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 price is necessarily 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. The climate-economy literature by and large has not adopted this richer set of preferences.
In this paper, we explore the implications of these richer preference specifications for the optimal pricing of carbon emissions. We develop a simple discrete-time model with Epstein-Zin utility in which uncertainty about the effect of carbon emissions on global temperature and on eventual damages is gradually resolved over 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 to historical real interest rates and the equity risk premium suggests a high price for carbon emissions today which is then expected to decline over time. This is in contrast to most modeled carbon price paths, which tend to start low and rise steadily over time.
Daniel, Kent, Robert Litterman, and Gernot Wagner. "Applying Asset Pricing Theory to Calibrate the Price of Climate Risk." Columbia Business School, February 2015.
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