Can we project well-being? Towards integral well-being projections in climate models and beyond

The paper addresses the lack of long-term projections for beyond-GDP indicators, despite their importance in measuring genuine societal development. While GDP projections are common, projections for indicators like the HDI are scarce, limiting policy relevance. The study emphasizes the need to understand future well-being trajectories, not just past trends. The authors highlight the limitations of GDP as a sole measure of societal progress, neglecting sustainability, inequality, and overall well-being. Various beyond-GDP indicators have been developed, including the HDI, GPI, U-index, subjective well-being measures, comprehensive wealth indicators, ecological footprints, Sustainable Development Goals, and planetary boundaries. Despite their existence, GDP remains dominant in forecasting and policy-making. The paper points to a critical knowledge gap: the absence of forward-looking projections for these beyond-GDP indicators. While some studies have begun projecting such indicators, integrating environmental changes' feedback into long-term well-being projections remains a significant challenge. The research aims to project countries' HDIs and explore climate change's impact on well-being, using the HDI as a widely accepted beyond-GDP indicator, and leveraging the SSP framework developed by the IPCC.

The paper reviews existing literature on beyond-GDP indicators and their limitations in long-term projections. It highlights studies demonstrating the potential of projecting beyond-GDP indicators and shows the importance of considering the synergies and trade-offs between climate change, population, economy, and well-being. The literature review also synthesizes how air pollution and climate change affect the three dimensions of the HDI (health, education, and income), drawing upon studies quantifying these impacts and providing evidence for the necessity of incorporating these environmental feedback effects into well-being projections.

The methodology consists of two parts: (1) HDI projection based on SSPs, and (2) a literature review to assess environmental impacts. Part 1 projects the HDI for 161 countries from 1970 to 2100 using SSPs 1-5. This involves calculating country-level HDIs based on life expectancy, mean years of schooling, and GDP per capita projections from the SSP database. The Gini coefficient is used to assess global well-being inequality, and a decomposition analysis quantifies the contributions of each HDI dimension to well-being changes over time. Part 2 employs a systematic snowballing literature review to synthesize how air pollution and climate change affect health, education, and income. This qualitative assessment is informed by IAM-SSP baseline runs showing trends in air pollutants (black carbon, SO2, and NO2) and global mean temperature. The findings from the literature review are then integrated into the initial HDI projections to provide a preliminary re-assessment, considering environmental feedback effects.

The study projects three distinct global well-being trajectories under the five SSPs. SSP1 (Sustainability) and SSP5 (Fossil-Fueled Development) show significant well-being improvement by 2100, reaching very high levels. SSP2 (Middle of the Road) achieves high well-being, while SSP3 (Regional Rivalry) and SSP4 (Inequality) show slower growth and reach only medium well-being levels by 2100. Decomposition analysis reveals education as the primary driver of well-being improvement in the earlier decades (2015-2055) for SSP1 and SSP5, with health becoming increasingly important in later decades. In SSP3 and SSP4, education is the main driver in the earlier period, but its stagnation in 2060-2100 leads to stagnant well-being. Regarding inequality, the study finds that between-country well-being inequality continues to decline under SSP2 and improves at an accelerated rate under SSP1 and SSP5, primarily due to improvements across all three HDI dimensions. However, under SSP3 and SSP4, inequality improvements are modest and could reverse the historical declining trends in health and income, largely due to slow development in poorer countries and reduced convergence among developed countries. Country-level analysis shows well-being improvements in all countries by 2100, but the extent of improvement varies significantly across SSPs. SSP1 and SSP5 show most developing countries reaching high well-being levels, while SSP3 and SSP4 leave many African countries at low well-being levels. The analysis of air pollution and climate change impacts reveals substantial variations across SSPs in global mean temperature rise and air pollution levels. The literature review shows negative impacts on health (increased mortality, diseases), education (reduced attendance, impaired performance), and income (reduced productivity, crop yields, capital losses). A preliminary assessment of the neglected well-being impacts, based on the literature and projected trends under SSPs, suggests significant variation in impacts across different SSPs, with some counterintuitive results (e.g., SSP5 showing the best SO2 improvement due to technological advancements).

The study's findings highlight the importance of integrating climate change feedback effects into well-being projections. The paradoxical similarity in HDI trajectories for SSP1 and SSP5, despite their differing narratives, underscores the need to account for climate change impacts. The analysis suggests that health is a crucial starting point for modeling feedback loops, as it influences education and income through various mechanisms. Temperature, representing global warming, is also identified as a pivotal factor due to its impact on multiple well-being aspects. The analysis stresses the need for interdisciplinary collaboration between well-being researchers, climate scientists, and policy modelers to develop more comprehensive and accurate well-being projections.

This study demonstrates the feasibility and importance of integrating well-being projections, using the HDI as a key metric, into climate models. The findings highlight the significant limitations of current climate models that fail to adequately incorporate the feedback effects of climate change on well-being. The authors advocate for a more holistic approach to modeling future scenarios, emphasizing the crucial role of health in mediating the impacts of climate change on education and income. Future research should focus on refining the methodology by including additional beyond-GDP metrics, incorporating climate justice considerations, and developing more nuanced scenarios that reflect diverse societal and environmental policies.

The study uses the HDI, which has limitations in comprehensively capturing all aspects of well-being. The analysis does not fully incorporate the complex feedback loops between climate change, well-being, and other social factors (e.g., conflict, mental health). The assessment of environmental impacts is preliminary and relies on existing literature; more quantitative and model-based assessments are needed. The analysis focuses on between-country inequality and doesn't account for within-country inequality. The study's projections are based on the current SSPs, which might not encompass all potential future pathways.