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Tipping points and ambiguity in the economics of climate change

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  • Lemoine, Derek M.
  • Traeger, Christian P.

Abstract

We model optimal policy when the probability of a tipping point, the welfare change due to a tipping point, and knowledge about a tipping point's trigger all depend on the policy path. Analytic results demonstrate how optimal policy depends on the ability to affect both the probability of a tipping point and also welfare in a post-threshold world. Simulations with a numerical climate-economy model show that possible tipping points in the climate system increase the optimal near-term carbon tax by up to 45% in base case speciffcations. The resulting policy paths lower peak warming by up to 0.5 C compared to a model without possible tipping points. Different types of tipping points have qualitatively different effects on policy, demonstrating the importance of explicitly modeling tipping points' effects on system dynamics. Aversion to ambiguity in the threshold's distribution can amplify or dampen the effect of tipping points on optimal policy, but in our numerical model, ambiguity aversionincreases the optimal carbon tax.

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Paper provided by Department of Agricultural & Resource Economics, UC Berkeley in its series Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series with number qt9nd591ww.

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Date of creation: 28 Dec 2011
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Handle: RePEc:cdl:agrebk:qt9nd591ww

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Keywords: tipping point; threshold; regime shift; ambiguity; climate; uncertainty; integrated assessment; dynamic programming; social cost of carbon; carbon tax; Social and Behavioral Sciences; Life Sciences;

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Citations

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Cited by:
  1. Yongyang Cai & Kenneth L. Judd & Thomas S. Lontzek, 2013. "The Social Cost of Stochastic and Irreversible Climate Change," NBER Working Papers 18704, National Bureau of Economic Research, Inc.
  2. Geoffrey Heal & Antony Millner, 2013. "Uncertainty and Decision in Climate Change Economics," NBER Working Papers 18929, National Bureau of Economic Research, Inc.
  3. Traeger, Christian, 2012. "A 4-stated DICE: quantitatively addressing uncertainty effects in climate change," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6jx2p7fv, Department of Agricultural & Resource Economics, UC Berkeley.
  4. Derek Lemoine & Christian Traeger, 2014. "Watch Your Step: Optimal Policy in a Tipping Climate," American Economic Journal: Economic Policy, American Economic Association, vol. 6(1), pages 137-66, February.
  5. Duncan Foley & Lance Taylor & Armon Rezai, 2013. "The Social Cost of Carbon Emissions," INET Research Notes 28, Institute for New Economic Thinking (INET).
  6. Fisher, Anthony C & Le, Phu V, 2014. "Reflections on Climate Policy:Science, Economics, and Extremes," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6tj3j4jb, Department of Agricultural & Resource Economics, UC Berkeley.
  7. Antony Millner & Raphael Calel & David Stainforth & George MacKerron, 2013. "Do probabilistic expert elicitations capture scientists’ uncertainty about climate change?," Climatic Change, Springer, vol. 116(2), pages 427-436, January.
  8. Elizabeth Kopits & Alex L. Marten & Ann Wolverton, 2013. "Moving Forward with Incorporating "Catastrophic" Climate Change into Policy Analysis," NCEE Working Paper Series 201301, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Jan 2013.
  9. David Comerford (University of Edinburgh), 2013. "A balance of questions: what can we ask of climate change economics?," ESE Discussion Papers 216, Edinburgh School of Economics, University of Edinburgh.
  10. Antony Millner & Simon Dietz & Geoffrey Heal, 2013. "Scientific Ambiguity and Climate Policy," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 55(1), pages 21-46, May.

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