The impact of climate change and the social cost of carbon

By Richard S. J. Tol. 2018

13 citations recorded by the source corpus.

The social cost of carbon is the marginal impact of climate change. Estimates of the total impact of climate change show that a century of climate change is about as bad as losing a decade of economic growth. Poorer countries are more vulnerable. The uncertainties are vast and skewed the wrong way. The many published estimates of the social cost of carbon span six orders of magnitude, and some studies find support for a carbon subsidy. There is mixed evidence for publication bias. Matlab code is used to illustrate key sensitivities of the social cost of carbon; readers can readily run their own analyses. The bulk of the published estimates suggests that carbon dioxide should be taxed somewhere between $20/tC and $400/tC, depending on the preferred rates of discount and risk aversion. Revealed preferences on carbon pricing are at the lower end of this range. The social cost of carbon rises at around 2% per year. The central estimate of the social cost of carbon has not moved much over the last two decades, but the range of estimates is tightening slowly.

Subfields: Economics and Econometrics, Management Science and Operations Research, Renewable Energy, Sustainability and the Environment, Economics & Operations Research, Social Sciences & Humanities

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In Economics and Econometrics

In Management Science and Operations Research

In Renewable Energy, Sustainability and the Environment

In Economics & Operations Research

Iason Gabriel

In Social Sciences & Humanities

Citations in the corpus

Ethical and social risks of harm from Language Models (2021, background): “As in other domains, it is an open challenge to determine what level of environmental cost is justified; approaches to assessing the net impact may draw on cost-benefit projections and metrics such as the Social Cost of Carbon (Tol, 2019).”
A Meta-Analysis of the Total Economic Impact of Climate Change (2022, methodology): “(Tol, 2019a) shows that this is more robust than estimating national impact functions.”