Exploring Farmers Conditions, Strategies and Sustainability Performances with the CSP Model.

Market mechanisms, policy instruments and legal frameworks have a major influence on the agricultural sector, production and food markets on the international, European and regional level. The Common Agricultural Policy (CAP), market regulation and policy in general continue to have a significant influence on volumes and prices of e.g. cereals, fruit, or dairy, beef and fish production in spite of policy reforms aimed at deregulating and reducing negative policy impacts. In order to steer developments in directions that are desirable in societal terms, and to foster the sustainability of agriculture in Europe’s regions, more carefully planned, targeted interventions might be needed. In the context of evidence-informed policy development, decision makers ask stakeholders and analysts for policy advice. Examples of questions are: How can we prepare farmers for changes caused by new trade agreements? Which measures help to reduce nitrate emissions in threatened water bodies? Why do innovative soil protection methods spread so slowly? Scientists develop models, apply scenario analyses and ex-ante assessments related to adjustments in relevant policy frameworks. Computational models tend to have the problem that simplifications of the often much more complex and heterogeneous farming reality are inevitable in particular because only limited data are available. Farmers’ decision-making processes as well as potentially very relevant environmental, socio-economic or cultural issues tend to be underestimated. Modelling outcomes also tend to be hard to communicate in their complexity, and sometimes the underlying assumptions limit policy-relevance. The influence of initiatives, for example, is a new challenge for projections. Due to the growing complexity of contemporary challenges and the rapidly increasing need for a more sustainable use and equitable sharing of limited resources, pressure on analysts is increasing to produce assessments that are more in line with the complexity and heterogeneity of situations