Skip to main content
SpringerLink
Log in

DICE Simplified

  • Published:
Environmental Modeling & Assessment Aims and scope Submit manuscript

Abstract

We analyze Nordhaus’ DICE model and show that the temperature and CO2 equations are needlessly complicated and can be simplified without loss of essence. In addition, we argue that the damage function can be altered in such a way that it lends itself to experiments involving extreme risk. We conclude that, within the philosophy of the DICE model, significant simplifications can be made which make the model more transparent, more robust, and easier to apply.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data Availability

Not applicable.

Code availability

Code is available upon request.

References

  1. Ackerman, F., Stanton, E. A., Bueno, R. (2010). Fat tails, exponents, extreme uncertainty: simulating catastrophe in DICE. Ecological Economics, 69, 1657–1665.

    Article  Google Scholar 

  2. Anderson, K., Peters, G. (2016). The trouble with negative emissions. Science, 354, 182–183.

    Article  CAS  Google Scholar 

  3. Calel, R., & Stainforth, D. A. (2017). On the physics of three integrated assessment models. Bulletin of the American Meteorological Society, 98, 1199–1216.

    Article  Google Scholar 

  4. De Luca, G., Magnus, J. R., Peracchi, F. (2018). Balanced variable addition in linear models. Journal of Economic Surveys, 32, 1183–1200.

    Article  Google Scholar 

  5. Dietz, S., & Venmans, F. (2018). Cumulative carbon emissions and economic policy: in search of general principles. Centre for Climate Change Economics and Policy, Working Paper.

  6. Editorial. (2015). IAM helpful or not? Nature Climate Change, 5, 81.

    Google Scholar 

  7. Editorial. (2018). Why current negative-emissions strategies remain ‘magical thinking’. Nature, 554. https://doi.org/10.1038/d41586-018-02184-x.

  8. Gerlagh, R., & Liski, M. (2018a). Consistent climate policies. Journal of the European Economic Association, 16, 1–44.

    Article  Google Scholar 

  9. Gerlagh, R., & Liski, M. (2018b). Carbon prices for the next hundred years. The Economic Journal, 128, 728–757.

    Article  Google Scholar 

  10. Golosov, M., Hassler, J., Krusell, P., Tsyvinski, A. (2014). Optimal taxes on fossil fuel in general equilibrium. Econometrica, 82, 41–88.

    Article  Google Scholar 

  11. Howard, P. H., & Sterner, T. (2017). Few and not so far between: a meta-analysis of climate damage estimates. Environmental Resource Economics, 68, 197–225.

    Article  Google Scholar 

  12. Ikefuji, M., Laeven, R. J. A., Magnus, J. R., Muris, C. (2013). Pareto utility. Theory and Decision, 75, 43–57.

    Article  Google Scholar 

  13. Ikefuji, M., Laeven, R. J. A., Magnus, J. R., Muris, C. (2015). Expected utility and catastrophic consumption risk. Insurance: Mathematics and Economics, 64, 306–312.

    Google Scholar 

  14. Ikefuji, M., Laeven, R. J. A., Magnus, J. R., Muris, C. (2020). Expected utility and catastrophic risk in a stochastic economy-climate model. Journal of Econometrics, 214, 110–129.

    Article  Google Scholar 

  15. Kelly, D. L., & Kolstad, C. D. (1999). Bayesian learning, growth, and pollution. Journal of Economic Dynamics & Control, 23, 491–518.

    Article  Google Scholar 

  16. Lemoine, D., & Rudik, I. (2017). Steering the climate system: using inertia to lower the cost of policy. American Economic Review, 107, 2947–2957.

    Article  Google Scholar 

  17. Nordhaus, W. D. (1992). An optimal transition path for controlling greenhouse gases. Science, 258, 1315–1319.

    Article  CAS  Google Scholar 

  18. Nordhaus, W. D. (2008). A question of balance: weighing the options on global warming policies. New Haven: Yale University Press.

    Google Scholar 

  19. Nordhaus, W. D. (2013). The climate casino: risk, uncertainty, and economics for a warming world. New Haven: Yale University Press.

    Google Scholar 

  20. Nordhaus, W. D. (2017). Revisiting the social cost of carbon. Proceedings of the U.S. National Academy of Sciences, 114, 1518–1523.

    Article  CAS  Google Scholar 

  21. Nordhaus, W. D. (2018a). Projections and uncertainties about climate change in an era of minimal climate policies. American Economic Journal: Economic Policy, 10, 333–360.

    Google Scholar 

  22. Nordhaus, W. D. (2018b). Evolution of modeling of the economics of global warming: changes in the DICE model, 1992–2017. Climatic Change, 148, 623–640.

    Article  Google Scholar 

  23. Pindyck, R. S. (2013). Climate change policy: what do the models tell us? Journal of Economic Literature, 51, 860–872.

    Article  Google Scholar 

  24. Pindyck. R. S. (2017). The use and misuse of models for climate policy. Review of Environmental Economics and Policy, 11, 100–114.

    Article  Google Scholar 

  25. Rezai, A., & Van der Ploeg, F. (2016). Intergenerational inequality aversion, growth, and the role of damages: Occam’s rule for the global carbon tax. Journal of the Association of Environmental and Resource Economists, 3, 493–522.

    Article  Google Scholar 

  26. Ricke, K. L., & Caldeira, K. (2014). Maximum warming occurs about one decade after a carbon dioxide emission. Environmental Research Letters, 9, 124002.

    Article  Google Scholar 

  27. Roe, G. H., & Bauman, Y. (2013). Climate sensitivity: should the climate tail wag the policy dog? Climatic Change, 117, 647–662.

    Article  Google Scholar 

  28. Stern, N. (2007). The economics of climate change: the Stern review. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  29. Traeger, CP. (2015). Analytic integrated assessment and uncertainty. Mimeo.

  30. Van den Bijgaart, I., Gerlagh, R., Liski, M. (2016). A simple formula for the social cost of carbon. Journal of Environmental Economics and Management, 77, 75–94.

    Article  Google Scholar 

  31. Van der Ploeg, F. (2018). The safe carbon budget. Climatic Change, 147, 47–59.

    Article  Google Scholar 

  32. Weitzman, M. L. (2009). On modeling and interpreting the economics of catastrophic climate change. The Review of Economics and Statistics, 91, 1–19.

    Article  Google Scholar 

Download references

Acknowledgments

We are grateful to the editor and advisory editor, and to Peter Boswijk, Rick van der Ploeg, and Hiroaki Sakamoto for comments and suggestions.

Funding

This research was funded in part by the Japan Society for the Promotion of Science (JSPS), KAKENHI Grant JP19K01669 (Ikefuji), and the Netherlands Organization for Scientific Research (NWO) under grant Vidi-2009 (Laeven).

Author information

Authors and Affiliations

  1. Faculty of Humanities and Social Sciences, University of Tsukuba, Ibaraki, Japan

    Masako Ikefuji

  2. ISER, Osaka University, Osaka, Japan

    Masako Ikefuji

  3. Amsterdam School of Economics, University of Amsterdam, CentER, Amsterdam, The Netherlands

    Roger J. A. Laeven

  4. EURANDOM, Eindhoven, The Netherlands

    Roger J. A. Laeven

  5. Department of Econometrics and Data Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Jan R. Magnus

  6. Tinbergen Institute, Amsterdam, The Netherlands

    Jan R. Magnus

  7. Department of Economics, McMaster University, Hamilton, Canada

    Chris Muris

Authors
  1. Masako Ikefuji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Roger J. A. Laeven
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jan R. Magnus
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chris Muris
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Masako Ikefuji.

Ethics declarations

Conflict of Interest

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

In this Appendix, we present two tables which together contain all variable and parameter definitions required to compute the optimum in DICE (the Nordhaus model) and S-DICE (our simplified version of DICE): the variables employed in S-DICE and DICE and their relationship, and the initial values of the six state variables of DICE (Table 4); and the parameters employed in S-DICE and DICE and their relationship (Table 5).

Table 4 Variables in S-DICE and DICE
Full size table
Table 5 Parameters in S-DICE and DICE
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ikefuji, M., Laeven, R.J.A., Magnus, J.R. et al. DICE Simplified. Environ Model Assess 26, 1–12 (2021). https://doi.org/10.1007/s10666-020-09738-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10666-020-09738-2

Keywords

Search

Navigation