Description du projet
Garantir la viabilité de la PAC de l’UE
La future politique agricole commune (PAC) de l’Union européenne joue un rôle essentiel dans le développement d’un secteur agricole durable. La future PAC sera plus flexible et adaptée aux besoins des États membres de l’UE et aux unités de prise de décision individuelle du secteur. Pour y parvenir, les États membres développent des plans stratégiques pour la PAC qui devraient définir des objectifs quantifiables et les moyens de les atteindre. Le projet MIND STEP, financé par l’UE, utilisera des données agricoles et biophysiques et intégrera une unité de prise de décision individuelle dans de nouveaux modèles politiques et dans ceux qui sont déjà en place, afin de réaliser des analyses d’impact. En recourant aux statistiques agricoles et aux grands ensembles de données, les nouveaux modèles de prise de décision individuelle seront évalués et calibrés, en s’appuyant sur des techniques économiques et d’apprentissage automatique évolutif.
Objectif
Agricultural policies like the EU CAP are widening the scope to contribute to the Paris climate agreement and the Sustainability Development Goals. From the Commission's legislative proposals (June 2018) it is expected that the European Union (EU) Common Agricultural Policy (CAP) will be redesigned in line with this. Consequences are among others a move of the CAP to farm specific measures and an improved link to environment, climate change and ecosystem services. It is proposed that Member States and regions develop their own CAP strategic plan with more attention to the regional implementation of the CAP. This wider scope and measures with a focus on individual farmers ask for a new generation of impact assessment tools. Current state-of-the-art agricultural models are not able to deliver individual farm and local effects as they are specified at higher levels of aggregation. Making use of improved possibilities opened up by progress in the ICT area, our project MIND STEP will improve exploitation of available agricultural and biophysical data and will include the individual decision making (IDM) unit in policy models. Based on a common data framework MIND STEP will develop IDM models, including agent-based models, focussing on different topics in an integrated manner in different regional case studies. The IDM models will be estimated and calibrated using agricultural statistics and big datasets, drawing on established econometric and evolving machine learning techniques and using both traditional models of optimising behaviour and theories from behavioural economics. MIND STEP will closely cooperate with a range of stakeholders to co-create and apply the MIND STEP model toolbox to selected regional, national and EU wide policy cases. MIND STEP cooperates with other consortia under the topic to share ideas and innovations. Finally, MIND STEP develops an Exploitation Strategy and Plan to guarantee the sustainability of the project results upon its completion.
Champ scientifique
- social scienceseconomics and businesseconomics
- natural sciencesbiological sciencesecologyecosystems
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Mots‑clés
Programme(s)
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Régime de financement
RIA - Research and Innovation actionCoordinateur
6708 PB Wageningen
Pays-Bas