Periodic Reporting for period 3 - MIND STEP (Modelling INdividual Decisions to Support The European Policies related to agriculture)
Reporting period: 2023-01-01 to 2023-12-31
MIND STEP: Accounting for farm-level decision making in policy design and analysis
The Horizon 2020 project MIND STEP (Modelling INdividual Decisions to Support The European Policies related to agriculture) aimed to support public decision making in agricultural, rural, environmental, and climate policies taking into account the behaviour of individual decision making (IDM) units in agriculture and the rural society. MIND STEP focussed on individual decision making processes at farm level.
Agricultural policies are supposed to address an increasing number of environmental and societal objectives. At the same time, the CAP moves further in the direction of farm specific measures and a stronger target-orientation. To facilitate the change away from the current ‘one size fits all’ approach, Member States are given more flexibility to develop their own CAP strategic plans, which should define measurable objectives and means to achieve them. Currently applied models at the European Commission are not able to assess impacts for individual farms as they are specified at higher levels of aggregation. The wider scope and the focus on measures targeting individual farmers ask for a new generation of impact assessment tools. In impact evaluations, much more attention has to be paid to the way the CAP is locally and regionally implemented.
For these reasons, MIND STEP developed a suite of models for assessing agricultural, rural, environmental, and climate policies by taking into account the behaviour of IDM units in agriculture and the rural society. Linking these IDM models with currently applied models used at the EU not only improved the consistency but also broadens the scope of policy analyses and impact assessment for efficient policy design.
The Horizon 2020 project MIND STEP (Modelling INdividual Decisions to Support The European Policies related to agriculture) aimed to support public decision making in agricultural, rural, environmental, and climate policies taking into account the behaviour of individual decision making (IDM) units in agriculture and the rural society. MIND STEP focussed on individual decision making processes at farm level.
Agricultural policies are supposed to address an increasing number of environmental and societal objectives. At the same time, the CAP moves further in the direction of farm specific measures and a stronger target-orientation. To facilitate the change away from the current ‘one size fits all’ approach, Member States are given more flexibility to develop their own CAP strategic plans, which should define measurable objectives and means to achieve them. Currently applied models at the European Commission are not able to assess impacts for individual farms as they are specified at higher levels of aggregation. The wider scope and the focus on measures targeting individual farmers ask for a new generation of impact assessment tools. In impact evaluations, much more attention has to be paid to the way the CAP is locally and regionally implemented.
For these reasons, MIND STEP developed a suite of models for assessing agricultural, rural, environmental, and climate policies by taking into account the behaviour of IDM units in agriculture and the rural society. Linking these IDM models with currently applied models used at the EU not only improved the consistency but also broadens the scope of policy analyses and impact assessment for efficient policy design.
From September 2018 to January 2024 MIND STEP has developed tools and models at different scales to do exactly this: monitor and assess policies related to agriculture and take aspect of individual decision-making into account. In describing and modelling the complexities and ever-evolving landscape of agriculture the MIND STEP project has contributed to innovations and progress in:
- Better representation of the diversity of farms heterogeneity in modeling
- Modelling interactions between farms
- Improved interfaces between data and models at different scales (farm, regional, national, EU)
- Transparency of methods, sustainable software development and model validation
MIND STEP has developed detailed bio-economic, farm level, mathematical programming and econometric optimisation and simulation models. These models are firstly based on individual farm data from the EU Farm Accountancy Data Network (FADN). Econometric activity-based cost accounting tools have been developed to assign different cost components in the EU FADN from the farm to the agricultural activity level. In a second stage, MIND STEP has developed tools to combine farm level data (FADN) with biophysical data. Using biophysical data, MIND STEP among other developed probabilities regarding spatial allocation of representative farms in the EU FADN and improved grassland yield response curves using remote sensing data. Surveys have been conducted to combine statistical data with socio-psychological data helping to understand individual farmers preferences, behavior and adoption of risks. In particular the concept of modularity for the design of a core bio-economic farm model has received substantial attention in MIND STEP as it is crucial for the combined use of rather complex analytical tools at farm level in different contexts. The addressed challenges in this area were, among others, to define basic functionalities of a core bio-economic farm model (BEFM), to facilitate and regulate the communication of the involved researchers, and establishing standards for computer codes and interfaces between models in the MIND STEP model toolbox. Besides individual farm models, MIND STEP also developed innovative Agent Based Models (ABMs) including interaction between individual farms e.g. used to explain farm exit and adoption of Agri-Environmental Schemes. The development of machine-learning-based surrogate models, allowed efficient and consistent integration of detailed farm models in an ABM, capturing structural change implications of policies for the farm population. This is an important step towards upscaling of agent-based models to larger regions that is normally restricted by computation time. MIND STEP made important contributions to improved micro-economic underpinnings of models at various scales, frequently used by the European Commission for assessments of policies related to agriculture. As a roadmap, MIND STEP gained important experiences in the field of a) validation and proof of concept, b) importance of stakeholder workshops and c) policy evaluation.
- Better representation of the diversity of farms heterogeneity in modeling
- Modelling interactions between farms
- Improved interfaces between data and models at different scales (farm, regional, national, EU)
- Transparency of methods, sustainable software development and model validation
MIND STEP has developed detailed bio-economic, farm level, mathematical programming and econometric optimisation and simulation models. These models are firstly based on individual farm data from the EU Farm Accountancy Data Network (FADN). Econometric activity-based cost accounting tools have been developed to assign different cost components in the EU FADN from the farm to the agricultural activity level. In a second stage, MIND STEP has developed tools to combine farm level data (FADN) with biophysical data. Using biophysical data, MIND STEP among other developed probabilities regarding spatial allocation of representative farms in the EU FADN and improved grassland yield response curves using remote sensing data. Surveys have been conducted to combine statistical data with socio-psychological data helping to understand individual farmers preferences, behavior and adoption of risks. In particular the concept of modularity for the design of a core bio-economic farm model has received substantial attention in MIND STEP as it is crucial for the combined use of rather complex analytical tools at farm level in different contexts. The addressed challenges in this area were, among others, to define basic functionalities of a core bio-economic farm model (BEFM), to facilitate and regulate the communication of the involved researchers, and establishing standards for computer codes and interfaces between models in the MIND STEP model toolbox. Besides individual farm models, MIND STEP also developed innovative Agent Based Models (ABMs) including interaction between individual farms e.g. used to explain farm exit and adoption of Agri-Environmental Schemes. The development of machine-learning-based surrogate models, allowed efficient and consistent integration of detailed farm models in an ABM, capturing structural change implications of policies for the farm population. This is an important step towards upscaling of agent-based models to larger regions that is normally restricted by computation time. MIND STEP made important contributions to improved micro-economic underpinnings of models at various scales, frequently used by the European Commission for assessments of policies related to agriculture. As a roadmap, MIND STEP gained important experiences in the field of a) validation and proof of concept, b) importance of stakeholder workshops and c) policy evaluation.
The MIND STEP project offered the unique opportunity to develop and include a new set of IDM models and tools that can be linked to a core farm-level model in a modular way. This resulted in more realistic policy assessment and design, beyond the state of the art. Selected policy evidence collected by the project are the following:
- Cost efficient policies affecting heterogenous farms require that policy measures are differentiated per individual farm taking into account farm specific characteristics and short and long-term farm management and investment options.
- Farmers tend to be efficient from a technical viewpoint given their current production technologies.
- Farmers respond to economic incentives (even if their responsiveness display significant heterogeneity), implying that economic policy instruments could be useful for achieving the objectives of the EU Green Deal
- A combination of emission taxations along with subsidies on mitigation technologies may be a suitable approach to mitigate extreme agricultural income and price effects, although environmental improvements will be dampened as well.
- A gradual implementation of emission taxes would allow farmers and markets time to invest and adjust.
- If a subsidy scheme on emission reduction is chosen, a gradual implementation is advised to find the optimal subsidy levels to circumvent overcompensation of income.
- Re-evaluation of the farm specific base GHG emission levels over time would result in an eventual phasing-out of the emission tax and emission reduction subsidy once the reduction potential has been reached.
- Risk behavior (loss aversion, use of heuristics) contributes to low insurance uptake of risk management instruments in case of yield variations under extreme weather events. It is advised to improve communication of risks (reframing of probabilities) and support multi-year contracts
- Cost efficient policies affecting heterogenous farms require that policy measures are differentiated per individual farm taking into account farm specific characteristics and short and long-term farm management and investment options.
- Farmers tend to be efficient from a technical viewpoint given their current production technologies.
- Farmers respond to economic incentives (even if their responsiveness display significant heterogeneity), implying that economic policy instruments could be useful for achieving the objectives of the EU Green Deal
- A combination of emission taxations along with subsidies on mitigation technologies may be a suitable approach to mitigate extreme agricultural income and price effects, although environmental improvements will be dampened as well.
- A gradual implementation of emission taxes would allow farmers and markets time to invest and adjust.
- If a subsidy scheme on emission reduction is chosen, a gradual implementation is advised to find the optimal subsidy levels to circumvent overcompensation of income.
- Re-evaluation of the farm specific base GHG emission levels over time would result in an eventual phasing-out of the emission tax and emission reduction subsidy once the reduction potential has been reached.
- Risk behavior (loss aversion, use of heuristics) contributes to low insurance uptake of risk management instruments in case of yield variations under extreme weather events. It is advised to improve communication of risks (reframing of probabilities) and support multi-year contracts