Consumers, development, and the future of wellbeing

As society recognizes and endeavors to combat threats to the environment, it is becoming increasingly clear that heterogeneity in human consumption behavior should receive greater attention to understand the impacts created by human development. The cross-cutting Socioeconomic Heterogeneity in Model Applications (SCHEMA) project focused on how accounting for socioeconomic heterogeneity in integrated assessments can improve both the prediction of global environmental change and their impacts on human wellbeing.

The project, which was completed in 2017, was a collective effort between four IIASA programs: Energy, Ecosystems Services and Management, Air Quality and Greenhouse Gases, and World Population. The aim was to generate a common layer of socioeconomic inputs that feed into at least three global models namely, the Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGE), the Global Biosphere Management Model (GLOBIOM), and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model. These inputs enabled the generation of more detailed representations of household diversity, specifically in aspects of basic subsistence, including food demand, cooking fuels, and related exposure to air pollution. The geographic focus of the project was India–a developing country with high socioeconomic contrasts.

The SCHEMA project has led to significant methodological advances and substantive insights in the different IIASA domains addressed by the cross-cutting team. Existing IIASA models were modified to incorporate primary drivers of change into the projections and future scenarios of food demand and undernutrition, cooking fuels, and related health impacts from exposure to harmful substances emitted by these fuels (wellbeing dimensions) [1].

Detailed projections of future demographics and income inequality were generated for different states, taking into account urbanization rates and intra-national migration patterns. Income inequality projections accounted for increasing technology-driven skill bias and education improvements. These primary drivers were then converted into food and energy demand projections at national and state level. The results revealed that socio-heterogeneity significantly affects the results of the projections.

According to the researchers, understanding food and energy demand in the country is difficult without looking at patterns across socioeconomic groups. Average national GDP per capita masks poverty levels due to the unequal distribution of income within the country, and fails to account for the different levels of uptake of clean cooking fuels in urban and rural India. Furthermore, the relative contributions of higher and lower income groups to ambient air pollution vary significantly for different activities, for instance cooking in contrast to transport and other economic activities. In the case of food consumption, the researchers performed a detailed analysis of Indian consumer expenditure over a period of twenty years (1993-2012), which allowed them to identify the most important drivers of change in dietary patterns over this period. Income distribution, urbanization, and aging were identified as key factors to understand the future of food demand and nutrition in the country. The Figure reveals the new capabilities of the IIASA models to project basic wellbeing dimensions under different socioeconomic futures.

SCHEMA wellbeing indicators (related to basic subsistence) for India in 2040 under different scenarios showing percentage of population (higher is less wellbeing). Shared Socioeconomic Pathways (SSP): SCHEMA-customized SSPs. SSP1: equitable world; SSP2: middle of the road; SSP3: unequal world. Three sensitivities SSP_UH/SSP2_UL: SSP2 with high/low urbanization. SSP_CG: SSP2 with constant Gini (low inequality).

In short, the project has laid a foundation from which multiple research and policy applications can be developed. The representation of different household groups enables the assessment of distributive impacts of various policies and policy shocks in all relevant sectors, such as carbon pricing, agricultural policies, or pollution control measures. Some of these policies can propagate through energy and food prices, where they have impacts on air pollution, greenhouse gas emissions, and other dimensions of wellbeing. This kind of analysis can potentially help identify winners and losers by, for example, identifying groups that bear undue pollution exposure without proportionate contributions to emissions. Additional scenarios can also be devised to assess particular objectives, such as the Sustainable Development Goals (SDGs) and other national development objectives.


[1] Samir KC, Gregor Kiesewetter, Shonali Pachauri, Narasimha Rao, Hugo Valin et al., The influence of socioeconomic heterogeneity in integrated assessment: the case of basic subsistence, in review.

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