KHM_1999_CSES_v01_M
Socio-Economic Survey 1999
Name | Country code |
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Cambodia | KHM |
Socio-Economic/Monitoring Survey [hh/sems]
The National Institute of Statistics (NIS) of the Ministry of Planning conducted the Cambodia Socio-Economic Survey (CSES) 1999. CSES 1999 is the second of two surveys sponsored by the Capacity Development for Socio-Economic Surveys and Planning Project CMB/96/019 of the Royal Government of Cambodia. The UNDP and the Swedish International Development Agency (SIDA) financed the Project, which is executed by the World Bank. CSES 1999 was planned, designed and implemented by the staff of the NIS with technical support provided by the Project experts.
The main objective of CSES 1999 was to, supplement the data base generated through CSES 1997, fill critical data gaps in a number of topics, and meet the data needs for analyzing and monitoring poverty, and support the anti-poverty programmes and interventions of the Royal Government of Cambodia. Accordingly, the scope of the survey was determined to canvass detailed information on household income and consumption, employment and earnings, labour utilization, child labour, and other current data needed to compile socio-economic indicators in several subject areas. Establishing and strengthening the capacity of NIS to conduct large scale household surveys and thereby institutionalize CSES as a national survey program was an important objective of the project.
Sample survey data [ssd]
The 1999 Cambodia Socio-Economic Survey covered the following topics:
VILLAGE LEVEL
HOUSEHOLD LEVEL
National
The sample was designed to provide estimates of the indicators at: 1. For National 2. For three strata: Phnom Penh, Other urban and Rural area 3. For four zones: Plain, Tonle Sap, Coastal, and Plateau/Mountain.
Select sample households from non-institutional households (All regular residents in Cambodia) in Cambodia.
Name | Affiliation |
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National Institute of Statistics | Ministry of Planning |
Name | Role |
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World Bank | Project Execution |
United Nations Development Program | Technical assiatance |
Swedish International Development Agency | Technical assiatance |
Name | Role |
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United Nations Development Program | Financial assiatance |
Swedish International Development Agency | Financial assistance |
A two stage stratified sampling design with the villages as the first stage units (PSU's) and households as the second stage units(SSU's) was used in the sampling strategy which was based on the method of inter-penetrating sub-samples. A truncated frame which excluded 4.5% of the villages was used because of the difficulty of conducting field work for security reasons in the excluded villages. The survey covered all non-institutional households including one person households. CSES 1999 sampled 6,000 households distributed in 600 villages in the country. The survey was conducted in two rounds to capture seasonal changes in the characteristics studied. The sampling design provided for estimates to be prepared for the urban and rural sectors and the capital city of Phnom Penh as well as for the four ecological zones of the Plain, Tonle Sap Lake, Coastal and Plateau and Mountain Regions. The design is not self-weighting and weights were used in the preparation of survey estimates.
Although CSES 1997 was successful operationally, improvements in the sampling design were considered essential while retaining the main features of the design which has been briefly outlined earlier. The inclusion of such topics as employment, child labor, per capita expenditure of households, health, and education expenditure demonstrated that the sample size should be adequate to produce statistically reliable estimates for the main stratification. The approximate computation of sampling errors of some key estimates in CSES 1997 that sampled 6,000 households showed that the relative errors were in the range of 3 % to 10% or a margin of error twice as much. It was thus necessary to reduce the sampling errors and it was evident that the sampling errors of estimates of the same variables canvassed in CSES 1999 as well as those which had similar prevalence rates would be high. Thus, it was clear that the sample size in fact should be raised above 6,000 households to produce nationally and sectorally representative and statically reliable estimates in respect of some of the key variables in the core questionnaire and in the income and employment module. Because of financial and administrative constraints, it was not feasible to increase the total number of households to be sampled. Therefore it was necessary to resort to the other options available that of improving the precision of the estimates by adopting a more efficient sampling design and attempting to lower the sampling errors.
When compared with the sampling designs that were adopted in surveys conducted earlier in Cambodia, a more efficient and improved sampling strategy was adopted in CSES 1999. The new sampling strategy has provided for estimates for the urban and rural sector, and the capital city of Phnom Penh as well as for the different ecological zones. The method of interpenetrating sub-samples has also provided for the preparation of separate estimates for ecological zones of the country from independent sub-samples enabling checks on the quality of data collected and on the precision of the estimates. Apart from these major innovations, the sampling procedures for the selection of villages which were the primary sampling units (PSU's) and households which formed the secondary sampling units (SSU's) were also improved by adopting circular systematic sampling with probability proportional to size (CSSPPS) techniques.
The sampling design of CSES 1997 followed the sampling strategy adopted in the two socio-economic surveys conducted earlier namely SESC 1993/94 and SESC 1996. The designs in these surveys were based on the division of the country into three domains Phnom Penh, other urban and rural areas so that separate estimates can be prepared for the capital city, and urban and rural sectors. These surveys used truncated frames that had excluded provinces, communes and villages in which data collection was difficult for security or other reasons. From each domain a specified number for villages were selected as first stage units (PSUs) and the second stage units (SSUs) which were households were selected after a pre-listing of households in the sample PSUs.
CSES 1999 sampled 6,000 households from 600 sample villages distributed in all 24 provinces in the country. The survey covered both urban and rural areas of Cambodia. Approximately 4% of the villages were excluded in 14 provinces because of difficulties of conducting field work for security reasons. The number of households sampled from each village was restricted to 10 to reduce the cluster effect and improve the precision of the estimates.
Estimates for round one and round two are provided separately for certain characteristics in addition to the estimates from both rounds of the survey. The estimates provided in the report are for the truncated frame used in the survey that excluded 4.2% of the villages because of the difficulty of conducting fieldwork for security reasons. In respect of a few key variables extrapolated estimates were prepared which covered the excluded areas of the country in addition to the truncated frame used in the survey.
Non-responding households were replaced. The need to adjust the weights for non-response did not arise as completed questionnaires from all sampled villages and households were retrieved achieving a 100% response rate.
The sampling design used in CSES 1999 is not self-weighting. Therefore it was necessary to calculate the weights or inflation factors applicable to both villages and households of each sampled village, before the data for villages or households were aggregated. The weights for estimation of the aggregates were computed (or the villages and households in the 10 domains into which the country is divided. The need to adjust the weights for non-response did not arise as completed questionnaires from all sampled villages and households were retrieved achieving a 100% response rate. Inflation factors were checked for each domain by comparison of the sum of the weighting factors of all sampled households which constitute an estimated total number of households in the domain against the total number of households for the domain in the sampling frame. The weighting factors (named WEIGHT in the data files) with the corresponding identifiers of villages and households were fed as an input into the computer to be merged with the data files.
As in CSES 1997, four questionnaires were used in CSES 1999 for data collection. These include:
CSES Form 1: household listing sheet was used to record all households in the village or part thereof selected for household enumeration. The current list of households was necessary for sampling households and also as an input to derive household weights.
CSES Form 2: Village Questionnaire canvassed data on village population, physical and social infrastructure, development programmes and institutions at the village level and village level prices and unskilled wage rates
CSES Form 3: Core Questionnaire canvassed data on demographic characteristics, education, health and immunization, household and housing characteristics; and household consumption.
CSES Form 4: Income and Employment Module canvassed detail information on employment, wages and earnings; child labour; all types of household economic activities; household assets and household income.
Start | End | Cycle |
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1999-01 | 1999-03 | Round 1 |
1999-06 | 1999-09 | Round 2 |
Name |
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National Institute of Statistics (NIS) |
Field enumerators and supervisors were drawn from the NIS, MOP and the provincial planning and statistics offices. In all, 93 enumerators and supervisors were trained in Phnom Penh from 6th to 19th December 1998 by the Project staff supported by senior NIS staff. A comprehensive manual was prepared for the use of the field staff and live interviews were conducted through field visits to provide hands on experience. The enumeration and supervisory staff were re-trained for one week from May 24 to 29, 1999 before they were re-deployed on fieldwork. Selected enumerators were specially trained before they were deployed on re-interviews.
Data collection was carried out through visits to the sampled household where several members of the household were interviewed by enumerators. The fieldwork on Round 1 was conducted between January and March 1999 and on Round 2 between June and September 1999. The complexity of the survey required revisits to households to correct incorrect entries and to clarify doubtful responses through the re-interview of more than 2,000 of the 6,000 sampled households. These field control procedures made it possible for the survey to produce adequately comprehensive and complete data on income and expenditure in which under declaration of income and incomplete consumption data are issues frequently encountered in many household surveys.
Data processing was carried out at the NIS on a net-worked computer system with 16 microcomputers and peripherals. 35 NIS staff were trained as editors and coders, key entry and supervisory staff. Completed questionnaires were checked, edited and coded by trained editors before the data was keyed in. IMPS (Integrated Micro Processing System ) software developed and supported by the US Bureau of the Census was used for data processing. The data entry and verification system designed for the survey provided for on-line editing. A number of edit programs were prepared to eliminate duplicate records and range edits and consistency checks were used in data cleaning and validation. The tabulations presented in this report were extracted after cleaning the data files.
The approximate computation of sampling errors of some key estimates in CSES 1997 that sampled 6,000 households showed that the relative errors were in the range of 3 % to 10% or a margin of error twice as much. It was thus necessary to reduce the sampling errors and it was evident that the sampling errors of estimates of the same variables canvassed in CSES 1999 as well as those which had similar prevalence rates would be high (Please see in the report of external resources).
Name | Affiliation | URL |
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Director General | National Institute of Statistics | www.nis.gov.kh |
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
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yes | The Statistics Law Article 22 specifies matters of confidentiality. It explicitly 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." |
Each dataset has an "Access policy". The NIS recommends three levels of accessibility:
Use of the dataset must be acknowledged using a citation which would include:
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Name | Affiliation | URL | |
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General Inquiries | National Institute of Statistics | info@nis.gov.kh | http://www.nis.gov.kh/ |
Data User Service Center | National Institute of Statistics | dusc@nis.gov.kh | http://www.nis.gov.kh/ |
DDI_WB_KHM_1999_v01_M
Name | Affiliation | Role |
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Development Economics Data Group | World Bank | Documentation of the DDI |
2011-06-06
Version 01 (June 2011) Adopted from "KHM-NIS-CSES-1999-v1" DDI. Source http://www.nis.gov.kh/nada/?page=catalog