This is the seventh Living Standards Survey (LSS) counducted in Ghana. Thus, this report is based on the seventh round of the Ghana Living Standards Survey conducted in 2016/17. Previous rounds of the survey were conducted in 1987/88, 1988/89, 1991/92, 1998/99, 2005/06, and 2012/13. The method used to estimate poverty rates in this report is identical to that used in the last two surveys, thus making it possible to compare poverty rates over time. The current survey uses the 2012/13 basket. The report assumes what would happen to poverty if a similar, or the same, basket of goods defined in 2012/13 was consumed in 2005/06 and 2016/17, and the same methodology was used to derive deflators for 2005/06 and 2016/17 to deflate the consumption per capita adult equivalent expenditure.
Since 1987, the Ghana Statistical Service (GSS) has been conducting the Ghana Living Standards Survey (GLSS) with the aim of measuring the living conditions and well-being of the population. The GLSS has been useful to policy makers and other stakeholders as it provides timely and reliable information about trends in poverty and helps identify priority areas for policy interventions that aim at improving the lives of the population. It has, over the years, served as one of the primary tools used in monitoring progress on poverty reduction strategies in the country. Monitoring poverty is an essential part of the struggle to end it.
The survey provides the required data at the regional and urban/rural levels for examining poverty and associated indicators for households and the population. The data also allow for decomposition of poverty changes between different groups: urban/rural, locality, region, and socioeconomic status.
Since the fifth round of the Ghana Living Standards Survey (GLSS5) in 2005, the Ghanaian economy benefited from the production of crude oil in commercial quantities and strong economic growth in 2011, leading to the achievement of lower-middle-income status for the country. Economic growth decreased thereafter to a low of 3.7 percent in 2016 but increased in 2017. However, it remains to be seen whether this growth has benefitted all sections of society, including the poorest. Several social intervention programs, including the Livelihood Empowerment Against Poverty (LEAP), Capitation Grant and School Feeding Programme, and now the Free Senior High School Programme started in 2017, have been implemented with the aim of alleviating poverty among the vulnerable population.
Poverty has many dimensions and is characterized by low income, malnutrition, ill-health, illiteracy, and insecurity, among others. The impact of the different factors could combine to keep households, and sometimes whole communities, in abject poverty. To address these, reliable information is required to develop and implement policies that would have an impact on the lives of the poor and vulnerable.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The scope for the survey covers
1. Household Questionnaire: Household roster; Education; Health; Economic activity; Migration; Housing; Agriculture; Household Expenditure (Food and non-food); Income transfers; Credits assets, savings and use of financial services, Governance, peace and security.
2. Community Questionnaire: Demographic information; Economy and infrastructure; Education; Health; Agriculture; Community Equivalence Scale
Producers and sponsors
Ghana Statistical Service (GSS)
The sampling employed a two-stage stratified sampling design. One thousand (1,000) enumeration areas (EAs) were selected to form the Primary Sampling Units (PSUs). The PSUs were allocated into the 10 administrative regions using probability proportional to population size (PPS). The list of EAs from which the samples were drawn was based on the 2010 Population and Housing Census. The EAs were further divided into urban and rural localities of residence. A complete listing of households in the selected PSUs was undertaken to form the Secondary Sampling Units (SSUs). At the second stage, 15 households from each PSU were systematically selected. The total sample size came to 15,000 households nationwide. The sampling is discussed in detail in the appendix of the reports attached as documentation/external resources.
The response rate was 93.3%.
The survey was not a self-weighting sample design because disproportionately larger samples from regions with smaller populations were drawn. Therefore, each sample household did not have the same chance of selection into the survey sample. Hence, weights were computed to reflect the different probabilities of selection in order to obtain the true contribution of each selected EA in the sample based on the first and second stage probabilities of selection. The calculation of the weights are discussed in detail in the appendix of the reports attached as documentation/external resources.
Dates of Data Collection
The application system for the collection of data was developed in CSPro software. All electronic data files for the GLSS7 were transferred remotely from the field (data collection locations) to GSS Head Office in Accra. Various levels of data protection measures were employed to ensure confidentiality of respondents' identification details and security of the data. Data editing, cleaning, coding and processing all started soon after data collected from the field were transferred to Head Office. The editing and cleaning included structure and consistency checks to ensure completeness of work in the field. It also included identification of outliers. Any inconsistencies identified in completed questionnaire from a particular EA were documented and reported to the team responsible to correct before they left the EA. Secondary editing, which required resolution of computer-identified inconsistencies was also undertaken. Even though most sections of the questionnaire were pre-coded some sections required coding in the office. This involved the assignment of numbers (codes) to the occupation and industry in which eligible household members worked using the detailed descriptions provided by the interviewer. Cleaning and aggregation of data were on-going as data were transferred from the field. The data processing including cleaning and aggregation started in October, 2017 and was completed in February, 2018.
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. Not to make 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 identity of any individual or household or establishment that may be inadvertently revealed in any documents or discussion, or analysis. Such unintended identification revealed should be immediately brought to the attention of GSS.
4. Data obtained from GSS are protected by copyright law and therefore not for redistribution or sale.
5. Prospective clients or data users may indicate in an affidavit confidentiality of data they access.
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. It will also assist the government to formulate appropriate policies and programmes to facilitate national development. GSS' policy framework provides access to data through:
Public use files
Datasets only accessible on location
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 for which access has been granted, except those authorized by GSS.
2. Not to use any technique in an attempt to identify any person, establishment, or sampling unit.
3. To hold in strictest confidence, the identification of any establishment or individual that may be inadvertently revealed in any document 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 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, thesis, 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.