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Beschreibung:
Uncertainty plays a significant role in evaluating climate policy, and fattailed uncertainty may dominate policy advice. Should we make our utmost effort to prevent the arbitrarily large impacts of climate change under deep uncertainty? In order to answer to this question we propose an new way of investigating the impact of (fat-tailed) uncertainty on optimal climate policy: the curvature of carbon tax against the uncertainty. We find that the optimal carbon tax increases as the uncertainty about climate sensitivity increases, but it does not accelerate as implied by Weitzman's Dismal Theorem. We find the same result in a wide variety of sensitivity analyses. These results emphasize the importance of balancing of the costs and the benefits of climate policy, also under deep uncertainty.