{"doc_desc":{"idno":"DDI_SLE_2023_AAS_v01_M_v01_A_ESS_FAO","producers":[{"name":"Statistics Sierra Leone","abbr":"Stats SL","affiliation":"Government of Sierra Leone","role":"Documentation of the study"},{"name":"Ministry of Agriculture and Food Security","abbr":"MAFS","affiliation":"Government of Sierra Leone","role":"Documentation of the study"},{"name":"Food and Agriculture Organization of the United Nations","abbr":"FAO","affiliation":"United Nations","role":"Documentation of the study"},{"name":"Statistics Division","abbr":"ESS","affiliation":"FAO","role":"Metadata adapted for FAM"},{"name":"Development Data Group","abbr":"DECDG","affiliation":"World Bank Group","role":"Metadata adapted for World Bank Microdata Library"}],"prod_date":"2025-04-15","version_statement":{"version":"Identical to a metadata (SLE_2023_AAS_v01_M_v01_A_ESS) published on FAO microdata repository (https://microdata.fao.org/index.php/catalog). Some of the metadata fields have been edited."}},"study_desc":{"title_statement":{"idno":"SLE_2023_AAS_v01_M_v01_A_ESS","title":"Annual Agricultural Survey 2023","alternate_title":"AAS 2023"},"authoring_entity":[{"name":"Statistics Sierra Leone"},{"name":"Ministry of Agriculture and Food Security"}],"production_statement":{"producers":[{"name":"Food and Agriculture Organization of the United Nations","abbr":"FAO","affiliation":"United Nations","role":"Technical assistance"}],"copyright":"All rights reserved (c) 2018, Statistics Sierra Leone","funding_agencies":[{"name":"Government of Sierra Leone","role":"Government funder"},{"name":"World Bank","abbr":"WB","role":"Financial assistance through the HISWA Project"}]},"series_statement":{"series_name":"Agriculture Integrated Survey[hh/nhh/agris]","series_info":"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).\n\nAAS 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."},"version_statement":{"version":"Version 2.1: Edited, anonymized dataset distributed as public use file.\nData have been edited and anonymized before the release. The type of release considered is Public Use File (PUF).","version_date":"2025-04-14"},"study_info":{"keywords":[{"keyword":"Agricultural yields","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"keyword":"Area measurement","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"keyword":"Food and nutrition","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"keyword":"Forestry","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"keyword":"Labour force","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"keyword":"Land economics","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"keyword":"Seeds","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"}],"topics":[{"topic":"Agricultural workers","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"topic":"Agricultural production","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"topic":"Crops","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"topic":"Households","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"},{"topic":"Livestock","vocab":"ELSST Thesaurus","uri":"https://thesauri.cessda.eu/elsst-5/en/"}],"abstract":"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.\nThe 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:\n\u00b7 Collection of timely data on agricultural production and productivity at both national regional and district levels;\n\u00b7 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; \n\u00b7 Compilation of fundamental statistics that facilitate comparisons in the development of the agriculture sector across the country.","coll_dates":[{"start":"2023-09-01","end":"2023-09-30","cycle":"Post Planting (PP)"},{"start":"2023-12-01","end":"2023-12-30","cycle":"Post Harvesting (PH)"}],"nation":[{"name":"Sierra Leone","abbreviation":"SLE"}],"geog_coverage":"National coverage, with the exception of the Western Urban district.","analysis_unit":"Agricultural households","universe":"Households involved in agricultural production and livestock rearing, in all the fifteen agricultural districts of the country, were considered for this study.","data_kind":"Sample survey data [ssd]","notes":"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."},"method":{"data_collection":{"data_collectors":[{"name":"Statistics Sierra Leone","abbr":"Stats SL","affiliation":"Government of Sierra Leone"},{"name":"Ministry of Agriculture and Food Security","abbr":"MAFS","affiliation":"Government of Sierra Leone"}],"sampling_procedure":"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.\n\nThe 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.\n\nThe 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.\n\nThe survey generated national, regional, and sub-regional estimates.","coll_mode":["Computer Assisted Personal Interview [capi]"],"research_instrument":"For this survey, two questionnaires were used: the Post Planting (PP) questionnaire and the Post Harvesting (PH) questionnaire.\nThey 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.\n\nThe questionnaires are provided as external resources.","coll_situation":"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.\n\nA 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","act_min":"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.\n\nThe 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.","weight":"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).\n\nThe weight variable is called \"HH_Final_weight\".","cleaning_operations":"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\u2019 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. 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."},"method_notes":"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.\nQuasi 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.\nThe software used was R.","analysis_info":{"sampling_error_estimates":"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":{"dataset_use":{"conf_dec":[{"txt":"Confidentiality of respondents is guaranteed by the Statistics Act of Sierra Leone, enacted in 2002."}],"contact":[{"name":"Statistics Sierra Leone","affiliation":"Government of Sierra Leone","email":"microdata@statistics.sl","uri":"https://www.statistics.sl/"}],"cit_req":"Statistics Sierra Leone, Annual Agricultural Survey 2023 (SLAAS 2023), Version 2.1 of the public use dataset (April 2025)\n\nDataset downloaded from https://microdata.statistics.sl/index.php/home","conditions":"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.","disclaimer":"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."}}},"schematype":"survey","tags":[{"tag":"NODOI"}],"type":"survey","data_files":[{"file_id":"F1","file_name":"Households_ano","description":"The file contains data related to the agricultural households and the head of agricultural households.\nThe information refers to the Post Planting questionnaire.","case_count":4998,"var_count":30,"producer":null,"data_checks":null,"version":null,"notes":null,"metadata":null},{"file_id":"F2","file_name":"Members_ano","description":"The file contains characteristics of all agricultural household members, including head of households.\nThe information refers to the Post Planting questionnaire.","case_count":26048,"var_count":20,"producer":null,"data_checks":null,"version":null,"notes":null,"metadata":null},{"file_id":"F3","file_name":"Parcels_ano","description":"The file contains data related to parcels used by the agricultural households. 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