The DOI matches its Crossref record.
Revisiting the social cost of carbon
Open accessAbstract
Significance: The most important single economic concept in the economics of climate change is the social cost of carbon (SCC). At present, regulations with more than $1 trillion of benefits have been written for the United States that use the SCC in their economic analysis. The DICE model (Dynamic Integrated model of Climate and the Economy) is one of three integrated assessment models used to estimate the SCC in the United States. The present study presents updated estimates based on a revised DICE model (DICE-2016R). The study estimates that the SCC is $31 per ton of CO 2 in 2010 US$ for the current period (2015). This study will be an important step in developing the next generation of estimates of the SCC in the United States and other countries.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Comprehensive evidence implies a higher social cost of CO2
Rennert, K., Errickson, F., Prest, B. C., Rennels, L., Newell, R. G., Pizer, W., Kingdon, C., Wingenroth, J., Cooke, R., Parthum, B., et al. (2022) · Nature · doi:10.1038/s41586-022-05224-9 · Cited by 1,067
Country-level social cost of carbon
Ricke, K., Drouet, L., Caldeira, K., & Tavoni, M. (2018) · Nature Climate Change · doi:10.1038/s41558-018-0282-y · Cited by 860
Assessing the efficiency of changes in land use for mitigating climate change
Searchinger, T. D., Wirsenius, S., Beringer, T., & Dumas, P. (2018) · Nature · doi:10.1038/s41586-018-0757-z · Cited by 617
Empirically grounded technology forecasts and the energy transition
Way, R., Ives, M. C., Mealy, P., & Farmer, J. D. (2022) · Joule · doi:10.1016/j.joule.2022.08.009 · Cited by 607
The global costs of extreme weather that are attributable to climate change
Newman, R., & Noy, I. (2023) · Nature Communications · doi:10.1038/s41467-023-41888-1 · Cited by 575
Metadata
- Authors
- Nordhaus, W. D.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2017-01-31
- Volume
- 114
- Issue
- 7
- Pages
- 1518-1523
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2584212846
- Cited by
- 1,366
- References
- 0
- FWCI
- 156.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Revisiting the social cost of carbon. https://app.cochat.ai/papers/10.1073/pnas.1609244114
- The paper
- Nordhaus, W. D. (2017). Revisiting the social cost of carbon. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1609244114
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
