{"doc_desc":{"idno":"DDI_LBR_2024_LAC-NHL_v01_M_v01_A_ESS_FAO","producers":[{"name":"Liberia Institute of Statistics and Geo-Information Services","affiliation":"Government of the Republic of Liberia","role":"Documentation of the study"},{"name":"Ministry of Agriculture","affiliation":"Government of the Republic of Liberia","role":"Documentation of the study"},{"name":"Food and Agriculture Organization of the United Nations","affiliation":"United Nations","role":"Documentation of the study and Metadata adapted for FAM"},{"name":"Development Data Group","abbr":"DECDG","affiliation":"World Bank Group","role":"Metadata adapted for World Bank Microdata Library"}],"version_statement":{"version":"Identical to a metadata (LBR_2024_LAC_NHL_v01_M_v_01_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":"LBR_2024_LAC-NHL_v01_M_v01_A_ESS","title":"Agriculture Census 2024, Non Household Listing","alternate_title":"LAC-NHL 2024"},"authoring_entity":[{"name":"Liberia Institute of Statistics and Geo-Information Services (LISGIS)","affiliation":"Government of Liberia"}],"oth_id":[{"name":"50x2030 Initiative","affiliation":"Global partnership program led by the World Bank, the Food and Agriculture Organization of the United Nations (FAO), and the International Fund for Agricultural Development (IFAD).","role":"Provided technical and financial support for the design, implementation, and analysis of the survey."}],"production_statement":{"producers":[{"name":"Ministry of Agriculture","abbr":"MoA","affiliation":"Government of Liberia","role":"Collaborator"},{"name":"Food and Agriculture Organization of the United Nations","abbr":"FAO","affiliation":"United Nations","role":"Technical assistance"}],"copyright":"\u00a9  LISGIS. All Rights Reserved","funding_agencies":[{"name":"Government of Liberia","abbr":"GOL","role":"Financial Contribution"},{"name":"World Bank","abbr":"WB","role":"Financial Contribution"}]},"distribution_statement":{"contact":[{"name":"Matthew Wantoe, Director for ICT Division","affiliation":"Liberia Institute of Statistics and Geo-Information Services","email":"matthew.wantoe@lisgis.gov.lr","uri":"https://lisgis.gov.lr/"},{"name":"Liberia Institute of Statistics and Geo-Information Services","email":"lisgis.admin@lisgis.gov.lr","uri":"https://lisgis.gov.lr/"}]},"series_statement":{"series_name":"Agricultural Census [ag/census]","series_info":"The LAC-2024 is an integrated census/survey modality program conducted in line with the World Programme for the Census of Agriculture (WCA) 2020 recommendations. The census also aligned with the objective of the 50x2030 Initiative to Close the Agricultural Data Gap. The LAC-2024 is expected to be followed by a series of annual modular agricultural surveys, including the 2024 Income, Labor, and Productivity (ILP) and the 2025 Production Methods and Environment (PME) surveys. As part of the census operations, information on non-household holdings was collected through cooperatives registered with the Cooperative Development Agency, concessions regulated by the National Bureau of Concessions (NBC), large-scale private farms, communal farms, and Farmer Based Organizations (FBOs).\n\nThe LAC-2024 also includes the Liberia Agriculture Census 2024 - Community Operations (https://microdata.fao.org/index.php/catalog/2710) and the Liberia Agriculture Census 2024 - Household Listing (https://microdata.fao.org/index.php/catalog/2711)."},"study_info":{"keywords":[{"keyword":"Agriculture","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Household Demographics","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Land Ownership","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Crop Production","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Livestock Ownership","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Farm Equipment","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Agriculture Inputs","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Extension Services","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Holding","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Land Use","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Subsistence Farming","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Land Tenure","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"},{"keyword":"Rural Households","vocab":"CESSDA (Council of European Social Science Data Archives)","uri":"https://vocabularies.cessda.eu/"}],"abstract":"The Government of Liberia and its Development Partners recognized agriculture as a pivotal sector in fostering economic growth, reducing poverty, and achieving food security. Since the end of the second civil war, the Government, in collaboration with development partners, has made substantial investments to develop and expand the agricultural sector. Over the years, policymakers and data users in the agricultural sector have experienced significant challenges in obtaining the requisite data to monitor and evaluate these interventions and make informed decisions on new interventions. To address these challenges, the Liberia Institute of Statistics and Geo-Information Services (LISGIS) and the Ministry of Agriculture (MoA) conducted several ad hoc agricultural surveys. While valuable, these surveys have often been limited in scope and unable to provide the comprehensive data needed for effective policymaking and planning. To support the sector more robustly, the government decided to undertake a comprehensive agricultural census. \n\nThe Liberia Agriculture Census 2024, the second agricultural census in Liberia since 1971 and the first to be conducted digitally, aimed to collect reliable structural data on various aspects of the agricultural sector. \n\nThe main objectives of the LAC-2024 were to:\n- Reduce the existing data gap in Liberia's agricultural sector;\n- Provide comprehensive data on the agriculture sector for policy formulation and evaluation of existing programs;\n- Enable LISGIS to establish an agriculture master sampling frame for the conduct of future agricultural surveys and research;\n- Identify the structural changes in the agriculture sector over time;\n- Provide information on crop, livestock, poultry, and aquaculture activities;\n- Determine the size, composition, practices, and related characteristics of Liberia's agricultural holdings;\n- Generate disaggregated statistics on agriculture;\n- Provide statistics for advocacy in Liberia's agricultural sector;\n- Identify agricultural practices and constraints at the community level.\n\nTo achieve these objectives, the LAC-2024 was designed to collect structural data for household and non-household holdings, and at the community level. This data provided a wealth of information used to understand the state of agriculture in Liberia. This documentation presents detailed information on the methodology used to collect data at the non-household level and provides useful metadata on the anonymized dataset for non-household holdings.","coll_dates":[{"start":"2024-01-22","end":"2024-03-22"}],"nation":[{"name":"Liberia","abbreviation":"LBR"}],"geog_coverage":"National coverage","analysis_unit":"Agricultural holdings","universe":"All non-household agricultural holdings in Liberia, to include agricultural cooperatives, concessions, communal farms, private farms, farmer-based organizations and other institutional farms engaged in agricultural activities during the 2024 farming season.","data_kind":"Census/enumeration data [cen]","notes":"The scope of the non-household holdings data includes:\n- Type of agricultural activities practiced by non-household holdings;\n- Characteristics of non-household holders and holdings;\n- Hired labor practice;\n- Agricultural parcels and plots characteristics;\n- Types of crops and methods of crop cultivation;\n- Inputs, tools and equipment use;\n- Type and number of livestock and poultry."},"method":{"data_collection":{"data_collectors":[{"name":"Liberia Institute of Statistics and Geo Information Services","abbr":"LISGIS","affiliation":"Government of Liberia"},{"name":"Ministry of Agriculture","abbr":"MOA","affiliation":"Government of Liberia"}],"sampling_procedure":"A full census of all non-household holdings in Liberia was envisioned. The LAC-2024 technical team used fifteen (15) days to develop a complete list of all non-household holdings in Liberia. This list was used  by 30 county inspectors for the non-household holdings enumeration during the census.","coll_mode":["Computer Assisted Personal Interview [capi]"],"research_instrument":"The LAC-2024 employed three questionnaires: the household questionnaire, the community questionnaire and the non-household questionnaire. These three questionnaires were based on the 50x2030 Initiative's standard model questionnaires. The Liberia Agriculture Census Technical Working Group (LAC-TWG), comprising technical staff from LISGIS, Ministry of Agriculture (MOA), National Fishery and Aquaculture Authority (NaFAA), Cooperative Development Agency (CDA), and the Ministry of Internal Affairs (MIA) worked with technicians from the 50x2030 Initiative to adapt the questionnaires to Liberia's context and realities. Suggestions and inputs were solicited from various stakeholders representing government ministries, commissions and agencies (MACs), non-governmental and international organizations, as well as academic institutions involved in agricultural issues. All questionnaires were finalized in English. Some questions in the questionnaires were translated into simple Liberian English, for the purpose of easy administration. \n\nThe non-household questionnaire was administered to the non-household holding head member or any member with extensive knowledge of the holding and its agricultural activities. The primary respondent (i.e., the non-household member who provided most of the information for the questionnaire or a given module) may vary across modules.","coll_situation":"The conduct of the 2024 Liberia Agriculture Census (LAC-2024) non-household component encountered several challenges and data limitations that must be recognized when using the microdata. These challenges reflect both the complexity of enumerating a diverse set of agricultural establishments outside of household structures and the logistical constraints inherent in implementing a nationwide census.\n\nFirst, the construction of the non-household census frame posed difficulties. While the frame was based on administrative records from multiple agencies, including the Cooperative Development Agency (CDA), Ministry of Agriculture (MOA), National Bureau of Concessions (NBC), and Ministry of Internal Affairs (MIA), there were discrepancies between administrative lists and actual field conditions. Some holdings recorded in registers were found to be dormant, defunct, or had shifted into other forms of activity. Conversely, some holdings that were active in the field were missing from the official lists. Although a verification exercise was conducted to improve coverage, the potential for undercoverage or misclassification cannot be entirely ruled out.\n\nSecond, accessibility issues affected data collection. Many non-household holdings are difficult to access due to lack of physical addresses of holders and administrative bureaucracies. This sometimes led to delays in reaching holdings, shortened interview times, or reliance on proxies for information. In a few cases, enumerators encountered difficulties arranging interviews with key managers, particularly within concession companies or larger private farms, where authorization procedures were required. This affected the ability to obtain detailed responses on sensitive topics such as land size, land use, use of tools and equipment, and type of labor utilized. In fact, three of the agricultural concessions recognized by the NBC were not covered by the census despite several attempts by enumerators and census staff.\n\nThird, while the census relied heavily on digital data collection tools (CAPI), connectivity constraints in rural areas occasionally delayed real-time data transfer and monitoring. Enumerators sometimes faced technical issues with tablets, particularly with battery life in areas lacking electricity. Although supervisors provided backup and troubleshooting support, these challenges highlight the need for stronger technological infrastructure to support fully digital operations.\n\nFourth, some respondents expressed reluctance to provide complete information, particularly on land size, land ownership arrangements, or labor practices. For example, questions on land size and labor hiring occasionally received partial or vague responses, reflecting both the sensitivity of the information and gaps in record-keeping among some institutions. Similarly, while the census intended to capture detailed data on equipment use and mechanization, many respondents could not provide exact numbers, leading to reliance on estimates.\n\nAnother challenge relates to the definition and thresholds applied for non-household holdings. For example, non-household livestock and poultry holdings were defined using specific size criteria (such as 25 heads of cattle or 500 chickens). Thus, smaller institutional farms were excluded despite contributing to agricultural production in significant ways at the local level. This limitation means that the census provides a picture of medium-to-large non-household holdings but may underrepresent smaller-scale institutional holdings.\n\nData were collected using Computer Assisted Personal Interview (CAPI) system. The CSpro application was used to develop the CAPI system. A total of 800 tablets was used for the household level interviews. In addition, some tablets were set aside for replacement of missing, damaged or malfunctioning tablets. \nDuring the data collection, team supervisors routinely synchronized their enumerators tablets for transmission of collected data to the LISGIS central server. At the end of the data collection, all tablets used for collecting the household-level data were synchronized by the team supervisors in the field and later by data quality assurance officers at LISGIS central office. The synchronized data were downloaded in SPSS and Stata format, checked for completeness (by comparing mapping and enumeration data) and inconsistencies, and then prepared for editing, tabulation and analysis.\nThe census technical team developed a tabulation plan prior to the start of the survey, which helped to guide the data editing, tabulation and analysis processes.","act_min":"The LAC-2024 data collection at the non-household level was conducted by 30 county inspectors. The work of these data collectors (or county inspectors) was coordinated by 11 regional and 22 national monitors, who routinely visited teams,  provided data quality checks, flagged and corrected  potential errors and provided in-field training where necessary. A total of 30 data quality assurance officers (one in each county) were deployed to assist county inspectors with technical issues arising from the CAPI Applications. At LISGIS central office, there were 5 monitors, called HQ monitors, who monitored the LAC-2024 dashboard daily and reported all identified errors and inconsistencies in data captured to regional and national monitors for appropriate actions.","cleaning_operations":"Data was edited using CSpro programs, version 7.7.3. The appropriate edit rules were established by programmers and subject matter specialists at LISGIS and MOA.\nIn few cases, manual editing techniques were applied to recode responses generated from "other specify" text responses. The SPSS software was used for this purpose.\n\n**STATISTICAL DISCLOSURE CONTROL (SDC)**\nThe datasets were anonymized using Statistical Disclosure Control methods to protect respondents' confidentiality while maintaining data utility. The process began with classifying variables into categories: variables to delete, quasi-identifiers, direct identifiers, and linked variables. All direct identifiers and unnecessary variables were removed. Quasi-identifiers and linked variables were analyzed to formulate disclosure scenarios, and disclosure risk was measured using k-anonymity and probabilistic risk techniques. The primary anonymization methods applied included recoding, shuffling, and local suppression. Finally, information loss was assessed to ensure that anonymization methods did not compromise the dataset's utility. The anonymization process was conducted using the R software."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"Confidentiality of respondents is guaranteed by the National Statistics and Geo-Information Act of Liberia, enacted 2004 and the United Nations Fundamental Principles on Official Statistics, specifically principle six. \n\nBefore being granted access to the dataset, all users have to formally agree: \n1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by LISGIS. \n2. Not to use any technique in an attempt to learn the identity of any person, household, non-household or community not identified on public use data files. \n3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor."}],"contact":[{"name":"Liberia Institute of Statistics and Geo-Information Services","affiliation":"Government of Liberia","email":"lisgis.admin@lisgis.gov.lr","uri":"https://lisgis.gov.lr/"}],"cit_req":"Liberia Institute of Statistics and Geo-Information Services. Liberia Agriculture Census 2022/2023 (LAC-2024) , Ref. LBR-LAC-2024_v01. Dataset downloaded from https://lisgis.gov.lr/","conditions":"The dataset has been anonymized and is available as a Public Use Dataset. It is  accessible to all for statistical and research purposes only, under the following terms and conditions:\n1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of LISGIS. \n2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations. \n3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to LISGIS. \n4. No attempt will be made to produce links among datasets provided by LISGIS, or among data from LISGIS and other datasets that could identify individuals or organizations. \n5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from LISGIS will cite the source of data in accordance with the Citation Requirement provided with each dataset. \n6. An electronic copy of all reports and publications based on the requested data will be sent to LISGIS. \n\nThe original collectors of the data, LISGIS, MOA, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.","disclaimer":"The user of the data acknowledges that the authorized distributor of the data (i.e., LISGIS), MOA and the relevant funding agency 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":"CROP_ano","description":"File contains anonymized data for crops","case_count":1775,"var_count":9,"producer":null,"data_checks":null,"version":null,"notes":null,"metadata":null},{"file_id":"F5","file_name":"Holding_ano","description":"This file is about the characteristics of 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