General Household Survey, Panel 2023-2024
Wave 5
Nigeria, 2023 - 2024
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NGA_2023_GHSP-W5_v01_M
General Household Survey, Panel 2023-2024
Wave 5
GHS-Panel Wave 5 2023-24
| Name | Country code |
|---|---|
| Nigeria | NGA |
Living Standards Measurement Study [hh/lsms]
The Nigeria General Household Survey panel component (GHS-Panel) is part of a larger, regional project in Sub-Saharan Africa. The GHS-Panel is the result of a partnership that the NBS has established with the Bill and Melinda Gates Foundation (BMGF) and the World Bank (WB). The ability to follow the same households over time makes the GHS-Panel a powerful tool for studying and understanding income generating activities and socio-economic outcomes in Nigeria. The GHS-Panel is the first panel survey to be carried out by NBS.
The 2023/24 GHS-Panel is the fifth round of the survey with prior rounds conducted in 2010/11, 2012/13, 2015/16, and 2018/19.
The General Household Survey-Panel (GHS-Panel) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program. The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, interinstitutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of approximately 5,000 households, which are also representative of the six geopolitical zones. The 2023/24 GHS-Panel is the fifth round of the survey with prior rounds conducted in 2010/11, 2012/13, 2015/16 and 2018/19. The GHS-Panel households were visited twice: during post-planting period (July - September 2023) and during post-harvest period (January - March 2024).
Sample survey data [ssd]
• Households
• Individuals
• Agricultural plots
• Communities
Version
Version 01: Edited, anonymized dataset for public distribution
Scope
The 2023-2024 Nigeria General Household Survey - Panel (GHS-Panel, Wave 5) covered the following topics:
HOUSEHOLD
• Household identification including geographic area identification information
• Household Roster
• Migration in the Last 12 Months
• Migration in the Past 10 Years
• Absentee Roster (Non-Household Members)
• Migration Aspirations
• Remittances
• Health
• Labour
• Work Activities in the Last 12 Months
• Savings and Insurance
• ICT – Mobile Phone Banking
• Credit
• Meals Away from Home
• Food Consumption and Expenditure
• Aggregate Food Consumption
• Non-food Expenditure
• Petrol
• Food Security
• Household Assets
• Other Household Income
• Education
• Early Child Development
• Childcare
• Subjective Skills
• Time Use
• Dietary Diversity
• Anthropometry
• Non-farm Enterprises
• Housing
• Food Consumption Shocks
• Safety Nets
• Economic Shocks
AGRICULTULRE
• Household identification including geographic area identification information
• Plot Roster
• Land Inventory
• Household Labour
• Hired and Exchange Labour
• Seed Acquisition
• Planted Crops
• Animal Holdings
• Animal Costs
• Animal Power and Dung
• Milk Production
• Egg Production
• Extension Services
• Extension Sources
• Digital Farming Information
• Input Use on Plot
• Input Acquisition
• Field Crop Harvest
• Crop Disposition
• Tree and Permanent Crop Harvest
• Post-Harvest Labour - Household
• Post-Harvest Labour – Hired and Exchange
• Agricultural Capital
COMMUNITY
• Community Identification
• Respondents Characteristics
• Food Prices
• Labour
• Land Prices and Credit
• Community Infrastructure and Transportation
• Community Organizations
• Community Resource Management
• Social Norms
• Community Changes
• Community Key Events
• Community Needs, Actions, and Achievements
• Expectations on Climate Extremes and Past Experience
Coverage
National
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Producers and sponsors
| Name | Affiliation |
|---|---|
| National Bureau of Statistics (NBS) | Federal Government of Nigeria |
| Name | Role |
|---|---|
| The World Bank | Collaborated in the implementation of the survey |
| Name | Abbreviation | Role |
|---|---|---|
| Bill and Melinda Gates Foundation | BMGF | Funded the study |
| Federal Government of Nigeria | Govt NGA | Funded the study |
| The World Bank | WB | Funded the study |
Sampling
The original GHS‑Panel sample was fully integrated with the 2010 GHS sample. The GHS sample consisted of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs), chosen from each of the 37 states in Nigeria. This resulted in a total of 2,220 EAs nationally. Each EA contributed 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,200 households, 5,000 households from 500 EAs were selected for the panel component, and 4,916 households completed their interviews in the first wave.
After nearly a decade of visiting the same households, a partial refresh of the GHS‑Panel sample was implemented in Wave 4 and maintained for Wave 5. The refresh was conducted to maintain the integrity and representativeness of the sample. The refresh EAs were selected from the same sampling frame as the original GHS‑Panel sample in 2010. A listing of households was conducted in the 360 EAs, and 10 households were randomly selected in each EA, resulting in a total refresh sample of approximately 3,600 households.
In addition to these 3,600 refresh households, a subsample of the original 5,000 GHS‑Panel households from 2010 were selected to be included in the new sample. This “long panel” sample of 1,590 households was designed to be nationally representative to enable continued longitudinal analysis for the sample going back to 2010. The long panel sample consisted of 159 EAs systematically selected across Nigeria’s six geopolitical zones.
The combined sample of refresh and long panel EAs in Wave 5 that were eligible for inclusion consisted of 518 EAs based on the EAs selected in Wave 4. The combined sample generally maintains both the national and zonal representativeness of the original GHS‑Panel sample.
Although 518 EAs were identified for the post-planting visit, conflict events prevented interviewers from visiting eight EAs in the North West zone of the country. The EAs were located in the states of Zamfara, Katsina, Kebbi and Sokoto. Therefore, the final number of EAs visited both post-planting and post-harvest comprised 157 long panel EAs and 354 refresh EAs. The combined sample is also roughly equally distributed across the six geopolitical zones.
Since Wave 1, every effort has been made to track and interview households that had moved away from their original EA and keep attrition to a minimum. These efforts continued in Wave 5, particularly for the long panel sample. Households that had moved away from their previous location were interviewed in a separate tracking phase following both the post-planting and post-harvest visits. Of the 1,590 households interviewed in Wave 1 within these 159 EAs, 1,376 households were successfully interviewed in both visits of Wave 5. This implies an overall attrition rate since 2010 across these EAs of 13.5 percent. However, attrition is highly variable across zones and sectors. The highest attrition was found in rural EAs in South West (28.8 percent) and the lowest attrition in rural EAs in North Central (5.3 percent). Attrition was also higher among urban (17.8 percent) than rural (11.4 percent) households. Overall, 168 long panel households had moved and were interviewed in their new location (over 10 percent of the sample). The highest number of households that had moved was in the urban area in South West (47 households, accounting for 25.7 percent of the sample).
As with any probability sample survey, sampling weights must be calculated and applied to produce estimates that are representative of the survey domains. The weights primarily reflect the inverse probability of inclusion of the interviewed households into the sample with adjustments to account for nonresponse/attrition and calibration to auxiliary data on population estimates. This section describes the different sets of weights calculated and included in the GHS-Panel wave 5 data. Three different weights were prepared for wave 5 of the GHS-Panel reflecting different subsamples and tailored to specific analytical objectives.
As described above, there are two main components of the wave 5 sample: the refresh and the long panel samples. The long panel sample is intended to be analysed independently since it constitutes a panel of households that extends back to wave 1. It therefore needs a dedicated weight. The other analytical sample considered for the GHS-Panel is the pooled or combined sample of longitudinal households and refresh households. The pooled sample will also of course need a separate weight.
In addition to the analytical samples, different weights are provided which are tailored to cross-sectional and longitudinal analysis using the GHS-Panel wave 5 data. While the GHS-Panel is primarily designed as a longitudinal survey and thus with longitudinal analysis as the primary goal, the survey could also provide valuable cross-sectional insights. Separate weights are provided which attempt to satisfy these two objectives
Thus, the three different sets of weights calculated and included in the GHS-Panel are:
- Longitudinal weights to be applied to the long panel sample: used for analysis that seeks to track dynamics within long panel households across the 5 waves of the GHS-Panel
- Longitudinal weights to be applied to the combined sample: used for analysis that seeks to track dynamics within all wave 5 households (long panel + refresh) between waves 4 and 5
- Cross-sectional weights to be applied to the combined sample: used for analysis that seeks to provide representative estimates of the current population of Nigerian households at the time of wave 5 (2023/24).
Slightly different though closely related approaches were applied to calculate these three different weights. When calculating all three weights, only households successfully interviewed in both visits of wave 5 were considered.
The longitudinal weights for both the long panel and combined samples were constructed in the following stages:
-
The original weights calculated in wave 4 for each sample served as the base weights
-
An adjustment was performed to attempt to correct for and limit any attrition or nonresponse bias between wave 4 and wave 5. The adjustment was performed via a modelled response propensity using a logit model:
ln[(p(x_i))/(1-p(x_i))]= a+ ß_1 X_i
where p(x_i) is the probability that household i was selected for the long-panel sample and successfully interviewed and X_i is a vast set of household characteristics from wave 1 which are potentially correlated with the probability of response . For the long panel sample, characteristics observed in wave 1 were used in the response propensity model while for the combined sample characteristics from wave 4 were used. Following estimation of the logit model, the predicted probability of each household being interviewed, p ^(x_i ), is derived using the model parameters. In principle, the inverse of the predicted probability could serve as the adjustment factor applied to the weights. However, in practice the unit-level inverse predicted probability is not taken as the adjustment factor, but rather the units are sorted into response (i.e., coverage) classes and the adjustment applied uniformly within those response classes . Response classes were created according to the decile of predicted probability (i.e., 10 classes) within each Zone and applied a conversion factor that takes the ratio of the sum of base weights for all targeted households over the sum of base weighs for the successfully interviewed households. The adjustment factor is then applied to the base weights to arrive at the adjusted weight.
-
The weights were calibrated to reflect the distribution of the target population. For both the long panel and combined samples, the longitudinal weights were calibrated to (1) reflect the total number of households in each Zone in 2010 (i.e. during the first wave of the GHS-Panel).
-
Lastly, for the combine sample, outlier weights were truncated applying lower and upper bounds that correspond to the maximum and minimum values of the wave 4 weights (while also maintaining the calibrated parameters in step 3). No trimming was deemed necessary for the longitudinal long panel weights.
The cross-sectional weights were constructed in three stages:
- The original weights calculated in wave 4 for the combined sample served as the base weights
- The base weights were then adjusted for non-response using the same response propensity modelling approach described above for the longitudinal weights.
- The weights were calibrated to reflect the distribution of the underlying population at the time of the wave 5 survey. Official population projections for 2023 were used as calibration constraints reflecting the individual population of males and females in each state. The population estimates used are displayed in Table 3.2.1 of the Basic Information Document.
All three weights can be found in the cover page data files for both the post-planting (secta_plantingw5.dta) and post-harvest (secta_harvestw5.dta). The variable names in both data files are wt_wave5 for the longitudinal weights applied to the combined samples, wt_longpanel_wave5 for the long-panel longitudinal weights, and wt_cross_wave5 for the cross-sectional weights.
Survey instrument
The GHS-Panel Wave 5 consisted of three questionnaires for each of the two visits. The Household Questionnaire was administered to all households in the sample. The Agriculture Questionnaire was administered to all households engaged in agricultural activities such as crop farming, livestock rearing, and other agricultural and related activities. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.
GHS-Panel Household Questionnaire: The Household Questionnaire provided information on demographics; education; health; labour; childcare; early child development; food and non-food expenditure; household nonfarm enterprises; food security and shocks; safety nets; housing conditions; assets; information and communication technology; economic shocks; and other sources of household income. Household location was geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets (forthcoming).
GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicited information on land ownership and use; farm labour; inputs use; GPS land area measurement and coordinates of household plots; agricultural capital; irrigation; crop harvest and utilization; animal holdings and costs; household fishing activities; and digital farming information. Some information is collected at the crop level to allow for detailed analysis for individual crops.
GHS-Panel Community Questionnaire: The Community Questionnaire solicited information on access to infrastructure and transportation; community organizations; resource management; changes in the community; key events; community needs, actions, and achievements; social norms; and local retail price information.
The Household Questionnaire was slightly different for the two visits. Some information was collected only in the post-planting visit, some only in the post-harvest visit, and some in both visits.
The Agriculture Questionnaire collected different information during each visit, but for the same plots and crops.
The Community Questionnaire collected prices during both visits, and different community level information during the two visits.
Data collection
| Start | End | Cycle |
|---|---|---|
| 2023-07 | 2023-09 | Post-Planting |
| 2024-01 | 2024-03 | Post-Harvest |
- Computer Assisted Personal Interview [capi]
| Name | Affiliation | Abbreviation |
|---|---|---|
| National Bureau of Statistics | Federal Government of Nigeria | NBS |
ORGANIZATION OF FIELDWORK: Data were collected by teams consisting of a supervisor and between 2 to 5 interviewers. The number of teams varied from state to state depending on the number of EAs identified using Wave 4 data. The teams moved in a roving manner and data collection lasted for between 20 – 30 days for each of the post-planting and post-harvest visits.
The GHS-Panel Wave 5 was administered in two visits: post-planting (July - September 2023) and post-harvest (January – March 2024). A tracking phase was conducted after both visits in October-November 2023 and April-May 2024 to interview long panel households that had moved from their location in the previous visit (Wave 4 post-harvest) or any household that had moved between the post-planting and post-harvest visits in Wave 5.
Among the GHS-Panel Wave 5 enumeration areas (EAs), 106 EAs were selected to participate in a mixed-mode study for measuring agricultural labor and inputs. This study targeted 937 households in these randomly selected agricultural/rural EAs in Nigeria. Phones and sim cards were distributed to these households during the post-planting visit. The households that agreed to participate in the study were called each month (4 rounds of phone calls in total) and information about the inputs use of up to three plots were collected in each call using the days since the last completed interview as a reference period. During the post-harvest, the reference period used for the targeted households was the last completed interview (including the monthly phone calls received in between the post-planting and post-harvest visit) in the modules (A2a) Household on-plot labour, (A2b) Hired on-plot labour, and (11c2) Input use in plots. Additional files will be included as part of the GHS-Panel data that include the data collected for these modules during the 4 rounds of phone calls.
GIFTS TO HOUSEHOLD: As a show of appreciation for the panel households’ continued participation, all households that were located, were given a gift (even if they refused to participate). Gifts were given during both the post-planting and post-harvest visits and consisted of different types of food flask (container for storing food). Additionally, the gifts (food flasks) were presented to the Community leader and their deputy to show appreciation for their participation to the community survey as well as for facilitating the interviews with the households within their community. Recipients were very appreciative of the gifts and in many cases were essential to ensure continued participation in the panel.
PRE-LOADED INFORMATION: Basic information on every household was pre-loaded in the CAPI assignments for each interviewer. The information was pre-loaded to (1) assist interviewers in locating and identifying the household and (2) ensure that each pre-loaded unit (person, plot, etc.) is properly addressed and easily matched to previous visits. Basic household information (location, household head name, phone number, etc.) was pre-loaded in both visits for all households.
In addition, in the post-planting visit, the list of individuals from Wave 4 and their basic characteristics were uploaded for households. This helped maintain the panel of individuals and ensure the status of each individual was confirmed in Wave 4. In the post-harvest visit, several information was pre-loaded that was collected in the post-planting visit. This included (1) the list of individuals and their basic characteristics, (2) the list of plots of land and their basic characteristics and (3) the list of crops cultivated on each plot of land.
FIELDWORK MONITORING AND EVALUATION: As an additional aid to ensuring good quality data, extensive monitoring was done of the field work. There were three levels of monitoring and evaluation. The first level of monitoring followed immediately after the zonal training. One (1) monitor was assigned to 2 states and all states were covered, including Federal Capital Authority, Abuja (FCT, Abuja). This monitoring was carried out by the technical team from the zonal training (i.e. the trainers) which included individuals from the Head Office of NBS. The second monitoring was carried out by NBS state officers and zonal controllers and took place over an extended period during the fieldwork. The third and final monitoring took place no later than a week before the end of fieldwork. The team involved in the third monitoring was selected from the team that carried out the first monitoring.
During first and second monitoring, the monitors made sure that proper compliance with the procedures as contained in the manual were followed, effected necessary corrections and tackled problems that arose. Where problems were found, these were corrected either directly or through a revisit to the household for verification of information or for further information.
Data processing
CAPI: Wave five exercise was conducted using Computer Assisted Person Interview (CAPI) techniques. All the questionnaires (household, agriculture, and community questionnaires) were implemented in both the post-planting and post-harvest visits of Wave 5 using the CAPI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Living Standards Measurement Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given a tablet which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CAPI was highly successful, as it allowed for timely availability of the data from completed interviews.
DATA COMMUNICATION SYSTEM: The data communication system used in Wave 5 was highly automated. Each field team was given a mobile modem which allowed for internet connectivity and daily synchronization of their tablets. This ensured that head office in Abuja had access to the data in real-time. Once the interview was completed and uploaded to the server, the data was first reviewed by the Data Editors. The data was also downloaded from the server, and Stata dofile was run on the downloaded data to check for additional errors that were not captured by the Survey Solutions application. An excel error file was generated following the running of the Stata dofile on the raw dataset. Information contained in the excel error files were then communicated back to respective field interviewers for their action. This monitoring activity was done on a daily basis throughout the duration of the survey, both in the post-planting and post-harvest.
DATA CLEANING: The data cleaning process was done in three main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork.
The second stage cleaning involved the use of Data Editors and Data Assistants (Headquarters in Survey Solutions). As indicated above, once the interview is completed and uploaded to the server, the Data Editors review completed interview for inconsistencies and extreme values. Depending on the outcome, they can either approve or reject the case. If rejected, the case goes back to the respective interviewer’s tablet upon synchronization. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences, these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. Additional errors observed were compiled into error reports that were regularly sent to the teams. These errors were then corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then approved by the Data Editor. After the Data Editor’s approval of the interview on Survey Solutions server, the Headquarters also reviews and depending on the outcome, can either reject or approve.
The third stage of cleaning involved a comprehensive review of the final raw data following the first and second stage cleaning. Every variable was examined individually for (1) consistency with other sections and variables, (2) out of range responses, and (3) outliers. However, special care was taken to avoid making strong assumptions when resolving potential errors. Some minor errors remain in the data where the diagnosis and/or solution were unclear to the data cleaning team.
Data Access
Before being granted access to the dataset, all users have to formally agree:
- To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor.
- Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
- To 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 data depositor.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
National Bureau of Statistics. Nigeria General Household Survey, Panel (GHS-Panel) Wave 5 2023-2024. Dataset downloaded from [source] 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.
Contacts
| Name | Affiliation | |
|---|---|---|
| Biyi Fafunmi, Director, Agriculture and Business Enterprises Statistics Department | National Bureau of Statistics | biyifafunmi@nigerianstat.gov.ng |
| LSMS Data Manager | The World Bank | lsms@worldbank.org |
Metadata production
DDI_NGA_2023_GHSP-W5_v01_M
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
2024-11-18
Metadata version
Version 01 (November 2024)