National Agricultural Sample Survey 2023
Agricultural Household Survey
Nigeria, 2022
Get MicrodataIdentification
NGA-NBS-NASS-2023-v01
National Agricultural Sample Survey 2023
Agricultural Household Survey
NASS 2023
| Name | Country code |
|---|---|
| Nigeria | NGA |
Agricultural Survey [ag/oth]
The National Agriculture Sample Survey (NASS) 2023 is the second round of NASS surveys, previously conducted around 2010/2011. NASS 2023 was conducted by the National Bureau of Statistics (NBS), in collaboration with Food and Agriculture Organization (FAO), Federal Ministry of Agriculture and Food Security (FMAFS), and the World Bank on all agricultural activities in the country at the household, establishment (corporate farm), and community levels, capturing crop production, fishery, forestry, livestock activities, and farmgate prices.
NASS is an exercise designed to provide accurate and up-to-date agricultural statistics that allows policymakers, researchers, and development partners to make informed decisions that directly impact the well-being of farmers, rural communities, and the broader economy. These statistics are essential for enhancing food security, improving productivity, and addressing regional disparities in agricultural performance. Additionally, robust agricultural data is vital in supporting Nigeria’s efforts to diversify its economy from oil dependency. By identifying key areas for investment, such as crop production, livestock management, and agro-processing, data can guide both public and private sector investments to boost agricultural output and expand exports. Moreover, they help track progress toward national goals while supporting Nigeria's efforts to meet global commitments like the Sustainable Development Goals (SDGs). Hence, NASS provides useful data for understanding the state of the agricultural sector and offer essential production and structural data to support evidence-based planning and implementation of agricultural programs vital for addressing current economic challenges and enhancing the livelihood of many Nigerians.
This survey is also essential for monitoring and evaluating the effectiveness of existing agricultural programs and ensuring that resources are allocated efficiently. Capturing detailed data on agriculture practices, outputs, and challenges, the survey supports the planning and implementation of initiatives aimed at improving productivity, enhancing food security, and adapting to challenges like climate change and market fluctuations.
The objectives of the survey are to;
i. provide data on agricultural production in 2022/ 2023 and the structure of the sector as a whole to assist the government in policy formulation and programme planning;
ii. effectively and efficiently provide appropriate agricultural information to increase public awareness; and
iii. provide data that could be used to compute agricultural sector contribution to the Gross Domestic Product (GDP).
Sample survey data [ssd]
Agricultural Households.
Version
v1.0: Edited, anonymized microdata
2024-07-31
This dataset is the anonymized version of the cleaned dataset of the Agricultural household survey.
Scope
The household survey component of National Agricultural Sample Survey (NASS) covered the following subject areas:
• General Household/Holding Identification
• Crop Farming
• Livestock/ Poultry farming
• Fisheries
• Forestry
• Apiary production (Beekeeping)
• Labour
| Topic | Vocabulary |
|---|---|
| Agricultural Production | World Bank |
Coverage
The National Population Commission (NPC) provided the frame of Enumeration Areas (EAs), newly demarcated for the proposed 2023 Housing and Population Census. This was used as the primary sampling frame. Although data was collected across the 36 states and the Federal Capital Territory (FCT), some Local Government Areas (LGAs) were not covered due to insecurity. The LGAs covered during the survey were seven hundred and sixty-seven (767) out of the 774 LGAs in Nigeria due to security challenges. The affected states/LGAs are Borno state (Monguno, Kukawa and Abadam LGAs) and Orlu, Orsu, Oru East, and Njaba LGAs in Imo state. The number of EAs covered varied from state to state depending on the number of Agricultural EAs and LGAs. Nationally, a total of 15,591 EAs were selected across the 36 States of the Federation and FCT and a total of 152,485 households were designated to be covered.
The final sampling units used were agricultural households involved in crop/ livestock farming, and fishery households selected in a subsample of EAs among the sample of EAs covered during the extensive listing survey.
Producers and sponsors
| Name | Affiliation |
|---|---|
| National Bureau of Statistics (NBS) | Federal Government of Nigeria (FGN) |
| Name | Affiliation | Role |
|---|---|---|
| Federal Ministry of Agriculture and Food Security (formerly Federal Ministry of Agriculture and Rural Development | Federal Government of Nigeria (FGN) | Technical support |
| World Bank | The World Bank Group (WBG) | Technical support |
| Food and Agriculture Organization of the United Nations | United Nations (UN) | Technical support |
| National Population Commision | Federal Government of Nigeria (FGN) | Technical support |
| The 50x2030 Initiative | Technical support |
| Name | Abbreviation | Role |
|---|---|---|
| The World Bank Group | WBG | Financial assistance |
| Name | Affiliation | Role |
|---|---|---|
| Federal Ministry of Finance | Federal Government of Nigeria | Supervision |
| Food and Agriculture Organization of the United Nations | United Nations | Technical assistance |
| The 50x2030 Initiative | Technical assistance |
Sampling
The final sampling units used were agricultural households involved in crop/ livestock farming, and fishery households selected in a subsample of EAs among the sample of EAs covered during the extensive listing survey. The sampling method of NASS-household is a stratified three-phased sampling as follows:
-First phase: Stratified Probability Proportional to Size (PPS) selection of 80 EAs
Second phase: systematic sub-sampling of 40 EAs for the extended listing
Third phase: two-stage sampling for NASS-household
i. First stage: Stratification of EAs into Agricultural and non-agricultural EAs drawn from the 40EAs listed in each LGA
ii. Second stage: Systematic sampling of 10 farming households (crop/ livestock farming) and a systematic selection of complementary households practicing only fishery in fishery-intensive LGAs (18) up to a maximum of 12 households were interviewed in the concerned EAs. That selection was stratified by sorting the listed farming households by various agricultural-related information including farming activities practiced, number of plots, livestock numbers in tropical livestock units, as well as the gender of the household head.
Sample Size and Reallocation
A total of 15,591 Enumeration Areas (EAs) were selected for the NASS household survey. The sample was distributed across Local Government Areas (LGAs) based on the estimated total number of plots per LGA. Within each LGA, the sample was further allocated between urban and rural areas in proportion to the estimated agricultural population. In the selected EAs, 152,485 households were finally sampled.
The probabilities of selecting EAs for NASS households were derived from two stages: the likelihood of their selection in the listing sample and the probability of selection from the subsample of EAs chosen for NASS households. These probabilities were then combined with the probabilities of selecting farming households within the EAs to determine the final selection probabilities for farming households. The design weights were calculated as the inverse of these selection probabilities.
These weights were further adjusted to account for non-responses, resulting in final sampling weights used in estimating means, totals, proportions, and other statistics through standard Horvitz-Thompson estimators. Special consideration was given to fishery-related estimates, ensuring that data from the independent sample of households engaged solely in fishery activities were fully incorporated.
Due to the complexity of the sampling design, sampling errors were estimated using resampling methods such as Bootstrap and Jackknife techniques.
The final probability of selection of each EA is the product of its probabilities of selection in the first and second phase sampling. The design weight is the inverse of the final selection probability. Design weights were adjusted for non-response and scaled to the updated frame population providing final weights for producing estimates (mean, totals, proportions…) with standard Horvitz-Thompson estimators.
It is important to note that the sampling weights were calibrated using preliminary estimates of numbers of households from the cartographic work by the National Population Commission of Nigeria.
The variable "nasc_listing_weight" in the microdata represents the household listing weight.
Survey instrument
The NASS household questionnaire served as a meticulously designed instrument administered within selected households to gather comprehensive data.
The questionnaire was structured into the following sections:
0A. HOLDING IDENTIFICATION
0B. ROSTER OF HOUSEHOLD MEMBERS
0C. AGRICULTURAL ACTIVITIES
0D. AGRICULTURALACTIVITIES
2. PLOT ROSTER AND DETAILS
3. CROP ROSTER
1A: TEMPORARY (NON-VEGETABLE) CROP PRODUCTION
1H: TEMPORARY CROP PRODUCTION (VEGETABLE CROPS)
1B: TEMPORARY CROP DESTINATION
2A: PERMANENT CROP PRODUCTION
2B: PERMANENT CROP DESTINATION
4: SEED AND PLANT USE
3C: INPUT USE
2(DS): PLOT ROSTER AND DETAILS
3(DS): CROP ROSTER
1A(DS): TEMPORARY (NON-VEGETABLE) CROP PRODUCTION - DRY SEASON
1H(DS): TEMPORARY CROP PRODUCTION (VEGETABLE CROPS) - DRY SEASON
1B(DS): TEMPORARY CROP DESTINATION - DRY SEASON
4(DS): SEED AND PLANT USE - DRY SEASON
3C(DS): INPUT USE - DRY SEASON
4A: LIVESTOCK IN STOCK
4B: CHANGE IN STOCK- LARGE AND MEDIUM-SIZED ANIMALS
4C: CHANGE IN STOCK-POULTRY
4G: MILKPRODUCTION
4H: EGG PRODUCTION
4I: OTHERLIVESTOCKPRODUCTS
4J:APIARYPRODUCTION (BEEKEEPING)
5A: FISH FARMING/AQUACULTUREPRODUCTION
6A: FISH HUNTING/CAPTURE
7A: FORESTRYPRODUCTION
9: LABOUR
2_GPS.PLOT GPS MEASUREMENT
99. END OFTHE SURVEY
STATISTICAL DISCLOSURE CONTROL
To safeguard the confidentiality of household information, rigorous anonymization techniques have been employed on the edited microdata. This process involved the removal of all direct identifiers, such as names, GPS locations, and specific addresses. Additionally, geographic information below the level of Local Government Area (LGA) has been excised to prevent any potential identification of individuals or households based on their location.
Furthermore, a masking technique (local suppression algorithms) has been implemented on the quasi-identifying variables using the R package sdcMicro. This ensures that even subtle patterns or combinations of variables that could potentially lead to re-identification are obfuscated, thereby enhancing the overall security and privacy of the dataset.
Data collection
| Start | End |
|---|---|
| 2022-07-06 | 2022-09-09 |
- Computer Assisted Personal Interview [capi]
| Name | Affiliation | Abbreviation |
|---|---|---|
| National Bureau of Statistics | Federal Government of Nigeria (FGN) | NBS |
Two rounds of monitoring exercise were carried out in addition to the remote monitoring of data collection. Trainers who also served as monitors, independent monitors, and coordinators participated in the monitoring exercise. They accompanied the field teams to monitor the kickstart of the survey for the first round of monitoring. The general roles of the monitors were to ensure proper compliance with laid-down rules and procedures by the enumerators, ensure that high-quality data were collected, ensure all farms within the household were measured, and suggest plausible solutions to problems where necessary.
The second round of monitoring was in the middle of the fieldwork. Monitors were further tasked with following up with states on the number and status of malfunctioning CAPI and GPS devices to promptly call for replacements, resolving technical issues, and visiting all the Corporate Farms that enumerators reported to have closed down, not in existence, could not be located, or had misclassification of activities to determine the veracity of their claims.
THE TRAINING OF FIELD STAFF
Trainings for the survey were done in three (3) phases; the Training of Trainers (ToT), Training of Enumerators (ToE), and Training of Data Editors and Data Assistants.
The First level of training was the national level Training of Trainers (ToT) held in Abuja. Participants for the ToT included staff of National Bureau of Statistics (NBS), Federal Ministry of Agriculture and Rural Development (FMARD), National Population Commission and Coordinators (Directorate staff of NBS, FMARD, NPC, World Bank and FAO). The training lasted for eight (8) days. Participants were engaged in two (2) aptitude tests to assess their knowledge of the training received and their performance.
The second level of training was the Training of Enumerators (ToE) at the state level. The participants trained include enumerators, NBS Zonal Controllers (supervisors), NBS State Officers (supervisors), Staff of State Statistical Agencies (supervisors), Staff of State Ministry of Agriculture (supervisors), Independent monitors, and coordinators. The training which also lasted for 8 days was carried out in two phases. The first three days of training were dedicated mostly to enumerators who collected data on corporate farm questionnaires and the training was concluded at the end of the third day to commence the lodgement of the corporate farm questionnaires. The remaining five days were used for the intensive training of enumerators who administered household and price questionnaires. It is important to note that the enumerators who conducted household surveys also administered price questionnaires at the community level. The Participants were subjected to two separate exams to test their knowledge of the training received.
There was a training for the data editors and data assistants in Abuja on households and price questionnaires. The rationale behind this level of training was to ensure that the editors understood all the sections of the questionnaires.
DATA COLLECTION
There were teams constituted in each states to carry out the assignment. Each team comprised a team lead and a teammate, and covered an average of 20 EAs. Some of the teams worked in more than one LGA. An enumerator interviewed 5 households in each EA visited, in two (2) and a half day. Cultivated plots used by households that were not too large or more than 2 hours away from the dwelling were measured on the last day in the EA. For Corporate Farms, the workload varied. However, all enumerators covered an average of 50 corporate farms depending on the number of corporate farms in the state. An average of 15 corporate farms questionnaires were lodged per week. Data collection lasted for 50 days for both households and corporate farms.
COORDINATION
Coordination of the entire survey process was carried out by the survey management team and the stakeholders from collaborating MDAs, to ensure a hitch-free activity by field personnel to ensure adherence to established procedures.
DATA TRANSMISSION AND QUESTIONNAIRE RETRIEVAL
For the Household and Producer Price questionnaire, information was captured electronically using CAPI Devices. There was real-time online transmission of data. However, enumerators engaged for the Corporate Farm were tasked with manually retrieving lodged questionnaires from the establishments at agreed date within the allotted timeline.
Data processing
Data processing and analysis involved data cleaning, data analysis, data verification/validation, and table generation. World Food Programme (WFP), Food and Agricultural Organization (FAO), and NBS carried out the data processing and analysis for both the household and corporate farms questionnaires. The corporate farm questionnaire involved manual editing as well as data entry.
Data appraisal
Given the complexity of the sample design, sampling errors were estimated through resampling approaches (Bootstrap/Jackknife)
Data Access
| Name | Affiliation | URL | |
|---|---|---|---|
| National Bureau of Statistics (NBS) | Federal Government of Nigeria (FGN) | www.nigerianstat.gov.ng | feedback@nigerianstat.gov.ng |
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| yes | The confidentiality of the individual respondent is protected by law (Statistical Act 2007) This is published in the Official Gazette of the Federal republic of Nigeria No. 60 vol. 94 of 11th June 2007. See section 26 para.2. Punitive measures for breeches of confidentiality are outlined in section 28 of the same Act. |
A comprehensive data access policy is been developed by NBS, however section 27 of the Statistical Act 2007 outlines the data access obligation of data producers which includes the realease of properly anonymized micro data.
National Bureau of Statistics, Nigeria, National Agricultural Sample Survey (NASS 2023)-v1.0
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.
(c) 2024, National Bureau of Statistics
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Prince Adeyemi Adeniran | National Bureau of Statistics (NBS) | sg@nigerianstat.gov.ng | www.nigerianstat.gov.ng |
| Mr. Fafunmi E.A | National Bureau of Statistics (NBS) | biyifafunmi@nigerianstat.gov.ng | www.nigerianstat.gov.ng |
| Mr. David Babalola | National Bureau of Statistics (NBS) | dababalola@nigerianstat.gov.ng | www.nigerianstat.gov.ng |
| Mr. Mustapha | National Bureau of Statistics (NBS) | mdazeez@nigerianstat.gov.ng | www.nigerianstat.gov.ng |
| Mr. Bishop Ohios | National Bureau of Statistics (NBS) | bishopohios@yahoo.com | www.nigerianstat.gov.ng |
Metadata production
DDI-NGA-NBS-NASS-2023-v01
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| National Bureau of Statistics | NBS | Federal Government of Nigeria | Producer |
| Federal Ministry of Agriculture and Food Security (fomerly Federal Ministry of Agriculture and Rural Development) | FMAFS(fomerly FMARD) | Federal Government of Nigeria | Contributor |
2025-09-23
Metadata version
Version 1.0