Synthesis of Evidence Yields High Social Cost of Carbon Due to Structural Model Variation and Uncertainties

Frances C. Moore, Moritz Drupp, James Rising, Simon Dietz, Ivan Rudik and Gernot Wagner

No 32544, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Estimating the cost to society from a ton of carbon dioxide (CO2) released into the atmosphere requires connecting a model of the climate system with a representation of the economic and social effects of changes in climate, as well as the valuation and aggregation of diverse, uncertain impacts across both time and space. The literature on this cost, termed the social cost of carbon (SCC), is large and growing. Prior work has largely focused on better constraining the values of parameters such as climate sensitivity, the discount rate, and the damage function. A growing literature has also examined the effect of varying more fundamental structural elements of the models supporting SCC calculations. These structural model choices—including the introduction of climate or economic tipping points, changing the structure of economic preferences, and accounting for the persistence of climate damages—have been analyzed in piecemeal, uncoordinated fashion, leaving their relative importance unclear. Here we perform a comprehensive synthesis of the evidence on the SCC, combining 1823 estimates of the SCC from 147 studies published between 2000 and 2020 with a survey of the authors of these studies. The distribution of published SCC values for a 2020 pulse year is wide and substantially right-skewed, showing evidence of a heavy right tail (truncated mean of $132, median $39). Analysis of variance reveals important roles for structural elements in driving SCC estimates, particularly the inclusion of persistent damages via effects on economic growth, representation of the Earth system, and distributional weighting. However, our survey reveals that experts believe the literature is biased downwards due to an under-sampling of structural model variations, as well as biases in damage-function and discount-rate parameters. To address this imbalance, we train a random forest model on variation in the literature and use it to generate a synthetic SCC distribution that more closely matches expert assessments of appropriate model structure and discounting. This synthetic distribution has a median and mean of $185 and $284 per ton CO2, respectively, for a 2020 pulse year (5%–95% range: $32–$874), higher than all official government estimates, including a 2023 update from the U.S. Environmental Protection Agency.

JEL-codes: Q0 Q50 Q54 (search for similar items in EconPapers)
Date: 2024-06
New Economics Papers: this item is included in nep-agr, nep-ene and nep-env
Note: EEE
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Related works:
Journal Article: Synthesis of evidence yields high social cost of carbon due to structural model variation and uncertainties (2024)
Working Paper: Synthesis of Evidence Yields High Social Cost of Carbon Due to Structural Model Variation and Uncertainties (2024)
Working Paper: Synthesis of evidence yields high social cost of carbon due to structural model variation and uncertainties (2024)
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