The Use and Misuse of Models for Climate Policy

In recent articles I have argued that integrated assessment models (IAMs) have flaws that make them close to useless as tools for policy analysis. IAM-based analyses of climate policy create a perception of knowledge and precision that is illusory and can fool policymakers into thinking that the forecasts the models generate have some kind of scientific legitimacy. However, some economists and climate scientists have claimed that we need to use some kind of model for policy analysis and that IAMs can be structured and used in ways that correct for their shortcomings. For example, it has been argued that although we know very little about key relationships in the model, we can get around this problem by attaching probability distributions to various parameters and then simulating the model using Monte Carlo methods. I argue that this would buy us nothing and that a simpler and more transparent approach to the design of climate change policy is preferable. I briefly outline what such an approach would look like.