Living Standards Survey IV 1998-1999
Ghana, 1998 - 1999
Ghana Statistical Service (GSS)
Last modified
June 12, 2017
Page views
68516
Documentation in PDF
Study website
Metadata
DDI/XML
JSON
Identification
IDNO
GHA_1998_GLSS_v01_M
Title
Living Standards Survey IV 1998-1999
Countries
| Name | Code |
|---|---|
| Ghana | GHA |
Study notes
The Ghana Living Standards Survey (GLSS), with its focus on the household as a key social and economic unit, provides valuable insights into living conditions in Ghana. The survey was carried out by the Ghana Statistical Service (GSS) over a 12-month period (April 1998 to March 1999). A representative nationwide sample of more than 5,998 households, containing over 25,000 persons, was covered in GLSS IV.
The fourth round of the GLSS has the following objectives:
· To provide information on patterns of household consumption and expenditure disaggregated at greater levels.
· In combination with the data from the earlier rounds to serve as a database for national and regional planning.
· To provide in-depth information on the structure and composition of the wages and conditions of work of the labor force in the country.
· To provide benchmark data for compilation of current statistics on average earnings, hours of work and time rates of wages and salaries that will indicate wage/salary differentials between industries, occupations, geographic locations and gender.
Additionally, the survey will enable policy-makers to
· Identify vulnerable groups for government assistance;
· Analyze the impact of decisions that have already been implemented and of the economic situation on living conditions of households;
· Monitor and evaluate the employment policies and programs, income generating and maintenance schemes, vocational training and similar programs. The joint measure of employment, income and expenditure provides the basis for analyzing the adequacy of employment of different categories of workers and income-generating capacity of employment-related economic development.
The fourth round of the GLSS has the following objectives:
· To provide information on patterns of household consumption and expenditure disaggregated at greater levels.
· In combination with the data from the earlier rounds to serve as a database for national and regional planning.
· To provide in-depth information on the structure and composition of the wages and conditions of work of the labor force in the country.
· To provide benchmark data for compilation of current statistics on average earnings, hours of work and time rates of wages and salaries that will indicate wage/salary differentials between industries, occupations, geographic locations and gender.
Additionally, the survey will enable policy-makers to
· Identify vulnerable groups for government assistance;
· Analyze the impact of decisions that have already been implemented and of the economic situation on living conditions of households;
· Monitor and evaluate the employment policies and programs, income generating and maintenance schemes, vocational training and similar programs. The joint measure of employment, income and expenditure provides the basis for analyzing the adequacy of employment of different categories of workers and income-generating capacity of employment-related economic development.
Kind of data
Sample survey data [ssd]
Version
Version
v01
Version notes
- Datasets and variables information (such as literal question, pre and post question text and interviewer instruction) are not added to the documentation.
- Relationship between datasets is not yet constructed.
- Relationship between datasets is not yet constructed.
Coverage
Geographic coverage
National
Unit of analysis
- Household
- Individual
- Community
- Commodity
- Individual
- Community
- Commodity
Producers and sponsors
Authoring entity
| Name | Affiliation |
|---|---|
| Ghana Statistical Service (GSS) | Government of Ghana |
Funding agencies
| Name | Abbreviation | Role |
|---|---|---|
| Government of Ghana | Finance | |
| World Bank | WB | Financial and technical assistance |
| European Union | EU | Financial and technical assistance |
Sampling
Sampling procedure
A nationally representative sample of households was selected in order to achieve the survey objectives. For the purposes of this survey the list of the 1984 population census Enumeration Areas (EAs) with population and household information was used as the sampling frame. The primary sampling units were the 1984 EAs with the secondary units being the households in the EAs. This frame, though quite old, was considered the best available at the time. Indeed, this frame was used for the earlier rounds of the GLSS.
In order to increase precision and reliability of the estimates, the technique of stratification was employed in the sample design, using geographical factors, ecological zones and location of residence as the main controls. Specifically, the EAs were first stratified according to the three ecological zones namely; Coastal, Forest and Savannah, and then within each zone further stratification was done based on the size of the locality into rural or urban.
A two-stage sample was selected for the survey. At the first stage, 300 EAs were selected using systematic sampling with probability proportional to size method (PPS) where the size measure is the 1984 number of households in the EA. This was achieved by ordering the list of EAs with their sizes according to the strata. The size column was then cumulated, and with a random start and a fixed interval the sample EAs were selected. It was observed that some of the selected EAs had grown in size over time and therefore needed segmentation. In this connection, such EAs were divided into approximately equal parts, each segment constituting about 200 households. Only one segment was then randomly selected for listing of the households. At the second stage, a fixed number of 20 households was systematically selected from each selected EA to give a total of 6,000 households. Additional 5 households were selected as reserve to replace missing households. Equal number of households was selected from each EA in order to reflect the labor force focus of the survey.
NOTE: The above sample selection procedure deviated slightly from that used for the earlier rounds of the GLSS, as such the sample is not self-weighting. This is because:
- given the long period between 1984 and the GLSS 4 fieldwork the number of households in the various EAs are likely to have grown at different rates.
- The listing exercise was not properly done as some of the selected EAs were not listed completely. Moreover, it was noted that the segmentation done for larger EAs during the listing was a bit arbitrary.
In order to increase precision and reliability of the estimates, the technique of stratification was employed in the sample design, using geographical factors, ecological zones and location of residence as the main controls. Specifically, the EAs were first stratified according to the three ecological zones namely; Coastal, Forest and Savannah, and then within each zone further stratification was done based on the size of the locality into rural or urban.
A two-stage sample was selected for the survey. At the first stage, 300 EAs were selected using systematic sampling with probability proportional to size method (PPS) where the size measure is the 1984 number of households in the EA. This was achieved by ordering the list of EAs with their sizes according to the strata. The size column was then cumulated, and with a random start and a fixed interval the sample EAs were selected. It was observed that some of the selected EAs had grown in size over time and therefore needed segmentation. In this connection, such EAs were divided into approximately equal parts, each segment constituting about 200 households. Only one segment was then randomly selected for listing of the households. At the second stage, a fixed number of 20 households was systematically selected from each selected EA to give a total of 6,000 households. Additional 5 households were selected as reserve to replace missing households. Equal number of households was selected from each EA in order to reflect the labor force focus of the survey.
NOTE: The above sample selection procedure deviated slightly from that used for the earlier rounds of the GLSS, as such the sample is not self-weighting. This is because:
- given the long period between 1984 and the GLSS 4 fieldwork the number of households in the various EAs are likely to have grown at different rates.
- The listing exercise was not properly done as some of the selected EAs were not listed completely. Moreover, it was noted that the segmentation done for larger EAs during the listing was a bit arbitrary.
Response rate
Out of the selected 6000 households 5999 were successfully interviewed. One household was further dropped during the data cleaning exercise because it had very few records for many of the sections in the questionnaire. This gave 5998 household representing 99.7% coverage. Overall, 25,694 eligible household members (unweighted) were covered in the survey.
Weighting
Detailed mathematical weighting coefficient computation is provided in the Ghana Living Standards Survey fourth round report which is provided as external resource.
Data Collection
Dates of collection
| Start | End |
|---|---|
| 1998-04 | 1999-03 |
Mode of data collection
Face-to-face [f2f]
Data collection supervision
The Supervisor was the team leader and was responsible for overseeing, monitoring and, where necessary, correcting the work of the interviewers and the data entry operator. The interviewers conducted daily interviews with the household. To avoid any interruption in the survey schedule, three interviewers were always at work while the fourth took some rest.
Questionnaires
The main questionnaire used in the survey was the household questionnaire. In addition to this, there were community and Price questionnaires.
- Household Questionnaire: The household questionnaire was used to collect information on various topics some of which pertain to eligible individual household members. The questionnaire is in two parts, A and B.
- Community Questionnaire: The main aim of the community questionnaire was is to identify the economic infrastructure, education and health facilities existing in the villages, as well as any related problems that affects their welfare. The questionnaire was administered in the rural EAs only.
- Price Questionnaire: As part of the survey a price questionnaire was designed to collect prices of most essential commodities in the local markets.
- Household Questionnaire: The household questionnaire was used to collect information on various topics some of which pertain to eligible individual household members. The questionnaire is in two parts, A and B.
- Community Questionnaire: The main aim of the community questionnaire was is to identify the economic infrastructure, education and health facilities existing in the villages, as well as any related problems that affects their welfare. The questionnaire was administered in the rural EAs only.
- Price Questionnaire: As part of the survey a price questionnaire was designed to collect prices of most essential commodities in the local markets.
Data collector(s)
| Name | Abbreviation |
|---|---|
| Ghana Statistical Service | GSS |
Data Processing
Data editing
Training: The project had 3 experienced computer programmers responsible for the data processing. Data processing started with a 2-weeks training of 15 data entry operators out of which the best 10 were chosen and 2 identified as standby. The training took place one week after the commencement of the fieldwork.
Data entry: Each data entry operator was assigned to one field team and stationed in the regional office of the GSS. The main data entry software used to capture the data was IMPS (Integrated Microcomputer Processing System). The data capture run concurrently as the data collection and lasted for 12 months.
Tabulation/Analysis: The IMPS data was read into SAS (Statistical Analysis System), after which the analysis and generation of the statistical tables were done using SAS.
Data entry: Each data entry operator was assigned to one field team and stationed in the regional office of the GSS. The main data entry software used to capture the data was IMPS (Integrated Microcomputer Processing System). The data capture run concurrently as the data collection and lasted for 12 months.
Tabulation/Analysis: The IMPS data was read into SAS (Statistical Analysis System), after which the analysis and generation of the statistical tables were done using SAS.
Data access
Access conditions
The Ghana Statistical Statistical Service accepts the offer of the LSMS Database Administrator to distribute the data from the Ghana Living Standard Survey. The Agreement will operate under the conditions listed below.
1. The Ghana Statistical Service retains complete control of who are allowed to use the data, and all wishing to use the data should obtain prior permission from the Ghana Statistical Service. This permission can be obtained by sending an outline of the proposed research together with contact information to:
Dr. Grace Bediako
Government Statistician
Ghana Statistical Service
P.O. Box GP 1098
Accra
GHANA
tel (233) (21) 682647, 682657, 682694, 663578
fax (233) (21) 664304
e-mail: statservice@gmail.com
2. Before the data may be released by the LSMS Database Administrator, a receipt from the Ghana Statistical Service indicating a fee has been transferred to the Ghana Statistical Service Account with the Bank of Ghana should be produced. Users must contact the Ghana Statistical Service for information on the fee structure. Payment can also be made by check issued to the Ghana Statistical Service and sent to the Government Statistician at the above address.
Account Name: GHANA STATISTICAL SERVICE
Address: Box GP 1098, Accra
Account Number: 02-253-600-580-00
Destination Bank: Bank of Ghana
Swift Code: BAGHGHAC
Please fax a copy of the receipt of payment to 233-21-664304
3. Users requesting permission to use the data should also fill in and send the <a href="http://siteresources.worldbank.org/INTLSMS/Resources/3358986-1181743055198/3877319-1190226677657/DATA_REQUEST_AGREEMENT_2007.doc">agreement form<a/><br/> which specifies the conditions for use of the data. The preferred method for sending the agreement form is by e-mail.
4. Under this agreement, the LSMS Office will be responsible for distributing the data for all countries outside Ghana, while the Ghana Statistical Service will distribute the data to users within Ghana. The CD-ROMs, containing both data and documentation, will be sent to you as soon as possible.
1. The Ghana Statistical Service retains complete control of who are allowed to use the data, and all wishing to use the data should obtain prior permission from the Ghana Statistical Service. This permission can be obtained by sending an outline of the proposed research together with contact information to:
Dr. Grace Bediako
Government Statistician
Ghana Statistical Service
P.O. Box GP 1098
Accra
GHANA
tel (233) (21) 682647, 682657, 682694, 663578
fax (233) (21) 664304
e-mail: statservice@gmail.com
2. Before the data may be released by the LSMS Database Administrator, a receipt from the Ghana Statistical Service indicating a fee has been transferred to the Ghana Statistical Service Account with the Bank of Ghana should be produced. Users must contact the Ghana Statistical Service for information on the fee structure. Payment can also be made by check issued to the Ghana Statistical Service and sent to the Government Statistician at the above address.
Account Name: GHANA STATISTICAL SERVICE
Address: Box GP 1098, Accra
Account Number: 02-253-600-580-00
Destination Bank: Bank of Ghana
Swift Code: BAGHGHAC
Please fax a copy of the receipt of payment to 233-21-664304
3. Users requesting permission to use the data should also fill in and send the <a href="http://siteresources.worldbank.org/INTLSMS/Resources/3358986-1181743055198/3877319-1190226677657/DATA_REQUEST_AGREEMENT_2007.doc">agreement form<a/><br/> which specifies the conditions for use of the data. The preferred method for sending the agreement form is by e-mail.
4. Under this agreement, the LSMS Office will be responsible for distributing the data for all countries outside Ghana, while the Ghana Statistical Service will distribute the data to users within Ghana. The CD-ROMs, containing both data and documentation, will be sent to you as soon as possible.
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 of the data files (for datasets obtained on-line)
Example:
Ghana Statistical Service. Ghana Living Standards Survey (GLSS) 1998-1999. Ref. GHA_1998_GLSS_v01_M. Dataset downloaded from http://microdata.worldbank.org 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 of the data files (for datasets obtained on-line)
Example:
Ghana Statistical Service. Ghana Living Standards Survey (GLSS) 1998-1999. Ref. GHA_1998_GLSS_v01_M. Dataset downloaded from http://microdata.worldbank.org on [date].
Disclaimer and copyrights
Disclaimer
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.
Contacts
Contact(s)
| Name | Affiliation | URI | |
|---|---|---|---|
| LSMS Data Manager | The World Bank | lsms@worldbank.org | http://go.worldbank.org/QJVDZDKJ60 |
Metadata production
IDNo
DDI_GHA_1998_GLSS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Generation of the DDI |
Production date
2006-03-17
Version
Version 02 (August 2015)
- Provided value labels for all categorical variables
Version 01 (June 2010)
- Provided value labels for all categorical variables
Version 01 (June 2010)