 6 7 8 9 10 11 ...
$ hhid: chr "2101801" "2101910" "2101802" "2101803" ...
$ Q05F1C01 : int 1 1 1 1 1 1 1 1 1 1 ...

Manual Cambodia CSES 2012 Version 2.0

40$ Q05F1C02 : int 1 1 1 1 1 1 1 1 1 1 ...
$ Q05F1C03 : int 240 18 400 16 6 12 24 35 60 450 ...
$ Q05F1C04 : int 2800000 500000 5000000 1000000 500000 200000 450000 500000 500000 2000000 ...
$ Q05F1C05 : int 30000 7000 30000 10000 40000 10000 25000 5000 100000 20000 ...
$ EntryUser : chr "buntha" "riya" "buntha" "buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:54:00" "2012-02-21 19:55:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:15"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 253 253 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 16 #### HHFishCultivation2 ##########'data.frame':
2614 obs. of 6 variables:$ pkid: int 3 5 6 7 8 9 10 11 12 13 ...
$ hhid: chr "0803010" "1209101" "2101801" "2101910" ...
$ Q05F2C01 : int 5 5 5 1 5 5 5 5 5 5 ...
$ Q05F2C03 : int 250000 10000 5000 40000 30000 50000 5000 400000 20000 10000 ...
$ EntryUser : chr "morokat" "Buntha" "buntha" "riya" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:40:00" "2012-02-21 19:44:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:15"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 17 #### HHFishCultivation3 ##########'data.frame':
3683 obs. of 6 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "0803010" "0803010" "0803010" ...
$ Q05F3C01 : int 1 2 3 4 2 3 2 3 2 3 ...
$ Q05F3C03 : int 1120000 700000 50000 60000 50000 10000 1000000 50000 300000 100000 ...
$ EntryUser : chr "morokat" "morokat" "morokat" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:40:00" "2012-02-21 19:40:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:15"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 18 #### HHForestryHunting1 ##########'data.frame':
5851 obs. of 9 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "0803010" "0803010" "2101801" ...

Manual Cambodia CSES 2012 Version 2.0

41$ Q05G1C01 : int 2 4 6 2 4 6 2 6 2 2 ...
$ Q05G1C03 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05G1C04 : int 470000 20000 40000 560000 60000 120000 240000 120000 470000 547000 ...
$ Q05G1C05 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05G1C06 : int 470000 20000 40000 560000 60000 120000 240000 120000 470000 547000 ...
$ EntryUser : chr "morokat" "morokat" "morokat" "buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:40:00" "2012-02-21 19:41:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:15"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 253 253 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 19 #### HHForestryHunting2 ##########'data.frame':
6645 obs. of 6 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "2101801" "2101910" "0803009" ...
$ Q05G2C01 : int 5 1 5 5 5 5 1 1 5 5 ...
$ Q05G2C03 : int 20000 0 15000 20000 20000 30000 0 0 10000 5000 ...
$ EntryUser : chr "morokat" "buntha" "riya" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:41:00" "2012-02-21 19:56:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:15"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 20 #### HHNonAgriculture1 ##########'data.frame':
1703 obs. of 15 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "1209101" "2101910" "0803009" "0803009" ...
$ Q05H1C01 : int 1 1 1 2 1 2 1 1 2 1 ...
$ Q05H1C04 : chr "4540" "4920" "4720" "4920" ...
$ Q05H1C05 : int 1 1 2 1 2 1 1 1 2 2 ...
$ Q05H1C06A : int NA NA 1 NA NA NA 2 NA NA 1 ...
$ Q05H1C06B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05H1C06C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05H1C06D : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05H1C06E : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05H1C06F : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05H1C06G : int NA NA NA NA NA NA NA NA NA NA ...
$ Q05H1C06H : int NA NA NA NA NA NA NA NA NA NA ...
$ EntryUser : chr "Buntha" "riya" "morokat" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:44:00" "2012-02-21 19:56:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%9s" ...
- attr(*, "types")= int 253 7 251 4 251 251 251 251 251 251 ...

Manual Cambodia CSES 2012 Version 2.0

42- attr(*, "val.labels")= chr- attr(*, "var.labels")= chr- attr(*, "version")= int 12
NULL"" "" "" "" ...
"" "" "" "" ...

## 21 #### HHNonAgriculture2 ##########'data.frame':
7418 obs. of 11 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "1209101" "1209101" "1209101" "1209101" ...
$ Q05H2C01 : int 3 4 5 6 1 4 5 14 17 18 ...
$ Q05H2C03 : int 50000 200000 30000 115000 15000000 16000000 432000 200000 2400000 980000 ...
$ Q05H2C04 : int NA NA NA NA 0 0 0 0 0 0 ...
$ Q05H2C05 : int NA NA NA NA 0 0 0 0 0 0 ...
$ Q05H2C06 : int NA NA NA NA 0 0 0 0 0 0 ...
$ Q05H2C07 : int NA NA NA NA 0 0 0 0 0 0 ...
$ Q05H2C08 : int NA NA NA NA 0 0 0 0 0 0 ...
$ EntryUser : chr "Buntha" "Buntha" "Buntha" "Buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:44:00" "2012-02-21 19:44:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 253 253 253 253 253 15 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 22 #### HHNonAgriculture3 ##########'data.frame':
2604 obs. of 11 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "1209101" "1209101" "2101910" "0803009" ...
$ Q05H3C01 : int 2 5 3 5 8 1 5 8 9 5 ...
$ Q05H3C03 : int 1250000 150000 41252000 79200000 NA 9600000 3600000 0 30000 18000000 ...
$ Q05H3C04 : int NA NA 0 NA 4000000 NA NA 1440000 NA 0 ...
$ Q05H3C05 : int NA NA 0 NA NA NA NA NA NA 0 ...
$ Q05H3C06 : int NA NA 0 NA NA NA NA NA NA 0 ...
$ Q05H3C07 : int NA NA 0 NA NA NA NA NA NA 0 ...
$ Q05H3C08 : int NA NA 0 NA NA NA NA NA NA 0 ...
$ EntryUser : chr "Buntha" "Buntha" "riya" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:45:00" "2012-02-21 19:45:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 253 253 253 253 253 15 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 23 #### HHLiabilities ##########'data.frame':
1365 obs. of 12 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "1209101" "2101801" "2101910" ...

Manual Cambodia CSES 2012 Version 2.0

43$ Q06_C01: int 1 1 1 1 1 1 1 1 1 1 ...
$ Q06_C02: int 4 8 5 4 12 3 36 2 3 12 ...
$ Q06_C03: int 12 16 7 2 24 9 NA 10 9 19 ...
$ Q06_C04: int 8 9 1 8 4 1 1 8 8 8 ...
$ Q06_C05: int 4 8 1 1 4 4 8 1 1 1 ...
$ Q06_C06: int 800000 6000000 500000 8000000 4000000 8000000 1200000 2000000 600000
2000000 ...
$ Q06_C07: int 457500 4000000 500000 8000000 2000000 8000000 1200000 2000000 600000
146700 ...
$ Q06_C08: num 2.5 2.7 0 1.9 3 5 0 3 3 2.5 ...
$ EntryUser : chr "morokat" "Buntha" "buntha" "riya" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:41:00" "2012-02-21 19:45:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 252 252 251 251 253 253 255 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 24 #### HHIncomeOtherSource ##########'data.frame':
4220 obs. of 8 variables:$ pkid: int 2 3 4 5 6 7 8 9 10 11 ...
$ hhid: chr "2101801" "2101910" "1209102" "2101909" ...
$ Q07_C01: int 2 5 2 2 1 11 11 13 2 11 ...
$ Q07_C03: int 10000 12000 300000 50000 1200000 60000 10000 400000 100000 20000 ...
$ Q07_C04: int 0 0 0 0 0 0 0 0 0 0 ...
$ Q07_C05: int 10000 12000 300000 50000 1200000 60000 10000 400000 100000 20000 ...
$ EntryUser : chr "buntha" "riya" "Buntha" "riya" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:56:00" "2012-02-21 19:58:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:15"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%12.0g" ...
- attr(*, "types")= int 253 7 251 253 253 253 15 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 25 #### HHConstruction ##########'data.frame':
3576 obs. of 27 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "1209101" "2101801" "2101910" ...
$ Q08_C01: int 1 1 1 1 1 1 1 1 2 1 ...
$ Q08_C02A : int 1 1 1 1 1 1 1 1 3 1 ...
$ Q08_C02B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q08_C02C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q08_C03: num 20 30 42 56 30 48 35 30 42 20 ...
$ Q08_C04: int 2007 1997 1990 1995 1979 2006 2001 2011 1999 1997 ...
$ Q08_C05: int 4200000 40000000 20000000 40000000 120000000 15000000 80000000 12000000
42000000 16000000 ...
$ Q08_C06: int 50000 120000 70000 100000 280000 100000 200000 60000 50000 100000 ...
$ Q08_C07: int 2 2 2 2 2 2 2 2 2 2 ...

Manual Cambodia CSES 2012 Version 2.0

44$ Q08_C08: int NA NA NA NA NA NA NA NA NA NA ...
$ Q08_C09: int 2 2 2 2 2 2 2 1 2 2 ...
$ Q08_C10: int NA NA NA NA NA NA NA 1 NA NA ...
$ Q08_C11A : int NA NA NA NA NA NA NA 5 NA NA ...
$ Q08_C11B : int NA NA NA NA NA NA NA 2011 NA NA ...
$ Q08_C12A : int NA NA NA NA NA NA NA 9 NA NA ...
$ Q08_C12B : int NA NA NA NA NA NA NA 2011 NA NA ...
$ Q08_C13: int NA NA NA NA NA NA NA 4 NA NA ...
$ Q08_C14: int NA NA NA NA NA NA NA 200000 NA NA ...
$ Q08_C15: int NA NA NA NA NA NA NA 4000000 NA NA ...
$ Q08_C16: int NA NA NA NA NA NA NA 0 NA NA ...
$ Q08_C17: int NA NA NA NA NA NA NA 0 NA NA ...
$ Q08_C18: int NA NA NA NA NA NA NA 0 NA NA ...
$ Q08_C19: int NA NA NA NA NA NA NA 0 NA NA ...
$ EntryUser : chr "morokat" "Buntha" "buntha" "riya" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:42:00" "2012-02-21 19:46:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:12"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 251 255 252 253 253 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 26 #### HHDurableGoods ##########'data.frame':
34809 obs. of 14 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "0803010" "0803010" "0803010" ...
$ Q09_C03: int 802 803 890 891 838 818 803 804 893 838 ...
$ Q09_C04: int 1 1 2 1 3 1 1 1 1 2 ...
$ Q09_C05A : int 1 1 1 1 1 1 1 1 1 1 ...
$ Q09_C05B : int NA NA 1 NA 1 NA NA NA NA 1 ...
$ Q09_C05C : int NA NA NA NA 1 NA NA NA NA NA ...
$ Q09_C05D : int NA NA NA NA NA NA NA NA NA NA ...
$ Q09_C06A : int NA NA NA NA NA 1 NA 1 NA NA ...
$ Q09_C06B : int 1 1 2 1 3 NA 1 NA 1 2 ...
$ Q09_C07: int NA NA NA NA NA 160000 NA 6600000 NA NA ...
$ Q09_C08: int 80000 40000 8000 70000 12000 NA 35000 NA 20000 10000 ...
$ EntryUser : chr "morokat" "morokat" "morokat" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:42:00" "2012-02-21 19:42:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:11"- attr(*, "formats")= chr "%12.0g" "%9s" "%12.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 253 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 27 #### PersonMaternalHealth ##########'data.frame':
1245 obs. of 15 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "2101801" "2101910" "0803009" ...

Manual Cambodia CSES 2012 Version 2.0

45$ Q10_C01: int 1 1 1 1 1 1 1 1 1 1 ...
$ Q10_C02: int 2 2 2 2 2 2 2 2 7 2 ...
$ Q10_C03: int 5 5 5 3 3 5 6 3 8 4 ...
$ Q10_C04: int 2 2 2 1 2 1 2 2 2 2 ...
$ Q10_C05: int 2 1 1 1 1 1 1 1 1 1 ...
$ Q10_C06: int 1 7 7 7 7 1 7 7 6 7 ...
$ Q10_C07A : int 3 3 3 3 3 3 3 1 3 3 ...
$ Q10_C07B : int NA 1 NA NA 1 NA NA 2 1 NA ...
$ Q10_C07C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q10_C07D : int NA NA NA NA NA NA NA NA NA NA ...
$ EntryUser : chr "morokat" "buntha" "riya" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:43:00" "2012-02-21 19:58:00" ...
$ persid: chr "080301001" "210180101" "210191001" "080300901" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:12"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 28 #### PersonHealthU2 ##########'data.frame':
585 obs. of 19 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "1209102" "2101804" "0301104" ...
$ Q11_C01: int 1 1 1 1 1 1 1 1 2 1 ...
$ Q11_C02: int 2 2 2 2 NA 3 2 3 5 7 ...
$ Q11_C03: int 5 3 4 4 5 6 4 9 8 6 ...
$ Q11_C04: int 1 1 1 1 2 1 1 1 1 1 ...
$ Q11_C05: int 1 1 1 1 NA 1 1 1 1 1 ...
$ Q11_C06A: int NA NA 0 0 NA NA NA NA NA 12 ...
$ Q11_C06B: int 2 1 NA NA NA 2 1 1 2 NA ...
$ Q11_C07: int 1 1 2 1 NA 1 1 1 2 1 ...
$ Q11_C08A: int 2 2 2 2 NA 1 1 2 2 2 ...
$ Q11_C08B: int 2 1 1 2 NA 2 1 1 1 1 ...
$ Q11_C09: int 1 1 1 1 1 1 1 1 1 1 ...
$ Q11_C10: int 2 2 2 2 2 2 2 2 2 1 ...
$ Q11_C11: int 1 1 1 2 1 1 1 1 1 1 ...
$ EntryUser: chr "morokat" "Buntha" "buntha" "tey" ...
$ ChangeDate : POSIXct, format: "2012-02-21 19:43:00" "2012-02-21 22:54:00" ...
$ Persid: chr "080301005" "120910203" "210180404" "030110404" ...
$ PersidMother: chr "080301002" "120910202" "210180402" "030110402" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:13"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 251 251 252 252 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 29 #### PersonIllness ##########'data.frame':
17644 obs. of 23 variables:

Manual Cambodia CSES 2012 Version 2.0

46$ pkid: int 2 3 4 5 6 7 8 9 10 11 ...
$ hhid: chr "0803010" "0803010" "0803010" "0803010" ...
$ Q13BC01: int 1 2 3 4 5 1 2 3 4 1 ...
$ Q13BC2A: int 2 2 1 1 1 2 2 1 1 1 ...
$ Q13BC2B: int NA NA 1 1 1 NA NA 4 4 5 ...
$ Q13BC03: int NA NA 2 2 2 NA NA 2 2 1 ...
$ Q13BC04: int NA NA 3 3 3 NA NA 2 3 2 ...
$ Q13BC05: int NA NA NA NA NA NA NA NA NA NA ...
$ Q13BC06: int NA NA 1 1 1 NA NA 1 1 1 ...
$ Q13BC07: int 0 0 0 0 0 0 0 0 0 0 ...
$ Q13BC08: int 0 0 2 1 2 0 0 2 3 3 ...
$ Q13BC9A: int NA NA 10 10 10 NA NA 14 14 14 ...
$ Q13BC9B: int NA NA 10 NA 10 NA NA 14 14 14 ...
$ Q13BC9C: int NA NA 2 2 2 NA NA 2 2 2 ...
$ Q13BC9D: int NA NA NA NA NA NA NA NA NA NA ...
$ Q13BC10: int NA NA 4000 3000 3000 NA NA 0 0 2000 ...
$ Q13BC11: int NA NA 20000 10000 10000 NA NA 6000 9000 15000 ...
$ Q13BC12A : int NA NA 2 2 2 NA NA 1 1 1 ...
$ Q13BC12B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q13BC12C : int NA NA NA NA NA NA NA NA NA NA ...
$ EntryUser : chr "morokat" "morokat" "morokat" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:43:00" "2012-02-21 19:43:00" ...
$ persid: chr "080301001" "080301002" "080301003" "080301004" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:13"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 30 #### PersonDisability ##########'data.frame':
17644 obs. of 18 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "0803010" "0803010" "0803010" ...
$ Q14_C01: int 1 2 3 4 5 1 2 3 4 1 ...
$ Q14_C02A : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q14_C02B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C02C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C03A : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C03B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C03C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C04A : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C04B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C04C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C05A : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C05B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q14_C05C : int NA NA NA NA NA NA NA NA NA NA ...
$ EntryUser : chr "morokat" "morokat" "morokat" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:44:00" "2012-02-21 19:44:00" ...
$ Persid: chr "080301001" "080301002" "080301003" "080301004" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:13"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...

Manual Cambodia CSES 2012 Version 2.0

47- attr(*, "types")= int 253 7 251 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 31 #### PersonEcoCurrent ##########'data.frame':
16086 obs. of 47 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "0803010" "0803010" "0803010" ...
$ Q15_C01: int 1 2 3 4 1 2 3 4 1 2 ...
$ Q15_C02: int 1 2 2 2 1 1 3 1 1 2 ...
$ Q15_C03: int 1 2 2 2 1 1 2 2 1 1 ...
$ Q15_C04: int NA 2 2 2 NA NA 2 2 NA NA ...
$ Q15_C05B : chr "634" "" "" "" ...
$ Q15_C06B : chr "0310" "" "" "" ...
$ Q15_C07: int 3 NA NA NA 3 4 NA NA 3 3 ...
$ Q15_C08: int 3 NA NA NA 3 1 NA NA 3 1 ...
$ Q15_C09: int 40 NA NA NA 63 60 NA NA 28 56 ...
$ Q15_C10A : int 17 NA NA NA 30 28 NA NA 20 28 ...
$ Q15_C10B : int 1 NA NA NA 1 1 NA NA 1 2 ...
$ Q15_C10C : int NA NA NA NA NA NA NA NA NA 2 ...
$ Q15_C10D : int 2 NA NA NA 2 2 NA NA 2 2 ...
$ Q15_C11: int 0 NA NA NA 0 0 NA NA 1 0 ...
$ Q15_C12B : chr "" "" "" "" ...
$ Q15_C13B : chr "" "" "" "" ...
$ Q15_C14: int NA NA NA NA NA NA NA NA 3 NA ...
$ Q15_C15: int NA NA NA NA NA NA NA NA 3 NA ...
$ Q15_C16: int NA NA NA NA NA NA NA NA 6 NA ...
$ Q15_C17A : int NA NA NA NA NA NA NA NA 10 NA ...
$ Q15_C17B : int NA NA NA NA NA NA NA NA 2 NA ...
$ Q15_C17C : int NA NA NA NA NA NA NA NA 2 NA ...
$ Q15_C18A : int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C18B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C19: int NA NA NA NA NA NA NA NA 34 NA ...
$ Q15_C20: int NA NA NA NA NA 400000 NA NA NA 40000 ...
$ Q15_C21: int 3 NA NA NA 2 3 NA NA 2 3 ...
$ Q15_C22A : int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C22B : int NA NA NA NA 10 NA NA NA 21 NA ...
$ Q15_C23: int NA NA NA NA 2 NA NA NA 2 NA ...
$ Q15_C24: int NA NA NA NA 2 NA NA NA 2 NA ...
$ Q15_C25: int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C26: int NA 2 2 2 NA NA 2 2 NA NA ...
$ Q15_C27A : int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C27B : int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C27C : int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C28: int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C29: int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C30: int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C31: int NA 8 7 6 NA NA 7 7 NA NA ...
$ Q15_C32: int NA NA NA NA NA NA NA NA NA NA ...
$ Q15_C33: int NA NA NA NA NA NA NA NA NA NA ...
$ EntryUser : chr "morokat" "morokat" "morokat" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:45:00" "2012-02-21 19:45:00" ...
$ Persid: chr "080301001" "080301002" "080301003" "080301004" ...

Manual Cambodia CSES 2012 Version 2.0

48- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:13"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 251 3 4 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 32 #### PersonviolenceA ##########'data.frame':
17588 obs. of 8 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0803010" "0803010" "0803010" "0803010" ...
$ Q17AC01: int 1 2 3 4 5 1 2 3 4 1 ...
$ Q17AC02: int 2 2 2 2 2 2 2 2 2 2 ...
$ Q17AC03: int NA NA NA NA NA NA NA NA NA NA ...
$ EntryUser : chr "morokat" "morokat" "morokat" "morokat" ...
$ ChangeDate: POSIXct, format: "2012-02-21 19:46:00" "2012-02-21 19:46:00" ...
$ persid: chr "080301001" "080301002" "080301003" "080301004" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:12"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 15 255 9- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 33 #### PersonViolenceB ##########'data.frame':
44 obs. of 14 variables:$ pkid: int 1 2 3 4 9 13 15 16 18 19 ...
$ hhid: chr "0102701" "1701904" "1701904" "1701904" ...
$ Q17BC01: int 1 1 1 1 2 1 2 1 2 2 ...
$ Q17BC02: int 1 1 2 3 1 2 2 3 1 2 ...
$ Q17BC03: int 11 1 3 4 1 1 3 4 4 4 ...
$ Q17BC04: int 2 1 2 2 1 2 1 2 2 2 ...
$ Q17BC05: int NA 1 NA NA 1 NA 2 NA NA NA ...
$ Q17BC06: int NA 2 NA NA 2 NA 2 NA NA NA ...
$ Q17BC07: int 4 3 3 3 2 3 2 3 3 3 ...
$ Q17BC08: int 2 2 2 2 1 2 1 2 2 2 ...
$ Q17BC09: int 1 2 1 1 1 1 1 1 1 1 ...
$ EntryUser : chr "riya" "buntha" "buntha" "buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-24 22:52:00" "2012-02-28 01:43:00" ...
$ persid: chr "010270101" "170190401" "170190401" "170190401" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:12"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL

Manual Cambodia CSES 2012 Version 2.0

49## 34 #### HHOtherInfo ##########'data.frame':
3840 obs. of 47 variables:$ pkid: int 1 2 3 4 5 6 7 8 9 10 ...
$ hhid: chr "0102701" "2101910" "0803010" "2101801" ...
$ Q01BQ1: int 1 1 1 1 1 1 1 1 1 1 ...
$ Q05AQ1A: int 2 2 2 2 2 2 2 2 2 2 ...
$ Q05AQ1B: int NA NA NA NA NA NA NA NA NA NA ...
$ Q05AQ2: int 1 1 2 1 2 1 2 1 1 1 ...
$ Q05AQ3: int 1 2 NA 4 NA 1 NA 2 2 2 ...
$ Q05ANote : int 0 0 NA 0 NA 0 NA 0 0 0 ...
$ Q05BQ1: int 2 1 NA 1 NA 1 NA 1 1 1 ...
$ Q05BNote : int NA 0 NA 0 NA 0 NA 0 0 0 ...
$ Q05CNote : int NA 0 NA 0 NA 0 NA 1 0 0 ...
$ Q05DQ1: int NA 1 NA 1 NA 2 NA 1 1 2 ...
$ Q05DNote1 : int NA 0 NA 0 NA 0 NA 0 0 0 ...
$ Q05D1Q1: int NA 1 NA 2 NA 2 NA 1 1 1 ...
$ Q05DNote2 : int NA 0 NA 0 NA 0 NA 0 0 0 ...
$ Q05EQ1: int 2 1 1 1 2 1 1 1 1 1 ...
$ Q05ENote1 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05ENote2 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05FQ1: int 2 1 2 2 2 2 2 2 2 2 ...
$ Q05FQ2: int 2 1 2 1 2 2 2 1 2 2 ...
$ Q05FNote1 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05FQ3: int 2 1 1 1 1 1 2 1 2 1 ...
$ Q05FNote2 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05FNote3 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05GQ1: int 2 1 1 1 2 1 2 1 1 1 ...
$ Q05GQ2: int 2 1 1 1 2 2 2 1 1 1 ...
$ Q05GNote1 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05GNote2 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05HQ1: int 1 1 2 2 1 1 2 2 2 2 ...
$ Q05HNote1 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05HNote2 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q05HNote3 : int 0 0 0 0 0 0 0 0 0 0 ...
$ Q06_Q1: int 2 1 1 1 1 2 2 1 1 2 ...
$ Q08_Q1: int 2 1 1 1 1 2 1 1 1 1 ...
$ Q10_Q1: int 2 1 1 1 2 1 1 2 2 2 ...
$ Q11_Q1: int 2 2 1 2 2 2 1 2 2 2 ...
$ Q13AQ1: int 2 2 2 2 2 2 2 2 2 2 ...
$ Q13AQ2A: int NA NA NA NA NA NA NA NA NA NA ...
$ Q13AQ2B: int NA NA NA NA NA NA NA NA NA NA ...
$ Q13AQ2C: int NA NA NA NA NA NA NA NA NA NA ...
$ Q13AQ3: int NA NA NA NA NA NA NA NA NA NA ...
$ Q13AQ4: int 2 2 2 2 2 2 2 2 2 2 ...
$ Q17AQ1: int 1 1 1 1 2 1 1 1 2 1 ...
$ Q17AQ2: int 1 2 2 2 2 2 2 2 2 2 ...
$ Q17AQ3: int 2 1 2 2 2 2 2 1 1 2 ...
$ EntryUser : chr "riya" "riya" "morokat" "buntha" ...
$ ChangeDate: POSIXct, format: "2012-02-24 18:50:00" "2012-02-21 20:06:00" ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:14"- attr(*, "formats")= chr "%12.0g" "%9s" "%8.0g" "%8.0g" ...
- attr(*, "types")= int 253 7 251 251 251 251 251 251 251 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12

Manual Cambodia CSES 2012 Version 2.0

50

NULL

## 35 #### PSUListing ##########'data.frame':
384 obs. of 16 variables:$ PSU: chr "01003" "01006" "01007" "01008" ...
$ Province_Code: chr "01" "01" "01" "01" ...
$ Province_Name: chr "Banteay Meanchey" "Banteay Meanchey" "Banteay Meanchey" "Banteay
Meanchey" ...
$ District_Code: chr "02" "02" "03" "04" ...
$ District_Name: chr "Mongkol Borei" "Mongkol Borei" "Phnum Srok" "Preah Netr Preah" ...
$ Commune_Code: chr "08" "13" "03" "02" ...
$ Commune_Name: chr "Rohat Tuek" "Ta Lam" "Ponley" "Chob Vari" ...
$ Village_Code: chr "13" "07" "04" "07" ...
$ Village_Name: chr "Chak Kaeut" "Khla Kham Chhkae" "Svay Khmau" "Chreab Chas" ...
$ Enum_Areas: int 2 2 3 2 4 2 17 9 5 5 ...
$ Selected_EA: int 2 2 2 1 3 1 15 1 1 3 ...
$ UrbanRural: int 2 2 2 2 2 2 1 1 1 1 ...
$ Households: int 119 141 275 189 462 291 1890 1024 664 503 ...
$ SurveyMonth: int 8 8 3 3 5 5 8 8 4 4 ...
$ HouseholdsInVillage: int 143 182 305 176 550 245 1281 1195 524 503 ...
$ HouseholdsInListing: int 63 64 112 81 65 67 118 268 105 79 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "17 Jul 2013 14:11"- attr(*, "formats")= chr "%9s" "%9s" "%100s" "%9s" ...
- attr(*, "types")= int 5 2 100 2 100 2 100 2 100 251 ...
- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "version")= int 12
NULL## 36 #### weighthouseholds ##########'data.frame':
3840 obs. of 7 variables:$ PSU: chr "01003" "01003" "01003" "01003" ...
$ HHID: chr "0100301" "0100302" "0100303" "0100304" ...
$ urbrur: chr "2" "2" "2" "2" ...
$ Stratum: chr "2" "2" "2" "2" ...
$ Poststratum: chr "12" "12" "12" "12" ...
$ hhsize: int 2 5 8 5 5 3 6 3 5 7 ...
$ hw12a: num 1237 1237 1237 1237 1237 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "23 Dec 2013 23:45"- attr(*, "formats")= chr "%50s" "%50s" "%50s" "%50s" ...
- attr(*, "types")= int 50 50 50 50 50 251 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "expansion.fields")=List of 2..$ : chr "hw12a" "destring" "Characters removed were:"..$ : chr "hhsize" "destring" "Characters removed were:"- attr(*, "version")= int 12
NULL## 37 #### weightpersons ##########'data.frame':
17644 obs. of 8 variables:

Manual Cambodia CSES 2012 Version 2.0

51$ PersID: chr "010030101" "010030102" "010030201" "010030202" ...
$ PSU: chr "01003" "01003" "01003" "01003" ...
$ HHID: chr "0100301" "0100301" "0100302" "0100302" ...
$ urbrur: chr "2" "2" "2" "2" ...
$ Stratum: chr "2" "2" "2" "2" ...
$ Poststratum: chr "12" "12" "12" "12" ...
$ hw12a: num 1237 1237 1237 1237 1237 ...
$ pw12a: num 1044 1044 1284 1222 1339 ...
- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "23 Dec 2013 23:42"- attr(*, "formats")= chr "%50s" "%50s" "%50s" "%50s" ...
- attr(*, "types")= int 50 50 50 50 50 50 255 255- attr(*, "val.labels")= chr "" "" "" "" ...
- attr(*, "var.labels")= chr "" "" "" "" ...
- attr(*, "expansion.fields")=List of 2..$ : chr "pw12a" "destring" "Characters removed were:"..$ : chr "hw12a" "destring" "Characters removed were:"- attr(*, "version")= int 12
NULL

Manual Cambodia CSES 2012 Version 2.0

52Generated list of variable names in each data frame> var.names<-list()> for(j in 1:37){+ var.names<-c(var.names,list(attributes(outfiles[[j]])$var.labels))+ }Unfortunately, no variable label was defined in STATA files.

Manual Cambodia CSES 2012 Version 2.0

53Chapert 5. Data Check

5.1 Summary of each data file
# Displayed the summary of each data file
> for(j in 1:37){+ cat("##",j,"#### ",Rnames[j]," ##########\n")+ print(summary(outfiles[[j]]))+ cat("\n\n")+ }## 1 #### Households ##########HHID
PSU
HHnumber
Length:3840
Length:3840
Length:3840
Class :character
Class :character
Class :character
Mode :character
Mode :character
Mode :character

Females
Total
SupervisorId
Min.
:0.000Min.
: 1.000
Length:3840
1st Qu.:2.000
1st Qu.: 3.000
Class :character
Median :2.000
Median : 4.000
Mode :character
Mean:2.395Mean: 4.595
3rd Qu.:3.000
3rd Qu.: 6.000
Max.
:8.000Max.
:15.000
SignOut
Operator
Min.
:2012-02-28 19:16:00
Length:3840
1st Qu.:2012-05-11 22:36:00
Class :character
Median :2012-12-17 17:50:00
Mode :characterMean:2012-10-08 09:12:49
3rd Qu.:2013-02-18 23:57:45
Max.
:2013-03-28 18:45:00## 2 #### HHMembers ##########
pkid
hhid
Min.
:
2
Length:17644
1st Qu.: 4479
Class :character
Median : 8930
Mode :character
Mean: 8956
3rd Qu.:13445
Max.
:17903
Q01AC04A
Min.
: 1.00
1st Qu.: 6.00
Median :11.00
Mean:12.67
3rd Qu.:19.00
Max.
:31.00NA's:75
Q01AC06

Q01AC04B
Min.
: 1.000
1st Qu.: 3.000
Median : 5.000
Mean: 5.696
3rd Qu.: 8.000
Max.
:12.000
NA's:18
Q01AC07

Q01AC01Min.
: 1.00
1st Qu.: 2.00
Median : 3.00
Mean
: 3.16
3rd Qu.: 4.00
Max.
:15.00Q01AC04CMin.
:1915
1st Qu.:1970
Median :1987
Mean
:1984
3rd Qu.:1999
Max.
:2012
NA's
:2
Q01AC08

Males
Min.
:0.000
1st Qu.:1.000
Median :2.000
Mean:2.199
3rd Qu.:3.000
Max.
:9.000
RowDiff
Min.
:0
1st Qu.:0
Median :0
Mean:0
3rd Qu.:0Max.
:0Q01AC03Min.
:1.000
1st Qu.:1.000
Median :2.000
Mean:1.521
3rd Qu.:2.000
Max.
:2.000Q01AC05Min.
: 0.00
1st Qu.:12.00
Median :25.00
Mean:28.09
3rd Qu.:42.00
Max.
:96.00Q01AC09

Manual Cambodia CSES 2012 Version 2.0

54

Min.
: 1.000
1st Qu.: 2.000
Median : 3.000
Mean: 3.212
3rd Qu.: 3.000
Max.
:15.000Min.
: 1.000Min.
: 0.000
Min.
:1.000
1st Qu.: 1.000
1st Qu.: 2.000
1st Qu.:1.000
Median : 1.000
Median : 2.000
Median :1.000
Mean: 1.375
Mean: 2.065
Mean:2.229
3rd Qu.: 1.000
3rd Qu.: 2.000
3rd Qu.:4.000
Max.
:14.000
Max.
:11.000
Max.
:4.000
NA's
:9759
NA's
:8362
NA's
:4436
Q01AC10
Q01AC11A
Q01AC11B
Q01AC12A
Min.
: 0.000
Min.
:1.000Min.
:1.000Min.
:0.0000
1st Qu.: 1.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:0.0000
Median : 2.000
Median :1.000
Median :1.000
Median :0.0000
Mean: 1.995
Mean:1.052Mean:1.004Mean:0.4189
3rd Qu.: 2.000
3rd Qu.:1.000
3rd Qu.:1.000
3rd Qu.:0.0000
Max.
:14.000
Max.
:8.000Max.
:2.000Max.
:9.0000
NA's:10434
NA's
:17
NA's
:31
NA's
:17
Q01AC12B
Q01AC12C
Q01AC13
Q01AC14Min.
:0.000Min.
:0.000Min.
:1.000Min.
: 0.00
1st Qu.:0.000
1st Qu.:0.000
1st Qu.:1.000
1st Qu.: 6.00
Median :0.000
Median :0.000
Median :1.000
Median :12.00
Mean:0.409Mean:0.443Mean:1.047Mean:18.933rd Qu.:0.000
3rd Qu.:0.000
3rd Qu.:1.000
3rd Qu.:32.00
Max.
:9.000Max.
:9.000Max.
:2.000Max.
:52.00NA's:16314NA's:17565NA's:1NA's:16815
EntryUser
ChangeDate
PersidLength:17644
Min.
:2012-02-21 19:17:00
Length:17644
Class :character
1st Qu.:2012-04-27 19:26:00
Class :character
Mode :character
Median :2012-12-13 19:27:00
Mode :characterMean:2012-10-03 21:17:26
3rd Qu.:2013-02-18 17:47:00
Max.
:2013-03-27 00:41:00## 3 #### HHFoodConsumption ##########
pkid
hhid
Q01BC01
Min.
:
1
Length:57784
Min.
: 1.0
1st Qu.:14586
Class :character
1st Qu.: 5.0
Median :29097
Mode :character
Median :10.0
Mean:29099Mean:10.1
3rd Qu.:43621
3rd Qu.:15.0
Max.
:58108Max.
:21.0
Q01BC04
Q01BC05
Min.
:
0
Min.
:
0
1st Qu.:0
1st Qu.: 2000
Median :0Median : 5000
Mean
: 1264
Mean: 10898
3rd Qu.:0
3rd Qu.: 15000
Max.
:112000
Max.
:520000
NA's
:8
NA's
:12
ChangeDate
Min.
:2012-02-21 19:18:00
1st Qu.:2012-05-21 18:21:00
Median :2012-12-18 18:23:00
Mean:2012-10-16 16:34:00
3rd Qu.:2013-02-14 23:40:00

Q01BC03Min.
:
0
1st Qu.: 2000
Median : 4500
Mean
: 96333rd Qu.: 12000
Max.
:520000
NA's:5

EntryUser
Length:57784
Class :character
Mode :character

Manual Cambodia CSES 2012 Version 2.0

55

Max.

:2013-03-27 00:45:00## 4 #### HHRecallNonFood ##########
pkid
HHID
Q01CC01
Min.
: 17
Length:40135
Min.
: 1.000
1st Qu.:10342
Class :character
1st Qu.: 4.000
Median :20791
Mode :character
Median : 6.000
Mean:20788Mean: 7.799
3rd Qu.:31203
3rd Qu.:12.000
Max.
:41382Max.
:17.000
Q01CC05
Q01CC06
Min.
:
0
Min.
:
0
1st Qu.:0
1st Qu.:8000
Median :0Median :50000
Mean: 2458Mean: 288028
3rd Qu.:0
3rd Qu.: 200000
Max.
:2500000
Max.
:28000000
NA's
:3192
NA's
:15
ChangeDate
Min.
:2012-02-21 19:27:00
1st Qu.:2012-05-23 17:50:00
Median :2012-12-18 23:40:00
Mean:2012-10-22 08:21:11
3rd Qu.:2013-02-14 18:50:00
Max.
:2013-06-13 21:32:00

EntryUser
Length:40135
Class :character
Mode :character## 5 #### HHVulnerability ##########
pkid
hhid
Q01DQ1Min.
: 1.0
Length:3843
Min.
:1.000
1st Qu.: 973.5
Class :character
1st Qu.:1.000
Median :1948.0
Mode :character
Median :1.000
Mean:1955.1
Mean:1.156
3rd Qu.:2938.5
3rd Qu.:1.000
Max.
:3918.0
Max.
:4.000Q01DQ3Min.
: 0.000
1st Qu.: 2.000
Median : 4.000
Mean: 8.096
3rd Qu.:12.000
Max.
:32.000
NA's:3677
Q01DQ4_4
Min.
:0.000
1st Qu.:0.000
Median :0.000
Mean:0.078
3rd Qu.:0.000
Max.
:1.000NA's:3677

Q01DQ4_1
Min.
:0.00
1st Qu.:0.00
Median :0.00
Mean
:0.12
3rd Qu.:0.00
Max.
:1.00
NA's
:3677
Q01DQ4_5
Min.
:0.000
1st Qu.:0.000
Median :0.000
Mean:0.078
3rd Qu.:0.000
Max.
:1.000NA's:3677

Q01CC04
Min.
:
0
1st Qu.:12000
Median :60000
Mean: 305598
3rd Qu.: 240000
Max.
:28000000
NA's
:3183

Q01DQ4_2
Min.
:0.000
1st Qu.:0.000
Median :0.000
Mean:0.1143rd Qu.:0.000
Max.
:1.000NA's:3677
Q01DQ4_6
Min.
:0.000
1st Qu.:0.000
Median :0.000
Mean:0.151
3rd Qu.:0.000
Max.
:1.000NA's:3677

Q01DQ2Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.0433rd Qu.:1.000
Max.
:2.000Q01DQ4_3
Min.
:0.000
1st Qu.:0.000
Median :0.000
Mean:0.0843rd Qu.:0.000
Max.
:1.000NA's:3677
Q01DQ4_7
Min.
:0.000
1st Qu.:0.000
Median :0.000
Mean:0.247
3rd Qu.:0.000
Max.
:1.000NA's:3677

Manual Cambodia CSES 2012 Version 2.0

56

Q01DQ4_8
Q01DQ4_9
Min.
:0.000Min.
:0.000
1st Qu.:0.000
1st Qu.:0.000
Median :0.000
Median :1.000
Mean:0.422Mean:0.627
3rd Qu.:1.000
3rd Qu.:1.000
Max.
:1.000Max.
:1.000
NA's
:3677
NA's
:3677
Q01DQ4_12
Q01DQ5Min.
:0.000Min.
:1.000
1st Qu.:0.000
1st Qu.:1.000
Median :0.000
Median :2.000
Mean:0.313Mean:2.012
3rd Qu.:1.000
3rd Qu.:3.000
Max.
:1.000Max.
:3.000
NA's
:3677
NA's
:3677
ChangeDate
Min.
:2012-02-21 19:25:00
1st Qu.:2012-05-11 18:35:00
Median :2012-12-14 21:31:00
Mean:2012-10-05 20:26:57
3rd Qu.:2013-02-16 00:57:30
Max.
:2013-03-27 00:49:00

Q01DQ4_10
Q01DQ4_11
Min.
:0.000Min.
:0.000
1st Qu.:0.000
1st Qu.:0.000
Median :1.000
Median :0.000
Mean:0.651Mean:0.4043rd Qu.:1.000
3rd Qu.:1.000
Max.
:1.000Max.
:1.000
NA's
:3677
NA's
:3677
EntryUser
Length:3843
Class :character
Mode :character## 6 #### PersonEducation ##########
pkid
hhid
Q02C01Min.
:
1Length:16754
Min.
: 1.000
1st Qu.: 4220
Class :character
1st Qu.: 2.000
Median : 8436
Mode :character
Median : 3.000
Mean: 8430
Mean: 3.054
3rd Qu.:12634
3rd Qu.: 4.000
Max.
:16843Max.
:15.000

Q02C1bMin.
: 1.00
1st Qu.: 1.00
Median : 2.00
Mean
: 2.15
3rd Qu.: 2.00
Max.
:14.00
NA's:13
Q02C02
Q02C03
Q02C04
Q02C05Min.
:1Min.
:1.000Min.
:1.000Min.
: 0.00
1st Qu.:1
1st Qu.:1.000
1st Qu.:1.000
1st Qu.: 4.00
Median :1
Median :1.000
Median :1.000
Median : 6.00
Mean
:1
Mean
:1.267Mean:1.177Mean: 6.343rd Qu.:1
3rd Qu.:2.000
3rd Qu.:1.000
3rd Qu.: 9.00
Max.
:1
Max.
:2.000Max.
:2.000Max.
:20.00
NA's
:3
NA's
:3
NA's
:2968
Q02C06
Q02C07
Q02C08
Q02C09Min.
: 0.000
Min.
:1.000Min.
: 0.000
Min.
:1.000
1st Qu.: 4.000
1st Qu.:1.000
1st Qu.: 3.000
1st Qu.:1.000
Median : 6.000
Median :2.000
Median : 5.000
Median :1.000
Mean: 8.383
Mean:1.691
Mean: 6.074
Mean:1.0643rd Qu.: 9.000
3rd Qu.:2.000
3rd Qu.: 9.000
3rd Qu.:1.000
Max.
:88.000
Max.
:2.000Max.
:21.000
Max.
:2.000
NA's
:2967
NA's
:2972
NA's
:12499NA's:12499Q02C10
Q02C11
Q02C12
Q02C13Min.
:1.000Min.
: 1.000
Min.
:1.000Min.
:1.000
1st Qu.:1.000
1st Qu.: 6.000
1st Qu.:2.000
1st Qu.:1.000
Median :2.000
Median :11.000
Median :2.000
Median :1.000
Mean:1.723Mean: 8.572
Mean:1.951Mean:1.278Manual Cambodia CSES 2012 Version 2.0

57

3rd Qu.:2.000
3rd Qu.:11.000
3rd Qu.:2.000
3rd Qu.:2.000
Max.
:2.000Max.
:12.000
Max.
:2.000Max.
:2.000NA's:12499NA's:15130NA's:15935
Q02C14
Q02C15
Q02C16A
Q02C16B
Min.
:1.000Min.
:1.000
Min.
:
0
Min.
:
0
1st Qu.:4.000
1st Qu.:2.000
1st Qu.:0
1st Qu.:0
Median :4.000
Median :2.000
Median :0Median :0
Mean:3.918Mean:1.753Mean: 173576
Mean: 92435
3rd Qu.:4.000
3rd Qu.:2.000
3rd Qu.:0
3rd Qu.:0
Max.
:6.000Max.
:2.000Max.
:14000000
Max.
:7400000NA's:16169NA's:1
NA's:12620NA's:12624
Q02C16C
Q02C16D
Q02C16E
Q02C16F
Min.
:
0
Min.
:
0
Min.
:
0
Min.
:
0
1st Qu.: 10000
1st Qu.: 11000
1st Qu.: 100000
1st Qu.:0
Median : 20000
Median : 25000
Median : 200000
Median :0
Mean: 43747Mean: 47667
Mean: 340233
Mean: 63643
3rd Qu.: 40000
3rd Qu.: 50000
3rd Qu.: 400000
3rd Qu.:0
Max.
:2000000
Max.
:1200000
Max.
:8640000
Max.
:4000000NA's:12622NA's:12622NA's:12622NA's:12623
Q02C16G
Q02C16H
EntryUser
Min.
:
0
Min.
:
0
Length:16754
1st Qu.:0
1st Qu.: 161000
Class :character
Median :0Median : 305000
Mode :characterMean: 2530Mean: 764658
3rd Qu.: 2000
3rd Qu.: 786125
Max.
:400000
Max.
:14950000
NA's:12623NA's:12622
ChangeDate
PersidMin.
:2012-02-21 19:25:00
Length:16754
1st Qu.:2012-04-28 01:05:00
Class :character
Median :2012-12-14 18:48:00
Mode :characterMean:2012-10-04 15:35:53
3rd Qu.:2013-02-18 18:41:00
Max.
:2013-03-28 18:45:00## 7 #### HHHousing ##########
pkid
hhid
Min.
: 1
Length:3841
1st Qu.: 961
Class :character
Median :1921
Mode :character
Mean
:1929
3rd Qu.:2901
Max.
:3865

Q04_01Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.046
3rd Qu.:1.000
Max.
:9.000

Q04_03Min.
: 1.000
1st Qu.: 1.000
Median : 1.000
Mean: 1.517
3rd Qu.: 2.000
Max.
:12.000

Q04_05Min.
:1.00
1st Qu.:2.00
Median :4.00
Mean
:3.54
3rd Qu.:4.00
Max.
:9.00

Q04_07:1.000Min.

Q04_04Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:2.555
3rd Qu.:4.000
Max.
:9.000
Q04_08: 1.000

Min.

Q04_02Min.
: 4.00
1st Qu.: 30.00
Median : 42.00
Mean: 46.84
3rd Qu.: 56.00
Max.
:475.00

Q04_09:0.00

Q04_06Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:3.447
3rd Qu.:4.000
Max.
:9.000Min.

Q04_10M1
Min.
:1.000Manual Cambodia CSES 2012 Version 2.0

58

1st Qu.:1.000
Median :1.000
Mean:2.177
3rd Qu.:3.000
Max.
:8.000

1st Qu.: 1.000
1st Qu.:5.00
1st Qu.:1.000
Median : 4.000
Median : 10.00
Median :1.000
Mean: 4.586
Mean: 42.89
Mean:1.397
3rd Qu.: 9.000
3rd Qu.: 30.00
3rd Qu.:1.000
Max.
:13.000
Max.
:7000.00
Max.
:9.000
NA's
:2
NA's
:2180
NA's
:2286
Q04_10M2
Q04_10M3
Q04_11
Q04_12Min.
:1.000Min.
:1.000Min.
: 2.00Min.
: 1.000
1st Qu.:2.000
1st Qu.:3.000
1st Qu.: 10.00
1st Qu.: 1.000
Median :2.000
Median :3.000
Median : 20.00
Median : 3.000
Mean:2.388Mean:3.425Mean: 21.99
Mean: 3.938
3rd Qu.:3.000
3rd Qu.:4.000
3rd Qu.: 30.00
3rd Qu.: 6.000
Max.
:9.000Max.
:9.000Max.
:300.00Max.
:13.000
NA's
:2476
NA's
:3224
NA's
:2288
Q04_13
Q04_14M1
Q04_14M2
Q04_14M3
Min.
: 0.00Min.
: 1.000Min.
: 1.000
Min.
:1.000
1st Qu.: 6.00
1st Qu.: 1.000
1st Qu.: 2.000
1st Qu.:3.000
Median : 15.00
Median : 1.000
Median : 2.000
Median :3.000
Mean: 62.59
Mean: 1.414Mean: 2.382
Mean:3.471
3rd Qu.: 50.00
3rd Qu.: 1.000
3rd Qu.: 2.750
3rd Qu.:4.000
Max.
:7000.00
Max.
:10.000Max.
:14.000
Max.
:9.000
NA's
:1462
NA's
:1715
NA's
:2015
NA's
:3056
Q04_15
Q04_16
Q04_17
Q04_18A
Min.
: 1.00
Min.
:
0
Min.
:1.000Min.
:1.000
1st Qu.: 15.00
1st Qu.:0
1st Qu.:1.000
1st Qu.:1.000
Median : 25.00
Median :0Median :1.000
Median :1.000
Mean: 27.41
Mean: 9923Mean:1.428Mean:1.127
3rd Qu.: 32.00
3rd Qu.: 17000
3rd Qu.:2.000
3rd Qu.:1.000
Max.
:300.00
Max.
:120000
Max.
:3.000Max.
:2.000
NA's
:1725
NA's
:655
Q04_18B
Q04_18C
Q04_18D
Q04_18E
Min.
:1.000Min.
:1.000Min.
:1.000Min.
:1.000
1st Qu.:2.000
1st Qu.:2.000
1st Qu.:2.000
1st Qu.:2.000
Median :2.000
Median :2.000
Median :2.000
Median :2.000
Mean:1.808Mean:1.998Mean:1.999Mean:1.988
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:2.000
Max.
:2.000Max.
:2.000Max.
:2.000Max.
:2.000
NA's
:655
NA's
:655
NA's
:655
NA's
:655
Q04_19A
Q04_19B
Q04_20
Q04_21Min.
:1.000Min.
:1.000
Min.
:
0.0
Min.
:
0
1st Qu.:2.000
1st Qu.:1.000
1st Qu.:0.0
1st Qu.:0
Median :2.000
Median :1.000
Median :0.0Median :0
Mean:4.066Mean:1.896
Mean
:
417.4
Mean
: 1207
3rd Qu.:7.000
3rd Qu.:3.000
3rd Qu.:0.0
3rd Qu.:0
Max.
:8.000Max.
:4.000Max.
:240000.0
Max.
:120000
NA's:3
Q04_22A
Q04_22B
Q04_22C1
Q04_22C2
Min.
:1.000Min.
:1.000Min.
:1.000Min.
: 1.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.: 2.000
Median :1.000
Median :2.000
Median :1.000
Median : 2.000
Mean:1.595Mean:1.723Mean:1.384Mean: 2.449
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:1.000
3rd Qu.: 3.000
Max.
:8.000Max.
:2.000Max.
:9.000Max.
:10.000
NA's
:878
NA's
:1698
NA's
:2187
Q04_22C3
Q04_22D
Q04_23A
Q04_23BMin.
: 1.000Min.
: 0.000
Min.
:
0
Min.
:
0

Manual Cambodia CSES 2012 Version 2.0

59

1st Qu.: 3.000
Median : 3.000
Mean: 3.626
3rd Qu.: 4.000
Max.
:13.000
NA's:3247
Q04_23CMin.
:
0
1st Qu.:0
Median :0
Mean: 1866
3rd Qu.: 1500
Max.
:80000
Q04_23GMin.
:
0.0
1st Qu.:0.0
Median :0.0
Mean: 683.5
3rd Qu.:0.0
Max.
:300000.0

1st Qu.: 2.000
Median : 3.000
Mean: 3.972
3rd Qu.: 5.000
Max.
:60.000
NA's:1734
Q04_23DMin.
:
0
1st Qu.:0
Median : 20000
Mean: 23123
3rd Qu.: 30000
Max.
:500000

Q04_26Min.
:
0
1st Qu.:0
Median :0
Mean: 2130
3rd Qu.:0
Max.
:1000000
NA's:26

1st Qu.:0
Median : 10000
Mean: 31823
3rd Qu.: 42000
Max.
:800000

1st Qu.:0
Median :0
Mean: 10302
3rd Qu.: 10000
Max.
:180000

Q04_23EMin.
:
0
1st Qu.:0
Median :0
Mean: 48643rd Qu.: 3000
Max.
:150000

Q04_23FMin.
:
0
1st Qu.:0
Median :0
Mean: 3735
3rd Qu.: 6000
Max.
:98000

Q04_24
Q04_25A
Q04_25B
Min.
:1.00
Min.
: 30000
Min.
:
5000
1st Qu.:1.00
1st Qu.: 120000
1st Qu.: 60000
Median :1.00
Median : 180000
Median : 100000
Mean
:1.12
Mean
: 353448
Mean: 237953
3rd Qu.:1.00
3rd Qu.: 400000
3rd Qu.: 237500
Max.
:4.00
Max.
:2800000
Max.
:6000000
NA's
:9
NA's
:3686
NA's
:155
EntryUser
ChangeDate
Length:3841
Min.
:2012-02-21 19:36:00
Class :character
1st Qu.:2012-05-11 18:30:00
Mode :character
Median :2012-12-14 21:23:00
Mean:2012-10-05 19:49:36
3rd Qu.:2013-02-16 01:06:00
Max.
:2013-03-27 19:23:00## 8 #### HHLandOwnership ##########
pkid
hhid
Q05AC01
Min.
: 4
Length:3781
Min.
: 1.000
1st Qu.: 969
Class :character
1st Qu.: 1.000
Median :1918
Mode :character
Median : 1.000
Mean
:1915
Mean
: 1.653
3rd Qu.:2867
3rd Qu.: 2.000
Max.
:3815
Max.
:13.000
Q05AC03Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.177
3rd Qu.:1.000
Max.
:4.000Q05AC04AMin.
:
2
1st Qu.:500
Median : 100000
Mean: 373871
3rd Qu.: 390000
Max.
:24000000
NA's:383
Q05AC05A
Q05AC05B
Min.
:
48
Min.
:1.00
1st Qu.:300
1st Qu.:1.00
Median :1000
Median :2.00
Mean: 622787
Mean:1.54
3rd Qu.: 300000
3rd Qu.:2.00
Max.
:70000000
Max.
:2.00

Q05AC04B
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.405
3rd Qu.:2.000
Max.
:3.000NA's:382
Q05AC05C
Min.
:2.000
1st Qu.:2.000
Median :3.000
Mean:2.5443rd Qu.:3.000
Max.
:3.000Q05AC02Min.
:
50
1st Qu.:2760
Median :5000
Mean: 10236
3rd Qu.: 10000
Max.
:1300000
Q05AC04C
Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:2.469
3rd Qu.:3.000
Max.
:3.000NA's:402
Q05AC06A
Min.
:
48
1st Qu.:485
Median :80000
Mean: 701903
3rd Qu.: 495000
Max.
:50000000

Manual Cambodia CSES 2012 Version 2.0

60

NA's
:3542
Q05AC06B
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.451
3rd Qu.:2.000
Max.
:2.000NA's:3639
Q05AC09Min.
:1.00
1st Qu.:1.00
Median :2.00
Mean
:2.36
3rd Qu.:3.00
Max.
:8.00
Q05AC13A
Min.
:1.000
1st Qu.:3.000
Median :4.000
Mean:3.3533rd Qu.:4.000
Max.
:7.000NA's:1523
Q05AC16AMin.
:1.00
1st Qu.:1.00
Median :1.00
Mean
:1.43
3rd Qu.:1.00
Max.
:6.00
NA's
:18
Q05AC18A
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.205
3rd Qu.:1.000
Max.
:8.000Q05AC20Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.091
3rd Qu.:1.000
Max.
:2.000

NA's
:3542
NA's
:3542
NA's
:3639
Q05AC06C
Q05AC07
Q05AC08Min.
:2.000Min.
: 1.000
Min.
:1959
1st Qu.:2.000
1st Qu.: 1.000
1st Qu.:1983
Median :2.000
Median : 1.000
Median :1993
Mean:2.465Mean: 1.974
Mean:1993
3rd Qu.:3.000
3rd Qu.: 2.000
3rd Qu.:2003
Max.
:3.000Max.
:10.000
Max.
:2012
NA's
:3639
NA's
:5
Q05AC10
Q05AC11
Q05AC12
Min.
:
50000
Min.
:1.000e+05
Min.
:1.000
1st Qu.:880000
1st Qu.:4.000e+06
1st Qu.:1.000
Median : 2500000
Median :8.000e+06
Median :1.000
Mean: 8945481
Mean:1.555e+07
Mean:1.4543rd Qu.: 8000000
3rd Qu.:1.600e+07
3rd Qu.:2.000
Max.
:500000000
Max.
:1.400e+09
Max.
:4.000NA's:3164
Q05AC13B
Q05AC14Q05AC15
Min.
:1.00
Min.
:1.000Min.
: 1.000
1st Qu.:3.00
1st Qu.:1.000
1st Qu.: 1.000
Median :4.00
Median :3.000
Median : 1.000
Mean
:4.12
Mean
:2.385Mean: 5.816
3rd Qu.:4.00
3rd Qu.:3.000
3rd Qu.: 1.000
Max.
:8.00
Max.
:7.000Max.
:99.000
NA's
:1523
NA's
:1526
Q05AC16B
Q05AC16C
Q05AC17Min.
:1.000
Min.
: NA
Min.
:1.000
1st Qu.:2.000
1st Qu.: NA
1st Qu.:1.000
Median :2.000
Median : NA
Median :3.000
Mean:2.471
Mean
:NaN
Mean
:2.736
3rd Qu.:3.000
3rd Qu.: NA
3rd Qu.:4.000
Max.
:4.000
Max.
: NA
Max.
:4.000
NA's
:3730
NA's
:3781
Q05AC18B
Q05AC18C
Q05AC19
Min.
:2
Min.
: NA
Min.
:1979
1st Qu.:2
1st Qu.: NA
1st Qu.:1992
Median :2
Median : NA
Median :2001
Mean
:2
Mean
:NaN
Mean
:2000
3rd Qu.:2
3rd Qu.: NA
3rd Qu.:2008
Max.
:2
Max.
: NA
Max.
:2012
NA's
:3780
NA's
:3781
NA's
:3458
Q05AC21
Q05AC22
EntryUser
Min.
:1979
Min.
:1.000Length:3781
1st Qu.:1983
1st Qu.:3.000
Class :character
Median :1992
Median :3.000
Mode :character
Mean
:1993
Mean
:2.978
3rd Qu.:2002
3rd Qu.:3.000
Max.
:2012
Max.
:3.000NA's:348

ChangeDate
Min.
:2012-02-21 19:44:00
1st Qu.:2012-04-25 23:32:00
Median :2012-12-05 18:28:00
Mean:2012-09-25 12:56:31
3rd Qu.:2013-02-14 17:52:00
Max.
:2013-03-27 00:51:00

Manual Cambodia CSES 2012 Version 2.0

61## 9 #### HHProductionCrops ##########
pkid
hhid
WetDryMin.
: 1
Length:4036
Min.
:1.000
1st Qu.:1033
Class :character
1st Qu.:1.000
Median :2046
Mode :character
Median :1.000
Mean
:2053
Mean
:1.2433rd Qu.:3075
3rd Qu.:1.000
Max.
:4101
Max.
:2.000Q05BC02Min.
: 1.000
1st Qu.: 1.000
Median : 1.000
Mean: 1.661
3rd Qu.: 2.000
Max.
:10.000

Q05BC01Min.
: 1.000
1st Qu.: 1.000
Median : 1.000
Mean: 1.585
3rd Qu.: 2.000
Max.
:10.000

Q05BC03B
Length:4036
Class :character
Mode :character

Q05BC04
Q05BC05
Min.
:
24
Min.
:
0
1st Qu.: 2500
1st Qu.: 2000
Median : 5000
Median : 5000
Mean
: 8750Mean: 7636
3rd Qu.: 10000
3rd Qu.: 10000
Max.
:500000
Max.
:200000
NA's
:1
NA's
:115
Q05BC06
Q05BC07
Q05BC08
Q05BC09
Min.
:
0
Min.
:
0.0
Min.
:
0.00
Min.
:
0
1st Qu.:380
1st Qu.:0.0
1st Qu.:0.00
1st Qu.: 800
Median :970
Median :7.0
Median :0.00
Median : 1000
Mean
: 5799
Mean
:
29.1
Mean
:
63.12
Mean
: 10843rd Qu.: 2000
3rd Qu.:20.0
3rd Qu.:12.00
3rd Qu.: 1100
Max.
:3000000
Max.
:11600.0
Max.
:20000.00
Max.
:17000
NA's
:14
NA's
:17
NA's
:23
NA's
:15
PastYear
EntryUser
ChangeDate
Min.
:2001
Length:4036
Min.
:2012-02-21 19:45:00
1st Qu.:2011
Class :character
1st Qu.:2012-04-25 23:59:45
Median :2011
Mode :character
Median :2012-12-06 18:52:00
Mean
:2011
Mean
:2012-09-26 02:11:30
3rd Qu.:2011
3rd Qu.:2013-02-15 20:41:45
Max.
:2012
Max.
:2013-03-26 23:59:00## 10 #### HHCostCultivationCrops ##########
pkid
hhid
WetDryMin.
: 1
Length:4034
Min.
:1.000
1st Qu.:1011
Class :character
1st Qu.:1.000
Median :2020
Mode :character
Median :1.000
Mean
:2020
Mean
:1.2443rd Qu.:3030
3rd Qu.:1.000
Max.
:4040
Max.
:2.000Q05CC02Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.635
3rd Qu.:2.000
Max.
:7.000Q05CC06

Q05CC03Min.
:
0
1st Qu.:
19200
Median :50000
Mean: 142162
3rd Qu.: 120000
Max.
:12000000
Q05CC07

Q05CC01Min.
: 1.000
1st Qu.: 1.000
Median : 1.000
Mean: 1.588
3rd Qu.: 2.000
Max.
:10.000

Q05CC04
Min.
:
0
1st Qu.:0
Median : 100000
Mean: 235969
3rd Qu.: 250000
Max.
:25000000
NA's:2
Q05CC08

Q05CC05
Min.
:
0
1st Qu.:0
Median :0
Mean: 29682
3rd Qu.: 40000
Max.
:1500000NA's:1
Q05CC09

Manual Cambodia CSES 2012 Version 2.0

62

Min.
:
0.0
1st Qu.:0.0
Median :
0.0
Mean
:
532.5
3rd Qu.:0.0
Max.
:1716000.0
NA's:4Q05CC10Min.
:
0
1st Qu.:0
Median :0
Mean: 139670
3rd Qu.: 140000
Max.
:28000000

Min.
:0
1st Qu.:0
Median :0
Mean: 56569
3rd Qu.: 20000
Max.
:9500000NA's:1
Q05CC11Min.
:
0
1st Qu.:0
Median :0
Mean: 13948
3rd Qu.:0
Max.
:3000000

Q05CC14Q05CC15
Min.
:
0
Min.
:
0
1st Qu.:0
1st Qu.:0
Median :0Median :0
Mean: 3559Mean: 10696
3rd Qu.:0
3rd Qu.:0
Max.
:1200000
Max.
:4000000
NA's
:3
NA's
:1
ChangeDate
Min.
:2012-02-21 19:46:00
1st Qu.:2012-04-26 00:00:15
Median :2012-12-06 01:12:00
Mean:2012-09-25 20:58:05
3rd Qu.:2013-02-14 21:11:00
Max.
:2013-03-27 00:00:00

Min.
:
0
1st Qu.:0
Median :4000
Mean: 16437
3rd Qu.: 16000
Max.
:4620000NA's:1
Q05CC12Min.
:
0.0
1st Qu.:0.0
Median :
0.0
Mean
:
244.2
3rd Qu.:0.0
Max.
:960000.0
NA's:1
Q05CC16Min.
:
0
1st Qu.: 166000
Median : 390000
Mean: 799915
3rd Qu.: 829700
Max.
:54500000
NA's:2## 11 #### HHInventoryCrops ##########
pkid
hhid
Q05DC01Min.
: 1.0
Length:1916
Min.
:1.0
1st Qu.: 479.8
Class :character
1st Qu.:1.0
Median : 960.5
Mode :character
Median :1.0
Mean
: 960.4
Mean:1.2
3rd Qu.:1441.2
3rd Qu.:1.0
Max.
:1921.0Max.
:4.0
Q05DC03
Q05DC04
EntryUser
Min.
:
0
Min.
:
0
Length:1916
1st Qu.: 480
1st Qu.: 900
Class :character
Median : 900
Median : 1000
Mode :character
Mean: 1243Mean: 1109
3rd Qu.: 1500
3rd Qu.: 1100
Max.
:26000Max.
:80000ChangeDate
Min.
:2012-02-21 19:47:00
1st Qu.:2012-05-11 23:56:45
Median :2012-12-06 20:00:00
Mean:2012-09-30 02:35:14
3rd Qu.:2013-02-18 18:41:15
Max.
:2013-03-26 20:49:00

Min.
:
0
1st Qu.:0
Median :0
Mean: 131359
3rd Qu.: 130000
Max.
:40000000
NA's:1
Q05CC13Min.
:
0
1st Qu.:0
Median :
0
Mean
:
19526
3rd Qu.:0
Max.
:10000000
EntryUser
Length:4034
Class :character
Mode :character

Q05DC02B
Length:1916
Class :character
Mode :character

Manual Cambodia CSES 2012 Version 2.0

63## 12 #### HHSalesCrops ##########
pkid
hhid
Q05D1C1Min.
: 1.0
Length:1625
Min.
:1.000
1st Qu.: 414.0
Class :character
1st Qu.:1.000
Median : 827.0
Mode :character
Median :1.000
Mean: 826.4
Mean:1.2843rd Qu.:1239.0
3rd Qu.:1.000
Max.
:1651.0
Max.
:5.000
Q05D1C3Min.
: 10
1st Qu.: 500
Median : 1000
Mean
: 3412
3rd Qu.: 3000
Max.
:99000

Q05D1C4Min.
:80
1st Qu.: 800
Median : 1000
Mean
: 1358
3rd Qu.: 1200
Max.
:55000
NA's:2

Q05D1C2
Length:1625
Class :character
Mode :character

EntryUser
Length:1625
Class :character
Mode :character

ChangeDate
Min.
:2012-02-21 19:48:00
1st Qu.:2012-05-17 18:18:00
Median :2012-12-11 18:22:00
Mean:2012-09-30 01:56:45
3rd Qu.:2013-02-15 18:31:00
Max.
:2013-03-27 01:46:00## 13 #### HHLivestock1 ##########
pkid
hhid
Q05E1C01
Min.
:
1
Length:20526
Min.
: 1.000
1st Qu.: 5158
Class :character
1st Qu.: 3.000
Median :10326
Mode :character
Median : 5.000
Mean:10321Mean: 5.488
3rd Qu.:15482
3rd Qu.: 8.000
Max.
:20639Max.
:10.000
Q05E1C04
Min.
: 0.000
1st Qu.: 2.000
Median : 4.000
Mean: 8.748
3rd Qu.: 10.000
Max.
:520.000NA's:16655
Q05E1C7bMin.
: 0.00
1st Qu.: 2.00
Median : 4.00
Mean
: 10.05
3rd Qu.: 12.00
Max.
:2100.00
NA's:16659Q05E1C11Min.
:
0
1st Qu.:0

Q05E1C03
Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.811
3rd Qu.:2.000
Max.
:2.000

Q05E1C05
Q05E1C06
Q05E1C7aMin.
: 0.000
Min.
:
0
Min.
:
0.0
1st Qu.: 1.000
1st Qu.:80000
1st Qu.:2.0
Median : 1.000
Median : 200000
Median :5.0
Mean: 1.649
Mean: 1672451
Mean: 12.43rd Qu.: 2.000
3rd Qu.: 2000000
3rd Qu.: 16.0
Max.
:20.000
Max.
:68000000
Max.
:3000.0NA's:18782NA's:16657NA's:16656
Q05E1C08
Q05E1C09
Q05E1C10
Min.
:
0
Min.
:
0
Min.
:
0
1st Qu.:80000
1st Qu.:0
1st Qu.:0
Median : 200000
Median :0Median :0
Mean: 1569198
Mean: 396590
Mean: 123574
3rd Qu.: 1995000
3rd Qu.: 100000
3rd Qu.:0Max.
:67000000
Max.
:19000000
Max.
:40000000
NA's:16680NA's:16657NA's:16660
Q05E1C12
Q05E1C13
Q05E1C14
Min.
:
0
Min.
:
0
Min.
:
0
1st Qu.:0
1st Qu.:0
1st Qu.:0

Manual Cambodia CSES 2012 Version 2.0

64Median :0
Mean: 39376
3rd Qu.: 60000
Max.
:6600000NA's:16656
Q05E1C15Min.
:
0.0
1st Qu.:0.0
Median :0.0
Mean: 434.5
3rd Qu.:0.0
Max.
:540000.0
NA's:16663

Median :0Median :0Median :
0
Mean
:
2719
Mean
:
11489
Mean
: 24806
3rd Qu.:0
3rd Qu.:0
3rd Qu.: 20000
Max.
:2000000
Max.
:29700000
Max.
:750000
NA's:16657NA's:16658NA's:16660
EntryUser
Changedate
Length:20526
Min.
:2012-02-21 19:36:00
Class :character
1st Qu.:2012-04-25 02:21:00
Mode :character
Median :2012-12-06 18:25:00
Mean:2012-09-24 09:06:16
3rd Qu.:2013-02-16 00:07:45
Max.
:2013-03-26 21:19:00## 14 #### HHLivestock2 ##########
pkid
hhid
Q05E2C01Min.
: 1.0
Length:3898
Min.
:1.000
1st Qu.: 978.2
Class :character
1st Qu.:1.000
Median :1971.5
Mode :character
Median :2.000
Mean:1966.0
Mean:2.348
3rd Qu.:2950.8
3rd Qu.:4.000
Max.
:3930.0
Max.
:6.000
EntryUser
Length:3898
Class :character
Mode :character

Q05E2C03
Min.
:
0
1st Qu.:12000
Median :60000
Mean: 189579
3rd Qu.: 195000
Max.
:10000000
NA's:1

ChangeDate
Min.
:2012-02-21 19:38:00
1st Qu.:2012-05-02 19:24:00
Median :2012-12-11 18:27:00
Mean:2012-10-03 10:09:15
3rd Qu.:2013-02-12 18:17:45
Max.
:2013-03-26 21:19:00## 15 #### HHFishCultivation1 ##########
pkid
hhid
Q05F1C01
Q05F1C02
Min.
: 1.00Length:82
Min.
:1.000Min.
:1.000
1st Qu.:22.25
Class :character
1st Qu.:1.000
1st Qu.:1.000
Median :42.50
Mode :character
Median :1.000
Median :1.000
Mean:42.45Mean:1.012Mean:1.0733rd Qu.:62.75
3rd Qu.:1.000
3rd Qu.:1.000
Max.
:83.00Max.
:2.000Max.
:5.000Q05F1C03
Q05F1C04
Q05F1C05
EntryUser
Min.
: 6.0
Min.
:
60000
Min.
: 5000Length:82
1st Qu.: 32.0
1st Qu.: 1000000
1st Qu.: 13500
Class :character
Median : 100.0
Median : 2000000
Median : 27500
Mode :characterMean: 289.7
Mean: 3510829
Mean: 64342
3rd Qu.: 300.0
3rd Qu.: 4000000
3rd Qu.: 60000
Max.
:4800.0Max.
:32000000
Max.
:400000
ChangeDate
Min.
:2012-02-21 19:54:00
1st Qu.:2012-03-07 18:28:00
Median :2012-06-13 10:45:30
Mean:2012-08-15 10:46:37
3rd Qu.:2013-02-07 19:02:00
Max.
:2013-03-15 00:29:00

Manual Cambodia CSES 2012 Version 2.0

65## 16 #### HHFishCultivation2 ##########
pkid
hhid
Q05F2C01
Min.
: 3
Length:2614
Min.
: 1.000
1st Qu.: 664
Class :character
1st Qu.: 5.000
Median :1342
Mode :character
Median : 5.000
Mean
:1339
Mean
: 5.478
3rd Qu.:2010
3rd Qu.: 5.000
Max.
:2677
Max.
:12.000
EntryUser
ChangeDate
Length:2614
Min.
:2012-02-21 19:40:00
Class :character
1st Qu.:2012-05-18 18:18:30
Mode :character
Median :2012-12-27 18:27:30
Mean:2012-10-20 14:45:25
3rd Qu.:2013-02-20 18:27:00
Max.
:2013-03-26 20:51:00## 17 #### HHFishCultivation3 ##########
pkid
hhid
Q05F3C01Min.
: 1.0
Length:3683
Min.
:1.000
1st Qu.: 929.5
Class :character
1st Qu.:2.000
Median :1864.0
Mode :character
Median :2.000
Mean:1866.6
Mean:2.6033rd Qu.:2799.5
3rd Qu.:3.000
Max.
:3738.0
Max.
:7.000
EntryUser
ChangeDate
Length:3683
Min.
:2012-02-21 19:40:00
Class :character
1st Qu.:2012-05-12 00:37:30
Mode :character
Median :2012-12-12 17:47:00
Mean:2012-10-09 05:25:03
3rd Qu.:2013-02-15 09:32:30
Max.
:2013-03-26 20:52:00

Q05F2C03
Min.
:
0
1st Qu.:0
Median :18000
Mean: 163064
3rd Qu.:50000
Max.
:97200000

Q05F3C03
Min.
:
0
1st Qu.:40000
Median : 100000
Mean: 330604
3rd Qu.: 250000
Max.
:36000000## 18 #### HHForestryHunting1 ##########
pkid
hhid
Q05G1C01
Min.
: 1
Length:5851
Min.
: 1.000
1st Qu.:1478
Class :character
1st Qu.: 2.000
Median :2948
Mode :character
Median : 4.000
Mean
:2946
Mean
: 4.339
3rd Qu.:4418
3rd Qu.: 6.000
Max.
:5882
Max.
:10.000
Q05G1C04
Min.
:
0
1st Qu.: 40000
Median : 100000
Mean: 189032
3rd Qu.: 300000
Max.
:4000000

Q05G1C05
Min.
:
0.0
1st Qu.:0.0
Median :
0.0
Mean
:
938.2
3rd Qu.:0.0
Max.
:120000.0
NA's:2

Q05G1C03
Min.
:
0
1st Qu.:0
Median :0
Mean: 35116
3rd Qu.:0Max.
:6000000NA's:4
Q05G1C06
EntryUser
Min.
:
0
Length:5851
1st Qu.: 40000
Class :character
Median : 120000
Mode :character
Mean: 225786
3rd Qu.: 350000
Max.
:6096000

ChangeDate
Min.
:2012-02-21 19:40:00
1st Qu.:2012-05-02 17:55:00

Manual Cambodia CSES 2012 Version 2.0

66Median :2012-12-06 20:14:00
Mean:2012-10-03 11:01:55
3rd Qu.:2013-02-13 19:14:30
Max.
:2013-03-27 00:07:00## 19 #### HHForestryHunting2 ##########
pkid
hhid
Q05G2C01
Min.
: 1
Length:6645
Min.
:1.000
1st Qu.:1680
Class :character
1st Qu.:2.000
Median :3350
Mode :character
Median :5.000
Mean
:3350
Mean
:4.052
3rd Qu.:5023
3rd Qu.:5.000
Max.
:6684
Max.
:7.000
EntryUser
ChangeDate
Length:6645
Min.
:2012-02-21 19:41:00
Class :character
1st Qu.:2012-12-04 23:37:00
Mode :character
Median :2013-01-10 19:37:00
Mean:2012-12-10 12:54:24
3rd Qu.:2013-02-20 23:59:00
Max.
:2013-03-27 00:07:00## 20 #### HHNonAgriculture1 ##########
pkid
hhid
Q05H1C01Min.
: 1.0
Length:1703
Min.
:1.000
1st Qu.: 427.5
Class :character
1st Qu.:1.000
Median : 854.0
Mode :character
Median :1.000
Mean: 853.7
Mean:1.171
3rd Qu.:1279.5
3rd Qu.:1.000
Max.
:1705.0
Max.
:4.000
Q05H1C05
Q05H1C06A
Min.
: 1.000Min.
: 1.000
1st Qu.: 1.000
1st Qu.: 2.000
Median : 1.000
Median : 2.000
Mean: 1.739
Mean: 2.438
3rd Qu.: 2.000
3rd Qu.: 3.000
Max.
:14.000Max.
:10.000
NA's
:5
NA's
:847
Q05H1C06D
Q05H1C06E
Min.
: 1.000
Min.
:6.000
1st Qu.: 5.000
1st Qu.:7.000
Median : 5.000
Median :8.000
Mean: 5.556
Mean:7.3333rd Qu.: 6.000
3rd Qu.:8.000
Max.
:11.000
Max.
:8.000
NA's
:1685
NA's
:1700
Q05H1C06H
EntryUserMin.
: NA
Length:1703
1st Qu.: NAClass :character
Median : NA
Mode :character
Mean
:NaN
3rd Qu.: NA
Max.
: NA

Q05G2C03
Min.
:
0
1st Qu.:0
Median :
0
Mean
:
7813
3rd Qu.:4000
Max.
:1500000

Q05H1C04
Length:1703
Class :character
Mode :character

Q05H1C06B
Q05H1C06C
Min.
: 1.000
Min.
:1.000
1st Qu.: 3.000
1st Qu.:4.000
Median : 3.000
Median :4.000
Mean: 3.705
Mean:4.562
3rd Qu.: 4.000
3rd Qu.:5.000
Max.
:12.000
Max.
:9.000
NA's
:1486
NA's
:1639
Q05H1C06F
Q05H1C06G
Min.
:7
Min.
: NA
1st Qu.:7
1st Qu.: NAMedian :7
Median : NA
Mean
:7
Mean
:NaN
3rd Qu.:7
3rd Qu.: NA
Max.
:7
Max.
: NA
NA's
:1702
NA's
:1703
ChangeDate
Min.
:2012-02-21 19:44:00
1st Qu.:2012-05-18 19:00:30
Median :2012-12-18 19:51:00
Mean:2012-10-12 16:55:28
3rd Qu.:2013-02-19 00:45:30
Max.
:2013-03-27 00:52:00

Manual Cambodia CSES 2012 Version 2.0

67

NA's

:1703

## 21 #### HHNonAgriculture2 ##########
pkid
hhid
Q05H2C01
Min.
: 1
Length:7418
Min.
: 1.000
1st Qu.:1887
Class :character
1st Qu.: 5.000
Median :3784
Mode :character
Median :10.000
Mean
:3772
Mean
: 9.965
3rd Qu.:5647
3rd Qu.:14.000
Max.
:7509
Max.
:21.000

Q05H2C03Min.
:0.000e+00
1st Qu.:6.000e+04
Median :2.000e+05
Mean:6.413e+06
3rd Qu.:1.000e+06
Max.
:1.815e+09
NA's:15
Q05H2C04
Q05H2C05
Q05H2C06
Q05H2C07
Min.
:
0
Min.
:
0
Min.
:
0
Min.
:0
1st Qu.:0
1st Qu.:0
1st Qu.:0
1st Qu.:0
Median :0Median :0Median :0Median :0
Mean: 2829294
Mean: 406336
Mean
:
85566
Mean
:0
3rd Qu.: 200000
3rd Qu.:0
3rd Qu.:0
3rd Qu.:0
Max.
:660000000
Max.
:84000000
Max.
:45000000
Max.
:0
NA's
:5546
NA's
:6574
NA's
:6665
NA's
:6679
Q05H2C08
EntryUser
ChangeDate
Min.
:0
Length:7418
Min.
:2012-02-21 19:44:00
1st Qu.:0
Class :character
1st Qu.:2012-05-22 00:13:00
Median :0
Mode :character
Median :2012-12-17 19:49:00
Mean
:0
Mean
:2012-10-22 17:43:42
3rd Qu.:0
3rd Qu.:2013-02-18 23:32:00
Max.
:0
Max.
:2013-03-27 00:53:00
NA's
:6679

## 22 #### HHNonAgriculture3 ##########
pkid
hhid
Q05H3C01Min.
: 1.0
Length:2604
Min.
: 1.000
1st Qu.: 654.8
Class :character
1st Qu.: 5.000
Median :1310.5
Mode :character
Median : 5.000
Mean:1311.1
Mean: 6.742
3rd Qu.:1968.2
3rd Qu.: 9.000
Max.
:2619.0
Max.
:20.000

Q05H3C03Min.
:0.000e+00
1st Qu.:5.000e+04
Median :3.768e+06
Mean:2.385e+07
3rd Qu.:2.033e+07
Max.
:1.891e+09
NA's:3
Q05H3C04
Q05H3C05
Q05H3C06
Q05H3C07
Min.
:
0
Min.
:
0
Min.
:
0
Min.
:0
1st Qu.:0
1st Qu.:0
1st Qu.:0
1st Qu.:0
Median :0Median :0Median :0Median :0
Mean: 9285982
Mean: 1603850
Mean: 333013
Mean:0
3rd Qu.: 5161250
3rd Qu.:0
3rd Qu.:0
3rd Qu.:0
Max.
:680000000
Max.
:87560000
Max.
:48000000
Max.
:0
NA's
:1970
NA's
:2338
NA's
:2369
NA's
:2373
Q05H3C08
EntryUser
ChangeDate
Min.
:0
Length:2604
Min.
:2012-02-21 19:45:00
1st Qu.:0
Class :character
1st Qu.:2012-05-26 00:10:45
Median :0
Mode :character
Median :2012-12-06 21:00:00
Mean
:0
Mean
:2012-10-26 12:31:06
3rd Qu.:0
3rd Qu.:2013-02-14 19:04:00
Max.
:0
Max.
:2013-03-27 00:53:00
NA's
:2373

Manual Cambodia CSES 2012 Version 2.0

68## 23 #### HHLiabilities ##########
pkid
hhid
Q06_C01
Min.
: 1
Length:1365
Min.
:1.000
1st Qu.: 342
Class :character
1st Qu.:1.000
Median : 683
Mode :character
Median :1.000
Mean
: 683
Mean
:1.056
3rd Qu.:1024
3rd Qu.:1.000
Max.
:1366
Max.
:5.000Q06_C02Min.
: 0.000
1st Qu.: 3.000
Median : 6.000
Mean: 7.618
3rd Qu.: 10.000Max.
:120.000
NA's:1
Q06_C06
Min.
:
20000
1st Qu.:800000Median : 1500000
Mean: 4303158
3rd Qu.: 4000000
Max.
:200000000

Q06_C03
Q06_C04
Q06_C05Min.
: 0.000Min.
: 1.000Min.
: 1.000
1st Qu.: 5.000
1st Qu.: 4.000
1st Qu.: 1.000
Median : 8.000
Median : 8.000
Median : 3.000
Mean: 9.124
Mean: 6.179
Mean: 3.197
3rd Qu.:12.000
3rd Qu.: 9.000
3rd Qu.: 4.000
Max.
:60.000Max.
:10.000Max.
:10.000
NA's:133
Q06_C07
Q06_C08
EntryUser
Min.
:
12000
Min.
: 0.000
Length:1365
1st Qu.: 500000
1st Qu.: 1.900
Class :character
Median : 1200000
Median : 3.000
Mode :character
Mean: 3218252
Mean: 2.931
3rd Qu.: 3000000
3rd Qu.: 3.000
Max.
:200000000
Max.
:40.000
NA's
:3
NA's
:2
ChangeDate
Min.
:2012-02-21 19:41:00
1st Qu.:2012-04-27 19:07:00
Median :2012-12-11 19:49:00
Mean:2012-09-30 10:42:08
3rd Qu.:2013-02-15 20:18:00
Max.
:2013-03-27 00:54:00## 24 #### HHIncomeOtherSource ##########
pkid
hhid
Q07_C01
Min.
: 2
Length:4220
Min.
: 1.000
1st Qu.:1058
Class :character
1st Qu.: 2.000
Median :2144
Mode :character
Median : 9.000
Mean
:2137
Mean
: 7.093
3rd Qu.:3203
3rd Qu.:11.000
Max.
:4270
Max.
:14.000
Q07_C04
Q07_C05
Min.
:
0
Min.
:
0
1st Qu.:0
1st Qu.:
10000
Median :0Median :60000
Mean: 132083
Mean:
560231
3rd Qu.:0
3rd Qu.:200000Max.
:48000000
Max.
:200000000
NA's:3
ChangeDate
Min.
:2012-02-21 19:56:00
1st Qu.:2012-06-13 00:55:45

Q07_C03Min.
:
0
1st Qu.:0
Median :
50000
Mean
:
428242
3rd Qu.:180000Max.
:200000000

EntryUser
Length:4220
Class :character
Mode :character

Manual Cambodia CSES 2012 Version 2.0

69Median :2012-12-17 18:59:00
Mean:2012-10-29 12:19:48
3rd Qu.:2013-02-12 18:02:30
Max.
:2013-03-27 00:08:00## 25 #### HHConstruction ##########
pkid
hhid
Q08_C01Min.
: 1.0
Length:3576
Min.
:1.000
1st Qu.: 895.8
Class :character
1st Qu.:1.000
Median :1794.5
Mode :character
Median :1.000
Mean:1795.4
Mean:1.011
3rd Qu.:2696.2
3rd Qu.:1.000
Max.
:3590.0
Max.
:3.000Q08_C02A
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.026
3rd Qu.:1.000
Max.
:3.000NA's:10Q08_C02B
Q08_C02C
Q08_C03
Q08_C04
Min.
:1.00
Min.
: NA
Min.
:
6.00
Min.
:1940
1st Qu.:3.00
1st Qu.: NA
1st Qu.: 30.00
1st Qu.:1995
Median :3.00
Median : NA
Median : 42.00
Median :2002
Mean
:2.98
Mean
:NaN
Mean
: 48.88
Mean:2000
3rd Qu.:3.00
3rd Qu.: NA
3rd Qu.: 59.00
3rd Qu.:2007
Max.
:3.00
Max.
: NA
Max.
:1997.00
Max.
:2012
NA's
:3424
NA's
:3576
NA's
:1
NA's
:5
Q08_C05
Q08_C06
Q08_C07
Q08_C08Min.
:8.000e+04
Min.
:
5000
Min.
:1.00
Min.
:
50000
1st Qu.:1.000e+07
1st Qu.: 60000
1st Qu.:2.00
1st Qu.: 480000
Median :2.000e+07
Median : 100000
Median :2.00
Median : 733000
Mean:6.131e+07
Mean: 248075
Mean
:1.99
Mean
: 1299000
3rd Qu.:5.200e+07
3rd Qu.: 240000
3rd Qu.:2.00
3rd Qu.: 1320000
Max.
:2.114e+09
Max.
:6000000
Max.
:2.00
Max.
:12000000
NA's
:1
NA's
:1
NA's
:3539
Q08_C09
Q08_C10
Q08_C11A
Q08_C11B
Min.
:1.000Min.
:1.000Min.
: 1.000
Min.
:2010
1st Qu.:2.000
1st Qu.:1.000
1st Qu.: 2.000
1st Qu.:2011
Median :2.000
Median :3.000
Median : 4.000
Median :2012
Mean:1.964Mean:2.357Mean: 4.543Mean:2012
3rd Qu.:2.000
3rd Qu.:3.000
3rd Qu.: 5.500
3rd Qu.:2012Max.
:2.000Max.
:3.000Max.
:12.000
Max.
:2012
NA's
:3450
NA's
:3541
NA's
:3541
Q08_C12A
Q08_C12B
Q08_C13
Q08_C14Min.
: 1.000
Min.
:2011
Min.
:1.000Min.
:
0
1st Qu.: 3.000
1st Qu.:2011
1st Qu.:2.000
1st Qu.:0
Median : 4.000
Median :2012
Median :4.000
Median :37500
Mean: 5.133
Mean
:2012
Mean
:3.118Mean: 786140
3rd Qu.: 7.000
3rd Qu.:2012
3rd Qu.:4.000
3rd Qu.: 487500
Max.
:10.000
Max.
:2012
Max.
:4.000Max.
:12000000
NA's
:3546
NA's
:3546
NA's
:3542
NA's
:3462
Q08_C15
Q08_C16
Q08_C17
Q08_C18
Min.
:
0
Min.
:
0
Min.
:
0
Min.
:
0
1st Qu.: 102875
1st Qu.:0
1st Qu.:0
1st Qu.:0
Median : 400000
Median :0Median :0Median :0
Mean: 4546359
Mean: 3062272
Mean: 43843
Mean: 31100
3rd Qu.: 3375000
3rd Qu.: 630000
3rd Qu.: 20000
3rd Qu.:0Max.
:48000000
Max.
:40000000
Max.
:2360000
Max.
:1400000
NA's
:3466
NA's
:3495
NA's
:3455
NA's
:3456

Manual Cambodia CSES 2012 Version 2.0

70

Q08_C19
Min.
:
0
1st Qu.:0
Median :0
Mean: 1889194
3rd Qu.:0Max.
:48000000
NA's
:3514

EntryUser
Length:3576
Class :character
Mode :character

ChangeDate
Min.
:2012-02-21 19:42:00
1st Qu.:2012-05-11 23:22:45
Median :2012-12-14 23:28:30
Mean:2012-10-07 11:15:34
3rd Qu.:2013-02-18 19:06:00
Max.
:2013-03-27 19:21:00## 26 #### HHDurableGoods ##########
pkid
hhid
Q09_C03
Min.
:
1
Length:34809
Min.
:801.0
1st Qu.: 8723
Class :character
1st Qu.:804.0
Median :17441
Mode :character
Median :818.0
Mean:17456
Mean:832.5
3rd Qu.:26202
3rd Qu.:838.0
Max.
:34925
Max.
:893.0

Q09_C04Min.
: 0.000
1st Qu.: 1.000
Median : 1.000
Mean: 1.777
3rd Qu.: 2.000
Max.
:20.000

Q09_C05A
Q09_C05B
Q09_C05C
Q09_C05D
Min.
:1.00
Min.
:1.000Min.
:1.000Min.
:1.000
1st Qu.:1.00
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:1.000
Median :1.00
Median :1.000
Median :1.000
Median :1.000
Mean
:1.03
Mean
:1.011Mean:1.006Mean:1.002
3rd Qu.:1.00
3rd Qu.:1.000
3rd Qu.:1.000
3rd Qu.:1.000
Max.
:4.00
Max.
:4.000Max.
:4.000Max.
:3.000
NA's
:93
NA's
:22790NA's:28179NA's:30864
Q09_C06A
Q09_C06B
Q09_C07
Q09_C08Min.
:1.000Min.
: 1.000
Min.
:
1500
Min.
:
500
1st Qu.:1.000
1st Qu.: 1.000
1st Qu.:35000
1st Qu.:
30000
Median :1.000
Median : 1.000
Median :100000Median :70000
Mean:1.194Mean: 1.732
Mean:
970820Mean:
799477
3rd Qu.:1.000
3rd Qu.: 2.000
3rd Qu.:391000
3rd Qu.:220000Max.
:8.000Max.
:20.000
Max.
:120000000
Max.
:410000000
NA's:30170
NA's
:2300
NA's
:30170NA's:2300
EntryUser
ChangeDate
Length:34809
Min.
:2012-02-21 19:42:00
Class :character
1st Qu.:2012-05-17 23:32:00
Mode :character
Median :2012-12-17 20:20:00
Mean:2012-10-10 07:42:04
3rd Qu.:2013-02-15 19:12:00
Max.
:2013-03-27 18:45:00## 27 #### PersonMaternalHealth ##########
pkid
hhid
Q10_C01Min.
: 1.0
Length:1245
Min.
:1.00
1st Qu.: 313.0
Class :character
1st Qu.:1.00
Median : 639.0
Mode :character
Median :1.00
Mean: 637.4
Mean:1.02
3rd Qu.: 966.0
3rd Qu.:1.00
Max.
:1283.0
Max.
:3.00
Q10_C03Min.
: 2.000

Q10_C04Min.
:1.000

Q10_C05Min.
:1.000

Q10_C02Min.
: 1.000
1st Qu.: 2.000
Median : 2.000
Mean: 2.421
3rd Qu.: 2.000
Max.
:11.000
Q10_C06Min.
: 1.000

Manual Cambodia CSES 2012 Version 2.0

71

1st Qu.: 4.000
Median : 5.000
Mean: 5.066
3rd Qu.: 6.000
Max.
:15.000

1st Qu.:2.000
Median :2.000
Mean:1.9733rd Qu.:2.000
Max.
:8.000

1st Qu.:1.000
Median :1.000
Mean:1.099
3rd Qu.:1.000
Max.
:8.000

Q10_C07A
Min.
:1.000
1st Qu.:2.000
Median :3.000
Mean:2.492
3rd Qu.:3.000
Max.
:5.000

Q10_C07B
Q10_C07C
Min.
:1.000Min.
:2.000
1st Qu.:2.000
1st Qu.:3.000
Median :3.000
Median :3.000
Mean:3.362Mean:3.528
3rd Qu.:5.000
3rd Qu.:5.000
Max.
:7.000Max.
:5.000
NA's
:671
NA's
:1192
EntryUser
ChangeDate
Length:1245
Min.
:2012-02-21 19:43:00
Class :character
1st Qu.:2012-04-24 18:37:00
Mode :character
Median :2012-12-11 23:27:00
Mean:2012-09-26 10:24:22
3rd Qu.:2013-02-14 20:05:00
Max.
:2013-03-27 18:45:00

1st Qu.: 4.000
Median : 7.000
Mean: 5.691
3rd Qu.: 7.000
Max.
:14.000
Q10_C07DMin.
: NA
1st Qu.: NAMedian : NA
Mean
:NaN
3rd Qu.: NA
Max.
: NA
NA's
:1245
persidLength:1245
Class :character
Mode :character## 28 #### PersonHealthU2 ##########
pkid
hhid
Q11_C01Min.
: 1.0
Length:585
Min.
:1.000
1st Qu.:148.0
Class :character
1st Qu.:1.000
Median :296.0
Mode :character
Median :1.000
Mean:301.8Mean:1.031
3rd Qu.:457.0
3rd Qu.:1.000
Max.
:607.0Max.
:2.000
Q11_C03Min.
: 2.000
1st Qu.: 4.000
Median : 5.000
Mean: 5.182
3rd Qu.: 6.000
Max.
:14.000
NA's:1
Q11_C06B
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.697
3rd Qu.:2.000
Max.
:5.000NA's:496
Q11_C09Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.0533rd Qu.:1.000
Max.
:8.000

Q11_C04Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.009
3rd Qu.:1.000
Max.
:2.000NA's:2
Q11_C07Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.177
3rd Qu.:1.000
Max.
:2.000NA's:19
Q11_C10Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.995
3rd Qu.:2.000
Max.
:5.000

Q11_C05Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.021
3rd Qu.:1.000
Max.
:2.000NA's:7
Q11_C08A
Min.
:1.000
1st Qu.:1.000
Median :2.000
Mean:1.6843rd Qu.:2.000
Max.
:2.000NA's:19
Q11_C11Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.0143rd Qu.:1.000
Max.
:2.000

Q11_C02Min.
: 1.000
1st Qu.: 2.000
Median : 2.000
Mean: 2.548
3rd Qu.: 3.000
Max.
:11.000
NA's:14
Q11_C06A
Min.
: 0.000
1st Qu.: 0.000
Median : 0.000
Mean: 1.233
3rd Qu.: 2.000
Max.
:23.000
NA's:91
Q11_C08B
Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.321
3rd Qu.:2.000
Max.
:2.000
NA's:18
EntryUser
Length:585
Class :character
Mode :character

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NA's
:2
NA's
:21
ChangeDate
Min.
:2012-02-21 19:43:00
1st Qu.:2012-04-20 18:13:00
Median :2012-12-06 19:17:00
Mean:2012-09-18 23:37:13
3rd Qu.:2013-02-14 19:26:00
Max.
:2013-03-27 18:45:00

NA's
:22
PersidLength:585
Class :character
Mode :character## 29 #### PersonIllness ##########
pkid
hhid
Q13BC01
Min.
:
2
Length:17644
Min.
: 1.00
1st Qu.: 4447
Class :character
1st Qu.: 2.00
Median : 8880
Mode :character
Median : 3.00
Mean
: 8881
Mean: 3.16
3rd Qu.:13320
3rd Qu.: 4.00
Max.
:17745Max.
:15.00

PersidMother
Length:585
Class :character
Mode :character

Q13BC2AMin.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.815
3rd Qu.:2.000
Max.
:2.000

Q13BC2B
Q13BC03
Q13BC04
Q13BC05Min.
:1.000Min.
:1.000Min.
:1.000Min.
: 1.00
1st Qu.:2.000
1st Qu.:2.000
1st Qu.:2.000
1st Qu.: 5.00
Median :4.000
Median :2.000
Median :2.000
Median :10.00
Mean:3.502Mean:1.812Mean:2.163Mean:14.543rd Qu.:5.000
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:30.00
Max.
:5.000Max.
:2.000Max.
:3.000Max.
:30.00NA's:14390NA's:14385NA's:14385NA's:17440
Q13BC06
Q13BC07
Q13BC08
Q13BC9AMin.
:1.000Min.
:0.0000Min.
: 0.0000Min.
: 1.000
1st Qu.:1.000
1st Qu.:0.0000
1st Qu.: 0.0000
1st Qu.: 9.000
Median :1.000
Median :0.0000
Median : 0.0000
Median :10.000
Mean:1.079Mean:0.2095
Mean: 0.3623
Mean: 9.664
3rd Qu.:1.000
3rd Qu.:0.0000
3rd Qu.: 0.0000
3rd Qu.:11.000
Max.
:2.000Max.
:6.0000Max.
:15.0000Max.
:18.000
NA's:14385NA's:14424
Q13BC9B
Q13BC9C
Q13BC9D
Q13BC10Min.
: 1.00Min.
:1.000Min.
: 1.000
Min.
:0
1st Qu.: 9.00
1st Qu.:2.000
1st Qu.: 2.000
1st Qu.:0
Median :10.00
Median :2.000
Median : 4.000
Median :0
Mean:10.09Mean:1.941Mean: 5.879Mean:9673
3rd Qu.:13.00
3rd Qu.:2.000
3rd Qu.: 7.000
3rd Qu.:5000
Max.
:98.00Max.
:2.000Max.
:30.000
Max.
:1000000NA's:15810NA's:14440NA's:17462NA's:14436
Q13BC11
Q13BC12A
Q13BC12B
Q13BC12C
Min.
:
0
Min.
:1.000Min.
:1.000Min.
:2.000
1st Qu.:7000
1st Qu.:1.000
1st Qu.:2.000
1st Qu.:3.750
Median : 20000
Median :1.000
Median :2.000
Median :5.000
Mean: 87364
Mean:1.438Mean:3.013Mean:4.625
3rd Qu.: 70000
3rd Qu.:2.000
3rd Qu.:4.000
3rd Qu.:6.000
Max.
:12000000
Max.
:6.000Max.
:6.000Max.
:6.000NA's:14424NA's:14446NA's:17565NA's:17636
EntryUser
ChangeDate
persidLength:17644
Min.
:2012-02-21 19:43:00
Length:17644
Class :character
1st Qu.:2012-04-27 19:37:00
Class :character
Mode :character
Median :2012-12-14 00:53:00
Mode :character

Manual Cambodia CSES 2012 Version 2.0

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Mean
:2012-10-03 21:46:12
3rd Qu.:2013-02-18 18:01:00
Max.
:2013-03-27 18:46:00## 30 #### PersonDisability ##########
pkid
hhid
Q14_C01
Min.
:
1
Length:17644
Min.
: 1.00
1st Qu.: 4418
Class :character
1st Qu.: 2.00
Median : 8842
Mode :character
Median : 3.00
Mean
: 8842Mean: 3.16
3rd Qu.:13263
3rd Qu.: 4.00
Max.
:17684Max.
:15.00
Q14_C02B
Q14_C02C
Q14_C03A
Min.
:0.000Min.
:1.000Min.
:1.000
1st Qu.:2.000
1st Qu.:4.000
1st Qu.:2.000
Median :3.000
Median :5.000
Median :2.000
Mean:3.311Mean:4.771Mean:1.986
3rd Qu.:4.000
3rd Qu.:6.000
3rd Qu.:2.000
Max.
:8.000Max.
:9.000Max.
:3.000NA's:17480NA's:17609NA's:16884
Q14_C03C
Q14_C04A
Q14_C04B
Min.
:1.000Min.
: 1.00Min.
: 1.00
1st Qu.:2.000
1st Qu.: 4.00
1st Qu.: 4.00
Median :3.000
Median : 5.00
Median :14.00
Mean:2.429Mean:10.74Mean:11.343rd Qu.:3.000
3rd Qu.:18.00
3rd Qu.:18.00
Max.
:3.000Max.
:98.00Max.
:19.00NA's:17609NA's:16884NA's:17481
Q14_C05A
Q14_C05B
Q14_C05C
Min.
:1.00
Min.
:1.000Min.
:1.000
1st Qu.:4.00
1st Qu.:4.000
1st Qu.:5.000
Median :4.00
Median :5.000
Median :6.000
Mean
:4.17
Mean
:4.894Mean:5.516
3rd Qu.:5.00
3rd Qu.:6.000
3rd Qu.:6.000
Max.
:6.00
Max.
:6.000Max.
:6.000NA's:16884NA's:17436NA's:17580ChangeDate
PersidMin.
:2012-02-21 19:44:00
Length:17644
1st Qu.:2012-04-27 19:39:30
Class :character
Median :2012-12-13 19:56:00
Mode :characterMean:2012-10-03 21:59:39
3rd Qu.:2013-02-18 18:02:00
Max.
:2013-03-27 18:47:00

Q14_C02A
Min.
: 0.0000
1st Qu.: 0.0000
Median : 0.0000
Mean: 0.1128
3rd Qu.: 0.0000
Max.
:98.0000
Q14_C03B
Min.
:1.00
1st Qu.:2.00
Median :2.00
Mean
:2.11
3rd Qu.:3.00
Max.
:3.00
NA's
:17480
Q14_C04C
Min.
: 2.00
1st Qu.: 5.00
Median :13.00
Mean:11.09
3rd Qu.:18.00
Max.
:18.00NA's:17609
EntryUser
Length:17644
Class :character
Mode :character## 31 #### PersonEcoCurrent ##########
pkid
hhid
Q15_C01
Min.
:
1
Length:16086
Min.
: 1.000
1st Qu.: 4042
Class :character
1st Qu.: 2.000
Median : 8088
Mode :character
Median : 3.000
Mean: 8097Mean: 2.984
3rd Qu.:12162
3rd Qu.: 4.000

Q15_C02Min.
: 1.000
1st Qu.: 1.000
Median : 2.000
Mean: 2.143
3rd Qu.: 2.000

Manual Cambodia CSES 2012 Version 2.0

74

Max.

:16189Max.

:14.000

Max.

:11.000

Q15_C03Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.356
3rd Qu.:2.000
Max.
:2.000

Q15_C04
Q15_C05B
Q15_C06B
Min.
:1.000Length:16086
Length:16086
1st Qu.:2.000
Class :character
Class :character
Median :2.000
Mode :character
Mode :character
Mean:1.995
3rd Qu.:2.000
Max.
:2.000NA's:10356
Q15_C07
Q15_C08
Q15_C09
Q15_C10A
Min.
:1.000Min.
:1.000Min.
: 1.00Min.
: 1.0
1st Qu.:3.000
1st Qu.:1.000
1st Qu.:28.00
1st Qu.:20.0
Median :3.000
Median :3.000
Median :42.00
Median :26.0
Mean:3.005Mean:2.385Mean:41.08Mean:23.4
3rd Qu.:3.000
3rd Qu.:3.000
3rd Qu.:56.00
3rd Qu.:30.0
Max.
:8.000Max.
:5.000Max.
:90.00
Max.
:30.0
NA's
:5701
NA's
:5701
NA's
:5729
NA's
:5730
Q15_C10B
Q15_C10C
Q15_C10D
Q15_C11Min.
:1.000Min.
:1.000
Min.
:1.00
Min.
:0.000
1st Qu.:1.000
1st Qu.:1.000
1st Qu.:2.00
1st Qu.:0.000
Median :1.000
Median :1.000
Median :2.00
Median :0.000
Mean:1.413Mean:1.277
Mean
:1.98
Mean
:0.381
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:2.00
3rd Qu.:1.000
Max.
:2.000Max.
:2.000
Max.
:2.00
Max.
:3.000
NA's
:5703
NA's
:11815
NA's
:5730
NA's
:5702
Q15_C12B
Q15_C13B
Q15_C14
Q15_C15
Length:16086
Length:16086
Min.
:1.000Min.
:1.000Class :character
Class :character
1st Qu.:3.000
1st Qu.:3.000
Mode :character
Mode :character
Median :3.000
Median :3.000
Mean:2.997Mean:2.996
3rd Qu.:3.000
3rd Qu.:3.000
Max.
:5.000Max.
:4.000NA's:12894NA's:12894
Q15_C16
Q15_C17A
Q15_C17B
Q15_C17C
Min.
: 1.00Min.
: 1.00Min.
:1.000Min.
:1.000
1st Qu.: 7.00
1st Qu.:10.00
1st Qu.:1.000
1st Qu.:1.000
Median :14.00
Median :20.00
Median :1.000
Median :1.000
Mean:14.42Mean:18.87Mean:1.485Mean:1.4843rd Qu.:21.00
3rd Qu.:30.00
3rd Qu.:2.000
3rd Qu.:2.000
Max.
:77.00Max.
:30.00Max.
:2.000Max.
:2.000NA's:12894NA's:12894NA's:12898NA's:14575
Q15_C18A
Q15_C18B
Q15_C19
Q15_C20Min.
: 1.000
Min.
:1.000Min.
: 4.00Min.
:
0
1st Qu.: 3.000
1st Qu.:1.000
1st Qu.: 40.00
1st Qu.: 259000
Median : 5.000
Median :2.000
Median : 52.00
Median : 380000
Mean: 6.207Mean:1.601
Mean: 50.41Mean: 469360
3rd Qu.: 8.000
3rd Qu.:2.000
3rd Qu.: 62.00
3rd Qu.: 540000
Max.
:30.000
Max.
:2.000Max.
:126.00
Max.
:8000000NA's:15348NA's:15349NA's:12894NA's:12162
Q15_C21
Q15_C22A
Q15_C22B
Q15_C23Min.
:1.000Min.
: 2.00Min.
: 2.00Min.
:1.000
1st Qu.:3.000
1st Qu.: 8.00
1st Qu.:15.00
1st Qu.:1.000
Median :3.000
Median :14.00
Median :20.00
Median :1.000
Mean:2.923Mean:15.87Mean:23.46Mean:1.297
3rd Qu.:3.000
3rd Qu.:20.00
3rd Qu.:30.00
3rd Qu.:2.000

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75

Max.
:3.000Max.
:60.00Max.
:60.00
NA's
:5711
NA's
:15911NA's:15636
Q15_C24
Q15_C25
Q15_C26Min.
:1.000Min.
: 0.000
Min.
:1.000
1st Qu.:2.000
1st Qu.: 2.000
1st Qu.:2.000
Median :2.000
Median : 3.000
Median :2.000
Mean:1.987Mean: 3.769
Mean:1.997
3rd Qu.:2.000
3rd Qu.: 5.000
3rd Qu.:2.000
Max.
:3.000Max.
:12.000
Max.
:2.000NA's:15635NA's:15796NA's:10385
Q15_C27B
Q15_C27C
Q15_C28
Min.
:3.0
Min.
: NA
Min.
:1
1st Qu.:3.0
1st Qu.: NA
1st Qu.:1
Median :3.0
Median : NA
Median :1
Mean
:3.5
Mean
:NaN
Mean
:1
3rd Qu.:3.5
3rd Qu.: NA
3rd Qu.:1
Max.
:5.0
Max.
: NA
Max.
:1
NA's
:16082NA's:16086NA's:16071
Q15_C30
Q15_C31
Q15_C32
Min.
:1
Min.
:1.000Min.
: 0.000
1st Qu.:2
1st Qu.:7.000
1st Qu.: 2.000
Median :3
Median :7.000
Median : 7.000
Mean
:3
Mean
:6.997Mean: 9.661
3rd Qu.:3
3rd Qu.:7.000
3rd Qu.:12.000
Max.
:6
Max.
:9.000Max.
:48.000
NA's:16073NA's:10400NA's:16024
EntryUser
ChangeDate
Length:16086
Min.
:2012-02-21 19:45:00
Class :character
1st Qu.:2012-04-28 01:11:00
Mode :character
Median :2012-12-14 19:57:00
Mean:2012-10-04 21:48:55
3rd Qu.:2013-02-18 18:59:45
Max.
:2013-03-27 18:50:00

Max.
NA's

:2.000:15635
Q15_C27AMin.
:1.0
1st Qu.:2.5
Median :3.0
Mean
:2.8
3rd Qu.:3.0
Max.
:5.0
NA's
:16071
Q15_C29Min.
:40.00
1st Qu.:48.50
Median :56.00
Mean:51.933rd Qu.:56.00
Max.
:56.00NA's:16071
Q15_C33Min.
:1.000
1st Qu.:1.000
Median :2.000
Mean:1.518
3rd Qu.:2.000
Max.
:2.000NA's:16030
PersidLength:16086
Class :character
Mode :character## 32 #### PersonviolenceA ##########
pkid
hhid
Q17AC01
Min.
:
1
Length:17588
Min.
: 1.000
1st Qu.: 4408
Class :character
1st Qu.: 2.000
Median : 8808
Mode :character
Median : 3.000
Mean: 8815Mean: 3.157
3rd Qu.:13217
3rd Qu.: 4.000
Max.
:17646Max.
:15.000
Q17AC03
EntryUser
Min.
:1.000Length:17588
1st Qu.:1.000
Class :character
Median :1.000
Mode :character
Mean:1.659
3rd Qu.:2.000
Max.
:5.000NA's:17544
persidLength:17588
Class :character

Q17AC02Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.997
3rd Qu.:2.000
Max.
:2.000ChangeDate
Min.
:2012-02-21 19:46:00
1st Qu.:2012-04-27 19:32:00
Median :2012-12-14 00:59:00
Mean:2012-10-03 19:57:06
3rd Qu.:2013-02-18 18:12:30
Max.
:2013-03-27 18:50:00

Manual Cambodia CSES 2012 Version 2.0

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Mode

:character## 33 #### PersonViolenceB ##########
pkid
hhid
Q17BC01Min.
: 1.00Length:44
Min.
:1.000
1st Qu.:20.75
Class :character
1st Qu.:1.000
Median :31.50
Mode :character
Median :2.000
Mean:34.77Mean:2.295
3rd Qu.:56.25
3rd Qu.:3.000
Max.
:68.00Max.
:5.000
Q17BC03Min.
: 1.000
1st Qu.: 2.000
Median : 3.000
Mean: 3.864
3rd Qu.: 4.000
Max.
:11.000

Q17BC04Min.
:1.0
1st Qu.:1.0
Median :1.5
Mean
:1.5
3rd Qu.:2.0
Max.
:2.0

Q17BC08Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.7733rd Qu.:2.000
Max.
:2.000

Q17BC09Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.2733rd Qu.:1.000
Max.
:4.000ChangeDate
Min.
:2012-02-24 22:52:00
1st Qu.:2012-04-20 13:34:00
Median :2012-04-26 18:51:00
Mean:2012-07-10 04:59:01
3rd Qu.:2012-12-13 19:33:00
Max.
:2013-03-19 18:55:00

Q17BC05
Q17BC06Min.
:1.000Min.
:2
1st Qu.:1.000
1st Qu.:2
Median :1.000
Median :2
Mean:1.409Mean:2
3rd Qu.:1.750
3rd Qu.:2Max.
:3.000
Max.
:2
NA's
:22
NA's
:22
EntryUser
Length:44
Class :character
Mode :character

Q05AQ2Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.434

Q17BC07Min.
:1.000
1st Qu.:3.000
Median :3.000
Mean:2.795
3rd Qu.:3.000
Max.
:4.000persidLength:44
Class :character
Mode :character## 34 #### HHOtherInfo ##########
pkid
hhid
Min.
: 1.0
Length:3840
1st Qu.: 961.8
Class :character
Median :1921.5
Mode :character
Mean:1921.9
3rd Qu.:2882.2
Max.
:3845.0
Q05AQ1BMin.
:1.00
1st Qu.:1.00
Median :3.00
Mean
:2.98

Q17BC02Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.636
3rd Qu.:2.000
Max.
:3.000Q01BQ1Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.121
3rd Qu.:1.000
Max.
:2.000Q05AQ3Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.742Q05AQ1AMin.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.9743rd Qu.:2.000
Max.
:2.000Q05ANoteMin.
:0
1st Qu.:0
Median :0
Mean:0

Manual Cambodia CSES 2012 Version 2.0

77

3rd Qu.:4.00
3rd Qu.:2.000
3rd Qu.:2.000
3rd Qu.:0
Max.
:7.00
Max.
:2.000Max.
:7.000
Max.
:0
NA's
:3739
NA's
:1665
NA's
:1671
Q05BQ1
Q05BNote
Q05CNote
Q05DQ1Min.
:1.000Min.
:0e+00Min.
:0e+00Min.
:1.000
1st Qu.:1.000
1st Qu.:0e+00
1st Qu.:0e+00
1st Qu.:1.000
Median :1.000
Median :0e+00
Median :0e+00
Median :1.000
Mean:1.091Mean:5e-04Mean:5e-04Mean:1.195
3rd Qu.:1.000
3rd Qu.:0e+00
3rd Qu.:0e+00
3rd Qu.:1.000
Max.
:2.000Max.
:1e+00Max.
:1e+00Max.
:2.000
NA's
:1665
NA's
:1867
NA's
:1868
NA's
:1863
Q05DNote1
Q05D1Q1
Q05DNote2
Q05EQ1Min.
:0.000Min.
:1.000Min.
:0e+00Min.
:1.000
1st Qu.:0.000
1st Qu.:1.000
1st Qu.:0e+00
1st Qu.:1.000
Median :0.000
Median :1.000
Median :0e+00
Median :1.000
Mean:0.001Mean:1.362Mean:5e-04Mean:1.462
3rd Qu.:0.000
3rd Qu.:2.000
3rd Qu.:0e+00
3rd Qu.:2.000
Max.
:1.000Max.
:2.000Max.
:1e+00Max.
:2.000
NA's
:1867
NA's
:1863
NA's
:1869
Q05ENote1
Q05ENote2
Q05FQ1Q05FQ2Min.
:0Min.
:0.000000
Min.
:1.000Min.
:1.000
1st Qu.:0
1st Qu.:0.000000
1st Qu.:2.000
1st Qu.:2.000
Median :0
Median :0.000000
Median :2.000
Median :2.000
Mean
:0
Mean
:0.000262
Mean:1.988Mean:1.979
3rd Qu.:0
3rd Qu.:0.000000
3rd Qu.:2.000
3rd Qu.:2.000
Max.
:0
Max.
:1.000000
Max.
:2.000Max.
:2.000
NA's
:24
NA's
:24
Q05FNote1
Q05FQ3
Q05FNote2
Q05FNote3Min.
:0.000000
Min.
:1.000Min.
:0.000000
Min.
:0
1st Qu.:0.000000
1st Qu.:1.000
1st Qu.:0.000000
1st Qu.:0
Median :0.000000
Median :2.000
Median :0.000000
Median :0
Mean:0.000786
Mean:1.546Mean:0.000524
Mean:0
3rd Qu.:0.000000
3rd Qu.:2.000
3rd Qu.:0.000000
3rd Qu.:0
Max.
:1.000000
Max.
:2.000Max.
:1.000000
Max.
:0
NA's
:25
NA's
:23
NA's
:23
Q05GQ1
Q05GQ2Q05GNote1
Q05GNote2
Q05HQ1
Min.
:1.00
Min.
:1.000
Min.
:0
Min.
:0
Min.
:1.000
1st Qu.:1.00
1st Qu.:1.000
1st Qu.:0
1st Qu.:0
1st Qu.:1.000
Median :1.00
Median :1.000
Median :0
Median :0
Median :2.000
Mean
:1.41
Mean
:1.441
Mean
:0
Mean
:0
Mean
:1.6243rd Qu.:2.00
3rd Qu.:2.000
3rd Qu.:0
3rd Qu.:0
3rd Qu.:2.000
Max.
:2.00
Max.
:2.000
Max.
:0
Max.
:0
Max.
:2.000
NA's
:23
NA's
:24
Q05HNote1
Q05HNote2
Q05HNote3
Q06_Q1
Q08_Q1
Min.
:0
Min.
:0
Min.
:0
Min.
:1.000Min.
:1.000
1st Qu.:0
1st Qu.:0
1st Qu.:0
1st Qu.:1.000
1st Qu.:1.000
Median :0
Median :0
Median :0
Median :2.000
Median :1.000
Mean
:0
Mean
:0
Mean
:0
Mean
:1.659Mean:1.079
3rd Qu.:0
3rd Qu.:0
3rd Qu.:0
3rd Qu.:2.000
3rd Qu.:1.000
Max.
:0
Max.
:0
Max.
:0
Max.
:2.000Max.
:2.000
NA's
:23
NA's
:22
NA's
:25
Q10_Q1
Q11_Q1Q13AQ1Q13AQ2AMin.
:1.000Min.
:1.000Min.
:1.000Min.
:1.000
1st Qu.:1.000
1st Qu.:2.000
1st Qu.:2.000
1st Qu.:1.000
Median :2.000
Median :2.000
Median :2.000
Median :1.000
Mean:1.678Mean:1.853Mean:1.892Mean:1.555Manual Cambodia CSES 2012 Version 2.0

78

3rd Qu.:2.000
Max.
:2.000

3rd Qu.:2.000
Max.
:2.000

3rd Qu.:2.000
Max.
:2.000Q13AQ2BMin.
:1.000
1st Qu.:2.000
Median :2.000
Mean:2.738
3rd Qu.:3.000
Max.
:8.000
NA's:3649
Q17AQ1Min.
:1.000
1st Qu.:1.000
Median :1.000
Mean:1.138
3rd Qu.:1.000
Max.
:2.000Q13AQ2CMin.
:3.000
1st Qu.:3.000
Median :4.000
Mean:4.009
3rd Qu.:4.000
Max.
:6.000
NA's:3725
Q17AQ2Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.959
3rd Qu.:2.000
Max.
:2.000Q13AQ3Min.
:1.000
1st Qu.:1.000
Median :2.000
Mean:2.632
3rd Qu.:3.000
Max.
:8.000
NA's:3424
Q17AQ3Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.936
3rd Qu.:2.000
Max.
:2.000

3rd Qu.:2.000
Max.
:8.000
NA's:3424
Q13AQ4Min.
:1.000
1st Qu.:2.000
Median :2.000
Mean:1.972
3rd Qu.:2.000
Max.
:8.000NA's:416
EntryUser
Length:3840
Class :character
Mode :character

ChangeDate
Min.
:2012-02-21 19:32:00
1st Qu.:2012-05-09 12:52:30
Median :2012-12-17 17:35:30
Mean:2012-10-06 05:38:36
3rd Qu.:2013-02-16 00:50:45
Max.
:2013-03-27 00:36:00## 35 #### PSUListing ##########
PSU
Province_Code
Length:384
Length:384
Class :character
Class :character
Mode :character
Mode :character

Province_Name
Length:384
Class :character
Mode :character

District_Code
Length:384
Class :character
Mode :character

District_Name
Length:384
Class :character
Mode :character

Commune_Name
Length:384
Class :character
Mode :character

Village_Code
Length:384
Class :character
Mode :character

Village_Name
Length:384
Class :character
Mode :character

Households
Min.
: 21.0
1st Qu.: 170.8
Median : 274.0
Mean: 517.7

Commune_Code
Length:384
Class :character
Mode :character

Enum_Areas
Selected_EA
UrbanRuralMin.
: 1.000Min.
: 1.000
Min.
:1.000
1st Qu.: 2.000
1st Qu.: 1.000
1st Qu.:1.000
Median : 3.000
Median : 2.000
Median :2.000
Mean: 4.219
Mean: 2.714Mean:1.625
3rd Qu.: 5.000
3rd Qu.: 3.000
3rd Qu.:2.000
Max.
:46.000Max.
:37.000
Max.
:2.000SurveyMonth
HouseholdsInVillage HouseholdsInListingMin.
: 1.00Min.
: 37.0Min.
: 28.00
1st Qu.: 3.75
1st Qu.: 179.2
1st Qu.: 69.00
Median : 6.50
Median : 274.5
Median : 88.00
Mean: 6.50Mean: 438.1
Mean: 90.99

Manual Cambodia CSES 2012 Version 2.0

79

3rd Qu.: 526.5
Max.
:4844.0

3rd Qu.: 9.25
Max.
:12.00

3rd Qu.: 515.2
Max.
:6129.0

3rd Qu.:107.00
Max.
:268.00## 36 #### weighthouseholds ##########PSU
HHID
urbrurLength:3840
Length:3840
Length:3840
Class :character
Class :character
Class :character
Mode :character
Mode :character
Mode :character

Poststratum
Length:3840
Class :character
Mode :characterhhsizeMin.
: 1.000
1st Qu.: 3.000
Median : 4.000
Mean: 4.595
3rd Qu.: 6.000
Max.
:15.000

hw12a
Min.
: 101.2
1st Qu.: 485.2
Median : 907.8
Mean: 802.7
3rd Qu.:1054.1
Max.
:2214.3## 37 #### weightpersons ##########
PersID
PSU
Length:17644
Length:17644
Class :character
Class :character
Mode :character
Mode :character

StratumLength:17644
Class :character
Mode :character

Poststratum
Length:17644
Class :character
Mode :character

StratumLength:3840
Class :character
Mode :character

HHID
Length:17644
Class :character
Mode :character

hw12a
Min.
: 101.2
1st Qu.: 488.4
Median : 909.9
Mean: 809.0
3rd Qu.:1055.9
Max.
:2214.3

urbrurLength:17644
Class :character
Mode :character

pw12a
Min.
: 85.4
1st Qu.: 504.0
Median : 906.4
Mean: 814.8
3rd Qu.:1064.6
Max.
:2396.9

Manual Cambodia CSES 2012 Version 2.0

80

5.2 Frequency of categoriacal variables# Displayed frequency table of categorical variables> # file names: Rnames[j](j=1 to 37)> # file list: outfiles[[j]]> # description of variable names: var.names[[j]] : none
> # list of column numbers of categorical variables> ck<-list() # Numbers of categorical variables> ck[[1]]<- c(3:6)> ck[[2]]<- c(3:4,9:19)> ck[[3]]<- c(3)> ck[[4]]<- c(3)> ck[[5]]<- c(3:18)> ck[[6]]<-c(3:18)> ck[[7]]<- c(3,5:10,12:14,16,18:20,23:30,33:37,46)> ck[[8]]<- c(3,5,7:8,10:11,13:15,17,20:31,33,35)> ck[[9]]<- c(3:5)> ck[[10]]<- c(3:5)> ck[[11]]<-c(3)> ck[[12]]<- c(3)> ck[[13]]<- c(3:4)> ck[[14]]<- c(3)> ck[[15]]<- c(3:4)> ck[[16]]<- c(3)> ck[[17]]<- c(3)> ck[[18]]<- c(3)> ck[[19]]<- c(3)> ck[[20]]<- c(3,5:13)> ck[[21]]<- c(3)> ck[[22]]<- c(3)> ck[[23]]<- c(3,6,7)> ck[[24]]<- c(3)> ck[[25]]<- c(3:6,11,13:14,19)> ck[[26]]<- c(4:8)> ck[[27]]<- c(3:12)> ck[[28]]<- c(3:7,10:15)> ck[[29]]<- c(3:7,9:14,18:20)> ck[[30]]<- c(3:15)> ck[[31]]<- c(3:6,9:10,13:16,19:20,23:24,26,29,32:33,35:39,42,44)> ck[[32]]<- c(3:5)> ck[[33]]<- c(3:11)> ck[[34]]<- c(3:45)> ck[[35]]<- c(2,12,14)> ck[[36]]<- c(3:6)> ck[[37]]<- c(4:6)>> for(j in 1:length(ck)){+ if(length(ck[[j]])==0) {next}+ cat("\n\n##",j,"#### Frequency of variables in",Rnames[j]," ###################\n\n")+ for(k in ck[[j]]){+ variable.name<-colnames(outfiles[[j]])[k]+ cat("---",k, ":",variable.name)+ print(addmargins(table(outfiles[[j]][k],useNA="ifany")))+ }Manual Cambodia CSES 2012 Version 2.0

81

+ }

## 1 #### Frequency of variables in Households--- 3 : HHnumber
01
02 03
04
384 384 384 384--- 4 : Males01
2
3
224 925 1332 816--- 5 : Females
01
2
3
25 872 1418 922--- 6 : Total
12
3
4
88 307 683 897###################

05
384

06
384

07
384

08
384

09
384

10 Sum384 3840

4
380

5
115

6
30

7
11

8
6

9 Sum
1 3840

4
383

5
148

6
56

7
12

8 Sum
4 3840

5
826

6
562

7
237

8
124

9
58

10
31

## 2 #### Frequency of variables in HHMembers--- 3 : Q01AC01
12343840 3752 3445 2762
14
15
Sum
4
1 17644--- 4 : Q01AC03
12Sum8448 9196 17644--- 9 : Q01AC06
12343840 3000 8345
36
14
15
Sum
3
8 17644--- 10 : Q01AC07
1
2
3
4
6933
326
158
157
14 <NA>Sum
2 9759 17644--- 11 : Q01AC0801
2
32 1397 7050
392
Sum
17644
--- 12 : Q01AC09
1
2
3
4
7274
246 1072 4616--- 13 : Q01AC100123
1 2977 3144
397
13
14 <NA>Sum
42 10434 17644--- 14 : Q01AC11A
1
2
3
4

11
16

12
4

13
3

14
3

15 Sum
1 3840###################

5
1865

6
1039

7
477

8
240

9
116

10
58

11
27

12
11

13
7

5
19

6
132

7
101

8
1125

9
120

10
584

11
75

12
170

13
86

5
75

6
81

7
64

8
45

9
15

10
12

11
5

12
6

13
6

4
122

5
116

6
97

7
43

8
35

9
23

10
3

11
2

<NA>
8362

8
44

9
25

10
16

11
9

12
3

<NA>
Sum
4436 17644
4
238

5
155

6
115

7
80

5

8

<NA>

Sum

Manual Cambodia CSES 2012 Version 2.0

82

17114
272
154
6
--- 15 : Q01AC11B
12 <NA>
Sum
17549
64
31 17644--- 16 : Q01AC12A
0
1
2
3
15564
166 1010
126--- 17 : Q01AC12B
0
1
2
3
1166
14
66
35
--- 18 : Q01AC12C
0
1
4
5
71
3
1
2
--- 19 : Q01AC13
1
2 <NA>
Sum
16810
833
1 1764480

1

17 17644

4
132

5
149

6
46

7
203

8
229

4
5

5
26

6
5

7
1

8
2

9
2

9 <NA>
Sum
10 16314 17644

9 <NA>
Sum
2 17565 17644## 3 #### Frequency of variables in HHFoodConsumption--- 3 : Q01BC01
12
33828 2542 3819
1415
163822 2020 2049

4
3622
17
2077

5
3221
18
2055

6
2168
19
2488

7
3808
20
2989

###################

893830 1758
21
Sum
1632 57784

10
2058

## 4 #### Frequency of variables in HHRecallNonFood--- 3 : Q01CC01
1
2
3
2766 3293 3412
1415
161080 3832
884

4
53829 3699
17
Sum
2299 40135

6
3717

7
848

8
2883

5
4

6
4

7
1

8
9

12
11

11
2586

12
3321

13
2091

###################

9890## 5 #### Frequency of variables in HHVulnerability--- 3 : Q01DQ1
1
2
3
4 Sum
3291 525
7
20 3843--- 4 : Q01DQ2
1
2 Sum
3677 166 3843--- 5 : Q01DQ3
0
1
2
3
4
5
12 27
25
28
Sum
3843
--- 6 : Q01DQ4_1
0
1 <NA> Sum146
20 3677 3843--- 7 : Q01DQ4_2
0
1 <NA> Sum147
19 3677 3843--- 8 : Q01DQ4_3

<NA>
Sum
17 17644

10
2597

11
1955

12
962

13
1189

###################

16
15

20
11

24
7

Manual Cambodia CSES 2012 Version 2.028
432 <NA>
3 367783

0
1 <NA> Sum
152
14 3677 3843--- 9 : Q01DQ4_4
0
1 <NA> Sum
153
13 3677 3843--- 10 : Q01DQ4_5
0
1 <NA> Sum
153
13 3677 3843--- 11 : Q01DQ4_6
0
1 <NA> Sum141
25 3677 3843--- 12 : Q01DQ4_7
0
1 <NA> Sum
125
41 3677 3843--- 13 : Q01DQ4_8
0
1 <NA> Sum
96
70 3677 3843--- 14 : Q01DQ4_9
0
1 <NA> Sum
62 104 3677 3843--- 15 : Q01DQ4_10
0
1 <NA> Sum
58 108 3677 3843--- 16 : Q01DQ4_11
0
1 <NA> Sum
99
67 3677 3843--- 17 : Q01DQ4_12
0
1 <NA> Sum
114
52 3677 3843--- 18 : Q01DQ5
1
2
3 <NA> Sum78
8 80 3677 3843## 6 #### Frequency of variables in PersonEducation--- 3 : Q02C01
12
343840 3748 3290 2538
14
15
Sum
3
1 16754--- 4 : Q02C1b
1
2
3
4
5946 6779 1754 1041
Sum
16754
--- 5 : Q02C02
1
Sum16754 16754--- 6 : Q02C03
1
2 <NA>
Sum
12286 4465
3 16754--- 7 : Q02C04
1
2 <NA>
Sum
13787 2964
3 16754--- 8 : Q02C05###################

5
1670

6
896

7
408

8
192

9
94

10
45

11
17

12
6

13
6

5
654

6
331

7
142

8
51

9
32

10
7

11
3

14
1

<NA>
13

Manual Cambodia CSES 2012 Version 2.0

84

0
1
2
3
4
5
6
7
260
817
971 1376 1512 1547 1237 1380
13
14
15
16
17
18
19
20
78
154
90
358
27
27
2
3
--- 9 : Q02C06
0
1
2
3
4
5
6
7
238
630
972 1352 1516 1530 1229 1350
13
14
15
16
17
18
19
20
382
703
50
30
47
377
15
5
--- 10 : Q02C07
1
2 <NA>
Sum
4253 9529 2972 16754--- 11 : Q02C08
0
1
2
3
4
5
6
7
120
412
515
462
462
376
356
253
15
16
17
21 <NA>Sum
76329
10 12499 16754--- 12 : Q02C09
1
2 <NA>
Sum
3981
274 12499 16754--- 13 : Q02C10
1
2 <NA>
Sum
1177 3078 12499 16754--- 14 : Q02C11
1
2
3
4
6
7
8
9
144
69
20
5
230
60
88
14
--- 15 : Q02C121
2
Sum
820 15934 16754--- 16 : Q02C13
1
2 <NA>
Sum591
228 15935 16754--- 17 : Q02C14
1
2
3
4
5
6 <NA>
Sum
4
43
6
483
42
7 16169 16754--- 18 : Q02C15
1
2 <NA>
Sum
4132 12621
1 16754## 7 #### Frequency of variables in HHHousing--- 3 : Q04_01
12
343709 106 175--- 5 : Q04_03
12
342501 933 261
88--- 6 : Q04_04
1
2
3
4805 1777 20 899--- 7 : Q04_05
12
3
4289 882 338 2021--- 8 : Q04_06
1
2
3
4

8
9
1059 1027<NA>Sum
2968 16754

10
622

11
441

12
798

8
1060
88
290

9
10
717
577
<NA>
Sum
2967 16754

11
425

12
292

8
219

9
210

10
161

11
159

12
198

10
12

11
975

12 <NA>Sum
7 15130 16754###################

5
1

6
1

7
1

9 Sum
1 3841

5
41

6
9

7
4

8
2

11
1

5
298

6
5

7
23

8
8

9 Sum
6 3841

5
4

6
14

7
4

8
286

9 Sum
3 3841568912 Sum
1 3841

Sum

Manual Cambodia CSES 2012 Version 2.0

85

217 1739 766 419
92 687
2 3841--- 9 : Q04_07
1
2
3
4
5
7
8 Sum
2013
37 1128 594
521
43 3841--- 10 : Q04_08
1
2
3
4
5
6
7
8
9
10
11
12
1199
1 707 158 383 260 117
14 848 103
935--- 12 : Q04_10M1
1
2
3
4
5
6
7
8
9 <NA> Sum
1200 204 101
22
11
7
5
4
1 2286 3841--- 13 : Q04_10M2
1
2
3
4
5
6
7
8
9 <NA> Sum
60 959 204
81
38
13
5
2
3 2476 3841--- 14 : Q04_10M3
1
2
3
4
5
6
7
8
9 <NA> Sum36
15 358 124
49
19
11
4
1 3224 3841--- 16 : Q04_12
1
2
3
4
5
6
7
8
9
10
11
12
1217
6 917 182 474 482 173
567 2531545--- 18 : Q04_14M1
1
2
3
4
5
6
7
8
10 <NA> Sum
1631 272 147
35
15
14
6
5
1 1715 3841--- 19 : Q04_14M2
1
2
3
4
5
6
7
8
9
14 <NA> Sum
90 1279 268 111
50
11
10
1
5
1 2015 3841--- 20 : Q04_14M3
1
2
3
4
5
6
7
8
9 <NA> Sum41
24 440 168
59
30
16
6
1 3056 3841--- 23 : Q04_17
1
2
3 Sum
2853 333 655 3841--- 24 : Q04_18A
1
2 <NA> Sum
2781 405 655 3841--- 25 : Q04_18B
1
2 <NA> Sum
613 2573 655 3841--- 26 : Q04_18C
1
2 <NA> Sum
8 3178 655 3841--- 27 : Q04_18D
12 <NA> Sum
2 3184 655 3841--- 28 : Q04_18E
12 <NA> Sum
38 3148 655 3841--- 29 : Q04_19A
1
2
3
4
5
6
7
8 Sum
739 1299 41
3620
29 1676
1 3841--- 30 : Q04_19B
12
3
4 <NA> Sum
2074 105 1644
15
3 3841--- 33 : Q04_22A
1
2
3
5
7
8 Sum
2554 409 836
30
1
11 3841--- 34 : Q04_22B

13 <NA> Sum
5
2 384113 Sum
5 3841

Manual Cambodia CSES 2012 Version 2.0

861
2 <NA> Sum
820 2143 878 3841--- 35 : Q04_22C1
1
2
3
4
5
6
1649 306 11938
910--- 36 : Q04_22C2
1
2
3
4
5
6
74 1117 256 120
53
18--- 37 : Q04_22C3
1
2
3
4
5
6
15
22 319 131
62
26--- 46 : Q04_24
12
34 <NA> Sum
3532 143 155
29 384176859 <NA> Sum
1 1698 3841

7
10

8
3

9
2

10 <NA> Sum
1 2187 3841

7
12

8
3

9
3

13 <NA> Sum
1 3247 3841## 8 #### Frequency of variables in HHLandOwnership--- 3 : Q05AC01
1
2
3
4
5
2169 1070 356 110
42--- 5 : Q05AC03
1
2
3
4 Sum
3351 239 142
49 3781--- 7 : Q05AC04B
1
2
3 <NA> Sum
2032 1357 10 382 3781--- 8 : Q05AC04C
1
2
3 <NA> Sum
31 1732 1616 402 3781--- 10 : Q05AC05B
1
2 <NA> Sum
110 129 3542 3781--- 11 : Q05AC05C
2
3 <NA> Sum
109 130 3542 3781--- 13 : Q05AC06B
12 <NA> Sum
78
64 3639 3781--- 14 : Q05AC06C
2
3 <NA> Sum
76
66 3639 3781--- 15 : Q05AC07
1
2
3
5
6
2527 441 231 350 144--- 17 : Q05AC09
1
2
3
4
5
1326 1415 168 449 247--- 20 : Q05AC12
1
2
3
4 Sum
2258 1407 40
76 3781--- 21 : Q05AC13A
1
2
3
4
5
274
15 643 1301
18--- 22 : Q05AC13B
1
2
3
4
5

6
21

7
12

13 Sum
1 3781

7
2

8
9

9
69

6
17

7
143

###################

10 <NA> Sum3
5 3781

8 Sum
16 37816
4

7 <NA> Sum
3 1523 3781

6

8 <NA>

Sum

Manual Cambodia CSES 2012 Version 2.0

87

216
16 599 1022
19
6 380 1523 3781--- 23 : Q05AC14
1
2
3
4
5
6
7 <NA> Sum
593 361 1188
81
22
6
4 1526 3781--- 24 : Q05AC15
1
2
3
4
5
6
7
8
9
3235 277 16
20
7
5
3
1
2
--- 25 : Q05AC16A
1
2
3
4
5
6 <NA> Sum
2954 428 167
29 15728
18 3781--- 26 : Q05AC16B
12
34 <NA> Sum
430
6
11 3730 3781--- 27 : Q05AC16C<NA> Sum
3781 3781--- 28 : Q05AC17
1
2
3
4 Sum
1217 415 297 1852 3781--- 29 : Q05AC18A
1
2
3
4
5
6
7
8 Sum
3459 113 138
7
5
14
39
6 3781--- 30 : Q05AC18B
2 <NA> Sum
1 3780 3781--- 31 : Q05AC18C<NA> Sum
3781 3781--- 33 : Q05AC20
1
2 Sum
3437 344 3781--- 35 : Q05AC22
1
2
3 Sum
14
54 3713 3781

10
1

11
3

## 9 #### Frequency of variables in HHProductionCrops--- 3 : WetDry
1
2 Sum
3057 979 4036--- 4 : Q05BC01
12
3
42482 1063 313 102--- 5 : Q05BC02
12
3
42291 1176 375 115

5
39

6
21

7
10

8
3

9
2

5
42

6
18

7
11

10 Sum
8 4036

77
60

4

5

6

7

8

9

99 Sum
1 3781###################

10 Sum
1 4036## 10 #### Frequency of variables in HHCostCultivationCrops--- 3 : WetDry
1
2 Sum
3049 985 4034--- 4 : Q05CC01
1
2
3

88
150

10

###################

Sum

Manual Cambodia CSES 2012 Version 2.0

882476 1064 316 102--- 5 : Q05CC0212342320 1159 373 113

39

20

10

3

5
40

6
18

7 Sum
11 40342

2 4034## 11 #### Frequency of variables in HHInventoryCrops--- 3 : Q05DC01
12
3
1592 274 41###################

4 Sum
9 1916## 12 #### Frequency of variables in HHSalesCrops--- 3 : Q05D1C1
1
2
31257 291 62

413###################

5 Sum
2 1625## 13 #### Frequency of variables in HHLivestock1--- 3 : Q05E1C01
12
32062 2059 2059--- 4 : Q05E1C03
1
2
Sum3872 16654 20526

4
2060

5
2058

6
2057

7
2061

8
2041

###################

92037## 14 #### Frequency of variables in HHLivestock2--- 3 : Q05E2C01
12341024 1788 105 761

5
126

10
Sum
2032 20526###################

6 Sum
94 3898## 15 #### Frequency of variables in HHFishCultivation1###################--- 3 : Q05F1C01
1
2 Sum
81
1 82
--- 4 : Q05F1C02
1
3 5 Sum80
1 1 82## 16 #### Frequency of variables in HHFishCultivation2###################--- 3 : Q05F2C01
1
2
3
4
5
99
90 60
65 171212 Sum91 2614

6
139

7
115

8
62

9
58

10
61

11
62

## 17 #### Frequency of variables in HHFishCultivation3###################

Manual Cambodia CSES 2012 Version 2.0

89--- 3 : Q05F3C011
2
3
4493 1741 781 366

5
114

6
81

7 Sum
107 3683## 18 #### Frequency of variables in HHForestryHunting1--- 3 : Q05G1C01
12
3
4
133 2225 106 532

5
6114 2116

7
254

8
103

9
189

10 Sum79 5851## 19 #### Frequency of variables in HHForestryHunting2--- 3 : Q05G2C01
1
2
3
4
5
1004 754 709 707 2060

6716###################

7 Sum
695 6645## 20 #### Frequency of variables in HHNonAgriculture1--- 3 : Q05H1C01
1
2
3
4 Sum
1442 237 18
6 1703--- 5 : Q05H1C05
1
2
3
4
5
884 591 123
45
25--- 6 : Q05H1C06A
1
2
3
4
5
200 363 1428135--- 7 : Q05H1C06B
1
2
3
4
5
19
8 92
44
29
--- 8 : Q05H1C06C
1
3
4
5
6
4
3 30
12
8
--- 9 : Q05H1C06D
1
3
5
6
7
1
1
9
4
1
--- 10 : Q05H1C06E
6
8 <NA> Sum
1
2 1700 1703--- 11 : Q05H1C06F
7 <NA> Sum
1 1702 1703--- 12 : Q05H1C06G<NA> Sum
1703 1703--- 13 : Q05H1C06H<NA> Sum
1703 1703###################

6
14

7
10

8
2

9
2

10
1

6
18

7
12

8
3

10 <NA> Sum
2 847 1703

6
17

7
2

8
1

9
4

7
6

9 <NA> Sum
1 1639 1703

91

11 <NA> Sum
1 1685 1703###################

14 <NA> Sum
1
5 170312 <NA> Sum
1 1486 1703## 21 #### Frequency of variables in HHNonAgriculture2###################--- 3 : Q05H2C01

Manual Cambodia CSES 2012 Version 2.0

90

1
116
17
534

2
291
18
716

3
41
19
132

4
717
20
50

5
6
694 877
21 Sum
66 7418

7
84

8
406

9
407

10
958

11
448

## 22 #### Frequency of variables in HHNonAgriculture3

1231--- 3 : Q05H3C01
1
2
3
4
5
169
85 27632 8461718 19
20 Sum26
27 25
29 2604

6
32

7
94

8
276

9
469

10
27

## 23 #### Frequency of variables in HHLiabilities--- 3 : Q06_C01
1
2
3
4
1307
45
9
3
--- 6 : Q06_C04
1
2
3
4
218
6 69 249--- 7 : Q06_C05
1
2
3
4370 205 416 137

13
30

14
601

15
46

16
173

11
58

###################

12
24

13
30

14
28

15
26

###################

16
25

5 Sum
1 1365
5
10

6
1

7
2

8
375

9
418

10 Sum17 1365

5
1

6
37

7
94

8
52

9
43

10 Sum
10 1365## 24 #### Frequency of variables in HHIncomeOtherSource###################--- 3 : Q07_C01
1
2
3
195 1273 99

12
95

4
92

5
162

6
101

7
83

8
76

9
91

10
11
207 1489## 25 #### Frequency of variables in HHConstruction

1383

14 Sum174 4220###################--- 3 : Q08_C01
1
2
3 Sum
3538
37
1 3576--- 4 : Q08_C02A
1
2
3 <NA> Sum
3519
3 44
10 3576--- 5 : Q08_C02B
1
2
3 <NA> Sum
1
1 150 3424 3576--- 6 : Q08_C02C<NA> Sum
3576 3576--- 11 : Q08_C07
1
2 Sum
37 3539 3576--- 13 : Q08_C09
1
2 Sum
127 3449 3576--- 14 : Q08_C10

Manual Cambodia CSES 2012 Version 2.0

91

1
2
3 <NA> Sum35
11 80 3450 3576--- 19 : Q08_C13
12
34 <NA> Sum
2
112
19 3542 3576## 26 #### Frequency of variables in HHDurableGoods--- 4 : Q09_C04
0
1
2
3
4
5
64 22708 5387 2676 1924
961
13
14
15
16
17
18
3
1
5
3
1
1
--- 5 : Q09_C05A
1
2
3
4 <NA>
Sum
34202
18
467
29
93 34809--- 6 : Q09_C05B
12
3
4 <NA>
Sum
11950
6
57
6 22790 34809--- 7 : Q09_C05C
1
2
3
4 <NA>
Sum
6611
2
15
2 28179 34809--- 8 : Q09_C05D
1
2
3 <NA>
Sum
3940
1
4 30864 34809

6
7
515
267
20
Sum
3 34809###################

8
139

9
53

## 27 #### Frequency of variables in PersonMaternalHealth1078--- 3 : Q10_C01
1
2
3 Sum
1222
21
2 1245--- 4 : Q10_C02
1
2
3
452 891 187
45--- 5 : Q10_C03
23455 235 306 284--- 6 : Q10_C04
1
2
8 Sum
58 1183
4 1245--- 7 : Q10_C05
1
2
8 Sum
1152
88
5 1245--- 8 : Q10_C06
1
2
3
4
215
22
4 141
--- 9 : Q10_C07A
1
2
3
4
306 140 681 117--- 10 : Q10_C07B
12
3
4
58 127 162
7--- 11 : Q10_C07C
2
35 <NA>

118###################

5
36

6
9

7
10

8
5

9
7

10
1

11 Sum
2 1245

6
201

7
94

8
59

9
28

10
16

11
10

12
4

13
1

14
1

15 Sum
1 1245

5
121

6
73

7
550

8
5

9
1

10
1

11
56

12
50

13
2

14 Sum
4 12455 Sum
1 1245
5
218

12
12

7 <NA> Sum
2 671 1245

Sum

Manual Cambodia CSES 2012 Version 2.0

9212
21 20 1192 1245--- 12 : Q10_C07D<NA> Sum
1245 1245## 28 #### Frequency of variables in PersonHealthU2--- 3 : Q11_C01
1
2 Sum
567 18 585--- 4 : Q11_C02
1
2
3
4
24 384 93
28--- 5 : Q11_C03
2
3
4
5
3 101 147 126--- 6 : Q11_C04
1
2 <NA> Sum
578
5
2 585
--- 7 : Q11_C05
1
2 <NA> Sum
566
12
7 585
--- 10 : Q11_C07
1
2 <NA> Sum
466 100 19 585--- 11 : Q11_C08A
1
2 <NA> Sum
179 387 19 585--- 12 : Q11_C08B
1
2 <NA> Sum
385 182 18 585--- 13 : Q11_C09
1
28 <NA>
564
17
2
2--- 14 : Q11_C10
12
34
87 412 50
11--- 15 : Q11_C11
12 <NA> Sum
555
8 22 585

5
19

6
7

7
6

8
2

9
5

10
1

11 <NA>
2
14

Sum
585

6
90

7
47

8
35

9
15

10
12

11
4

12
2

14 <NA>1
1

5 <NA>
4
21

Sum
585

13
1

Sum
585

Sum
585

## 29 #### Frequency of variables in PersonIllness--- 3 : Q13BC01
1233840 3752 3445
14
15
Sum
4
1 17644--- 4 : Q13BC2A
1
2
Sum
3259 14385 17644--- 5 : Q13BC2B
1
2
3
703
230
148

###################

4
2762

5
1865

6
1039

7
477

4
1078

5 <NA>
Sum
1095 14390 17644

8240###################

9
116

10
58

Manual Cambodia CSES 2012 Version 2.0

11
27

12
11

13
7

93

--- 6 : Q13BC03
1
2 <NA>
Sum
612 2647 14385 17644--- 7 : Q13BC04
1
2
3 <NA>
Sum
204 2321
734 14385 17644--- 9 : Q13BC06
1
2 <NA>
Sum3003
256 14385 17644--- 10 : Q13BC07
0
1
2
3
4
5
6
Sum
16867
30
13
20
25
654
35 17644--- 11 : Q13BC08
0
1
2
3
4
5
6
7
14424 1386 1011
527
191
67
17
5
Sum
17644
--- 12 : Q13BC9A
1
2
3
4
5
7
8
9
70
101
77
294
13
8
82
551
15
18 <NA>
Sum
16
20 14424 17644--- 13 : Q13BC9B
1
2
3
4
5
7
8
9
34
54
35
134
12
6
45
294
15
16
17
18
98 <NA>
Sum
17
1
1
16
1 15810 17644--- 14 : Q13BC9C
1
2 <NA>
Sum
188 3016 14440 17644--- 18 : Q13BC12A
1
2
3
4
5
6 <NA>
Sum
2188
801
125
20
30
34 14446 17644--- 19 : Q13BC12B
1
2
3
4
5
6 <NA>
Sum
1
41
16
4
11
6 17565 17644--- 20 : Q13BC12C
2
3
4
6 <NA>
Sum
1
1
2
4 17636 17644

8
2

10
11

12
1

14
1

15
1

10
819

11
435

12
8

13
132

14
594

10
491

11
191

12
3

13
90

14
409

## 30 #### Frequency of variables in PersonDisability--- 3 : Q14_C01
12
33840 3752 3445
14
15
Sum
4
1 17644--- 4 : Q14_C02A
0
1
2
16884
377
56
--- 5 : Q14_C02B
0
1
2
1
10
59
--- 6 : Q14_C02C
1
2
3###################

4
2762

5
1865

6
1039

7
477

8
240

9
116

10
58

11
27

3
25

4
227

5
42

6
23

7
3

8
3

9
3

98
Sum
1 17644

3
14

4
46

5
23

6
5

7
4

8 <NA>
Sum
2 17480 17644

4

5

6

7

9

<NA>

Sum

Manual Cambodia CSES 2012 Version 2.0

12
11

13
7

94

1
3
3
10
6
5
6
1 17609 17644--- 7 : Q14_C03A
1
2
3 <NA>
Sum
180
411
169 16884 17644--- 8 : Q14_C03B
1
2
3 <NA>
Sum24
98
42 17480 17644--- 9 : Q14_C03C
1
2
3 <NA>
Sum4
12
19 17609 17644--- 10 : Q14_C04A
1
2
3
4
5
6
7
8
13
14
15
17
18
26
30
45
229
71
11
2
3
9
14
1
1
296
19
98 <NA>Sum
16
6 16884 17644--- 11 : Q14_C04B
1
2
3
4
5
6
8
13
14
18
19 <NA>
Sum
1
4
4
47
16
4
1
3
2
78
3 17481 17644--- 12 : Q14_C04C
2
4
5
6
7
13
14
15
18 <NA>
Sum
1
6
6
3
1
2
1
1
14 17609 17644--- 13 : Q14_C05A
1
2
3
4
5
6 <NA>
Sum
53
54
5
380
135
133 16884 17644--- 14 : Q14_C05B
1
2
3
4
5
6 <NA>
Sum
3
8
2
40
97
58 17436 17644--- 15 : Q14_C05C
145
6 <NA>
Sum2
6
9
47 17580 17644## 31 #### Frequency of variables in PersonEcoCurrent--- 3 : Q15_C01
12
343840 3742 3111 2381
14Sum
3 16086--- 4 : Q15_C02
12
345714 6545 1678 1011--- 5 : Q15_C03
1
2
Sum10356 5730 16086--- 6 : Q15_C04
1
2 <NA>
Sum
30 5700 10356 16086--- 9 : Q15_C07
1
2
3
4
593
15 8695 1012--- 10 : Q15_C08
1
2
3
4
3797
5 5367 1215--- 13 : Q15_C10B
1
2 <NA>
Sum###################

5
1525

6
806

7
362

8
170

9
83

10
37

11
14

5
601

6
310

7
141

8
45

9
33

10
5

11
Sum
3 16086

5
7

6
31

7
23

8
9

5
1

<NA>
Sum
5701 16086

<NA>
Sum
5701 16086

Manual Cambodia CSES 2012 Version 2.0

12
6

13
6

95

6091 4292 5703 16086--- 14 : Q15_C10C
1
2 <NA>
Sum
3090 1181 11815 16086--- 15 : Q15_C10D
1
2 <NA>
Sum
207 10149 5730 16086--- 16 : Q15_C11
0
1
2
3 <NA>
Sum
7193 2453
708
30 5702 16086--- 19 : Q15_C14
12345 <NA>
Sum
7
2 3176
6
1 12894 16086--- 20 : Q15_C15
12
34 <NA>
Sum169
2 2695326 12894 16086--- 23 : Q15_C17B
1
2 <NA>
Sum
1642 1546 12898 16086--- 24 : Q15_C17C
1
2 <NA>
Sum
780
731 14575 16086--- 26 : Q15_C18B
1
2 <NA>
Sum294
443 15349 16086--- 29 : Q15_C21
12
3 <NA>
Sum
172
451 9752 5711 16086--- 32 : Q15_C23
1
2 <NA>
Sum317
134 15635 16086--- 33 : Q15_C24
1
2
3 <NA>
Sum
21415
15 15635 16086--- 35 : Q15_C26
12 <NA>
Sum
15 5686 10385 16086--- 36 : Q15_C27A
12
3
45 <NA>
Sum
3
18
2
1 16071 16086--- 37 : Q15_C27B
3
5 <NA>
Sum
3
1 16082 16086--- 38 : Q15_C27C<NA>
Sum
16086 16086--- 39 : Q15_C28
1 <NA>
Sum
15 16071 16086--- 42 : Q15_C31
1
2
3
4
5
6
7
10
9
14
35
83
795 3539--- 44 : Q15_C33
1
2 <NA>
Sum27
29 16030 16086

81190

9 <NA>
Sum
11 10400 16086

Manual Cambodia CSES 2012 Version 2.0

96## 32 #### Frequency of variables in PersonviolenceA--- 3 : Q17AC0112
33832 3743 3438
14
15
Sum
4
1 17588--- 4 : Q17AC02
1
2
Sum
44 17544 17588--- 5 : Q17AC03
1
2
3
25
11
7

4
2748

5
1860

6
1035

7
473

8
238

9
115

###################

10
57

11
27

12
10

5 <NA>
Sum
1 17544 17588## 33 #### Frequency of variables in PersonViolenceB--- 3 : Q17BC01
1
2 3
4
5 Sum
13 17 56
3 44--- 4 : Q17BC02
1
2 3 Sum
23 14 7 44--- 5 : Q17BC03
1
2 3
4
6
8
10
3 11 11
1
5--- 6 : Q17BC04
1
2 Sum
22 22 44--- 7 : Q17BC05
1
2
3 <NA> Sum
16
3
3
22
44
--- 8 : Q17BC06
2 <NA> Sum22
22 44--- 9 : Q17BC07
1
2 3
4 Sum
6
2 31
5 44
--- 10 : Q17BC08
1
2 Sum
10 34 44--- 11 : Q17BC09
1
2 3
4 Sum
37
4 1
2 44

9
1

###################

11 Sum
2 44## 34 #### Frequency of variables in HHOtherInfo###################--- 3 : Q01BQ1
1
2 Sum
3375 465 3840--- 4 : Q05AQ1A
1
2 Sum
101 3739 3840--- 5 : Q05AQ1B

Manual Cambodia CSES 2012 Version 2.0

13
7

97

1
2
3
4
41
5 13
19
--- 6 : Q05AQ2
1
2 Sum
2175 1665 3840--- 7 : Q05AQ3
12
341102 718 245
68--- 8 : Q05ANote
0 <NA> Sum
2169 1671 3840--- 9 : Q05BQ1
1
2 <NA> Sum
1976 199 1665 3840--- 10 : Q05BNote0
1 <NA> Sum
1972
1 1867 3840--- 11 : Q05CNote
0
1 <NA> Sum
1971
1 1868 3840--- 12 : Q05DQ1
1
2 <NA> Sum
1592 385 1863 3840--- 13 : Q05DNote10
1 <NA> Sum
1971
2 1867 3840--- 14 : Q05D1Q1
1
2 <NA> Sum
1262 715 1863 3840--- 15 : Q05DNote20
1 <NA> Sum
1970
1 1869 3840--- 16 : Q05EQ1
1
2 Sum
2064 1776 3840--- 17 : Q05ENote1
0 <NA> Sum3816
24 3840--- 18 : Q05ENote20
1 <NA> Sum3815
1 24 3840--- 19 : Q05FQ1
1
2 Sum
48 3792 3840--- 20 : Q05FQ2
1
2 Sum
81 3759 3840--- 21 : Q05FNote10
1 <NA> Sum
3812
3 25 3840--- 22 : Q05FQ3
1
2 Sum
1744 2096 3840--- 23 : Q05FNote20
1 <NA> Sum3815
2 23 3840

5
9

6
8

7 <NA> Sum
6 3739 3840

5
21

6
9

7 <NA> Sum
12 1665 3840

Manual Cambodia CSES 2012 Version 2.0

98--- 24 : Q05FNote30 <NA> Sum3817
23 3840--- 25 : Q05GQ1
1
2 Sum
2264 1576 3840--- 26 : Q05GQ2
1
2 Sum
2145 1695 3840--- 27 : Q05GNote1
0 <NA> Sum3817
23 3840--- 28 : Q05GNote2
0 <NA> Sum3816
24 3840--- 29 : Q05HQ1
1
2 Sum
1443 2397 3840--- 30 : Q05HNote1
0 <NA> Sum3817
23 3840--- 31 : Q05HNote2
0 <NA> Sum3818
22 3840--- 32 : Q05HNote30 <NA> Sum3815
25 3840--- 33 : Q06_Q1
1
2 Sum
1308 2532 3840--- 34 : Q08_Q1
1
2 Sum
3537 303 3840--- 35 : Q10_Q1
1
2 Sum
1237 2603 3840--- 36 : Q11_Q1
1
2 Sum
565 3275 3840--- 37 : Q13AQ1
1
2 Sum
416 3424 3840--- 38 : Q13AQ2A
1
2
3
4
6
8 <NA> Sum
232 1675
6
3
3 3424 3840--- 39 : Q13AQ2B
1
2
3
4
5
6
8 <NA> Sum
5 114 2734
3
3
5 3649 3840--- 40 : Q13AQ2C
3
4
5
6 <NA> Sum
36
58
5
16 3725 3840--- 41 : Q13AQ3
1
2
3
4
5
8 <NA> Sum
196
87 36
30
13
54 3424 3840--- 42 : Q13AQ4
1
2
8 <NA> Sum

Manual Cambodia CSES 2012 Version 2.0

99

107 3315
2 416 3840--- 43 : Q17AQ1
1
2 Sum
3311 529 3840--- 44 : Q17AQ2
1
2 Sum
156 3684 3840--- 45 : Q17AQ3
1
2 Sum
246 3594 3840## 35 #### Frequency of variables in PSUListing--- 2 : Province_Code
01 02 03 04 05 06
18 29 42 12 18 14
21 22 23 24 Sum
18
6 1
4 384
--- 12 : UrbanRural
1
2 Sum
144 240 384--- 14 : SurveyMonth
1
2 3
4
5
6
32 32 32 32 32 32###################

07
16

08
26

09
5

10
6

11
3

12
78

13
3

7
32

8
32

9
32

10
32

11
32

12 Sum32 38414
24## 36 #### Frequency of variables in weighthouseholds--- 3 : urbrur
1
2 Sum
1440 2400 3840--- 4 : Stratum
1
2 Sum
1440 2400 3840--- 5 : Poststratum
101 102 11 111
10
50 80
10
181 182 191 192
50
20 20
30
42
51 52
61
90
30 15010--- 6 : hhsize
12
3
4
88 307 683 897

15
11

16
3

17
24

18
7

19
5

20
11

###################

112
20
202
110
62
130

12
100
21
110
71
40

121
740
212
180
72
120

122
40
22
180
81
50

132
30
221
20
82
210

141
20
222
40
91
30

142 151220
20
232 2411020
92 Sum20 3840

152
90
242
20

162
30
31
60

171
90
32
360

5
826

6
562

7
237

8
124

9
58

10
31

11
16

13
3

14
3

15 Sum
1 3840## 37 #### Frequency of variables in weightpersons

124###################--- 4 : urbrur
1
2
Sum6478 11166 17644--- 5 : Stratum
12Sum6478 11166 17644--- 6 : Poststratum

Manual Cambodia CSES 2012 Version 2.0

172
150
41
30

100

101
41
162
153
232
45
81
225

102
243
171
397
241
95
82
996

11
370
172
759
242
87
91
138

111
112
41
95
181
182
232
106
31
32
271 1711
92Sum
89 17644

12
466
191
107
41
150

121
3307
192
128
42
383

122
187
202
474
51
136

132
155
21
501
52
694

141
80
212
822
61
48

142
952
22
860
62
634

>

Manual Cambodia CSES 2012 Version 2.0

151
88
221
97
71
154

152
418
222
181
72
528

101

5.3 Relationship among data files and identifiers
Data file: 01 Household
The number of sample household is 3,840.
The variables are HHID, PSU, HHnumber, Males, Females, and Total.
The variable HHID is unique, and consisted of PSU and HHnumber.
> d<-outfiles[[1]]> dim(d)[1] 3840

10> head(d)HHID

PSU HHnumber Males Females Total SupervisorId RowDiff

1 0100301 01003

01

1

1

2

011

0

2 0100302 01003

02

3

2

5

011

0

3 0100303 01003

03

3

5

8

011

0

4 0100304 01003

04

2

3

5

011

0

5 0100305 01003

05

3

2

5

011

0

6 0100306 01003

06

0

3

3

011

0

SignOut Operator
1 2013-01-18 18:07:00

zada

2 2013-01-18 18:31:00

zada

3 2013-01-18 19:04:00

zada

4 2013-01-18 19:38:00

zada

5 2013-01-18 20:10:00

zada

6 2013-01-21 20:13:00

zada> table(d$HHID==paste(d$PSU,d$HHnumber,sep=""))
TRUE
3840
> length(unique(d$HHID))[1] 3840> table(d$Total==(d$Male+d$Female))
TRUE
3840

Manual Cambodia CSES 2012 Version 2.0

102Data file: 02 HHMembers
The number of sample household members is 17,644.
The unique number of hhid is 3,840, and perfectly the same as 01 Household.
> d<-outfiles[[2]]> dim(d)[1] 17644

23> head(d)pkidhhid Q01AC01 Q01AC03 Q01AC04A Q01AC04B Q01AC04C Q01AC05 Q01AC06

1

2 2101910

1

1

23

3

1972

39

1

2

3 2101910

2

2

4

6

1974

37

2

3

4 2101910

3

1

29

11

1992

19

3

4

5 2101910

4

1

20

11

1995

16

3

5

6 2101910

5

2

20

8

2008

3

3

6

7 0803010

1

1

10

9

1983

28

1

Q01AC07 Q01AC08 Q01AC09 Q01AC10 Q01AC11A Q01AC11B Q01AC12A Q01AC12B Q01AC12C
1

NA

NA

1

2

1

1

2

0

NA

2

NA

NA

1

1

1

1

0

NA

NA

3

1

2

4

NA

1

1

0

NA

NA

4

1

2

4

NA

1

1

2

0

NA

5

1

2

NA

NA

1

1

0

NA

NA

6

NA

NA

1

2

1

1

0

NA

NA

Q01AC13 Q01AC14 EntryUser

ChangeDate

Persid1

1NAriya 2012-02-21 19:17:00 210191001

2

1

NA

riya 2012-02-21 19:17:00 210191002

3

1

NA

riya 2012-02-21 19:17:00 210191003

4

2

30

riya 2012-02-21 19:18:00 210191004

5

1

NA

riya 2012-02-21 19:18:00 210191005

6

1

NA

morokat 2012-02-21 19:24:00 080301001> length(unique(d$HHID))[1] 3840> t<-unique(d$HHID)> table(t[order(t)]==outfiles[[1]]$HHID)
TRUE
3840

Manual Cambodia CSES 2012 Version 2.0

103



The number of members within the household is compatible with 01 Household.

However, the number of household member by sex differs in two sample households.
> table(tapply(d$pkid,d$HHID,length)==outfiles[[1]]$Total)
TRUE
3840

# Q01AC03: Sex# Number of household members by sex within the household> t<-tapply(d$pkid,list(d$HHID,d$Q01AC03),length)> t[is.na(t)]<-0> table(t[,1]==outfiles[[1]]$Male)
FALSE

TRUE

2

3838

> table(t[,2]==outfiles[[1]]$Female)
FALSE

TRUE

2

3838



Two sample households with erroneous number of household members by sex> outfiles[[1]][t[,1]!=outfiles[[1]]$Male,1:6]
HHID
143

PSU HHnumber Males Females Total

0102503 01025

03

0

1

1

1629 0802209 08022

09

0

1

1

> subset(outfiles[[1]],HHID=="0102503")[1:6]
HHID

PSU HHnumber Males Females Total

143 0102503 01025

03

0

1

1

> d[d$HHID=="0102503",1:9]
pkid

hhid Q01AC01 Q01AC03 Q01AC04A Q01AC04B Q01AC04C Q01AC05 Q01AC06

3964 1773 0102503

1

1

17

1

1950

Summary:62

The household with HHID=0102503 should have only one male members.

Manual Cambodia CSES 2012 Version 2.0

1

104

> subset(outfiles[[1]],HHID=="0802209")[1:6]
HHID

PSU HHnumber Males Females Total

1629 0802209 08022

09

0

1

1

> d[d$HHID=="0802209",1:9]
pkid

hhid Q01AC01 Q01AC03 Q01AC04A Q01AC04B Q01AC04C Q01AC05 Q01AC06

8796 9145 0802209

1

1

15

9

1950

Manual Cambodia CSES 2012 Version 2.0

61

1

105

Data file: 35 PSUListing
The number of PSU is 384.
The file includes variables of Province_Code and UrbanRural.
> d<-outfiles[[35]]> dim(d)[1] 38416> head(d)PSU Province_Code

Province_Name District_Code

District_Name Commune_Code

1 01003

01 Banteay Meanchey

02

Mongkol Borei

08

2 01006

01 Banteay Meanchey

02

Mongkol Borei

13

3 01007

01 Banteay Meanchey

03

Phnum Srok

03

4 01008

01 Banteay Meanchey

04 Preah Netr Preah02

5 0101101 Banteay Meanchey

05

Ou Chrov

03

6 0101201 Banteay Meanchey

05

Ou Chrov

09

Commune_Name Village_Code1

Rohat Tuek

2

Village_Name Enum_Areas Selected_EA UrbanRural Households

13

Chak Kaeut

2

2

2

119

Ta Lam07 Khla Kham Chhkae

2

2

2

141

3

Ponley04

Svay Khmau

3

2

2

275

4

Chob Vari07

Chreab Chas

2

1

2

189

5

Kuttasat

03

Kuttaksat

4

3

2

462

6

Ou Beichaon

09

Thnal Bat

2

1

2

291

SurveyMonth HouseholdsInVillage HouseholdsInListing
1

8

143

63

2

8

182

64

3

3

305

112

4

3

176

81

5

5

550

65

6

5

245

67

Manual Cambodia CSES 2012 Version 2.0

106Data file: 36 weighthouseholds
This file corresponds to the file 01 Household.
The files includes variables of urbrur, Stratum, Poststratum and hhsize.
The sum of houseold weight, that is, estimated number of households is 3,082,446.
The estimated number of household member is 14,273,806.
> d<-outfiles[[36]]> dim(d)[1] 3840

7> head(d)PSU

HHID urbrur Stratum Poststratum hhsize

hw12a

1 01003 0100301

2

2

12

2 1236.831

2 01003 0100302

2

2

12

5 1236.831

3 01003 0100303

2

2

12

8 1236.831

4 01003 0100304

2

2

12

5 1236.831

5 01003 0100305

2

2

12

5 1236.831

6 01003 0100306

2

2

12

3 1236.831> table(outfiles[[1]]$HHID==outfiles[[36]]$HHID)
TRUE
3840
> sum(d$hw12a)[1] 3082446> sum(d$hhsize*d$hw12a)[1] 14273806

Stratum

The variable of Stratum has two categories, which correspond to urban and rural.
The number of categories of Poststratum is 43.
> table(d$Stratum,d$urbrur)
1

2

1 1440020 2400> length(unique(d$Poststratum))[1] 43> table(d$Stratum,d$Poststratum)

Manual Cambodia CSES 2012 Version 2.0

107

101 10211 111 112

12 121 122 132 141 142 151 152 162 171 172 181 182 191 192 202

1

10

0

80

10

0

0 740

2

0

50

0

0

20 100

0

0

20

0

20

0

0

90

0

50

0

20

0

0

40

30

0 220

0

90

30

0 150

0

20

0

30 11022 221 222 232 241 242

31

32

41

42

51

52

61

62

71

72

81

82

91

92

0

20

0

0

20

0

60

0

30

0

30

0

10

0

40

0

50

0

30

0

2 180 180

0

40

10

0

20

0 360

0

90

0 150

0 210

0

20

212
1

0

0 130

0 120

21

0 110
0

Whaht is poststratum?



Three Regions

NIS often uses three regions; “Phnom Pen”(including urban and rural), “Other urban” and “Other
rural” in a table.
So, generated the variable of region;# Phnom Pen: Province_Code=12 in data file “35 PSUListing”# Urbanrural: urbrur in data file “36 weighthouseholds”# Variables of PSU and HHID in data file “01 Households” and “36 weighthouseholds”> d<-merge(d,outfiles[[35]][,c("PSU","Province_Code")],by="PSU",all.x=T)> dim(d)[1] 3840

8> head(d)PSU

HHID urbrur Stratum Poststratum hhsize

hw12a Province_Code

1 01003 0100301

2

2

12

2 1236.831

01

2 01003 0100302

2

2

12

5 1236.831

01

3 01003 0100303

2

2

12

8 1236.831

01

4 01003 0100304

2

2

12

5 1236.831

01

5 01003 0100305

2

2

12

5 1236.831

01

6 01003 0100306

2

2

12

3 1236.831

01> d$region<-ifelse(d$Province_Code==12,1,0)> d$region<-ifelse(d$region==0 & d$urbrur==1, 2, d$region)> d$region<-ifelse(d$region==0 & d$urbrur==2, 3, d$region)> t<-table(d$region)> names(t)<-c("Phnom Pen","Other urban","Other rural")# Number of sample households by three regions> addmargins(t)Manual Cambodia CSES 2012 Version 2.0

108

Phnom Pen Other urban Other rural
780

700

Sum

2360

3840

> head(d)PSU

HHID urbrur Stratum Poststratum hhsize

hw12a Province_Code region

1 01003 0100301

2

2

12

2 1236.831

01

3

2 01003 0100302

2

2

12

5 1236.831

01

3

3 01003 0100303

2

2

12

8 1236.831

01

3

4 01003 0100304

2

2

12

5 1236.831

01

3

5 01003 0100305

2

2

12

5 1236.831

01

3

6 01003 0100306

2

2

12

3 1236.831

01

3> dim(d)[1] 3840

9> outfiles[[36]]<-d

Manual Cambodia CSES 2012 Version 2.0

109Data file: 37 weightpersons
This file corresponds to the file 02 HHMembers.
The variable of PersID, personal identifier is composed of variables of hhid and Q01AC01 in 02
HHMembers.
The sum of person weight is 14,376,414.
> d<-outfiles[[37]]> dim(d)[1] 17644

8> head(d)PersIDPSU

HHID urbrur Stratum Poststratum

hw12a

pw12a

1 010030101 01003 0100301

2

2

12 1236.831 1043.975

2 010030102 01003 0100301

2

2

12 1236.831 1043.692

3 010030201 01003 0100302

2

2

12 1236.831 1283.659

4 010030202 01003 0100302

2

2

12 1236.831 1222.307

5 010030203 01003 0100302

2

2

12 1236.831 1338.835

6 010030204 01003 0100302

2

2

12 1236.831 1247.047> d<-outfiles[[2]]> d$PersID<-paste(d$hhid,formatC(d$Q01AC01,width=2,flag="0"),sep="")> d<-d[order(d$PersID),]> table(d$PersID==outfiles[[37]]$PersID)
TRUE
17644

> d<-outfiles[[37]]> sum(d$pw12a)[1] 14376414

Manual Cambodia CSES 2012 Version 2.0

110



Rearrangement of data files



The variable label “hhid” should be replaced with “HHID”.

> outfiles.old<-outfiles> for(j in 2:34){+ d<-outfiles[[j]]+ colnames(d)[2]<-"HHID"+ outfiles[[j]]<-d+}Confirmed by;> for(j in 1:37){+ d<-outfiles[[j]]+ cat(j,":",colnames(d),"¥n")+}> save(outfiles,Rnames,file="CSES2012_rearrange3.RData")

 The variable of personal identifier “PersID” or “persid” should be replaced with “PID”.
> outfiles.old<-outfiles> colnames(outfiles[[2]])[1] "pkid""HHID""Q01AC01""Q01AC03""Q01AC04A"[6] "Q01AC04B""Q01AC04C""Q01AC05""Q01AC06""Q01AC07"[11] "Q01AC08""Q01AC09""Q01AC10""Q01AC11A""Q01AC11B"[16] "Q01AC12A""Q01AC12B""Q01AC12C""Q01AC13""Q01AC14"[21] "EntryUser" "ChangeDate" "Persid"> colnames(outfiles[[2]])[23]<-"PID"> colnames(outfiles[[27]])[1] "pkid""HHID""Q10_C01""Q10_C02""Q10_C03"[6] "Q10_C04""Q10_C05""Q10_C06""Q10_C07A""Q10_C07B"[11] "Q10_C07C""Q10_C07D""EntryUser" "ChangeDate" "persid"> colnames(outfiles[[27]])[15]<-"PID"> colnames(outfiles[[28]])[1] "pkid""HHID""Q11_C01""Q11_C02"[5] "Q11_C03""Q11_C04""Q11_C05""Q11_C06A"[9] "Q11_C06B""Q11_C07""Q11_C08A""Q11_C08B"[13] "Q11_C09""Q11_C10""Q11_C11""EntryUser"[17] "ChangeDate""Persid""PersidMother"> colnames(outfiles[[28]])[18]<-"PID"> colnames(outfiles[[29]])[1] "pkid""HHID""Q13BC01""Q13BC2A""Q13BC2B"[6] "Q13BC03""Q13BC04""Q13BC05""Q13BC06""Q13BC07"[11] "Q13BC08""Q13BC9A""Q13BC9B""Q13BC9C""Q13BC9D"

Manual Cambodia CSES 2012 Version 2.0

111[16] "Q13BC10""Q13BC11""Q13BC12A""Q13BC12B""Q13BC12C"[21] "EntryUser" "ChangeDate" "persid"> colnames(outfiles[[29]])[23]<-"PID"> colnames(outfiles[[30]])[1] "pkid""HHID""Q14_C01""Q14_C02A" "Q14_C02B"[6] "Q14_C02C""Q14_C03A""Q14_C03B" "Q14_C03C" "Q14_C04A"[11] "Q14_C04B""Q14_C04C""Q14_C05A" "Q14_C05B" "Q14_C05C"[16] "EntryUser" "ChangeDate" "Persid"> colnames(outfiles[[30]])[18]<-"PID"> colnames(outfiles[[31]])[1] "pkid""HHID""Q15_C01""Q15_C02""Q15_C03"[6] "Q15_C04""Q15_C05B""Q15_C06B" "Q15_C07""Q15_C08"[11] "Q15_C09""Q15_C10A""Q15_C10B" "Q15_C10C" "Q15_C10D"[16] "Q15_C11""Q15_C12B""Q15_C13B" "Q15_C14""Q15_C15"[21] "Q15_C16""Q15_C17A""Q15_C17B" "Q15_C17C" "Q15_C18A"[26] "Q15_C18B""Q15_C19""Q15_C20""Q15_C21""Q15_C22A"[31] "Q15_C22B""Q15_C23""Q15_C24""Q15_C25""Q15_C26"[36] "Q15_C27A""Q15_C27B""Q15_C27C" "Q15_C28""Q15_C29"[41] "Q15_C30""Q15_C31""Q15_C32""Q15_C33""EntryUser"[46] "ChangeDate" "Persid"> colnames(outfiles[[31]])[47]<-"PID"> colnames(outfiles[[32]])[1] "pkid""HHID""Q17AC01""Q17AC02""Q17AC03"[6] "EntryUser" "ChangeDate" "persid"> colnames(outfiles[[32]])[8]<-"PID"> colnames(outfiles[[33]])[1] "pkid""HHID""Q17BC01""Q17BC02""Q17BC03"[6] "Q17BC04""Q17BC05""Q17BC06""Q17BC07""Q17BC08"[11] "Q17BC09""EntryUser" "ChangeDate" "persid"> colnames(outfiles[[33]])[14]<-"PID"

Manual Cambodia CSES 2012 Version 2.0

112

Chapter 6. Household Expenditure
Background
CSES2012 data has been collected by interviewers (NIS officials) using both recall and diarymethods. However, the estimation of household income and expenditure is principally based onrecall data.

There are some descriptions on how to use the data in the CSES2009 survey report as below.
CSES2012 is almost the same as CSES2009 with some differences, which are also noted in the
below table.
Page

Related description in the survey report

6

Expenditure: the household expenditure in Cambodia 2009 was calculated using recall
data from the household questionnaire.

104

Consumption data in the 2009 survey was collected using recall questions in thehousehold questionnaire. Consumption data was also collected in a Diary where all
expenditure transactions and consumption of own produced goods during the survey
month were reported. The diary method was introduced in CSES 2004. For calculating
poverty estimates the recall data was used all years. However, for 2004 poverty estimates
were calculated using both methods. The most recent presentation of Poverty Estimates
was carried out by the World Bank.

104

The result presented in this chapter is compiled from recall data. The household
questionnaire had two sets of questions, one for food expenditure/consumption and thesecond set for non-food expenditure. The questionnaire was designed to collect data onpurchase in cash, consumption of own production, consumption of items received as
wages in kind. It also included gifts, free collection and barter, and in kind expenditure.
The food section comprised 20 items(*) covering all food, including alcoholic, tobacco,and food taken away from home, prepared meals bought outside and eaten at home. The
non-food section embraced 13 items(**) covering all non-food expenditure except
housing. Expenditure on housing was collected in the Housing module. The reference
period for food items was the last seven days. For non-food items the reference periodvaried from last month to last 12 month (see the Questionnaire in appendix 8).

(Note) * The food section of CSES2012 comprised 21 items. “Cereals” in CSES 2009 is
divided into “rice” and “other cereals”.
** The non-food section of CSES2012 appended 14-17 items, which are
non-consumption expenditure to be used for calculating disposable income.

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105

In this report the monthly consumption is calculated. The consumption concept used inthis report differ from the calculation of consumption for poverty estimates where
adjustments for price differences, rental values etc. is done, see section Definition andWorld Bank report.

107 -The grouping of items follows the questionnaire, except for domestic salaries and108

gambling. Domestic salaries are included in Furniture, household operation etc. Gamblingis excluded to be consistent with the income concept where income from Gambling andlotteries is excluded in total income.
For “Housing” charges on water, sewage, wastewater disposal, garbage collection andfuel for lighting and cooking are included as well as paid rent. For owner occupied houses
the household was asked to estimate the value for rent of a similar house. Expenditure
spent on maintenance and minor repairs is also included(*). All this data are collected in
the Housing module.
Food share are calculated as the share of total consumption. Food includes all food items,
non-alcoholic and alcoholic beverages.

(Note) * Questions on expenditure spent on maintenance and repairs is not included in
Housing questionnaire of CSES2012.
Table

Classification of consumption composition used in tables is as below;(Note) The above consumption composition is the same as CSES2012.

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6.1 FOOD ITEMSCreated household-level data frame consisted of vectors of food items.

# outfiles[[3]]: HHFoodConsumption# Q01BC01: Item number (01 to 21)# Q01BC05: Total consumption in the last 7 days
> d<-outfiles[[3]]> df<-tapply(d$ Q01BC05,list(d$HHID,d$ Q01BC01),sum)> dim(df)[1] 3840 21> head(df)
1
2
3
4
5
6
7
8
9
10 11
12
13
14 15
16
17
0100301 16000 7000 20000 18000 5000
NA 3000 10000
NA
NA NA 5000
NA 7000 NA
NA
NA
0100302 16000 10000 27000 13000 2000
NA 3000 14000
NA
NA NA
NA
NA 10000 NA
NA 3000
0100303 28000 7000 20000 20000
NA 2500 4000 22000
NA
NA NA
NA
NA 10000 NA
NA
NA
0100304 16000 7000 20000 16000 3000 6000 3000 13000
NA
NA NA 6000
NA 7000 NA
NA
NA
0100305 23100 6000 40000 13000 3000
NA 2000 12000 2500 1000 NA 7000
NA 12000 NA 4000 4000
0100306 15000 4000 15000 20000 2000
NA 1300 7000 2000
NA NA 3000 4000 10000 NA
NA
NA
18
19
20
21
0100301 NA 3000
NA
NA
0100302 NA 4000
NA
NA
0100303 NA 3000 17000
NA
0100304 NA
NA
NA
NA
0100305 9100 2000 35000 5000
0100306 NA 2000 20000
NA> df[is.na(df)]<-0> df<-as.data.frame(df)> hhfood<-df# Converted to monthly> hhfood<-round(hhfood*52/12)> head(hhfood)
1
2
3
4
5
6
7
8
9
10 11
12
13
14 15
0100301 69333 30333 86667 78000 21667
0 13000 43333
0
0 0 21667
0 30333 00100302 69333 43333 117000 56333 8667
0 13000 60667
00 0
00 43333 00100303 121333 30333 86667 86667
0 10833 17333 95333
00 0
00 43333 00100304 69333 30333 86667 69333 13000 26000 13000 56333
00 0 26000
0 30333 00100305 100100 26000 173333 56333 13000
0 8667 52000 10833 4333 0 30333
0 52000 0
0100306 65000 17333 65000 86667 8667
0 5633 30333 8667
0 0 13000 17333 43333 0
16
17
18
19
20
21
0100301000 13000000100302
0 13000
0 17333000100303000 13000 73667
001003040000000100305 17333 17333 39433 8667 151667 21667
010030600
0 8667 86667
0Remarks:
Here, the multiplier of 52/12 is used instead of 30/7.

# Generated data frame exp.food with variables of HHID and 21 item groups> exp.food<-data.frame(HHID=rownames(hhfood),hhfood,row.names=NULL)> colnames(exp.food)[2:22]<-paste("item",formatC(1:21,width=2,flag="0"),sep="")> head(exp.food)

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HHID item01 item02 item03 item04 item05 item06 item07 item08 item09 item10 item11 item12
1 0100301 69333 30333 86667 78000 21667
0 13000 43333
000 21667
2 0100302 69333 43333 117000 56333
8667
0 13000 60667
00003 0100303 121333 30333 86667 86667
0 10833 17333 95333
00004 0100304 69333 30333 86667 69333 13000 26000 13000 56333
000 26000
5 0100305 100100 26000 173333 56333 13000
08667 52000 10833
4333
0 30333
6 0100306 65000 17333 65000 86667
8667
05633 30333
8667
00 13000
item13 item14 item15 item16 item17 item18 item19 item20 item21
1
0 303330000 130000020 4333300 13000
0 173330030 433330000 13000 73667
04
0 30333
0
0
0
0
0
0
0
5
0 52000
0 17333 17333 39433
8667 151667 21667
6 17333 43333
00008667 86667
0# Generated the variables;# food: sum of items 01:16,19:21# alcohol: sum of items 17 and 18# total: sum of items 01:21> exp.food$food<-rowSums(exp.food[,c(2:17,20:22)])> exp.food$alcohol<-rowSums(exp.food[,18:19])> exp.food$total<-rowSums(exp.food[,2:22])> head(exp.food)
HHID item01 item02 item03 item04 item05 item06 item07 item08 item09 item10 item11 item12
1 0100301 69333 30333 86667 78000 21667
0 13000 43333
000 21667
2 0100302 69333 43333 117000 56333
8667
0 13000 60667
00003 0100303 121333 30333 86667 86667
0 10833 17333 95333
00004 0100304 69333 30333 86667 69333 13000 26000 13000 56333
000 26000
5 0100305 100100 26000 173333 56333 13000
08667 52000 10833
4333
0 30333
6 0100306 65000 17333 65000 86667
8667
05633 30333
8667
00 13000
item13 item14 item15 item16 item17 item18 item19 item20 item21
food alcohol total
1
0 303330000 13000
00 407333
0 407333
2
0 4333300 13000
0 1733300 428999
13000 441999
30 433330000 13000 73667
0 578499
0 578499
40 303330000000 420332
0 420332
5
0 52000
0 17333 17333 39433
8667 151667 21667 726266
56766 783032
6 17333 43333
00008667 86667
0 456300
0 456300

Average monthly amount of food consumption by food items (in thousand Riels)# Estimated monthly total amount of food consumption (in million Riels)> table(exp.food$HHID==outfiles[[36]]$HHID)
TRUE
3840
> hw<-outfiles[[36]]$hw12a # household weight> tm<-sapply(exp.food[,2:25],function(x) round(sum(x*hw))) # in Riels> round(tm/10^6) # in million Riels
item01 item02 item03 item04 item05 item06 item07 item08 item09354896 68691 398010 260085
39332
35551
39514 159083
11833
item12 item13 item14 item15 item16 item17 item18 item19 item20
93111 19482 101837
27609
33622
57612
35937
29791 181005
alcohol total
93548 2012439

Manual Cambodia CSES 2012 Version 2.0

item10 item11
12012
17039
item21food
36387 1918891

116# Average monthly amount of food consumption by food item (in thousand Riels)# Per household> (NH<-sum(hw)) # estimated number of households[1] 3082446> (th<-round(tm/NH/1000))
item01 item02 item03 item04 item05 item06 item07 item08 item09 item10
115
22
129
84
13
12
13
52
4
4
item12 item13 item14 item15 item16 item17 item18 item19 item20 item21
30
6
33
9
11
19
12
10
59
12
alcohol total
30
653

item11
6
food623# Item names> t0<-c("Rice","Cereals","Fish","Meat & poultry","Eggs","Dairy products","Oil and fats",+ "Fresh vegetables","Tuber","Pulses and legumes","Prepared and preserved vegetables",+ "Fruit etc.","Dried nuts and edible seeds","Sugar, salt and spices","Tea, coffee, cocoa",+ "Non-alcoholic beverages","Alcoholic beverages","Tobacco products","Other food products",+ "Food taken away from home","Prepared meals bought outside and eaten at home")> t0<-c(t0,"Food and non-alcoholic beverages","Alcohol and tobacco","Food total")# Average monthly amount of food consumption per household# by food items (in thousand Riels)> (m<-data.frame(item=t0,perhh=th,row.names=NULL))
item perhh
1
Rice
115
2
Cereals
22
3
Fish
129
4
Meat & poultry
84
5
Eggs
13
6
Dairy products
127
Oil and fats
13
8
Fresh vegetables
52
9
Tuber
4
10
Pulses and legumes
411
Prepared and preserved vegetables
6
12
Fruit etc.
30
13Dried nuts and edible seeds
6
14
Sugar, salt and spices
33
15
Tea, coffee, cocoa
916Non-alcoholic beverages
11
17
Alcoholic beverages
19
18
Tobacco products
12
19
Other food products
10
20
Food taken away from home59
21 Prepared meals bought outside and eaten at home
12
22
Food and non-alcoholic beverages
623
23
Alcohol and tobacco
30
24Food total
653

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117> str(exp.food)'data.frame':
3840 obs. of 25 variables:$ HHID : Factor w/ 3840 levels "0100301","0100302",..: 1 2 3 4 5 6 7 8 9 10 ...
$ item01 : num 69333 69333 121333 69333 100100 ...
$ item02 : num 30333 43333 30333 30333 26000 ...
$ item03 : num 86667 117000 86667 86667 173333 ...
$ item04 : num 78000 56333 86667 69333 56333 ...
$ item05 : num 21667 8667 0 13000 13000 ...
$ item06 : num 0 0 10833 26000 0 ...
$ item07 : num 13000 13000 17333 13000 8667 ...
$ item08 : num 43333 60667 95333 56333 52000 ...
$ item09 : num 0 0 0 0 10833 ...
$ item10 : num 0 0 0 0 4333 ...
$ item11 : num 0 0 0 0 0 0 0 6500 13000 0 ...
$ item12 : num 21667 0 0 26000 30333 ...
$ item13 : num 0 0 0 0 0 ...
$ item14 : num 30333 43333 43333 30333 52000 ...
$ item15 : num 0 0 0 0 0 0 0 0 0 0 ...
$ item16 : num 0 0 0 0 17333 ...
$ item17 : num 0 13000 0 0 17333 ...
$ item18 : num 0 0 0 0 39433 ...
$ item19 : num 13000 17333 13000 0 8667 ...
$ item20 : num 0 0 73667 0 151667 ...
$ item21 : num 0 0 0 0 21667 ...
$ food : num 407333 428999 578499 420332 726266 ...
$ alcohol: num 0 13000 0 0 56766 ...
$ total : num 407333 441999 578499 420332 783032 ...
> exp.food$HHID<-as.character(exp.food$HHID)# in Riel

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6.2 NON-FOOD ITEMSCreated household-level data frame consisted of vectors of non-food items.

# outfiles[[4]]: HHRecallNonFood# Q01CC01: Non-food item (01 to 17)# Q01CC06: Total expenditure in Riels# Reference periods differ by item and are indicated on the questionnaire> d<-outfiles[[4]]> df<-tapply(d$Q01CC06,list(d$HHID,d$Q01CC01),sum)> dim(df)[1] 3840 17> head(df)
1
2
3
4
5
6 7
8 9
10
11 12
13 14
0100301
NA 40000 20000
NA 200000
NA NA 1000000 NA
NA 4000000 NA 100000 NA
0100302 2000 17000
NA 12000 160000 180000 NA 300000 NA 569000 120000 NA 90000 NA
0100303 200000 30000 8000 10000 600000 150000 NA 200000 NA 174000 300000 NA 120000 NA
0100304 30000 20000
NA 5000 170000 70000 NA 300000 NA
NA 120000 NA 70000 NA
0100305 165000 200000 40000 14000 400000 130000 NA 190000 NA
NA
30000 NA
4000 NA
0100306
NA 40000 20000 6000 300000 95000 NA 200000 NA 410000 100000 NA
7000 NA
15 16
170100301 1550000 NA
NA
0100302 520000 NA
NA
0100303 1220000 NA
NA
0100304 530000 NA
NA
0100305 4060000 NA 9000
0100306 650000 NANA> df[is.na(df)]<-0> df<-as.data.frame(df)# Converted to monthly# Item 01-04: a month# Item 05: 6 months# Item 06-17: 12 months> hhnonfood<-df> hhnonfood[,5]<-round(df[,5]/6)> hhnonfood[,6:17]<-round(df[,6:17]/12)> head(hhnonfood)
1
2
3
4
5
6 7
8 9
10
11 12
13 14
15 16
0100301
0 40000 20000
0 33333
0 0 83333 0
0 333333 0 8333 0 129167 00100302 2000 17000
0 12000 26667 15000 0 25000 0 47417 10000 0 7500 0 43333 0
0100303 200000 30000 8000 10000 100000 12500 0 16667 0 14500 25000 0 10000 0 101667 00100304 30000 20000
0 5000 28333 5833 0 25000 0
0 10000 0 5833 0 44167 00100305 165000 200000 40000 14000 66667 10833 0 15833 002500 0333 0 338333 0
0100306
0 40000 20000 6000 50000 7917 0 16667 0 34167
8333 0583 0 54167 0
170100301 0
0100302 0
0100303 0
0100304 0
0100305 750
0100306 0> exp.nonfood<-data.frame(HHID=rownames(hhnonfood),hhnonfood,row.names=NULL)> colnames(exp.nonfood)[2:18]<-paste("item",formatC(1:17,width=2,flag="0"),sep="")Manual Cambodia CSES 2012 Version 2.0

119> head(exp.nonfood)
HHID item01 item02 item03 item04 item05 item06 item07 item08 item09 item10 item11 item12
1 0100301
0 40000 20000
0 3333300 8333300 333333
02 0100302 2000 17000
0 12000 26667 15000
0 25000
0 47417 10000
03 0100303 200000 30000
8000 10000 100000 12500
0 16667
0 14500 25000
04 0100304 30000 20000
05000 28333
5833
0 2500000 100000
5 0100305 165000 200000 40000 14000 66667 10833
0 15833002500
06 0100306
0 40000 20000
6000 50000
7917
0 16667
0 341678333
0
item13 item14 item15 item16 item1718333
0 129167002
7500
0 43333003 10000
0 101667
0045833
0 44167005
333
0 338333
0
750
6
583
0 54167
00Average monthly amount of non-food consumption by food items (in thousand Riels)# Total amount of non-food consumption (in million Riels)> t2<-sapply(exp.nonfood[,2:18],function(x) sum(x*hw))# Total monthly amount of non-food consumption by item (in million Riels)> tm<-round(t2/10^6)> (tm<-c(tm,total.0113=sum(tm[1:13])))
item01
item02
item03
item04item05
item06
item0726981521868063581
57402
10738135302
947
item08item09item10
item11
item12
item13
item1447156
3185
169636
28663
1799
3535
6411
item15
item16
item17
total total.0113
272743532
6150
1007082
1007082# Average monthly amount of non-food consumption by item (in thousand Riels)# Per household> th<-round(t2/NH/1000)> (th<-c(th,total.0113=sum(th[1:13])))
item01
item02
item03
item04item05
item06
item07
88
71
21
19
35
11
0
item08item09item10
item11
item12
item13
item14
15
1
55
9
1
1
2
item15
item16
item17 total.0113
88
0
2
327

# Item names> t0<-c("Medical care","Transportation","Communication","Personal care","Clothing and footwear",+ "Furniture, furnishings and household equipment and operation","Domestic salaries",+ "Recreation within Cambodia","Recreation abroad","Education","Personal effects",+ "Gambling","Miscellaneous items",+ "Charities","Inter-households transfer","Income tax","Property tax")> t0<-c(t0,"Non-food total (01-13)")Manual Cambodia CSES 2012 Version 2.0

120# Average monthly amount of non-food consumption per household# by non-food items (in thousand Riels)> (m2<-data.frame(item=t0,perhh=th,row.names=NULL))
item perhh
1
Medical care
88
2Transportation
71
3
Communication
21
4
Personal care
19
5
Clothing and footwear
35
6 Furniture, furnishings and household equipment and operation
11
7
Domestic salaries
08
Recreation within Cambodia
15
9
Recreation abroad
1
10
Education
55
11
Personal effects
912
Gambling
1
13
Miscellaneous items
1
14
Charities
2
15
Inter-households transfer
88
16
Income tax
0
17
Property tax
2
18
Non-food total (01-13)
327> str(exp.nonfood)'data.frame':
3840 obs. of 18 variables:$ HHID : Factor w/ 3840 levels "0100301","0100302",..: 1 2 3 4 5 6 7 8 9 10 ...
$ item01: num 0 2000 200000 30000 165000 0 19000 0 50000 0 ...
$ item02: num 40000 17000 30000 20000 200000 40000 90000 20000 10000 100000 ...
$ item03: num 20000 0 8000 0 40000 20000 40000 8000 0 80000 ...
$ item04: num 0 12000 10000 5000 14000 6000 10000 4000 9000 20000 ...
$ item05: num 33333 26667 100000 28333 66667 ...
$ item06: num 0 15000 12500 5833 10833 ...
$ item07: num 0 0 0 0 0 0 0 0 0 0 ...
$ item08: num 83333 25000 16667 25000 15833 ...
$ item09: num 0 0 0 0 0 0 0 0 0 0 ...
$ item10: num 0 47417 14500 0 0 ...
$ item11: num 333333 10000 25000 10000 2500 ...
$ item12: num 0 0 0 0 0 0 0 0 0 0 ...
$ item13: num 8333 7500 10000 5833 333 ...
$ item14: num 0 0 0 0 0 0 0 0 0 0 ...
$ item15: num 129167 43333 101667 44167 338333 ...
$ item16: num 0 0 0 0 0 0 0 0 0 0 ...
$ item17: num 0 0 0 0 750 0 375 0 0 1000 ...
> exp.nonfood$HHID<-as.character(exp.nonfood$HHID)# in Riel

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6.3 HOUSING# outfiles[[7]]: HHHousing> d<-outfiles[[7]]> nrow(d)[1] 3841

There is a duplicated HHID of "1300503", because the number of record is 3841.
> length(unique(d$HHID))[1] 3840> d[duplicated(d$HHID),]> d[duplicated(d$HHID),"HHID"][1] "1300503"> d[d$HHID=="1300503",]
pkid
HHID Q04_01 Q04_02 Q04_03 Q04_04 Q04_05 Q04_06 Q04_07 Q04_08 Q04_09 Q04_10M1
1598 1598 1300503
1
56
2
5
3
2
8
6
25
1
1601 1601 1300503
1
56
2
2
3
2
8
6
25
1
Q04_10M2 Q04_10M3 Q04_11 Q04_12 Q04_13 Q04_14M1 Q04_14M2 Q04_14M3 Q04_15 Q04_16 Q04_17
1598
2
NA
20
6
25
1
2
NA
NA
0
3
1601
2
NA
20
6
25
1
2
NA
20
0
3
Q04_18A Q04_18B Q04_18C Q04_18D Q04_18E Q04_19A Q04_19B Q04_20 Q04_21 Q04_22A Q04_22B
1598
NA
NA
NA
NA
NA
7
3
0
0
1
2
1601
NA
NA
NA
NA
NA
7
3
0
0
1
2
Q04_22C1 Q04_22C2 Q04_22C3 Q04_22D Q04_23A Q04_23B Q04_23C Q04_23D Q04_23E Q04_23F
1598
1
NA
NA
4
0
0
0
30000
0
0
1601
1
NA
NA
4
0
0
0
30000
0
0
Q04_23G Q04_24 Q04_25A Q04_25B Q04_26 EntryUser
ChangeDate
1598
8000
1
NA
80000
0
morokat 2012-06-25 18:17:00
1601
8000
1
NA
80000
0
morokat 2012-06-26 00:08:00


Dropped the record with pkid=1598, because the record with pkid=1601 is the latest entry.

> d<-subset(d,pkid!=1598)> dim(d)[1] 3840 51> sum(duplicated(d$HHID))[1] 0> outfiles[[7]]<-d# Variable descriptions> colnames(d)[1] "pkid""HHID""Q04_01"[8] "Q04_06""Q04_07""Q04_08"[15] "Q04_11""Q04_12""Q04_13"[22] "Q04_16""Q04_17""Q04_18A"[29] "Q04_19A""Q04_19B""Q04_20"[36] "Q04_22C2""Q04_22C3""Q04_22D"[43] "Q04_23E""Q04_23F""Q04_23G"[50] "EntryUser" "ChangeDate"
22
31
32
39
40

q04_16q04_20q04_21
q04_23aq04_23b"Q04_02""Q04_09""Q04_14M1""Q04_18B""Q04_21""Q04_23A""Q04_24""Q04_03""Q04_10M1""Q04_14M2""Q04_18C""Q04_22A""Q04_23B""Q04_25A""Q04_04""Q04_10M2""Q04_14M3""Q04_18D""Q04_22B""Q04_23C""Q04_25B""Q04_05""Q04_10M3""Q04_15""Q04_18E""Q04_22C1""Q04_23D""Q04_26"

water charges pay last month (riels)?
expenditure in sewage or waste water disposal last montlh?
how much did your hh spend for garbage collection lat month?
how much did the hh spend last month on electricity?
how much did the hh spend last month on gas (lpg)?

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122

41
42
43
44
45
47
48
49

q04_23c
how much did the hh spend last month on kerosene?
q04_23d
how much did the hh spend last month on firewood?
q04_23e
how much did the hh spend last month on charcoal?
q04_23f
how much did the hh spend last month on battery?
q04_23g
how much did the hh spend last month on other?
q04_25a
if rented, how much did you pay for rent of this house last month?
q04_25b how much would you have to pay per month to rent a similar dwelling? (estimatedq04_26 how much did you spend on maintenance and minor repairs of the dwelling last mon> df<-d[c(2,22,31,32,39:45,47:49)]> head(df)
HHID Q04_16 Q04_20 Q04_21 Q04_23A Q04_23B Q04_23C Q04_23D Q04_23E Q04_23F Q04_23G Q04_25A
1 0803010
0
0
0
14000
0
0
10000
0
6000
0
NA
2 2101910 40000
0
0
0
10000
0
20000
0
30000
0
NA
3 2101801
0
0
0
0
0
0
45000
0
10000
0
NA
4 1209101 5000
0
0
8000
0
0
15000
2000
0
0
NA
5 1209102 27700
0
0
38500
12000
0
21000
0
0
0
NA
6 0803009
0
0
0
0
0
0
40000
0
11000
0
NA
Q04_25B Q04_26
1
50000
0
2 100000
0
3
70000
0
4 120000
05 2800000
6 1600000> dim(df)[1] 3840 14> df[is.na(df)]<-0> df["housing"]<-rowSums(df[,2:14])> head(df)
HHID Q04_16 Q04_20 Q04_21 Q04_23A Q04_23B Q04_23C Q04_23D Q04_23E Q04_23F Q04_23G Q04_25A
1 0803010
0
0
0
14000
0
0
10000
0
6000
0
0
2 2101910 40000
0
0
0
10000
0
20000
0
30000
0
0
3 2101801
0
0
0
0
0
0
45000
0
10000
0
0
4 1209101 5000
0
0
8000
0
0
15000
2000
0
0
0
5 1209102 27700
0
0
38500
12000
0
21000
0
0
0
0
6 0803009
0
0
0
0
0
0
40000
0
11000
0
0
Q04_25B Q04_26 housing
1
50000
0
80000
2 100000
0 200000
370000
0 125000
4 120000
0 150000
5 280000
0 379200
6 160000
0 211000> colnames(df)<-c("HHID","water","sewage","garbage","electricity","gas","kerosene","firewood",+ "charcoal","battery","other","house.rent","imputed.rent","maintenance","housing")> head(df)
HHID water sewage garbage electricity
gas kerosene firewood charcoal battery other1 0803010
0
0
0
14000
0
0
10000
0
6000
0
2 2101910 40000
000 10000
0
20000
0
30000
0
3 2101801
0
0
0
0
0
0
45000
0
10000
0
4 1209101 5000
0
0
8000
0
0
15000
2000
0
0
5 1209102 27700
0038500 12000
0
21000
0
0
0
6 0803009
0
0
0
0
0
0
40000
0
11000
0

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1
2
3
4
5
6

house.rent imputed.rent maintenance housing
0
50000
0
80000
0
1000000 200000
070000
0 125000
01200000 150000
02800000 37920001600000 211000> exp.housing<-df> str(exp.housing)'data.frame':
3840 obs. of 15 variables:$ HHID: chr "0803010" "2101910" "2101801" "1209101" ...
$ water: int 0 40000 0 5000 27700 0 40000 14000 0 15000 ...
$ sewage: int 0 0 0 0 0 0 0 0 0 0 ...
$ garbage: int 0 0 0 0 0 0 0 0 0 0 ...
$ electricity : int 14000 0 0 8000 38500 0 0 35000 0 16000 ...
$ gas: int 0 10000 0 0 12000 0 0 0 0 2600 ...
$ kerosene: int 0 0 0 0 0 0 0 0 0 0 ...
$ firewood: int 10000 20000 45000 15000 21000 40000 45000 35000 40000 30000 ...
$ charcoal: int 0 0 0 2000 0 0 0 0 0 2400 ...
$ battery: int 6000 30000 10000 0 0 11000 10000 0 6000 0 ...
$ other: int 0 0 0 0 0 0 0 0 0 2000 ...
$ house.rent : num 0 0 0 0 0 0 0 0 0 0 ...
$ imputed.rent: num 50000 100000 70000 120000 280000 160000 100000 60000 100000 200000 ...
$ maintenance : num 0 0 0 0 0 0 0 0 0 0 ...
$ housing: num 80000 200000 125000 150000 379200 ...

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6.4

Total expenditureGrouping of items of expenditure

No

Group

Items

Data frame

Source data file1

Food and non-alcoholic

01 to 16, 19 to 21

exp.food

S01B.foodconsumption

beverages
2

Alcohol and tobacco

17, 18

exp.food

S01B.foodconsumption

3

Clothing and footwear

5, 11(personal effects)

exp.nonfood

S01C.nonfoodexpenses

4

Housing, water, electricity

exp.housing

S04.housing

5

Furnishing etc.

6, 7(domestic salaries)

exp.nonfood

S01C.nonfoodexpenses

6

Health1

exp.nonfood

S01C.nonfoodexpenses

7

Transportation2

exp.nonfood

S01C.nonfoodexpenses

8

Communication

3

exp.nonfood

S01C.nonfoodexpenses

9

Recreation and culture

8, 9

exp.nonfood

S01C.nonfoodexpenses

10

Education

10

exp.nonfood

S01C.nonfoodexpenses

11

Miscellaneous goods

13, 4(personal care)

exp.nonfood

S01C.nonfoodexpenses

Note: Item 12 (gambling) in non-food was excluded.
 Generated household-level data frame “hhexp” of monthly consumption by groups# Confirmed HHID of exp.food and exp.nonfood> table(exp.food$HHID==exp.nonfood$HHID)
TRUE
3840
> hhexp<-exp.food[,c("HHID","food","alcohol")]> hhexp$clothing<-rowSums(exp.nonfood[,c(6,12)])> head(hhexp)
hhid food alcohol clothing
1 100101 414700
03500
2 100102 388702
033333
3 100103 322401
34667
7667
4 100104 220134
0
30000
5 100105 756598
8667
25000
6 100106 772634
02500> hhexp<-merge(hhexp,exp.housing[,c("HHID","housing")],by="HHID",all.x=T)> head(hhexp)
HHID food alcohol clothing housing
1 0100301 407333
0366666 430000
2 0100302 428999
13000
36667 222000
3 0100303 578499
0125000 127000
4 0100304 420332
038333 225000
5 0100305 726266
56766
69167 169500
6 0100306 456300
0
58333
63000

Manual Cambodia CSES 2012 Version 2.0

125> dim(hhexp)[1] 3840
5> hhexp[is.na(hhexp)]<-0> hhexp$furnishing<- rowSums(exp.nonfood[,c(7,8)])> hhexp$health<-exp.nonfood[,2]> hhexp$transportation<-exp.nonfood[,3]> hhexp$communication<-exp.nonfood[,4]> hhexp$recreation<-rowSums(exp.nonfood[,c(9,10)])> hhexp$education<-exp.nonfood[,11]> hhexp$miscellaneous<- rowSums(exp.nonfood[,c(14,5)])> hhexp$total<-rowSums(hhexp[,2:12])> hhexp$foodshare<-round((hhexp$food+hhexp$alcohol)/hhexp$total*100,1)> head(hhexp)
HHID food alcohol clothing housing furnishing health transportation communication
1 0100301 407333
0366666 430000
0
0
40000
20000
2 0100302 428999
13000
36667 222000
15000
2000
17000
0
3 0100303 578499
0125000 127000
12500 200000
30000
8000
4 0100304 420332
038333 225000
5833 30000
20000
05 0100305 726266
56766
69167 169500
10833 165000
20000040000
6 0100306 456300
0
58333
63000
7917
0
40000
20000
recreation education miscellaneous
total foodshare
1
83333
0
8333 1355665
30.0
2
25000
47417
19500 826583
53.5
3
16667
14500
20000 1132166
51.1
4
25000
0
10833 775331
54.2
5
15833
0
14333 1467698
53.4
6
16667
34167
6583 702967
64.9

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

Estimate average monthly per household and per capita consumption by three region# hhexp: monthly household expenditure by group# outfiles[[36]]: household weight and region
Appended weight and region to hhexp> table(hhexp$HHID==outfiles[[36]]$HHID)
TRUE
3840
> hhexp<-cbind(hhexp,outfiles[[36]][c("hw12a","urbrur","Province_Code","region")])> head(hhexp)
HHID food alcohol clothing housing furnishing health transportation communication
1 0100301 407333
0366666 430000
0
0
40000
20000
2 0100302 428999
13000
36667 222000
15000
2000
17000
0
3 0100303 578499
0125000 127000
12500 200000
30000
8000
4 0100304 420332
038333 225000
5833 30000
20000
05 0100305 726266
56766
69167 169500
10833 165000
20000040000
6 0100306 456300
0
58333
63000
7917
0
40000
20000
recreation education miscellaneous
total foodshare
hw12a urbrur Province_Code region
1
83333
0
8333 1355665
30.0 1236.831
2
01
3
2
25000
47417
19500 826583
53.5 1236.831
2
01
3
3
16667
14500
20000 1132166
51.1 1236.831
2
01
3
4
25000
0
10833 775331
54.2 1236.831
2
01
3
5
15833
0
14333 1467698
53.4 1236.831
2
01
3
6
16667
34167
6583 702967
64.9 1236.831
201
3# Average monthly expenditure per household by group (in thousand Riels)> t1<-sapply(hhexp[,2:13],function(x) weighted.mean(x,hhexp$hw12a))/1000> data.frame(Item=names(t1),Value=round(t1),row.names=NULL)
Item Value
1

food

623

2

alcohol

30

3clothing

44

4

housing253

5

furnishing

12

6

health88

7transportation

71

8

communication

21

9

recreation

16

10

education55

11

miscellaneous

20

12

total

1232

Manual Cambodia CSES 2012 Version 2.0

127# Aveage monthly expenditure per household by group and region> (t<-by(hhexp,hhexp$region,function(df)+ round(sapply(df[,2:13],function(x) weighted.mean(x,df$hw12a)/1000))))hhexp$region: 1
food
alcohol
clothing
housingfurnishing
939
38
65
700
26
transportation communication
recreation
education miscellaneous
150
44
38
109
33
----------------------------------------------------------------------hhexp$region: 2
food
alcohol
clothing
housingfurnishing
787
39
58
406
15
transportation communication
recreation
education miscellaneous
95
32
29
100
25
----------------------------------------------------------------------hhexp$region: 3
food
alcohol
clothing
housingfurnishing
550
28
39
164
9
transportation communication
recreation
education miscellaneous
56
15
11
40
17
> m<-matrix(unlist(t),nrow=12)> colnames(m)<-c("Phnom Pen","Other urban","Other rural")> rownames(m)<-colnames(hhexp)[2:13]> cbind(Cambodia=round(t1),m)
Cambodia Phnom Pen Other urban Other rural
food

623

939

787

550

alcohol

30

38

39

28

clothing

44

65

58

39

housing

253

700

406

164

furnishing

12

26

15

9

health

88

53

87

92

transportation

71

150

95

56

communication

21

44

32

15

recreation

16

38

29

11

education

55

109

100

40

miscellaneous

20

33

25

17

1232

2194

1672

1023

total

Manual Cambodia CSES 2012 Version 2.0

health
53
total
2194

health
87
total
1672

health
92
total
1023

128




Comparison with the results of CSES2012 survey report
The amount of average monthly total household consumption in Table 6 is almost the same as
the above estimation.

# Average monthly expenditure per capita by item
> d<-outfiles[[36]]> NP<-sum(d$hhsize*d$hw12a)> NP[1] 14273806> t<-round(apply(hhexp[2:13],2,function(x) sum(x*hhexp$hw12a)/NP/1000))> data.frame(Item=names(t),Value=t,row.names=NULL)
Item Value
1

food

134

2

alcohol

7

3clothing

10

4

housing55

5

furnishing

3

6

health197transportation

15

8communication

4

9

recreation

4

10

education

12

11

miscellaneous

4

12

total

266

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129Manual Cambodia CSES 2012 Version 2.0

130Chapter 7. Household Income
7.0 Provided summary file of household income

According to the CSES 2012 report, the average monthly household income in 2012 was 1,019
thousand Riels.



The composition of household income was shown in the below table; wage income, agricultural
income, non-agricultural income, owner occupied house (imputed rent), property income andtransfers received.



The summary file of household income was provided in CSES 2009. It was not included in
CSES 2012 dataset provided in March 2015, however, it was provided on the occasion of theworkshop in 2018..

The document of “Income_Composition_CSES2009.doc” was provided in the previous time.
The estimation method of CSES 2012 followed this document in principle.

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

Summary file of houshold income: Incomehousehold_2012.sav

The income data file of CSES 2012 at household level was provided on the occasion of theworkshop 2018.

# Import SPSS data into R> library(foreign)> d2012<-read.spss("IncomeHousehold_2012.sav",to.data.frame=TRUE)> dim(d2012)[1] 3840 85> colnames(d2012)[1] "HHID""HW12A"[3] "PW12A""hhSize"[5] "Salary""DiarySalaryCash"[7] "DiarySalaryInkind""CostCrop"[9] "CostLivestock""CostFish"[11] "CostForestry""ReceiptCrop"[13] "ReceiptLivestock""ReceiptFish"[15] "ReceiptForestry""AgriIncome"[17] "CostNonAgri""ReceiptNonAgri"[19] "NonAgriIncome""IncomeOwnHouse"[21] "BankInterest""InterestOtherLoans"[23] "Dividends""RentFromLand"[25] "GrossPropertyIncome""InterestPaidAgri"[27] "InterestPaidNonAgri""InterestPaidOwnOccupied"[29] "InterestPaidNet""PropertyIncome"[31] "PrimaryIncome""PensionDomestic"[33] "PensionAbroad""Pension"[35] "NGOtransfers""RemittanceDomestic"[37] "RemittanceAbroad""TotalPrivateTransfers"[39] "ScholarshipGovernment""ScholarshipNGO"[41] "TotalScholarship""Gifts"[43] "OtherTransfer""TotalTransfers"[45] "TotalIncome""WageRatio"[47] "AgriRatio""OtherSelfEmpRatio"[49] "PropertyRatio""TransfersRatio"[51] "DiaryTaxes""DiaryInterHHtransfers"[53] "DiaryCashTransferChar""DiaryTotalNegativeTransfers"[55] "DisposableIncome""DiaryCostAgri"[57] "DiaryReceiptAgri""DiaryAgriIncome"[59] "DiaryCostNonAgri""DiaryReceiptNonAgri"[61] "DiaryNonAgriIncome""DiaryBankInterest"[63] "DiaryInterestOtherLoans""DiaryDividends"[65] "DiaryOtherFinancialAccount" "DiaryGrossPropertyIncome"[67] "DiaryPropertyIncome""DiaryPrimaryIncome"[69] "DiaryPensionDomestic""DiaryPensionAbroad"[71] "DiaryPension""DiaryInsuranceDomestic"[73] "DiaryInsuranceAbroad""DiaryNGOtransfers"

Manual Cambodia CSES 2012 Version 2.0

132[75] "DiaryRemittanceDomestic"[77] "DiaryTotalPrivateTransfers"[79] "DiaryGifts"[81] "DiaryTotalTransfers"[83] "DiaryDisposableIncome"[85] "DisposableIncome_Recall"> d<-d2012"DiaryRemittanceAbroad""DiaryScholarship""DiaryOtherTransfers""DiaryTotalIncome""TotalNegativeTransfers"# Weighted mean of each variable> t<-apply(d[4:85],2,function(x) weighted.mean(x,d$HW12A))> data.frame(Item=names(t),Mean=round(t/12000),row.names=NULL)
Item Mean
1
hhSize0
2
Salary 403
3
DiarySalaryCash
0
4
DiarySalaryInkind
0
5
CostCrop 82
6
CostLivestock 31
7
CostFish 12
8
CostForestry
1
9
ReceiptCrop 236
10
ReceiptLivestock 48
11ReceiptFish 32
12
ReceiptForestry 34
13
AgriIncome 223
14
CostNonAgri 878
15
ReceiptNonAgri 1139
16
NonAgriIncome 261
17
IncomeOwnHouse 98
18
BankInterest
1
19InterestOtherLoans
2
20
Dividends
3
21
RentFromLand
1
22
GrossPropertyIncome
623InterestPaidAgri
124InterestPaidNonAgri
025InterestPaidOwnOccupied
026
InterestPaidNet
1
27
PropertyIncome
528PrimaryIncome 990
29
PensionDomestic
430
PensionAbroad
031
Pension4
32
NGOtransfers
133
RemittanceDomestic 12
34
RemittanceAbroad 10
35
TotalPrivateTransfers 22
36
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37
ScholarshipNGO
038
TotalScholarship
1
39
Gifts
4
40
OtherTransfer
341
TotalTransfers 35
42
TotalIncome 1025
43
WageRatio
044
AgriRatio
045
OtherSelfEmpRatio
046
PropertyRatio
047
TransfersRatio
048
DiaryTaxes
049
DiaryInterHHtransfers
050
DiaryCashTransferChar
0
51 DiaryTotalNegativeTransfers
052
DisposableIncome
053
DiaryCostAgri
054
DiaryReceiptAgri
055
DiaryAgriIncome
056
DiaryCostNonAgri
057
DiaryReceiptNonAgri
058
DiaryNonAgriIncome
059
DiaryBankInterest
060
DiaryInterestOtherLoans
061
DiaryDividends
0
62 DiaryOtherFinancialAccount063
DiaryGrossPropertyIncome
064
DiaryPropertyIncome
065
DiaryPrimaryIncome
066
DiaryPensionDomestic
067
DiaryPensionAbroad
068
DiaryPension
069
DiaryInsuranceDomestic
070
DiaryInsuranceAbroad
071
DiaryNGOtransfers
072
DiaryRemittanceDomestic
073
DiaryRemittanceAbroad
0
74 DiaryTotalPrivateTransfers
075
DiaryScholarship076
DiaryGifts
077
DiaryOtherTransfers
078
DiaryTotalTransfers
079
DiaryTotalIncome
080
DiaryDisposableIncome
081
TotalNegativeTransfers NA
82
DisposableIncome_Recall 1020

Manual Cambodia CSES 2012 Version 2.0

134# Comparison with the survey report

Source of income

Report (p)Computed from2012

IncomeHousehold_2012

Primary income

984

Salary403

Self employment

576

Agriculture

229

223

Non-agriculture

249

261

Own house98

98

Property income

55Transfers received

35

35

Total income

1019

1025

Transfers paid / negative
incomeDisposable income

403

5
1014

1020

3840

3840

Remarks
No. of records
Almost the same as the report.

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

Estimation of each income componentIncome composition by source of income will be discussed in the following sections.

Source of income

Section in this chapter

Primary income
Wage and salary

7.1

Self employment
Agriculture

7.2

Non-agriculture

7.3

Own house

7.4

Property income

7.5Transfers received

7.6

Total income
Transfers paid / negative income

7.7

Disposable incomePrepared data frame of monthly household income with variables of income components.

INCOME# hhinc: Household-level data frame of income componemts to be generated.
> hhinc<-outfiles[[36]][,c("HHID","hw12a","hhsize")]> head(hhinc)
HHID

hw12a hhsize

1 0100301 1236.831

2

2 0100302 1236.831

53 0100303 1236.831

84 0100304 1236.831

55 0100305 1236.831

5

6 0100306 1236.831

3> dim(hhinc)[1] 3840

3> HHID<-hhinc$HHID> length(HHID)[1] 3840

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7.1 WAGE AND SALARY
No

Variable of incomeFilecomponentNosalary31

SectionVariables to be usedperiod15

Q15_C20# outfiles[[31]]: 15. Economic status# Q15_C20: salary/wage earned during the last month> d<-outfiles[[31]][,c("PID","HHID","Q15_C20")]> dim(d)[1] 16086

3> head(d)PID

HHID Q15_C20

1 080301001 0803010

NA

2 080301002 0803010

NA

3 080301003 0803010

NA

4 080301004 0803010

NA

5 120910101 1209101

NA

6 120910102 1209101

400000> d[is.na(d)]<-0> t<-tapply(d$Q15_C20,d$HHID,sum)> df<-data.frame(HHID=names(t),salary=t)> dim(df)[1] 3840

2> head(df)HHIDsalary0100301 0100301

00100302 0100302

8500000100303 0100303 1630000
0100304 0100304

8800000100305 0100305

00100306 0100306

0Reference

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137

> hhinc<-merge(hhinc,df,by="HHID",all.x=T)> hhinc[is.na(hhinc)]<-0> head(hhinc)
HHID

hw12a hhsize

salary1 0100301 1236.831

20

2 0100302 1236.831

58500003 0100303 1236.831

8 1630000

4 0100304 1236.831

58800005 0100305 1236.831

50

6 0100306 1236.831

30> hhinc.save<-hhincWeighted mean of monthly salary (in Riels)> weighted.mean(hhinc$salary,hhinc$hw12a)[1] 402574.9

Summary: The estimated value of monthly wage income is 403 thousand Riels, andcompletely the same as the survey report.

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7.2 AGRI INCOME
Generated the following variables of monthly agricultural income, principally
following CSES 2009.

No

Variable ofFileincome componentNoSectionVariables to be used

Reference
periodCOST
1cost.crop

105C

Q05CC16 (Total of col. 3-15)

12M

2

cost.livestock1

13

5E1

Q05E1C10 (Total paid for)12M

3

cost.livestock2

14

5E2

Q05E2C03 (Spend on livestock)

12M

4

cost.fish1

15

5F1

Q05F1C05 (Monthly rent)

1M

5

cost.fish2

16

5F2

Q05F2C03 (Amount spent)

12M

6

cost.forestry

19

5G2

Q05G2C03 (Amount spent)

12M

7interest.agri

23

6

Subset of Q06_C05==1 (Agricultural),

1M

Q06_C08*Q06_C07/(100+Q06_C08)(Household liabilities)
RECEIPT8

rcpt.crop

09

5B(Q05BC06 –Q05BC07) x Q05BC09

12M(production of crops)9

rcpt.livestock

13

5E1

Q05E1C09 + Q05E1C11 to Q05E1C15

12M(Sold, own consumption, gift, etc.)10rcpt.fish

17

5F3

Q05F3C03 (Amount received)

12M

11

rcpt.forestry

18

5G1

Q05G1C06 (Total amount of products)

12M

12

agri.income

The above receipts - costs

Note: Some of “variables to be used” in the above table are sum of items.
Consistency check should be crucial.

1) Cost.crop> d<-outfiles[[10]][,c("HHID","Q05CC16")]> d[is.na(d)]<-0> t<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(t),cost.crop=t)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)> head(hhinc)
HHID
hw12a hhsize salary cost.crop
1 0100301 1236.831
2
0 405833.3
2 0100302 1236.831
5 850000NA

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3 0100303 1236.831
4 0100304 1236.831
5 0100305 1236.831
6 0100306 1236.831

8 1630000
5 880000
5
0
3
0

NA
NA
538000.0105875.0

Remarks: Data check
One record with inconsistency is corrected.
> d<-outfiles[[10]]> colnames(d)[1] "pkid""HHID""WetDry""Q05CC01""Q05CC02""Q05CC03"[7] "Q05CC04""Q05CC05""Q05CC06""Q05CC07""Q05CC08""Q05CC09"[13] "Q05CC10""Q05CC11""Q05CC12""Q05CC13""Q05CC14""Q05CC15"[19] "Q05CC16""EntryUser" "ChangeDate"> d[is.na(d)]<-0> table(d$Q05CC16==rowSums(d[6:18]))
FALSE TRUE
1 4033> d[d$Q05CC16!=rowSums(d[6:18]),]pkid
HHID WetDry Q05CC01 Q05CC02 Q05CC03 Q05CC04 Q05CC05 Q05CC06 Q05CC07
367 368 0602307
1
1
1 460000 180000 150000
00Q05CC08 Q05CC09 Q05CC10 Q05CC11 Q05CC12 Q05CC13 Q05CC14 Q05CC15 Q05CC16
367
10000
6e+05 1200000
0
0
0
0
40000
0
EntryUser
ChangeDate
367
Noeun 2012-03-02 18:50:00> d$Q05CC16<-rowSums(d[6:18])> outfiles[[10]]<-d2) Cost.livestock1> d<-outfiles[[13]][,c("HHID","Q05E1C10")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID =names(df),cost.livestock1=df)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

3) Cost.livestock2> d<-outfiles[[14]][,c("HHID","Q05E2C03")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),cost.livestock2=df)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

4) Cost.fish1> d<-outfiles[[15]][,c("HHID","Q05F1C05")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),cost.fish1=df)> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

Manual Cambodia CSES 2012 Version 2.0

1405) Cost.fish2> d<-outfiles[[16]][,c("HHID","Q05F2C03")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),cost.fish2=df)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

6) Cost.forestry> d<-outfiles[[19]][,c("HHID","Q05G2C03")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),cost.forestry=df)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

7) Interest.agri> hhinc.save<-hhinc> d<-subset(outfiles[[23]],Q06_C05==1)> d[is.na(d)]<-0> d$int<-d$Q06_C08*d$Q06_C07/(100+d$Q06_C08)> df<-tapply(d$int,d$HHID,sum)> df<-data.frame(HHID =names(df),interest.agri=df)> hhinc<-merge(hhinc,df,by="HHID",all.x=T)> head(hhinc)
HHID
hw12a hhsize salary cost.crop cost.livestock1 cost.livestock2
1 0100301 1236.831
2
0 405833.3
NANA
2 0100302 1236.831
5 850000NA
05833.333
3 0100303 1236.831
8 1630000
NANA
NA
4 0100304 1236.831
5 880000
NANANA
5 0100305 1236.831
50 538000.001083.333
6 0100306 1236.831
30 105875.0
NANA
cost.fish1 cost.fish2 cost.forestry interest.agri
1NANA
0.0000NA
2
NA 1666.6667
0.0000NA
3NA 2500.0000
0.0000NA
4NA 7500.0000
0.0000NA
5NA 14166.6667
583.3333
203883.50
6NA
458.3333
333.3333
20388.35

8) Receipt.crop> d<-outfiles[[9]][,c("HHID","Q05BC06","Q05BC07","Q05BC09")]> d[is.na(d)]<-0> d$rcpt<-(d[,2]-d[,3])*d[,4]> head(d)HHID Q05BC06 Q05BC07 Q05BC09
rcpt
1 2101910
2250
50
950 2090000
2 2101910
200
10
1400
2660003 2101910 21150
150
950 19950000
4 2101801
720
0
1000
7200005 2101801
240
0
1000
2400006 2101801
150
0
1000
150000Manual Cambodia CSES 2012 Version 2.0

141> df<-tapply(d$rcpt,d$HHID,sum)> df<-data.frame(HHID=names(df),rcpt.crop=df)> df[,2]<-df[,2]/12> dim(df)[1] 1976
2> head(df)
HHID rcpt.crop
0100301 0100301 580416.67
0100305 0100305 1197333.33
0100306 0100306
81516.67
0100307 0100307 111562.50
0100310 0100310 485916.67
0100601 0100601 660000.00> hhinc<-merge(hhinc,df,by="HHID",all.x=T)
Remarks 1:
What if "Q05BC07" and "Q05BC08" are subtracted from "Q05BC06" ?
> d<-outfiles[[9]][,c("HHID","Q05BC06","Q05BC07","Q05BC08","Q05BC09")]> d[is.na(d)]<-0> d$rcpt2<-(d[,2]-d[,3]-d[,4])*d[,5]> df<-tapply(d$rcpt2,d$HHID,sum)> df<-data.frame(HHID=names(df),rcpt.crop2=df)> df[,2]<-df[,2]/12> dim(df)[1] 19762> df<-merge(outfiles[[36]],df,by="HHID",all.x=T)> df[is.na(df)]<-0> weighted.mean(df$rcpt.crop2,df$hw12a)[1] 414291.3
The mean values per household are 420,000 and 414,000. The difference is small.

Remarks 2:
What if the questionnaire 05.D.2 (Sales of crops) is used for receipt?
> d<-outfiles[[12]] # HHSalesCrops> colnames(d)[1] "pkid""HHID""Q05D1C1""Q05D1C2"[7] "EntryUser" "ChangeDate"> d[is.na(d)]<-0> d$crop3<-d$Q05D1C3*d$Q05D1C4> df<-tapply(d$crop3,d$HHID,sum)> df<-data.frame(HHID=names(df),crop3=df)> df[2]<-df[2]/12> df<-merge(outfiles[[36]],df,by="HHID",all.x=T)> df[is.na(df)]<-0> weighted.mean(df$crop3,df$hw12a)[1] 130526.4
"Q05D1C3"

The mean value per household is 130,526.

Manual Cambodia CSES 2012 Version 2.0"Q05D1C4"

1429) Receipt.livestock> hhinc.save<-hhinc> d<-outfiles[[13]][,c("HHID","Q05E1C09","Q05E1C11","Q05E1C12","Q05E1C13",+ "Q05E1C14","Q05E1C15")]> d[is.na(d)]<-0> d$rcpt<-rowSums(d[,2:7])> df<-tapply(d$rcpt,d$HHID,sum)> df<-data.frame(HHID=names(df),rcpt.livestock=df)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

10) Receipt.fish> d<-outfiles[[17]][,c("HHID","Q05F3C03")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),rcpt.fish=df)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

11) Receipt.forestry> d<-outfiles[[18]][,c("HHID","Q05G1C06")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),rcpt.forestry=df)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)> head(hhinc)
HHID
hw12a hhsize salary cost.crop cost.livestock1 cost.livestock2
1 0100301 1236.831
2
0 405833.3
NANA
2 0100302 1236.831
5 850000NA
05833.333
3 0100303 1236.831
8 1630000
NANA
NA
4 0100304 1236.831
5 880000
NANANA
5 0100305 1236.831
50 538000.001083.333
6 0100306 1236.831
30 105875.0
NANA
cost.fish1 cost.fish2 cost.forestry interest.agri rcpt.crop rcpt.livestock1NANA0.0000NA 580416.67
NA2
NA 1666.6667
0.0000NA
NA6250.000
3NA 2500.0000
0.0000NANANA
4NA 7500.0000
0.0000NANANA
5NA 14166.6667
583.3333
203883.50 1197333.33
3333.3336NA458.3333
333.3333
20388.35
81516.67
NA
rcpt.fish rcpt.forestry
1NA20000.000
2 30833.33
16666.667
3 47500.00
4416.667
4 26666.67
22500.000
5 41666.67
14166.667
6 10833.33
29166.667

12) Agri.income> hhinc[is.na(hhinc)]<-0> hhinc$agri.income<-rowSums(hhinc[,12:15])-rowSums(hhinc[,5:11])> head(hhinc)Manual Cambodia CSES 2012 Version 2.0

143

HHID
hw12a hhsize salary cost.crop cost.livestock1 cost.livestock2
1 0100301 1236.831
2
0 405833.3
00.000
2 0100302 1236.831
5 8500000.0
05833.333
3 0100303 1236.831
8 1630000
0.0
0
0.000
4 0100304 1236.831
5 880000
0.0
0
0.000
5 0100305 1236.831
50 538000.001083.333
6 0100306 1236.831
30 105875.0
00.000
cost.fish1 cost.fish2 cost.forestry interest.agri rcpt.crop rcpt.livestock
100.00000.00000.00 580416.67
0.000
20 1666.6667
0.00000.00
0.00
6250.000
30 2500.0000
0.0000
0.00
0.00
0.000
4
0 7500.0000
0.0000
0.00
0.00
0.000
5
0 14166.6667
583.3333
203883.50 1197333.33
3333.333
6
0458.3333
333.3333
20388.35
81516.67
0.000
rcpt.fish rcpt.forestry agri.income
1
0.00
20000.000
194583.33
2 30833.33
16666.667
46250.00
3 47500.00
4416.667
49416.67
4 26666.67
22500.000
41666.67
5 41666.67
14166.667
498783.17
6 10833.33
29166.667-5538.35> hhinc.save1<-hhincWeighted mean of monthly agricultural income> t<-round(sapply(hhinc[,c(5:16)],function(x) weighted.mean(x,hhinc$hw12a)))> data.frame(Item=names(t),Value=round(t),row.names=NULL)
Item

Value

1

cost.crop

81913

2

cost.livestock1

11726

3

cost.livestock2

19067

4

cost.fish1

1646

5

cost.fish2

10372

6

cost.forestry

1374

7

interest.agri

7511

8

rcpt.crop 419872

9rcpt.livestock

47643

10

rcpt.fish

32027

11

rcpt.forestry

34494

12

agri.income 400426

Summary Weighted mean of each component variable, except “rcpt.crop”,in the above table seems proper.
The sum of “agri.income”
Agriculture income in the survey report of CSES 2012 is 229,000 Riels.

Manual Cambodia CSES 2012 Version 2.0

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7.3 NON-AGRI INCOME
No

Variable of incomeFilecomponent

No

SectionVariables to be used

Reference
periodCOST
1cost.nonagri

21

5H2

Q05H2C03 to Q05H2C08

12M

2interest.nonagri

23

6

Subset of Q06_C05==2,

1M

Q06_C08*Q06_C07/(100+Q06_C08)
RECEIPT3

rcpt.nonagri

22

5H3

Subset of Q05H3C01 != 13,

12M

Q05H3C03 to Q05H3C08
4

nonagri.income

The above receipts - costs

1) Cost.nonagri> d<-outfiles[[21]]> d[is.na(d)]<-0> d$cost<-rowSums(d[,4:9])> df<-tapply(d$cost,d$HHID,sum)> df<-data.frame(HHID=names(df),cost.nonagri=df)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

2) Interest.nonagri> d<-subset(outfiles[[23]],Q06_C05==2)> d[is.na(d)]<-0> d$int<-d$Q06_C08*d$Q06_C07/(100+d$Q06_C08)> df<-tapply(d$int,d$HHID,sum)> df<-data.frame(HHID=names(df),interest.nonagri=df)> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

3) Receipt.nonagri> d<-subset(outfiles[[22]],Q05H3C01!=13)> d[is.na(d)]<-0> d$rcpt<-rowSums(d[,4:9])> df<-tapply(d$rcpt,d$HHID,sum)> df<-data.frame(HHID=names(df),rcpt.nonagri=df)> df[,2]<-df[,2]/12> hhinc<-merge(hhinc,df,by="HHID",all.x=T)

4) Nonagri.income> hhinc[is.na(hhinc)]<-0> hhinc$nonagri.income<-hhinc$rcpt.nonagri-hhinc$cost.nonagri-hhinc$interest.nonagri> head(hhinc)Manual Cambodia CSES 2012 Version 2.0

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HHID
hw12a hhsize salary cost.crop cost.livestock1 cost.livestock2
1 0100301 1236.831
2
0 405833.3
405833.3
0.000
2 0100302 1236.831
5 8500000.0
0.0
5833.333
3 0100303 1236.831
8 1630000
0.0
0.0
0.000
4 0100304 1236.831
5 880000
0.0
0.0
0.000
5 0100305 1236.831
50 538000.0
538000.01083.333
6 0100306 1236.831
30 105875.0
105875.0
0.000
cost.fish1 cost.fish2 cost.forestry interest.agri rcpt.crop rcpt.livestock
100.00000.0000
0.00
0
0.000
2
0 1666.6667
0.00000.00
06250.000
30 2500.0000
0.0000
0.00
0
0.000
4
0 7500.0000
0.0000
0.00
0
0.000
5
0 14166.6667
583.3333
203883.50
03333.333
6
0458.3333
333.3333
20388.35
00.000
rcpt.fish rcpt.forestry agri.income cost.nonagri interest.nonagri
1
0.00
20000.000 -791666.67
567083.33
02 30833.33
16666.667
46250.00
0.00
03 47500.00
4416.667
49416.67
0.00
04 26666.67
22500.000
41666.67
0.00
05 41666.67
14166.667 -1236550.16
99416.67
0
6 10833.33
29166.667 -192930.02
0.00
0
rcpt.nonagri nonagri.income
1817083.3
250000.00
2
0.0
0.00
3
0.0
0.00
4
0.0
0.00
5
183333.3
83916.67
6
0.0
0.00> hhinc.save2<-hhincWeighted mean of non-agri income> round(sapply(hhinc[,17:20],function(x) weighted.mean(x,hhinc$hw12a)))cost.nonagri interest.nonagri
rcpt.nonagri
nonagri.income
8775185538
1139291
256235Manual Cambodia CSES 2012 Version 2.0

146

7.4 INCOME OWN HOUSE

Estimating imputed rent is a very difficult work. The survey report CSES 2009 described about
this at page 102, as below.

“The method that is used in CSES originates from the view that income from owner occupied
house can be treated as an investment and that one can look for an alternative investment of thecapital in the owner occupied house. This alternative investment can be the long-term returnfrom Government bonds. Income from owner-occupied dwellings and houses is calculated bysubtract the remaining debt from the market value of the dwelling. This value is multiplied by
the long-term interest for Government bonds. A problem with this method is that it can yield
unreasonable high estimates of imputed rent in large cities with high land values. In Cambodia
this is the case in Phnom Penh. To prevent unreasonable high values of imputed rent to distort
the results, imputed rent is limited to a maximum 12 million Riels per year.”

Variables used
Item

File

SectionVariables to be usedNo

periodLong-term interest fora constant of 3%, which is considered

Government bonds

an annual rate

Market value of the

25

08

dwelling

Q08_C05: How much would you have to pay
to buy a building like this in thevillage? (in Riels)

Outstanding loan

2306Subset of Q06_C05==7: Primary purpose= Purchase/improvement of dwelling
Q06_C07: How much is the outstanding
loan now (this month)? Interest should
not be included. (in Riels)

Interest rate

23

Reference

06

Q06_C08: If interest is charged, whatis the monthly rate of interest? (%)

income.ownhouse1{Q08_C05 – Q06_C07/(1+Q06_C08/100)}*0.03/12

income.ownhouse2

Min{income.ownhouse1, 12*10^6}Manual Cambodia CSES 2012 Version 2.0

147

Note:
 It is not clear whether the 3% of the long-term interest for Government bonds is monthly or annual.
 The median of q06_c08 (monthly interest rate) is 3%.
 In 7,532 cases, the results of using 3% as annual rate are the same as Yearly.Income. This supportsthat the 3% is annual rate.
1) Market value of the dwelling> oh<-outfiles[[36]][,c("HHID","hw12a","hhsize")]> d<-outfiles[[25]][,c("HHID","Q08_C05")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),market.value=df)> oh<-merge(oh,df,by="HHID",all.x=T)> head(oh)HHID
hw12a hhsize market.value
1 0100301 1236.831
2
1.7e+07
2 0100302 1236.831
51.2e+07
3 0100303 1236.831
8
1.2e+07
4 0100304 1236.831
51.3e+07
5 0100305 1236.831
54.0e+07
6 0100306 1236.831
3
2.5e+06

2) Remaining debt
> d<-outfiles[[23]][,c("HHID","Q06_C05","Q06_C07","Q06_C08")]> dim(d)[1] 13654> d<-subset(d,Q06_C05==7)> dim(d)[1] 94 4> head(d)HHID Q06_C05 Q06_C07 Q06_C08
16 2101806
7 3600000
1.8
26 0501901
7 1000000
0.0
27 0700904
7 3200000
0.0
45 0700808
7 800000
3.0
48 1501008
7 2000000
3.0
62 1205110
7 2864000
2.0> d$remaining.debt<-d$Q06_C07/(1+d$Q06_C08/100)> head(d)HHID Q06_C05 Q06_C07 Q06_C08 remaining.debt
16 2101806
7 3600000
1.83536346
26 0501901
7 1000000
0.0
1000000
27 0700904
7 3200000
0.03200000
45 0700808
7 800000
3.0
77669948 1501008
7 2000000
3.0
1941748
62 1205110
7 2864000
2.02807843> df<-tapply(d$remaining.debt,d$HHID,sum)> df<-data.frame(HHID=names(df),remaining.debt=df)> oh<-merge(oh,df,by="HHID",all.x=T)> head(oh)HHID
hw12a hhsize market.value remaining.debt
1 0100301 1236.831
2
1.7e+07NA
2 0100302 1236.831
51.2e+07
NA

Manual Cambodia CSES 2012 Version 2.0

148

3 0100303 1236.831
4 0100304 1236.831
5 0100305 1236.831
6 0100306 1236.831

8
5
5
3

1.2e+07
1.3e+074.0e+072.5e+06

NA
NA
NA
NA

3) Monthly income.ownhouse> oh[is.na(oh)]<-0> oh$income.ownhouse1<-(oh$market.value-oh$remaining.debt)*0.03/12> oh$income.ownhouse2<-ifelse(oh$income.ownhouse1>10^6,10^6,oh$income.ownhouse1)> head(oh)HHID
hw12a hhsize market.value remaining.debt income.ownhouse1
1 0100301 1236.831
2
1.7e+07042500
2 0100302 1236.831
51.2e+07030000
3 0100303 1236.831
8
1.2e+07030000
4 0100304 1236.831
51.3e+07032500
5 0100305 1236.831
54.0e+070
1000006 0100306 1236.831
3
2.5e+0606250
income.ownhouse2
1
42500
2
30000
3
30000
4
32500
5
10000066250



The value of income.ownhouse1 was replaced with the upper limit in 82 cases.

> table(oh$income.ownhouse1>10^6)
FALSE TRUE
3758
82



Weighted mean of income own house> round(sapply(oh[,4:7],function(x) weighted.mean(x,oh$hw12a)))market.value
remaining.debt income.ownhouse1 income.ownhouse2
39905134
13716499420
90503

Remarks: (CSES 2009)
The delegates from Cambodia to the seventh workshop explained the concept and definition of
imputed rent used in SES as follows;“The respondent was asked to impute for their own house but in case they could not impute therespondent was asked impute the same price of the closed (in the village) house has been rented withthe similar characteristic of their own housing. “Manual Cambodia CSES 2012 Version 2.0

149

7.5 PROPERTY INCOME
No

Item

File

SectionVariables to be usedNo1bank.interest

24

Reference
period07

Subset of Q07_C01==7

12M

Q07_C05
2

interest.otherloans

2407Subset of Q07_C01==912M

Q07_C053

dividents

24

07

Subset of Q07_C01==8

12M

Q07_C05
4

rent.fromland

22

05H3

Subset of Q05H3C01==13

12M

Q05H3C03 to Q05H3C08: Activities
5

gross.property.income

Sum of the above four items

12M

6interest.paidnet

23

1M

06

Subset of Q06_C05==3-6, 8-10
Q06_C08*Q06_C07/(100+Q06_C08)
q06_c05:What was the primary purpose forwhich your household borrowed the money?

7

property.income= gross.property.income (minus) interest.paidnet

primary.income

Sam of 7.1 to 7.5> pi<-outfiles[[36]][,c("HHID","hw12a","hhsize")]

1) Bank interest> d<-subset(outfiles[[24]],Q07_C01==7)[,c("HHID","Q07_C05")]> dim(d)[1] 83 2> head(d)HHID Q07_C05
125 1205010 4600000
135 1201301
860000150 1201307 1600000
162 1201310
800000754 0401403 2000000
1160 1206909 14600000> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),bank.interest=df)> df[,2]<-df[,2]/12> pi<-merge(pi,df,by="HHID",all.x=T)> pi[is.na(pi)]<-0> head(pi)Manual Cambodia CSES 2012 Version 2.0

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HHID
hw12a hhsize bank.interest
1 0100301 1236.831
20
2 0100302 1236.831
50
3 0100303 1236.831
80
4 0100304 1236.831
50
5 0100305 1236.831
50
6 0100306 1236.831
302) Interest.otherloans> d<-subset(outfiles[[24]],Q07_C01==9)[,c("HHID","Q07_C05")]> dim(d)[1] 91 2> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),interest.otherloans=df)> df[,2]<-df[,2]/12> pi<-merge(pi,df,by="HHID",all.x=T)> pi[is.na(pi)]<-0

3) Dividents> d<-subset(outfiles[[24]],Q07_C01==8)[,c("HHID","Q07_C05")]> dim(d)[1] 76 2> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),dividents=df)> df[,2]<-df[,2]/12> pi<-merge(pi,df,by="HHID",all.x=T)> pi[is.na(pi)]<-0> pi.save<-pi4) Rent from land
> d<-subset(outfiles[[22]],Q05H3C01==13)> dim(d)[1] 30 11> d[is.na(d)]<-0> head(d)pkid
HHID Q05H3C01 Q05H3C03 Q05H3C04 Q05H3C05 Q05H3C06 Q05H3C07
54
56 1201402
13 8640000
0
0
0
0
56
58 1201403
13 23040000
0
0
0
0
74
76 1205109
13 7200000
0000846 851 0803501
13
0
0
0
0
0
867 872 0803502
13
0
0
0
0
0
889 894 0803503
13
0
0
0
0
0
Q05H3C08 EntryUser
ChangeDate540
tey 2012-02-25 00:02:00
56
0
tey 2012-02-25 00:28:00
74
0riya 2012-02-27 19:02:00
846
0
tey 2012-11-22 19:45:00
867
0
tey 2012-11-23 00:17:00
889
0
tey 2012-11-23 01:12:00> d$rent<-rowSums(d[,4:9])> df<-tapply(d$rent,d$HHID,sum)

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151> df<-data.frame(HHID=names(df),rent.fromland=df)> df[,2]<-df[,2]/12> pi<-merge(pi,df,by="HHID",all.x=T)> pi[is.na(pi)]<-0> pi.save<-pi5) Gross property income> pi$grossproperty.income<-rowSums(pi[,4:7])> head(pi)HHID
hw12a hhsize bank.interest interest.otherloans dividents
1 0100301 1236.831
20002 0100302 1236.831
50003 0100303 1236.831
80004 0100304 1236.831
50005 0100305 1236.831
5000
6 0100306 1236.831
3000rent.fromland grossproperty.income
1
0
0
2
0
0
3
0
0
4
0
0
5
0
0
6
0
0

6) Interest paid net> d<-subset(outfiles[[23]],is.element(Q06_C05,c(3:6,8:10)))> dim(d)[1] 696 12> d[is.na(d)]<-0> d$paid<-d$Q06_C08*d$Q06_C07/(100+d$Q06_C08)> df<-tapply(d$paid,d$HHID,sum)> df<-data.frame(HHID=names(df),interest.paidnet=df)> pi<-merge(pi,df,by="HHID",all.x=T)> pi[is.na(pi)]<-0> pi.save<-pi7) Property income> pi$property.income<-pi$grossproperty.income-pi$interest.paidnet> head(pi)HHID
hw12a hhsize bank.interest interest.otherloans dividents
1 0100301 1236.831
20002 0100302 1236.831
50003 0100303 1236.831
80004 0100304 1236.831
50005 0100305 1236.831
5000
6 0100306 1236.831
3000rent.fromland grossproperty.income interest.paidnet property.income
1
0
0
0
0
2
0
0
0
0
3
0
0
0
0
4
0
0
0
0
5
0
0
0
0
6
0
0
0
0

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152> pi.save<-piWeighted mean

> round(sapply(pi[,4:10],function(x) weighted.mean(x,hhinc$hw12a)))bank.interest interest.otherloans
dividents
534
1808
3170
rent.fromland grossproperty.income
interest.paidnet
700
6213
10759
property.income-4547> table(pi$property.income>0)
FALSE TRUE3804
36
> table(pi$property.income<0)
FALSE TRUE
3292
548
> table(pi$property.income==0)
FALSE TRUE
584 3256

Remarks;
Property income is positive in 36cases, and negative in 548 cases.

# Appended income.ownhouse and property.income to hhinc> hhinc.save<-hhinc> hhinc<-merge(hhinc,oh[,c("HHID","income.ownhouse2")],by="HHID",all.x=T)> hhinc.save<-hhinc> hhinc<-merge(hhinc,pi[,-2],by="HHID",all.x=T)> hhinc.save<-hhinc# Generated primary income.
> colnames(hhinc)[1] "HHID""hw12a""hhsize.x"[4] "salary""cost.crop""cost.livestock1"[7] "cost.livestock2""cost.fish1""cost.fish2"[10] "cost.forestry""interest.agri""rcpt.crop"[13] "rcpt.livestock""rcpt.fish""rcpt.forestry"[16] "agri.income""cost.nonagri""interest.nonagri"[19] "rcpt.nonagri""nonagri.income""income.ownhouse2"[22] "hhsize.y""bank.interest""interest.otherloans"[25] "dividents""rent.fromland""grossproperty.income"[28] "interest.paidnet""property.income"> hhinc$primary.income<-rowSums(hhinc[,c(4,16,20,21,29)])

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7.6 TRANSFERS RECEIVED
No

Item

File

SectionVariables to be usedNo1

pension.domestic

24

Reference
period07

Subset of Q07_C01==1

12M

Q07_C032

pension.abroad

24

07

Subset of Q07_C01==1

12M

Q07_C043

pension=pension.domestic + pension.abroad

12M

4ngo.transfer

24

12M

07

Subset of Q07_C01==5
Q07_C05

5

remittance.domestic1

24

07

Subset of Q07_C01==2: Remittances

12M

from other relatives or others(notreported in current migration
section)
Q07_C03
remittance.domestic2

903B

Subset of q03bc05b>0: Total value

12Mof the transfers and cash gifts
sent to the household
q03bc12
6

remittance.abroad1

24

07

Subset of Q07_C01==2

12M

Q07_C04
remittance.abroad2

903B

Subset of q03bc05c>0

12M

q03bc12
7

total.private.transfers

8

scholarship.governmen= remittance.domestic + remittance.abroad

12M

24

12M

07

t
9

scholarship.ngo

Subset of Q07_C01==3
Q07_C05

24

07

Subset of Q07_C01==4

12M

Q07_C05
10

total.scholarship= scholarship.government + scholarship.ngo

12M

11

gifts

24

12M

07

Subset of Q07_C01==10,11
Q07_C05

12

other.transfer

2407Subset of Q07_C01==12

12M

Q07_C05

13

total.transfers

Sum of the above 6 items

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12M

154

Remarks: The questionnaire of 03B which existed in CSES 2009 is no more available in CSES 2012.
> tr<-outfiles[[36]][,c("HHID","hw12a","hhsize")]

1) Pension domestic> d<-subset(outfiles[[24]],Q07_C01==1)[,c("HHID","Q07_C03")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),pension.domestic=df)> df[,2]<-df[,2]/12> tr<-merge(tr,df,by="HHID",all.x=T)> tr[is.na(tr)]<-02) Pension abroad> d<-subset(outfiles[[24]],Q07_C01==1)[,c("HHID","Q07_C04")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),pension.abroad=df)> df[,2]<-df[,2]/12> tr<-merge(tr,df,by="HHID",all.x=T)> tr[is.na(tr)]<-0

3) Total pension> tr$pension<-tr$pension.domestic+tr$pension.abroad> tr.save<-tr> head(tr)HHID
hw12a hhsize pension.domestic pension.abroad pension
1 0100301 1236.831
20002 0100302 1236.831
50003 0100303 1236.831
80004 0100304 1236.831
50005 0100305 1236.831
5000
6 0100306 1236.831
3000> table(tr$pension>0)
FALSE TRUE
3717
123

# 4) NGO transfers> d<-subset(outfiles[[24]],Q07_C01==5)[,c("HHID","Q07_C05")]> dim(d)[1] 162 2> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),ngo.transfers=df)> df[,2]<-df[,2]/12> tr<-merge(tr,df,by="HHID",all.x=T)> tr[is.na(tr)]<-0

Manual Cambodia CSES 2012 Version 2.0

155# 5) Remittance domestic> d<-subset(outfiles[[24]],Q07_C01==2)[,c("HHID","Q07_C03")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),remittance.domestic1=df)> df[,2]<-df[,2]/12> tr<-merge(tr,df,by="HHID",all.x=T)> tr[is.na(tr)]<-0> head(tr)HHID
hw12a hhsize pension.domestic pension.abroad pension ngo.transfers
1 0100301 1236.831
2
0
0
0
0
2 0100302 1236.831
5
0
0
0
0
3 0100303 1236.831
8
0
0
0
0
4 0100304 1236.831
5
0
0
0
0
5 0100305 1236.831
5
0
0
0
0
6 0100306 1236.831
3
0
0
0
0
remittance.domestic1
1
25000.000
2
0.000
38333.333
4
25000.000
5
6666.667
62083.333> table(tr$remittance.domestic1>0)
FALSE TRUE
2749 1091# 6) Remittance abroad> d<-subset(outfiles[[24]],Q07_C01==2)[,c("HHID","Q07_C04")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),remittance.abroad1=df)> df[,2]<-df[,2]/12> tr<-merge(tr,df,by="HHID",all.x=T)> tr[is.na(tr)]<-0> table(tr$remittance.abroad1>0)
FALSE TRUE
3672
168

# 7) Total private transfers> colnames(tr)[1] "HHID""hw12a""hhsize"[4] "pension.domestic""pension.abroad""pension"[7] "ngo.transfers""remittance.domestic1" "remittance.abroad1"> tr$total.private.transfers<-rowSums(tr[,8:9])> tr.save<-tr# 8) Scholarship government> d<-subset(outfiles[[24]],Q07_C01==3)[,c("HHID","Q07_C05")]

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156> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),scholarship.gov=df)> df[,2]<-df[,2]/12> tr<-merge(tr,df,by="HHID",all.x=T)> tr[is.na(tr)]<-0# 9) Scholarship NGO> d<-subset(outfiles[[24]],Q07_C01==4)[,c("HHID","Q07_C05")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),scholarship.ngo=df)> df[,2]<-df[,2]/12> tr<-merge(tr,df,by="HHID",all.x=T)> tr[is.na(tr)]<-0# 10) Total scholarship> tr$total.scholarship<-tr$scholarship.gov+tr$scholarship.ngo> tr.save<-tr> head(tr)HHID
hw12a hhsize pension.domestic pension.abroad pension ngo.transfers
1 0100301 1236.831
2
0
0
0
0
2 0100302 1236.831
5
0
0
0
0
3 0100303 1236.831
8
0
0
0
0
4 0100304 1236.831
5
0
0
0
0
5 0100305 1236.831
5
0
0
0
0
6 0100306 1236.831
3
0
0
0
0
remittance.domestic1 remittance.abroad1 total.private.transfers scholarship.gov
125000.000
025000.000
0
2
0.000
0
0.000
0
3
8333.333
08333.3330425000.000
025000.000
05
6666.667
0
6666.667062083.333
02083.3330scholarship.ngo total.scholarship
1
0
0
2
0
0
3
0
0
4
0
0
5
0
0
6
0
0
> table(tr$scholarship.gov>0)
FALSE TRUE3814
26
> table(tr$scholarship.ngo>0)
FALSE TRUE
3821
19#11) Gifts> d<-subset(outfiles[[24]],Q07_C01==10|Q07_C01==11)[,c("HHID","Q07_C05")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)

Manual Cambodia CSES 2012 Version 2.0

157> df<-data.frame(HHID=names(df),gifts=df)> df[,2]<-df[,2]/12> tr<-merge(tr,df,by="HHID",all.x=T)> tr[is.na(tr)]<-0# 12) Other transfers> d<-subset(outfiles[[24]],Q07_C01==12)[,c("HHID","Q07_C05")]> d[is.na(d)]<-0> df<-tapply(d[,2],d$HHID,sum)> df<-data.frame(HHID=names(df),other.transfers=df)> df[,2]<-df[,2]/12> tr<-merge(tr,df,by="HHID",all.x=T)> tr[is.na(tr)]<-0# 13) Total transfers> colnames(tr)[1] "HHID""hw12a"[4] "pension.domestic""pension.abroad"[7] "ngo.transfers""remittance.domestic1"[10] "total.private.transfers" "scholarship.gov"[13] "total.scholarship" "gifts" "other.transfers"> tr$total.transfers<-rowSums(tr[,c(6,7,10,13:15)])> tr.save<-tr> table(tr$total.transfers>0)
FALSE TRUE
1566 2274"hhsize""pension""remittance.abroad1""scholarship.ngo"


Weighted mean of transfers received> t<-round(sapply(tr[,4:16],function(x) weighted.mean(x,hhinc$hw12a)))> data.frame(Item=names(t),Value=round(t),row.names=NULL)
Item Value
1pension.domestic

3907

2

pension.abroad

170

3

pension4077

4

ngo.transfers

804

5

remittance.domestic1 12398

6

remittance.abroad1

9571

7

total.private.transfers 21970

8

scholarship.gov

357

9

scholarship.ngo

480

10

total.scholarship

837

11

gifts

3981

12

other.transfers

3186

13

total.transfers 34855

Manual Cambodia CSES 2012 Version 2.0

158# 14) Total income> hhinc<-merge(hhinc,tr[,-2],by="HHID",all.x=T)> hhinc$total.income<-hhinc$primary.income+hhinc$total.transfers> hhinc.save<-hhinc

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159

7.7 NEGATIVE TRANSFERS (TRANSFERS PAID)

Estimation method for negative transfer differs between CSES 2009 and 2012.
In CSES 2009, diary data was used for negative transfer. However, recall data was used in
CSES 2012.

CSES 2012> colnames(outfiles[[4]])[1] "pkid""HHID"[8] "ChangeDate""Q01CC01""Q01CC04""Q01CC05""Q01CC06""EntryUser"# file: outfile[[04]] : HHRecallNonFood# Q01CC01 = 14:17# Q01CC06

Negative transfers from recall data
Item

File

SectionVariables to be used

Reference
periodCharities

04 HHRecallNonFood

1C

Subset of Q01CC01==1412M

Q01CC06
Inter-households

04 HHRecallNonFood

1C

transfers
Taxes on income

Subset of Q01CC01==15

12M

Q01CC06
04 HHRecallNonFood

1C

Subset of Q01CC01==1612M

Q01CC06
Taxes on property

04 HHRecallNonFood

1C

Subset of Q01CC01==1712M

Q01CC06
Total transfers paid

Sum of the above / 12

1M

= total.income (minus)

1M(Negative transfers)

disposable.income1

total.negative.transfers
disposable.income2

Replaced

by

4,000

if

disposable.income1<0> NF<-outfiles[[4]] # HHRecallNonFood> colnames(NF)[1] "pkid""HHID""Q01CC01"[7] "EntryUser" "ChangeDate""Q01CC04""Q01CC05"# Negative transfers> nt<-outfiles[[36]][,c("HHID","hw12a","hhsize")]

Manual Cambodia CSES 2012 Version 2.0"Q01CC06"

1M

160

# Charities (12M)> d[is.na(d)]<-0> df<-tapply(d[,6],d$HHID,sum)> df<-data.frame(HHID=names(df),charity=df)> head(df[df$charity>0,])
HHID charity
0102307 0102307 200000
0102308 0102308
40000
0102601 0102601 200000
0102602 0102602 200000
0102603 0102603 100000
0102604 0102604 150000> nt<-merge(nt,df,by="HHID",all.x=T)> nt[is.na(nt)]<-0> dim(nt)[1] 3840
4> head(nt[nt$charity>0,])HHID
hw12a hhsize charity
137 0102307 1217.582
6 200000
138 0102308 1217.582
640000
151 0102601 615.723
9 200000
152 0102602 615.723
5 200000
153 0102603 615.723
5 100000
154 0102604 615.723
6 150000> weighted.mean(nt$charity,nt$hw12a)[1] 24958.79> nt.save<-nt# Inter HH transfers (12M)> d<-subset(NF,Q01CC01==15)> dim(d)[1] 38328> d[is.na(d)]<-0> df<-tapply(d[,6],d$HHID,sum)> df<-data.frame(HHID=names(df),hhtransfer=df)> head(df[df$hhtransfer>0,])
HHID hhtransfer
0100301 0100301
1550000
0100302 0100302
5200000100303 0100303
1220000
0100304 0100304
5300000100305 0100305
4060000
0100306 0100306
650000> nt<-merge(nt,df,by="HHID",all.x=T)> nt[is.na(nt)]<-0> dim(nt)[1] 3840
5> head(nt[nt$charity>0 & nt$hhtransfer>0,])HHID
hw12a hhsize charity hhtransfer
137 0102307 1217.582
6 200000
6e+05
138 0102308 1217.582
6
40000
2e+05
151 0102601 615.723
9 200000
5e+05
152 0102602 615.723
5 200000
7e+05

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161

153 0102603 615.723
5 100000
154 0102604 615.723
6 150000> weighted.mean(nt$hhtransfer,nt$hw12a)[1] 1061794> nt.save<-nt

4e+05
4e+05

Remarks:
The value of inter-household transfers paid is too large, and might include outliers.
Boxplot of inter-household transfers paid

0.0e+00

5.0e+06

1.0e+07

1.5e+07> summary(nt$hhtransfer)
Min. 1st Qu.
Median0460000870000Mean
1141000

3rd Qu.
Max.
1500000 16000000# Taxes on income (12M)> d<-subset(NF,Q01CC01==16)> dim(d)[1] 884 8> d[is.na(d)]<-0> df<-tapply(d[,6],d$HHID,sum)> df<-data.frame(HHID=names(df),income.tax=df)> head(df[df$income.tax>0,])
HHID income.tax
0101403 0101403
2400000102705 0102705
18000
0200808 0200808
7000
0201405 0201405
20000
0301808 0301808
8000
0304501 0304501
5000> nt<-merge(nt,df,by="HHID",all.x=T)> nt[is.na(nt)]<-0> dim(nt)[1] 3840
6> head(nt[nt$income.tax>0,])Manual Cambodia CSES 2012 Version 2.0

162

HHID
hw12a hhsize charity hhtransfer income.tax
73 0101403 746.2335
30878000240000165 0102705 639.4503
703500000
18000
238 0200808 996.4721
202035000
7000
275 0201405 399.3942
1001450000
20000
588 0301808 960.9381
702050000
8000
771 0304501 1182.2439
402010000
5000> weighted.mean(nt$income.tax,nt$hw12a)[1] 2072.628> nt.save<-nt# Taxes on property (12M)> d<-subset(NF,Q01CC01==17)> dim(d)[1] 22998> d[is.na(d)]<-0> df<-tapply(d[,6],d$HHID,sum)> df<-data.frame(HHID=names(df),property.tax=df)> head(df[df$property.tax>0,])
HHID property.tax
0100305 0100305
9000
0100307 0100307
4500
0100310 0100310
12000
0100601 0100601
9000
0100602 0100602
4500
0100604 0100604
4500> nt<-merge(nt,df,by="HHID",all.x=T)> nt[is.na(nt)]<-0> dim(nt)[1] 3840
7> head(nt[nt$property.tax>0,])HHID
hw12a hhsize charity hhtransfer income.tax property.tax
5 0100305 1236.831
5040600000
9000
7 0100307 1236.831
605040000
04500
10 0100310 1236.831
701550000
012000
11 0100601 1328.537
1003300000
0
9000
12 0100602 1328.537
901000000
04500
14 0100604 1328.537
4088000004500> weighted.mean(nt$property.tax,nt$hw12a)[1] 23942.09> nt.save<-nt# Total transfers paid / Negative transfers (1M)
> nt$negative.transfers<-rowSums(nt[,4:7])/12> nt.save<-nt> head(nt)HHID
hw12a hhsize charity hhtransfer income.tax property.tax
1 0100301 1236.831
201550000
002 0100302 1236.831
50520000003 0100303 1236.831
801220000
00
4 0100304 1236.831
50530000005 0100305 1236.831
50406000009000
6 0100306 1236.831
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163

1
2
3
4
5
6

negative.transfers
129166.67
43333.33
101666.67
44166.67
339083.33
54166.67

Weighted mean of monthly negative transfers> t<-round(sapply(nt[,4:8],function(x) weighted.mean(x,nt$hw12a)))> t<-c(round(t[1:4]/12),t[5])> data.frame(Item=names(t),Value=round(t),row.names=NULL)
Item Value
1charity2080

2

hhtransfer 88483

3

income.tax

173

4

property.tax

1995

5 negative.transfers 92731# Appended negative transfers to hhinc and generated disposable.income1> hhinc<-merge(hhinc,nt[,c(-2,-3)],by="HHID",all.x=T)> hhinc$disposable.income1<-hhinc$total.income-hhinc$negative.transfers> hhinc.save<-hhincf# disposable.income2> hhinc$disposable.income2<-ifelse(hhinc$disposable.income1<0,+ 4000,hhinc$disposable.income1)> hhinc.save<-hhinc

Manual Cambodia CSES 2012 Version 2.0

164
Weighted mean of household income> t<-round(sapply(hhinc[,c(4,16,20,21,29,44,45,50,51)],function(x)weighted.mean(x,hhinc$hw12a)))> data.frame(Item=names(t),Value=round(t/1000),row.names=NULL)
Item Value1salary403

2agri.income

400

3

nonagri.income

256

4

income.ownhouse2

91

5

property.income-5

6

total.transfers

35

7

total.income

1180

8 negative.transfers

93

9 disposable.income1

1087

Source of income

Report (p)My trial

Computed from

2012

2012

IncomeHousehold_2012

403

403

Primary income

984

Salary403

Self employment

576

Agriculture

229

400

223

Non-agriculture

249

256

261

Own house

98

91

98

Property income

5

-5

5

Transfers received

35

35

35

Total income

1019

1180

1025

5

93

1014

1087

1020

3840

3840

3840

Transfers paid / negative
incomeDisposable income
Remarks
No. of records

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165(For reference)> t<-round(sapply(hhinc[,c(-1,-2,-3)],function(x) weighted.mean(x,hhinc$hw12a)))> data.frame(Item=names(t),Value=round(t/1000),row.names=NULL)
Item Value1salary403
2cost.crop82
3
cost.livestock1
12
4
cost.livestock2
19
5
cost.fish1
2
6
cost.fish2
10
7
cost.forestry
18interest.agri
89rcpt.crop
420
10
rcpt.livestock48
11
rcpt.fish32
12
rcpt.forestry
34
13
agri.income
400
14
cost.nonagri
878
15interest.nonagri
616rcpt.nonagri 1139
17
nonagri.income
256
18
income.ownhouse2
91
19
hhsize.y020bank.interest
1
21
interest.otherloans
222
dividents
3
23
rent.fromland
1
24
grossproperty.income
625interest.paidnet
11
26
property.income-527
primary.income 1145
28
hhsize029
pension.domestic
430
pension.abroad
031
pension4
32
ngo.transfers
133
remittance.domestic1
1234
remittance.abroad1
10
35 total.private.transfers
2236
scholarship.gov
0Manual Cambodia CSES 2012 Version 2.0

166

Chapter 8. Resampled micro data to be provided
Strategy
1. Resampling
The data files (except “PSUListing”) will be resampled as follows;
1.1 To select 80% of HHID by systematic sampling method.
1.2 To select records which HHID belongs to the above selected HHID from the data files.
1.4 To adjust household weight and person weight by dividing by 0.8.
2. The Village data files will not be included.
3.

The data file of “hhexp” which the author generated in Chapter 6 will be included.

4.

The provided summary file of household income will be included. This will be discussed later.

5.

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

6.

All data of “PSUListing” will be provided.

# Saved data frame “hhexp” in outfiles[[38]] and addes “hhexp” to Rnames> outfiles[[38]]<-hhexp> Rnames[38]<-"hhexp"> length(outfiles)[1] 38Resampling# list of all HHID
> hhid.all<-outfiles[[1]]$HHID> length(hhid.all)[1] 3840# Selected 80% of hhid2> Int<-5> (St<-sample(1:5,1))[1] 4> hhid.selected<-hhid.all[(1:3840)%%Int!=(St-1)]> length(hhid.selected)/length(hhid.all)[1] 0.8> hhid.selected<-hhid.selected[order(hhid.selected)]> head(hhid.selected)[1] "0100301" "0100302" "0100304" "0100305" "0100306" "0100307"# Resampled at the rate of 80%# outfiles[[1]] to outfiles[[38]]> Rnames.resampled<-paste(Rnames,".80",sep="")> Rnames.resampled

Manual Cambodia CSES 2012 Version 2.0

167[1] "Households.80"[3] "HHFoodConsumption.80"[5] "HHVulnerability.80"[7] "HHHousing.80"[9] "HHProductionCrops.80"[11] "HHInventoryCrops.80"[13] "HHLivestock1.80"[15] "HHFishCultivation1.80"[17] "HHFishCultivation3.80"[19] "HHForestryHunting2.80"[21] "HHNonAgriculture2.80"[23] "HHLiabilities.80"[25] "HHConstruction.80"[27] "PersonMaternalHealth.80"[29] "PersonIllness.80"[31] "PersonEcoCurrent.80"[33] "PersonViolenceB.80"[35] "PSUListing.80"[37] "weightpersons.80""HHMembers.80""HHRecallNonFood.80""PersonEducation.80""HHLandOwnership.80""HHCostCultivationCrops.80""HHSalesCrops.80""HHLivestock2.80""HHFishCultivation2.80""HHForestryHunting1.80""HHNonAgriculture1.80""HHNonAgriculture3.80""HHIncomeOtherSource.80""HHDurableGoods.80""PersonHealthU2.80""PersonDisability.80""PersonviolenceA.80""HHOtherInfo.80""weighthouseholds.80""hhexp.80"> outfiles.80<-list()> for(j in 1:38){+ d<-outfiles[[j]]+ outfiles.80[[j]]<-subset(d,is.element(d$HHID,hhid.selected))+ }> length(outfiles.80)[1] 38# Adjusted weight and named as HW and PW> d<-outfiles.80[[36]]> colnames(d)[1] "PSU""HHID""urbrur"[5] "Poststratum" "hhsize""hw12a"[9] "region"> d$HW<-d$hw12a/0.8> outfiles.80[[36]]<-d> d<-outfiles.80[[37]]> colnames(d)[1] "PID""PSU""HHID"[5] "Stratum""Poststratum" "hw12a"> d$HW<-d$hw12a/0.8> d$PW<-d$pw12a/0.8> outfiles.80[[37]]<-d> d<-outfiles.80[[38]]> colnames(d)[1] "HHID""food"[4] "clothing""housing""Stratum""Province_Code""urbrur""pw12a""alcohol""furnishing"

Manual Cambodia CSES 2012 Version 2.0

168[7] "health""transportation" "communication"[10] "recreation""education""miscellaneous"[13] "total""foodshare""hw12a"[16] "urbrur""Province_Code" "region"> d$HW<-d$hw12a/0.8> outfiles.80[[38]]<-dResampling of provided summary household income data

> d2012<-read.spss("IncomeHousehold_2012.sav",to.data.frame=TRUE)> dim(d2012)[1] 3840 85> d2012.80<-subset(d2012,is.element(d2012$HHID,hhid.selected))> dim(d2012.80)[1] 3072 85> hhinc.80<-d2012.80[order(d2012.80$HHID),]> table(hhinc.80$HHID==outfiles.80[[1]]$HHID)
TRUE
3072
> hhinc<-d2012> save(hhinc,hhinc.80,file="IcomeHousehold2012.RData")> write.csv(hhinc.80,"hhinc.80.csv",row.names=F)# Appended to dataframes of outfiles and outfiles.80> length(outfiles)[1] 38> outfiles[[39]]<-hhinc> length(outfiles.80)[1] 38> outfiles.80[[39]]<-hhinc.80> Rnames[39]<-"hhinc"> Rnames.resampled[39]<-"hhinc.80"

 Replace outfiles.80[[35]]: “PSUListing” file with outfiles[[35]]> outfiles.80[[35]]<-outfiles[[35]]Note: outfiles.80[[35]] and "PSUListing_80.csv" are not resampled.

Manual Cambodia CSES 2012 Version 2.0

169# Number of records and variables in each resampled file
> for(j in 1:39){+ cat(format(j,width=2),": ",format(Rnames.resampled[j],width=30),": ",+ format(nrow(outfiles.80[[j]]),width=7),",",+ format(ncol(outfiles.80[[j]]),width=3),"\n")
+ }
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 :

Households.80
HHMembers.80
HHFoodConsumption.80
HHRecallNonFood.80
HHVulnerability.80
PersonEducation.80
HHHousing.80
HHLandOwnership.80
HHProductionCrops.80
HHCostCultivationCrops.80
HHInventoryCrops.80
HHSalesCrops.80
HHLivestock1.80
HHLivestock2.80
HHFishCultivation1.80
HHFishCultivation2.80
HHFishCultivation3.80
HHForestryHunting1.80
HHForestryHunting2.80
HHNonAgriculture1.80
HHNonAgriculture2.80
HHNonAgriculture3.80
HHLiabilities.80
HHIncomeOtherSource.80
HHConstruction.80
HHDurableGoods.80
PersonMaternalHealth.80
PersonHealthU2.80
PersonIllness.80
PersonDisability.80
PersonEcoCurrent.80
PersonviolenceA.80
PersonViolenceB.80
HHOtherInfo.80
PSUListing.80
weighthouseholds.80
weightpersons.80
hhexp.80
hhinc.80

:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:

3072 ,
14152 ,
46214 ,
32114 ,
3074 ,
13440 ,
3072 ,
3031 ,
3209 ,
3207 ,
1533 ,
1295 ,
16402 ,
3098 ,
64 ,
2086 ,
2974 ,
4691 ,
5284 ,
1370 ,
5987 ,
2075 ,
1076 ,
3371 ,
2867 ,
27791 ,
1000 ,
465 ,
14152 ,
14152 ,
12896 ,
14117 ,
29 ,
3072 ,
384 ,
3072 ,
14152 ,
3072 ,
3072 ,

10
23
8
8
20
29
51
37
15
21
8
8
19
6
9
6
6
9
6
15
11
11
12
8
27
14
15
19
23
18
47
8
14
47
16
10
10
19
85

# Converted to CSV> CSVnames<-gsub("\\.","_",Rnames.resampled)> CSVnames<-paste(CSVnames,".csv",sep="")Manual Cambodia CSES 2012 Version 2.0

170> CSVnames[1] "Households_80.csv"[3] "HHFoodConsumption_80.csv"[5] "HHVulnerability_80.csv"[7] "HHHousing_80.csv"[9] "HHProductionCrops_80.csv"[11] "HHInventoryCrops_80.csv"[13] "HHLivestock1_80.csv"[15] "HHFishCultivation1_80.csv"[17] "HHFishCultivation3_80.csv"[19] "HHForestryHunting2_80.csv"[21] "HHNonAgriculture2_80.csv"[23] "HHLiabilities_80.csv"[25] "HHConstruction_80.csv"[27] "PersonMaternalHealth_80.csv"[29] "PersonIllness_80.csv"[31] "PersonEcoCurrent_80.csv"[33] "PersonViolenceB_80.csv"[35] "PSUListing_80.csv"[37] "weightpersons_80.csv"[39] "hhinc_80.csv""HHMembers_80.csv""HHRecallNonFood_80.csv""PersonEducation_80.csv""HHLandOwnership_80.csv""HHCostCultivationCrops_80.csv""HHSalesCrops_80.csv""HHLivestock2_80.csv""HHFishCultivation2_80.csv""HHForestryHunting1_80.csv""HHNonAgriculture1_80.csv""HHNonAgriculture3_80.csv""HHIncomeOtherSource_80.csv""HHDurableGoods_80.csv""PersonHealthU2_80.csv""PersonDisability_80.csv""PersonviolenceA_80.csv""HHOtherInfo_80.csv""weighthouseholds_80.csv""hhexp_80.csv"> for(j in 1:39){+ cmd<-paste("write.csv(outfiles.80[[",j,"]],'",CSVnames[j],"',row.names=F)",sep="")+ eval(parse(text=cmd))+ }> list.files()[1] "HHConstruction_80.csv"[3] "HHDurableGoods_80.csv"[5] "HHFishCultivation1_80.csv"[7] "HHFishCultivation3_80.csv"[9] "HHForestryHunting1_80.csv"[11] "HHHousing_80.csv"[13] "HHInventoryCrops_80.csv"[15] "HHLiabilities_80.csv"[17] "HHLivestock2_80.csv"[19] "HHNonAgriculture1_80.csv"[21] "HHNonAgriculture3_80.csv"[23] "HHProductionCrops_80.csv"[25] "HHSalesCrops_80.csv"[27] "Households_80.csv"[29] "PersonEcoCurrent_80.csv"[31] "PersonHealthU2_80.csv"[33] "PersonMaternalHealth_80.csv"[35] "PersonViolenceB_80.csv"[37] "weighthouseholds_80.csv"[39] "hhinc_80.csv""HHCostCultivationCrops_80.csv""hhexp_80.csv""HHFishCultivation2_80.csv""HHFoodConsumption_80.csv""HHForestryHunting2_80.csv""HHIncomeOtherSource_80.csv""HHLandOwnership_80.csv""HHLivestock1_80.csv""HHMembers_80.csv""HHNonAgriculture2_80.csv""HHOtherInfo_80.csv""HHRecallNonFood_80.csv""HHVulnerability_80.csv""PersonDisability_80.csv""PersonEducation_80.csv""PersonIllness_80.csv""PersonviolenceA_80.csv""PSUListing_80.csv""weightpersons_80.csv"

Manual Cambodia CSES 2012 Version 2.0

CONFIDENTIAL

Royal Government
171of Cambodia
Ministry of Planning
National Institute of Statistics

All information collected in this survey isstrictly confidential and will be used forstatistical purposes onlyPSU

HH SERIAL No

HOUSEHOLD SOCIO-ECONOMIC SURVEY 2012DAIRY SHEETS OF HOUSEHOLD EXPENDITURES & CONSUMPTION OF OWN-PRODUCED FOOD AND HOUSEHOLD INCOME & RECEIPTS - Form 4
A. To be completed by Supervisors before interview

B. To be completed by Interviewer

Province /City

Name of household Head
Address (House No., Street….) ofother identification)

District /Khan
Commune/Sankat
Sample Village/MondolFirst visit date

Zone

Last visit date

Sector (Urban=1, Rural=2)Day:

Month:

Year:

Day:

Month:Year:

DIARY SHEET MUST BE RECORDED EVERY DAY FOR THE WHOLE MONTH

Serial Number of Sample Village

Interviewer’s Name:

Sample Reference Number of Household

Interviewer’s signature:
Team Number:

Id:

No. Of the month (from 01 to 15):

C. To be completed by Supervisors after checking completed questionnaire thoroughly

D: To be completed after Re-interview (when required)Supervisor’s Name:

Name of Re-interviewer:

Id:

Date checked bySupervisor (Week 1)

Day:

Month:Year:

Date of Re-interview

Date checked bySupervisor (Week 2)

Day:Month:

Year:

Interviewer’s signature:

Day:

Month:

Year:

Day:

Month:Year:

Date checked bySupervisor (Week 3)
Date checked bySupervisor (Week 4)
Supervisor’ s Signature:

Remarks of Reinterviewer:
Manual Cambodia CSES 2012 Version 2.0

Id:
Day:

Month:

Year:

172

PAGE Nº 01

Expenditures and consumption of own-produced
FOR THE HOUSEHOLDFOR THE HOUSEHOLD

FOR
NIS

FORM OFACQUISITION

1=Paid in cash
2=Paid in kind
3=Purchased on
credit4=Gift received
5=Stock of ownproduced

LINE NUMBER(1)

DATE (DD/MM)

ITEM DESCRIPTIONUNIT OFQUANTI-TY

(2)

(3)

(4)

CODE
OF UNIT(5)

QUANTITYVALUE IN RIELS

(6)

(7)

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
90

FOR ENUMERATORSTOTAL:
ManualCambodia CSES 2012 Version 2.0(8)

ORIGIN
1 = Householdproduction
2 = Produced in
Cambodia
3 = Imported fromabroad
4 = Don't know theorigin5 = No product(9)

FOR NISPURPOSE
01 = Own household consumption
02 = For agricultural production
03 = For manufacturing production
04 = For mining production
05 = For services production
06 = For other household production
07 = Gifts & remittances to other households
08 = Offerings,donations,charities, etc.
09 = Interests
10 = Payback of loans
11 = Taxes
12 = Other (specify)(10)

ITEM CODE
(11)

173

PAGE Nº 01

Household Income and Receipts
FOR THE HOUSEHOLDFOR THE HOUSEHOLDFOR NISTYPE OFINCOME

LINE NUMBER
(1)

DATE
(DD/MM)

ITEM DESCRIPTIONUNIT OFQUAN-TITY

(2)

(3)

(4)

CODE
OF
QUANTITYQUAN-TITYVALUE IN RIELS

(5)

(6)

(7)

01
02
03
04
04
06
07
08
09
10
11
12
13
14
15
90

FOR ENUMERATORSManual TOTAL:
Cambodia CSES 2012 Version 2.0

01 = Wage or salary (in cash or kind)
02 = Agricultural or forestry production or sales
03 = Fishing or hunting production or sales
04 = From mining production
05 = Sales of manufactured products
06 = Receipts from services rendered
07 = Received as gift
08 = Remittances received
09 = Pensions or other social assistances
1 = In cash 10 = Study support in cash or kind (Scholarships, stipends or other)2 = In kind 11 = Dividends, interests, commissions, rents etc.
12 = Receipts from sale of possessions/own property
3 = Bartered 13 = Withdrawals from savings/loans obtained
14 = Payback of loans
15 = Windfall gains/inheritance
16 = Tax refunds
17 = Maturity payment on insurance policies
18 = Lump-sum compensation for injury, legal damages received
19 = Other (specify)(8)

FOR NIS

KIND OF INCOME(9)ITEM CODE
(10)

174

CONFIDENTIAL
All information collected in this survey
is strictly confidential and will be used
for statistical purposes only

Royal Government of Cambodia
Ministry of Planning
National Institute of Statistics

Household ID

CAMBODIA SOCIO-ECONOMIC SURVEY 2012
HOUSEHOLD QUESTIONNAIRE
A. To be completed by interviewer before interview
Province /Capital
District/City/Khan
Commune/Sankat
Sample Village/Mondol
Zone
Sector (Urban=1, Rural=2)
Sample reference number of household
B. To be completed by interviewer
Name of household head

Phone:

Address (house No., street….) of otheridentification)
Date of first visit to Household

Day:

Month:Year:

Date of last visit

Day:

Month:

Year:

Team Number

Interviewer’s Id:

Interviewer’s name:Interviewer’s signature:

Interviewer’s phone no:Month and Year of Survey

Month

To be completed after filling-out the list of household members

Male:

Year:

Female:Total members:

C. To be completed by supervisor after checking completed questionnaire and diary thoroughlySupervisor’s name:Completed
Put X

Date checked by supervisor

Id:

Not completed
Put X

Day

Month

Date checked week 1
Date checked week 2 (large sample year)
Diary checked (large sample year)
Household refused from the beginning of the interview week(s)/not in village during the interview week(s)Supervisor’ s signature:

Supervisor’ s phone no:
Reception

Id:

Date:

Preparation
Id:

Date:

Manual Cambodia CSES 2012 Version 2.0

Data Entry
Id:

Date

Year

175

01. INITIAL VISIT
Respondent: head of household, spouse of the head of household, or another adult household member

INITIAL VISIT

A. LIST OF HOUSEHOLD MEMBERS
The questions should be asked of the head of household, spouse of the head of household or other adult household member if both head and spouse are absent.
Please provide the following information on all members usually residing in this household.
Please give me the names of all household members, Sex
What is..[NAME]..’s datestarting with head of the household.
of birth?
A person is counted as a household member if he/she
lives here or has been absent for less than 12
months.

ID NUMBER

1 = Male
2 = Female

Write ' - ' if don´tknow, for day ormonth or year

What is..
Relationship to the head
[NAME] ...’sage incompleted 01 = Head
10 = Son/Daughter-inyears?
02 = Spouselaw

03 = Son/Daughter
04 = Stepchild
Write '0' if
05 = Adopted child/less than one Foster childyear of age, 06 = Parent
and07 = Sibling" - " if don´t 08 = Grand child
09 = Nephew/Nieceknow

11 = Brother/Sister-inlaw
12 = Parent-in-law
13 = Other relatives
14 = Servant
15 = Other non-relative
including boarder

Does thefather of..[NAME]..
live in thehousehold?

If YES, write
the ID CODE,
if NO write" -"Great/grand child should be reported
in other relatives
(1)

(2)

(3)

DAY

MONTH

YEAR

YEARS

(4a)

(4b)

(4c)

(5)

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

Manual Cambodia CSES 2012 Version 2.0

(6)

(7)

176

Respondent: head of household, spouse of the head of household or another adult household member

INITIAL VISITID NUMBER

01. A. LIST OF HOUSEHOLD MEMBERS (CONTINUED)

Only for members aged 13 andDoes theIs ..[NAME]..Khmer or Does
above:
mother ofother ethnic group? ..[NAME]..
..[NAME]..
speak
live in the
Khmer?
1 = Khmer (>> 12)
What is ..[NAME].. ´sDoes thehousehold?
marital status?
spouse of 2 = Cham..[NAME].. 3 = Other local ethnic
live in this group
1 = Married/Living
household? 4 = Chinese
together
5 = Vietnamese
If YES, write
2 = Divorced/Separated
6 = Thaithe ID CODE,
7 = Lao(>> 11)
if NO write
8 = Other (Specify)
3 = Widowed (>> 11)" -"4 = Never married/Never If YES, write
1=Yes
the ID CODE,
lived with a partner
if NO write(>> 11)
" -"

(1)

(8)

(9)

Can ..[NAME].speak other languages
than Khmer?

0=No
1= French
2= English
3= Chinese
4= Vietnamese
5= Thai6= Lao7= Chaam
8= Other local language
9= Other (Specify)

Has ..[NAME].. How many
been present all weeks has
days last week? ..[NAME]..
been absent
from homeduring thepast 12months?
1=Yes>> NEXTPERSON
2=No

WRITE '0' IF
LESS THAN
ONE WEEK

2=No>> NEXTPERSON

(10)

(11a)

(11b)

1

2

3

(12a)

(12b)

(12c)

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

Manual Cambodia CSES 2012 Version 2.0

WEEKS
(13)

(14)

177

01. B. FOOD, BEVERAGES AND TOBACCO CONSUMPTION DURING THE LAST 7 DAYS
Respondent: The household member who knows most about food, beverage, tobacco consumption in the last 7 days
Q1 Did your household have any economic activity, e.g. agriculture production (farming), producing goods, service etc. during the last 7days?

INITIAL VISIT
1 = Yes

Only expenditure/value of own production for household consumption!
Note that any household´s expenditure on economic activity shall not be included in this section, because it will be asked in the sections on the economic
activities (Section 5B-H).
For each item group try to estimate quantity of items consumed and then how
Value of consumption in Riels
much of the consumed quantity had been purchased in cash and how much was
Write '0' if nothingfrom own production or received as payment in kind for work, or as gift, or free
Purchased in cash
Own production, wages in
Total consumption
collection.
( Col 3 + Col 4)
kind, gifts, free collections(imputed value)

Q01BC01

ITEM NUMBER

2 = NoFOOD/BVERAGE/TOBACCO ITEMS

RIELS

RIELS

RIELS

(2)

(3)

(4)

(5)

Q01BC03

Q01BC04

Q01BC05(1)

01

Rice (All kind of rice to be included)

02

Other cereals (bread, corn, wheat flour, rice flour, corn meal, rice cakes, noodles,
biscuits, etc.)

03

Fish (fresh fish, salted and dried fish, canned fish, shrimp, prawn, crab, etc.)

04

Meat & poultry (beef, buffalo, mutton, lamb, pork, chicken, duck, innards, inch liver,spleen, dried beef)05

Eggs (chicken egg, duck egg, quail egg, fermented/salted egg, etc.)

06

Dairy products (fresh milk, condensed or powdered milk, ice cream, cheese, otherdairy products, etc.)

07

Oil and fats (rice bran oil, vegetable oil, pork fat, butter, margarine, coconut/frying oil,
etc.)

08

Fresh vegetables (trakun, onion, shallot, cabbage, spinach, carrot, beans, chilli,
tomato, etc.)

09

Tuber (cassava, sweet potato, potato, traov, sugar beet, etc.)

10

Pulses and legumes (green gram, dhall, cowpea, bean sprout, other seeds, etc.)11

Prepared and preserved vegetables (cucumber pickles, other pickles, tomato paste,
etc.)

12

Fruit (banana, orange, mango, pineapple, lemon, papaya, durian, water melon,
grape, apple, canned and dried fruits, etc.)

13

Dried nuts and edible seeds (coconut, cashew nut, lotus nut, peanut, gourd seed,other nuts)

14

Sugar, salt and spices (sugar, jaggery, salt, chocolate, candy, coriander, red pepper
spice, garlic, ginger, soy sauce, fish sauce, monosodium glutamate, etc.)

15

Tea, coffee, cocoa

16Non-alcoholic beverages (canned or bottled soft drinks, mineral water, fruit juice,fruit syrup, etc.)17

Alcoholic beverages (beer, wine, whisky, scotch, other distilled spirits)

18

Tobacco products (cigarettes, mild tobacco, strong tobacco, etc.)

19

Other food products (fried insects, peanut preparation, flavoured ice, ice, other foodproducts)

20

Food taken away from home (meals at work, school, restaurants, snacks, coffee,
soft drinks purchased outside home)21

Prepared meals bought outside and eaten at home

22

Total 1 - 21:

Manual Cambodia CSES 2012 Version 2.0

178

01. C. RECALL NON-FOOD EXPENDITURES
Respondent: The household member who knows most about the non-food expenditure in the household

NON-FOOD ITEMS

(1)

(2)

No.

Q01CC01

Only expenditure for household consumption
What was your household's expenditure on the following items during theindicated time periods?

01

Value (in Riels)
Write '0' if nothing
In-cash expenditure
Time period(3)Medical care (doctors' fees, other medical services, drugs, hospital charges,
other medical supplies, etc.)

Last 1 month(4)

Q01CC04

Last 1 month

02

Transportation (personal transport equipment, operation of transport
equipment, maintenance and repair of equipment, gasoline and diesel for own
transportation, fees for public transport, moving fee, driving lessons, etc.)

03

Communication (postage stamps, fax, telephone and internet phone charges,
cell phones, phone cards, internet charges etc.)

04

Personal care (soap, toothpaste, razor, sanitary napkins, haircut, manicure,
etc.)

05

Clothing and footwear (tailored clothes, ready-made clothes, rain clothes,
underwear, baby clothes, diapers, hats, shoes, boots, etc.)

Last 1 month
Last 1 month
Last 6 months
Last 12 months

06

Furniture, furnishings and household equipment and operation (curtain,
household appliances, cooking utensils, light bulbs, soap and detergents etc.)

10

Domestic salaries (servant's salary, hired labour for cleaning, laundry, cooking Last 12 months
etc.)
Last 12 months
Recreation within Cambodia (entertainment services, recreational goods andsupplies, tourist travel, hotel accommodation)
Last 12 months
Recreation abroad (entertainment services, recreational goods and supplies,
tourist travel, hotel accommodation)
Last 12 months
Education (school fees, textbooks, private tutoring charges, etc.)

11

Personal effects (costume/gold jewellery, handbags, wallets, wristwatch,clocks, umbrella)

12Gambling (lottery, sports and animal betting: casino gambling, card games,
football, boxing, cockfighting etc.)

07
08
09

13
14
15

Last 12 months
Last 12 months

Last 12 months
Miscellaneous items (special occasions as funeral rituals, weddings, parties, ,cash gifts, charity, etc.)
Regular cash transfers to charities (exclude "non-regular" transfers to charities, Last 12 months
which should be reported in item 15)
Regular Inter-households transfers (regular cash and in kind support to people Last 12 months
living in other households)
Taxes on income (tax on salary)

Last 12 months

Taxes on property (e.g houses, cars)

Last 12 months

16
17

18

INITIAL VISIT

Total 1-17:

Manual Cambodia CSES 2012 Version 2.0

In-kind expenditure or gifts
given away

Total expenditure

(5)

(6)

Q01CC05(Col 4 + Col 5)

Q01CC06

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01. D. VULNERABILITY
Respondent: Head of household, spouse of the head of household or another adult household member

INITIAL VISIT

Q1 Did your family use iodized salt, yesterday?
Ask the respondent for a teaspoon full of cooking salt and test for iodine.

1 = Iodine present
2 = No iodine
3 = No salt in the household
4 = Salt not tested

Q2 In the last 12 months, has this household had enough food all days or were there

1 = Enough food all the last 12 months(>> NEXT SECTION)
2 = Not enough fooddays and weeks with very little or no food so that the household had to starve ("washungry")?

Q3 How many of the last 52 weeks did the household have so little food that it was starving ("was hungry")?

Number of WEEKS:
Write '0' if less than 1 week
Month
1 2

Q4 Which months of the last 12 months did the household starve ("was hungry")?
(1 = January, 2 = February, 3 = March…)
Code "1" if starving and "0" otherwise
Q5 Does the household have an IDPoor Card or other Social Equity Card?

01 = IDPoor Card
02 = Other Social
Equity card
03 = No card forassistance

Note: With starvation means "being hungry" involuntarily.
Note: If one household member is starving than the household is considered to be starving.

END OF INITIAL VISIT

Manual Cambodia CSES 2012 Version 2.0

3

4

5

6

7

8

9 10 11 12

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02. EDUCATION AND LITERACY
Respondent: All household members aged 3 years and older. For children 3-6 years ask their parents.
Please provide information on all members aged 3 years and older who usually reside in this household. If absent person, proxy interview is allowed.

ID NUMBERID
NUMBEROFRESPONDENT

(1)

(1b)

Can
..[NAME]...
read asimplemessage inanylanguage?

Can..[NAME]...
write asimplemessage inanylanguage?

1 = Yes
2 = No

1 = Yes
2 = No

(2)

(3)

Has
..[NAME]...
everattendedschool?

How many
years has...[NAME]…
attendedschool?

(4)(5)

What is the highest level ..[NAME].. hascompleted?

Is ..[NAME]..
currently in theschool system?

What’s thelevel..[NAME]'s.. iscurrently attending?

Is the school
public or private?

98 = Don´t know
88 = No class completed
00 = Pre-school/
00 = Pre-school/Kindergarten
Kindergarten
1 = Public
01 = Class one completed
01 = Class one
2 = Private
02 = Class two completed...
02 = Class two...,
1 = Yes...................
................
09 = Class nine completed without certificate 2 = No (>>11)
11 = Class eleven
1 = Yes...
12 = Class twelve
2 = No (>> 11)...................
Enter
If the child is on 15 = Technical/vocational
completed 11 = Class eleven completed
holidays, he/she pre-secondary diploma/
number of 12 = Class twelve completed without
is considered in certificate
years
the school system 16 = Technical/vocational
certificate
13 = Lower education certificate (diploma)
post-secondary
14 = Higher education certificate (BacII)
diploma/certificate
15 = Technical/vocational pre-secondary
17 = College/university
diploma/certificate
undergraduate studies
16 = Technical/vocational post-secondary
21 = Postgraduate studies
diploma/certificate
17 = College/university undergraduate but nodegree18 = Bachelor degree (B.A., BSc, etc.)
19 = Masters degree (M.A., MSc, etc)
20 = Doctorate degree (PhD)
21 = Other (Specify)
YEARS
(6)

(7)

(8)

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
Note: If he/she pass national exam in class nine or twelve put code 13 or 14 respectively
Note: To continue to class 10 the student must have completed class 9 with diploma (code 13)
Note: Collage/university undergraduate. A student may have completed one or more term/year exam but do not yet
accomplished a degree. Then note down code “17”.

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181

02. EDUCATION AND LITERACY (CONTINUED)
Respondent: All household members aged 3 years and older. For children 3-6 years ask their parents.

ID NUMBER

Please provide information on all members aged 3 years and older who usually reside in this household. If absent person, proxy interview is allowed.
If Col. 4 = 2 or Col.7 = 2 and below 18 Has ..[NAME].. ever Is ..[NAME].. currently What kind of non-formal class is
Is ..[NAME]..
years of age
currently taking
attended non-formal attending non-formal ..[NAME].. currently attending/did
private lessonsclass?
classes?
..[NAME].. attend?
after school?
Why is ..[NAME].. not attending (has never
1 = Literacy programmes(languages,
attended) school?
(6 months)
math, science,
2 = Vocational training (Tailoring,music, sports)?
motor repairing, Khmer classical

(1)

1=Yes
2=No

>>12

(10)

01 = Don’t want to
02 = Did not do well in school
03 = No suitable school available/school is too far
04 = No teacher/Supplies
05 = High cost of schooling
06 = Must contribute to household income
07 = Must help with household chores
08 = Too poor
09 = Due to disability
10 = Due to long term illness (over 3 months)
11 = Too young
12 = Other (specify)(11)

1 = Yes
2 = No (>> 15)(12)

Did ..[NAME]..
attend school
past school year(including nonformal class)?

music training, hairdressing,pottery...etc.
3 = Post literacy programmes
1 = Yes
1 = Yes (>> 16a)
(Agricultural training includes such
2 = No2 = No >> NEXT
(if Col.12 = 1>> 14 else as planting vegetable, mushrooms, PERSON)
raising fish, animal..
>> 15)
4 = Foreign Languages
5 = Computer literacy
6 = Others (Specify)

(13)

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

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(15)

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02. EDUCATION AND LITERACY (CONTINUED)
Respondent: All household members aged 3 years and older. For children 3-6 years ask their parents.
Please provide information on all members aged 3 years and older who usually reside in this household. If absent person, proxy interview is allowed.

If code 1 in col. 15, please fill up columns 16a-16h, otherwise,
leave it blank and continue with next person.
What were the educational expenses for ..[NAME]..during the past school year including the expense on non-formal education and private lesson?

ID NUMBER

Write 0 if no expenses(1)

Note in Col.16e: For educational expenses a way from home should include thing (item) that any household member spent on(bought) while going to study, irrespective of distance from home to school (far or near)

A. School fees(Studying fees)

B. Tuition (suchas paying forprivate lession,
etc...)

C. Text books

D. Other school E. Allowances for F. Transport cost G. Gifts to
supplieschildren studying
teachers, schoolaway from homebuilding/development fund etc.

RIELS

RIELS

RIELS

RIELS

RIELS

RIELS

RIELS

RIELS

(16a)

(16b)

(16c)

(16d)

(16e)

(16f)

(16g)

(16h)

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
Note: ( Col. 16e) "Expenses on studying away from home" includes all amount of money spent (allowances) for thechilds study, regardless of the distance from home to the school.

Manual Cambodia CSES 2012 Version 2.0

H. TOTAL(Col 16a - 16g)

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04. HOUSING
Respondent: Head of household, spouse of the head of household, or another adult household member
The following questions should be asked of the head of household, spouse of the head of household, or of another adult household member, if both head and spouse are absent.

Q1 How many households reside in the same housing unit as your household?

NUMBER OF HOUSEHOLDS:

Q2 What is the floor area of the housing/dwelling unit occupied by your household?

NUMBER OF SQUARE METERS:

Q3 How many rooms in the dwelling unit are usedby the household (other than kitchen, toilet and bathrooms)?

NUMBER OF ROOMS:

Q4 What is the primary construction material of the wall of the housing/dwelling unit occupied by your household?
WALL CODES
1 = Bamboo, Thatch/leaves, Grass
2 = Wood or logs
3 = Plywood

CODE:

4 = Concrete, brick, stone
5 = Galvanized iron or aluminium orother metal sheets
6 = Fibrous cement/Asbestos

7 = Makeshift, mixed materials
8 = Clay/dung with straw
9 = Other, specify

Q5 What are the primary construction material of the roof of the housing / dwelling unit occupied by your household?
ROOF CODES
1 = Thatch/leaves/grass
2 = Tiles
3 = Fibrous cement
4 = Galvanized iron or aluminium

CODE:

5 = Salvaged materials
6 = Mixed but predominantly made of galvanizediron/aluminium, tiles or fibrous cement
7 = Mixed but predominantly made of thatch/leave/grass or salvaged materials

8 = Concrete
9 = Plastic sheet
10 = Other (Specify)

Q6 What are the primary construction material of the floor of the housing / dwelling unit occupied by your household?
FLOOR CODES
1 = Earth, clay
2 = Wooden planks
3 = Bamboo strips

CODE:

4 = Cement/Brick/Stone
5 = Parquet, polished wood
6 = Polished stone, marble

7 = Vinyl
8 = Ceramic tiles
9 = Other (Specify)

Q7 What is your household’s main source of lighting?
LIGHTING SOURCE CODES
1 = Publicly-provided electricity/City power
2 = Generator

CODE:

3 = Battery
4 = Kerosene lamp

5 = Candle
6 = None

7 = Solar
8 = Other (specify)

Q8 What is your household's main source of drinking water in wet season?
DRINKING WATER SOURCE CODES IN WET SEASON

CODE:

01 = Piped in dwelling or on premises (>> Q12)
02 = Public tap
03 = Tubed/piped well or borehole
04 = Protected dug well (including all of the following: lining, headwall,
platform, cover)
05 = Unprotected dug well
06 = Pond, river or stream (fetch water from pond, river, stream)
07 = Pond, river or stream (pump to the house) (>> Q12)

08 = Improved rainwater collection (catchment tank/concrete rain water collectionneeds to have all the following: completely closed, tap to withdraw water and at
least 3000 litres capacity (>> Q12)
09 = Unimproved rainwater collection (>> Q12)
10 = Water bought from tanker truck or vendor (Vendor brought water home,write "0" in distance and >> Q12)
11 = Water bought from tanker truck or vendor (Any household member goes tocollect, write distance in Q9 then ask Q10 and Q11.)
12 = Bottled water
13 = Other (Specify)

Q9What is the distance from home to the drinking water source in wet season (source reported in Q8)?

Q10

Which members of your household are fetching drinking water in the wet season?

Q11

How many minutes per day do they spend in total on fetching drinking water in wet season?

METERS:

IDcode (1)Manual Cambodia CSES 2012 Version 2.0(2)

MINUTES PER DAY:

(3)

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04. HOUSING (CONTINUED)
Q12What is your household's main source of drinking water in dry season?

CODE:

DRINKING WATER SOURCE CODES IN DRY SEASON
01 = Piped in dwelling or on premises (>> Q16)
02 = Public tap
03 = Tubed/piped well or borehole
04 = Protected dug well (including all of the following: Lining,
headwall, platform, cover)
05 = Unprotected dug well
06 = Pond, river or stream (fetch water from pond, river, stream)
07 = Pond, river or stream (pump to the house) (>> Q16)

08 = Improved rainwater collection (catchment tank/concrete rain water collectionneeds to have all the following: completely closed, tap to withdraw water and at
least 3000 litres capacity (>> Q16)
09 = Unimproved rainwater collection (>> Q16)
10 = Water bought from tanker truck or vendor (Vendor brought water home,write "0" in distance and >> Q16)
11 = Water bought from tanker truck or vendor (Any household member goes tocollect, write distance in Q13 then ask Q14 and Q15.)
12 = Bottled water
13 = Other (Specify)

Q13

What is the distance from home to the drinking water source in dry season (source reported in Q12)?

Q14

Which members of your household are fetching drinking water in the dry season?

Q15

How many minutes per day do they spend in total on fetching drinking water in dry season?

MINUTES PER DAY:

Q16

How much water charges did your household pay last month? (Put "0" for not buying water source)

RIELS:Q17

Did your household treat water in anyway to make it safer to drink during the last month?
1 = Yes, always
2 = Sometimes

3 = No, never (>>Q19)

Q18

Q19a

METERS:

IDcode (1)How did you usually treat your drinking water during the last month?
a. Boil water?
c. Chemical?
1 = Yes
2 = Nob. Filter water?
d. White alum?

(2)

(3)

Q04_16e. Other method (Specify)?

What toilet facility does your household have within the premises? (in the area close to the dwelling)
1 = Pour flush (or flush) connected to sewerage
2 = Pour flush (or flush) to septic tank or pit
3 = Pour flush (or flush) to elsewhere (i.e. not a sewer or pit/tank)
4 = Pit latrine with slab
5 = Pit latrine without slab or open pit
6 = Latrine overhanging field or water (drop in the field, pond, lake, river, sea)
7 = None
8 = Other, specify

CODE:

Q19b

What toilet facility does your household usually use?
1 = Toilet that we have
2 = Public toilet/pit latrine or shared with others (any type)
3 = Open land
4 = Other (Specify)

Q20

How much did your household spend for sewage or waste water disposal last month? (Write 0 if nothing)

RIELS:

Q04_20Q21

How much did your household spend for garbage collection last month?

RIELS:

Q04_21

CODE:(Write 0 if nothing)

Manual Cambodia CSES 2012 Version 2.0

18504. HOUSING (CONTINUED)

Q22(a) What type of fuel does your household mainly use for cooking?
FUEL CODES
1 = Firewood
6 = Household generator (>> Q23)
7 = None/don’t cook (>> Q23)
2 = Charcoal
8 = Other (Specify) (>> Q23)
3 = Liquefied petroleum gas LPG (>> Q23)
4 = Kerosene (>> Q23)
5 = Publicly-provided electricity/City Power (>> Q23)

CODE:

1 = Yes (>> Q23)(b) Does the vendor bring the firewood/charcoal home?

2 = No(c) Which household members are collecting or fetching firewood or charcoal?
(1)

IDcode OF HH MEMBER(d) How many hours per week in total do they spend on collecting or
fetching firewood/charcoal?
Q23

(2)

(3)

HOURS PER WEEK:If less than one hour write '0'

How much did the household spend on the following items last month (including lights and cooking)?
RIELS

INCLUDE THE VALUE OF OWN PRODUCTION OR RECEIVED AS PAYMENT IN
KIND FOR WORK OR AS GIFT OR FREE COLLECTION

a. Electricity

Q04_23A

b. Gas (LPG)

Q04_23B

c. Kerosene

Q04_23C

d. Firewood

Q04_23De. Charcoal

Q04_23E

f. Battery

Q04_23F

g. Other (Specify)

Q04_23G( ENTER " 0 " IF DID NOT SPEND ANYTHING )

Q24

Q25a

What's the legal status of the dwelling?
LEGAL STATUS CODE
1 = Owned by the household (>> Q25b)
2 = Not owned but no rent is paid (>> Q25b)
3 = Rented
4 = Other (Specify) (>> Q25b)

CODE:

Q04_24

If rented:
How much did you pay for rent of this house last month? (=>> Q26)

RIELS:

Q04_25A

Q25b

How much would you have to pay per month to rent a similar dwelling? (Estimated value)

RIELS:

Q04_25B

Q26

Whether owned or rented:
RIELS:

Q04_26

How much did you spend on maintenance and minor repairs of the dwelling last month?

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05. HOUSEHOLD ECONOMIC ACTIVITIESRespondent: head of household, spouse of the head of household or another adult household member
The following questions should be asked of the head of household, spouse of the head of household, or of another adult household member,
if both head and spouse are absent.
05.A LAND OWNERSHIP
I would now like to ask you about all land owned or operated by your household. That means all land that is used or could be used for vegetable gardening, agriculturalor farming activities - crop cultivation, livestock raising and private forestry. (Do not include residential land not used to any of these activities)
Q1a Has the household sold any open land in the last 12 months?

1 = YES

1 = To address family health issues
2 = Invest in business
3 = To weed or buy farm equipment or for otheragricultural activities
4 = To pay debt
5 = To buy motor bike or cell phoneor for other household consumption needs
6 = Rituals (marriage ceremony, funeral etc.)
7 = Other (specify)

Q1b What was the primary reason/purpose for which you sold the land?

Q2 Does anyone in your household own or operate any land that is used / could be used forvegetable gardening, agricultural or farming activities (crop cultivation, livestock raising or private
forestry)?

1 = YESQ3 How many plots does your household own or operate?

Note: Use additional questionnaires
if there are more than 7 plots
If owned but rented out
Col 3 = 2

PLOT

NUMBER

1 = Own (>> 4a)
How much would it cost to rent a plot like this in this2 = Own, but rent
village?
out/pawned/granted In cash or in kind(>> 5a)(>> Col 7)
For what time
3 = Rented inperiod?
(>> 6a)Unit
1 = Month
4 = Free use of land
1 = Riel
2 = Season(>> 4a)2 = Kg
3 = Year
5 = Other (specify)
3 = Other
4 = OtherAmount (if in cash) (specify)(specify)
Quantity (if in kind)
(2)

(3)

01

m2

02

m2

03

m2

04

m2

05

m2

06

m

07

m

2 = NO (>> NEXT SECTION E)

NUMBER OF PLOTS:

Please list each plot that your household owns, or rent in from others, or used for free(including owned land that is rented out)
If owned or free use of land
What is the area of the plot in Do you own this2
Col 3 = 1 or 4
land, rent it or have itsquare meters (m )?
in some other way?

(1)

2 = NO (>> Q2)

(4a)

(4b)

(4c)

How much rent do you receive for this plot?
In cash or in kind(>> Col 7)

Amount (if in cash)
Quantity (if in kind)
(5a)

Unit
1 = Riel
2 = Kg
3 = Other(specify)
(5b)

2
2

Note: ( Col. 3) Pawned is treated as one single time rent paid. (Pawn amount=rent paid). Granted is treated as rented out (rent = 0).
Note: ( Col. 3) If the land is rented out or pawned it cannot be used for collateral loan. If granted - it can be used for collateral loan.

Manual Cambodia CSES 2012 Version 2.0

For what time
period?
1 = Month2 = Season
3 = Year
4 = Other(specify)
(5c)

187

LAND OWNERSHIP (CONTINUED)
Please fill out the detailed information for each of the plots your household owns or rent in from others or used for free (including owned land that is rented out)
If rented in
If bought
What type of land is it? In what year did How did you acquire it?
Col 3 = 3
Col 9 = 3 or 4
you first have/start using thisplot ?
01 = Wet-season land
1 = Given by the government
02 = Dry-season landor local authority (>> 11)
How much rent do you pay for this plot?
03 = Wet and dry season
2 = By inheritance or gift from How much did you pay to buy
In cash or in kind
this plot?
landrelatives (>> 11)

PLOT

NUMBER

05.A.

Amount (if in cash)
Quantity (if in kind)
(1)

(6a)

Unit
1 = Riel
2 = Kg
3 = Other(specify)(6b)

For what time
period?
1 = Month2 = Season
3 = Year
4 = Other(specify)

05 = Kitchen garden(backyard)/Chamkar land
06 = Land withpermanent crops
07 = Land for raising
livestock08 = Private forestry land
09 = Idle land
10 = Other land (specify)(6c)3 = Bought it from a relative
4 = Bought it from a nonrelative
5 = Cleared land/occupied forfree (>> 11)
6 = Donated by friend(>> 11)7 = Rented in (>> 11)
8 = Other (specify) (>>11)

YEAR
(7)

Riels

(8)

(9)

(10)

01
02
03
04
05
06
07

NUMBER

Please fill out the detailed information for each of the plots your household owns or rent in from others or used for free (including owned land that is rented out)
All plots
If YES in Col 12
Do you have a paper to
Can you show me the document Whose name is on thecertify your ownership orthat you have for this plot?
ownership document or
How much would it cost to buy a rental agreement?
What kind of paper do you have?
rental contract?
plot like this in this village today?
Enter answer given by respondent Enter 8 if do not see certificate

PLOT

1 = Yes
2 = Never had (>> 15)
3 = Lost it (>> 15)
4 = Don´t know (>> 15)

1 = Application receipt
2 = Land investigation paper
3 = Certificate (title) from thegovernment
4 = Paper from local authority
5 = Rental contract
6 = Other (specify)
7 = Don't know / not sure

Riels
(1)

(11)

(12)

1 = Application receipt
2 = Land investigation paper
3 = Certificate (title) from thegovernment
4 = Paper from local authority
5 = Rental contract
6 = Other (specify)
7 = Don't know / not sure
8 = No paper shown(13a)

1 = Head of household
2 = Spouse
3 = Both head ofhousehold and spouse
4 = Father
5 = Mother
6 = Other relative
7 = Other (specify)

(13b)

01
02
03
04
05
06
07
Note: ( Col. 14) If both the name of the head of household and the name of the spouse is written on the land title - than entercode "3" .

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05. A. LAND OWNERSHIP (CONTINUED)PLOTNUMBER

Please fill out the detailed information for each of the plots your household owns or rent in from others (including owned land that is rented out)
Who is the plot manager? Which crop did you grow on this plot in the last
Can you add water to this plot with Have you made any investments on thisseasons?
irrigation and / or water pumped
plot since you acquired it? (record up to
from the well?
3 most important investments)
Write ID Code if a person 1 = Rice
2 = Other crops (water melon, pumpkin, vegetables, maize,
in your householdbean, potato, etc.)
77 = Other, female not in 3 = Fruit and nut trees (mango, coconut, cashew etc.)
4 = Rubber
the household
5 = Bamboo shoots
88 = Other, male not in the
6 = Bamboo treehousehold
7 = Don't know which crop
99 = Unknown
8 = None

1 = Yes, Wet season
2 = Yes, Dry season
3 = Yes, both seasons
4 = No, cannot irrigate or pumpwater at all for this plot

Enter all crops (up to the 3 most important) if you growmore than one crop
(1)

(15)

(16a)

(16b)

1 = None (=>> 20)
2 = Digging well
3 = Digging ditch / canal
4 = Terracing
5 = Drainage construction
6 = Soil reclamation
7 = Establish fruit and nut trees
8 = Other (specify)Enter the 3 most important

(16c)

(17)

(18a)

01
02
03
04
05
06
07
Note: ( Col. 15) It is not always the owner who is managing the plot. If e.g. the plot is granted to someone notbelonging to the household than the person managing the plot is the "plot user". E.g. code "77" or "88" or even "99".

If more than one
investment, ask about 1 = Yes
the most important
2 = No (>> 22)

1 = Yes, now
2 = Yes, previously
3 = NoPLOTNUMBER

In what year did you make Can you use this plot as collateral for loan? When did you start to Have you ever hadthese investments?
have the rights to use any conflict about thisit as a collateral?
plot?

If don't know, leave
blank

YEAR
(1)

(19)

YEAR
(20)

(21)

(22)

01
02
03
04
05
06
07

NIS code

Manual Cambodia CSES 2012 Version 2.0

(18b)

(18c)

189

05. B. PRODUCTION OF CROPS (INCLUDING FRUITS AND VEGETABLES ETC.)
Please provide the following information on crops, including fruits and vegetables, grown by your household during the past two seasons. Please provide plot-wise details.
Note: Past wet-season should refer to the wet-season last calendar year.
If interview takes place in January - June: past dry-season should refer to the dry-season last calendar year.
If interview takes place in July - December: past dry-season should refer to the dry-season this calendar year.

SERIAL NUMBER

Q1 Did your household produce any crops including fruits and vegetables during the past wet-season or the past dry-season?

(1)

COPY
What crop(s) have yourTHE
household grown (on what plots)?
PLOT
NUMBER
FROM
PART AHow big area wascultivated?

1 = Yes

How big area washarvested?

How much was How much has been How much(quantity) was
produced /the post– harvest
harvested?
loss until the day of given as crop
rent?
interview?

What was the saleprice of the crop
produced per kg?

Note: (6) incl.
(7) and (8)Write '0' if
nothing(2)

2 = No (>> Part E)

Losses mean rotted,
lost, eaten by birds,
rodents, etc.
Write '0' if nothing
Write '0' if nothing

Name of crop or by-product

NIS
code

2

m

2

m

KG

KG

KG

RIELS / Kg

(3a)

(3b)

(4)

(5)

(6)

(7)

(8)

(9)

PAST WET SEASON, What year?.........................................
01

m2

m2 Q05BC06

02

m2

m2

03

m2

m2

04

m2

m2

05

m2

m2

06

m2

m2

07

m2

m2

08

m2

m2

09

m2

m2

10

m2

m2

Q05BC07

Q05BC09

11
PAST DRY SEASON, What year?.........................................
12

m2

m2

13

m2

m2

14

m2

m2

15

m2

m2

16

m2

m2

17

m2

m2

18

m2

m2

19

m2

m2

20

m2

m2

21

m2

m2

22
Note: If different crop on the plot, report the area cultivated for each crop, e.g. split the total plot into smaller areas. If cultivate twice on the same area during one season
report the same area twice AND write a note. This is important! If the reported cultivated area is incorrect reported the total cultivated area in Cambodia can beoverestimatedNote: Area harvested should only be reported if the household have produced any crop on the plot. If no production the harvested area should be '0'.
Note: Sale price means the price per kg the received when they sold the crop OR should have received if they had sold the crop they kept in storage. The sale pricereported for different crop must be reasonable. If you are not sure, discuss with the supervisor.
Note: For Bamboo tree use m 3 instead of kg.

Manual Cambodia CSES 2012 Version 2.0

NIS code190

05. C. COST OF CULTIVATION OF CROPS (INCLUDING FRUITS AND VEGETABLES ETC.)
Please provide the following information on cost of cultivation of crops, including fruits and vegetables, grown by your household during the past two seasons.
Please provide plot-wise details.

SERIAL NUMBER

COPY THE
PLOT
NUMBERFROM PART B

(1)

(2)

Planting materials
Chemical fertilizers,(seeds, seedlings,
pesticide, weedicide
young plants):
and fungicidepurchased/supplied
from home production

Animal and plant
Electricity for theOil, gas or gasoline Storage items (e.g..,manure: purchased/ farming (not including and diesel for theburlap bags, plastic
supplied from home household use!)
farming (not including sheeting etc.)
producehousehold use!)

Payment to hired
draft power (tractors/
animals) including
human labour, if any,for ploughing/harrowing

Write '0' if nothing

Write '0' if nothing

Write '0' if nothing

Write '0' if nothing

Write '0' if nothing

Write '0' if nothing

Write '0' if nothing

RIELS

RIELS

RIELS

RIELS

RIELS

RIELS

RIELS

(3)

(4)

(5)

(6)

(7)

(8)

(9)

PAST WET SEASON
01
02
03
04
05
06
07
08
09
10
11
PAST DRY SEASON
12
13
14
15
16
17
18
19
20
21
22

Manual Cambodia CSES 2012 Version 2.0

191

05. C. COST OF CULTIVATION OF CROPS (INCLUDING FRUITS AND VEGETABLES ETC.) (CONTINUED)
Please provide the following information on cost of cultivation of crops, including fruits and vegetables, grown by your household during the past two seasons.

SERIAL NUMBER

Please provide plot-wise details.

(1)

Other hired labour Irrigation charges Services/
Transportation
technical support of input
charges (cash plus
from government materials,kind)and otherequipment andagencies
products

Repair andRental paid to owner for
maintenance of farm land, farm house,farm house, farm equipment etc. rented inequipment,from others
animal shed etc.

Total
Col. 3-15

Both in cash and in kind
Write '0' if nothing

Write '0' if
nothing

Write '0' if
nothing

Write '0' if
nothing

Write '0' if
nothing

Write '0' if nothing

Write '0' if nothing

RIELS

RIELS

RIELS

RIELS

RIELS

RIELS

RIELS

(10)

(11)

(12)

(13)

(14)

(15)

(16)

PAST WET SEASON

Q05CC16

01
02
03
04
05
06
07
08
09
10
11

TOTAL 01-10:
PAST DRY SEASON

12
13
14
15
16
17
18
19
20
21
22

TOTAL 12-21:

NIS code

Manual Cambodia CSES 2012 Version 2.0

192

05. D. INVENTORY OF CROPS (INCLUDING FRUITS AND VEGETABLES ETC.)
Please provide the following information on crops, including fruits and vegetables, grown by your household
and in storage December 31 last year.
1 = Yes 2 = No (>> Part D2 )SERIAL NUMBER

Did your household have any crops in storage December 31 last year?

(1)

Crop(s) that your household had in storage
December 31 last year

How much of …[CROP]… did What was the sales price for …
your household have in[CROP]… per kg at December
storage at December 31 last 31 last year ?
year?

Last year means 2011

Crop Item

NIS
code

KG

RIELS/KG

(2a)

(2b)

(3)

(4)

01
02
03
04
05
06
07
08
09
10

NIS code

Note: In this module all finished crops (including fruits and vegetables etc.) shall be reported

05.D.2 SALES OF CROPS (INCLUDING FRUITS AND VEGETABLES ETC.)
Please provide the following information on crops (including fruits and vegetables etc.) grown by your household
and sold the last 12 months.

SERIAL NUMBER

Did your household sell any crops (rice, fruits, vegetables, etc.) during the last 12 months?

(1)

Crop(s) (rice, fruits, vegetables, etc.) that your household had
sold during the last 12 months.

1 = Yes 2 = No (>> Part E )How much of …[CROP]… did What was the sales price for …
your household sell during the [CROP]… per kg?
last 12 months?
If different prices try toestimate an average price

Crop Item
(2a)

(2b)

KG

RIELS/KG

(3)

(4)

01
02
03
04
05

NIS code

Manual Cambodia CSES 2012 Version 2.0

19305. E. INPUTS AND OUTPUTS OF LIVESTOCK AND POULTRY RAISING ACTIVITIESSERIAL NUMBER

Q1 Has your household or anyone in your household had any livestock in the past 12 months, that is from ..[MONTH].. last year?
Type of animal or Has anyone inbird
your household
raised any..[LIVESTOCK]..
in the past 12
months?
1=Yes
2=no (>> Next
animal / bird)

(1)

(2)

Number of..[LIVE
STOCK]..
currently
owned ?

Of the total
What would be the..[LIVE
total sales value of
STOCK]..
..[LIVESTOCK]..
currently
currently owned?
owned howmany arefemaleanimals / bird?

If none, write If none, write
'0'
'0'

(3)

Write '0' if nothing

1= Yes 2=No (>> Part F )Number of Number of Total sales value of…[LIVE..[LIVE..[LIVESTOCK]..
STOCK]..
STOCK]..
owned December 31
owned 12 owned
last year at the premonths ago, December vailing prices?
that is [in31 last year?
MONTH] lastyear?

Value of..[LIVESTOCK]..
sold during the past
12 months?

If none, write
If none write'0''0'

Write '0' if nothing

Write '0' if nothing

NUMBERNUMBERRIELS

NUMBERNUMBER

RIELS

RIELS

(4)

(5)

(6)

(7a)

(7b)

(8)

(9)

Q05E1C09

01 Cattle
02 Buffaloes
03 Horses, Ponies
04 Pigs
05 Sheep
06 Goats
07 Chickens
08 Ducks
09 Quail
10 Other (specify)

SERIAL NUMBER

11 TOTAL 01 - 10:
Type of animal or Total paid for ..
Imputed value of meat products frombird
LIVESTOCK].. bought
livestock/poultry in riels
during the past 12
Consumed in theUsed for barter, gifts,
months?
household during the past charity, etc. during the
12

(2)

(1)

01 Cattle

th

t 12

th

Value of other products than meat (milk, butter, eggs, hide and skin, manure etc.)
sold, consumed in household, used as gifts etc. during the past 12 months
Sold

Consumed in household

Gifts, charity, barter etc.

Write '0' if nothing

Write '0' if nothing

Write '0' if nothing

Write '0' if nothing

Write '0' if nothing

Write '0' if nothing

RIELS

RIELS

RIELS

RIELS

RIELS

RIELS

(10)

(11)

(12)

(13)

(14)

(15)

Q05E1C10

Q05E1C11

Q05E1C12

Q05E1C13

02 Buffaloes
03 Horses, Ponies
04 Pigs
05 Sheep
06 Goats
07 Chickens
08 Ducks
09 Quail
10 Other (specify)
11

TOTAL 01 - 10:

Manual Cambodia CSES 2012 Version 2.0

Q05E1C14

Q05E1C15

194

NIS code
05. E. INPUTS AND OUTPUTS OF LIVESTOCK AND PULTRY RAISING ACTIVITIES (CONTINUED)
How much did your household spend on the following
items during the past 12 months?
Write '0' if nothing

ITEM
NUMBERITEMSAMOUNT IN RIELS

(1)

(2)

(3)

1

Feed and feed supplements (e.g. rice straw) for livestock/poultry - purchased

2

Feed and feed supplements (e.g. rice straw) for livestock/poultry- supplied from home farm/public land

3

Hired labour to care for the livestock/poultry (cash plus kind)

4

Veterinary services and medicine

5Service /technical support from government/other agencies

6

Transporting livestock/poultry, livestock/poultry products, manure, feed and feed
supplements to/from market

7

Q05E2C03

TOTAL 1 - 6:

Note: If animal and poultry consider about the feed and feed supplements (in Item No 1 and 2).

Manual Cambodia CSES 2012 Version 2.0

NIS code195

05. F. INPUTS AND OUTPUTS FROM FISH CULTIVATION AND FISHING/TRAPPING OF AQUATIC PRODUCTS
Q1 Did your household or anyone in your household raise fish (or any other aquatic product like frogs or
crocodiles) during the past 12 months?

1 = Yes

2 = NoQ2 Does your household or anyone in your household own or operate a pond for fish or shrimp culture?

1 = Yes

2 = No (>> Q3)

POND NUMBER

Note : Pond is a small body of standing water formed naturally or often artificially made. It is smaller than a lake.
Do you own this pond, rent it or have it some otherway?
1 = Own
2 = Own, but rent out
3 = Rented in from others
4 = Free use of pond
5 = Other (specify)

(1)

AREA
MARKET VALUEMONTHLY RENT
How many square meters is the How much would you have to How much would you have to
pond?
pay to buy a pond like this in pay monthly to rent a pond likethis in this village?
this village?

SQUARE METERS

RIELS

RIELS

(3)

(4)

(5)

(2)

Q05F1C05

1
2
3

NIS code

Q3 Did your household or anyone in your household catch fish, shrimp, crabs,
oysters, etc. during the past 12 months?

1 = Yes

2 = NoITEM NUMBER

If Yes on Q1 or Q2 or Q3, please ask the following questions. If No on all 3 questions (Q1-Q3) >> G
EXPENSES

Amount spent

How much did your household spend on the following items
during the past 12 months?

Write '0' if nothing

ITEM

RIELS

(2)

(3)

(1)

01 Breeding stock for raising fish/shrimp etc.

Q05F2C03

02 Feed for raising fish/shrimp etc.
03 Hired labour (cash plus Kind)
04 Ice05 Repair and maintenance of nets and traps etc.
06 Repair and maintenance of boat
07 Boat fuel08 Boat rent (cash)
09 Cash rent for tank, if leased in
10 Transportation of fish/shrimp/crab etc. to market
11 Services (technical assistance) received
12 Other (specify)
13

Total 01 - 12:

NIS code

Manual Cambodia CSES 2012 Version 2.0

196

ITEM NUMBER

05. F. INPUT AND OUTPUTS FROM FISH CULTIVATION AND FISHING/TRAPPING OF AQUATIC PRODUCTS (CONTINUED)INCOME

Amount received

How much did your household receive under the following item during the past 12
months?

Write '0' if nothing

ITEM

RIELS

(2)

(3)

(1)

01 Proceeds from sale of fish, shrimp, crab etc. raised or captured (*)(*) Do not include
fish, shrimp, crabetc (paid in-kind) for
renting boat or
tank..

Q05F3C03

02 Value of fish, shrimp, crab etc. consumed in household
03 Value of fish, shrimp, crab etc. given away as gift, charity, barter, etc.
04 Value of fish, shrimp used for drying (dried fish/shrimp, smoked fish etc.)
05 Value of fish, shrimp used for preparation of fish/shrimp sauce
06 Value of fish, shrimp used for animal feed
07 Value of fish, shrimp used for other (specify)
Total 1 - 7:

08

NIS code

05. G. INPUTS AND OUTPUTS FROM FORESTRY AND HUNTING
Q1 Did anyone in your household collect firewood, charcoal, timber or other forest products during the past 12 months?

1 = Yes

2 = NoQ2 Did anyone in your household collect palm juice, root crops, herbs, honey or hunt wild animals or birds during the past 12 months?

1 = Yes

2 = NoPRODUCT NUMBER

If YES on Q1 or Q2 ask the following questions, if NO on both of them >>Part H
What were the value of products that your household collected in this way
during the past 12 months?

INCOME(1)

Write '0' if nothing
Receipts from sale of Imputed value of
Imputed value of
products gathered or such products
such products given
hunted?
consumed in theaway for gifts, charity,
household?
barter, etc.?

Total amount(Col. 3 - 5)

ITEM

RIELS

RIELS

RIELS

RIELS

(2)

(3)

(4)

(5)

(6)

01 Sawing logs

Q05G1C06

02 Firewood
03 Wood for charcoal
04 Rattan, bamboo, palm leaves, other fibrous material
05 Palm juice
06 Root crops, fruits and vegetables
07 Herbs
08 Honey
09 Wild animals and birds
10 Other products (specify)
11

Total 01 - 10:

NIS code

Manual Cambodia CSES 2012 Version 2.0

197

05. G. INPUTS AND OUTPUTS FROM FORESTRY AND HUNTING (CONTINUED)ITEM NUMBER

EXPENSES

Amount spent

How much did your household spend on thefollowing items during the past 12 months?

(1)

Write '0' if nothing

ITEMS

RIELS

(2)

(3)

01 Transport costs including transport to market

Q05G2C03

02 Fuel03 Draft animal feed
04 Hired labour charges
05 Tools, equipment, including maintenance
06 Commissions, tips, rents, etc.
07 Other (specify)
08

Total 1 - 7:

NIS code05. H. LIST OF HOUSEHOLD NON-AGRICULTURAL ECONOMIC ACTIVITIES DURING THE PAST 12 MONTHSACTIVITY NUMBER

Q1 Did anyone in your household run an enterprise or business during the past 12 months?

(1)

DESCRIPTION OF THE ACTIVITY
Write a clear description of theactivity (see field manual page 65)(2)

2 = No (>> NEXT SECTION)

1 = Yes

ID CODE OF

MAIN PRODUCTIn this column themain product should
NIS
be described
INDUSTRY
CODE
(3)

Main
Other household members participating in the activity
personrunning theenterprise/business

(4)

(5)

1º

2º

3º

4º

5º

6º

7º

8º

(6a)

(6b)

(6c)

(6d)

(6e)

(6f)

(6g)

(6h)

01
02
03
04
05
06
Note: Use page 27-28 if there are more than 3 activities running by the household.

NIS code

Note: Write a clear description of the activity. For example: If a household produce and then sell the product (or by-product) they have produced,
write that the household produce and also sell the produced product.

Manual Cambodia CSES 2012 Version 2.0

198

05. H. LIST OF HOUSEHOLD NON-AGRICULTURAL ECONOMIC ACTIVITIES DURING THE PAST 12 MONTHS (CONTINUED)
COST NUMBER

How much did you spend on the different items listed for activity 1, during the past 12 months, that is since..[MONTH].. last year? (Use the same question for activity 2 to 6)
Write '0' if nothing(1)

Activity 1

Activity 2

Activity 3

COST ITEM

RIELS

RIELS

RIELS

(2)

(3)

(4)

(5)

Q05H2C03

Q05H2C04

Q05H2C05

01

02

Capital goods to be used for the production such asmachines, cars, motorbikes
Raw material used for processing
This item should be used for ALL kind of activity where
you buy raw material: Rice for producing rice noodles,
soya beans for producing Tofu, wood for making furniture,stone for making sculpture etc.

04

Materials used for construction
Fuels used for production or generation of electricity,
service etc.

05
06

Lubricants
Purchase of goods for resale (only trade)

03

Report all goods bought for resale in a shop, market etc.
By resale means that the good is not used for processing,i.e. fresh vegetables bought from a farmer for resale freshin the market, cigarettes bought to sell in a shop in front of
the house etc.
07

Food, drink and tobacco products served tocustomers
All food, drinks and tobacco bought to serve to customers
in "restaurants" (all places where food is served, evenmobile restaurants), which means meat, vegetables forcooking, coca cola, beer, cigarettes etc.

08Electricity purchased

09

Water and sanitation charges

10

Containers, packing materials

11

Freight and transport expenses

12

Insurance

13

Bank charges

14

Telephone, postage and other communication

15
16

18

Office supplies, stationary and other items
Rents paid for land, buildings, storage, warehousing,equipment & machines
Repair/maintenance of buildings, equipment &machinery/material/services
Registration and other govt. fees, taxes, market fees("Phasy") and donations

19

Wages/salaries of hired labour (cash plus kind)20
21

Services rendered by others (commissions, etc.)
All other expenses not included in the list from 1 to 17

17

Exclude Capital goods to be used for the production, suchas machines, cars, motorbikes. They are registered inrow 19 above.
22

Total 01 -21:

Note: Use page 27-28 if there are more than 3 activities running by the household.

Manual Cambodia CSES 2012 Version 2.0

NIS code

199

REVENUE NUMBER

05. H. LIST OF HOUSEHOLD NON-AGRICULTURAL ECONOMIC ACTIVITIES DURING THE PAST 12 MONTHS (CONTINUED)
How much did your household receive under the different items listed for activity 1, during the past 12 months, that issince ..[MONTH].. last year?
(Use the same question for activity 2 to 6)

Q05H3C01

Activity 1

Write '0' if nothing
Activity 2

Activity 3

REVENUE ITEM

RIELS

RIELS

RIELS

(1)

(2)

(3)

(4)

(5)

01

Receipts from sale of products and by-products fromown production

Q05H3C03

Q05H3C04

Q05H3C05

Products and by-products which the household has
produced by buying raw material or using own produced
raw material

03

Charges for repair services
Other professional and service charges andcommissions, etc.

04
05

Charges for construction work done
Proceeds from sale of goods sold (only trade)

02

Proceeds for sale of goods you purchased for resale(see item 05 - cost item)
06
07

Charges for board and lodging
Receipts from sales/services at hotels/restaurants
All kind of restaurants, include small restaurant in front of
the house,in market etc

08
09
10
11

Charges for transport services provided (taxi, mot

Imputed value of products/goods for resale, etc.
consumed in the household
Imputed value of products/by-products used asintermediate goods
Imputed value of products/by-products used as gifts,
charity, etc.

13

Supply of electricity, gas and water
Rental income from land & buildings & storage &warehousing

14

Rental income from equipment and machinery

15

Charges for financial / insurance / real estate services

16

Charges for medical services

17

Charges for educational services

18

20

Charges for recreational and cultural services
Charges for other community, social and personal
services
All other income receipts and charges from the activity
not included in (01-19)

21

Total 01 - 20:

12

19

NIS code
Note: Use page 27-28 if there are more than 3 activities running by the household.

Manual Cambodia CSES 2012 Version 2.0

200

05. H. LIST OF HOUSEHOLD NON-AGRICULTURAL ECONOMIC ACTIVITIES DURING THE PAST 12 MONTHS (CONTINUED)

COST NUMBER

How much did you spend on the different items listed for activity 1, during the past 12 months, that is since..[MONTH].. last year? (Use the same question for activity 2 to 6)
Write '0' if nothing(1)

Activity 4

Activity 5

Activity 6

COST ITEM

RIELS

RIELS

RIELS

(2)

(6)

(7)

(8)

01

02

Capital goods to be used for the production such asmachines, cars, motorbikes
Raw material used for processing
This item should be used for ALL kind of activity where
you buy raw material: Rice for producing rice noodles,
soya beans for producing Tofu, wood for making furniture,stone for making sculpture etc.

04

Materials used for construction
Fuels used for production or generation of electricity,
service etc.

05
06

Lubricants
Purchase of goods for resale (only trade)

03

Report all goods bought for resale in a shop, market etc.
By resale means that the good is not used for processing,i.e. fresh vegetables bought from a farmer for resale freshin the market, cigarettes bought to sell in a shop in front of
the house etc.
07

Food, drink and tobacco products served tocustomers
All food, drinks and tobacco bought to serve to customers
in "restaurants" (all places where food is served, evenmobile restaurants), which means meat, vegetables forcooking, coca cola, beer, cigarettes etc.

08Electricity purchased

09

Water and sanitation charges

10

Containers, packing materials

11

Freight and transport expenses

12

Insurance

13

Bank charges

14

Telephone, postage and other communication

15
16

Office supplies, stationary and other items
Rents paid for land, buildings, storage, warehousing,equipment & machines
Repair/maintenance of buildings, equipment &machinery/material/services

17

18

Registration and other govt. fees, taxes, market fees("Phasy") and donations

19

Wages/salaries of hired labour (cash plus kind)20
21

Services rendered by others (commissions, etc.)
All other expenses not included in the list from 1 to 17

22

Exclude Capital goods to be used for the production, suchhit bik Thi Totalt d i01 -21:

NIS code

Manual Cambodia CSES 2012 Version 2.0

REVENUE NUMBER

201

How much did your household receive under the different items listed for activity 1, during the past 12 months, that issince ..[MONTH].. last year?
(Use the same question for activity 2 to 6)
Write '0' if nothing

Activity 4

Activity 5

Activity 6

REVENUE ITEM

RIELS

RIELS

RIELS

(1)

(2)

(6)

(7)

(8)

01

Receipts from sale of products and by-products fromown production
Products and by-products which the household has
produced by buying raw material or using own produced
raw material

03

Charges for repair services
Other professional and service charges andcommissions, etc.

04
05

Charges for construction work done
Proceeds from sale of goods sold (only trade)

02

Proceeds for sale of goods you purchased for resale(see item 05 - cost item)
06
07

Charges for board and lodging
Receipts from sales/services at hotels/restaurants
All kind of restaurants, include small restaurant in front of
the house,in market etc

08
09
10
11

Charges for transport services provided (taxi, mot
Imputed value of products/goods for resale, etc.
consumed in the household
Imputed value of products/by-products used asintermediate goods
Imputed value of products/by-products used as gifts,
charity, etc.

13

Supply of electricity, gas and water
Rental income from land & buildings & storage &warehousing

14

Rental income from equipment and machinery

15

Charges for financial / insurance / real estate services

16

Charges for medical services

17

Charges for educational services

18

20

Charges for recreational and cultural services
Charges for other community, social and personal
services
All other income receipts and charges from the activity
not included in (01-19)

21

Total 01 - 20:

12

19

NIS code

Manual Cambodia CSES 2012 Version 2.0

202

06. HOUSEHOLD LIABILITIESRespondent: Head of household, spouse of the head of household, or another adult household member
Q1 Does your household have outstanding debts to other households or institutions?

LOAN NUMBER

How old is the
debt? (Incompletedmonths)(1)

01

In how many months From whom did yourwill the debt be fully household obtain the loan?
paid back?

1 = Yes

2 = No (>> NEXT SECTION)

What was the primary purpose for which What was the total
your household borrowed the money? amount borrowed?

01 = Relatives in Cambodia
02 = Relatives who live abroad 01 = Agricultural activities
02 = Non-agricultural activities
Since how
Note: How many 03 = Friends/neighbours
03 = Household consumption needs
many months months from this 04 = Moneylender05 = Trader
04 = Illness, injury, accident
did yourmonth
06 = Landlord
05 = Other emergencies (fire, flood,household07 = Employer
theft)
obtain the loan
08 = Bank
06 = Rituals (marriage ceremony,
Put '0' if less than
09 = NGO (non-profit andfuneral etc.)
one monthprofit)07 = Purchase/improvement of dwelling
10 = Other (specify)
08 = Purchase of consumer durables
Put '0' if less
09 = Servicing and existing debts
than one month Leave blank if Don't
10 = Other (specify)
know
MONTHSMONTHS

If more than one enter themost important

(2)

(3)

(4)

(5)

Q06_C05

02
03
04
05
06

Manual Cambodia CSES 2012 Version 2.0

How much is the
If interest isoutstanding loan now charged, what is(this month)?
the monthly rateof interest?
Interest should not
be included
Refer to theoutstanding
loan in Col 7

If no interest,
write '0'
Leave blank if
Don't know
RIELS

RIELS

PERCENTAGE

(6)

(7)

(8)

Q06_C07

Q06_C08

203

07. HOUSEHOLD INCOME FROM OTHER SOURCES
Respondent: Head of household, spouse of the head of household, or another adult household member

SOURCE NUMBER

How much did your household receive from ..[SOURCE].. during the last 12 months?

Q07_C01

REVENUE ITEMS(1)02

Remittances from other relatives or others
Governmental scholarships, stipends for any student member of thehousehold
Other scholarships, stipends for any student member of the household(NGO, private institutions etc.)

06

Transfers (assistance/support) from NGO or other institutions (not credit)
Income from lottery and gambling (Include all kind of lottery andgambling winnings)

07

Bank interests

08

Dividends

09
10

Interests on loans to others (only interest)
Imputed value of goods received through barter (not recorded
elsewhere)

11

Imputed value of gifts received (not recorded elsewhere)

12

Sold land

13

Other sold property such as house, car, jewellery

14

Other (not included in 1 to 14)

05

15

Total
(Col 3 + Col 4)

Write '0' if nothing
IN RIELS

Write '0' if nothing
IN RIELS

Write '0' if nothing
IN RIELS

(3)

(4)

(5)

Q07_C03

Pensions, social welfare/benefits, provident fund04

From abroad

(2)

01

03

From Cambodia

Q07_C04

Q07_C05

Total received: 01 - 14:

Note: Income from economic activity will be reported in module 05 (agricultural and non-agricultural activity) and in module 15 (salary if paid employee)

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8. CONSTRUCTION ACTIVITIES IN THE PAST 12 MONTHS
Respondent: Head of household, spouse of the head of household, or another adult household member
Q1 Does the household own its own dwelling or any other building(s) used for residential, agricultural, commercial or industrial purposes?
Note: This section refer to all buildings owned by the household, that means the building the household live in and all other buildings that are
owned by the household
2 = No (>> NEXT SECTION)

BUILDING NUMBER

1 = Yes
What is the building used What is the What year wasfor?
total area for the building
living orconstructed?
1 = Residential
other use of
2 = Agricultural
the building? Enter the year
3 = Commercial
when the(purchase/sale ofconstruction
goods and services)
was finished
4 = Industrial(manufacturing)

Enter the three mostimportant
(1)

(2a)

(2b)

SQUAREMETERS(2c)

How much would you How much would you Is any part of this How much does your Was this building
have to pay to buy a have to pay perbuilding rented household receive in constructed,
building like this in the month to rent aout?
monthly rent for this extended or repaired
village (where thebuilding?
in the last 12 months,
building like this in thebuilding isthat is, sincevillage (where thelocated)?
..[MONTH].. lastbuilding is located)?
year?
1 = Yes
2 = No (>> 9)
If don´t know, leaveblank

If don´t know, leave
blank

YEAR

RIELS

RIELS

(4)

(5)

(6)

Leave blank if
not yet finished(3)

Q08_C05

1

1 = Yes
2 = No (>> NEXT
BUILDING)

RIELS
(7)

(8)

(9)

Q08_C06

2
3
4

BUILDING NUMBER

What kind of work
was it?

(1)

In what year and month In what year and month Who built this building?
did the construction start? did people start to use thisbuilding?
1 = Household members only

1 = Constructed
2 = Extension (>>14)
3 = Repair (>> 14)(if not yet used leave it
blank for month andyear)

Enter the mostimportant

MONTH

YEAR

MONTH

YEAR

(10)

(11a)

(11b)

(12a)

(12b)

2 = Household members and other relatives
3 = Household members and hired help
4 = Contracted builder
5 = Other (specify)

How much did your household pay those
who helped constructing, extending or
repairing this building (hired or contracted)?

Write '0' if nothing and leave it blank if don´tknow
For building still under work ask forthe cost up till now

RIELS
(13)

1
2
3
4
Note: If the kind of work is both extension and repair report "Extension" and include reparation in the amount in column 14-16

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8. CONSTRUCTION ACTIVITIES IN THE PAST 12 MONTHS (Continued)
For buildings not yet completed:
If not possible to separate If anyone in the household has If anyone else not belonging tolabour and materials:
the household has put in own
put in own labour for
labour try to estimate the value
constructing, extending orof it as if you had engaged
repairing this building try to
What is the estimated remaining cost of
someone to do it?
estimate the value of it as if
the building's construction, extension orWrite '0' if nothing and leave it How much were the total
you had engaged someone toblank if don't know
repair to be completed?
costs?
do it?

BUILDING NUMBER

How much did your householdspend for materials?

(1)

For building still under work
ask for the cost up till now

Write '0' if nothing

Write '0' if nothing

RIELS

RIELS

RIELS

RIELS

RIELS

(15)

(16)

(17)

(18)

(19)

1
2
3
4
Note: If the household cannot separate the costs for labour and material fill out column 16 and leave column 14 and 15 blank.

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09. DURABLE GOODS
Respondent: Head of household, spouse of the head of household, or another adult household member
For items bought or
Did you buy it, receive it as a gift, How many of this (these) For items bought or
as pay for work or in other way? ..[ITEM].. were acquired received within the last received before the
12 months:
last 12 months:
or received...:If more than one item ask foreach item and put a code ineach column. If more than 4
What was the purchase According to current
ask for the 4 most recent
value (or the imputed
prices, what do you thinkvalue) of all these
you could get if you sold
1 = Purchased..[ITEM]s..?
..[ITEM]s..?
a. Within the b. Before the
2 = Payment for services
last 12
last 12TOTAL 3 = Received as a giftmonths?
months?
NUMBER 4 = Other (specify)
RIELS
RIELS

How many of the following items does your household own?

ITEM NUMBER(Write '0' if none and =>> Next item)ITEM

PRODUCT
CODE

(2)

(3)

(1)

(4)

(5a)

(5b)

(5c)

(5d)

(6a)

(6b)

(7)

Home Electronics
01 Radio (Vitju)

801

02 Television (TV)802

03 Telephone817

04 Cell phone818

05 Video/VCD/DVD player/recorder807

06 Stereo

808

07 Camera (picture/video)809

08 Satellite dish824

Personal transport
09

Bicycle (including bicycle with battery help
engine)803

10 Motorcycle (including electrical moto's)804

11 Car829

12 Jeep/Van

830

Household equipment
13 Sewing machine

806

14 Refrigerator

810

15 Electric Kitchen/Gas Stove813

16 Washing machine819

17 Dishwasher

820

18 Freezer

821

19 Vacuum cleaner

822

20 Electric iron823

21 Electric fan

811

22 Air conditioner

812

23 Suitcases/box for store/ travelling890

Note: 23 includes wooden boxes used when travel, bigger canvas bags with zipper (or the like) and bigger back packers etc.

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ITEM NUMBER

09. DURABLE GOODS
For items bought or
How many of the following items does your household own? Did you buy it, receive it as a gift, How many of this (these) For items bought or
as pay for work or in other way? ..[ITEM].. were acquired received within the last received before the
12 months:
last 12 months:(Write '0' if none and >> Next item)or received...:If more than one item ask foreach item and put a code ineach column. If more than 4
What was the purchase According to current
ask for the 4 most recent
value (or the imputed
prices, what do you thinkvalue) of all these
you could get if you sold
1 = Purchased..[ITEM]s..?
..[ITEM]s..?
2 = Payment for services
a. Within the b. Before the
3 = Received as a gift
PROlast 12
last 12TOTAL 4 = Other (specify)
DUCT
ITEM

CODE

NUMBER

(2)

(3)

(4)

(1)

24 Generator

816

25 Batteries

891

(5a)

(5b)

(5c)

months?

months?

(6a)

(6b)

(5d)

Furniture
26 Sofa set

814

27 Dining set (dining table + chairs)

815

28 Bed sets (Bed, Mattress…)*)892

29 Wardrobe, cabinets

893

Computers and printers
30 Computer (desktop or laptop)

825

31 Printer826

Recreation
32 Musical instruments

827

33 Sport equipment

828

Water transport
34 Rowing boat

831

35 Motor Boat

832

Agriculture and other production
36 Cart (pulled by animal)

805

37 Tractor

833

38 Bulldozer/roller

834

39 Plough835

40 Threshing machine837

41 Harrow/rake/hoe/spade/axe…

838

42 Hand Tractor (Kou Yon)

839

43 Rice mill840

44 Water pump

836

Other items
45 Other (specify)

841

46 Other (specify)

894*) Refer to the bed. If the household only have a bed (without a mattress, cushions etc ..) report that.

Manual Cambodia CSES 2012 Version 2.0

RIELS

RIELS

(7)

(8)

208

10. MATERNAL HEALTH

Respondent: All women with living children under 5 years old

LAST PREGNANCY & DELIVERY
1= Yes 2=No (>> SECTION 11 )Q1 Are there any women living in the household with living children under 5 years old?
Note: The child can be living in another household.
Please provide the following information on the last pregnancy. Ask the woman personally!

SERIAL NUMBER

COPY ID CODE ID No. of child if living During this pregnancy
Did you see anyone for
OF THE
in the household
did you suffer from night antenatal care for this
MOTHER
pregnancy?
blindness?
FROM
ROSTER

Leave blank if the childis not living in the
1 = Yeshousehold2 = No
8 = Don't know

1 = Yes
2 = No
8 = Don't know

Where did you
give birth?

Who assisted you in the deliveryof the child?

Enter Code1 = Doctor/Medical assistant
2 = Nurse
If don't know 3 = Midwife
4 = Traditional birth attendant
enter '98'
5 = Relative/friend
6 = Other (Specify)
7 = None
Leave it blank
if don't know
(Enter up to 4
most important persons)

(1)

(2)

(3)

(4)

(5)

(6)

(7a)

(7b)

(7c)

(7d)

01
02
03
04
Note: If the woman is not in the household (absent) during the interview month, leave blank in column 4-7.

Manual Cambodia CSES 2012 Version 2.0

Codes for col. 6
Home:
01 = Your home
02 = Midwife/TBA home
03 = Other home (specify)
Public sector:
04 = National Hospital (PP)05 = Province Hospital (RH)
06 = District Hospital (RH)
07 = Health Centre
08 = Health Post
09 = Military Hospital
10 = Other Public (Specify)
Private Medical Sector
11 = Private Hospital
12 = Private Clinic
13 = Other Private (Specify)
Other:
14 = Other (Specify)
Overseas Medical Service:
15 = Overseas Medical Service

209

11. CHILD HEALTH

Respondents: Mothers or caretakers of children under 2 years old

YOUNGEST CHILD & AND ALL CHILDREN UNDER 2
1= Yes 2=No (>> SECTION 13 )Q1 Check in the household list if there are any children 00-23 months old living in the household?

SERIAL NUMBER

Please provide the following information on the youngest child of each mother and all children 00-23 month old(1)

COPY ID CODE COPY ID Is this your youngest Did you ever breastfeed How long after birth did you first put the
OF THE
CODE OF child?
child to the breast?
your child?
MOTHERTHE CHILDFROMFROMROSTERROSTER
1 = Yes
2 = No (>> 9)(2)

If less than one hour record '00' hours 1 = Yes
If less than 24 hours record hours 2 = No
Otherwise record days

1 = Yes
2 = No(>> 9)

Leave blank if
themother/caretaker is notliving in thehouseholdAre you stillbreastfeeding?

If don't know, leave blank

(3)

(4)

(5)

HOURS

DAYS

(6a)

(6b)

(7)

01
02
03
04
05
06
07

SERIAL NUMBER

Now I would like to ask you about liquids your child drankyesterday during day or night.
Did your child drink …..
A. Infant formula or any other milk such as tinned,
condensed or fresh animal milk
B. Plain water, fruit juice such as coconut juice, tea

Have this child everWhere did the child receive
received a vaccination? most of the vaccinations?

1 = Yes
2 = No (>> NEXTCHILD)
8 = Don't know(>> NEXT CHILD)

1 = Yes
2 = No
8 = Don't know
(1)

01

A

B

(8a)

(8b)

(9)

1 = Outreach activities
2 = Health centre
3 = National, provincial,
district hospital
4 = Private clinic
5 = Other (specify)

(10)

.

02
03
04
05
06
07

Manual Cambodia CSES 2012 Version 2.0

Do you have a yellow card
where [NAME]'s vaccinations
are written down?
If 'Yes': Can I see the yellow
card?

1 = Yes
2 = No(>> NEXT CHILD)

(11)

210

13. HEALTH CARE SEEKING & EXPENDITURE
Respondent: Head of household or the spouse of the head of household
The following questions should be asked of the head of household, spouse of the head of household, or another adulthousehold member, if both head and spouse are absent.
A. SUBSIDIZED HOUSEHOLD HEALTHCARE
Q1 In the last 12 months, has any member of the household received free orsubsidized health care that other people would normally have to pay for?
(including private health insurance)
Q2 How did they obtain this free / subsidized treatment?

If the household has obtained
free / subsidized treatment in morethan one way, record up to the 3 ways.
If more than 3 ways record
the most recent

1 = Yes

2 = No (>> Q4)

8 = Don't know

1 = Household Priority Access Card, Equity Card, or other document that allows free orsubsidized health care
2 = Name(s) are on a List of Poor Households held by the local authorities
3 = Health facility staff asked them questions from a list / filled out a form before treatment
4 = Health facility staff provided free treatment (without asking questions or filling out aform)
5 = Have private health insurance
6 = Belong to community health insurance scheme
7 = Other (specify)
8 = Don’t know

Q3 When they received free / subsidized treatment, were they treated thesame as other people who were paying for their healthcare?

1 = Yes, always treated the same
2 = Yes, most times treated the same

4 = No, most times not treated the same
5 = No, never treated the same

3 = Sometimes yes, sometimes no

8 = Don’t know

Q4 If Q1 = 2, Otherwise (>> Col.2 next page)
Do you or any member of the household have a Priority Access Card, Equity Card, or any otherdocument that allows free or subsidized health care?

1 = YesManual Cambodia CSES 2012 Version 2.0

2 = No

8 = Don't know

a.
b.
c.

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13. HEALTH CARE SEEKING & EXPENDITURE (CONTINUED)
Respondent: Head of household or the spouse of the head of household
Please provide information on all members who usually reside in this household.
B

ILLNESS AND HEALTHCARE EXPENDITURE DURING THE LAST 30DAYS
Please tell me if any
member of yourhousehold is sick, has an
illness or injury now or at
any time in the last 30
days.

If an illness
What kind of
illness (mainpresenting) did… [Name} …
have in the last
30 days?

How many days did
this illness/injury
stopped ..[NAME]..
from doing usual
activities?

Was consultation Has there been any other reason toor treatment
go to a health facility or seek healthsought for this care?
illness/injury?
If no, PROBE
Has this person received care in
Refer to the last relation to a pregnancy,
immunization or supplementation?
30 days

ID NUMBER

It should be the same Refer to the last 30 days
illness that comes andgoes (chronic)
1 = Fever
1= Yes2 = Cough2= No (>> 6)
Enter number of
3 = Diarrhoea
3= No usual activities
1 = Yes
4 = Flu(>> 6)
1=
Yes
Refer to the last 30 2 = No
5 = Other (specify)(e.g. small children, old
2 = Nodays
person, etc.)

1 = Yes
2 = No (>> 7)

Only ask if an
illness
If injury leave
blank
(1)

If an illness
Was ..[NAME].. so ill
Did …[Name} …have this (because of illness/injury)
illness for more than one that s/he could not do
his/her usual activities?
year already?

(2)

(2a)

1 = Antenatal care
2 = Delivery
3 = Postnatal care
4 = Vitamin A or deworming
5 = Health check6 = Other (specify)

If injury leave blank

Register 0 if no.
Number of days
(3)

(4)

(5)

(6)

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
Note: The first 3 codes in column 7 are valid only for women. Code 5 means health checks for students, for work, HIV before marriage etc.

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13. HEALTH CARE SEEKING & EXPENDITURE (CONTINUED)
Respondent: Head of household or the spouse of the head of household
Please provide information on all members who usually reside in this household.

ID NUMBER

B(1)

ILLNESS AND HEALTHCARE EXPENDITURE (CONTINUED)
Ask if answer in Was ..[NAME].. How many nights How much in total was
In the last thirty days, In the past 30
How much in total was
How was the treatment
how many times did days, which was Col. 8 is more hospitalised for was .. [NAME].. spent on transport to go to spent on treatment at any financed?
than 1
hospitalised[NAME] seek health the first provider
the treatment/
and return from any health health provider in the pastcare for illness, injury, that wascare during the during the last 30 provider in the past 30
30 days?
1 = Household incomedays?
or any other reason? consulted forlast 30 days?
days?
2 = Savings
In the past 30[NAME]'s health?
3 = Borrowing
days, which was
4 = Selling assets
the
last
/
most
If 0, PROBE.
1 = Yes
5 = Selling household
recentprovider2 = NoInclude expenditure for Include expenditure for
Has this person
production in advancethatwastreatment/care in other treatment/care in otherbought medicine or
6 = Other sources
consulted
forcountries
countries
consulted with kru
IncludeInclude(specify)[NAME]'s
health?
khmer, a traditional
treatment/care treatment/carebirth attendant, or ain otherin othermonk
countries
countries
Enter CodeEnter Code(See below)(See below)
Write '0' if nothing
Write '0' if nothing
Enter the 3 withthe highest amounts
Enter number ofIf '2' >> Col (10)times sought health If don't know
If don't know
enter '98'
enter '98'
If '0' >> NEXTPERSON
No of Nights
RIELS
RIELS
(8)

(9a)

(9b)

(9c)

(9d)

(10)

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
Codes for col. 9a and 9b
Privatemedical sector:
Public sector:
08 = Private hospital
01 = National hospital (PP)09 = Private clinic
02 = Provincial hospital (RH)
10 = Private pharmacy
03 = District hospital (RH)
11 = Home/Office of trained health04 = Health centre
worker/nurse
05 = Health post
06 = Provincial rehabilitation centre (PRC) 12 = Visit of trained healthworker/nurseor Community based rehabilitation (CBR)
13 = Other private medical (Specify)
07 = Other publ

Not medical sector:
14 = Shop selling drugs/market
15 = Kru Khmer/ Magician
16 = Monk/religious leader
17 = Traditional birth attendant
18 = Other (Specify)
Overseas Medical Service:
19 = Overseas Medical Service

Manual Cambodia CSES 2012 Version 2.0

(11)

(12a)

(12b)

(12c)

213

14. DISABILITY

Respondent: Head of household or the spouse of the head of household

Please provide information on all members who usually reside in this household.
Does ..[NAME].. have any of thefollowing?

ID NUMBEREnter the 3 most important
01 = Difficulty seeing
02 = Difficulty hearing
03 = Difficulty speaking
04 = Difficulty moving
05 = Difficulties in feeling or sensing
06 = Psychological or behaviouraldifficulties
07 = Learning difficulties
08 = Fits
09 = Other (specify)
98 = Don´t know

Is the difficulty …

What was the cause?

1 = Mild
2 = Moderate
3 = Severe

01 = Mine/UXO
02 = Traffic Accident
03 = Work Accident
04 = Disease(s)05 = Congenital
06 = Fever
07 = Difficulty Delivery
08 = Chemical Accident
09 = Rape
10 = Violent Attack
11 = Domestic Violent
12 = Suicide AttemptEnter one code for each of the
difficulties reported in Col 2a-2cEnter '0' if none,(>> NEXT PERSON)

13 = Mental Trauma due to
war and other traumatic events
14 = War Injuries
15 = Malnutrition
16 = Burns
17 = Torture
18 = Old Age
19 = Other (specify)
98 = Don't know

Enter one code (the most important) for each of the
difficulties reported in Col 2a-2c

The 3 most important
(1)

(2a)

(2b)

(2c)

(3a)

(3b)

(3c)

(4a)

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

Manual Cambodia CSES 2012 Version 2.0

(4b)

(4c)

214

14. DISABILITY (CONTINUED)

Respondent: Head of household or the spouse of the head of household

Please provide information on all members who usually reside in this household.

ID NUMBER

Does the difficulty/difficulties prevent..[NAME].. from participation or accessto any of the following?

1 = Education (ask if aged 3 or over)2 = Housing
3 = Land ownership (ask if
aged over 18)
4 = Employment and income generation
5 = Health services
6 = Transport

Enter the three most important

Leave blank if "None"
(1)

(5a)

(5b)

(5c)

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

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15. CURRENT ECONOMIC ACTIVITY
Respondents: All household members aged 5 years and older
ACTIVITY STATUS DURING THE PAST 7 DAYS

Please provide information on all members aged 5 years and older who usually reside in this household. Try to interview the household members individually

ID NUMBERID
NUMBEROFRESPONDENT

(1)

(2)

Did ..[NAME].. do any work at all, even Although ..[NAME].. did What was ..[NAME].. 's main occupation/economic activity during the
not work even for one past 7 days?
one hour, during the past 7 days, i.e.
- worked or helped on a farm, grinding hour during the past 7
days, did ..[NAME]..
grain, making palm sugar, caring forhave a economic
animals, weaving etc.
activity from which- worked in a business or workplace(private or public sector, own account or he/she was temporarily
in business belonging to someone else absent? (e.g.: absent
due to holiday orin your household
illness)

Note: beggar and sex worker are occupations

1 = Yes (>> 5)

1 = Yes

2 = No2 = No (>>26)

(3)

(4)

Occupation description

NIS OCC:
CODE

(5a)

(5b)

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

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15. CURRENT ECONOMIC ACTIVITY (CONTINUED)
Respondents: All household members aged 5 years and older
ACTIVITY STATUS DURING THE PAST 7 DAYS (CONTINUED)
In what kind of industry/business (economic activity) did ..[NAME].. work in his/her main Under what type of employer did What was ..[NAME]..'s
occupation/activity (e.g. agriculture, manufacturing, construction, hotel/restaurant,..[NAME].. work in his/her main employment status intrade)?
occupation/economic activity?
his/her main
occupation/economic
activity?

ID NUMBER

1 = Government
2 = State owned enterprise
3 = Cambodian enterprise
4 = Foreign enterprise (private)
5 = Non profit institution
6 = Household sector
7 = Embassies, International
institutions and foreign aid anddevelopment agencies
8 = Other, specify …..

(1)

Industry description

NIS ISIC
CODE

(6a)

(6b)

(7)

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

Manual Cambodia CSES 2012 Version 2.0

1 = Employee
2 = Employer
3 = Own account worker
4 = Unpaid family worker(contributing family
worker)
5 = Other, specify….

(8)

217

15. CURRENT ECONOMIC ACTIVITY (CONTINUED)
Respondents: All household members aged 5 years and older
ACTIVITY STATUS DURING THE PAST 7 DAYS (CONTINUED)
How many days If Col 3 = 1 (Work If Col. 10b = 2
during the past 7
did ..[NAME]..
Is..[NAME]..`swork in his/her days) or Col 4 = 1
work
the past 7
main occupation/ (temporary absent)days
inthe maineconomic activity
occupation
Otherwise (>> during the past/economic
10b)month?
activityseasonal?
ID NUMBER

If Col. 3 = 1(Work during
the past 7
days)

If Col 3 = 1(Work during
the past 7days) orCol 4 = 1
(temporary
absent)if Col.8 = 3, 4 or 5
(employment status)

Besides ..[NAME]..'s main
occupation/economic
activity, how many
additional economic
Were the farm or fish products
activities
did he/she haveor other goods that (NAME)
duringthepast 7 days?
produced or helped produce inthe last seven days in themain occupation /economic
activity?

Does ..[NAME].. work Note:Seasonal
1= Only for own household use
the whole year in the is work done
2= Mainly for own household
only part of the Is..[NAME]..`smain
use but partly for saleoccupation/economic year but the main occupation/ 3= Mainly for sale, but partly
same job is economic activity
activity ?
for own household use
reoccurring done in a foreign
4= Only for saleEnter '0' if nocountry?
every year.

How many hours
did..[NAME]..workin his/her main
occupation/econ
omic activity
during thepast 7 days?

more
economic activities(>> 20)

1 = Yes (>>10d)2 = No

(1)

HOURS

DAYS

(9)

(10a)

(10b)

1 = Yes
2 = No

1 = Yes
2 = No

(10c)

(10d)

NO OF ECON.ACTIVITIES

(10e)

(11)

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
Note to column 10C, 17C and 33: Examples of Seasonal work (except farming)
Construction: Not being able to work with road construction during wet season.
Tourism: If no or less tourists arriving e.g. during wet season. Tourism in Cambodia is peaking during November to February. Fewer tourists during
wet season might affect the possibilities for tourism work.
Salt field worker: During wet season not possible to extract salt out of sea water. When not working no salary paid.
Teachers: When not schooling teachers having vacation. As they have salary during vacation this is not seasonal work.

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15. CURRENT ECONOMIC ACTIVITY (CONTINUED)
Respondents: All household members aged 5 years and older
ACTIVITY STATUS DURING THE PAST 7 DAYS (CONTINUED)
In what kind of industry/business (economic activity) did ..[NAME].. workin his/her secondary occupation/economic activity (e.g. agriculture,
manufacturing, construction, hotel/restaurant, trade)?

ID NUMBER

What was ..[NAME].. 's secondary occupation/economic activity during thepast 7 days?

Note: beggar and sex worker are occupations(1)

Occupation description

NIS OCC:
CODE

Industry description

NIS ISIC
CODE

(12a)

(12b)

(13a)

(13b)

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

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15. CURRENT ECONOMIC ACTIVITY (CONTINUED)
Respondents: All household members aged 5 years and older
ACTIVITY STATUS DURING THE PAST 7 DAYS (CONTINUED)ID NUMBER

Under what type of employer did..[NAME].. work in his/her secondary
occupation/economic activity?

(1)

What was ..[NAME].. 's
employment status in
his/her secondary
occupation/economic
activity?

1 = Government
2 = State owned enterprise
3 = Cambodian enterprise
4 = Foreign enterprise (private)
5 = Non profit institution
1 = Employee
6 = Household sector
7 = Embassies, International institutions 2 = Employer
3 = Own account worker
and foreign aid and development
4 = Unpaid family worker
agencies(contributing family
8 = Other, specify …..
worker)
5 = Other, specify….

(14)

(15)

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

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15. CURRENT ECONOMIC ACTIVITY (CONTINUED)
Respondents: All household members aged 5 years and older

ID NUMBER

ACTIVITY STATUS DURING THE PAST 7 DAYS (CONTINUED)
If Col. 11 = 1 ore How many
If Col. 17b = 2
If Col 11 more than 1 Is any of ..[NAME] ..`sDoes
If Col 15 = 3, 4 or 5
more
(3 or more jobs/
days did..[NAME] ..
work the past 7 days
Is..[NAME]..`s(2 or more
economic activities) in the other..[NAME]..
work the(employment status)
jobs/economic
If Col 11 = 1 (>> Col 19) occupation/economic
work inwhole year work the past 7
Were the farm or fishdays in theactivities )his/herin theactivities seasonal?
products or other goods
secondarysecondary secondaryIn
addition
to
the
hours
that (NAME) produced or
occupation/ occupation/e occupation/econ helped produce in the last worked during the past 7
omic activity
How many hours economic
conomic
days in main andNote: Seasonal isseven days in theseasonal?
did ..[NAME]..
activity
activity?
secondarywork done only partsecondary occupation
work in his/herduring theof the year but theoccupation/economic/economic activity …?
secondarypast month?
Note: Seasonal issame job isactivity how manyoccupation/
work done only
reoccurring every
additional hours did
economic activity
part of the year
year.
..[NAME].. work in the
1= only for own household use
but the same
during the past 7
1 = Yes economic activity 2= Mainly for own household use other jobs/activities duringdays?
the past 7 days?
is reoccurring(>>18a)but partly for saleevery year.
2 = Noown household use

Note: Do not count all
hours. Only count theadditional hours.

4= Only for sale

HOURS

(17d)

(18a)

3= Mainly for sale, but partly for

(1)

HOURS

DAYS

(16)

(17a)

1 = Yes
2 = No
(17b)

(17c)

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

Manual Cambodia CSES 2012 Version 2.0

1 = Yes
2 = No

(18b)

221

If Col 11 more than 1(3 or more jobs/
economic activities)
If Col 11 = 1 (>> Col 19)
In addition to the hours worked
during the past 7 days in main andsecondary occupation/economic
activity how many additional hours
did ..[NAME].. work in the otherjobs/activities during the past 7
days?
Note: Do not count all hours.
Only count the additional hours.

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15. CURRENT ECONOMIC ACTIVITY (CONTINUED)
Respondents: All household members aged 5 years and older
ACTIVITY STATUS DURING THE PAST 7 DAYS (CONTINUED)ID NUMBER

How many hours intotal did ..[NAME]..
work (main +secondary +additional
occupations/
economic activities)
during the past 7
days?

Ask only if Employee
If Col. 21 = 2
If Col 21 = 2Given the total number of If Col. 21 = 1(Code 1 in Col 8 - main
(more hours)
hours worked during the How many hours less How many hours
occupation/economic activity or past 7 days, would
If Col 21 = 1 (>> NEXTthen (hours) worked more then (hours)
Col 15 - secondary occupation) ..[NAME].. like to work
PERSON)
the past 7 days
worked the past 7days (stated in col 19)
less, more or unchanged (stated in col 19)
would .. [NAME] .. like would ..[NAME] .. like Was ..[NAME].. able tohours, given that theto work?
income would change in a to work?
(available to) work more
How much did ..[NAME].. earn in corresponding way?
hours (stated in Col 9 orsalary/wages during the last month19) during the past 7 days
from all economic activities?
or start working more
(In cash or in kind)
hours within 2 weeks
from now (the interview)?

Write "0" if nothing

(1)

HOURS

RIELS

(19)

(20)

01

1 = Less hours
2 = More hours
Note: Do not count all hours. Only count3 = Unchanged hours (>> the hours..[NAME]..want to reduce orNEXT PERSON)
increase ..[NAME]..'s work with.

(21)

HOURSMINUS

HOURSEXTRA

(22a)

(22b)

1 = Yes
2 = No(23)

Q15_C20

02
03
04
05
06
07
08
09
10
11
12
13
14
15
Note to column 23: The respondent has stated that he/she would like to work more than he/she does today. It is important to know whether the
respondent could start work within two weeks from now(only Yes or No).
This regardless if there are any jobs available, the respondents personal skills, sickness or else. In the following (column 24) the respondent is asked why
he/she doesn’t work more than now.
Examples, see next page

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15. CURRENT ECONOMIC ACTIVITY (CONTINUED)
Respondents: All household members aged 5 years and older
ACTIVITY STATUS DURING THE PAST 7 DAYS (CONTINUED)ID NUMBER

If Col 21 = 2 (morehours)

If Col 21 = 2 (more hours) and
If No work during In what ways did
Col 23 = 1 (available to work the past 7 days (Col ..[NAME]..try to find amore hours)
3 = 2 and Col 4 = 2) work?
If Col 23 = 2 (>> NEXT PERSON)
Why did.. [NAME].. work
If work (Col 3 = 1 orless hours the past 7 days
Col 4 = 1 (>> NEXT 1 = Applied tothan the hours he/she
PERSON)
advertisement
liked to work?
2 = Contacted (potential)
How many months has ..[NAME] ..
employers
been working less hours than
3 = Enquired with friends
he/she wanted (hours stated in Col Has ..[NAME].. been
relatives etc
1 = Temporary illness
19) and also been available to work actively seeking work
4 = Employment agency
2 = Not enough work
more hours?
during the past 4
5 = Tried to start own
available
weeks?
business but failed
3 = Other reasons
6 = Other (specify)
Number of months.
If less than 1 month put '0'
Leave it blank if don't know
months(24)(25)

1 = Yes
2 = NoWrite '0' ifnone

1 = Yes
2 = No (>> 31)

MONTHS(1)

Was ..[NAME]..
How many
available for work
hours does
during the past 7..[NAME]..
days or available to want to work
start working within 2 per week?
weeks from now(interview)?

Enter up to 3 codes
(26)

(27a)

(27b)

(27c)

HOURS
(28)

(29)

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
Employed: An employed person who has broken an arm is not able to work within 2 weeks from now. It should be equals to” No” in column 23 and ”Illness” incolumn 24.
An employed construction worker wanting to work more than today and can start working more already tomorrow but there are no employer offering work . Itshould be equals to” Yes” in column 23 and ”Not enough work available” in column 24.
Two more examples on next page

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15. CURRENT ECONOMIC ACTIVITY (CONTINUED)
Respondents: All household members aged 5 years and older
ACTIVITY STATUS DURING THE PAST 7 DAYS (CONTINUED)
How many months has..[NAME].. been out ofwork and actively been
looking for work?

If Col 26 = 2(Not actively seeking work)

How many months in total If Col 32 < 13 Months
has..[NAME].. been out of
Was the latest work
work?
..[NAME].. seasonal?

If Col 26 = 1 (>> NEXT PERSON)ID NUMBER

Why did [NAME] not actively seek work
during the past 4 weeks?

(1)

Leave it blank if don't
know months.

1 = Believes no work is available
2 = Awaiting result of application
3 = Waiting to start new job
4 = Permanent disabled
5 = Illness/disease/injured
6 = Too young, too old, retired
7 = Student
8 = Housekeeping, caring for children,
elderly or disabled
9 =Other reason, specify....

Note: Looking for andnot looking for work.
Number of months.
If less than 1 month
put '0'Note: Seasonal is work
done only part of theyear but the same
economic activity isreoccurring every year.

1 = Yes
2 = NoLeave it blank if don't
know months

MONTHS

If 6-8 >> NEXT PERSONMONTHS

(30)

(31)

(32)

(33)

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
Business: A woman wanting to work more in their own shop than today but have to take care of children. It should be equals to” No” in column 23 and ”Other
reasons” in column 2
Farmer: A farmer harvesting rice to times a year. When harvesting and planting the crops are completed he/she could start working with the neighbours cattle
within a week. It should be equals to” Yes” in column 23 and ”Not enough work available” in column 24 if not offered job by the neighbour.

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17.A. VICTIMIZATION

Respondent: Head of household, spouse of the head of household, or of another adult household member
Q1 Do you feel safe from crime and violence in this neighbourhood?

1 = Yes

2 = NoQ2 Has this household or any of its members been exposed to theft, burglary or robberyin the last 12 months, that is, since ..[MONTH].. last year?

1 = Yes

2 = NoQ3 Has anyone in the household had an accident that caused injury in the last 12 months?

1 = Yes

2 = NoNote: Robbery is the case when one or several offenders are using threat and/or violence when stealing something from you.

VICTIM OF VIOLENCEID NUMBER

Have you been
exposed to any act ofviolence that caused
injury in the last 12
months?

How often have you been
exposed in the last 12
months?

Note: The purpose of these questions is to gather information on victimizations and feelingsof safety in Cambodia. The results are very important when undertaking efforts to reduce
victimization and fear and to develop the criminal justice system in Cambodia. The
information is strictly confidential and data is only analysed in aggregated tables.

1 = Once
2 = Twice
3 = Three times
4 = 4-9 times
5 = 10 or moretimes

1 = Yes
2 = No(>> NEXTPERSON)(1)

Ask each household member individually, for children ask their parents

(2)

(3)

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

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17.B. VICTIMIZATION (CONTINUED)

Ask each household member individually, for children ask their parents

VICTIM OF VIOLENCE(1)EVENT NUMBERID NUMBER

For each person in the household that have been exposed to violence, please provide information from each event.
Write the ID Number in column 1.
Was the event reported Which authority did Did any
Was this act ofWas the injury How long did it take
To which kind of violence?
tosomeauthorities?
the
event
get
event
go
to
violence
committed
so serious that for the injury to
If more than three events, refer toreported to?
court
by some unknown or medical careheal?
the three most recent ones.
procedure? by someone known was needed?
01 = Push you, shake you, or throw
to you?
something at you.

(2)

02 = Twist your arm.
03 = Punch you with a fist or withsomething that could hurt you.
04 = Kick you or drag you.
05 = Try to strangle you or burn you.
06 = Attack you with a knife, gun orother type of weapon
07 = Rape, forced to have sexualintercourse when you did not want to
08 = Slap/Strike/Beat you with hand
09 = Slap/Strike/Beat you with object
10 = Rob you
11 = Other (specify(3)

1 = Yes
2 = No (>> 7)

1 = Yes
2 = No
1 = Unknown
person(s) -male
2 = Unknown
person(s) - female
3 = Known person(s) - male
4 = Known person(s) - female
5 = Other (specify)

1 = Village leader
2 = Police
3 = Other (specify)

(4)

(5)

01
02
03
01
02
03
01
02
03
01
02
03
01
02
03

Manual Cambodia CSES 2012 Version 2.0

(6)

(7)

1 = Yes
2 = No(8)

1 = Less than one
week
2 = 1- 2 weeks
3 = 3- 4 weeks
4 = One month or
more

(9)

229

Rules for Income Composition in STR 2014
When Diary at the beginning of the Variable name data is collected in Diary,
otherwise it is collected through Recall method.
The variables in this document are stored in Table IncomeHousehold in CSES2014STR database.
The 16 income types are stored in Table f_HHIncome in CSES2014STR database(see page 7 in this document)
Variable
SalarySQL-table
vPersonEcoCurrent

Rule
SalaryWages*12

Note
PersonQ15C20

SalaryvPersonEcoCurrent

SalaryWages *12
Sum HHID

Household
Q15C20

DiarySalaryCash

vDiaryIncome

DiarySalaryInKind

vDiaryIncome

CostCrop

vHHCostCultivationCrops
vHHLivestock1
vHHLivestock2

ValueRiel*12
If KindOfIncome = 1 and
TypeOfIncome = 1 or 0 (null)
ValueRiel*12
If KindOfIncome = 1 and
TypeOfIncome = 2,3
Total3_15

Bartered isincluded
here
Q05CC16

TotalPaidBought12Months +AmountInRiels

Q05E1C10
Q05E2C03(IncomeType 1)

CostLivestock

CostFishvHHFish-Cultivation1
vHHFish-Cultivation2

MonthlyRentPond*12 + AmountSpent

Q05F1C05
Q05F2C03

CostForestry

vHHForestry-Hunting2

ExpActivity12M

Q05G2C03

ReceiptCrop

vHHProductionCrops(ProducedOrHarvested –PostHarvestLoss) *SalesPriceCropsProduced

Q05BC06
Q05BC07
Q05BC09

ReceiptLivestock

vHHLivestock1

Q05E1C09
Q05E1C11-C15

ReceiptFish

vHHFish-Cultivation3

ValueSoldPast12Months +(ConsumedInHHPast12Months +UseForBarterGiftCharity +ValueLivestockProductsSold +ValueLivestockProductsConsumed +ValueLivestockUsedAsGifts)
AmountReceived

ReceiptForestry

vHHForestry-Hunting1

TotalAmountRiels

Q05G1C06

AgriIncome(IncomeType 2)

Q05F3C03(see below)(ReceiptCrop + ReceiptLivestock +ReceiptFish + ReceiptForestry) minus(CostCrop + CostLivestock + CostFish+ CostForestry + InterestPaidAgri)

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CostNonAgri

vHHNonAgri-culture2(Activity1 + Activity2 + Activity3 + Activity4 +Activity5 + Activity6) + InterestPaidNonAgri

Q05H2C03C08

ReceiptNonAgri

vHHNonAgri-culture3(Activity1 + Activity2 + Activity3 + Activity4 +Activity5 + Activity6)
If RevenueNumber is not 13(see below)
Q05H3C03C08
Q05H3C01
13 is
separate

NonAgriIncome(IncomeType 3)
IncomeOwnHouse

ReceiptNonAgri minus CostNonAgri

vHHConstructionvHHLiabilities

3% of
Q08_C05(HowMuchToBuyBuilding – (RemainingLoan/100+ Q06_C07
MonthlyRateInterest))
Q06_C08
If PrimaryPurposeBorrMoney = 7
Q06_C05

BankInterest

vHHIncomeOtherSource

AmountRielsTotal
If SourceNumber = 7

Q07_C05
Q07_C01

InterestOtherLoansvHHIncomeOtherSource

AmountRielsTotal
If SourceNumber = 9

Q07_C05
Q07_C01

Dividends

vHHIncomeOtherSource

AmountRielsTotal
If SourceNumber = 8

Q07_C05
Q07_C01

RentFromLand

vHHNonAgriculture3(Activity1 + Activity2 + Activity3 + Activity4 +Activity5 + Activity6)
If RevenueNumber = 13

Q05H3C03-C08(IncomeType 4)

Q05H3C01
GrossPropertyIncome
InterestPaid-AgrivHHLiabilities

BankInterest + InterestOtherLoans + Dividends+ RentFromLand
MonthlyRateInterest *RemainingLoan/(100+MonthlyRateInterest)
If PrimaryPurposeBorrMoney = 1

Q06_C08
Q06_C07
Q06_C08
Q06_C05

InterestPaidNonAgri

vHHLiabilities

MonthlyRateInterest *RemainingLoan/(100+MonthlyRateInterest)
If PrimaryPurposeBorrMoney = 2

Q06_C08
Q06_C07
Q06_C08
Q06_C05

InterestPaidOwnOccupied

vHHLiabilities

MonthlyRateInterest *RemainingLoan/(100+MonthlyRateInterest)
If PrimaryPurposeBorrMoney = 7

Q06_C08
Q06_C07
Q06_C08
Q06_C05

InterestPaidNet

vHHLiabilities

MonthlyRateInterest *RemainingLoan/(100+MonthlyRateInterest)
If PrimaryPurposeBorrMoney = 3-6
or 8-10

Q06_C08
Q06_C07
Q06_C08
Q06_C05

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231PropertyIncome

GrossPropertyIncome InterestPaidNet(IncomeType 5)
PrimaryIncome

vHHIncomeOtherSource

Salary + AgriIncome +NonAgriIncome +IncomeOwnHouse +PropertyIncome
WithinCambodia
If SourceNumber = 1

Q07_C03
Q07_C01vHHIncomeOtherSource

FromAbroad
If SourceNumber = 1

Q07_C04
Q07_C01vHHIncomeOtherSource

PensionDomestic + PensionAbroad
AmountRielsTotal
Q07_C05
If SourceNumber = 5
Q07_C01vHHIncomeOtherSource

WithinCambodia
If SourceNumber = 2

Q07_C03
Q07_C01vHHIncomeOtherSource

FromAbroad
If SourceNumber = 2

Q07_C04
Q07_C01

ScholarshipGovernment

vHHIncomeOtherSource

RemittanceDomestic +RemittanceAbroad
AmountRielsTotal
If SourceNumber = 3

Q07_C05
Q07_C01

ScholarshipNGO

vHHIncomeOtherSource

AmountRielsTotal
If SourceNumber = 4

Q07_C05
Q07_C01

PensionDomestic(IncomeType 6)
PensionAbroad(IncomeType 8)
PensionNGOtransfers(IncomeType 9)
RemittanceDomestic(IncomeType 10)
RemittanceAbroad(IncomeType 11)
TotalPrivateTransfers

TotalScholarship(IncomeType 7)
Gifts(IncomeType 12)
OtherTransfer(ncomeType 13)
TotalTransfers

ScholarshipGovernment +ScholarshipNGO
vHHIncomeOtherSource

AmountRielsTotal
If SourceNumber = 10, 11

Q07_C05
Q07_C01vHHIncomeOtherSource

AmountRielsTotal
If SourceNumber = 12, 13, 14, 15

Q07_C05
Q07_C01

TotalIncome

TotalPrivateTransfers +TotalScholarship + Gifts +OtherTransfer + NGOtransfers +PensionPrimaryIncome + TotalTransfers

WageRatio

Salary / TotalIncome

AgriRatio

AgriIncome / TotalIncome

OtherSelfEmpRatio
PropertyRatio(NonAgriIncome +IncomeOwnHouse) / TotalIncome
PropertyIncome / TotalIncome

TransfersRatio

TotalTransfers / TotalIncome

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232

DiaryTaxes

vDiary-Expenditure Value * 12
If Purpose = 9(IncomeType 14)

DiaryInterHHtransfers(IncomeType 15)

DiaryCashTransferChar(IncomeType 16)

vDiary-Expenditure Value * 12
If Purpose = 7 andAcquisition = 1,2

vDiary-Expenditure Value * 12
If Purpose = 8 andAcquisition = 1

DiaryExp_Q7,
DiaryExp_Q10
Is also calc.
from Recall
DiaryExp_Q7,
DiaryExp_Q10
Is also calc.
from Recall
DiaryExp_Q7,
DiaryExp_Q10
Is also calc.
from Recall

DiaryTotalNegativeTransfers

DiaryTaxes +DiaryInterHHtransfers +DiaryCashTransferChar
TotalIncome minus
DiaryTotalNegativeTransfers

DisposableIncome

DiaryCostAgri

vDiary-Expenditure (Value * 12 if Purpose = 2) + (Value *12 if
Item = 8117
and Purpose is not 2)

DiaryReceiptAgri

vDiaryIncome

Only used
when diarydata andrecall dataarecombined
DiaryExp_Q7,
DiaryExp_Q10,
DiaryExp_Q11

ValueRiel * 12
If ItemCode =201,202,203,204,205,206,207,
208,301,302,303,304
DiaryReceiptAgri minus
DiaryCostAgri

Diary
Inc_Q7,
Diary
Inc_Q10

DiaryCostNonAgri

vDiary-Expenditure (Value * 12 if Purpose = 3,4,5) +(Value * 12
if Item = 8212
and Purpose is not 3,4,5)

DiaryReceiptNonAgri

vDiaryIncome

DiaryExp_Q7,
DiaryExp_Q10,
DiaryExp_Q11
Diary
Inc_Q7,
Diary
Inc_Q10

DiaryAgriIncome

ValueRiel * 12
if ItemCode = 401,402,501-514,599

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DiaryNonAgriIncome

DiaryReceiptNonAgri minus
DiaryCostNonAgri

DiaryBankInterest

vDiaryIncome

ValueRiel * 12
If ItemCode = 1002

DiaryInterestOtherLoansvDiaryIncome

ValueRiel * 12
If ItemCode = 1006

DiaryDividends

vDiaryIncome

ValueRiel * 12
If ItemCode = 1001

DiaryOtherFinancialAccountvDiaryIncome

ValueRiel * 12
If ItemCode =1003,1004,1005,1007,1099

DiaryGrossPropertyIncome

DiaryBankInterest +DiaryInterestOtherLoans +DiaryDividends +DiaryOtherFinancialAccountDiaryGrossPropertyIncome

DiaryPropertyIncome

DiaryPrimaryIncome

DiaryPensionDomesticvDiaryIncome

DiaryPensionAbroad

vDiaryIncome

DiaryPension

DiarySalaryCash +DiarySalaryInKind +DiaryAgriIncome +DiaryNonAgriIncome +DiaryPropertyIncome
ValueRiel * 12
If ItemCode = 901

ValueRiel * 12
If ItemCode = 902

Diary
Inc_Q7,
Diary
Inc_Q10
Diary
Inc_Q7,
Diary
Inc_Q10
Diary
Inc_Q7,
Diary
Inc_Q10
Diary
Inc_Q7,
Diary
Inc_Q10

DiaryIPNet
does not
exist

Diary
Inc_Q7,
Diary
Inc_Q10
Diary
Inc_Q7,
Diary
Inc_Q10

DiaryPensionDomestic +DiaryPensionAbroad

DiaryInsuranceDomesticvDiaryIncome

ValueRiel * 12
If ItemCode = 903

DiaryInsuranceAbroad

vDiaryIncome

ValueRiel * 12
If ItemCode = 904

DiaryNGOTransfers

vDiaryIncome

ValueRiel * 12
If ItemCode = 905 and 999

Manual Cambodia CSES 2012 Version 2.0

Diary
Inc_Q7,
Diary
Inc_Q10
Diary
Inc_Q7,
Diary
Inc_Q10
Diary
Inc_Q7,
Diary
Inc_Q10

234

DiaryRemittanceDomesticvDiaryIncome

ValueRiel * 12
If ItemCode = 801

DiaryRemittanceAbroad

vDiaryIncome

ValueRiel * 12
If ItemCode = 802

DiaryTotalPrivateTransfers

DiaryRemittanceDomestic +DiaryRemittanceAbroad

DiaryScholarship

vDiaryIncome

ValueRiel * 12
If ItemCode = 1101,1102,1103,1199

DiaryGifts

vDiaryIncome

ValueRiel * 12
If TypeOfIncome = 2,3 and ItemCode= 701

DiaryOtherTransfers

vDiaryIncome

ValueRiel * 12
If ItemCode = 1299

DiaryTotalTransfers

DiaryDisposableIncome

DisposableIncome_Recall

Diary
Inc_Q7,
Diary
Inc_Q10
Diary
Inc_Q7,
Diary
Inc_Q10
Diary
Inc_Q7,
Diary
Inc_Q10

DiaryPension +DiaryInsuranceDomestic +DiaryInsuranceAbroad +DiaryNGOTransfers +DiaryTotalPrivateTransfers +DiaryScholarship + DiaryGifts +DiaryOtherTransfers
DiaryPrimaryIncome +DiaryTotalTransfers

DiaryTotalIncome

TotalNegativeTransfers

Diary
Inc_Q7,
Diary
Inc_Q10
Diary
Inc_Q7,
Diary
Inc_Q10

DiaryTotalIncome minus
DiaryTotalNegativeTransfers
vHHRecallNonFood
Taxes on income +Taxes on property +Interhousehold transfers +Transfers to charity
TotalIncome minus
TotalNegativeTransfers

Manual Cambodia CSES 2012 Version 2.0

Q01CC06
RowNo
22
23
21
20

235

Rules for Income Types
Variable in STR database
HHIncome(Only from recall)

Income Type 2

IncomeType 1

Variables in
IncomeHousehold
in STR

1 = 1-5

Primary Income
SalaryIncome fromagriculture
Income from nonagriculture
Income fromowner occupied
house
Property income
Governmental transfers

1
2

SalaryAgriIncome

3

NonAgriIncome

4

IncomeOwnHouse

Domestic pensions
Scholarships
Other received transfers

67

Pensions fromabroadNGO transfers
Domestic
Remittances
Remittances fromabroadGifts received
Other transfers
Negative transfers from recall

8

PensionAbroad

910

NGOtransfers
RemittanceDomestic

11

RemittanceAbroad

12
13

Gifts
OtherTransfer
TotalNegativeTransfers

5

PropertyIncome
2 = 6-7
PensionDomestic
TotalScholarship
3 = 8-13

4 = 14-16

Taxes

14

Interhousehold
cash transfers

15

Cash transfers tocharities

16

Manual Cambodia CSES 2012 Version 2.0

Q01CC05
RowNo 22 , 23
Q01CC05
RowNo 21
Q01CC05
RowNo 20