Project
MIND STEP - Modelling INdividual Decisions to Support The European Policies related to agriculture
MIND STEP - Modelling INdividual Decisions to Support The European Policies related to agriculture
MIND STEP addresses the Work Programme Topic RUR-04-2018-2019, contributing to Rural Renaissance by further developing analytical tools and models to support policies related to agriculture and food.
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.
Background and Objective
PROJECT OBJECTIVES
The overall ambition of MIND STEP is to support public decision making in agricultural, rural, environmental and climate policies, taking into account the behaviour of individual decision-making units in agriculture and the rural society.
The MIND STEP specific objectives are
- to develop a highly modular and customisable suite of Individual Decision Making (IDM) models focussing on behaviour of individual agents in the agricultural sector to better analyse 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 analyse 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.
INTENDED IMPACTS
- improvement of the capacity to model policies dealing with agriculture and related natural resources, food and international trade
- improvement of policy design, impact assessments and monitoring
- strengthened transdisciplinary research and integrated scientific support for relevant EU policies and priorities.
Approach
In MIND STEP three working groups of the Thünen Institute are part of this project.
One group of Thünen Institute of Farm Economics is working on data requirements for indicators on European policies related to agriculture and data management:
- Collects and reviews data requirements from all partners and develops with other partners a guide for building data interfaces
- The guide addresses beside conceptual implementation also the technical programming environment, the software production cycle, the integration into the MIND STEP model toolbox
- Develop and apply approaches to match economic and biophysical data sets
and farm structural change:
- The improvement of farm exit decisions in current models by developing and estimating innovative empirical models based on geo-referenced, bio-physical and single-farm data
- Develop and implement a structural change/strategic behaviour/farm exit module
- Results from exit estimations will be employed to improve the Agrispace model and/or for the land market module of the IFM-CAP model
Another group of Thünen Institute of Farm Economics is working on influence of risk in agricultural production. The aim is to improve capacity to model the uptake and the impacts of (policy) risk management instruments at the farm level. The potential of different behavioural theories to improve the modelling of the adoption of different risk management instruments will be analysed. The empirical application will focus on weather risk in crop farms. The analysis will combine new survey data with existing regional and farm data.
The team of Thünen Institute of Market Analysis is working on ...
Data and Methods
Main data sources:
- Farm accountancy data
- Farm structure survey data
- Several weather, climate and soil data
- Agricultural prices
- Survey data on farmers decision behaviour
Methods:
- Regression models (OLS and logit models)
- Machine learning algorithms
- Selection models
- Behavioural theories on risk decision making
Our Research Questions
- What explains farm exit?
- Which role plays spatial distribution?
- How is risk influencing production decisions?
- What are drivers of farm structural change?
Links and Downloads
www.mind-step.eu
https://twitter.com/MindstepP
Thünen-Contact
Involved Thünen-Partners
- Banse, MartinMA Institute of Market Analysis
- Duden, ChristophBW Institute of Farm Economics
- Neuenfeldt, SebastianBW Institute of Farm Economics
- Offermann, FrankBW Institute of Farm Economics
- Salamon, PetraMA Institute of Market Analysis
- Stepanyan, DavitBW Institute of Farm Economics
- Yang, XinxinBW Institute of Farm Economics
Involved external Thünen-Partners
-
Rheinische Friedrich-Wilhelms-Universität Bonn
(Bonn, Deutschland) - Wageningen University & Research (WUR)
(Wageningen, Niederlande) -
Institut national de recherche pour l’agriculture, l’alimentation et l’environnement (INRAE)
(Paris, Toulouse, Montpellier, Avignon, Ivry-sur-Seine, Clermont-Ferrand, Rennes, Thiverval-Grignon, Dijon, Orleans, Bordeaux, Pierroton, Frankreich) - International Institute for Applied Systems Analysis (IIASA)
(Laxenburg, Österreich) - Leibniz-Institut für Agrarentwicklung in Transformationsökonomien
(Halle, Deutschland) - Universita Cattolica del Sacro Cuore
(Mailand, Italien) - Wageningen University & Research (WUR)
(Wageningen, Niederlande) - Joint Research Centre (JRC)
(Brüssel, Belgien) -
Geonardo
(Budapest, Ungarn) - Institute for Rural and Regional Research
(Trondheim, Norwegen)
Duration
9.2019 - 12.2023
More Information
Project status:
finished
Publications to the project
- 0
Perez Soba M, Helming J, Müller M, Krisztin T, Appel F, Addo F, Bardazzi E, Frank S, Hinkel N, Kremmydas D, Kristkova Z, Vicario DR, Scherer H, Sckokai P, Stepanyan D, Varacca A (2024) MIND STEP Deliverable D 6.4: Policy evaluation. 102 p
- 1
Neuenfeldt S, Gocht A, Mittenzwei K (2023) MIND STEP Deliverable D 4.2: Report on modelling structural change and farm interaction on land markets and interfaces with the MIND STEP model toolbox (M36+4). 93 p
- 2
Gocht A, Neuenfeldt S (2021) MIND STEP Deliverable D 2.1: Summary of required data from WP 3/4/5. 19 p
- 3
Gocht A, Neuenfeldt S, Yang X, Müller M, Helming JF, Roerink G, Sander J, Oudendag D, Kremmydas D, Brouwer A (2021) MIND STEP Deliverable D 2.2: A guide/handbook to build an interface for accessing the data in the project required by partners WP 2-6. 117 p
- 4
Gocht A, Neuenfeldt S (2021) MIND STEP Deliverable D 2.4: Prototype for interfaces. 27 p
- 5
Gocht A, Neuenfeldt S (2021) MIND STEP Deliverable D 2.5: Final version for interfaces. 57 p
- 6
Rieger J, Gocht A, Leip A (2021) MIND STEP Deliverable D 2.6: Literature review of methods for linking economic and bio-physical databases. 18 p
- 7
Neuenfeldt S, Gocht A, Heckelei T, Mittenzwei K, Ciaian P (2021) Using aggregated farm location information to predict regional structural change of farm specialisation, size and exit/entry in Norway agriculture. Agriculture 11(7):643, DOI:10.3390/agriculture11070643
- 8
Neuenfeldt S, Gocht A (2019) MIND STEP Deliverable D 7.3: List of data storage and processing capacities required by partners WP 2-6. 11 p