Future agricultural policy assessment cannot rely on a single policy instrument, impact category or modelling perspective. A change in agricultural policy can affect production and farm income while also influencing prices, trade, land use, environmental pressures, consumption and wider economic activity. The effects can also vary according to Member State implementation, uptake, compliance, administrative conditions and market responses.
The post-2027 CAP adds further complexity because policy choices involve interacting objectives and policy instruments, while their implementation remains subject to national and regional conditions. External developments—including climate and biodiversity objectives, technological change, trade and geopolitical developments, demographic trends, health-related concerns and budgetary constraints—can also influence the context in which agricultural policies operate.
KER-03 addresses this complexity by providing a structured basis for constructing scenarios that make these conditions and interactions explicit. It supports analysis of alternative futures without treating scenarios as forecasts or assuming that a single modelling approach can capture every relevant effect.
D1.2 provides a systematic basis for identifying and structuring scenarios for CAP post-2027 analysis. It combines a review of policy developments, external drivers, stakeholder perspectives and modelling capabilities with a detailed assessment of the coverage and limitations of AGMEMOD, CAPRI, GLOBIOM and MAGNET.
The resulting approach starts from the policy question and identifies the policy instruments, external conditions and impact channels that need to be represented. Scenario assumptions can then specify relevant elements such as eligibility, uptake, enforcement, payment design, policy interactions, market conditions and other parameters that condition interpretation.
The approach also recognises that different models capture different parts of the agricultural and food system. AGMEMOD provides dynamic Member State-level market analysis; CAPRI offers detailed EU and spatial representation; GLOBIOM captures global land-use, resource and environmental interactions; and MAGNET provides economy-wide, trade and distributional perspectives. Scenarios can therefore be matched to complementary modelling approaches according to the policy question, geographical scale, time horizon and impact channels concerned.
Five fast-track scenario clusters were identified as early applications:
The scenario framework also explicitly considers spillovers and interactions. Depending on the question, these can include trade-mediated effects, land-use displacement, environmental leakage, changes in production and consumption, distributional effects and interactions between policy instruments.
Where an outcome cannot be represented credibly within the four core models—for example, certain farm-level distributional effects, behavioural responses, administrative feasibility or demographic dynamics—the approach identifies the need for complementary tools or evidence instead of extending the aggregate models beyond their appropriate scope.
KER-03 strengthens the connection between policy questions and the analytical evidence used to examine them.
Its value lies in helping analysts define what a scenario represents, which assumptions determine its interpretation, which models are suited to the relevant impact channels, and where complementary evidence is needed. This provides a more transparent basis for exploring interactions and trade-offs across the agricultural and food system.
The approach also helps keep the distinction between assumptions, modelled effects and areas outside analytical scope visible. This is particularly important for policy questions where implementation conditions and spillovers can materially affect the interpretation of results.
KER-03 can support several user groups:
Policymakers and policy-support organisations can use the scenario structure to formulate and discuss policy questions and explore potential consequences of alternative policy configurations.
Researchers and modelling communities can use it to identify relevant scenario dimensions, match questions with complementary models, define common indicators and identify areas requiring model linkage or additional analytical approaches.
Stakeholders and expert communities can use the scenarios as structured cases for discussing policy assumptions, implementation conditions, potential effects and evidence needs.
Future ACT4CAP27 activities can use the scenario foundation for further modelling, tool development, scenario refinement and integrated assessment.
KER-03 can support the development and analysis of alternative agricultural policy futures, including:
The five fast-track scenario clusters provide concrete examples of how the approach can be applied to different policy questions and impact channels.
The D1.2 foundation is disseminated through the ACT4CAP27 project website and open-access project repositories, together with related scientific, modelling and communication outputs.
Its exploitation also takes place through continued ACT4CAP27 modelling and analytical activities. The scenario approach provides a basis for subsequent scenario applications, model linkages, indicator development and stakeholder engagement. Scenario findings and methodological developments can therefore be communicated through project events, stakeholder activities, scientific outputs and other project dissemination channels.
The scenario-design foundation is established through D1.2 and can already be used as a basis for framing and structuring future policy scenarios.
At the same time, the individual scenario applications are at different stages of development. The five fast-track clusters provide an initial set of applications, while further modelling, data preparation, model linkages, indicator development and validation continue within ACT4CAP27.
D1.2 establishes the scenario-analysis framework and identifies scenario priorities; subsequent ACT4CAP27 work operationalises and extends selected scenarios through modelling and complementary analytical work.
KER-03 can contribute to:
Policy analysis by providing structured representations of alternative policy configurations and their potential interactions.
Modelling practice by supporting clearer matching between policy questions, model capabilities, assumptions and indicators.
Integrated assessment by connecting market, production, trade, land-use, environmental and demand-side perspectives where the relevant analytical approaches can be linked.
Stakeholder dialogue by providing concrete scenarios around which policy assumptions, evidence needs and potential effects can be discussed.
Future scenario development by providing a structured basis for extending the analysis to emerging policy questions and changing implementation conditions.
Stakeholders can contribute to scenario development by discussing the relevance of policy questions, identifying important implementation conditions, reviewing assumptions and indicators, and highlighting interactions or potential effects that should be considered.
This makes the scenarios useful as working analytical cases that can be refined and tested as policy information, evidence and modelling capabilities develop. Stakeholder input can also help identify where additional data, indicators, model linkages or complementary evidence are required.
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