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MIND-STEP (2019-2023) - Modelling Individual Decisions to Support the European Policies Related to Agriculture
The 4-year Horizon 2020 project MIND-STEP (770747, 2019-2023) - Modelling Individual Decisions to Support the European Policies Related to Agriculture, funded by the EU, aims to improve exploitation of available agricultural and biophysical data and will include the individual decision making (IDM) unit in policy models.
Objectives of the project:
- To develop a highly modular and customizable suite of Individual Decision Making (IDM) models focusing on behaviour of individual agents in the agricultural sector to better analyze impacts of policies
- To develop linkages between the new IDM models and current models used at the European Commission to improve the consistency and to broaden the scope of the analysis of policies
- To develop an integrated data framework to support analysis and monitoring of policies related to agriculture
- To apply the MIND STEP model toolbox to analyze regional and national policies and selected EU CAP reform options and global events affecting the IDM farming unit, working together with policymakers, farmers and other stakeholders
- To safeguard the governance and future exploitation of the MIND STEP model toolbox
- John Helming, WUR, The Netherlands (coordinator)
- 11 partners from seven countries in Europe (The Netherlands, Germany, Austria, Italy, France, Spain, Norway and Hungary)
More information on the MIND-STEP project can be found at its home page.
The Economic and Agricultural Policy group contributes by its expertise in analyzing linkages and realizing integration between IDM models and large scale models. We are leading work package 4 (Development of models focusing on interaction between farmers and along agents of the supply chain). Our expertise in machine learning (ML) will be applied to integrate complex IDMs with Agent-based Models, in order to speed up simulation of large scale models regarding impact of European agricultural policies. Jointly with Economic Modeling of Agricultural Systems Group, we are involved in work package 2 (Data requirements for indicators on European policies related to agriculture and data management), as well as other work packages.
The Economic Modeling of Agricultural Systems group contributes by its expertise in analyzing policy measures with the highly detailed single-farm model FARMDyn and its link to Agent Based Models. We are therefore mostly involved work package 3 on "Development of a modular and customisable suit of models focusing on the Individual Decision Model farming unit" and provide simulated data sets to work package 4 "Development of models focusing on interaction between farmers and along agents of the supply chain". Furthermore, we will continue in MINDSTEP our co-operation in the context of the AGRISPACE model with NILF (Norwegian Agricultural Economics Research Institute).
Economic and Agricultural Policy group:
Ecomnomic Modeling of Agricultural Systems group:
Publications related to the project
Britz, W., Ciaian, P., Gocht, A., Kanellopoulos, A., Kremmydas, D., Müller, M., Petsakos, A., Reidsma, P. (2021): A design for a generic and modular bio-economic farm model, Agricultural Systems 191(June 2021): 103133
Pahmeyer, C., Schäfer, D., Kuhn, T., Britz, W. (2021): Data on a synthetic farm population of the German federal state of North Rhine-Westphalia, Data in Brief,Available online 27 March 2021
Kuhn, T., Enders, A., Gaiser, T., Schäfer, D., Srivastava, A., Britz, W. (2019): Coupling crop and bio-economic farm modelling to evaluate the revised fertilization regulations in Germany, Agricultural Systems, Link.
Kuhn, T., Schäfer, D., Holm-Müller, K., Britz, W. (2019): On-farm compliance costs with the EU-Nitrates Directive: A modelling approach for specialized livestock production in northwest Germany, Agricultural Systems 173: 233-243, Link.
Mittenzwei, K., Britz, W. (2018): Analysing Farm-specific Payments for Norway using the Agrispace Model, Journal of Agricultural Economics 69(3): 777-793, Link.
Last updated: Thursday, April 30, 2020
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