Building Uncertainty into the Adaptation Cost Estimation in Integrated Assessment Models

Abstract

This paper proposes an operationally simple and easily generalizable methodology to incorporate climate change damage uncertainty into Integrated Assessment Models (IAMs). Uncertainty is transformed into a risk-premium, damage-correction, region-specific factor by extracting damage distribution means and variances from an ensemble of socio economic and climate change scenarios. This risk premium quantifies what society would be willing to pay to insure against the uncertainty of the damages, and it can be considered an add-up to the standard "average damage". Our computations show the addition to be significant, but highly sensitive to the coefficient of relative risk aversion. Once the climate change damage function incorporates the risk premium into the model, results show a substantial increase in both mitigation and adaptation, reflecting a more conservative attitude by the social planner. Interestingly, adaptation is stimulated more than mitigation in the first half of the century, while the situation reverses afterwards. Over the century, the risk premium correction fosters more mitigation, which doubles, than adaptation, which rises by about 80%.