Applying Asset Pricing Theory to Calibrate the Price of Climate Risk

Kent D. Daniel, Robert B. Litterman, Gernot Wagner

NBER Working Paper No. 22795
Issued in November 2016
NBER Program(s):Asset Pricing, Environment and Energy Economics, Political Economy

Pricing greenhouse gas emissions is a risk management problem. It involves making trade-offs between consumption today and unknown and potentially catastrophic damages in the (distant) future. The optimal carbon price is based on society’s willingness to substitute consumption across time and across uncertain states of nature. A large body of work in macroeconomics and finance has attempted to infer societal preferences using the observed behavior of asset prices, and has concluded that the standard preference specifications are inconsistent with observed asset valuations. This literature has developed a richer set of preferences that are more consistent with asset price behavior.

In this paper, we explore the implications of these richer preference specifications for the Social Cost of Carbon (SCC), the expected discounted damage of each marginal ton of carbon emissions at an optimal emissions reductions pathway. We develop a simple discrete-time model in which the representative agent has an Epstein-Zin preference specification, and in which uncertainty about the effect of carbon emissions on global temperature and on eventual damages is gradually resolved over time. In our model the SCC is equal to the value of the carbon emissions price at any given point in time that maximizes the utility of the representative agent at that time. We embed a number of features including tail risk, the potential for technological change, and backstop technologies. When coupled with the potential for low-probability, high-impact outcomes, our calibration allows us to decompose the SCC into the expected damages and the risk-premium. In contrast to most modeled carbon price paths, our calibration suggests a high SCC today that is expected to decline over time. It also points to the importance of backstop technologies and, in contrast to standard specifications, to potentially very large deadweight costs of delay. We find, for example, that with damage distributions calibrated to an SCC of $40, a value associated with only a small risk premium, the deadweight loss in utility associated with delaying the implementation of optimal pricing by 15 years is equivalent to a 6% loss of consumption.

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Document Object Identifier (DOI): 10.3386/w22795

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