Agricultural statistics are vital for monitoring food security, guiding rural development, and tracking progress toward the Sustainable Development Goals (SDGs) (FAO, 2019; Carletto et al., 2015). In Egypt, the Economic Census conducted by the Central Agency for Public Mobilization and Statistics (CAPMAS) is a key source of agricultural data (CAPMAS, 2025). Yet, the reliability of these statistics largely depends on the effectiveness of training for enumerators and supervisors, especially in administering the agricultural activity questionnaire. This paper examines Egypt’s experience during the 2022 Economic Census, with a focus on training challenges and their implications for data quality. A mixed-method approach was applied, combining analysis of enumerator performance records, questionnaire error rates, and semi-structured interviews with trainers and supervisors. Findings highlighted systemic barriers such as the technical complexity of the agricultural module, insufficient time for hands-on practice, varied educational backgrounds among enumerators, and logistical constraints in rural areas. Comparisons with earlier census rounds (2006 and 2012/2013) showed gradual improvements in coverage and standardization, yet persistent difficulties remain in aligning training practices with international frameworks such as the FAO World Programme for the Census of Agriculture (WCA 2020) and the SEEA-AFF (FAO, 2019; UNSD, 2020). The 2022 census placed stronger emphasis on harmonization and geospatial integration, expanding analytical potential while raising training demands. The study highlights innovative pathways for sustainable capacity building in agricultural statistics, stressing the need for continuous investment in training infrastructure, stronger collaboration with research institutions, and adaptive strategies tailored to field realities. The Egyptian case provides transferable lessons for both developing contexts and advanced statistical systems worldwide.
