Limitations of integrated assessment models of climate change
- Author(s): Ackerman, Frank;
- DeCanio, Stephen J.;
- Howarth, Richard B.;
- Sheeran, Kristen
- et al.
Published Web Locationhttps://doi.org/10.1007/s10584-009-9570-x
The integrated assessment models (IAMs) that economists use to analyze the expected costs and benefits of climate policies frequently suggest that the “optimal” policy is to go slowly and to do relatively little in the near term to reduce greenhouse gas emissions. We trace this finding to the contestable assumptions and limitations of IAMs. For example, they typically discount future impacts from climate change at relatively high rates. This practice may be appropriate for short-term financial decisions but its extension to intergenerational environmental issues rests on several empirically and philosophically controversial hypotheses. IAMs also assign monetary values to the benefits of climate mitigation on the basis of incomplete information and sometimes speculative judgments concerning the monetary worth of human lives and ecosystems, while downplaying scientific uncertainty about the extent of expected damages. In addition, IAMs may exaggerate mitigation costs by failing to reflect the socially determined, path-dependent nature of technical change and ignoring the potential savings from reduced energy utilization and other opportunities for innovation. A better approach to climate policy, drawing on recent research on the economics of uncertainty, would reframe the problem as buying insurance against catastrophic, low-probability events. Policy decisions should be based on a judgment concerning the maximum tolerable increase in temperature and/or carbon dioxide levels given the state of scientific understanding. The appropriate role for economists would then be to determine the least-cost global strategy to achieve that target. While this remains a demanding and complex problem, it is far more tractable and epistemically defensible than the cost-benefit comparisons attempted by most IAMs.