We replicate Bocquého et al. (2014), who used multiple price lists to investigate the risk preferences of 107 French farmers. We collected new data from 1430 participants in 11 European farming systems. In agreement with the original study, farmers' risk preferences are best described by Cumulative Prospect Theory. Structural model estimates show that farmers in the new samples are, on average, less loss averse and more susceptible to probability distortion than in the original study. Explorative analyses indicate differences between estimation approaches, as well as heterogeneity between and within samples. We discuss challenges in replications of economic experiments with farmers across farming contexts.

Summary: In order to keep pace with the evolution of the objectives and means of the EU's Common Agricultural Policy, evaluation tools also need to adapt. A set of tools that have proved highly effective in other policy fields is economic experiments. These allow the testing of a new policy before its implementation, provide evidence of its specific effects, and identify behavioural dimensions that can influence policy outcomes. We argue that agricultural policy should be subject to economic experiments, providing examples to illustrate how they can inform CAP design. We identify the additional efforts needed to establish further proof‐of‐concept, by running more – and more robust – experiments related to the CAP. This can happen only by integrating experimental evaluation results within the policy cycle and addressing ethical and practical challenges seriously. To do so, researchers would benefit from a concerted European effort to promote the methodology across the EU; organise the replication in time and across Europe of experiments relevant for the CAP; and build a multi‐national panel of farmers willing to participate in experiments. Steps are being taken in this direction by the Research Network of Economics Experiments for CAP evaluation (REECAP).

La Commission européenne dans sa proposition de réforme de la Politique agricole commune a déclaré vouloir introduire plus d’équité dans la distribution des aides agricoles du premier pilier entre États-membres et au sein des États-membres. Cet article analyse la dispersion des soutiens directs dans la situation avant réforme. Une décomposition de l’indice de Theil démontre qu’elle est plus liée à la distribution au sein des États-membres qu’entre les États-membres. Les auteurs la caractérisent dans les deux cas et présentent les notions d’équité qui sous-tendent l’accord politique obtenu entre le Parlement européen, le Conseil et la Commission européenne. Les mesures négociées dans cet accord – la convergence des montants des droits à paiements de base, la dégressivité et le paiement redistributif – sont présentées et illustrées dans le cas français. Enfin, l’analyse du processus dit de « convergence externe », c’est-à-dire de transferts en faveur des États-membres ayant des montants d’aides directes par hectare plus faibles que la moyenne, conclut sur des changements marginaux en termes de montants et de bénéficiaires concernés.

Risk is a pervasive factor in agriculture and a subject of great interest to agricultural economists. However, there is a lack of comprehensive understanding of the knowledge held by farm advisors, students, and economists with regards to farmers' risk preferences. Misconceptions about farmers’ willingness to take risks could lead to misguided advice. This study builds upon a recent multinational endeavor that employed a multiple price list to assess risk preferences among European farmers. We expand this research by gathering predictions for farmers’ risk preferences from 561 farm advisors, students, and economists. Our objectives are threefold: firstly, we explore variations as to how accurately participants can predict risk preferences in different specializations; secondly, we compare the predictive accuracy of different groups of forecasters; and thirdly, we assess whether modifying incentive mechanisms can improve the accuracy of predictions. Whereas our findings reveal substantial variation in individual predictions, the averages closely align with the observed responses of farmers. Notably, the most accurate predictions were provided by a sample of experimental economics researchers. Furthermore, predictions for different production systems exhibit minimal disparities. Introducing incentive schemes, such as a tournament structure, where the best prediction receives a reward, or a high-accuracy system, where randomly selected participants are compensated for the accuracy of their predictions, does not significantly impact accuracy. Further research and exploration are needed to identify the most reliable sources of advice for farmers. JEL-Codes: Q12, Q16, C91