Developing data-driven damage and adaptation functions for Integrated Assessment Models: An application in AD-MERGE 2.0

Integrated Assessment Models (IAMs) have been the primary tool for studying the global trade-offs of climate change mitigation over the past decades. These models rely on estimated functions of climate change induced economic damages. These are, however, based on severely limited or decades-old data, or both. This paper aims to estimate the most robust possible regional impact cost functions given the available data and implement them into the AD-MERGE 2.0 IAM. We estimate the impacts of climate change on coastal flooding, river flooding, mortality and morbidity, energy consumption, labour productivity and tourism using recent observational data or results of recent modelling exercises. In addition, we estimate proactive and reactive adaptation benefits, as well as associated adaptation costs. The resulting global damage function aligns closely with the estimated damage functions reported in Howard and Sterner (2017) and extends the observed pattern, whereby more recent damage functions imply greater damage for given temperature increases. Regional disparities in the damage function are substantial, with Africa and the Other Asian States incurring greater damage for each incremental increase in temperature than other regions.