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Enhancing Agricultural Resilience in the Ethiopian Highlands: M&E Framework and Innovations

This project outlines a comprehensive Monitoring and Evaluation (M&E) framework tailored for agricultural interventions in the Ethiopian Highlands. It includes methodologies for site identification, data analysis, and the application of key indicators, such as nutrition and market effects. Focusing on cost/benefit analysis and RCT evaluations, the project uses diverse datasets, including household surveys and spatial data, to stratify development domains. The aim is to develop whole-farm models and improve insights into innovations, thereby enhancing productivity and sustainability at both community and national levels.

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Enhancing Agricultural Resilience in the Ethiopian Highlands: M&E Framework and Innovations

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  1. Africa Rising M&E Components, Activities, and Outputs Outputs • Program/Project Site Identification Data/Analysis Platform • M&E Outputs • FtF Indicators • Outcome mapping (incl. nutrition & market effect) • Cost/Benefit analyses • RCT evaluation • Adoption studies? Ethiopian Highlands Contextual Data (national/regional) - Statistics - HH survey & census - Spatial data Sudano – Sahelian Project Site Stratification (Development Domains) A B A C Derived Indicators - HH Typologies - Intensification Index - Sustainability Index - Nutrition index? East and Southern Africa Maize Mixed Ranking domains by key AR attributes A ________ C ________ B ________ FtF Indicators / reports by - Research sites - Country / National level - Project sites - Program / SSA • Action research site selection criteria • Site access • Existing activity/platforms • Research design • Intervention type • M&E approach • ……. • M&E approach Project/Activity/ Partner Inventory - Project DB (& maps) Identify research sites in priority domains that satisfy selection criteria SI Innovation Catalogue - Inventory (cross-site) - Characterization - Open access Innovation Inventory - Standard metadata - User interfaces Research Site Baseline survey Set up trials Monitoring Mid-line survey (?) End-line survey Communities/ Farms/Plots Site Data - Climate, soils, market access, etc - Community/HH survey data - Experimental data - Model input data • Performance Variables • (modeling & validation) • ∆Whole farm productivity • Technology performance • ∆ Yield • ∆ Labor prod.- by gender • ∆ NUE, WUE • - ∆Revenues, Costs, Profits + + + + + Project Planning & Management Improved insights into innovations , delivery platforms, and site selection + • Whole-farm models Learning

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