Production networks and planetary boundaries: challenges and opportunities for integrated assessment models

Thesis

Integrated Assessment Models (IAMs) are used to understand the complex interactions between the Earth system and socio-economic processes. These models help us understand possible futures associated with different levels of human impact on the climate system. As such, they wield significant influence on policy-making and society as a whole. At the heart of this thesis is a fundamental inquiry into advancing IAMs. This deep inquiry is rooted in the understanding that the economy is a complex system and in the acknowledgement of the intertwined nature of the climate and ecological crises; both are mostly overlooked in IAMs. This thesis provides insights and advances for IAMs with the goal of strengthening their ability to address the climate and ecological crises together.

First, this thesis finds that IAMs are not up to the task of addressing the climate and ecological crises together. Using the Planetary Boundaries (PBs) framework, it assesses the ecological feasibility of Paris-compliant mitigation pathways that were considered in the recent IPCC Sixth Assessment Report. Almost all scenarios transgress PBs. Even “low-demand” or “sustainability” pathways do not meet the ecological feasibility criteria set forth by the PBs framework. These findings highlight the need for a comprehensive and integrated approach.

Second, drawing from complexity economics and recent findings in the literature on supply chain networks, this thesis argues that IAMs overlook key micro-level mechanisms that are essential for understanding the evolution, stability and resilience of the economic system – and thus of society as a whole. It explores how we might have a more fine-grained macroeconomic model that takes into account supply chain interactions at the firm level. It finds that serious data limitations must be overcome before we can achieve this level of granularity in IAMs. Using methods from complexity science, it addresses the data limitations using two different approaches and makes two major contributions: (1) it provides the first comprehensive picture of the most fundamental statistics on production networks, thus providing a basis for generating synthetic data or calibrating macroeconomic models; and (2) it provides the first thorough evaluation of a maximum entropy reconstruction method applied to firm-level production networks. This thesis also contributes to an emerging agenda to develop standards for data collection, cleaning and matching for micro-level production network data around the world.

Authors: Bacilieri, A

• DOI: 10.5287/ora-ko7x2bpqj
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: network reconstruction; firm-level data; missing information; production networks; planetary boundaries; maximum entropy; integrated assessment models; climate change; input-output analysis; supply chain networks
• Subjects: Economics; Complexity science; Sustainability; Climate change mitigation