MNE_2024_PP_v01_M_v01_A_ESS DDI_MNE_2024_PP_v01_M_v01_A_ESS_FAO Statistical Office of Montenegro (MONSTAT, Uprava za statistiku Crne Gore) Statistics Division Nesstar Publisher Agricultural Census 2024 Popis poljoprivrede 2024 MNE_2024_PP_v01_M_v01_A_ESS Statistical Office of Montenegro (MONSTAT, Uprava za statistiku Crne Gore) Ministry of Agriculture, Forestry and Water Management (Ministarstvo poljoprivrede, šumarstva i vodoprivrede) Biotechnical Faculty Ministry of Spatial Planning, Urbanism and State Property (Ministarstvo prostornog planiranja, urbanizma i državne imovine) Nesstar Publisher Statistical Office of Montenegro (MONSTAT, Uprava za statistiku Crne Gore) Agricultural Census [ag/census] The Agricultural Census 2024 was the second census to be conducted in Montenegro, while the first was conducted in 2010. Structure of Agriculture Land use Crops Livestock and Poultry Labour in the Agricultural Sector Forestry Machinery and Equipment The Agricultural Census 2024 collected detailed information on the structure of agriculture covering among other information: number of holdings, people participating in agricultural production, utilised agricultural land, livestock, irrigated area, etc. Montenegro The Agricultural Census 2024 covered the entire country. Agricultural holdings Census/enumeration data [cen] Computer Assisted Personal Interview [capi] Direct data capture was ensured by the CAPI method using the CSPro software. Accuracy control was carried out at all stages of the census. Data accuracy control began at the very start of the census. State instructors and controllers reviewed the questionnaires completed by enumerators daily and made the necessary corrections. Data control was carried out online, using a special program (Python) developed exclusively for monitoring and verifying the accuracy of completed questionnaires. After the completion of the fieldwork phase of the census, the verification of data accuracy continued during the data processing stage through matching data with administrative data sources and applying statistical, computational, and logical checks. Data processing was performed using SAS software and Excel. Imputation methods were applied to handle missing data, also in SAS software and Excel. Administrative data sources, such as the subvention for crop variables, data on direct payments in livestock farming and the organic farming register, were used for imputation. This allowed the derivation of missing values for many characteristics based on logical relationships and available information from administrative data sources. Data validation for some questions was done in SAS software and Excel. Also, the validation rules of EUROFARM were used.