GMB_1993_HEHS_v01_M
Household Education and Health Survey 1993-1994
Name | Country code |
---|---|
Gambia, The | GMB |
Other Household Survey [hh/oth]
The Household Education and Health Survey has one fundamental objective, to provide reliable information base for formulating economic and social policy. The focus of the survey is therefore diagnostic - explaining how and why households respond to changes in the macroeconomic environment and how their well-being is thereby affected.
Sample survey data [ssd]
Household
Individal/ person
Children under 5 years of age
The 1993-94 Household Education and Health Survey covered the following topics:
National coverage
Name | Affiliation |
---|---|
Central Statistics Department | Ministry of Finance and Economic Affairs, The Gambia |
Name | Role |
---|---|
African Development Fund | Funded the project |
Overall sampling and budgetary consideration suggested that a sample size of about 2000 households would be both statistically appropriate and financially feasible. It would be statistically appropriate because it would provide more than enough cases for a national sample and sufficient cases for Divisional level analysis. It was appropriate to the budget because estimates of the time and resources suggested it was well within the capabilities of the team envisaged for data collection.
It is technically possible to draw a simple random sample from all of the 100,000 households in Gambia. However it is not economically feasible to conduct such a survey because of the large amount of travel that would be required to conduct the interviews in rural areas with a scattered population. Therefore some method of clustering the households was necessary to provide for a staged sampling procedure.
Geographical clustering already exists in the form of census Enumeration Areas. These EAs are mapped to contain approximately 500 persons, and cover the entire country, conforming to the administrative boundaries. Enumeration Areas are approximately the same size [500 persons]. However in actuality they range from about 300 to 1000 persons. Some classification by size is desirable to maintain sampling probabilities.
The number of households selected per EA is a further factor in the sampling process. Maximizing the number of households per EA has the advantage of reducing travel costs. It also increases sampling error by sharply reducing the number of EAs sampled. Minimizing the number of households per EA greatly increases costs but does not affect sampling error to the same extent. A constant tae of households per EA has no effect on the sampling error ever proportional probability sampling in stage one. Because urban populations are more likely to be residentially homogenous the constant take for urban EAs is set at half of that for rural EAs. In villages the rich and the poor are more likely to be found within the same EA.
Taking all the above considerations into account it was decided to use a multi-stage sampling approach using probability proportional to size as recommended in the Working Paper.
(Refer to Chapter 2 (Methodology) in the survey final report for details of sampling information)
Start | End |
---|---|
1993-11 | 1994-03 |
Training
All supervisors, interviewers and data entry clerks went through four weeks of training on data collection. The training included interview techniques, detailed discussion of each question and training in measuring and estimating quantities consumed for the consumption of own produce section.
Because the majority of interviews would be conducted in one of the local languages some time was spent on ensuring standard translations of the key questions. It was anticipated that most interviews would be conducted in Mandinka, Wollof or Fula the three most common local languages. Interviewers were in structured to secure an interpreter if there was no common language.
The trainees conducted some household interviews under close supervision in the Greater Banjul area and also in the North Bank Division which is largely rural and agricultural. The data entry clerks collected data in Greater Banjul for a month then they received further training in the specifics of the data entry program.
Data Collation
The data was collected from the beginning of November 1993 to the end of March 1994. In rural areas a field team conducted roughly a round of interviews in two EAs (36 interviews) per week. The field teams were based in five locations around the country.
Interviews took place in Mandinka[55 percent] or Wollof[33 percent]. A minority used Fula[4 percent] or some other language. Interpreters were used in 2 percent of cases.
Households were defined as a group of persons acknowledging one head and with some sharing of food and budgets. In the Gambian context this meant that most polygamous households were counted as one large household.
Quality control of the data was conducted at a number of levels. Team supervisors checked survey forms for missing data and coded some data. The Team Leader and Field Manager visited each rural team at several points in the data collection, while members of the Head Office staff supervised the two teams working in and around Greater Banjul. Supervisors came into the Head Office on a number of occasions for consultation and progress reporting.
Each survey was checked again by a member of the professional staff once ot reached Head Office. Missing or suspect data detected at this point resulted in the return of the questionnaire to the team with a request to call back on the household and obtain or verify the data.
Data Entry
The data entry tool place in the head office in Banjul, where the process was supervised by senior staff. Data entry used the US Bureau of Census program IMPS, which provided extensive facilities for data entry and checking. The surveys were extensively precoded and the data entry operators referred any questionable data back to one of the office supervisors. One of the advantages of the IMPS system is its ability to produce concatenated batches easily and to process frequency tables using the data dictionary defined for data entry. It was therefore possible to have frequent updates of the data entered and check for trends and obvious errors. The data entry operators were able to maintain a good speed of data entry.
Data Cleaning
Because of the preceded data entry program there were few out of range errors in the data. Most of the data cleaning process was involved with ensuring that each household was represented in the seventeen data sets that comprised the complete run of data. Some households were duplicated and some had not been collected or not returned after call backs.
There were some errors on mispunched legitimate codes but on the whole the rigorous program of checking at several stages before data entry kept the reliability and integrity of the data high.
Name | Affiliation | URL |
---|---|---|
Central Statistics Department | Ministry of Finance and Economic Affairs, The Gambia | http://www.gambia.gm/Statistics/index.htm |
Use of the dataset must be acknowledged using a citation which would include:
Example:
Central Statistics Department, The Gambia. Household Education and Health Survey 1993-1994. Ref. GMB_1993_HEHS_v01_M. Dataset downloaded from [source] on [date].
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 | |
---|---|---|---|
Household Survey, Central Statistics Department | Ministry of Finance and Economic Affairs, The Gambia | Householdsurvey@csd.gm | http://www.gambia.gm/Statistics/index.htm |
DDI_GMB_1993_HEHS_v01_M_WB
Name | Role |
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World Bank, Development Economics Data Group | Documentation of the DDI |
2013-09-12
Version 01 (September 2013): Metadata in this DDI is excerpted from "1993-94 Household Education and Health Survey Report".