{"doc_desc":{"title":"UGA_2015_SHS_v02_M","idno":"DDI_UGA_2015_SHS_v02_M_WB","producers":[{"name":"Development Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Documentation of the DDI"}],"prod_date":"2016-03-03","version_statement":{"version":"Version 02 (April 2018)\nIdentical to v01 (March 2016), with two datasets updated."}},"study_desc":{"title_statement":{"idno":"UGA_2015_SHS_v02_M","title":"CGAP Smallholder Household Survey 2015","sub_title":"Building the Evidence Base on the Agricultural and Financial Lives of Smallholder Households","alt_title":"SHS 2015"},"authoring_entity":[{"name":"Jamie Anderson","affiliation":"The World Bank (GFMGP - CGAP)"}],"oth_id":[{"name":"LSMS Team","affiliation":"The World Bank (GFMGP - CGAP)","email":"","role":"Knowledge exchange"},{"name":"LSMS Team","affiliation":"","email":"","role":"Technical assistance in sampling selection"},{"name":"IPSOS Uganda","affiliation":"","email":"","role":"Technical assistance in data collection and data processing"}],"production_statement":{"producers":[{"name":"InterMedia Survey Institute","affiliation":"","role":""}],"copyright":"CGAP (Consultative Group to Assist the Poor), 2016."},"distribution_statement":{"contact":[{"name":"Jamie Anderson","affiliation":"The World Bank (GFMGP - CGAP)","email":"janderson12@worldbank.org","uri":""},{"name":"Max Mattern","affiliation":"The World Bank (GFMGP - CGAP)","email":"mmattern@worldbank.org","uri":""},{"name":"Anna Nunan","affiliation":"The World Bank (GFMGP - CGAP)","email":"anunan@worldbank.org","uri":""}],"depositor":[{"name":"Jamie Barbara Anderson","abbreviation":"","affiliation":"The World Bank"}]},"series_statement":{"series_name":"Other Household Survey","series_info":"Advancing its earlier global segmentation framework (Christen and Anderson 2013), CGAP has been working to build the evidence base on the financial and agricultural lives of smallholder households. This nationally-representative survey of smallholder households collected information on household demographics, poverty status, agricultural activities, income sources and expenses, mobile phones, and informal and formal financial services. The data was used to detail a national picture of the smallholder sector and identify the characteristics of its key segments in a segmentation analysis. To date, CGAP has smallholder household surveys completed or underway in Mozambique, Uganda, Tanzania, Cote d'Ivoire, and Bangladesh."},"version_statement":{"version":"v02: Edited data, second version","version_date":"2015-12-01","version_notes":"The following datasets have been revised, updated to version02: \n - CGAP Smallholder Household Survey_UGA 2015_Household_Mar 18 \n - CGAP Smallholder Household Survey_UGA 2015_Single_Mar 18\n \nVariable: PPI_PROB \n\u201cA data point from the PPI look up table was wrongly entered in the calculation syntax, leading to an error in the likelihood of being poor below the $2.50 line. This has been corrected."},"study_info":{"abstract":"The objectives of the Smallholder Household Survey in Uganda were to:\n\u2022 Generate a clear picture of the smallholder sector at the national level, including household demographics, agricultural profile, and poverty status and market relationships; \n\u2022 Segment smallholder households in Uganda according to the most compelling variables that emerge; \n\u2022 Characterize the demand for financial services in each segment, focusing on customer needs, attitudes and perceptions related to both agricultural and financial services; and,\n\u2022 Detail how the financial needs of each segment are currently met, with both informal and formal services, and where there may be promising opportunities to add value.","coll_dates":[{"start":"2015-08-16","end":"2015-09-07","cycle":""}],"nation":[{"name":"Uganda","abbreviation":"UGA"}],"geog_coverage":"National coverage","analysis_unit":"Households and individual household members","universe":"The universe for the survey consists of smallholder households defined as households with the following criteria: \n1) Household with up to 5 hectares OR farmers who have less than 50 heads of cattle, 100 goats\/sheep\/pigs, or 1,000 chickens; AND \n2) Agriculture provides a meaningful contribution to the household livelihood, income, or consumption.","data_kind":"Sample survey data [ssd]","notes":"The CGAP national surveys of smallholder households used three questionnaires:  (1) household questionnaire, (2) multiple respondent questionnaire, and (3) single respondent questionnaire.  \n\n1. Household questionnaire\nRespondent: Head of the household, their spouse, or a knowledgeable adult\nContent: Basic information on all household members (e.g. age, gender, education attainment, schooling status) and information about household assets and dwelling characteristics in order to derive poverty status.\n\n2. Multiple respondent questionnaire\nRespondents: All household members over 15 years old who contributed to the household income and\/or participated in its agricultural activities\nContent: Demographics (e.g. land size, crop and livestock, decision-making, associations and markets, financial behaviors), agricultural activities (e.g. selling, trading, consuming crops, livestock, suppliers), and household economics (e.g., employment, income sources, expenses, shocks, borrowing, saving habits, investments).\n\n3. Single respondent questionnaire\nRespondent: One randomly-selected adult in the household\nContent: Agricultural activities (e.g. market relationships, storage, risk mitigation), household economics (e.g. expense prioritization, insurance, financial outlook), mobile phones (e.g., usage, access, ownership, desire and importance), and formal and informal financial tools (e.g., ownership, usage, access, importance, attitudes toward financial service providers)."},"method":{"data_collection":{"data_collectors":[{"name":"Ipsos Uganda","abbreviation":"","affiliation":""}],"sampling_procedure":"The CGAP smallholder household survey in Uganda is a nationally-representative survey with a target sample size of 3,000 smallholder households. The sample was designed to provide reliable survey estimates at the national level and for the following administrative four regions: Central, Eastern, Northern, and Western regions. The Central region includes central metro (i.e., four municipalities surrounding Kampala), the parishes in Kampala with poultry activity but it excludes Kampala city which is entirely urban. \n\nSampling Frame\n\nThe sampling frame for the smallholder household survey is the list of enumeration areas (EAs) created for the 2014 Uganda National Population and Housing Census. Uganda is divided into 112 districts with each district comprised of counties\/municipalities. Each county\/municipality consists of sub-counties\/town councils with each of them being further divided into parishes\/wards and villages\/cells.\n\nFor the 2014 population census, each village and cell was further divided into EAs. Information on the number of agricultural households at the EA level will be available in December 2015, and thus not on time for the smallholder survey. As a result, the sample allocation of the survey was based on the distribution of households per region and urban and rural according to the 2014 Census.\n\nSample Allocation and Selection\n\nIn order to take non-response into account, the target sample size was increased to 3,158 households assuming a household non-response rate of 5% observed in similar national households. The total sample size was first allocated to the four regions proportionally to their number of households. Within each region, the resulting sample was then distributed to urban and rural areas proportionally to their size.  \n\nThe sample for the smallholder survey is a stratified multistage sample. Stratification was achieved by separating each region into urban and rural areas. The urban\/rural classification is based on the 2014 population census. Therefore, eight strata were created and the sample was selected independently in each stratum.  Prior to the sample selection, the sampling frame was sorted by the nine agricultural zones called Zardi (Zonal Agriculture Research Development Institute). \n\nIn the first stage, 216 EAs were selected as primary sampling units with probability proportional to size, the size being the number of households in the EAs. A household listing operation was carried out in all selected EAs to identify smallholder households according to the definition used in the survey, and to provide a frame for the selection of smallholder households to be included in the sample.  \n\nIn the second stage, 15 smallholder households were selected in each EA with equal probability.  Due to rounding, this yielded a total of 3,240 smallholder households. In each selected household, a household questionnaire was administered to the head of the household, the spouse or any knowledgeable adult household member to collect information about household characteristics. A multiple respondent questionnaire was administered to all adult members in each selected household to collect information on their agricultural activities, financial behaviors and mobile money usage.  In addition, in each selected household only one household member was selected using the Kish grid and was administered the single respondent questionnaire. \n\nThe full description of the sample design can be found in the user guide for this data set.","coll_mode":"Computer Assisted Personal Interview [capi]","research_instrument":"Building on secondary research on the smallholder sector and discussions with stakeholders, the design process for the survey instrument began. This process involved defining the end goal of the research by:\n\u2022 Drawing from existing survey instruments;\n\u2022 Considering the objectives and needs of the project;\n\u2022 Accounting for stakeholder interests and feedback;\n\u2022 Learning from the ongoing financial diaries in country; and,\n\u2022 Building from a series of focus groups conducted early on in the study.\n\nUsing this foundation, a framework for the survey instrument was developed to share with stakeholders and capture all the necessary elements of a smallholder household. The framework consisted of five main subject areas: (i) demographics, (ii) household economics, (iii) agricultural practices, (iv) mobile phones, and (v) financial services. \n\nIn order to capture the complexity inside smallholder households, the smallholder household survey was divided into three questionnaires: the household questionnaire, the multiple respondent questionnaire and the single respondent questionnaire.  In addition to English, the questionnaires were translated into nine local languages: Lugishu, Luganda, Ateso, Lugbara, Runyakole, Lutooro, Ngakaaramojong, Langi, and Acholi. \n\nThe household questionnaire collected information on:\n\u2022 Basic household members\u2019 individual characteristics (age, gender, education attainment, schooling status, relationship with the household head)\n\u2022 Whether each household member contributes to the household income or participates in the household\u2019s agricultural activities.  This information was later used to identify all household members eligible for the other two questionnaires.  \n\u2022 Household assets and dwelling characteristics \n\nBoth the Multiple and Single Respondent questionnaires collected different information on:\n\u2022 Agricultural practices: farm information such as size, crop types, livestock, decision-making, farming associations and markets\n\u2022 Household economics: employment, income, expenses, shocks, borrowing and saving habits, and investments\n\nIn addition, the Single respondent questionnaire collected information on:\n\u2022 Mobile phones: attitudes toward phones, usage, access, ownership, desire and importance\n\u2022 Financial services: attitudes towards financial products and services such as banking and mobile money, including ownership, usage, access and importance.  \n   \nFollowing the finalization of questionnaires, a script was developed to support data collection on mobile phones. The script was tested and validated before its use in the field.","coll_situation":"InterMedia\u2019s local field partner conducted the recruitment of interviewers and supervisors for the main fieldwork taking into account their language skills. Following the recruitment of 130 field staff, the training was conducted 3-8 August 2015 in Kampala. Five independent field quality control staff directly hired by InterMedia also attended the training. The training consisted of instructions on interview techniques and field procedures, a detailed review of the survey questionnaires, mock interviews between participants in the classroom, and a field practice with real respondents in the areas outside the sampled EAs.   \n\nTwenty-six interviewing teams carried out data collection for the survey on mobile phones. Each team consisted of one supervisor and five interviewers. Four staff members from InterMedia\u2019s local field partner coordinated and supervised fieldwork activities in addition to the five independent quality control (QC) team hired by InterMedia. The QC team stayed with the survey teams during fieldwork to closely supervise and monitor them. Data collection took place from 16 August to 07 September 2015. During data collection, InterMedia received weekly partial data from the field which was analyzed for quality control and used to provide timely feedback to field staff.    \n\nThe final data file was checked for inconsistencies and errors by InterMedia and corrections were made as necessary and where possible.","act_min":"InterMedia\u2019s local field partner recruited 130 field that included interviewers and supervisors. In addition five independent field quality control staff were directly hired by InterMedia. Each team consisted of one supervisor and four to five interviewers. Four staff members from InterMedia\u2019s local field partner coordinated and supervised fieldwork activities and the independent quality control (QC) team hired by InterMedia oversaw the overall quality function of data collection. The QC team stayed with the survey teams during fieldwork to closely supervise and monitor them.","weight":"The sample for the smallholder household survey is not self-weighting, therefore sampling weights were calculated. The first component of the weights is the design weight based on the probability of selection for each stage of selection. The second component is the response rate at both household and individual levels. \n\nThe design weights for households were adjusted for non-response at the household level to produce adjusted household weights. Sampling weights for the multiple respondent data file were derived from adjusted household weights by applying to them non-response rates at the individual level. For the single respondent data file, the same process was applied after taking into account the sub-sampling done within the household. \n\nFinally, household and individual sampling weights were normalized separately at the national level so the weighted number of cases equals the total sample size. The normalized sampling weights were attached to the different data files and used during analysis.","cleaning_operations":"During data collection, InterMedia received a weekly partial SPSS data file from the field which was analyzed for quality control and used to provide timely feedback to field staff while they were still on the ground. The partial data files were also used to check and validate the structure of the data file. \n\nThe full data file was also checked for completeness, inconsistencies and errors by InterMedia and corrections were made as necessary and where possible.","method_notes":"Following the finalization of questionnaires, a script was developed using Dooblo to support data collection on smart phones. The script was thoroughly tested and validated before its use in the field."},"analysis_info":{"response_rate":"The user guide includes household and individual response rates for the CGAP smallholder household survey in Uganda.","sampling_error_estimates":"The sample design for the smallholder household survey was a complex sample design featuring clustering, stratification and unequal probabilities of selection. For key survey estimates, sampling errors taking into account the design features were produced using either the SPSS Complex Sample module or STATA based on the Taylor series approximation method."}},"data_access":{"dataset_use":{"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n- the Identification of the Primary Investigator\n- the title of the survey (including country, acronym and year of implementation)\n- the survey reference number\n- the source and date of download\n\nAnderson, Jamie. 2016. Survey of Smallholder Households in Uganda: Household Level Data. Washington, D.C.: CGAP, March. Ref UGA_2015_SHS_v01_M. Downloaded from [url] on [date].","conditions":"Direct access.","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."}}},"schematype":"survey","tags":[{"tag":"noDOI"}]}