Introduction

Economic assessment of climate change and climate policy depends on information that is not currently available, and may not become available until it is too late to do anything about it. Two central uncertainties, in particular, pose challenges to quantitative economic analysis. First, how bad will the climate get – that is, how much will temperatures rise as a result of increasing atmospheric concentrations of greenhouse gases? Second, how bad will the worsening climate be for the economy – that is, how much economic damage will be caused by increased temperatures and associated physical impacts of climate change? Such questions remain unanswered and perhaps intrinsically unanswerable except in retrospect, despite the increasingly detailed understanding of climate processes that is emerging from scientific research. Yet with bad enough answers to these questions, climate change might lead to disastrous results for the global economy.

Conventional economic analysis does not appear to be stymied by the problems of irreducible uncertainty and catastrophic risks. Integrated assessment models (IAMs) often adopt deterministic estimates or “best guesses” about a number of crucial unknowns. This procedure eliminates uncertainty from the model, at the cost of making the results dependent on the particular estimates that are employed. (On the theory and limitations of IAMs in general, see Ackerman et al. 2009b; Stanton et al. 2009). Using their chosen resolutions of key uncertainties, IAMs have often found that the optimal policy response is to do relatively little about climate change in the near term. The catastrophic risks that are increasingly discussed in climate science and policy analyses almost never translate into catastrophic economic outcomes in IAMs.