Cambodia Socio-Economic Survey 2008
Cambodia, 2008
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Reference ID
KHM_2008_CSES_v01_EN_M_v01_A_OCS
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National Institute of Statistics
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Identification
Survey ID Number
KHM_2008_CSES_v01_EN_M_v01_A_OCS
Title
Cambodia Socio-Economic Survey 2008
Translated Title
Ang Ket Setha Kech Sang Kum Kech Kampuchea 2008
Country
| Name | Country code |
|---|---|
| Cambodia | KHM |
Study type
Socio-Economic/Monitoring Survey [hh/sems]
Series Information
The Cambodia Socio-Economic Survey (CSES) 2008 is the seventh Cambodia Socio Economic Survey conducted by National Institute of Statistics. The survey was conducted in the years 1993/94, 1996, 1997, 1999, 2004, 2007 and 2008.
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.
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.
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
Households
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 get 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, equipments 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 7 main areas of social concern:
1. Demographic characteristics
2. Housing
3. Agriculture
4. Education
5. Labour Force
6. Health and Nutrition
7. Household Income and Consumption
These 7 areas were also covered by corresponding modules in the CSES 2008, together with a diary method as well as a recall method.
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 determined by the household's command over labour and resources for own-production in terms of land and livestock for agricultural activities, equipments 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 7 main areas of social concern:
1. Demographic characteristics
2. Housing
3. Agriculture
4. Education
5. Labour Force
6. Health and Nutrition
7. Household Income and Consumption
These 7 areas were also covered by corresponding modules in the CSES 2008, together with a diary method as well as a recall method.
Coverage
Geographic Coverage
National Coverage
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Institute of Statistics | Ministry of Planning |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Swedish International Development Agency | SIDA | Funding |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Statistics Sweden | SCB | Technical Assistance (TA) |
Sampling
Sampling Procedure
The sampling design in the CSES 2008 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.
Stage 1: A stratified systematic pps6 sample of villages was selected. Strata were defined by provinces and the urban/rural classification of villages. The size measure used in the systematic pps sampling was the number of households in the village according to the population census 1998.
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 households was selected by systematic sampling.
The design described above was used for the CSES 2004 survey. In 2008, a subsample of the villages, or EAs, in the 2004 sample was selected by SRS. The villages and EAs surveyed in 2008 were thus included in the sample in both years. In each selected EA a sample of households was selected by systematic sampling. The selected households in 2008 are not necessarily the same as those included in the sample in 2004.
The selection of households in stage three was done in field by first listing the households in the selected EA, and then selecting a systematic sample of households. Selected households were observed during one calendar month. The allocation of the households over the months in 2008 was done so that each village in the 2008 sample was observed in the same calendar month as in 2004. The sample size in 2008 was 360 villages or 3,600 households, compared to the sample for the 2004 survey of 720 villages or 12,000 households. Some provinces were excluded, due to cost and other reasons, in the sample for 2008. The estimates are however, adjusted for the under coverage error caused by excluding those provinces.
Stage 1: A stratified systematic pps6 sample of villages was selected. Strata were defined by provinces and the urban/rural classification of villages. The size measure used in the systematic pps sampling was the number of households in the village according to the population census 1998.
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 households was selected by systematic sampling.
The design described above was used for the CSES 2004 survey. In 2008, a subsample of the villages, or EAs, in the 2004 sample was selected by SRS. The villages and EAs surveyed in 2008 were thus included in the sample in both years. In each selected EA a sample of households was selected by systematic sampling. The selected households in 2008 are not necessarily the same as those included in the sample in 2004.
The selection of households in stage three was done in field by first listing the households in the selected EA, and then selecting a systematic sample of households. Selected households were observed during one calendar month. The allocation of the households over the months in 2008 was done so that each village in the 2008 sample was observed in the same calendar month as in 2004. The sample size in 2008 was 360 villages or 3,600 households, compared to the sample for the 2004 survey of 720 villages or 12,000 households. Some provinces were excluded, due to cost and other reasons, in the sample for 2008. The estimates are however, adjusted for the under coverage error caused by excluding those provinces.
Response Rate
The CSES 2008 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 design weights are used to compensate for differences in the selection probabilities. The weight for the PSU is inversely proportional to its selection probability.
A further adjustment of the weights was done in order to calibrate the weights so that estimates of population totals would agree with projections based on the 1998 Population Census. Weights for households in the household file were adjusted so that estimated number of households agreed with census projections for each zone, urban and rural. Weights for individuals in the person file were adjusted so that the estimated number agreed with the projected number in each sex and age group in each zone (urban and rural).
Some of the villages are very large. The best procedure would have been to put the very large villages (villages with a size Mhi larger than Mh/nh) in a separate stratum. This was not done. As a result there are a few villages where the inclusion probability exceeds 1.00 and consequently the first stage sampling weight is below 1.00. To rectify this we set the first stage sampling weight (W1) equal to 1.00 for these villages. When doing so we had to adjust the weights downwards for the other villages in the stratum in order to have the same sum of weights for the stratum as before the adjustment.
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 or 20). There were actually two variables indicating the number of households in the village, one was the number obtained by the interviewer (variable E_HHs) and the other was the number obtained by the supervisor (HHs_Vill).
The household sampling weights (Wprel) are calculated by multiplying W1 by W2. All the sampled households in the village get the same household weight. A check of the weights revealed that there were a few extremely low and high weights. These "outliers" will tend to inflate the variance for some estimates. We decided to trim the weights by adjusting the extreme weights towards the center. Weights above 300 were adjusted downwards to 300 and weights below 30 were adjusted upwards to 30. In all only six weights were adjusted. The variation of the weights reflects changes in village sizes between the Census 1998 and the time of the survey. If the current number of households were the same as during the census in all the sample villages there would be no variation at all in the weights. The rather large variation in the weights is by and large a consequence of the long time lag between the census and the survey.
The distribution of the weights for the urban households shows a tendency towards bimodality. Most of the weights are centered around 100 - 120 but there is a cluster of weights around 200 - 220. The reason for this slight abnormality is that the proportional allocation of the sample to strata was not strictly followed. In two urban strata, the sample size was below proportion, resulting in substantially larger sampling weights.
A further adjustment of the weights was done in order to calibrate the weights so that estimates of population totals would agree with projections based on the 1998 Population Census. Weights for households in the household file were adjusted so that estimated number of households agreed with census projections for each zone, urban and rural. Weights for individuals in the person file were adjusted so that the estimated number agreed with the projected number in each sex and age group in each zone (urban and rural).
Some of the villages are very large. The best procedure would have been to put the very large villages (villages with a size Mhi larger than Mh/nh) in a separate stratum. This was not done. As a result there are a few villages where the inclusion probability exceeds 1.00 and consequently the first stage sampling weight is below 1.00. To rectify this we set the first stage sampling weight (W1) equal to 1.00 for these villages. When doing so we had to adjust the weights downwards for the other villages in the stratum in order to have the same sum of weights for the stratum as before the adjustment.
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 or 20). There were actually two variables indicating the number of households in the village, one was the number obtained by the interviewer (variable E_HHs) and the other was the number obtained by the supervisor (HHs_Vill).
The household sampling weights (Wprel) are calculated by multiplying W1 by W2. All the sampled households in the village get the same household weight. A check of the weights revealed that there were a few extremely low and high weights. These "outliers" will tend to inflate the variance for some estimates. We decided to trim the weights by adjusting the extreme weights towards the center. Weights above 300 were adjusted downwards to 300 and weights below 30 were adjusted upwards to 30. In all only six weights were adjusted. The variation of the weights reflects changes in village sizes between the Census 1998 and the time of the survey. If the current number of households were the same as during the census in all the sample villages there would be no variation at all in the weights. The rather large variation in the weights is by and large a consequence of the long time lag between the census and the survey.
The distribution of the weights for the urban households shows a tendency towards bimodality. Most of the weights are centered around 100 - 120 but there is a cluster of weights around 200 - 220. The reason for this slight abnormality is that the proportional allocation of the sample to strata was not strictly followed. In two urban strata, the sample size was below proportion, resulting in substantially larger sampling weights.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2008-10 | 2008-12-31 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
The fieldwork started in October 2007 and finished in the end of December 2008. The results in the survey report are based on data from the calendar year 2008.
Supervisors and enumerators were recruited by NIS and trained for the field work. The training took place at NIS in Phnom Penh. A comprehensive field manual was used during the training and the field work. Each fieldwork team consisted of one supervisor and three enumerators. For each selected village one enumerator was assigned as responsible and carried out interviews of ten households in the village.
Altogether, 30 enumerators and 10 supervisors, divided into 10 teams carried out the fieldwork at the same time. Two groups of teams were formed and alternated monthly so that each interviewer and supervisor worked in the field every second month. For a given month the team arrived in the village 2-3 days before the first day of the month for preparatory tasks like discussing with village authorities, filling in the Household listing form and sampled the households to be interviewed.
Supervisors and enumerators were recruited by NIS and trained for the field work. The training took place at NIS in Phnom Penh. A comprehensive field manual was used during the training and the field work. Each fieldwork team consisted of one supervisor and three enumerators. For each selected village one enumerator was assigned as responsible and carried out interviews of ten households in the village.
Altogether, 30 enumerators and 10 supervisors, divided into 10 teams carried out the fieldwork at the same time. Two groups of teams were formed and alternated monthly so that each interviewer and supervisor worked in the field every second month. For a given month the team arrived in the village 2-3 days before the first day of the month for preparatory tasks like discussing with village authorities, filling in the Household listing form and sampled the households to be interviewed.
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:
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, health of children, mortality, current economic activity, health and illness, smoking and HIV/AIDS awareness.
Form 4: Diary form on daily household expenditure and income
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, health of children, mortality, current economic activity, health and illness, smoking and HIV/AIDS awareness.
Form 4: Diary form on daily household expenditure and income
Data Processing
Other Processing
The data processing was done at NIS in Phnom Penh using the SQL data management system that verifies the data entry operation. A team of data editors, data coders and data entry staff was formed. The data editors were checking the questionnaires before the data entry and also took care of errors to ensure that entered data were consistent with the collected data in the questionnaires or diaries. Before the data entry the coders also put relevant codes in the questionnaire and diary.
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
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Director, Demographic Statistics, Census and Survey Department | National Institute of Statistics | [email protected] | www.nis.gov.kh |
| Data User Service Center | National Institute of Statistics | [email protected] | www.nis.gov.kh |
| Director, ICT Department | National Institute of Statistics | [email protected] | www.nis.gov.kh |
Confidentiality
All information collected in CSES 2008 is strictly confidential and will be used for statistical purpose only, in accordance with the 2005 Cambodian Law on Statistics.
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
Cambodia Socio-Economic Survey 2008 (CSES 2008), National Institute of Statistics, Ministry of Planning, Cambodia
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Director General | National Institute of Statistics | [email protected] | www.nis.gov.kh |
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the National Institute of Statistics, Cambodia beares no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
(c) 2009, National Institute of Statistics, Cambodia
Metadata production
DDI Document ID
DDI_KHM_2008_CSES_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Kim Chantharith | KC | NIS | Archivist |
| Duch Chamroeun | DC | NIS | Archivist |
| Saint Lundy | SLD | NIS | Archivist |
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Metadata adapted for FAM |
DDI Document version
KHM_2008_CSES_v01_EN_M_v01_A_OCS_v01