The Ghana Socioeconomic Panel Survey is a joint effort between the Economic Growth Centre at Yale University and the Institute of Statistical, Social and Economic Research (ISSER), at the University of Ghana (Legon, Ghana). The survey is meant to remedy a major constraint on the understanding of development in low-income countries - the absence of detailed, multi-level and long-term scientific data that follows individuals over time and describes both the natural and man-made environment in which the individuals reside. Most data collection efforts are short-term - carried out at one point in time; and limited in scope – collecting information on only a few aspects of the lives of the persons in the study; and when there are multiple rounds of data collection, individuals who leave the study area are dropped. This means that the most mobile people are not included in existing surveys and studies, perhaps substantially biasing inferences about who benefits from and who bears the cost of the development process. The goal of this project is to follow all individuals, or a random subset, over time using a comprehensive set of survey instruments to shed new light on long-run processes of economic development.
The 2009 survey is the first in a series that is intended to include 5 surveys over the next 15-21 years. Surveys will be implemented approximately every 3 years. In subsequent waves of the panel, a sample of moved households and individuals who have moved out of original households to form new households or joined other households originally not in the panel sample, will be interviewed in addition to the original sample. The number of households in the Panel Study thus has the potential of increasing due to the nature of the design; tracking wholly moved and split households.
The principal objective of the panel survey is to provide a comprehensive data base for carrying out a wide range of studies of the medium- and long-term changes, or lack of changes, that take place during the process of development.
The information gathered from the survey is expected to inform decision makers in the formulation of economic and social policies to:
- Identify target groups for government assistance;
- Construct models to stimulate the impact on individual groups of the various policy options and to analyze the impact of decisions that have already been implemented;
- Access the economic situation on living conditions of households; and
- Provide benchmark data for district assemblies.
v0.1: The first version of the data includes the household and individual level data, but does not include the community level data. The consumption aggregate has also been provided, but this may also be revised in the future.
impact of policy options
benchmark district assemblies
The survey provides regionally representative data for the 10 regions of Ghana. In all, 5010 households from 334 Enumeration Areas (EAs) were sampled. Fifteen households were selected from each of the EAs. The number of EAs for each region was proportionately allocated based on estimated 2009 population share for each region. EAs for Upper East and Upper West regions, which have relatively smaller population sizes, were over sampled to allow for a reasonable number of households to be interviewed in these regions.
Nationally representative, regionally representative for all 10 regions.
Producers and sponsors
Institute of Statistical, Social and Economic Research
University of Ghana
Economic Growth Center
Institute of Statistical, Social and Economic Research
University of Ghana
Economic Growth Center
Economic Growth Center
The survey provides regionally representative data for the 10 regions of Ghana. In all, 5010 households from 334 Enumeration Areas (EAs) were sampled. Fifteen households were selected from each of the EAs. The distribution of the enumeration areas across the regions in Ghana is presented in Table 1. The number of EAs for each region was proportionately allocated based on estimated 2009 population share for each region. EAs for Upper East and Upper West regions, which have relatively smaller population sizes, were over sampled to allow for a reasonable number of households to be interviewed in these regions.
A two-stage stratified sample design was used for the survey. Stratification was based on the regions of Ghana. The first stage involved selecting geographical precincts or clusters from an updated master sampling frame constructed from the 2000 Ghana Population and Housing Census. A total of 334 clusters (census enumeration areas) were selected from the master sampling frame. The clusters were randomly selected from the list of EAs in each region. The selection was based on a simple random sampling technique. A complete household listing was conducted in 2009 in all the selected clusters to provide a sampling frame for the second stage selection of households.
The second stage of selection involved a simple random sampling of 15 of the listed households from each selected cluster. The primary objective of the second stage of selection was to ensure adequate numbers of completed individual interviews to provide estimates for key indicators with acceptable precision at the regional level. Other sampling objectives were to facilitate manageable interviewer workload within each sample area and to reduce the effects of intra-class correlation within a sample area on the variance of the survey estimates.
Since the design is not self-weighting, household sample weights have been computed and applied for the estimation of the survey results. This was to facilitate estimation of the true contribution of each selected cluster in the sample.
Dates of collection
Mode of data collection
The information gathered from the survey will assist decision makers in the formulation of economic and social policies to:
- Identify target groups for government assistance
- Construct models to stimulate the impact on individual groups of the various policy options and to analyze the impact of decisions that have already been implemented
- Access the economic situation on living conditions of households
- Provide benchmark data for district assemblies
To achieve these objectives, detailed data has been collected in the following subject areas:
1. Demographic characteristics: employment, education, migration
2. Information about non-resident spouses and relatives
4. Agricultural Production
- Land information:
(i) Plot background (ii) Size (iii) Fallowing information, soil type, irrigation (iv) Investment, ownership, rental status (v) Crops (vi) Chemical inputs (vii) Tractor use (viii) Seeds (ix) Labour inputs
- Sales and storage:
(ii) Revenues from crop production (ii) Crop stores
5. Non-farm Household Enterprise
- Basic Information and Assets
(i) Basic information (ii) Enterprise assets
- Information about employees
(i) Information about all employees (ii) Information about four important employees (iii) Enterprises operating in the past 1 month (iv) Enterprise in a typical month
- Accounting: General enterprise
- Accounting: Trade/wholesale enterprise
- Accounting: Food enterprise
- Accounting: Services
6. Household Health
- Activities of daily living
- Miscellaneous health
- Health in the past 2 weeks
- Health in the past 12 month
7. Womens' Health
8. Mens' Health
- Reproductive Health
9. Children's Module
- Young child health - children younger than 5 years old
- Digit span test- children aged 5-15
- Raven's Pattern Cognitive Assessment- children aged 5-15
- Math questions- children aged 9-26
- English questions- children aged 9-26
10. Psychology/Social Networking
(i) Depression (ii) Subjective social welfare (iii) Regretted consumption (iv) Townsend questions (v) Trust and solidarity (vi) Time use
- Big 5 personality questions
- Social networking
- Information seeking
(i) Interaction with organizations (ii) Extension services (iii) Volunteerism
11. Consumption Module
- Food items consumed
- Clothing and footwear
- Expenditure on other items in last 12 months
- Fuel and other lubricants
12. Housing Characteristics
- Part A - Rent, water, light, cooking, waste disposal, building materials
- Part B - Dwelling type, ownership, living conditions, power supply, surroundings
The community inventory documents a broad range of natural and institutional features of the community, including political organizations, financial institutions, the presence of various development programs, and community infrastructure. There was also a questionnaire for Districts and Municipal Assemblies. As of December 2015, Seperate documentation for the Community survey and the data will be made available later.
The processing of the survey data began shortly after the fieldwork commenced. The first stage of data processing involved office editing and post-coding. Questionnaires were edited to double-check for completeness and consistency in the questionnaires returned, while the post-coding served to define new response categories to pre-coded question or define a response set for open ended questions. Once the editing and post-coding were done, the questionnaires were passed on for data entry.
The data entry program was designed in CSPro version 4.0. The entry program was designed with the necessary skip patterns and consistency checks to ensure adequate data quality and validity. All questionnaires were entered twice (100 percent verification) and the two files were compared for entry errors which were subsequently verified and corrected with the questionnaires. The data entry was completed in August of 2010. The consolidated data files in CSPro format were then converted to STATA format for further consistency checks and cleaning.
In receiving these data it is recognized that the data are supplied for use within the researcher's organization, and the researcher agrees to the following stipulations as conditions for the use of the data:
1. The data are supplied solely for statistical and research purposes, and will not be made available to other organizations or individuals. Other organizations or individuals may request the data directly.
2. A copy of all publications, conference papers, or other research reports based entirely or in part upon the requested data will be supplied to:
Institute of Statistical, Social, and Economic Research University of Ghana AND Economic Growth Center Yale University
3. The researcher will refer to the 2009-10 Ghana Socioeconomic Panel Survey as the source of the information in all publications, conference papers, and manuscripts with the following statement :
"The data used in this paper come from the 2009-10 Ghana Socioeconomic Panel Study Survey which is a nationally representative survey of over 5,000 households in Ghana. The survey is a joint effort undertaken by
the Institute of Statistical, Social and Economic Research (ISSER) at the University of Ghana, and the Economic Growth Centre (EGC) at Yale University. It was funded by the Economic Growth Center. At the same time,
ISSER and the EGC are not responsible for the estimations reported by the analyst(s)."
4. Users who download the data may not pass the data to third parties.
5. The database cannot be used for commercial ends, nor can it be sold.
- Public use files, accessible to all
Citation requirement is the way that the dataset should be referenced when cited in any publication. Every dataset should have a citation requirement. This will guarantee that the data producer gets proper credit, and that analytical results can be linked to the proper version of the dataset. The Access Policy should explicitly mention the obligation to comply with the citation requirement. The citation should include at least the primary investigator, the name and abbreviation of the dataset, the reference year, and the version number. Include also a website where the data or information on the data is made available by the official data depositor.
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
ECG-ISSER.Ghana Socioeconomic Panel Study Survey: 2009-2010. Distributed by The World Bank. Study ID: GHA_2009_GSPS_v01_M
Disclaimer and copyrights
ISSER and the EGC are not responsible for the estimations reported by the analyst(s)