Project description
Guaranteeing the sustainability of the EU CAP
The European Union’s future Common Agricultural Policy (CAP) plays a pivotal role in developing a sustainable agricultural sector. The future CAP will be more flexible and adaptable to the needs of EU Member States and the individual decision making (IDM) units in the sector. To achieve this Member States develop strategic plans for the CAP that should define measurable objectives and means to achieve them. The EU-funded MIND STEP project will make use of agricultural and biophysical data and include individual decision making (IDM) unity in new and existing policy models for impact assessments. Using agricultural statistics and big datasets, the new IDM models will be estimated and calibrated, drawing on established economic and evolving machine learning techniques.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- 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
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Keywords
Programme(s)
Topic(s)
Call for proposal
(opens in new window) H2020-RUR-2018-2020
See other projects for this callSub call
H2020-RUR-2018-2
Funding Scheme
RIA - Research and Innovation actionCoordinator
6708 PB Wageningen
Netherlands