Author: Pauline Mace (Oréade-Brèche)
Editor: Miranda García (AEIDL)
As part of the Tools4CAP Replication Lab, the French case study implemented in the Occitanie Region explored innovative approaches to evaluate agri-environment-climate measures (AECMs) and to better understand how farmers perceive and respond to policy incentives. Initially designed as a Discrete Choice Experiment (DCE), the study aimed to analyse how specific attributes of agri-environmental schemes influence farmers’ enrolment decisions.
However, constraints related to data availability and the legal framework required a methodological shift towards the Theory of Planned Behaviour (TPB). This adaptation shed light on the social norms, perceptions, and behavioural factors shaping farmers’ intentions. The case led to the design of a survey, sent to 273 farmers, that integrated elements from both approaches (retaining some attributes originally defined in the DCE), thereby enhancing the relevance and explanatory power of the data collected compared with a conventional survey. However, the survey faced several challenges, notably a limited sample size, farmers limited availability due to the summer timing.
The results highlighted several key lessons for policy design. Farmers’ participation is influenced by how well measures align with existing farming systems, the simplicity of administrative procedures, and the level of trust between farmers and public institutions. The case study also underlined important operational challenges, including the need for early data-sharing agreements, adequate expertise, and strong stakeholder engagement to avoid scaling down initial ambitions.
Overall, the French case study worked to demonstrate the added value of integrating behavioural approaches into CAP monitoring. These methods broaden the analytical perspective and increase the relevance of evidence for policymakers. At the same time, the experience showed that realistic planning, sufficient resources and, in some cases, simpler participatory methods are essential to ensure successful implementation in constrained contexts. This work contributed to advancing more adaptive, evidence-based, and socially grounded evaluation practices within the CAP.