Ghana Core Welfare Indicators Questionnaire Survey 1997
First round
Ghana, 1997
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Reference ID
GHA-GSS-CWIQ-1997-v2.0
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Identification
Survey ID Number
GHA-GSS-CWIQ-1997-v2.0
Title
Ghana Core Welfare Indicators Questionnaire Survey 1997
Subtitle
First round
Country
| Name | Country code |
|---|---|
| Ghana | GHA |
Study type
Core Welfare Indicators Questionnaire [hh/cwiq]
Series Information
CWIQ I is the first round of the Core Welfare Indicators Questionnaire Surveys. It was carried out by the Ghana Statistical
Service (GSS) with technical assistance from the World Bank to furnish policy makers, planners and programme managers with a set of simple indicators for monitoring poverty and the effects of development policies, programmes and projects on living standards in the country.
Service (GSS) with technical assistance from the World Bank to furnish policy makers, planners and programme managers with a set of simple indicators for monitoring poverty and the effects of development policies, programmes and projects on living standards in the country.
Abstract
The 1997 Core Welfare Indicators Questionnaire (CWIQ) Survey is a nationwide probability sample survey designed to provide simple indicators on timely basis for monitoring poverty and the effects of development policies, programmes and projects on living standards in the country. The survey was conducted by the Ghana Statistical Service with technical assistance from the World Bank. The fieldwork for the survey was carried out between September 1997 and November 1997.
The main objectives of the 1997 CWIQ Monitoring Survey are:
1· To furnish policy makers, planners and programme managers with a set of simple indicators for monitoring poverty and the effects of development policies, programmes and projects on living standards in the country.
2· To provide reliable data on timely basis for monitoring changes in the welfare status in various sub-groups of the population.
3· To ensure rapid data capture, processing, tabulation and analysis.
4· To ensure optimal precision by the use of as large a sample as is feasible, given national statistical resource constraints and the need for rapid results.
5· To eliminate data entry bottlenecks through the use of “scanning” technique with Optical Mark Reader (OMR).
Household and demographic characteristics:
A total of 14,514 households were successfully interviewed. An average household size of 4.1 was obtained for the country with rural households having an average household size of 4.3 compared with 3.8 for urban areas. Generally, households in the poorer quintiles and those in the rural parts of Northern Ghana recorded the highest average household size.
Education:
The literacy rate for the nation is 47.9 percent. The rate for males (62.3%) is considerably higher than that of females (36.4%). The urban rate of 63.0 percent is significantly higher than the rural rate of 39.9 percent. In the rural areas, the Volta
Region has the highest literacy rate of 55.7 percent while in the urban areas, Greater Accra Region has the highest rate of 75.7 percent. The Northern Region has the lowest rate in both rural (6.9%) and urban (37.9%) areas.
Health status:
Pregnant women in the country are more likely to receive pre/post natal care than delivery care. Whereas 87.2 percent of pregnant women received pre/post natal care, only 28.3 percent received delivery care. Generally, women in rural areas are less likely to receive maternity care than their counterparts in the urban areas. Majority of households that reported sick in the four weeks preceding the survey are from the poorest quintiles where the household head was unemployed (27.8%). A breakdown of the type of sickness suffered by respondents, indicate that while the incidence of fever/malaria was higher in the urban areas, the incidence of diarrhoea/gastro intestinal disease was more evident in rural Ghana (3.4%).
Employment:
The unemployment rate for the country is 3.9 percent, comprising 4.7 percent males and 3.2 percent females. The urban rate (9.2%) is relatively higher than the rural rate of 2.3 percent. Eastern Region has the highest rural unemployment rate of 4.2 percent while Upper West Region has the lowest of 0.2 percent. In the urban areas, Ashanti Region has the highest unemployment rate (9.9%) while Upper West Region has the lowest of 2.4 percent.
Household ammenities, assets and access to services:
Over a third (37.3%) of all households own their dwellings, 18.4 percent pay rent while the remaining do not pay any rent. Ownership of home is most common among households headed by own-account workers in the agriculture sector, and is
also predominant in rural (46.9%) than urban (18.9%) areas.
The national average number of rooms per household is 2.0, that for rural households is 2.1 and that for urban is 1.8. Over half (57.7%) of all households live in mud or mud-brick homes while 40.9 percent occupy stone or burnt-brick or cement houses.Most households in the country use fuel wood for cooking: 69.1 percent use firewood and 26 percent use charcoal. With regard to lighting fuel, kerosene (83.2%) is most common in rural areas and among the poorest households, whereas electricity (78.4%) predominates in the urban areas and among the non-poor households.
About a quarter (25.4%) of all households have access to flush toilets, 20.4 percent use “KVIP” toilet, 25.2 percent use pit latrine, while 22.8 percent have no toilet facilities. The use of modern toilet facilities is generally an urban phenomenon.
Nearly forty percent (39.9%) of all households have access to pipe-borne or protected well water, while over a third (34.2%) depend on unprotected well/river/lake for their drinking water. Households headed by own-account workers in the agricultural sector are the worst off.
Ownership of land and livestock is most noticeable in rural than urban areas, and is predominated by households headed by own-account workers in the agricultural sector, particularly in the northern regions. Ownership of electrical appliances is
common among less poor households especially those headed by workers in the formal sector. In all 17.4 percent of households own a bicycle, 1.2 percent own a motorcycle and 2.3 percent own a car. Rural households tend to own a bicycle and/or a motorcycle while their urban counterparts are more likely to own a car.
The main objectives of the 1997 CWIQ Monitoring Survey are:
1· To furnish policy makers, planners and programme managers with a set of simple indicators for monitoring poverty and the effects of development policies, programmes and projects on living standards in the country.
2· To provide reliable data on timely basis for monitoring changes in the welfare status in various sub-groups of the population.
3· To ensure rapid data capture, processing, tabulation and analysis.
4· To ensure optimal precision by the use of as large a sample as is feasible, given national statistical resource constraints and the need for rapid results.
5· To eliminate data entry bottlenecks through the use of “scanning” technique with Optical Mark Reader (OMR).
Household and demographic characteristics:
A total of 14,514 households were successfully interviewed. An average household size of 4.1 was obtained for the country with rural households having an average household size of 4.3 compared with 3.8 for urban areas. Generally, households in the poorer quintiles and those in the rural parts of Northern Ghana recorded the highest average household size.
Education:
The literacy rate for the nation is 47.9 percent. The rate for males (62.3%) is considerably higher than that of females (36.4%). The urban rate of 63.0 percent is significantly higher than the rural rate of 39.9 percent. In the rural areas, the Volta
Region has the highest literacy rate of 55.7 percent while in the urban areas, Greater Accra Region has the highest rate of 75.7 percent. The Northern Region has the lowest rate in both rural (6.9%) and urban (37.9%) areas.
Health status:
Pregnant women in the country are more likely to receive pre/post natal care than delivery care. Whereas 87.2 percent of pregnant women received pre/post natal care, only 28.3 percent received delivery care. Generally, women in rural areas are less likely to receive maternity care than their counterparts in the urban areas. Majority of households that reported sick in the four weeks preceding the survey are from the poorest quintiles where the household head was unemployed (27.8%). A breakdown of the type of sickness suffered by respondents, indicate that while the incidence of fever/malaria was higher in the urban areas, the incidence of diarrhoea/gastro intestinal disease was more evident in rural Ghana (3.4%).
Employment:
The unemployment rate for the country is 3.9 percent, comprising 4.7 percent males and 3.2 percent females. The urban rate (9.2%) is relatively higher than the rural rate of 2.3 percent. Eastern Region has the highest rural unemployment rate of 4.2 percent while Upper West Region has the lowest of 0.2 percent. In the urban areas, Ashanti Region has the highest unemployment rate (9.9%) while Upper West Region has the lowest of 2.4 percent.
Household ammenities, assets and access to services:
Over a third (37.3%) of all households own their dwellings, 18.4 percent pay rent while the remaining do not pay any rent. Ownership of home is most common among households headed by own-account workers in the agriculture sector, and is
also predominant in rural (46.9%) than urban (18.9%) areas.
The national average number of rooms per household is 2.0, that for rural households is 2.1 and that for urban is 1.8. Over half (57.7%) of all households live in mud or mud-brick homes while 40.9 percent occupy stone or burnt-brick or cement houses.Most households in the country use fuel wood for cooking: 69.1 percent use firewood and 26 percent use charcoal. With regard to lighting fuel, kerosene (83.2%) is most common in rural areas and among the poorest households, whereas electricity (78.4%) predominates in the urban areas and among the non-poor households.
About a quarter (25.4%) of all households have access to flush toilets, 20.4 percent use “KVIP” toilet, 25.2 percent use pit latrine, while 22.8 percent have no toilet facilities. The use of modern toilet facilities is generally an urban phenomenon.
Nearly forty percent (39.9%) of all households have access to pipe-borne or protected well water, while over a third (34.2%) depend on unprotected well/river/lake for their drinking water. Households headed by own-account workers in the agricultural sector are the worst off.
Ownership of land and livestock is most noticeable in rural than urban areas, and is predominated by households headed by own-account workers in the agricultural sector, particularly in the northern regions. Ownership of electrical appliances is
common among less poor households especially those headed by workers in the formal sector. In all 17.4 percent of households own a bicycle, 1.2 percent own a motorcycle and 2.3 percent own a car. Rural households tend to own a bicycle and/or a motorcycle while their urban counterparts are more likely to own a car.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households, Individuals
Version
Version Description
v2.0 Edited, anonymous dataset for public distribution.
Version Date
1998-08-27
Scope
Notes
The CWIQ used a household-based questionnaire which consists of four (4) double-sided forms. Pre-coded multiple choice response questions were used. Information solicited from households were on the following modules:
1· Background Characteristics of household members - Household characteristics, household listing and demographic characteristics.
2· Education - Literacy and school attendance.
3· Health - Disability, health facility, health personnel and pre/postnatal care.
4· Employment - Status in employment, occupation, industry and sector of employment.
5· Household Assets - Dwelling, land, livestock, animal and electrical appliances.
6· Household Amenities - Material of roof and wall, lighting/cooking fuel, time taken to market, hospital and school.
7· Poverty Predictors - Use of paper rolls, toothbrush and toothpaste etc.
8· Child Anthropometry - Child roster, place of birth, health attendance etc.
1· Background Characteristics of household members - Household characteristics, household listing and demographic characteristics.
2· Education - Literacy and school attendance.
3· Health - Disability, health facility, health personnel and pre/postnatal care.
4· Employment - Status in employment, occupation, industry and sector of employment.
5· Household Assets - Dwelling, land, livestock, animal and electrical appliances.
6· Household Amenities - Material of roof and wall, lighting/cooking fuel, time taken to market, hospital and school.
7· Poverty Predictors - Use of paper rolls, toothbrush and toothpaste etc.
8· Child Anthropometry - Child roster, place of birth, health attendance etc.
Topics
| Topic | Vocabulary | URI |
|---|---|---|
| economic conditions and indicators [1.2] | CESSDA | Link |
| employment [3.1] | CESSDA | Link |
| unemployment [3.5] | CESSDA | Link |
| working conditions [3.6] | CESSDA | Link |
| compulsory and pre-school education [6.2] | CESSDA | Link |
| post-compulsory education [6.5] | CESSDA | Link |
| mass media [7.4] | CESSDA | Link |
| accidents and injuries [8.1] | CESSDA | Link |
| general health [8.4] | CESSDA | Link |
| nutrition [8.7] | CESSDA | Link |
| housing [10.1] | CESSDA | Link |
| children [12.1] | CESSDA | Link |
| social change [13.7] | CESSDA | Link |
| time use [13.9] | CESSDA | Link |
Keywords
| Keyword |
|---|
| Sex |
| Relationship |
| Age |
| Marital status |
| Education |
| Read |
| Write |
| School |
| Grade |
| Level |
| Problem |
| Disabled |
| Pre-natal |
| Post-natal |
| Pregnancy |
| Pregnant |
| Activities |
| Injury |
| Health provider |
| Health professional |
| Medical |
| Work |
| Industry |
| Occupation |
| Sector |
| Status |
| Dwelling |
| Land |
| Livestock |
| Animal |
| Own |
| Material |
| Roof |
| Wall |
| Fuel |
| Nearest |
| Water |
| School |
| Food |
| Market |
| Hospital |
| Facility |
| Toilet |
| Stunted |
| Household |
| Savings |
| Poverty |
| Health |
| Roster |
| Child |
| Delivery |
| Birth |
| Weight |
| Height |
Coverage
Geographic Coverage
National Regional
Universe
The survey covered all de jure household members (usual residents) in sample.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Ghana Statistical Service | Office of the President |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Ghana Statistical Service | Office of the President | Compiling, reviewing and archiving |
| The World Bank | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Government of Ghana | GoG | Logistical assistance |
| The World Bank | WB | Financial and technical assistance |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Dr. Sudharshan Canagarajah | World Bank | Technical assistance |
| Mr. Timothy Merchant | World Bank, Africa region | Technical assistance |
Sampling
Sampling Procedure
The 1997 CWIQ Monitoring Survey is based on a two-stage, stratified, nationally representative sample of households. The National Sampling
Frame of Enumeration Areas (EA’s) derived from the 1984 census with population and household information formed the basis of the sample design for the survey. The frame was first stratified into three ecological zones, namely coastal, forest and savannah, and then into rural and urban EAs. Additionally, the EAs were stratified into the 10 administrative regions in the country.
At the first stage of sampling, 588 EAs were selected with probabilities proportional to the number of households (PPS-Method). Households within the selected EAs were subsequently listed and a systematic sample of 25 households per EA was selected at the second stage. The survey was designed to yield a total sample of 14,700 households nationwide.
Frame of Enumeration Areas (EA’s) derived from the 1984 census with population and household information formed the basis of the sample design for the survey. The frame was first stratified into three ecological zones, namely coastal, forest and savannah, and then into rural and urban EAs. Additionally, the EAs were stratified into the 10 administrative regions in the country.
At the first stage of sampling, 588 EAs were selected with probabilities proportional to the number of households (PPS-Method). Households within the selected EAs were subsequently listed and a systematic sample of 25 households per EA was selected at the second stage. The survey was designed to yield a total sample of 14,700 households nationwide.
Deviations from the Sample Design
There was no deviation from the sampling design.
Response Rate
The survey was designed to yield a total sample of 14,700 households nationwide but a total of 14,511 households were successfully interviewed. This number from the dataset is short of 3 as stated in both the main report and bulletin.
Weighting
This sample is not self-weighting, hence, there was the need to compute weights or "Raising Factors" for the estimation
of parameters, based on the probabilities of selection. For details of the computation of weights see Appendix A of the main report.
of parameters, based on the probabilities of selection. For details of the computation of weights see Appendix A of the main report.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 1997-09-01 | 1997-11-29 |
Data Collection Mode
Face-to-face [f2f]
Supervision
There was a Supervisor, who was the team leader and was responsible for overseeing, monitoring and, where necessary, correcting the work of the interviewers and the data entry operator. Regional Statisticians were also on the ground to ensure good quality data is collected.
Data Collection Notes
The actual implementation of the fieldwork involved 73 technical staff and 13 drivers. Each of the 13 teams comprised a supervisor, four interviewers and a driver. In addition, there was one standby supervisor and seven interviewers ready for relieve assignments whenever necessary. In order to ensure high quality data, frequent scheduled visits in addition to several random visits were undertaken by senior project management personnel.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Ghana Statistical Service | GSS | Office of the president |
Questionnaires
Questionnaires
The CWIQ I Survey adopted a household -based questionnaire consisting of five double sided sheets with pre-coded multiple choice reponse questions. The Questionnaire covered the Demographic Characteristics, Educational Status, Health status, Household assets and ammenities as well as child anthropometry.
Data Processing
Data Editing
Data capture assistants logged in questionnaires received from the field.The questionnaires were checked and edited manually before being scanned. There was on-line editing while using the Scantools application. Mandatory fields that the scanner could not read were shown on the screen. The scanner assigned a serial number to each questionnaire and this was used to locate the household questionnaire for editing. Automatic correction was done for some selected fields by the CWIQ I application based on some validation rules within the system. Manual editing was done after generating reports for households that failed the validation checks. The EA and the household numbers were then used to locate the household questionnaire for editing.
One major problem encountered with the CWIQ I application was with supplementary questionnaire for larger households
(households with 13 or more members). Responses from supplementary questionnaire were mixed up and thus generated
a lot of error lines in validation runs. This led to manual data entry of the supplementary questionnaire.
One major problem encountered with the CWIQ I application was with supplementary questionnaire for larger households
(households with 13 or more members). Responses from supplementary questionnaire were mixed up and thus generated
a lot of error lines in validation runs. This led to manual data entry of the supplementary questionnaire.
Other Processing
For the first time in the history of the GSS the survey was conducted using Optical Mark Recognition (OMR) "bubble" questionnaire. To enter the data, these questionnaires were read by high speed scanners. The data processing team was able to perform simple on-line edit corrections while scanning. The data was then gradually transferred into a customized Access application for further, more complex validations. The Access application produced clean, validated and documented data files. This process took place at the same time the fieldwork was on-going and finished only four days after the last enumerator returned from the field. The clean data generated by the Access cleaning application was then processed through SPSS statistical package to produce a standard output bulletin within 12 days of the end of fieldwork.
The hardware for the CWIQ I data processing consisted of four NSC Opscan4 (OMR), computers and accessories. Three scanners were used while the fourth served as a standby.
Data scanning and validation for the CWIQ I were timed to have maximum overlap with the fieldwork. Thus data scanning and validation started on 8th September, only seven days after commencement of fieldwork and ended four days after completion of fieldwork on 27th November, 1997. Output tables were produced by 10th December, 1997. In all, 14,514 household questionnaires were successfully scanned and validated. On the average, about 300 household questionaires were scanned and validated in a day.
The hardware for the CWIQ I data processing consisted of four NSC Opscan4 (OMR), computers and accessories. Three scanners were used while the fourth served as a standby.
Data scanning and validation for the CWIQ I were timed to have maximum overlap with the fieldwork. Thus data scanning and validation started on 8th September, only seven days after commencement of fieldwork and ended four days after completion of fieldwork on 27th November, 1997. Output tables were produced by 10th December, 1997. In all, 14,514 household questionnaires were successfully scanned and validated. On the average, about 300 household questionaires were scanned and validated in a day.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Government Statistician | Ghana Statistical Service | statservice@gmail.com | www.statsghana.gov.gh |
Confidentiality
Ghana Statistical Service (GSS) requires all users to keep information and data strictly confidential. In this regard, before being granted access to datasets, all users have to formally agree to observe the following:
1. To make no copies of any files or portions of files to which access has been granted except with the authorization by GSS.
2. Not to willfully identify any individual or household or establishment in the dataset.
3. To hold in strictest confidence the identification of any individual or household or establishment that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed should be immediately brought to the attention of GSS.
4. Data obtained from GSS are protected by copy right law and therefore not for re-distribution or sale.
5. Prospective clients or data users may indicate in affidavit of confidentiality.
Access conditions
The Ghana Statistical Service as a public institution has the obligation to promote data dissemination to facilitate national development. Making data available will enable students and the academia to conduct research works, assist investors to take business decision, help the individual to evaluate and take appropriate decisions and assist the government to formulate appropriate policies and programmes. GSS has policy framework by which the individuals, groups of people and companies could access GSS data.
Three levels of accessibility are considered by GSS:
1) Public use files. These categories of data sets are accessible by all without any payment
2) Licensed datasets. These categories of data sets are accessible under certain conditions. Thus, prospective clients/data users may access any data based on certain conditions that GSS will dictate
3) Datasets only accessible on location. Under this, some categories of data sets are accessible at GSS head office and prospective data users have to physically be available at GSS head office for further discussions before data are released
The following terms and conditions apply:
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by GSS.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the GSS.
4. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of GSS.
5. The data will be used for statistical and scientific research purposes only.
6. The data will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
7. 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 GSS.
8. No attempt will be made to produce links among datasets provided by the GSS with other datasets that could identify individuals or organizations.
9. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the GSS would cite the source of data in accordance with the citation statement provided with the dataset
10. An electronic copy of all reports and publications based on the requested data will be sent to the GSS.
Three levels of accessibility are considered by GSS:
1) Public use files. These categories of data sets are accessible by all without any payment
2) Licensed datasets. These categories of data sets are accessible under certain conditions. Thus, prospective clients/data users may access any data based on certain conditions that GSS will dictate
3) Datasets only accessible on location. Under this, some categories of data sets are accessible at GSS head office and prospective data users have to physically be available at GSS head office for further discussions before data are released
The following terms and conditions apply:
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by GSS.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the GSS.
4. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of GSS.
5. The data will be used for statistical and scientific research purposes only.
6. The data will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
7. 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 GSS.
8. No attempt will be made to produce links among datasets provided by the GSS with other datasets that could identify individuals or organizations.
9. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the GSS would cite the source of data in accordance with the citation statement provided with the dataset
10. An electronic copy of all reports and publications based on the requested data will be sent to the GSS.
Citation requirements
GSS, Core Welfare Indicator Questionnaire Survey (CWIQ I) - 1997, v2.0
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Ghana Statistical Service | GSS | statservice@gmail.com | www.statsghana.gov.gh |
Disclaimer and copyrights
Disclaimer
The original collector of the data, Ghana Statistical Service, other producers and sponsors cited in this document bear no responsibility for use of the data, for interpretations and inferences based upon such uses.
Copyright
©1998, Ghana Statistical Service
Metadata production
DDI Document ID
DDI-GHA-GSS-CWIQ-1997-v2.0
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Ghana Statistical Service | GSS | Office of the President | Compiling, reviewing and archiving the survey |
Date of Metadata Production
2008-04-17
DDI Document version
Version 2.0