{"doc_desc":{"title":"Ghana Living Standards Survey 5: 2005-2006","idno":"DDI-GHA-GSS-GLSS-2005-v2.0","producers":[{"name":"Ghana Statistical Service","abbreviation":"GSS","affiliation":"Office of the President","role":"Compiling, reviewing and archiving the survey"}],"version_statement":{"version":"Version 2.0 (November 2008)"}},"study_desc":{"title_statement":{"idno":"GHA-GSS-GLSS-2005-v2.0","title":"Ghana Living Standard Survey 5: 2005","sub_title":"With Non-Farm Household Enterprise Module","alt_title":"GLSS 2005"},"authoring_entity":[{"name":"Ghana Statistical Service (GSS)","affiliation":"Office of the President"}],"oth_id":[{"name":"GSS Project Staff","affiliation":"","email":"","role":""}],"production_statement":{"producers":[{"name":"Dr. Harold Coulombe","affiliation":"World Bank","role":"(Technical Assistance) data analysis"},{"name":"Dr. Ana Tabunda","affiliation":"Philippines","role":"(Technical Assistance) data analysis"},{"name":"Dr. Jose Ramon Albert","affiliation":"Philippines","role":"(Technical Assistance) data analysis"}],"copyright":"(c) 2008, Ghana Statistical Service","funding_agencies":[{"name":"Government of Ghana","abbreviation":"GOG","role":"Funding"},{"name":"World Bank","abbreviation":"WB","role":"Support"},{"name":"European Union","abbreviation":"EU","role":"Support"}]},"distribution_statement":{"contact":[{"name":"The Government Statistician","affiliation":"Ghana Statistical Service","email":"statservice@gmail.com","uri":"www.statsghana.gov.gh"}]},"series_statement":{"series_name":"Living Standards Measurement Study [hh\/lsms]","series_info":"The Living Standards Measurement Study (LSMS) customized by implementing countries including Ghana (Ghana Living Standards Survey) is a research project that was initiated in 1980 by the Policy Research Division of the World Bank. \n\nIn Ghana, the first Ghana Living Standards Survey (GLSS) was conducted in 1987.  The second, third and fourth rounds followed in 1988, 1991\/92 ,1998\/99 and 2005\/2006 respectively. The previous rounds of GLSS have always had a specific focus. In the 5th Round, the Non-Farm Household Enterprises Module was made the focus and additional sections covering Tourism , Migrants and Remittances were introduced.\n\nIt focuses on the household as a key socio-economic unit and provides valuable insights into living conditions in Ghana. This was to make available relevant data for policy and decision makers to measure socio-economic indicators and appreciate their determinants. Programmes could then be drawn to address challenges identified in sectors of the economy such as health, education, economic activities and housing among others.  Living Standards surveys have therefore come to provide valuable insights into living conditions of developing countries."},"version_statement":{"version":"v2.0:  Edited data, prepared for dissemination for public use","version_date":"2008-10-03"},"study_info":{"keywords":[{"keyword":"Poverty","vocab":"","uri":""},{"keyword":"Expenditure pattern","vocab":"","uri":""},{"keyword":"Consumption expenditure","vocab":"","uri":""},{"keyword":"Housing conditions","vocab":"","uri":""},{"keyword":"Education","vocab":"","uri":""},{"keyword":"Health conditions","vocab":"","uri":""},{"keyword":"Employment","vocab":"","uri":""},{"keyword":"Migration","vocab":"","uri":""},{"keyword":"Own produce consumption","vocab":"","uri":""},{"keyword":"Agriculture","vocab":"","uri":""},{"keyword":"Remittances","vocab":"","uri":""},{"keyword":"Savings","vocab":"","uri":""},{"keyword":"Assets","vocab":"","uri":""},{"keyword":"Enterprise","vocab":"","uri":""}],"topics":[{"topic":"consumption\/consumer behaviour [1.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"income, property and investment\/saving [1.5]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"employment [3.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"in-job training [3.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"labour relations\/conflict [3.3]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"unemployment [3.5]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"working conditions [3.6]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"basic skills education [6.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"vocational education [6.7]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"accidents and injuries [8.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"childbearing, family planning and abortion [8.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"general health [8.4]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"health care and medical treatment [8.5]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"health policy [8.6]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"nutrition [8.7]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"plant and animal distribution [9.4]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"housing [10.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"land use and planning [10.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"TRANSPORT, TRAVEL AND MOBILITY [11]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"fertility [14.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"migration [14.3]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"information technology [16.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"}],"abstract":"One of the major challenges facing Ghana is the need for a more comprehensive, reliable and up-to-date statistics and indicators to monitor and evaluate the effects of development polices and programmes on living standards. The Ghana Living Standards Survey was initiated to address this need. \n\nThe Ghana Living Standards Survey (GLSS) has emerged as one of the important tools in the welfare monitoring system and together with other surveys like the Core Welfare Indicators Questionnaire (CWIQ) and the Ghana Demographic and Health Survey (GDHS) has provided a wealth of information for understanding living conditions in Ghana. \n\nThe objectives of the Ghana Living Standards Survey- Round Five are to:\n Provide insight into living standards in Ghana by providing data to facilitate in-depth analysis of the living conditions of     \n households.\n Provide information on patterns of household consumption and expenditure at a sub-regional levels of disaggregation.\n Provide data on total earnings, hours of work, etc., for in-depth study of differentials among branches of industry, sectors of employment, occupations at geographic areas, levels and between women and men.\nProvide the basis for the construction of the consumer price index.\nUp-date the National Accounts and\nProvide databases for national and regional level planning and poverty monitoring.","coll_dates":[{"start":"2005-09-04","end":"2006-09-03","cycle":""}],"nation":[{"name":"Ghana","abbreviation":"GHA"}],"geog_coverage":"National Regional","analysis_unit":"Household","universe":"The survey covered all de jure household members (usual residents) who have not been away from their usual residents for more than 6 months. This excludes heads of households.","data_kind":"Sample survey data [ssd]","notes":"The scope of the Ghana Living Standards Survey includes:\nHousehold: Housing characteristics, agricultural inputs, crop production, expenditure on food items consumed, assets, savings and loans\nIndividuals:Demographic characteristics like education, health, economic activty, migration and tourism of individuals in the household\nCommunity: Demographic characteristics of rural communities, economy and infrastructure, education, health and agriculture"},"method":{"data_collection":{"data_collectors":[{"name":"Ghana Statistical Service","abbreviation":"GSS","affiliation":"Office of the President"}],"sampling_procedure":"Sampling Frame and Units\nAs in all probability sample surveys, it is important that each sampling unit in the surveyed population have a known, non-zero probability of selection.  To achieve this, there has to be an appropriate list, or sampling frame of the primary sampling units (PSUs).The universe defined for the GLSS 5 survey is the population living within private households in Ghana.  The institutional population (such as schools, hospitals etc), which represents a very small percentage in the 2000 Population and Housing Census (PHC), is excluded from the frame for the GLSS 5 survey.\n\nThe Ghana Statistical Service (GSS) maintains a complete list of census EAs, together with their respective population and number of households as well as maps, with well defined boundaries, of the EAs. .  This information was used as the sampling frame for the GLSS 5.  Specifically, the EAs were defined as the primary sampling units (PSUs), while the households within each EA constituted the secondary sampling units (SSUs).  \n\nStratification\nIn order to take advantage of possible gains in precision and reliability of the survey estimates from stratification, the EAs were first stratified into the ten administrative regions.  Within each region, the EAs were further sub-divided according to their rural and urban areas of location.  The EAs were also classified according to ecological zones and inclusion of Accra (GAMA) so that the survey results could be presented according to the three ecological zones, namely 1) Coastal, 2) Forest, and 3) Northern Savannah, and for Accra.\n\nSample size and allocation\nThe number and allocation of sample EAs for the GLSS 5 depends on the type of estimates to be obtained from the survey and the corresponding precision required. It was decided to sample a total sample of 8000 households nationwide .\n\nTo ensure adequate numbers of complete interviews that will allow for reliable estimates at the various domains of interest, the GLSS 5 sample was designed to ensure that at least 400 households were selected from each region.\n\nA two-stage stratified random sampling design was adopted. Initially, a total sample of 550 EAs was considered at the first stage of sampling, followed by a fixed take of 15 households per EA.  The distribution of the selected EAs into the ten regions or strata was based on proportionate allocation using the population. \n\nUnder this sampling scheme, it was observed that the 400 households minimum requirement per region could be achieved in all the regions but not the Upper West Region.  The proportionate allocation formula assigned only 17 EAs out of the 550 EAs","sampling_deviation":"Under this sampling scheme, it was observed that the 400 households minimum requirement per region could be achieved in all the regions but not the Upper West Region.  The proportionate allocation formula assigned only 17 EAs out of the 550 EAs nationwide and selecting 15 households per EA would have yielded only 255 households for the region.  In order to surmount this problem, two options were considered:  retaining the 17 EAs in the Upper West Region and increasing the number of selected households per EA from 15 to about 25, or increasing the number of selected EAs in the region from 17 to 27 and retaining the second stage sample of 15 households per EA.\n\nThe second option was adopted in view of the fact that it was more likely to provide smaller sampling errors for the separate domains of analysis. Based on this, the number of EAs in Upper East and the Upper West were adjusted from 27 and 17 to 40 and 34 respectively, bringing the total number of EAs to 580 and the number of households to 8,700.","coll_mode":["Face-to-face [f2f]"],"research_instrument":"Five different questionnaires were used for the GLSS 5 survey: PART A, PART B, SECTION 10, COMMUNITY and  PRICE  questionnaires\nPART A Questionnaire comprise:\n Section 1: Household roster collecting information on age, sex, marital status, nationality, religion etc.\n Section 2: Education- General education, Educational carreer, Literacy and Apprenticeship.\n Section 3: Health - Health conditions, Preventive health, Immunisation, Post natal care, Fertility, Contraceptive use and \n                    HIV  awareness and  Health insurance.\nSection 4: Employment and time use, activity status and characteristics of main and secondary jobs, underemployment, \n                   unemployment, employment searchin last 12 months and housekeeping activities.\nSection 5: Migration, Domestic and Outbound tourism.\nSection 6: Identification of household members for agriculture and Non farm enterprises.\nSection 7: Housing characteristics (type of dwelling, utilities and housing expenses), Information technology.\n\nPART B Questionnaire sought information on :\nSection 8: Agricultural assets, Land, Livestock and Equipment, Farm details, Harvest and disposal of crops, Seasonality   \n                   of sales and purchases of key staples, Other agricultural income in cash and kind, Processing of agricultural \n                   produce and Consumption of own produce.\nSection 9: Household expenditure on food and non food, frequently purchased and less frequently purchased items, \n                   Availability of selected consumer items.\nSection 10: Basic characteristics of non farm enterprises, Wage earnings, Employment, Revenue of enterprises, (closing \n                   stock, sales and exports),  Wholesale and retail activities, Preparation of meals, Other revenue, Expenditure of \n                   enterprises and assets of enterprises. \nSection 11: Income transfer and receipts by households, Income and miscellaneous income and expenditure.\nSection 12: Credit, assets, consumer goods and Savings.\n\nCOMMUNITY Questionnaire:\nSection 1: Demographic information of the community ( total population, ethnic groupings etc)\nSection 2: Economy and infrastructure\nSection 3: Education\nSection 4: Health\nSection 5: Agriculture\n\nPRICE Questionnaire consist of \nFood and Non food prices of selected items\n\nMIGRANTS AND REMITTANCES Questionnaire ***(this dataset is not for public use at the moment)\nMigration and Remitances of returned  and current migrants , Improvement to dwelling","coll_situation":"A two week pilot survey was held in Accra for selected enumerators who later became supervisors during the main survey. There  was a one month training for enumerators in Kumasi. Field practice during training were also done in the major languages (akan, ga and hausa).","act_min":"Data Collection\nTwenty-four teams were involved in the data collection, 20 of which worked during each cycle.  Providing for four extra teams afforded each of the 20 regular teams the opportunity to take one month off as annual leave.  The leave arrangements were such that there were always 20 teams at work in a given cycle.\n\nTeam Composition\nFor both urban and rural areas, a field team consisted of seven members: one supervisor, one senior interviewer, 3 interviwers, one data cature staff and a driver.\n\nInterviewer Workload\nA team of three interviewers worked in three EAs during a 33 day cycle. One interviewer was assigned to work in one EA during a cycle. In both rural and urban areas, each interviewer conducted five interviews per day. Thus, at the end of each 33 day period (one cycle) a team will have interviewed 45 households. The Data Capture staff entered all 45 Part A questionnaires before the team left for the next set of EAs.\n\nAn interviewer visited each household in the EA assigned to him\/her every third day. Thus an interviewer's workload of 15 households was divided into three batches of five households.","weight":"The GLSS 5 is 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 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.\n\n The household weight variable is called WEIGHT which is attached to each section data \n A grossing up factor (637.89) was used for the agriculture sections instead of the weight variable.","cleaning_operations":"Data editing at the Statistical Service occurs at 3 levels\n\n1. Field editing by interviewers and supervisors\n2. Office editing\n3. Data cleaning and imputation (including structural checking and completeness)","method_notes":"The data capture at GSS takes the following forms:\n\n1. Manual data entry\n2. Scanning\n\nData editing of the captured data usually consists of:\n\n1. Verification or double entry\n2. Consistency checks\n3. Structure edits\n4. Quality Control\n\nTwenty data entry operators were used to capture the data manually in eight regions. Each operator was assigned a desktop computer and printer. After each batch of questionnaires are entered (one batch consist of questionnaires from 15 households), an operator runs a batch edit program and prints out the errors. These she corrects with her team supervisor before backing up on a Cd-rom and a copy sent to the head office in Accra.\n\nAll the datasets were concatenated in CSPRO and exported to SPSS and frequencies generated and checked for outliers.\nTabulation of the final results were done in SPSS, STATA and CENVAR . Two main reports are currently available:\n        Ghana Living Standards survey, Report of the  fifth round\n        Patterns and Trends in Ghana: 1991 - 2006"},"analysis_info":{"response_rate":"At the end of the survey, 8,687 households were successfully interviewed representing a 99.85 percent response rate","sampling_error_estimates":"The CENVAR software of IMPS was used for estimating the sampling errors, the coefficient of variation (CV), the confidence limits and the design effect for the GLSS 5 data. A design effect of 1.0 indicates that the sample design is as efficient as a simple random sample, whereas a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design (see Table A1.2 in main report).","data_appraisal":"A series of data quality tables and graphs are available to review the quality of the data in the main report"}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"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:\n1.\tNot to make copies of any files or portions of files to which access has been granted except with the authorization by GSS\n2.\tNot to willfully identify any individual or household or establishment in the dataset\n3.\tTo 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.\n4.\tData obtained from GSS are protected by copyright law and therefore not for re-distribution or sale\n5.\tProspective clients or data users may indicate in an affidavit confidentiality of data they access.","required":"yes","form_no":"","uri":""}],"contact":[{"name":"The Government Statistician","affiliation":"Ghana Statistical Service","email":"statservice@gmail.com","uri":"www.statsghana.gov.gh"}],"cit_req":"Ghana Living Standards Survey (GLSS)-2005, version 2.0, Ghana Statistical Service","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. It will also assist the government to formulate appropriate policies and programmes to facilitate national development. GSS' policy framework provides access to data through:\n\n1.\tPublic use files. These categories of data sets are accessible by all without any payment. They are available on-line to all interested users, for research and statistical purposes only.                               \n2.\tLicensed datasets. These categories of data sets are accessible under certain conditions. Thus, prospective clients\/data users may access any data based on certain conditions  set by the GSS\n3.\tDatasets only accessible on location. We consider this category as a data enclave where some data sets are only accessible at GSS head office and prospective data users and researches have to physically be available at GSS head office for further discussions before data are released. Thus, data enclave would not be linked to the outside world through our web site or other medium. \n                                                                    \nThe following terms and conditions apply: \nBefore being granted access to the dataset, all users have to formally agree: \n1.\tTo make no copies of any files or portions of files for which access has been granted, except those authorized by GSS. \n2.\tNot to use any technique in an attempt to identify any person, establishment, or sampling unit. \n3.\tTo 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.\n4.\tThe data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of GSS.\n5.\tThe data will be used for statistical and scientific research purposes only.\n6.\tThe data will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.\n7.\tNo 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.\n8.\tNo attempt will be made to produce links among datasets provided by the GSS with other datasets that could identify individuals or organizations.\n9.\tAny 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\n10.\tAn electronic copy of all reports and publications based on the requested data will be sent to the GSS.","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."}}},"schematype":"survey"}