Identification
Survey ID Number
KHM_2009_CSES_v01_M
Title
Socio-Economic Survey 2009
Subtitle
Household Survey 2009
Country
| Name | Country code |
|---|---|
| Cambodia | KHM |
Study type
Socio-Economic/Monitoring Survey [hh/sems]
Series Information
The Cambodia Socio-Economic Survey (CSES) 2009 is the eighth Cambodia Socio Economic Survey conducted by National Institute of Statistics. The Socio Economic Surveys were conducted in the years 1993/94, 1996, 1997 and 1999. 2004, and then conducted annually from 2007 to 2009.
Abstract
The CSES is a household survey with questions to households and the household members. In the household questionnaire there are a number of modules with questions relating to the living conditions, e.g. housing conditions, education, health, expenditure/income and labour force. It is designed to provide information on social and economic conditions of households for policy studies on poverty, household production and final consumption for the National Accounts and weights for the CPI.
The main objective of the survey is to collect statistical information about living standards of the population and the extent of poverty. Essential areas as household production and cash income, household level and structure of consumption including poverty and nutrition, education and access to schooling, health and access to medical care, transport and communication, housing and amenities and family and social relations. For recording expenditure, consumption and income the Diary Method was applied for the first time. The survey also included a Time Use Form detailing activities of household members during a 24-hour period.
Another main objective of the survey is also to collect accurate statistical information about living standards of the population and the extent of poverty as an essential instrument to assist the government in diagnosing the problems and designing effective policies for reducing poverty, and in evaluating the progress of poverty reduction which are the main priorities in the "Rectangular Strategy" of the Royal Government of Cambodia.
The main objective of the survey is to collect statistical information about living standards of the population and the extent of poverty. Essential areas as household production and cash income, household level and structure of consumption including poverty and nutrition, education and access to schooling, health and access to medical care, transport and communication, housing and amenities and family and social relations. For recording expenditure, consumption and income the Diary Method was applied for the first time. The survey also included a Time Use Form detailing activities of household members during a 24-hour period.
Another main objective of the survey is also to collect accurate statistical information about living standards of the population and the extent of poverty as an essential instrument to assist the government in diagnosing the problems and designing effective policies for reducing poverty, and in evaluating the progress of poverty reduction which are the main priorities in the "Rectangular Strategy" of the Royal Government of Cambodia.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Household
Individual
Village/ Community
Individual
Village/ Community
Version
Version Date
2010
Scope
Notes
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 are also incorporated into the “Rectangular Strategy of Cambodia”.
Cambodia is still a predominantly rural and agricultural society. The vast majority of the population gets their subsistence in households as self-employed in agriculture. The level of living is determined by the household's command over labour and resources for own-production in terms of land and livestock for agricultural activities, equipment and tools for fishing, forestry and construction activities and income-earning activities in the informal and formal sector. Data to calculate household production were obtained from the household questionnaire and the diaries as well as data from the labour force module.
Briefly the four earlier CSES rounds have all made it possible to report sets of indicators on 8 main areas of social concern:
1. Demographic characteristics
2. Housing
3. Agriculture
4. Education
5. Labour Force
6. Health and Nutrition
7. Victimization
8. Household Income and Consumption
These 8 areas were also covered by corresponding modules in the CSES 2009, together with a diary method as well as a recall method, the other following the module design and variable content of previous rounds of the CSES with needed modifications and complements.
Cambodia is still a predominantly rural and agricultural society. The vast majority of the population gets their subsistence in households as self-employed in agriculture. The level of living is determined by the household's command over labour and resources for own-production in terms of land and livestock for agricultural activities, equipment and tools for fishing, forestry and construction activities and income-earning activities in the informal and formal sector. Data to calculate household production were obtained from the household questionnaire and the diaries as well as data from the labour force module.
Briefly the four earlier CSES rounds have all made it possible to report sets of indicators on 8 main areas of social concern:
1. Demographic characteristics
2. Housing
3. Agriculture
4. Education
5. Labour Force
6. Health and Nutrition
7. Victimization
8. Household Income and Consumption
These 8 areas were also covered by corresponding modules in the CSES 2009, together with a diary method as well as a recall method, the other following the module design and variable content of previous rounds of the CSES with needed modifications and complements.
Topics
| Topic | Vocabulary | URI |
|---|---|---|
| Demographic characteristics | CESSDA | http://www.nesstar.org/rdf/common |
| Housing [10.1] | CESSDA | http://www.nesstar.org/rdf/common |
| Agriculture | CESSDA | http://www.nesstar.org/rdf/common |
| Education [6] | CESSDA | http://www.nesstar.org/rdf/common |
| Labour Force | CESSDA | http://www.nesstar.org/rdf/common |
| Health and Nutrition [8] | CESSDA | http://www.nesstar.org/rdf/common |
| Victimization [8] | CESSDA | http://www.nesstar.org/rdf/common |
| Household Income and Consumption [1.1] | CESSDA | http://www.nesstar.org/rdf/common |
Keywords
| Keyword |
|---|
| Household |
Coverage
Geographic Coverage
National
Geographic Unit
14 Domains:
11 individual provinces:
Bantey Meanchy
Battambang
Kampong Cham
Kampong Speu
Kampong Thom
Kanda
Phnom Penh
Prey Veng
Siem Reap
Svay Rieng
Takeo
3 groups of provinces:
Group 1: Kampong Chhnang, and Pursat; Tonle Sap provinces
Group 2: Kampot, Sihanouk Ville, Kaoh Kong, and Krong Keb; Coastal provinces
Group 3: Kratie, Steung Treng, Rattanakiri, Mondol Kiri, Preah Vihear, Oddor Meanchey, and Krong Pailin; Mountain provinces
11 individual provinces:
Bantey Meanchy
Battambang
Kampong Cham
Kampong Speu
Kampong Thom
Kanda
Phnom Penh
Prey Veng
Siem Reap
Svay Rieng
Takeo
3 groups of provinces:
Group 1: Kampong Chhnang, and Pursat; Tonle Sap provinces
Group 2: Kampot, Sihanouk Ville, Kaoh Kong, and Krong Keb; Coastal provinces
Group 3: Kratie, Steung Treng, Rattanakiri, Mondol Kiri, Preah Vihear, Oddor Meanchey, and Krong Pailin; Mountain provinces
Universe
All resident households in Cambodia
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Institute of Statistics | Ministry of Planning |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Swedish International Development Cooperation Agency | SIDA | Funding |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Statistics Sweden | SCB | Technical Assistance |
Sampling
Sampling Procedure
The sampling design for the 2009 survey is the same as that used for the CSES 2004
Sampling Design
The sampling design in the CSES 2009 survey is a three-stage design. In stage one a sample of villages is selected, in stage two an Enumeration Area (EA) is selected from each village selected in stage one, and in stage three a sample of households is selected from each EA selected in stage two. The sampling designs used in the three stages were:
Stage 1. A systematic pps sample of villages, Primary Sampling Units (PSUs) was selected from each stratum,
i.e. without replacement systematic sampling with probabilities proportional to size. The size measure used was the number of households in the village according to the sampling frame.
Stage 2. One EA was selected by Simple Random Sampling (SRS), in each village selected in stage 1.
As mentioned above, in a few large villages more than one EA was selected.
Stage 3. In each selected EA a sample of households was selected by systematic sampling.
The selection of villages and EAs were done at NIS while the selection of households in stage three was done in field. As mentioned in section 1.1 all households in selected EAs were listed by the enumerator. The sample of households was then selected from the list.
Sampling Frame
Preliminary data from the General Population Census 2008 was used to construct the sampling frame for the first stage sampling, i.e. sampling of villages. All villages except 'special settlements' were included in the frame. In all, the first stage sampling frame of villages consisted of 14,073 villages, see Appendix 1. Compared to previous years the frame used for the 2009 survey based on the census 2008 was more up to date than in previous surveys which were based on the population census 1998.
The following variables were used from the census: Province code, province name, district code, district name, commune code, commune name, village code, village name, urban-rural classification of villages, the number of households per village and, the number of enumeration areas in the village.
Sample sizes and allocation
The sample size of PSUs, were, as in the 2004 survey, 720 villages (or EAs). In urban villages 10 households were selected and in rural 20 households. In all 12,000 households were selected.
Urban and rural villages were treated separately in the allocation. The allocation was done in two steps. First the sample sizes for urban and rural villages in the frame were determined and then sample sizes for the provinces within urban and rural areas were determined, i.e. the strata sample sizes.
The total sample size was divided into two, one sample size for urban villages and the other for rural villages. The calculation of the sample sizes for urban and rural areas were done using the proportion of consumption in the two parts of the population. Data on consumption from the CSES 2007 survey was used. The resulting sample sizes for urban villages was 240 and for rural 480. (Some adjustments of the calculated sample sizes were done, resulting in the numbers 240 and 480).
Monthly samples
The annual sample was divided into 12 monthly samples of equal sizes. The monthly samples consisted of 20 urban and 40 rural villages. The division of the annual sample into monthly samples was done so that as far as possible each province would be represented in each monthly sample. Since the sample size of villages in some provinces is smaller than 12, all provinces were not included in all monthly samples. Also, the outline of the fieldwork with teams of 4 enumerators and one supervisor puts constraints on how to divide the annual sample into monthly samples. The supervisors must travel between the villages in a team and therefore the geographical distance between the villages surveyed by a team cannot be too large.
Further details on the sampling design of the survey are provided in Section 11 of the CSES 2009 report.
Sampling Design
The sampling design in the CSES 2009 survey is a three-stage design. In stage one a sample of villages is selected, in stage two an Enumeration Area (EA) is selected from each village selected in stage one, and in stage three a sample of households is selected from each EA selected in stage two. The sampling designs used in the three stages were:
Stage 1. A systematic pps sample of villages, Primary Sampling Units (PSUs) was selected from each stratum,
i.e. without replacement systematic sampling with probabilities proportional to size. The size measure used was the number of households in the village according to the sampling frame.
Stage 2. One EA was selected by Simple Random Sampling (SRS), in each village selected in stage 1.
As mentioned above, in a few large villages more than one EA was selected.
Stage 3. In each selected EA a sample of households was selected by systematic sampling.
The selection of villages and EAs were done at NIS while the selection of households in stage three was done in field. As mentioned in section 1.1 all households in selected EAs were listed by the enumerator. The sample of households was then selected from the list.
Sampling Frame
Preliminary data from the General Population Census 2008 was used to construct the sampling frame for the first stage sampling, i.e. sampling of villages. All villages except 'special settlements' were included in the frame. In all, the first stage sampling frame of villages consisted of 14,073 villages, see Appendix 1. Compared to previous years the frame used for the 2009 survey based on the census 2008 was more up to date than in previous surveys which were based on the population census 1998.
The following variables were used from the census: Province code, province name, district code, district name, commune code, commune name, village code, village name, urban-rural classification of villages, the number of households per village and, the number of enumeration areas in the village.
Sample sizes and allocation
The sample size of PSUs, were, as in the 2004 survey, 720 villages (or EAs). In urban villages 10 households were selected and in rural 20 households. In all 12,000 households were selected.
Urban and rural villages were treated separately in the allocation. The allocation was done in two steps. First the sample sizes for urban and rural villages in the frame were determined and then sample sizes for the provinces within urban and rural areas were determined, i.e. the strata sample sizes.
The total sample size was divided into two, one sample size for urban villages and the other for rural villages. The calculation of the sample sizes for urban and rural areas were done using the proportion of consumption in the two parts of the population. Data on consumption from the CSES 2007 survey was used. The resulting sample sizes for urban villages was 240 and for rural 480. (Some adjustments of the calculated sample sizes were done, resulting in the numbers 240 and 480).
Monthly samples
The annual sample was divided into 12 monthly samples of equal sizes. The monthly samples consisted of 20 urban and 40 rural villages. The division of the annual sample into monthly samples was done so that as far as possible each province would be represented in each monthly sample. Since the sample size of villages in some provinces is smaller than 12, all provinces were not included in all monthly samples. Also, the outline of the fieldwork with teams of 4 enumerators and one supervisor puts constraints on how to divide the annual sample into monthly samples. The supervisors must travel between the villages in a team and therefore the geographical distance between the villages surveyed by a team cannot be too large.
Further details on the sampling design of the survey are provided in Section 11 of the CSES 2009 report.
Response Rate
The CSES 2009 enjoyed almost a 100 percent response rate. The high response rate together with close and systematic fieldwork supervision by the core group members were a major contribution for achieving high quality survey results.
Weighting
The weights are determined by the sampling design, design weights, and adjusted for nonresponse and other deficiencies such as under coverage and, to improve the precision of the estimates. The formula used to derive the household weights as well further discussion on the weights of the survey is provided in Section 11 of the CSES 2009 report.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2009-01-01 | 2009-12-01 |
Data Collection Mode
Face-to-face [f2f]
Supervision
Monitoring
Any survey of the CSES dimensions needs a comprehensive system for quality management and monitoring. Only then errors can be found in time to avoid quality problems later in the data process.
The CSES management group within NIS therefore set up a monitoring scheme to be implemented from the very beginning. The monitoring team included five NIS staff. The DG of NIS has spent 2-3 days monthly while other members of NIS core group (3-4 staff) were in the field for two weeks on the average. At times other officials from NIS or the Ministry participated.
Inspections entailed both announced and unannounced visits. Every team was visited at least once during their fieldwork period. There were numerous purposes of these visits. One important intention was to get a disciplinary effect on supervisors and enumerators from their knowledge inspections must be expected throughout the fieldwork, including also the very end of the diary month. Important was also to give feedback and encouragement to fieldworkers as well to complement training by advice and suggestions as to sort out any problem that might occurred in the course of fieldwork. Anotherarea of concern was to ensure that the household listing and sampling was done in accordance with the procedures that were prescribed.
In appendix 6 of the CSES 2009 report, an example of the Field Supervision Plans is included (for January 2009). Field Supervision Plans for other months look very much the same.
Any survey of the CSES dimensions needs a comprehensive system for quality management and monitoring. Only then errors can be found in time to avoid quality problems later in the data process.
The CSES management group within NIS therefore set up a monitoring scheme to be implemented from the very beginning. The monitoring team included five NIS staff. The DG of NIS has spent 2-3 days monthly while other members of NIS core group (3-4 staff) were in the field for two weeks on the average. At times other officials from NIS or the Ministry participated.
Inspections entailed both announced and unannounced visits. Every team was visited at least once during their fieldwork period. There were numerous purposes of these visits. One important intention was to get a disciplinary effect on supervisors and enumerators from their knowledge inspections must be expected throughout the fieldwork, including also the very end of the diary month. Important was also to give feedback and encouragement to fieldworkers as well to complement training by advice and suggestions as to sort out any problem that might occurred in the course of fieldwork. Anotherarea of concern was to ensure that the household listing and sampling was done in accordance with the procedures that were prescribed.
In appendix 6 of the CSES 2009 report, an example of the Field Supervision Plans is included (for January 2009). Field Supervision Plans for other months look very much the same.
Data Collection Notes
Enumerator and supervisor training
Prior to the start of the fieldwork intensive interviewer and supervisor training were carried out.
The 200 interviewers and 50 supervisors recruited were split into two groups, each group consisting of 100 interviewers and 25 supervisors. The two groups alternated so that the first group did their fieldwork during odd survey months (i.e. January, March, May, July, September, and November 2009) while the second group covered the even survey months (i.e. February, April, June, August, October, and December 2009).
The training was designed with this in mind. The first group was trained in December 2008 while the second group was trained in January 2009 using premises at the NIS head office. Training of the first and second group was provided in Khmer by the appointed NIS core group and was assisted by Sida consultants. The supervisors and interviewers were jointly trained for two weeks over the 4 forms of questionnaires.
During the training a special session on Gender issues relating to data collection was provided by Ministry of Women's Affair (supported by UNDP). Yet another session was held by the Cambodian Disabled People's Organization to get the enumerators better understanding the concept and definitions of disability. The Working Group on Water and Sanitation provided useful training material on the definition on improved water sources and sanitation.
Field Operations
Interviewers and supervisors were initially divided into teams consisting of five persons (one supervisor and four interviewers), making in total 50 teams for the fieldwork. Each month 25 teams were working in the field with a workload of 10 households per interviewer. In urban areas four PSU's (“villages”) were allocated to one team while in rural areas two PSU's were allocated. The fieldwork plan was designed in order to gather information from about 40 households monthly per team.
For a given month the team arrived in the village three days before the first day of the interview month to tend to preparatory tasks like discussing with village authorities, filling in the Household Listing Form and thereafter sample those households to be interviewed.
The Village Form was filled in by the supervisor.
The Household Questionnaire had 17 sections that were filled in by the interviewer during the first visit to the household, and in the following four weeks according to the following scheme:
During a survey month different questions were asked in different weeks according to the following:
· Week 1. Questions about education, migration, and housing
· Week 2. Questions about economic activity, agricultural and non-agricultural business, household liabilities and other household incomes.
· Week 3. Questions about construction, durable goods, health (maternal, child, general and disability)
· Week 4. Questions about current economic activities, usual economic activities and Victimization
When the month ended, the team went back to the NIS headquarter in Phnom Penh.
Questionnaires from the same PSU were delivered to the NIS team for editing and coding by the supervisor in a packet including all the documents used and produced in the fieldwork, such as maps, enumeration lists and questionnaires. Appendix 6 of the CSES 2009 report contains an example (the first survey month) from the allocation of teams to PSU's.
Before going to the villages the teams were briefed and introduced to minor adjustments of the interviewing procedure that were made as a result of monitoring activities and feed-back from the data processing.
Prior to the start of the fieldwork intensive interviewer and supervisor training were carried out.
The 200 interviewers and 50 supervisors recruited were split into two groups, each group consisting of 100 interviewers and 25 supervisors. The two groups alternated so that the first group did their fieldwork during odd survey months (i.e. January, March, May, July, September, and November 2009) while the second group covered the even survey months (i.e. February, April, June, August, October, and December 2009).
The training was designed with this in mind. The first group was trained in December 2008 while the second group was trained in January 2009 using premises at the NIS head office. Training of the first and second group was provided in Khmer by the appointed NIS core group and was assisted by Sida consultants. The supervisors and interviewers were jointly trained for two weeks over the 4 forms of questionnaires.
During the training a special session on Gender issues relating to data collection was provided by Ministry of Women's Affair (supported by UNDP). Yet another session was held by the Cambodian Disabled People's Organization to get the enumerators better understanding the concept and definitions of disability. The Working Group on Water and Sanitation provided useful training material on the definition on improved water sources and sanitation.
Field Operations
Interviewers and supervisors were initially divided into teams consisting of five persons (one supervisor and four interviewers), making in total 50 teams for the fieldwork. Each month 25 teams were working in the field with a workload of 10 households per interviewer. In urban areas four PSU's (“villages”) were allocated to one team while in rural areas two PSU's were allocated. The fieldwork plan was designed in order to gather information from about 40 households monthly per team.
For a given month the team arrived in the village three days before the first day of the interview month to tend to preparatory tasks like discussing with village authorities, filling in the Household Listing Form and thereafter sample those households to be interviewed.
The Village Form was filled in by the supervisor.
The Household Questionnaire had 17 sections that were filled in by the interviewer during the first visit to the household, and in the following four weeks according to the following scheme:
During a survey month different questions were asked in different weeks according to the following:
· Week 1. Questions about education, migration, and housing
· Week 2. Questions about economic activity, agricultural and non-agricultural business, household liabilities and other household incomes.
· Week 3. Questions about construction, durable goods, health (maternal, child, general and disability)
· Week 4. Questions about current economic activities, usual economic activities and Victimization
When the month ended, the team went back to the NIS headquarter in Phnom Penh.
Questionnaires from the same PSU were delivered to the NIS team for editing and coding by the supervisor in a packet including all the documents used and produced in the fieldwork, such as maps, enumeration lists and questionnaires. Appendix 6 of the CSES 2009 report contains an example (the first survey month) from the allocation of teams to PSU's.
Before going to the villages the teams were briefed and introduced to minor adjustments of the interviewing procedure that were made as a result of monitoring activities and feed-back from the data processing.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| National Institute of Statistics | NIS | Ministry of Planning |
Questionnaires
Questionnaires
Four different questionnaires or forms were used in the survey:
1. Household listing form
The Household listing and mapping were done prior to the sampling. During the household listing the enumerator recorded household information on e.g. location, number of members and principal economic activity.
2. Village questionnaire
The Village questionnaire was used to gather basic common information on:
1. Demographic information
2. Economy & Infrastructure
3. Rainfall & Natural disasters
4. Education
5. Health
6. Retail prices (food and non-food items)
7. Employment & Wages
8. Access to common property resources during the last 5 years
9. Sale prices of agricultural land in the village
10. Recruitment of children for work outside the village
3. Household questionnaire
The following modules were included in the Household questionnaire:
01. Initial visit
01A. List of household member
01B. Food, beverages and tobacco consumption during the last 7 days
01C. Recall non-food expenditures
01D. Vulnerability
02. Education & Literacy
03. Information on migration (includes past and current migration)
04. Housing
05. Household economic activities
05A. Land ownership
05B. Production of crops
05C. Cost of cultivation of crops
05D .Inventory of crops (crop storage)
05E. Inputs and outputs of livestock and poultry raising activities
05F. Inputs and outputs from fish cultivation and fishing/trapping of aquatic products
05G. Inputs and outputs from forestry and hunting
05H. List of household non-agricultural economic activities
06. Household liabilities
07. Household income from other sources
08. Construction activities
09. Durable goods
10. Maternal health (Last pregnancy and delivery)
11. Child health (youngest child and all children under 2)
12. Health check of children under 5
13. Health care seeking and expenditure
13A. Subsidised household healthcare
13B. Illness and health care expenditure
14. Disability
15. Current economic activities (activity status during the past seven days)
16. Usual economic activity (activity in the past 12 months)
17. Victimization
17A. Household security
17B. Victim of theft
17C. Victim of accidents
17D. Victim of violence
18. Summary of presence in the household
4. The Diary sheet (diary method)
a. Diary for expenditure & consumption of own-production
b. Diary for household income & receipts
Minor changes were done in “kind of income” and “purpose of expenditure”.
The CSES 2009 questionnaires are based on the questionnaires in CSES 2004-2008 with the intention to as far as possible keep the cmparability between surveys. The questionnaires were updated and some questions of each module were also changed based on the experience and evaluation of the questionnaires of CSES 2004, 2007 and 2008.
1. Household listing form
The Household listing and mapping were done prior to the sampling. During the household listing the enumerator recorded household information on e.g. location, number of members and principal economic activity.
2. Village questionnaire
The Village questionnaire was used to gather basic common information on:
1. Demographic information
2. Economy & Infrastructure
3. Rainfall & Natural disasters
4. Education
5. Health
6. Retail prices (food and non-food items)
7. Employment & Wages
8. Access to common property resources during the last 5 years
9. Sale prices of agricultural land in the village
10. Recruitment of children for work outside the village
3. Household questionnaire
The following modules were included in the Household questionnaire:
01. Initial visit
01A. List of household member
01B. Food, beverages and tobacco consumption during the last 7 days
01C. Recall non-food expenditures
01D. Vulnerability
02. Education & Literacy
03. Information on migration (includes past and current migration)
04. Housing
05. Household economic activities
05A. Land ownership
05B. Production of crops
05C. Cost of cultivation of crops
05D .Inventory of crops (crop storage)
05E. Inputs and outputs of livestock and poultry raising activities
05F. Inputs and outputs from fish cultivation and fishing/trapping of aquatic products
05G. Inputs and outputs from forestry and hunting
05H. List of household non-agricultural economic activities
06. Household liabilities
07. Household income from other sources
08. Construction activities
09. Durable goods
10. Maternal health (Last pregnancy and delivery)
11. Child health (youngest child and all children under 2)
12. Health check of children under 5
13. Health care seeking and expenditure
13A. Subsidised household healthcare
13B. Illness and health care expenditure
14. Disability
15. Current economic activities (activity status during the past seven days)
16. Usual economic activity (activity in the past 12 months)
17. Victimization
17A. Household security
17B. Victim of theft
17C. Victim of accidents
17D. Victim of violence
18. Summary of presence in the household
4. The Diary sheet (diary method)
a. Diary for expenditure & consumption of own-production
b. Diary for household income & receipts
Minor changes were done in “kind of income” and “purpose of expenditure”.
The CSES 2009 questionnaires are based on the questionnaires in CSES 2004-2008 with the intention to as far as possible keep the cmparability between surveys. The questionnaires were updated and some questions of each module were also changed based on the experience and evaluation of the questionnaires of CSES 2004, 2007 and 2008.
Data Processing
Data Editing
Data editing and coding
The NIS team commenced their work of checking and coding in beginning of February after the first month of fieldwork was completed. Supervisors from the field delivered questionnaires to NIS. SIDA project experts and NIS Survey Manager helped solving relevant matters that became apparent when reviewing questionnaires on delivery.
All questionnaires from each PSU were delivered to editors and coders by supervisor. The editors and coders were responsible for handling the questionnaires from the brought from the field supervisor's until finishing the process of checking and coding. When checking and coding a red pen was used in the questionnaire.
How the workflow is organised at the office
Data editing and coding is an important part of the overall data processing for CSES. In brief, the implementation of data editing and coding comprise the following functions:
· When a field supervisor delivered questionnaires from a PSU the delivery contained a set of mappings, listings, village questionnaires, household questionnaires and diary forms. Editors and coders started checking each PSU including mapping information and all other forms. Field supervisor had to wait for editor and coder's checking. If any problem occurred, editor had to immediately ask field supervisor to correct the error.
· After corrections were completed, editor started the coding process. The code to be used included e.g. crop-code, occupation, industry code, income and expenditure code, and unit code. When editor encountered a mistake which could not be corrected directly by editor it had to be discussed with the supervisor or called back to enumerator.
· After checking and coding was finished, the data editor staff put all documents from the PSU into a designated box labeled with the PSU number and sent it to the data-entry operator.
· In case the data-entry operator encountered any mistakes caused by checking and coding, the operator sent the questionnaire back for re-edit and checking.
· Editing and coding proceeds every month and is done one week before data entry starts.
The NIS team commenced their work of checking and coding in beginning of February after the first month of fieldwork was completed. Supervisors from the field delivered questionnaires to NIS. SIDA project experts and NIS Survey Manager helped solving relevant matters that became apparent when reviewing questionnaires on delivery.
All questionnaires from each PSU were delivered to editors and coders by supervisor. The editors and coders were responsible for handling the questionnaires from the brought from the field supervisor's until finishing the process of checking and coding. When checking and coding a red pen was used in the questionnaire.
How the workflow is organised at the office
Data editing and coding is an important part of the overall data processing for CSES. In brief, the implementation of data editing and coding comprise the following functions:
· When a field supervisor delivered questionnaires from a PSU the delivery contained a set of mappings, listings, village questionnaires, household questionnaires and diary forms. Editors and coders started checking each PSU including mapping information and all other forms. Field supervisor had to wait for editor and coder's checking. If any problem occurred, editor had to immediately ask field supervisor to correct the error.
· After corrections were completed, editor started the coding process. The code to be used included e.g. crop-code, occupation, industry code, income and expenditure code, and unit code. When editor encountered a mistake which could not be corrected directly by editor it had to be discussed with the supervisor or called back to enumerator.
· After checking and coding was finished, the data editor staff put all documents from the PSU into a designated box labeled with the PSU number and sent it to the data-entry operator.
· In case the data-entry operator encountered any mistakes caused by checking and coding, the operator sent the questionnaire back for re-edit and checking.
· Editing and coding proceeds every month and is done one week before data entry starts.
Other Processing
Training
In December 2008, the data processing team participated in a training course for enumerators and supervisors. The main objective of the training was to identify anomalies in the questionnaire and also discuss certain ideas raised during training sessions to avoid and reduce future mistakes. From January 2009 and onwards, the supervisor for data editing and coding took part in reviewing problems raised by instructors and enumerators encountered during fieldwork interviews.
In late 2006 and beginning of 2007 a new system for data processing and storage were introduced for the Cambodia Socio Economic Survey (CSES). It includes a relational database system for storing CSES data in SQL format and an application framework developed in-house for data-entry. Since NIS staff already was familiar with Visual Basic and Microsoft SQL Server database software the transition from previous data processing system was feasible. A modern network infrastructure within the NIS was also implemented to host the new CSES system and facilitate for concurrent data-entry.
The application and storage platform developed in 2006 and supervised by Statistics Sweden consultancy has since been used consecutively for all CSES data processing from 2007 and onwards.
The database contains data tables for all modules comprising the CSES household, village and diary questionnaires. There are also code-tables used for data integrity controls during data-entry and tables for data management including error lists. In all the database counts a total of 185 tables divided by:
Data tables: 39
Code tables: 129
Management tables: 17
To facilitate for easier data retrieval there are also a set of views or virtual tables available in the database.
Data in the system is for the most part processed by three distinct application components all developed in Microsoft Visual Basic 6.0:
· The CSES editing component: is used for entering household information from cover page of questionnaire such as; PSU number, household number and number of members in household.
· The CSES entry component: is used for entering data from each CSES module. This is the main component for data processing.
· The CSES management component: is used to correct errors and view information about operator statistics.
All database modules as well as application components have since 2008 been maintained and improved by staff from the NIS ICT department.
Work flow of CSES data processing system
Step 1. Questionnaires sent from field operators arrives monthly at NIS and is taken care of by data processing staff
Step 2. Questionnaires are updated with appropriate codes for household identification. They are checked and edited for any apparent errors or misunderstandings from the field operator. All changes are written to the questionnaire.
Step 3. Data about number of rows for each module are entered into the management module as well as number of households per PSU. These practices are to ensure that all data rows are entered.
Step 4. Data-entry of all modules including Household, Diary and Village.
Step 5. After finished data entry an iterative error correction phase is started and run from the database server. Any errors from data controls are visible in the management module.
In December 2008, the data processing team participated in a training course for enumerators and supervisors. The main objective of the training was to identify anomalies in the questionnaire and also discuss certain ideas raised during training sessions to avoid and reduce future mistakes. From January 2009 and onwards, the supervisor for data editing and coding took part in reviewing problems raised by instructors and enumerators encountered during fieldwork interviews.
In late 2006 and beginning of 2007 a new system for data processing and storage were introduced for the Cambodia Socio Economic Survey (CSES). It includes a relational database system for storing CSES data in SQL format and an application framework developed in-house for data-entry. Since NIS staff already was familiar with Visual Basic and Microsoft SQL Server database software the transition from previous data processing system was feasible. A modern network infrastructure within the NIS was also implemented to host the new CSES system and facilitate for concurrent data-entry.
The application and storage platform developed in 2006 and supervised by Statistics Sweden consultancy has since been used consecutively for all CSES data processing from 2007 and onwards.
The database contains data tables for all modules comprising the CSES household, village and diary questionnaires. There are also code-tables used for data integrity controls during data-entry and tables for data management including error lists. In all the database counts a total of 185 tables divided by:
Data tables: 39
Code tables: 129
Management tables: 17
To facilitate for easier data retrieval there are also a set of views or virtual tables available in the database.
Data in the system is for the most part processed by three distinct application components all developed in Microsoft Visual Basic 6.0:
· The CSES editing component: is used for entering household information from cover page of questionnaire such as; PSU number, household number and number of members in household.
· The CSES entry component: is used for entering data from each CSES module. This is the main component for data processing.
· The CSES management component: is used to correct errors and view information about operator statistics.
All database modules as well as application components have since 2008 been maintained and improved by staff from the NIS ICT department.
Work flow of CSES data processing system
Step 1. Questionnaires sent from field operators arrives monthly at NIS and is taken care of by data processing staff
Step 2. Questionnaires are updated with appropriate codes for household identification. They are checked and edited for any apparent errors or misunderstandings from the field operator. All changes are written to the questionnaire.
Step 3. Data about number of rows for each module are entered into the management module as well as number of households per PSU. These practices are to ensure that all data rows are entered.
Step 4. Data-entry of all modules including Household, Diary and Village.
Step 5. After finished data entry an iterative error correction phase is started and run from the database server. Any errors from data controls are visible in the management module.
Data Appraisal
Estimates of Sampling Error
In order to provide a basis for assessing the reliability or precision of CSES estimates, the estimation of the magnitude of sampling error in the survey data shall be computed. Since most of the estimates from the survey are in the form of weighted ratios, thus variances for ratio estimates will thus be presented.
The Coefficients of Variation (CV) on national level estimates are generally below 4 percent. The exception is the CV for total value of assets where there are rather high CVs especially in the urban areas, which should be expected.
The CVs are somewhat higher in the urban and rural domains but still generally below 7 percent. For the five zones, the average CVs are in the range 5 to 13 percent with a few exceptions where the CVs are above 20 percent. For provinces the CVs for food consumption are 9 percent on average.
The sample take within Primary Sampling Units (PSU) was set to 10 households per PSU in the CSES 1999. When data on variances became available, it was possible to make crude calculations of the optimal sample take within PSU. Calculations on some of the central estimates in the CSES 1999 show that the design effects in most cases are in the range 1 to 5.
Intra-cluster correlation coefficients have been calculated based on the design effects. These correlation coefficients are somewhat high. The reason is that the characteristics that are measured tend to be concentrated (clustered) within the PSUs. The optimal sample size within PSUs under different assumptions on cost ratios and intra-cluster correlation coefficients was then calculated. The cost ratio is the average cost for adding a village to the sample divided by the average cost of including an extra household in the sample. In the CSES, it was chosen to adopt a fairly low cost ratio due to the fact that the interview time per household is long. Under this assumption the optimal sample size is probably around 10 households per village for many of the CSES indicators.
The Coefficients of Variation (CV) on national level estimates are generally below 4 percent. The exception is the CV for total value of assets where there are rather high CVs especially in the urban areas, which should be expected.
The CVs are somewhat higher in the urban and rural domains but still generally below 7 percent. For the five zones, the average CVs are in the range 5 to 13 percent with a few exceptions where the CVs are above 20 percent. For provinces the CVs for food consumption are 9 percent on average.
The sample take within Primary Sampling Units (PSU) was set to 10 households per PSU in the CSES 1999. When data on variances became available, it was possible to make crude calculations of the optimal sample take within PSU. Calculations on some of the central estimates in the CSES 1999 show that the design effects in most cases are in the range 1 to 5.
Intra-cluster correlation coefficients have been calculated based on the design effects. These correlation coefficients are somewhat high. The reason is that the characteristics that are measured tend to be concentrated (clustered) within the PSUs. The optimal sample size within PSUs under different assumptions on cost ratios and intra-cluster correlation coefficients was then calculated. The cost ratio is the average cost for adding a village to the sample divided by the average cost of including an extra household in the sample. In the CSES, it was chosen to adopt a fairly low cost ratio due to the fact that the interview time per household is long. Under this assumption the optimal sample size is probably around 10 households per village for many of the CSES indicators.
Access policy
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Director General | National Institute of Statistics | sythan@forum.org.kh | www.nis.gov.kh |
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Director, Demographic Statistics, Census and Survey Department | National Institute of Statistics | census@camnet.com.kh | www.nis.gov.kh |
| Data User Service Center | National Institute of Statistics | dusc@nis.gov.kh | www.nis.gov.kh |
| Director, ICT Department | National Institute of Statistics | lundysaint@yahoo.com | www.nis.gov.kh |
Confidentiality
All information collected in CSES 2009 is strictly confidential and will be used for statistical purpose only, in accordance with the 2005 Cambodian Law on Statistics.The Statistics Law Article 22 sexplicitly says that all staff working with statistics within the Government of Cambodia "shall ensure confidentiality of all individual information obtained from respondents, except under special circumstances with the consent of the Minister of Planning. The information collected under this Law is to be used only for statistical purposes."
Access conditions
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the National Institute of Statistics.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the National Institute of Statistics.
4. No attempt will be made to produce links among datasets provided by the National Institute of Statistics, or among data from the National Institute of Statistics and other datasets that could identify individuals or organizations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the National Institute of Statistics will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to the National Institute of Statistics.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the National Institute of Statistics.
4. No attempt will be made to produce links among datasets provided by the National Institute of Statistics, or among data from the National Institute of Statistics and other datasets that could identify individuals or organizations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the National Institute of Statistics will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to the National Institute of Statistics.
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
National Institute of Statistics, Cambodia. Cambodia Socio-Economic Survey 2009. Ref. KHM_2009_CSES_v01_M. Dataset downloaded from http://www.nis.gov.kh/nada/index.php/catalog on [date].
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
National Institute of Statistics, Cambodia. Cambodia Socio-Economic Survey 2009. Ref. KHM_2009_CSES_v01_M. Dataset downloaded from http://www.nis.gov.kh/nada/index.php/catalog on [date].
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the National Institute of Statistics, Cambodia bears no responsibility for use of the data or for interpretations or inferences based upon such uses.
Metadata production
DDI Document ID
DDI_KHM_2009_CSES_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Chum Puthivan | CPTV | National Institute of Statistics | Archivist |
| Saint Lundy | SLD | National Institute of Statistics | Archivist |
| Accelerated Data Program | ADP | International Household Survey Network | Editing for IHSN Survey Catalog |
Date of Metadata Production
2011-09-12
DDI Document version
Version 1.0 - National Institute of Statistics - Original documentation of the study.
Version 2.0 - Edited version by ADP based on Version 1.0 of NIS downloaded from http://www.nis.gov.kh/nada/index.php/catalog on 21 May 2013.
Version 2.0 - Edited version by ADP based on Version 1.0 of NIS downloaded from http://www.nis.gov.kh/nada/index.php/catalog on 21 May 2013.