{"doc_desc":{"title":"NGA_2015_FNLP-BL_v01_M","idno":"DDI_NGA_2015_FNLP-BL_v01_M_WB","producers":[{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Documentation of the DDI"}],"prod_date":"2017-08-09","version_statement":{"version":"Version 01 (August 2017)."}},"study_desc":{"title_statement":{"idno":"NGA_2015_FNLP-BL_v01_M","title":"Feed the Future Nigeria Livelihoods Project 2015","sub_title":"Baseline Survey","alt_title":"FNLP-BL 2015"},"authoring_entity":[{"name":"Gautam Bastian","affiliation":"World Bank "},{"name":"Sreelakshmi Papineni","affiliation":"World Bank "}],"production_statement":{"funding_agencies":[{"name":"The World Bank","abbreviation":"","role":""}]},"distribution_statement":{"contact":[{"name":"Gautam Bastian","affiliation":"World Bank ","email":"gbastian@worldbank.org","uri":""},{"name":"Sreelakshmi Papineni","affiliation":"World Bank ","email":"spapineni@worldbank.org","uri":""}],"depositor":[{"name":"Brittany Nicole Hill","abbreviation":"AFRGI - Gender Impact Evaluation","affiliation":"The World Bank"}]},"series_statement":{"series_name":"Impact Evaluation Survey"},"version_statement":{"version":"- v01, edited anonymous datasets for public distribution.\n\nVariables related to names, phone numbers, addresses and emails of respondents and GPS coordinates were anonymized."},"study_info":{"abstract":"Feed the Future Nigeria Livelihoods Project (FNLP) is a multi-component development project based on the graduation model pioneered by Bangladesh Rural Advancement Committee (BRAC) that intends to help 42,000 very poor households across rural communities of northern Nigeria\u2019s Sokoto and Kebbi states, and the Federal Capital Territory (FCT). FNLP is a 5-year program implemented by Catholic Relief Services (CRS). Both the program and the impact evaluation are funded by United States Agency for International Development (USAID).\n\nThis program approach is founded on an agriculture-led growth strategy that is expected to help vulnerable families diversify their income and grow assets while the community is strengthened by improving nutrition, water sanitation, and hygiene. The most vulnerable families receive cash transfers. A caseworker-led livelihood mentoring scheme also matches households with the resources they need to engage effectively in the local economy and break free from the cycle of poverty and malnutrition.\n\nThe impact evaluation, led by The World Bank\u2019s Africa Gender Innovation Lab (GIL), is being conducted in Kebbi state in North-West Nigeria and will evaluate the impact of the overall program as well as two experiments that focus on the impact of the cash transfers and the caseworker mentoring scheme. Baseline data was collected for the FNLP starting in May 2015.","coll_dates":[{"start":"2015-05-01","end":"2015-06-01","cycle":"Baseline"}],"nation":[{"name":"Nigeria","abbreviation":"NGA"}],"geog_coverage":"The impact evaluation was conducted in Kebbi state in two Local Government Authorities (LGAs) Birnin Kebbi and Danko Wasagu across eight wards: Ujariyo\/Junju, Lagga\/Randalli, Kardi, Makera\/Maurida, Kanya, Ribah\/Waje, Maga\/Kyabu and Danko.","analysis_unit":"-  Households","universe":"Households in both FNLP villages and villages not receiving FNLP services but are part of the control group for the impact evaluation.","data_kind":"Sample survey data [ssd]","notes":"The scope of Feed the Future Nigeria Livelihoods Project (FNLP) includes:\n\n-  HOUSEHOLD: Household roster and demographics, Labor, Non-farm enterprises, Credit and savings, Household and agriculture assets, Housing, Food consumption and expenditure, Non-food expenditure, Food security, Safety nets, Economic shocks, Health, Risk aversion, Hyperbolic discounting, Aspirations and Women's survey.\n\n-  AGRICULTURE:  Plot roster, Land inventory, Agricultural labor, Field crops and seed acquisition, Crop disposition, Animal holdings and costs, Agriculture by-product and Extension services."},"method":{"data_collection":{"sampling_procedure":"To determine which areas within Kebbi State would benefit from the FNLP program and to establish a sample of vulnerable households that will be part of the program and impact evaluation, CRS and GIL identified eligible communities and households in Kebbi using a number of steps. Detailed explanations of each stage in the process are provided in the baseline report (Attached in the Related Materials).\n\nFor the Impact Evaluation baseline survey, a sample of 2,400 EV households and 1,100 households equally divided between the VV and ML households was necessary based on power calculations. We sampled 2,074 of the \u2018Class B\u2019 households in FNLP treatment villages and 2,254 from FNLP control villages and sent this sample of 4,328 households to the survey firm to conduct a baseline survey.","coll_mode":"Computer Assisted Personal Interview [capi]","research_instrument":"For the baseline survey, three instruments were used for data collection:\n\n1. Household questionnaire: The household questionnaire was administered to all households in the sample and collected demographic characteristics for all household members, information on dwelling characteristics, household consumption expenditures, household asset holdings, aspirations, exposure to shocks, and level of participation in safety net programs. In addition, individual-level questions around food security, risk aversion, and time preferences were asked to both the male and female decision-makers in the households.\n\n2. Women\u2019 questionnaire: Women were also asked to respond to a separate Women\u2019s Survey that had questions based on the Women\u2019s Empowerment in Agriculture Index (WEAI).\n\n3. Agricultural questionnaire: An agriculture questionnaire was administered to all households engaged in agricultural activities such as crop farming, livestock rearing and other agricultural and related activities. The instrument asked questions on land holdings, agriculture production, sales, agricultural income and level of participation in extension services programs. Plot-level information was collected from the male and female decision-makers in the households who were the target respondents for this questionnaire.\n\n4. Community questionnaire: A community questionnaire was administered to each village to collect information on the socio-economic indicators of the village communities where the sampled households reside. The community questionnaire collected information on basic characteristics of the community such as location, size, distance to larger towns and markets, and availability of and distance to sources of health services and schools. Data was collected from 5-10 community members during the Household Targeting Committee meetings.","coll_situation":"Although data collection was originally planned to begin in February, restrictions related to Federal and State elections throughout Nigeria led to the survey and the program implementation being delayed. The data collection finally started on May 4th in Birnin Kebbi and continued to Danko Wasagu concluding on June 16th 2015.\n\nSince the households interviewed during the baseline survey were selected from the PPI database, some of the supervisors and interviewers had already visited the locality prior to the baseline data collection and locating households was easier as a result.\n\nThe male and female decision-makers in the household completed the survey together unless there was only one decision-maker in the household. The respondents are those which are self-identified as the primary male and female members responsible for the decision making, both social and economic decisions mainly related to agriculture, within the household. If only one of these people were available at the time of the first visit, interviewers would complete the sections relevant to them and a second visit would be rescheduled for when the other was in attendance to complete the survey.\n\nThe questionnaires were administered in face-to-face interviews in the respondents\u2019 home, using tablet computers. Many of the female respondents in Kebbi were not permitted to come out of their homes to answer questions; in such cases, female interviewers were permitted access to their homes. The field teams worked to ensure that this challenge was minimized by having enough female interviewers as part of each team.\n\nIn some cases, power failure due to the hot and dry climate increased the duration of the interview by one to two hours. In such cases, the interviewers were encouraged to conduct the interviews in shaded areas away from direct sunlight when interviewing respondents in an effort to preclude such adverse outcomes. Some interviews were also conducted in the early morning or late afternoon to mitigate this challenge. In addition, power banks and paper questionnaires were employed in cases where power was an issue.\n\nTNS-RMS worked with CRS to ensure that the baseline data collection activities were completed before program implementation began. This was a concern because the program needed to start before the start of planting season, which varied across the sample by location and crop mix.","act_min":"8 supervisors for the baseline survey.","cleaning_operations":"Data quality was ensured at several levels. At the tablet level, the questionnaire was programmed so that questions or sections could not be skipped by interviewers. Numerous quality checks were also built into the programming that identified inconsistencies and prevented interviewers from moving forward with the survey until errors were corrected. Logic checks and range checks were also included in the programming so that implausible entries were flagged to the interviewer at the time of surveying.\n\nMonitoring of data collection activities was also conducted by several people. Supervisors monitored interviewer performance by observing interviews and conducting spot checks that consisted of assessing whether questions were being asked appropriately and providing immediate feedback to interviewers. The World Bank\u2019s Project Manager and Field Coordinator also provided another layer of quality control, visiting each interviewer team at least twice each week to observe interviews and review household listings.\n\nA final level of data quality control involved the use of quality control reports that were automatically generated using a quality-check file created by the research team at the World Bank. The file would scan the data for possible errors or large outliers as soon as data was downloaded from the server. The types of checks the file would make included the following: whether the household identifiers were unique within the dataset, whether interviews were being completed in their entirety, reviewing observations with duplicate values of a variable for which duplicates are uncommon, checking that no variables have only missing values, checking important skip patterns, range checks and interviewer comments. This helped with data accuracy as the report was reviewed at least every week by the research team throughout the data collection period and any errors could be sent back to the field team and rectified in real time while the data collection was still taking place."},"analysis_info":{"response_rate":"The number of household interviews completed was 3,976 for a household response rate of 92 percent."}},"data_access":{"dataset_use":{"cit_req":"The use of the datasets must be acknowledged using a citation which would include:\n- the identification of the Primary Investigator (including country name);\n- the full title of the survey and its acronym (when available), and the year(s) of implementation;\n- the survey reference number;\n- the source and date of download (for datasets disseminated online).\n\nExample:\n\nGautam Bastian, Sreelakshmi Papineni, World Bank. Nigeria - Feed the Future Nigeria Livelihoods Project 2015, Baseline Survey. Ref. NGA_2015_FNLP-BL_v01_M. Dataset downloaded from [URL] on [date].","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":"DOI"}]}