Disaggregating the costs and benefits of climate action

Abstract

Integrated assessment models (IAMs) are greatly influential in global climate policy discussions and decision making. Mainstream IAMs suggest climate mitigation pathways which amount to making very little changes to emissions, consumption, and investment patterns in the short term. Instead, they rely on back-loading the mitigation efforts to reach outcomes that are the most economically efficient, and hence considered most socially optimal. It implicitly finds the social costs associated with the impacts of climate change acceptable up to the point where it affects the aggregated economic costs negatively. These socially optimum policies from IAMs lie at odds with the calls to expedited action by climate scientists and ethicists. Criticism is also levelled at IAMs for a evaluating the hardship caused by climate change to future generations much lower than present benefits from not avoiding it.

The thesis investigates this apparent dissonance by reviewing the economic foundations of the DICE IAM. The dissonance is traced back to the conceptualisation of welfare used in DICE based on the neoclassical Ramsey-Cass-Koopman growth theory in DICE. The welfare function includes the twin factors of time discounting, and evaluation of relative economic utility of costs and benefits of mitigating climate damage within each time-period. The shortcomings of the approach in context of climate economics are discussed by analysing the normative assumptions that underpin it. A novel disaggregation of the utility welfare is proposed to include a disutility of damage. The disutility of damage is modelled similarly, but evaluated independently from
the utility of consumption to incorporate the impact of an uncertain climate damage more meaningfully in IAMs.

The proposed concept is demonstrated by simulating the outcomes from a corresponding modification to DICE. Towards this end, DICE is transformed from a deterministic optimisation model into a simulation model. An exploratory modelling and analysis (EMA) approach is used to evaluate the outcomes over a large ensemble of potential scenarios and policies. The outcomes are analysed and compared with those from Nordhaus’ approach used in DICE. Results suggest that a disutility of damage function calibrated by a prescriptive or descriptive consideration of the Elasticity of Marginal Disutility of Damage (EMDD) has a significant negative impact on the overall welfare outcome.

The approach provides a useful way to incorporate prevalent as well as changing social preferences towards consumption growth and its utility in light of increasing, omnifarious, and deeply uncertain damaging effects of rapidly changing climate. It also makes IAMs more useful to evaluate the relative costs and benefits from more expedient mitigation proposals including a more realistic social cost of carbon (SCC), greater investment in emission reduction and control technologies, and considerations of a global economy not driven by ever increasing consumption
growth demands.