I review the economic characteristics of the climate problem, focusing on the choice of discount rates in the presence of a stock externality, risk and uncertainty/ambiguity, and the role of integrated assessment models (IAMs) in analyzing policy choices. I suggest that IAMs can play a role in providing qualitative understanding of how complex systems behave, but are not accurate enough to provide quantitative insights. Arguments in favor of action on climate issues have to be based on aversion to risk and ambiguity and the need to avoid a small but positive risk of a disastrous outcome.

Manmade climate change (CC) has catastrophic consequences. The United States has already experienced wholesale population realignment due to climate as households have relocated to the Sunbelt and West. The irony is that people are moving toward the heat and major storms associated with CC. As CC intensifies, with high rates of internal US factor mobility, firms and households will likely again relocate to areas with higher utility and profits, reducing CC costs. Yet current research typically focuses on CC costs in a given location without considering this realignment. We propose several avenues to overcome such shortcomings in US CC modeling.

Financial market information can provide an objective assessment of losses anticipated from temperature changes. In an APT model in which temperature shocks are a systematic risk factor, the risk premium is significantly negative, loadings for most assets are negative, and asset portfolios in more vulnerable industries have stronger negative loadings on a temperature shock factor. Weighted average increases in the cost of equity capital attributed to uncertainty about temperature changes are 0.22 percent, implying a present value loss of 7.92 percent of wealth. These costs represent a new channel that may contribute to cost of climate change assessment.

Common views hold that the efficient way to limit warming to a chosen level is to price carbon emissions at a rate that increases exponentially. We show that this Hotelling tax on carbon emissions is actually inefficient. The least-cost policy path takes advantage of the climate system's inertia to delay reducing emissions and allow greater cumulative emissions. The efficient carbon tax follows an inverse-U-shaped path and grows more slowly than the Hotelling tax. Economic models that assume exponentially increasing carbon taxes are overestimating the cost of limiting warming, overestimating the efficient near-term carbon tax, and overvaluing technologies that mature sooner.

This paper develops a method for forecasting the marginal abatement cost (MAC) of climate policy using three features of the failed Waxman-Markey bill. First, the MAC is revealed by the price of traded permits. Second, the permit price is estimated using a regression discontinuity design (RDD) comparing stock returns of firms on either side of the policy's free permit cutoff rule. Third, because Waxman-Markey was never implemented, I extend the RDD approach to incorporate prediction market prices which normalize estimates by policy realization probabilities. A final bounding analysis recovers a MAC range of $5 to $19 per ton CO 2 e.