MIND STEP: Modelling Individual Decisions to Support the Europan Policies related to Agriculture (H2020)

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MIND STEP: Modelling Individual Decisions to Support the Europan Policies related to Agriculture (H2020)

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.

Coordinated by Stichting Wageningen Research (The Netherlands) the consortium includes 11 partners from 8 countries.

Further information can be found on the project's online channels
- project website: https://mind-step.eu/
- Twitter: https://twitter.com/MindstepP/
- Linkedin: https://www.linkedin.com/in/mind-step-project/
- Cordis factsheet of the project: https://cordis.europa.eu/project/rcn/223209/factsheet/en

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement Nr. 817566.

Date: 1 September 2019 - 31 August 2023

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Curated by:
drbalazskatalin
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This community collects uploads from the MIND STEP H2020 project. The uploads need to contain the EU acknowledgement as follows:

"This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement Nr. 817566."

Created:
October 2, 2019
Harvesting API:
OAI-PMH Interface

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