The social cost of carbon in U.S. regulatory impact analyses: an introduction and critique

By L. Johnson, Chris Hope. Journal of Environmental Studies and Sciences, 2012

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In 2010, as part of a rulemaking on efficiency standards, the U.S. government published its first estimates of the benefits of reducing CO2 emissions, referred to as the social cost of carbon (SCC). Using three climate economic models, an interagency task force concluded that regulatory impact analyses should use a central value of \$21 per metric ton of CO2 for the monetized benefits of emission reductions. In addition, it suggested that sensitivity analysis be carried out with values of \$5, \$35, and \$65. These estimates have been criticized for relying upon discount rates that are considered too high for intergenerational cost–benefit analysis, and for treating monetized damages equivalently between regions, without regard to income levels. We reestimate the values from the models (1) using a range of discount rates and methodologies considered more appropriate for the very long time horizons associated with climate change and (2) using a methodology that assigns “equity weights” to damages based upon relative income levels between regions—i.e., a dollar’s worth of damages occurring in a poor region is given more weight than one occurring in a wealthy region. Under our alternative discount rate specifications, we find an SCC 2.6 to over 12 times larger than the Working Group’s central estimate of \$21; results are similar when the government’s estimates are equity weighted. Our results suggest that regulatory impact analyses that use the government’s limited range of SCC estimates will significantly understate potential benefits of climate mitigation. This has important implications with respect to greenhouse gas standards, in which debates over their stringency focus critically on the benefits of regulations justifying the industry compliance costs.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/8573cd82a1eb5c600b16b1becc460f4d1c269e4d

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