Facebook
TwitterThe 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).
National
• Households • Individuals • Agricultural plots • Communities
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Sample survey data [ssd]
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.
Computer Assisted Personal Interview [capi]
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.
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.
Response
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Households and NPISHs Final consumption expenditure (annual % growth) in Nigeria was reported at 25.62 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Household final consumption expenditure (annual % growth) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.
Facebook
Twitterhttps://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Price Level of Household Consumption for Nigeria (PLCCPPNGA670NRUG) from 1950 to 2019 about Nigeria, consumption, households, and price.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Actual value and historical data chart for Nigeria Household Final Consumption Expenditure Current Us$
Facebook
TwitterPanel data possess several advantages over conventional cross-sectional and time-series data, including their power to isolate the effects of specific actions, treatments, and general policies often at the core of large-scale econometric development studies. While the concept of panel data alone provides the capacity for modeling the complexities of human behavior, the notion of universal panel data – in which time- and situation-driven variances leading to variations in tools, and thus results, are mitigated – can further enhance exploitation of the richness of panel information.
The Basic Information Document (BID) provides a brief overview of the Nigerian General Household Survey (GHS) but focuses primarily on the theoretical development and application of panel data, as well as key elements of the universal panel survey instrument and datasets generated by the four rounds of the GHS. As the BID does not describe in detail the background, development, or use of the GHS itself, the wave-specific GHS BIDs should supplement the information provided here.
The Nigeria Universal Panel Data (NUPD) consists of both survey instruments and datasets from the two survey visits of the GHS - Post-Planting (PP) and Post-Harvest (PH) - meticulously aligned and engineered with the aim of facilitating the use of and improving access to the wealth of panel data offered by the GHS. The NUPD provides a consistent and straightforward means of conducting user-driven analyses using convenient, standardized tools.
The design of the NUPD combines the four completed Waves of the GHS Household Post-Planting and Post-Harvest Surveys – Wave 1 (2010/11), Wave 2 (2012/13), Wave 3 (2015/16), and Wave 4 (2018/19) – into pooled, module-specific survey instruments and datasets. The panel survey instruments offer the ease of comparability over time, with modifications and variances easily identifiable as well as those aspects of the questionnaire which have remained identical and offer consistent information. By providing all module-specific data over time within compact, pooled datasets, panel datasets eliminate the need for user-generated merges between rounds and present data in a clear, logical format, increasing both the usability and comprehension of complex data.
National
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Sample survey data [ssd]
Please see the GHS BIDs for each round for detailed descriptions of the sample design used in each round and their respective implementation efforts as this is a compilation of datasets from all previous waves.
Face-to-face [f2f]
The larger GHS-Panel project consists of three questionnaires (Household Questionnaire, Agriculture Questionnaire, Community Questionnaire) for each of the two visits (Post-Planting and Post-Harvest). The GHS-NUPD only consists of the Household Questionnaire.
GHS-Panel Household Questionnaire: The Household Questionnaire provides information on demographics; education; health (including anthropometric measurement for children); labor; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; and other sources of household income.
The Household Questionnaire is 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.
Please see the GHS BIDs for each round for detailed descriptions of data editing and additional data processing efforts as this is a compilation of datasets from all previous waves.
Facebook
TwitterBased on a survey conducted in 2023, the majority of Nigerians paid between 1,000 and ***** Nigerian naira (**** U.S. dollars and **** U.S. dollars) monthly for their household's electricity consumption. Around ** percent of men and ** percent of women reported paying an amount within that pay band. Furthermore, the share of people generally decreased as the price increased, while around a fifth of the women claimed they did not know or refused to answer compared to ** percent for men.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Nigeria NG: Female Headed Households data was reported at 14.600 % in 2015. This records a decrease from the previous number of 18.500 % for 2013. Nigeria NG: Female Headed Households data is updated yearly, averaging 16.600 % from Dec 1990 (Median) to 2015, with 7 observations. The data reached an all-time high of 19.300 % in 2008 and a record low of 14.300 % in 1990. Nigeria NG: Female Headed Households data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Population and Urbanization Statistics. Female headed households shows the percentage of households with a female head.; ; Demographic and Health Surveys.; ; The composition of a household plays a role in the determining other characteristics of a household, such as how many children are sent to school and the distribution of family income.
Facebook
TwitterRetirement Notice: This item is in mature support as of November 2025 and will be retired in December 2026. A replacement item has not been identified at this time. Esri recommends updating your maps and apps to phase out use of this item. This layer shows the average household size in Nigeria in 2023, in a multiscale map (Country, State, and Local Government Area). Nationally, the average household size is 4.5 people per household. It is calculated by dividing the household population by total households.The pop-up is configured to show the following information at each geography level:Average household size (people per household)Total populationTotal householdsCount of population by 15-year age increments The source of this data is Michael Bauer Research. The vintage of the data is 2023. This item was last updated in October, 2023 and is updated every 12-18 months as new annual figures are offered.Additional Esri Resources:Esri DemographicsThis item is for visualization purposes only and cannot be exported or used in analysis.We would love to hear from you. If you have any feedback regarding this item or Esri Demographics, please let us know.Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.
Facebook
TwitterThe 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 2018/19 is the fourth round of the survey with prior rounds conducted in 2010/11, 2012/13, and 2015/16. GHS-Panel households were visited twice: first after the planting season (post-planting) between July and September 2018 and second after the harvest season (post-harvest) between January and February 2019.
National
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Sample survey data [ssd]
The original GHS-Panel sample of 5,000 households across 500 enumeration areas (EAs) and was designed to be representative at the national level as well as at the zonal level. The complete sampling information for the GHS-Panel is described in the Basic Information Document for GHS-Panel 2010/2011. However, after a nearly a decade of visiting the same households, a partial refresh of the GHS-Panel sample was implemented in Wave 4.
For the partial refresh of the sample, a new set of 360 EAs were randomly selected which consisted of 60 EAs per zone. The refresh EAs were selected from the same sampling frame as the original GHS-Panel sample in 2010 (the “master frame”). A listing of all households was conducted in the 360 EAs and 10 households were randomly selected in each EA, resulting in a total refresh sample of approximated 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 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 the 6 geopolitical Zones. The systematic selection ensured that the distribution of EAs across the 6 Zones (and urban and rural areas within) is proportional to the original GHS-Panel sample. Interviewers attempted to interview all households that originally resided in the 159 EAs and were successfully interviewed in the previous visit in 2016. This includes households that had moved away from their original location in 2010. In all, interviewers attempted to interview 1,507 households from the original panel sample.
The combined sample of refresh and long panel EAs consisted of 519 EAs. The total number of households that were successfully interviewed in both visits was 4,976.
While the combined sample generally maintains both national and Zonal representativeness of the original GHS-Panel sample, the security situation in the North East of Nigeria prevented full coverage of the Zone. Due to security concerns, rural areas of Borno state were fully excluded from the refresh sample and some inaccessible urban areas were also excluded. Security concerns also prevented interviewers from visiting some communities in other parts of the country where conflict events were occurring. Refresh EAs that could not be accessed were replaced with another randomly selected EA in the Zone so as not to compromise the sample size. As a result, the combined sample is representative of areas of Nigeria that were accessible during 2018/19. The sample will not reflect conditions in areas that were undergoing conflict during that period. This compromise was necessary to ensure the safety of interviewers.
Computer Assisted Personal Interview [capi]
The GHS-Panel Wave 4 consists 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 provides information on demographics; education; health (including anthropometric measurement for children); labor; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; and other sources of household income. Household location is geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets.
GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicits information on land ownership and use; farm labor; inputs use; GPS land area measurement and coordinates of household plots; agricultural capital; irrigation; crop harvest and utilization; animal holdings and costs; and household fishing activities. Some information is collected at the crop level to allow for detailed analysis for individual crops.
GHS-Panel Community Questionnaire: The Community Questionnaire solicits information on access to infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.
The Household Questionnaire is 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 collects different information during each visit, but for the same plots and crops.
CAPI: For the first time in GHS-Panel, the Wave four 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 4 using the CAPI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Survey Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given tablets 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 4 was highly automated. Each field team was given a mobile modem allow for internet connectivity and daily synchronization of their tablet. This ensured that head office in Abuja has access to the data in real-time. Once the interview is completed and uploaded to the server, the data is first reviewed by the Data Editors. The data is 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 is generated following the running of the Stata dofile on the raw dataset. Information contained in the excel error files are communicated back to respective field interviewers for action by the interviewers. This action is 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
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Household consumption, billion currency units in Nigeria, December, 2023 The most recent value is 37757.62 billion Nigerian Naira as of Q4 2023, a decline compared to the previous value of 41828.45 billion Nigerian Naira. Historically, the average for Nigeria from Q1 2010 to Q4 2023 is 21168.48 billion Nigerian Naira. The minimum of 7896.9 billion Nigerian Naira was recorded in Q2 2010, while the maximum of 41828.45 billion Nigerian Naira was reached in Q3 2023. | TheGlobalEconomy.com
Facebook
TwitterAs of 2023, most respondents in all regions in Nigeria (except in North East) reported spending between 1,000 and ***** Nigerian naira (around **** U.S. dollars and **** U.S. dollars) for electricity each month. For the North East geo-political zone, the majority (** percent) disclosed that they paid between ***** and 10,000 Nigerian naira (**** U.S. dollars and ***** U.S. dollars). Furthermore, the South South had the highest share (***** percent) among the regions claiming to pay over ****** Nigerian naira (***** U.S. dollars).
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Nigeria NG: GDP: PPP: Household Final Consumption Expenditure data was reported at 676,669.931 Intl $ mn in 2016. This records a decrease from the previous number of 690,971.866 Intl $ mn for 2015. Nigeria NG: GDP: PPP: Household Final Consumption Expenditure data is updated yearly, averaging 175,681.317 Intl $ mn from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 690,971.866 Intl $ mn in 2015 and a record low of 57,063.655 Intl $ mn in 1994. Nigeria NG: GDP: PPP: Household Final Consumption Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Gross Domestic Product: Purchasing Power Parity. Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. Data are converted to current international dollars using purchasing power parity rates based on the 2011 ICP round.; ; World Bank, International Comparison Program database.; Gap-filled total;
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Actual value and historical data chart for Nigeria Household Final Consumption Expenditure Per Capita Growth Annual Percent
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The GHS-Panel is a longitudinal subsample of the GHS survey, a cross-sectional survey of 22,000 households carried out annually in Nigeria. The GHS-Panel collects data on around 5,000 households across all 36 states of Nigeria. It aims to supplement GHS data with information about the agricultural sector and link this to other facets of household characteristics. Baseline data collection (wave 1) took place from 2010 to 2011, wave 2 from 2012 to 2013, wave 3 from 2015 to 2016, wave 4 from 2018 to 2019 and wave 5 from 2023 to 2024. Each wave includes interviews at two time-points: during the post-planting period (July to September) and during the post-harvest period (January to March the following year).
Facebook
TwitterNational
Sample survey data [ssd]
Face-to-face [f2f]
Facebook
TwitterIn 2018, Nigerian households counted on average *** members. Large households with ***** members or more held about ** percent of the share, while some ** percent of all households in the country had *** or less individuals.
Facebook
TwitterIn the past decades, Nigeria has experienced substantial gaps in producing adequate and timely data to inform policy making. In particular, the country is lagging behind in producing sufficient and accurate agricultural production statistics. The current set of household and farm surveys conducted by the NBS covers a wide range of sectors. Except for the Harmonized National Living Standard Survey (HNLSS) which covers multiple topics, these different sectors are usually covered in separate surveys none of which is conducted as a panel. As part of the efforts to continue to improve data collection and usability, the NBS has revised the content of the annual General household survey (GHS) and added a panel component. The GHS-Panel is conducted every 2 years covering multiple sectors with a focus to improve data from the agriculture sector.
The Nigeria General Hosehold Survey-Panel, is the result of a partnership that NBS has established with the Federal Ministry of Agriculture and Rural Development (FMARD), the National Food Reserve Agency (NFRA), the Bill and Melinda Gates Foundation (BMGF) and the World Bank (WB). Under this partnership, a method to collect agricultural and household data in such a way as to allow the study of agriculture's role in household welfare over time was developed. This GHS-Panel Survey responds to the needs of the country, given the dependence of a high percentage of households on agriculture activities in the country, for information on household agricultural activities along with other information on the households like human capital, other economic activities, access to services and resources. The ability to follow the same households over time, makes the GHS-Panel a new and powerful tool for studying and understanding the role of agriculture in household welfare over time as it allows analyses to be made of how households add to their human and physical capital, how education affects earnings and the role of government policies and programs on poverty, inter alia.
The objectives of the survey are as follows 1. Allowing welfare levels to be produced at the state level using small area estimation techniques resulting in state-level poverty figures 2. With the integration of the longitudinal panel survey with GHS, it will be possible to conduct a more comprehensive analysis of poverty indicators and socio-economic characteristics 3. Support the development and implementation of a Computer Assisted Personal Interview (CAPI) application for the paperless collection of GHS 4. Developing an innovative model for collecting agricultural data 5. Capacity building and developing sustainable systems for the production of accurate and timely information on agricultural households in Nigeria. 6. Active dissemination of agriculture statistics
The second wave consists of two visits to the household: the post-planting visit occurred directly after the planting season to collect information on preparation of plots, inputs used, labour used for planting and other issues related to the planting season. The post-harvest visit occurred after the harvest season and collected information on crops harvested, labour used for cultivating and harvest activities, and other issues related to the harvest cycle.
National Coverage
Households
Agricultural farming household members.
Sample survey data [ssd]
The sample is designed to be representative at the national level as well as at the zonal (urban and rural) levels. The sample size of the GHS-Panel (unlike the full GHS) is not adequate for state-level estimates.
The sample is a two-stage probability sample:
First Stage: The Primary Sampling Units (PSUs) were the Enumeration Areas (EAs). These were selected based on probability proportional to size (PPS) of the total EAs in each state and FCT, Abuja and the total households listed in those EAs. A total of 500 EAs were selected using this method.
Second Stage: The second stage was the selection of households. Households were selected randomly using the systematic selection of ten (10) households per EA. This involved obtaining the total number of households listed in a particular EA, and then calculating a Sampling Interval (S.I) by dividing the total households listed by ten (10). The next step was to generate a random start 'r' from the table of random numbers which stands as the 1st selection. Consecutive selection of households was obtained by adding the sampling interval to the random start.
Determination of the sample size at the household level was based on the experience gained from previous rounds of the GHS, in which 10 households per EA are usually selected and give robust estimates.
In all, 500 clusters/EAs were canvassed and 5,000 households were interviewed. These samples were proportionally selected in the states such that different states had different samples sizes depending on the total number of EAs in each state.
Households were not selected using replacement. Thus the final number of household interviewed was slightly less than the 5,000 eligible for interviewing. The final number of households interviewed was 4,986 for a non-response rate of 0.3 percent. A total of 27,533 household members were interviewed. In the second, or Post-Harvest Visit, some household had moved as had individuals, thus the final number of households with data in both points of time (post planting and post harvest) is 4,851, with 27,993 household members.
Face-to-face paper [f2f]
Data Entry This survey used a concurrent data entry approach. In this method, the fieldwork and data entry were handled by each team assigned to the state. Each team consisted of a field supervisor, 2-4 interviewers and a data entry operator. Immediately after the data were collected in the field by the interviewers, the questionnaires were handed over to the supervisor to be checked and documented. At the end of each day of fieldwork, the questionnaires were then passed to the data entry operator for entry. After the questionnaires were entered, the data entry operator generated an error report which reported issues including out of range values and inconsistencies in the data. The supervisor then checked the report, determined what should be corrected, and decided if the field team needed to revisit the household to obtain additional information. The benefits of this method are that it allows one to: - Capture errors that might have been overlooked by a visual inspection only, - Identify errors early during the field work so that if any correction required a revisit to the household, it could be done while the team was still in the EA
The CSPro software was used to design the specialized data entry program that was used for the data entry of the questionnaires.
The data cleaning process was done in a number of stages. The first step was to ensure proper quality control during the fieldwork. This was achieved in part by using the concurrent data entry system which was, as explained above, designed to highlight many of the errors that occurred during the fieldwork. Errors that are caught at the fieldwork stage are 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 sent from the state to the head office of NBS where a second stage of data cleaning was undertaken.
During the second stage the data were examined for out of range values and outliers. The data were also examined for missing information for required variables, sections, questionnaires and EAs. Any problems found were then reported back to the state where the correction was then made. This was an ongoing process until all data were delivered to the head office.
After all the data were received by the head office, there was an overall review of the data to identify outliers and other errors on the complete set of data. Where problems were identified, this was reported to the state. There the questionnaires were checked and where necessary the relevant households were revisited and a report sent back to the head office with the corrections.
The final stage of the cleaning process was to ensure that the household- and individual-level data sets were correctly merged across all sections of the household questionnaire. 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. This was also done for crop- by-plot information as well.
The response rate was very high. Response rate after field work was calculated to be 93.9% while attrition rate was 6.1% for households. During the tracking period, 52.4% of the attrition was tracked while at the end of the whole exercise, the response rate was: Post Harvest: 97.1%
No sampling error
Facebook
TwitterThe Nigerian General Household Survey (GHS) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program and was revised in 2010 to include a panel component (GHS-Panel). The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, inter- institutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of 5,000 households, which are also representative of the geopolitical zones (at both the urban and rural level). The households included in the GHS-Panel are a sub-sample of the overall GHS sample households. This survey is the third wave of the GHS-Panel, which was implemented in 2015-2016.
National Coverage
Households
Household Members
Sample survey data [ssd]
The GHS sample is comprised of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs) chosen from each of the 37 states in Nigeria. This results in a total of 2,220 EAs nationally. Each EA contributes 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,000 households, 5,000 households from 500 EAs were selected for the panel component and 4,916 households completed their interviews in the first wave. Given the panel nature of the survey, some households had moved from their location and were not able to be located by the time of the Wave 3 visit, resulting in a slightly smaller sample of 4,581 households for Wave 3.
In order to collect detailed and accurate information on agricultural activities, GHS-Panel households are visited twice: first after the planting season (post-planting) between August and October and second after the harvest season (post-harvest) between February and April. All households are visited twice regardless of whether they participated in agricultural activities. Some important factors such as labour, food consumption, and expenditures are collected during both visits. Unless otherwise specified, the majority of the report will focus on the information collected during the post-planting visit.
Face-to-face paper [f2f]
The data cleaning process was done in a number of stages. The first step was to ensure proper quality control during the fieldwork. This was achieved in part by using the concurrent data entry system which was designed to highlight many of the errors that occurred during the fieldwork. Errors that are caught at the fieldwork stage are 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 sent from the state to the head office of NBS where a second stage of data cleaning was undertaken. During the second stage the data were examined for out of range values and outliers. The data were also examined for missing information for required variables, sections, questionnaires and EAs. Any problems found were then reported back to the state where the correction was then made. This was an ongoing process until all data were delivered to the head office.
After all the data were received by the head office, there was an overall review of the data to identify outliers and other errors on the complete set of data. Where problems were identified, this was reported to the state. There the questionnaires were checked and where necessary the relevant households were revisited and a report sent back to the head office with the corrections.
The final stage of the cleaning process was to ensure that the household- and individual-level datasets were correctly merged across all sections of the household questionnaire. 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. This was also done for crop-by-plot information as well.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Households and NPISHs Final consumption expenditure, PPP (current international $) in Nigeria was reported at 652530347414 USD in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Household final consumption expenditure, PPP (current international $) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.
Facebook
TwitterNational coverage
households/individuals
survey
Yearly
Sample size:
Facebook
TwitterThe 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).
National
• Households • Individuals • Agricultural plots • Communities
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Sample survey data [ssd]
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.
Computer Assisted Personal Interview [capi]
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.
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.
Response