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Country-level social cost of carbon

An Author Correction to this article was published on 25 March 2019

This article has been updated


The social cost of carbon (SCC) is a commonly employed metric of the expected economic damages from carbon dioxide (CO2) emissions. Although useful in an optimal policy context, a world-level approach obscures the heterogeneous geography of climate damage and vast differences in country-level contributions to the global SCC, as well as climate and socio-economic uncertainties, which are larger at the regional level. Here we estimate country-level contributions to the SCC using recent climate model projections, empirical climate-driven economic damage estimations and socio-economic projections. Central specifications show high global SCC values (median, US$417 per tonne of CO2 (tCO2); 66% confidence intervals, US$177–805 per tCO2) and a country-level SCC that is unequally distributed. However, the relative ranking of countries is robust to different specifications: countries that incur large fractions of the global cost consistently include India, China, Saudi Arabia and the United States.

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Fig. 1: GSCC in 2020 under various assumptions and scenarios.
Fig. 2: CSCCs.
Fig. 3: Lorenz curve and Gini coefficients for the country-level contributions to the GSCC in 2020.
Fig. 4: Winners and Losers of climate change among the G20 nations.

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Data availability

The database of the CSCCs with uncertainty bounds under all scenarios, model specifications and discounting schemes is available as a part of the Supplementary Information and via

Change history

  • 25 March 2019

    In the version of this Article originally published, owing to a code error, the CSCC values for all income-dependent (that is, rich-poor) impact model specifications were incorrect, showing higher values relative to the preferred model rather than lower. These have now been recalculated for BHM SR RP, BHM LR RP and DJO RP, and Figs 1, 2b and 3b, as well as Supplementary Figs 2, 4–6 and 9, have been updated to reflect these recalculations. In addition, the text reading, “The GSCC tends to be similar in both pooled and rich/poor specifications of the damages model, with the exception of SSP3, in which the estimated GSCC is much higher in the rich/poor specifications. The DJO specification of the economic impact function yields significantly higher GSCC values” has been modified to reflect this recalculation and now reads, “The GSCC is always lower using the rich/poor specifications of the damages model with confidence intervals that, in most cases, extend into the negative SCC range. The DJO specification of the economic impact function, which also estimates distinct effects for rich and poor countries, yields significantly lower GSCC values.” The sentence beginning, “This results in higher (almost twice as much) global values of the SCC...” has also been modified to “In the case of the LR BHM specifications, this results in higher (almost twice as much) global values of the SCC...” The income thresholds and coefficients in the Supplementary Text, as well as the interpretation of the DJO sensitivity analysis results, have also been updated to reflect these changes. The authors thank Yixuan Zheng for identifying the code error.


  1. Tol, R. S. J. The social cost of carbon. Annu. Rev. Resour. Econ. 3, 419–443 (2011).

    Article  Google Scholar 

  2. IAWG Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866 (US Government, 2013).

  3. Pindyck, R. S. The Social Cost of Carbon Revisited (National Bureau of Economic Research, 2016).

  4. Anthoff, D. & Tol, R. S. J. The uncertainty about the social cost of carbon: a decomposition analysis using fund. Climatic Change 117, 515–530 (2013).

    Article  Google Scholar 

  5. Moore, F. C. & Diaz, D. B. Temperature impacts on economic growth warrant stringent mitigation policy. Nat. Clim. Change 5, 127–131 (2015).

    Article  Google Scholar 

  6. Nordhaus, W. Estimates of the social cost of carbon: concepts and results from the DICE-2013R model and alternative approaches. J. Assoc. Environ. Resour. Econ. 1, 273–312 (2014).

    Google Scholar 

  7. Bansal, R., Kiku, D. & Ochoa, M. Price of Long-Run Temperature Shifts in Capital Markets (National Bureau of Economic Research, 2016).

  8. National Academies of Sciences, Engineering and Medicine Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon Dioxide (National Academies, Washington, 2017).

  9. Anthoff, D., Tol, R. S. J. & Yohe, G. W. Risk aversion, time preference, and the social cost of carbon. Environ. Res. Lett. 4, 024002 (2009).

    Article  Google Scholar 

  10. Weitzman, M. L. Tail-hedge discounting and the social cost of carbon. J. Econ. Lit. 51, 873–882 (2013).

    Article  Google Scholar 

  11. Ackerman, F. & Stanton, E. A. Climate risks and carbon prices: revising the social cost of carbon. Economics 6, 2012–10 (2012).

    Google Scholar 

  12. Hope, C. Discount rates, equity weights and the social cost of carbon. Energy Econ. 30, 1011–1019 (2008).

    Article  Google Scholar 

  13. Cai, Y., Judd, K. L. & Lontzek, T. S. The social cost of carbon with economic and climate risks. Preprint at (2015).

  14. Adler, M. et al. Priority for the worse-off and the social cost of carbon. Nat. Clim. Change 7, 443–449 (2017).

    Article  Google Scholar 

  15. Moyer, E., Woolley, M., Glotter, M. & Weisbach, D. Climate Impacts on Economic Growth as Drivers of Uncertainty in the Social Cost of Carbon Working Paper No. 65 (Coase-Sandor Institute for Law & Economics, 2013).

  16. Kopp, R. E., Golub, A., Keohane, N. O. & Onda, C. The influence of the specification of climate change damages on the social cost of carbon. Economics 6, 2012–13 (2012).

    Google Scholar 

  17. Nordhaus, W. Estimates of the social cost of carbon: concepts and results from the DICE-2013R model and alternative approaches. J. Assoc. Environ. Resour. Econ. 1, 273–312 (2014).

    Google Scholar 

  18. Cai, Y., Judd, K. L. & Lontzek, T. S. The Social Cost of Stochastic and Irreversible Climate Change (National Bureau of Economic Research, 2013).

  19. Barrett, S. Self-enforcing international environmental agreements. Oxf. Econ. Pap. 46, 878–894 (1994).

    Article  Google Scholar 

  20. Carraro, C. & Siniscalco, D. Strategies for the international protection of the environment. J. Public Econ. 52, 309–328 (1993).

    Article  Google Scholar 

  21. Adams, R. M., McCarl, B. A. & Mearns, L. O. in Issues in the Impacts of Climate Variability and Change on Agriculture (ed. Mearns, L. O.) 131–148 (Springer Netherlands, Dordrecht, 2003).

  22. Pizer, W. et al. Using and improving the social cost of carbon. Science 346, 1189–1190 (2014).

    Article  CAS  Google Scholar 

  23. Nordhaus, W. D. Revisiting the social cost of carbon. Proc. Natl Acad. Sci. USA 114, 1518–1523 (2017).

    Article  CAS  Google Scholar 

  24. O’Neill, B. C. et al. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic Change 122, 387–400 (2013).

    Article  Google Scholar 

  25. Riahi, K. et al. The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42, 153–168 (2017).

    Article  Google Scholar 

  26. Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).

    Article  CAS  Google Scholar 

  27. Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

    Article  Google Scholar 

  28. Joos, F. et al. Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis. Atmos. Chem. Phys. 13, 2793–2825 (2013).

    Article  Google Scholar 

  29. Ricke, K. L. & Caldeira, K. Maximum warming occurs about one decade after a carbon dioxide emission. Environ. Res. Lett. 9, 124002 (2014).

    Article  Google Scholar 

  30. Burke, M., Hsiang, S. M. & Miguel, E. Global non-linear effect of temperature on economic production. Nature 527, 235–239 (2015).

    Article  CAS  Google Scholar 

  31. Dell, M., Jones, B. F. & Olken, B. A. Temperature shocks and economic growth: evidence from the last half century. Am. Econ. J. Macroecon. 4, 66–95 (2012).

    Article  Google Scholar 

  32. Diaz, D. & Moore, F. Quantifying the economic risks of climate change. Nat. Clim. Change 7, 774–782 (2017).

    Article  Google Scholar 

  33. Jones, C. I. & Klenow, P. J. Beyond GDP? Welfare across countries and time. Am. Econ. Rev. 106, 2426–2457 (2016).

    Article  Google Scholar 

  34. Guo, J., Hepburn, C., Tol, R. S. J. & Anthoff, D. Discounting and the social cost of carbon: a closer look at uncertainty. Environ. Sci. Policy 9, 205–216 (2006).

    Article  Google Scholar 

  35. Ramsey, F. P. A mathematical theory of saving. Econ. J. 38, 543–559 (1928).

    Article  Google Scholar 

  36. Lemoine, D. & Kapnick, S. A top-down approach to projecting market impacts of climate change. Nat. Clim. Change 6, 51–55 (2016).

    Article  Google Scholar 

  37. Burke, M., Davis, W. M. & Diffenbaugh, N. S. Large potential reduction in economic damages under UN mitigation targets. Nature 557, 549–553 (2018).

    Article  CAS  Google Scholar 

  38. Gastwirth, J. L. The estimation of the Lorenz curve and Gini index. Rev. Econ. Stat. 54, 306–316 (1972).

    Article  Google Scholar 

  39. Raffinetti, E., Siletti, E. & Vernizzi, A. On the Gini coefficient normalization when attributes with negative values are considered. Stat. Methods Appl. 24, 507–521 (2015).

    Article  Google Scholar 

  40. Oh, C. H. & Reuveny, R. Climatic natural disasters, political risk, and international trade. Glob. Environ. Change 20, 243–254 (2010).

    Google Scholar 

  41. Bohra-Mishra, P., Oppenheimer, M. & Hsiang, S. M. Nonlinear permanent migration response to climatic variations but minimal response to disasters. Proc. Natl Acad. Sci. USA 111, 9780–9785 (2014).

    Article  CAS  Google Scholar 

  42. Thornton, J. & Covington, H. Climate change before the court. Nat. Geosci. 9, 3–5 (2016).

    Article  CAS  Google Scholar 

  43. Rao, S. et al. A multi-model assessment of the co-benefits of climate mitigation for global air quality. Environ. Res. Lett. 11, 124013 (2016).

    Article  Google Scholar 

  44. Pindyck, R. S. Climate change policy: what do the models tell us? J. Econ. Lit. 51, 860–872 (2013).

    Article  Google Scholar 

  45. Lempert, R. J. Shaping the Next One Hundred Years: New Methods for Quantitative, Long-Term Policy Analysis (Rand Corporation, 2003).

  46. Matsuura, K. & Willmott, C. Terrestrial Air Temperature and Precipitation: 1900–2006 Gridded Monthly Time Series Version 1.01 (Univ. Delaware, 2007);

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M.T. thanks M. Burke for an early discussion of these ideas and about the climate impact functions. K.R. thanks C. McIntosh and J. Moreno-Cruz for helpful discussions during the revisions of this manuscript. M.T. received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 336155 (project COBHAM). L.D received funding from the EU’s Horizon 2020 research and innovation programme under grant agreement no. 642147 (CD-LINKS).

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Authors and Affiliations



M.T. conceived the study. K.R. performed the climate data analysis. L.D. replicated the economic damage functions and performed the CSCC calculations and uncertainty analysis. K.R., M.T. and L.D. analysed the results. K.R. and M.T. wrote the manuscript. All authors discussed the results and provided input on the manuscript.

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Correspondence to Katharine Ricke.

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Supplementary Information

Supplementary Information

Supplementary Discussion, Supplementary Figures 1–13, Supplementary Tables 1–6, Supplementary References

Supplementary Data 1

CSCC Database

Supplementary Data 2

CSCC Database Readme

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Ricke, K., Drouet, L., Caldeira, K. et al. Country-level social cost of carbon. Nature Clim Change 8, 895–900 (2018).

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