Researchers and practitioners gathered at the Joint Research Centre in Italy to explore how to move beyond GDP and develop operational frameworks for measuring sustainable and inclusive wellbeing.
We joined a group of researchers and practitioners at the Joint Research Centre (JRC) in Ispra, Italy to tackle one of the most pressing questions in global policy: how do we move beyond Gross Domestic Product (GDP) and meaningfully measure Sustainable and Inclusive Wellbeing (SIW)?
As outlined in our workshop recommendations to the UN High Level Expert Group on Beyond GDP, the time for incremental change has passed. We now need coherent, operational frameworks that can guide real world decisions.
Our discussions centred on the following four core challenges.
Reducing dashboards without losing meaning
There are hundreds of indicators related to wellbeing that have been proposed. Our research shows that they all include many of the same metrics, so there is broad agreement on what is important to SIW. But even if we agree on a long list, policymakers cannot realistically manage 100 or more metrics. The key question is how to reduce dashboards to perhaps no more than 20 core indicators without stripping away representativeness. We explored both indicator-based approaches, such as principal component and latent factor analysis, and observation-based approaches, such as clustering comparisons, to test whether smaller sets retain explanatory power. Rather than selecting indicators by intuition alone, we argued for rational validation of any proposed subset.
Aggregating dashboards into indices
Many composite indices rely on simple weighted averages. But wellbeing does not behave linearly. Health, education, environmental quality and social cohesion often display diminishing returns and limiting factor relationships. Linear aggregation risks distorting country rankings and masking structural weaknesses. We highlighted non-linear and partially compensatory approaches, including methods that account for ecological constraints, such as the Planetary pressure adjusted HDI. Our recommendation was clear: the HLEG should not shy away from creating an overall SIW index simply because methods are contested. Instead, it should convene further technical work to build consensus around robust, non-linear aggregation approaches.
Measuring wellbeing efficiency
Shifting from a growth paradigm to a development paradigm requires asking not “How much?” but “How well?” SIW efficiency measures how effectively societies convert economic, social, and environmental resources into SIW outcomes. Crucially, efficiency is not the same as sustainability, and both must be evaluated separately. A comprehensive SIW framework would allow countries to assess trade-offs, spillovers and institutional differences, and to identify investments that yield the highest wellbeing returns.
Global geospatial mapping
Perhaps the most transformative discussion focused on spatial data and machine learning. With existing technology, it is now possible to generate high resolution, regularly updated SIW estimates globally. This could address data gaps, enable subnational analysis, and bring SIW measurement to a level of timeliness and rigor comparable to GDP. We recommended expanding collaboration between JRC, UNDP, UNCTAD, DESA and OECD, potentially through a dedicated Knowledge Centre, to advance global geospatial SIW mapping.
These recommendations are not purely academic. They reflect a growing recognition that measurement shapes policy. What we count determines what we prioritise.
This is also where education becomes essential. At the UCL Institute for Global Prosperity’s Prosperity, People and Planet MSc, we train students to grapple with exactly these challenges, connecting Earth system science, ecological economics, governance innovation and data analytics to redesign metrics of progress. The workshop’s themes, non-linear systems, efficiency thinking, spatial modelling and institutional design, sit at the heart of the PPP curriculum. Tomorrow’s policymakers and researchers must be fluent not only in critique of GDP, but in building the next generation of SIW indicators.
Moving beyond GDP is no longer a rhetorical ambition. With advances in data science, systems modelling and interdisciplinary collaboration, it is now technically and institutionally possible. The real question is whether we can generate the collective will to implement it.
Researchers from the Joint Research Centre have prepared a set of recommendations for the UN High Level Expert Group on Beyond GDP, available here.
