Advancing Monitoring Tools for Food System Evaluation and Policy Design (KB-53-000-018)

This project strengthens how we understand and evaluate Europe’s food and farming systems. It improves how food prices affect the affordability of healthy diets, clarifies the role of monitoring and evaluation in policy making, and develops better ways to gather farm data.

This project aims to strengthen the evidence base and analytical tools used to understand and improve Europe’s food and farming systems. It focuses on three interconnected challenges: food price dynamics and diet affordability, the diversity of monitoring and evaluation practices in agricultural policy, and the need for more detailed and efficient farm-level data to meet emerging information requirements.

 

First, the project analyses how prices move along the agri-food value chain and how these changes affect what consumers ultimately pay. By applying advanced econometric models, it will identify how prices are tranferred in the food chain and how it influences the affordability of healthy diets.

 

Second, the project brings clarity to the wide range of monitoring and evaluation (M&E) approaches used across the sector. Currently, terms such as compliance monitoring, performance monitoring, impact assessment, and ex-ante evaluation are often applied inconsistently. Through a systematic review and comparative analysis, the project will develop a clear typology of M&E methods, helping policymakers and practitioners choose the most appropriate tools and improve the coherence of policy cycles.

 

Third, the project explores innovative ways to enhance data granularity within the FADN/FSDN systems. Many emerging research and policy questions—including environmental performance and sustainability reporting—require information at the level of individual production units, not just whole farms. To reduce the burden on farmers, the project will evaluate alternative methods such as heuristic allocation rules, data sharing with farm management information systems, and machine learning techniques that infer detailed data from existing data.