The Social Cost of Carbon When We Wish for Full-Path Robustness

Yifan Zhao (), Arnab Basu (), Thomas S. Lontzek () and Karl Schmedders
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Yifan Zhao: Rhine-Westphalia Technical University of Aachen, 52056 Aachen, Germany
Arnab Basu: Department of Industrial Engineering, Bilkent University, 06800 Cankaya, Ankara, Turkey
Thomas S. Lontzek: Rhine-Westphalia Technical University of Aachen, 52056 Aachen, Germany

Management Science, 2023, vol. 69, issue 12, 7585-7606

Abstract: We compute the social cost of carbon (SCC) when decision makers want robust estimates in the face of deep (or “Knightian”) uncertainty. We introduce the notion of full-path accumulated robust preferences from stochastic control theory to an integrated assessment model. Robust preferences are appropriate for analyzing climate-related problems because, given the large uncertainty in climate science, they enable decision makers to attain solutions that are robust to a wide range of climate change scenarios. We solve the resulting model, which includes uncertainty about climate change and the ensuing economic damage and show the existence of optimal solutions and time-consistent optimal deterministic Markov policies. Additionally, we also prove that the standard Hansen–Sargent recursive utility provides an upper bound of this full-path utility. In our baseline model specification, we find that the year 2020’s optimal SCC is US$162 per tCO 2 with an average annual growth rate of 2.5%, setting the world on a 1.37°C path, which requires full decarbonization by 2068. We introduce the notion of the SCC robustness premium, which we define as the additional SCC price tag for robustness. For a plausible range of preference parameters, the SCC robustness premium in 2020 is between US$1.41 and US$25.89 per tCO 2 with US$2.20 per tCO 2 in our baseline calibration. Over time, this premium grows significantly. The forecasts of our model facilitate managerial decision making during the world’s transition from a carbon- and emission-intensive economy to a regenerative economy. The high estimates for the SCC predict drastic rises in emission costs for high-emission industries.

Keywords: full-path robustness; model uncertainty; risk-sensitive preferences; robustness premium; social cost of carbon (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:69:y:2023:i:12:p:7585-7606

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