Sierra Leone Annual Agricultural Survey 2023
Sierra Leone, 2023
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SLE_2023_AAS_v01_M_v01_A_ESS
Sierra Leone Annual Agricultural Survey 2023
SLAAS 2023
| Name | Country code |
|---|---|
| Sierra Leone | SLE |
Agriculture Integrated Survey[hh/nhh/agris]
The 2023 Sierra Leone Annual Agricultural Survey (AAS) is the first round of AAS conducted in Sierra Leone. It was implemented under the 50x2030 Initiative, a program jointly lauched 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 first round covers the CORE module and the ILP (Income, Labor and Productivity) module.
The Sierra Leone Annual Agricultural Survey (SLAASS 2023) is a key component of Stats SL's efforts to provide up-to-date information on the agricultural sector. The 2023 SLAASS builds upon the successes of previous surveys and aligns with the best international practices.
The primary objective of the SLAASS 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. Specifically, it involved:
· Collection of timely data on agricultural production and productivity at both national regional and district levels;
· Gathering core data to help develop and review agricultural policies and to guide the implementation of agricultural plans at national and regional levels between agricultural sub-sectors;
· Compilation of fundamental statistics that facilitate comparisons in the development of the agriculture sector across the country.
Sample survey data [ssd]
Agricultural households
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), access to inputs/resources, farm income, and labor force.
| Topic | Vocabulary | URI |
|---|---|---|
| Agricultural workers | 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/ |
| Households | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
| Livestock | ELSST Thesaurus | https://thesauri.cessda.eu/elsst-5/en/ |
Coverage
National coverage, with the exception of the Western Urban district.
Households involved in agricultural production and livestock rearing, in all the fifteen agricultural districts of the country, were considered for this study.
Producers and sponsors
| Name |
|---|
| Statistics Sierra Leone |
| Ministry of Agriculture and Food Security |
| 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
The survey employed a stratified random sampling technique to ensure a representative sample of agricultural households across all five regions and fifteen districts of Sierra Leone with the exception of the Western Urban district. 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. The total number of EAs selected for the survey was 520, with 5,200 households interviewed in total. For each EA, the field team had a list of 10 households.
The survey included households engaged in crop cultivation and/or livestock rearing, regardless of the scale of their operations. However, it did not cover non-household holdings, such as large-scale commercial farms, or sectors like aquaculture, forestry, and fisheries.
The survey generated national, regional, and sub-regional estimates.
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 is called "HH_Final_weight".
Survey instrument
For this survey, two 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 modules, the CORE module and the ILP (Income, Labor and Productivity) module, split into several topics such as household demographics, land ownership, agricultural activities, livestock rearing, labor force composition, and participation in off-farm activities.
The questionnaires are provided as external resources.
The dataset was anonymized using statistical disclosure methods. 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.
Quasi identifiers have been anonymized using recoding, shuffling and local suppression which was applied to both the quasi-identifiers and the linked variables. In addition, information loss was mainly measured based on the number of missing values introduced during anonymization and dependency coefficient between categorical variables.
The software used was R.
Data collection
| Start | End | Cycle |
|---|---|---|
| 2023-09-01 | 2023-09-30 | Post Planting (PP) |
| 2023-12-01 | 2023-12-30 | 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 reviewing each questionnaire before it is submitted.
The number of persons per team varied from district to district. It ranged from 2 to 5, for a total of 104 enumerators and 26 teams deployed in the selected EAs to collect the data.
The data of the SLAAS 2023 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
The PP and PH questionnaire were implemented using CAPI with CSPRO. 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 with SPSS software allowed for cleaning both cases and variables. Duplicated cases were deleted and then the sampling weights were adjusted to take the two non-covered EAs into account (out of the 520 EAs originally planned, 518 were actually completed). 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/ | [email protected] |
| 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 2023 (SLAAS 2023), Version 2.1 of the public use dataset (April 2025)
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_2023_AAS_v01_M_v01_A_ESS_FAO
| 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 Organization of the United Nations | FAO | United Nations | Documentation of the study |
| Statistics Division | ESS | FAO | Metadata adapted for FAM |
2025-04-15