As governments and institutions rethink what it means to build economies that are fair, just, and aligned with planetary limits, modelling becomes a critical tool for navigating this transition. To contribute to that discussion, in June 2025, MERGE’s partners, supported by sibling projects MAPS and ToBe, organised a workshop on modelling a just and sustainable economy in collaboration with the European Commission (EC)’s staff, the Joint Research Council (JRC)’s researchers and ecological economists.
The workshop aimed to explore how existing models capture and represent core sustainability challenges through multiple methodological lenses. A common objective for EC analysts and external researchers was to arrive at a more complete and nuanced picture of the possible futures outcomes, in view of inherent and fundamental uncertainties, that better informs policy making.
Why modelling matters for sustainable and inclusive wellbeing (SIW)
Building a just and sustainable economy requires decisions and policies that hold a long horizon. Those choices depend on how we understand the economy and on how we estimate its behaviour under a given set of circumstances. One tool for this estimation is economic modelling.
Modelling is best thought of as evidence-informed “what-if” analysis: What if carbon prices rise? What if we expand public transport or introduce a Basic Income? What if clean technologies diffuse faster than expected? But this is only one part of the story. Models can also be used to analyse or quantify specific mechanisms, uncover the structural drivers behind aggregate behaviour, and develop projections, whether by extending current trends or simulating alternative future scenarios. Economic models make these tasks possible by simulating complex systems under a structured set of relationships between a manageable number of parameters.
For policymakers, models function as diagnostic tools that test potential policies, help quantify trade-offs, and reveal how different groups in society might be affected, among other things. Rather than predicting the future with utmost certainty, economic models offer possible pathways with detailed information that can be used to make informed choices. This said, modelling results depend on the underlying assumptions that are built into them.
Thus far, models based on optimisation (maximisation or minimisation of an objective such as welfare or cost, respectively) have been most commonly in use. Over the years, these models have become increasingly more complex and dynamic, addressing concerns with inequalities, distributional effects and ecological ceilings. Research has further pointed out that modelling tools based on simulation and systemic feedback could also provide policy foresight, especially with respect to the multiple frontiers of sustainable and inclusive wellbeing. The workshop was, therefore, meant to bring together different schools of modelling thought to explore paths for mutual learning and advancement.
What the room agreed on: broadening the toolbox
In the workshop, the discussion spanned various themes: from how to represent ecological feedback and biophysical limits in models, to how models can account for a wider set of social parameters, such as time-use and the skill levels required for the green transition. Researchers and policy experts reached a clear consensus: no single model can capture the complexity of a just and sustainable economy. Different theoretical approaches illuminate different aspects of economic and social systems while also carrying distinct blind spots.
As an illustration:
- E-QUEST is a dynamic general equilibrium model developed by the Directorate‑General for Economic and Financial Affairs (DG ECFIN) of the EC to assess the macroeconomic impact of climate policy. It represents multiple sectors through input–output linkages, accounts for emissions from fossil fuel combustion and industrial processes, and features nonlinear transition simulations (e.g., large shocks). The model is used to analyse, for example, the impacts and implications of achieving the 2050 net-zero EU targets, and to assess pathways to address high energy prices resulting from the renewables transition. As part of a broader ecosystem of modelling tools used at the Commission, E-QUEST helps estimate various macroeconomic trade-offs, sectoral shifts, and dynamic responses to policy options across multiple economic sectors and population groups by reaching a new cross-market equilibrium.
- COMPASS, developed by the University of Barcelona, takes a different approach. It combines a stock-flow-consistent, Post-Keynesian (demand-driven) macroeconomic core with a multi-sector, environmentally extended input-output structure within a system-dynamics framework. In other words, the model dynamically simulates national-level social, environmental, and economic outcomes for a range of policies and future pathways. COMPASS is designed to holistically assess the impact of (national) policy choices on human wellbeing and ecological sustainability, and to support the development of national transition strategies that meet people’s needs while keeping resource use and pollution within safe limits. It integrates environmental and social indicators inspired by the Doughnut framework and allows testing of diverse policy options (e.g., worktime reduction, carbon tax) across different sustainability visions (including green growth and post-growth).
Many other models, such as EUROGREEN, GEM-3E, RHOMOLO, EUDOMOD, and iSDG, were also presented with their implications and findings discussed. This wide assortment of modelling approaches was deliberately sought, as relying on a limited set of modelling techniques and assumptions risks missing important dynamics and possible outcomes and providing a weaker basis for informing policy and long-term foresight.
It is mutually enriching to bring together modellers from different paradigms who are united by a shared goal: improving modelling for sustainable and inclusive wellbeing. Through open-minded discussions that moved beyond silos, the workshop emphasised that diversity in modelling techniques should not be treated as a barrier, but as an advantage, even when the outcomes of different modelling approaches are qualitatively different. A diverse portfolio of modelling approaches, insofar as they are suitable for the issue at hand, can offer a more complete picture of possible future outcomes and thus contribute to more comprehensive and resilient policy design amidst fundamental uncertainty.
The open questions: what can (and can’t) models tell us?
Besides the broad agreement, participants in the workshop also posed critical questions around the overarching topic of SIW in modelling. Here, we highlight three key dimensions.
1. How much narrow or broad, simple or complex is appropriate for a given policy question?
Policymakers often face choices along two axes when selecting models: narrow vs. broad scope and simple vs. complex design. Narrow-scope models can provide highly detailed insights but they leave out important dynamics that lie outside their focus. Broad-scope models, by contrast, capture interactions across the entire socioeconomic system and the biosphere, revealing interdependencies and risks that narrower models may miss. At the same time, simpler models tend to be more transparent and easier to interpret, whereas more complex models can incorporate richer dynamics but may be harder for decision-makers to fully understand or apply to specific sectors or groups. Determining the “right” balance across these two axes remains an open design choice that must be assessed case by case.
2. How should biophysical feedbacks and planetary boundaries be represented in economic models?
There is no consensus on how best to incorporate ecological constraints such as biodiversity loss, land-use change, or natural resource depletion. Key questions include how to quantify parameters that are not easy to translate into monetary terms, and how to integrate them into economic dynamics. Different approaches can produce very different assessments of long-term sustainability.
3. Which theoretical foundations should guide modelling choices?
Models grounded in, for example, Post-Keynesian demand-led frameworks or ecological economics incorporate different ground assumptions respective to the school or branch of economics they stem from. Different branches and methodologies offer valid but contrasting views of how economies behave. Different underlying assumptions then lead to different policy interpretations. Choosing the most appropriate theoretical approach for a given policy context remains an open, and sometimes contested, issue.
Ways forward: from model competition to model cooperation
The group outlined a few practical steps toward a more plural, open, and policy-relevant modelling ecosystem that can support achieving the goal of sustainable and inclusive wellbeing:
1. Use multiple lenses
Combine different economic models to gather insights on economic efficiency, social equity, and ecological resilience. Doing so requires a willingness to work across modelling paradigms and accept that different theories will highlight different (and sometimes conflicting) truths.
2. Build bridges between modelling teams
Encourage open-source code, shared datasets, and cross-DG or cross-ministry workshops to reduce duplication and bridge disciplinary divides. Modelling “communities” are often siloed, each with its own assumptions and incentives, but structured collaboration can illuminate and shrink blind spots.
3. Run “model intercomparison” exercises
As suggested in the workshop, systematically testing the same scenario across different models should become standard practice. This allows policymakers to evaluate how assumptions shape results: convergence across models builds confidence, while divergence highlights uncertainties and areas where further inquiry is needed. Intercomparison requires institutional support and resources, but it is one of the most effective ways to explore the impact of varied policy options under deep uncertainty.
4. Keep the purpose in sight
Ultimately, models are decision-support tools, not ends in themselves. Models should be judged by how well they help societies navigate uncertainty, balance fairness with feasibility, and design effective policy. A purpose-driven approach keeps modelling debates from devolving into technical competition and focuses attention on the real-world outcomes that matter.
The bigger picture
Bringing these threads together, the workshop emphasised that the future of modelling for sustainable and inclusive wellbeing lies not in perfecting any single tool but in cultivating a richer modelling ecosystem and inclusive and open-minded conversations between modelling teams. Several Horizon Europe initiatives such as MAPS, ToBe, WISE Horizons and MERGE are already advancing this agenda by building on established methods while integrating a holistic set of environmental, social, and economic indicators. Strengthening and supporting such initiatives will be essential for equipping policymakers with the tools needed to shape resilient, fair, and forward-looking policies in the years ahead.
