Feed the Future Nigeria Livelihoods Project 2015, Baseline Survey
Impact Evaluation Survey
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’s 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).
This 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.
The impact evaluation, led by The World Bank’s 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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- v01, edited anonymous datasets for public distribution.
Variables related to names, phone numbers, addresses and emails of respondents and GPS coordinates were anonymized.
The scope of Feed the Future Nigeria Livelihoods Project (FNLP) includes:
- 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.
- AGRICULTURE: Plot roster, Land inventory, Agricultural labor, Field crops and seed acquisition, Crop disposition, Animal holdings and costs, Agriculture by-product and Extension services.
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.
Households in both FNLP villages and villages not receiving FNLP services but are part of the control group for the impact evaluation.
Producers and sponsors
The World Bank
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).
For 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 ‘Class B’ 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.
The number of household interviews completed was 3,976 for a household response rate of 92 percent.
Dates of Data Collection
Data Collection Mode
Computer Assisted Personal Interview [capi]
8 supervisors for the baseline survey.
Data Collection Notes
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.
Since 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.
The 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.
The questionnaires were administered in face-to-face interviews in the respondents’ 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.
In 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.
TNS-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.
For the baseline survey, three instruments were used for data collection:
1. 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.
2. Women’ questionnaire: Women were also asked to respond to a separate Women’s Survey that had questions based on the Women’s Empowerment in Agriculture Index (WEAI).
3. 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.
4. 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.
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.
Monitoring 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’s 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.
A 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.
The use of the datasets must be acknowledged using a citation which would include:
- the identification of the Primary Investigator (including country name);
- the full title of the survey and its acronym (when available), and the year(s) of implementation;
- the survey reference number;
- the source and date of download (for datasets disseminated online).
Gautam 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 and copyrights
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.
DDI Document ID
Development Economics Data Group
The World Bank
Documentation of the DDI
Date of Metadata Production
DDI Document version
Version 01 (August 2017).