On this episode of Free Range, Mike Livermore speaks with Frances Moore, a Professor of Environmental Science and Policy at UC Davis whose work focuses on climate economics. Recently, Moore was the lead author of a paper in Nature that examines an important set of feedbacks between politics and the climate system.

The discussion begins by examining the key differences between the model development by Moore and her team and other approaches. Generally, climate models take emissions as a given, or as resulting from large macro phenomenon like economic growth. The innovation of Moore’s model is to treat emissions as “endogenous” to political and social processes. Her model includes the formation of policy, which affects emissions and, therefore, the climate system (0:41 – 2:58).

Expanding more on different ways of modeling, Livermore brings up two broad approaches to climate modeling: the process used in the natural sciences, which is relied on by the IPCC (Intergovernmental Panel on Climate Change) vs. the process that economists use that feeds into social policies. He poses the question of how Moore's model fits into these two broad categories of the IPCC vs. SCC (social cost of carbon) approach in regards to climate modeling (3:00 – 4:51).

Moore’s model is distinct to both approaches. In the economist approach, a social decision maker maximizes welfare by controlling emissions over time. Moore’s model does not optimize anything (4:57 – 6:57). On the other hand, the IPCC takes a predictive approach, but without asking what policies are most likely. Moore’s model integrates policy into the predictive approach.

Moore dives further into details about the feedbacks in her paper (7:00 – 12:49). Examples of the feedbacks explored in the paper are: normative social conformity feedback; climate change perception feedback; temperature emissions feedback; and the expressive force of law feedback. Moore dives deeper into the law feedback, discussing the challenges they faced when trying to qualitative information in a quantitative way for their modeling (13:26 – 16:37). Moore and Livermore discuss different interpretations of the expressive force of law and how it might fit into a predictive model (16:46 – 22:00). Another type of feedback studied involved individual behavior. This behavior is important for global emissions only when it leads to preferences that eventually produce large-scale changes (22:01 – 28:25).

Livermore and Moore discuss the hopeful headline conclusion of Moore’s model, which is the possibility of global net zero emissions by 2080-2090, which follows a 2.3° pathway by 2100. This pathway is very similar to what the 2030-2050 emission commitments look like from the Paris Climate Agreement. Livermore notes that some of the model runs resulted in a 3-4° world. The model features of these worlds included high social norm effects, political systems with bias towards the status quo, high bias assimilations responsiveness of the political systems, and energy systems not evolving (28:35 – 39:33).

Livermore notes some of his work on climate-society feedbacks concerning the potential for climate damages to undermine conditions necessary for climate cooperation at a global scale. Moore explains why they didn't include this feedback in the model, stating that looking at these tipping points would be involved in the next steps of extending the model (40:00 – 45:02).

Livermore brings up the topic about the philosophical differences between Moore’s fully causal model of the human climate system and other models. Moore’s goal of modeling is primarily understanding and descriptive, which differentiates it from other models. They end the episode discussing that carbon pricing over the next 5-10 years should be a good signal to tell us what type of temperature change trajectory our world will be on: one of reasonable temperature change or one of catastrophic change (50:23 – 1:00:23).