Shaping the SSP storylines in economy-wide models
Organizer: Bert Saveyn (Joint Research Centre of the European Commission), Rob Dellink (OECD), Dominique van der Mensbrugghe (Purdue University)
Assessing disruptive technologies in economy-wide models for climate change analyses
Carolina Grottera, Center for Integrated Studies on Climate Change and Environment
4:15 PM-4:30 PM
Baseline scenario building in CGE models: What is the state of play?
Dominique van der Mensbrugghe, Purdue University
4:30 PM-4:45 PM
Projections for Europe and the World to 2050 through the lens of the Water, Land, Energy, Food and Climate Nexus
Jason Levin-Koopman, Wageningen Economic Research
4:45 PM-5:00 PM
Linking material flows to their economic drivers: a multisectoral global outlook
Rob Dellink, Organisation for Economic Co-operation and Development
5:00 PM-5:15 PM
The robustness of a coalition's supply side strategy to future scenarios
Taran Fæhn, Research Department, Section for Energy and Environmental Economics
The quantitative assessment of climate change—both physical and socio-economic—necessarily entails a dynamic component given the built-in lags in the climate system. Socio-economic assessments of climate change cover a wide range of factors and end-results. Driving factors include changing demographics and sectoral and regional economic activity: economic growth, income convergence, servitisation of the economy, and changing trade patterns. End-results include projections of land use and energy mix and resulting greenhouse gas emissions, impacts from rising temperatures and changing precipitation patterns and adaptation responses, and the effect of mitigation policies on emissions and residual adaptation. Some models then also include feedbacks from these climate end results to the socioeconomic drivers.
Quantitative frameworks, no matter how detailed, necessarily simplify reality. A certain degree of humility is called for when projecting out to 2100 or beyond. One only needs to place oneself in 1900 to recognize the challenges of projecting the future 100 years ahead. The purpose of this session is to highlight these challenges by elucidating the range of practices undertaken by some of the key integrated assessment modeling (IAM) teams from around the globe, highlight possible best practices and propose further research directions to improve our understanding of the pitfalls and challenges of quantitative assessments of the future.
All IAM teams are working in the context of the so-called socio-economic pathways (SSPs), developed by the IAM community to provide context for ongoing quantitative assessment of climate change. The five SSP storylines entail very different socio-economic outcomes through 2100, both at the boundary level—for example output and population growth, but also at the more detailed level such as structure of the economy, food and energy consumption, technological change, energy mix and ensuing greenhouse gas emissions with their socio-economic impacts. Though most integrated assessment modeling (IAM) teams have harmonized their SSP scenarios on the aforementioned boundary conditions, there are infinite pathways to describe the more detailed elements of the storylines. This has led to growing unease in the IAM community about the lack of transparency, reproducibility and collaboration on scenarios.
A model comparison exercise on best practices in specifying dynamic socio-economic trends, including some of the world's leading computable general equilibrium (CGE) and IAM modeling teams. The aim was to exchange current practices and start a process of developing guidelines and best practices for projecting futures for the global economy, abstracting from the influence of policy shocks. The exercise consists of seven working groups working on different aspects of dynamic model specification: macro drivers of economic growth, demand side and consumer behavior, supply side and producer behavior, linking sectoral and macroeconomic models, energy and environment, trade, and nutrition and food security.
This session will highlight some of the key findings that have emerged from the seven working groups, with an emphasis on the linkages between these findings and the SSPs. Though the focus of the exercise is on dynamic socioeconomic projections, the findings are applicable to all scenario development. All scenarios relate to many fundamental socio-economic mechanisms that directly affect emissions, impacts, adaptation and mitigation: technological change (autonomous and endogenous); producer and consumer preferences; the cost, availability and acceptability of yet-to-be-deployed technologies (such as bio-energy with carbon capture and storage); and the underlying uncertainty of all of these factors.
The focus on the SSPs should also not deter from the fact that these same underlying mechanisms relate to sustainability writ large and that many of these same modeling teams are broadening their focus to include the United Nations Sustainable Development Goals (SDGs).