Sierra Leone Annual Agricultural Survey 2024
Sierra Leone, 2024
Get MicrodataIdentification
SLE-StatsSL-AAS-2024-v01
Sierra Leone Annual Agricultural Survey 2024
SLAAS 2024
| Name | Country code |
|---|---|
| Sierra Leone | SLE |
Agriculture Integrated Survey[hh/nhh/agris]
The 2024 Sierra Leone Annual Agricultural Survey (AAS) is the second round of AAS conducted in Sierra Leone. It was implemented under the 50x2030 Initiative, a program jointly launched by the World Bank, Food and Agriculture Organization of the United Nations (FAO) and International Fund for Agricultural Development (IFAD). The lead national implementing agencies in Sierra Leone are Statistics Sierra Leone (Stats SL) and the Ministry of Agriculture and Food Security (MAFS).
AAS was designed to ensure the production of foundational agricultural data that are timely and of quality, fit the needs of the country and match the main national development targets. The approach adopted is that of a modular approach. This second survey round cover the CORE survey with additional focus on the Production Methods and Environment (PME) module.
The Sierra Leone Annual Agricultural Survey (SLAAS) is a key component of Stats SL's efforts to provide up-to-date information on the agricultural sector. The SLAAS program follows the AGRIS methodology, an integrated approach that combines a core questionnaire with rotating thematic modules to capture the technical, economic, environmental, and social dimensions of agricultural holdings. In 2024, the Production Methods and Environment (PME) module was adopted, enriching the core survey with detailed data on irrigation, energy use, land management, rice cultivation, livestock breeding strategies, environmental strategies and adaptation to climate change which are important in identifying and quantifying the gaps that exist and capitalizing on specific interventions that address these gaps.
The overall objective of the SLAAS was to collect comprehensive data on crop and livestock production, as well as other relevant agricultural indicators. This information is essential for policymakers, researchers, and other stakeholders to assess the performance of the agricultural sector, identify opportunities for improvement, and inform evidence-based interventions.
The specific objectives of the SLAAS 2024 include:
- To collect disaggregated and timely data on agricultural production and productivity at both national, regional and district levels.
- To produce baseline and monitoring data that supports the formulation, implementation and evaluation of agricultural policies and programs.
- To generate consistent and comparable agricultural statistics for assessing trends, informing budget allocations, and facilitating investment in the sector.
- To compile fundamental statistics that facilitate comparisons in the development of the agriculture sector across the country.
- To collect key data necessary to assess the impact of agricultural activities on the environmental, social and economic sustainability of farming.
Sample survey data [ssd]
Agricultural households
Version
v1.0: Edited and anonymized dataset files for dissemination. The type of release considered is Public Use File (PUF).
2026-03-18
Scope
This survey collected data from agricultural households, covering the Post Planting (PP) season and the Post Harvesting (PH) season. The topics covered are: characteristics of agricultural households, agricultural production (crops, livestock, aquaculture, fisheries and forestry), input use, labor force, land use, energy use and environmental issues.
| Topic | Vocabulary | URI |
|---|---|---|
| Agricultural households | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
| Agricultural production | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
| Crops | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
| Livestock | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
| Fishing | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
| Forestry | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
| Inputs | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
| Environment | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
Coverage
National coverage, with the exception of the Western Urban district
The survey covered agricultural households engaged in crop production, livestock rearing, fishing and aquaculture, and forestry production regardless of their scale of operation.
Producers and sponsors
| Name | Affiliation |
|---|---|
| Statistics Sierra Leone | Government of Sierra Leone |
| Ministry of Agriculture and Food Security | Government of Sierra Leone |
| Name | Affiliation | Role |
|---|---|---|
| Food and Agriculture Organization of the United Nations | United Nations | Technical assistance |
| Name | Abbreviation | Role |
|---|---|---|
| Government of Sierra Leone | Government funder | |
| World Bank | WB | Financial assistance through the HISWA Project |
Sampling
A two-stage sampling method was employed to select households. Both stages of sampling employed probabilistic methods.
The country was divided into districts and within each district, areas called Enumeration Areas (EAs) were identified. A sample of EAs was then selected, followed by a sample of agricultural households (Ag HHs) within each chosen EA. A total number of 520 EAs were selected as Primary Sampling Units (PSUs), out of which 5200 households were selected as Secondary Sampling Units (SSUs).
Due to operational constraints, not all sampled households were successfully surveyed during data collection. In total, only 518 EAs and 5110 households were actually covered during the survey.
Consequently, the PP phase comprised 4,998 households. Additionally, survey attrition occurred during the PH phase. Weight variables for each phase have been adjusted to account for these variations.
Sample weights were calculated for the data files. They were computed as the inverse of the probability of selection of agricultural household, which is the product of the probability of selection of the EA in which the household is located (at the first stage) and the probability of selection of the household (at the second stage).
The weight variable in both visits is called "HH_Final_weight". Users should note that the PH weight was adjusted from the PP weight to account for differences in household coverage due to deviations in the sampling design and some decisions taken during the data cleaning process.
Survey instrument
For this survey, two (02) questionnaires were used: the Post Planting (PP) questionnaire and the Post Harvesting (PH) questionnaire.
They were administered in each household, preferably to the head of household. They cover two (02) modules, the CORE module and the PME (Production Methods and Environment) module, splitted into several topics such as household demographics, agricultural production (crop, livestock, fishing and aquaculture, forestry), input use and labor, land use, energy use and environmental issues.
The questionnaires are provided as external resources.
Data collection
| Start | End | Cycle |
|---|---|---|
| 2024-01 | 2024-06 | Post Planting (PP) |
| 2024-07 | 2024-12 | Post Harvesting (PH) |
- Computer Assisted Personal Interview [capi]
| Name | Affiliation | Abbreviation |
|---|---|---|
| Statistics Sierra Leone | Government of Sierra Leone | Stats SL |
| Ministry of Agriculture and Food Security | Government of Sierra Leone | MAFS |
The teams of data collectors were divided into two groups: enumerators, primarily responsible for collecting data from eligible and consenting households, and supervisors, responsible for assigning and assisting enumerators in solving problems that they may encounter during the administration of the survey questionnaire and review each questionnaire before it is submitted.
The data of the SLAAS 2024 was collected throughout the annual agricultural period. This period is divided into two seasons: the first season gave rise to the first phase of the data collection, corresponding to the Post Planting (PP) phase, and the second season gave rise to the second phase of the data collection, corresponding to the Post Harvesting (PH) phase.
A training of enumerators was held before each phase. During the training, the questionnaires were presented and tested, and the main roles of each team member were discussed and elaborated.
Data processing
| Type | Description |
|---|---|
| Statistical Disclosure Control (SDC) | The dataset was anonymized using Statistical disclosure methods on R software. To start the process, variables were classified into main categories as variables to delete, quasi-identifiers, direct identifiers, linked variables. All direct identifiers and unnecessary variables were removed. Then, quasi-identifiers (and linked variables) were considered to formulate disclosure scenarios. Disclosure risk was mainly measured using k-anonymity and probabilistic risk. Both categorical and numerical quasi-identifiers have been anonymized using recoding, shuffling, top coding and local suppression, where necessary. In addition, information loss was mainly measured based on number of missing values introduced during anonymization and comparison of certain indicators. During the anonymization process, the EA codes have been shuffled. Their final usage is just to identify households in the same primary sampling unit. So, any use of these codes to infer geographic variables would be misleading. Also, in the crop roster, the main 20 crop IDs have been maintained (same as in the SLAAS 2024 report and the aggregated tables), while the remaining crop IDs have been recoded into broader crop groups. This may, however, result in some duplicated values as a result of this recoding for the broader categories. Same applies to any roster with crop information. Ultimately, these recoded categories are other crop codes with lower analytical values, compared to the main 20 crops in the country. Overall, users must be aware that data protection with SDC methods involves some perturbations in the microdata. This implies information loss and bias which may affect the interpretation of some resulting estimates and their parameters. In general, the smaller the subpopulation, the higher the potential impact derived from the anonymization process. |
| Other Processing | During the data cleaning procedure, about 160 HHs were dropped from the sampled PP HHs, due to inconsistencies and incompleteness. However, the original sample was considered to be pre-loaded for the PH visit. Therefore, there are more HHs in the PH than the PP. Accordingly, the weights in the PH data has been adjusted to reflect this inclusion. |
The PP and PH questionnaire were implemented on CSPRO as CAPI tool. During data collection, some validation controls were integrated into the app to minimize mistakes when typing households’ answers. After data collection, a processing program designed under SPSS software permitted to clean both cases and variables. Duplicated cases were deleted and then the sampling weights adjusted to take the two non-covered EAs into account. Missing, illegal, unlike and incoherent values were detected and then locally imputed objectively in respecting filters. Finally, the necessary tabulation variables were created and then tables were produced according to the tabulation plan designed earlier.
Data appraisal
To appreciate the data quality, some tables were supported by sampling errors estimates. Especially, coefficients of variations and standard errors were estimated for a set of indicators for open data publishing purposes.
Data Access
| Name | Affiliation | URL | |
|---|---|---|---|
| Statistics Sierra Leone | Government of Sierra Leone | https://www.statistics.sl/ | microdata@statistics.sl |
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| yes | Confidentiality of respondents is guaranteed by the Statistics Act of Sierra Leone, enacted in 2002. |
The datasets have been anonymized and are available as Public Use Files (PUF). They contain individual-level data (non-aggregated) that has undergone treatment to ensure strict confidentiality, preventing direct or indirect identification of individuals or households. This confidentiality protection aligns with relevant legislation.
Statistics Sierra Leone, Annual Agricultural Survey 2024 (SLAAS 2024), Version 2.3 of the public use dataset (April 2026).
Dataset downloaded from https://microdata.statistics.sl/index.php/home
Disclaimer and copyrights
The original collectors of the data, Stats SL, MAFS, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
All rights reserved (c) 2018, Statistics Sierra Leone
Metadata production
DDI-SLE-StatsSL-AAS-2024-v01
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Statistics Sierra Leone | Stats SL | Government of Sierra Leone | Documentation of the study |
| Ministry of Agriculture and Food Security | MAFS | Government of Sierra Leone | Documentation of the study |
| Food and Agriculture Organisation | FAO | United Nations | Documentation of the study |
2026-03-18
Metadata version
Version 1.0 (March 2026). This is the first draft version of the metadata.