MIND STEP

EU’s Common Agricultural Policy (CAP) increasingly aims to contribute to the Paris climate agreement and the Sustainability Development Goals. Efforts and proposals to redesign the CAP seek for efficient regional and farm specific measures and an improved link to environment, climate change and ecosystem services. This development calls for a new generation of impact assessment tools that explicitly focus on the farm level and the farmers individual decision making (IDM). MIND STEP will contribute in this direction and aims to establish a model toolbox for policy analysis. In particular, we seek to i) develop and enhance IDM models, ii) estimate and calibrate these models, and iii) improve the exploitation of available agricultural and biophysical data. In this process, MIND STEP draws on state of the art econometric and innovative machine learning techniques and closely cooperates with various stakeholders to co-create and apply the MIND STEP model toolbox to selected regional, national and EU wide policy cases.

IAMO contributes to MIND STEP by leading work package 6 (Validation and policy evaluation) and by the provision of the agent-based models AgriPoliS and FarmAgriPoliS. As part of MIND STEPs model toolbox, these models can be applied towards relevant policy questions, will be further developed, and (potentially) linked with other models used by partners.

• Coordination: Wageningen University & Research (WUR), The Netherlands
• Norwegian Institute of Bioeconomy Research (NIBIO)
• Johann Heinrich von Thünen Institute Federal Research Institute for Rural Areas, Forestry and Fisheries
• Rheinische Friedrich-Wilhelms-Universität Bonn
• International Institute for Applied Systems Analysis (IIASA)
• Geonardo Environmental Technologies Ltd.
• French National Institute for Agricultural Research (INRA), Bordeaux-Aquitaine Centre, France
• Università Cattolica del Sacro Cuore
• JRC - Joint Research Center - European Commission

• EU Horizon 2020

This project has received funding from the European Union's research and innovation programme (Call: H2020-RUR-2018-2, Program: H2020-EU.3.2.1.3., Grant Agreement No. 817566).