Abstract
We use perturbation methods to derive a rule for the optimal risk-adjusted social cost of carbon (SCC) that incorporates the effects of uncertainties associated with climate and the economy from a calibrated DSGE model. We allow for different aversions to risk and intertemporal fluctuations, convex damages, uncertainties in economic growth, atmospheric carbon, climate sensitivity and damages, their correlations, and distributions that are skewed in the longer run to capture long-run climate feedbacks. Our non-certainty-equivalent rule for the SCC incorporates precaution, risk insurance, and climate sensitivity and damage rate hedging effects to deal with future economic and climatic and damage risks.
Highlights
Climate policy must take account of the highly uncertain nature of the impact of the atmospheric carbon stock on global mean temperature, of temperature on damages to aggregate output and the highly uncertain nature of future GDP
Using asymptotic methods, we have derived a tractable rule for the optimal riskadjusted social cost of carbon (SCC) under a range of economic and climatic uncertainties allowing for the convexity of global warming damages and the skewness of shocks to the climate sensitivity and global warming damages, and the time scales on which they arise
This gives insight into the ethical determinants and the stochastic economic and geophysical drivers of the optimal carbon price and is a very good approximation to our more fundamental result, which only requires that climate damages are a small percentage of world GDP
Summary
The aggregate capital stock is accumulated according to the stochastic equation (2.2). The absolute value of the atmospheric carbon stock is denoted by S. We define the part associated with man-made emissions E as the difference between the current value ( S ) and the pre-industrial carbon stock, SPI , so that E S SPI. Atmospheric carbon decays at the rate 0.12 The dynamics of the carbon stock is given by. 15 Temperature is often explained by a logarithmic function of the carbon stock (Arrhenius, 1896). (2.6) total factor productivity and aggregate output decreases in the carbon stock and the shocks to climate sensitivity and damages:. The vector of all four states can be described by one multi-variate Ornstein-Uhlenbeck process:. E E where ij , i j, i, j K , E, , denote the partial correlation coefficients
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