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Quantification of an efficiency–sovereignty trade-off in climate policy

Abstract

The Paris Agreement calls for a cooperative response with the aim of limiting global warming to well below two degrees Celsius above pre-industrial levels while reaffirming the principles of equity and common, but differentiated responsibilities and capabilities1. Although the goal is clear, the approach required to achieve it is not. Cap-and-trade policies using uniform carbon prices could produce cost-effective reductions of global carbon emissions, but tend to impose relatively high mitigation costs on developing and emerging economies. Huge international financial transfers are required to complement cap-and-trade to achieve equal sharing of effort, defined as an equal distribution of mitigation costs as a share of income2,3, and therefore the cap-and-trade policy is often perceived as infringing on national sovereignty2,3,4,5,6,7. Here we show that a strategy of international financial transfers guided by moderate deviations from uniform carbon pricing could achieve the goal without straining either the economies or sovereignty of nations. We use the integrated assessment model REMIND–MAgPIE to analyse alternative policies: financial transfers in uniform carbon pricing systems, differentiated carbon pricing in the absence of financial transfers, or a hybrid combining financial transfers and differentiated carbon prices. Under uniform carbon prices, a present value of international financial transfers of 4.4 trillion US dollars over the next 80 years to 2100 would be required to equalize effort. By contrast, achieving equal effort without financial transfers requires carbon prices in advanced countries to exceed those in developing countries by a factor of more than 100, leading to efficiency losses of 2.6 trillion US dollars. Hybrid solutions reveal a strongly nonlinear trade-off between cost efficiency and sovereignty: moderate deviations from uniform carbon prices strongly reduce financial transfers at relatively small efficiency losses and moderate financial transfers substantially reduce inefficiencies by narrowing the carbon price spread. We also identify risks and adverse consequences of carbon price differentiation due to market distortions that can undermine environmental sustainability targets8,9. Quantifying the advantages and risks of carbon price differentiation provides insight into climate and sector-specific policy mixes.

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Fig. 1: World economic development and emission mitigation projections.
Fig. 2: Carbon pricing and regional effort.
Fig. 3: Sovereignty versus cost-efficiency trade-off and consequences of differentiated carbon prices.

Data availability

Scenario data have been uploaded in Zenodo with the identifier https://doi.org/10.5281/zenodo.4010426. Source data are provided with this paper.

Code availability

The model codes of REMIND (identifier: ab2c995116e7fb402f6dd0183724496373af996e) and MAgPIE (identifier: 950bc7a08fd0e6c8f790c1399c7837133233e2fc) are open source (https://github.com/remindmodel/remind and https://github.com/magpiemodel/magpie).

References

  1. 1.

    Okereke, C. & Coventry, P. Climate justice and the international regime: before, during, and after Paris: climate justice and the international regime. Wiley Interdiscip. Rev. Clim. Change 7, 834–851 (2016).

    Google Scholar 

  2. 2.

    Tavoni, M. et al. Post-2020 climate agreements in the major economies assessed in the light of global models. Nat. Clim. Change 5,119–126 (2015).

    ADS  Google Scholar 

  3. 3.

    Tavoni, M. et al. The distribution of the major economies’ effort in the Durban Platform scenarios. Clim. Change Econ. 04, 1340009 (2013).

    Google Scholar 

  4. 4.

    Leimbach, M. & Giannousakis, A. Burden sharing of climate change mitigation: global and regional challenges under shared socio-economic pathways. Climatic Change 155, 273–291 (2019).

    ADS  Google Scholar 

  5. 5.

    Lüken, M. et al. The role of technological availability for the distributive impacts of climate change mitigation policy. Energy Policy 39, 6030–6039 (2011).

    Google Scholar 

  6. 6.

    Aldy, J. E., Krupnick, A. J., Newell, R. G., Parry, I. W. H. & Pizer, W. A. Designing climate mitigation policy. J. Econ. Lit. 48, 903–934 (2010).

    Google Scholar 

  7. 7.

    Victor, V. The Collapse of the Kyoto Protocol and the Struggle to Slow Global Warming (Princeton Univ. Press, 2001).

  8. 8.

    González-Eguino, M., Capellán-Pérez, I., Arto, I., Ansuategi, A. & Markandya, A. Industrial and terrestrial carbon leakage under climate policy fragmentation. Clim. Policy 17, S148–S169 (2017).

    Google Scholar 

  9. 9.

    Otto, S. A. C. et al. Impact of fragmented emission reduction regimes on the energy market and on CO2 emissions related to land use: a case study with China and the European Union as first movers. Technol. Forecast. Soc. Change 90, 220–229 (2015).

    Google Scholar 

  10. 10.

    Böhringer, C. & Welsch, H. Burden sharing in a greenhouse: egalitarianism and sovereignty reconciled. Appl. Econ. 38, 981–996 (2006).

    Google Scholar 

  11. 11.

    Nordhaus, W. Climate clubs: overcoming free-riding in international climate policy. Am. Econ. Rev. 105, 1339–1370 (2015).

    Google Scholar 

  12. 12.

    Csereklyei, Z. & Stern, D. I. Global energy use: decoupling or convergence? Energy Econ. 51, 633–641 (2015).

    Google Scholar 

  13. 13.

    International Comparison Program Purchasing Power Parities and Real Expenditures of World Economies: Summary of Results and Findings of the 2011 International Comparison Program (World Bank, 2014).

  14. 14.

    Stern, D. I., Pezzey, J. C. V. & Lambie, N. R. Where in the world is it cheapest to cut carbon emissions? Aust. J. Agric. Resour. Econ. 56, 315–331 (2012).

    Google Scholar 

  15. 15.

    Fujimori, S. et al. Will international emissions trading help achieve the objectives of the Paris Agreement? Environ. Res. Lett. 11, 104001 (2016).

    ADS  Google Scholar 

  16. 16.

    Weyant, J. P. & Hill, J. Introduction and overview. The costs of the Kyoto Protocol: a multi-model evaluation. Energy J. (Spec. Issue) vii–xliv (1999).

  17. 17.

    Zhou, P. & Wang, M. Carbon dioxide emissions allocation: a review. Ecol. Econ. 125, 47–59 (2016).

    Google Scholar 

  18. 18.

    van den Berg, N. J. et al. Implications of various effort-sharing approaches for national carbon budgets and emission pathways. Climatic Change https://doi.org/10.1007/s10584-019-02368-y (2019).

  19. 19.

    Höhne, N., den Elzen, M. & Escalante, D. Regional GHG reduction targets based on effort sharing: a comparison of studies. Clim. Policy 14, 122–147 (2014).

    Google Scholar 

  20. 20.

    Manne, A. S. & Stephan, G. Global climate change and the equity–efficiency puzzle. Energy 30, 2525–2536 (2005).

    Google Scholar 

  21. 21.

    Kriegler, E. et al. Making or breaking climate targets: the AMPERE study on staged accession scenarios for climate policy. Technol. Forecast. Soc. Change 90, 24–44 (2015).

    Google Scholar 

  22. 22.

    Aldy, J. et al. Economic tools to promote transparency and comparability in the Paris Agreement. Nat. Clim. Change 6, 1000–1004 (2016).

    ADS  Google Scholar 

  23. 23.

    Jacoby, H. D., Chen, Y.-H. H. & Flannery, B. P. Informing transparency in the Paris Agreement: the role of economic models. Clim. Policy 17, 873–890 (2017).

    Google Scholar 

  24. 24.

    Vandyck, T., Keramidas, K., Saveyn, B., Kitous, A. & Vrontisi, Z. A global stocktake of the Paris pledges: implications for energy systems and economy. Glob. Environ. Change 41, 46–63 (2016).

    Google Scholar 

  25. 25.

    Vrontisi, Z. et al. Enhancing global climate policy ambition towards a 1.5 °C stabilization: a short-term multi-model assessment. Environ. Res. Lett. 13, 044039 (2018).

    ADS  Google Scholar 

  26. 26.

    Rogelj, J. et al. Paris Agreement climate proposals need a boost to keep warming well below 2 °C. Nature 534, 631–639 (2016).

    ADS  CAS  PubMed  Google Scholar 

  27. 27.

    The Emissions Gap Report 2019 (UNEP, 2019).

  28. 28.

    Luderer, G. et al. Residual fossil CO2 emissions in 1.5–2 °C pathways. Nat. Clim. Change 8, 626–633 (2018).

    ADS  CAS  Google Scholar 

  29. 29.

    Kriegler, E. et al. Fossil-fueled development (SSP5): an energy and resource intensive scenario for the 21st century. Glob. Environ. Change 42, 297–315 (2017).

    Google Scholar 

  30. 30.

    Dellink, R., Chateau, J., Lanzi, E. & Magné, B. Long-term economic growth projections in the shared socioeconomic pathways. Glob. Environ. Change 42, 200–214 (2017).

    Google Scholar 

  31. 31.

    Rogelj, J., Forster, P. M., Kriegler, E., Smith, C. J. & Séférian, R. Estimating and tracking the remaining carbon budget for stringent climate targets. Nature 571, 335–342 (2019); correction 580, E4 (2020).

    ADS  CAS  PubMed  Google Scholar 

  32. 32.

    Luderer, G. et al. Economic mitigation challenges: how further delay closes the door for achieving climate targets. Environ. Res. Lett. 8, 034033 (2013).

    ADS  Google Scholar 

  33. 33.

    Bauer, N. et al. Shared socio-economic pathways of the energy sector—quantifying the narratives. Glob. Environ. Change 42, 316–330 (2017).

    Google Scholar 

  34. 34.

    Diffenbaugh, N. S. & Burke, M. Global warming has increased global economic inequality. Proc. Natl Acad. Sci. USA 116, 9808–9813 (2019).

    CAS  PubMed  Google Scholar 

  35. 35.

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

    ADS  CAS  PubMed  Google Scholar 

  36. 36.

    De Cian, E., Hof, A. F., Marangoni, G., Tavoni, M. & van Vuuren, D. P. Alleviating inequality in climate policy costs: an integrated perspective on mitigation, damage and adaptation. Environ. Res. Lett. 11, 074015 (2016).

    ADS  Google Scholar 

  37. 37.

    Evans, D. J. & Sezer, H. Social discount rates for member countries of the European Union. J. Econ. Stud. 32, 47–59 (2005).

    ADS  Google Scholar 

  38. 38.

    Weitzman, M. L. Can negotiating a uniform carbon price help to internalize the global warming externality? J. Assoc. Environ. Resour. Econ. 1, 29–49 (2014).

    Google Scholar 

  39. 39.

    Barrett, S. in Conflicts and Cooperation in Managing Environmental Resources (ed. Pethig, R.) 11–35 (Springer, 1991).

  40. 40.

    Carraro, C. & Siniscalco, D. in The Economics of Sustainable Development (eds Goldin, I. & Winters, L. A.) 264–288 (Cambridge Univ. Press, 1995).

  41. 41.

    Kornek, U. & Edenhofer, O. The strategic dimension of financing global public goods. Eur. Econ. Rev. 127, 103423 (2020).

    Google Scholar 

  42. 42.

    Lazarus, M. & van Asselt, H. Fossil fuel supply and climate policy: exploring the road less taken. Climatic Change 150, 1–13 (2018).

    ADS  Google Scholar 

  43. 43.

    Canadell, J. G. & Raupach, M. R. Managing forests for climate change mitigation. Science 320, 1456–1457 (2008).

    ADS  CAS  PubMed  Google Scholar 

  44. 44.

    Glachant, M. & Dechezleprêtre, A. What role for climate negotiations on technology transfer? Clim. Policy 17, 962–981 (2017).

    Google Scholar 

  45. 45.

    Schultes, A. et al. Optimal international technology cooperation for the low-carbon transformation. Clim. Policy 18, 1165–1176 (2018).

    Google Scholar 

  46. 46.

    Paroussos, L. et al. Climate clubs and the macro-economic benefits of international cooperation on climate policy. Nat. Clim. Change 9, 542–546 (2019).

    ADS  Google Scholar 

  47. 47.

    Chichilnisky, G. & Heal, G. Who should abate carbon emissions? An international viewpoint. Econ. Lett. 44, 443–449 (1994).

    MATH  Google Scholar 

  48. 48.

    Obersteiner, M. et al. How to spend a dwindling greenhouse gas budget. Nat. Clim. Change 8, 7–10 (2018).

    ADS  Google Scholar 

  49. 49.

    Realmonte, G. et al. An inter-model assessment of the role of direct air capture in deep mitigation pathways. Nat. Commun. 10, 3277 (2019).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Azar, C., Johansson, D. J. A. & Mattsson, N. Meeting global temperature targets—the role of bioenergy with carbon capture and storage. Environ. Res. Lett. 8, 034004 (2013).

    ADS  Google Scholar 

  51. 51.

    Lundsgaarde, E., Dupuy, K. & Persson, A. Coordination Challenges in Climate Finance (Danish Institute for International Studies, 2018); https://www.econstor.eu/bitstream/10419/204624/1/1042180393.pdf

  52. 52.

    Motty, M. & Ackom, E. K. in Climate Action (eds Leal Filho, W. et al.) 1–11 (Springer International Publishing, 2019); https://doi.org/10.1007/978-3-319-71063-1_104-2

  53. 53.

    Sharma, A. Precaution and post-caution in the Paris Agreement: adaptation, loss and damage and finance. Clim. Policy 17, 33–47 (2017).

    Google Scholar 

  54. 54.

    BP Statistical Review of World Energy 2020 (BP, 2020); https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/downloads.html

  55. 55.

    World Development Indicators, DataBank (World Bank, 2020); https://databank.worldbank.org/source/world-development-indicators#

  56. 56.

    Kriegler, E. et al. The role of technology for achieving climate policy objectives: overview of the EMF 27 study on global technology and climate policy strategies. Climatic Change 123, 353–367 (2014).

    ADS  Google Scholar 

  57. 57.

    Riahi, K. et al. Locked into Copenhagen pledges—implications of short-term emission targets for the cost and feasibility of long-term climate goals. Technol. Forecast. Soc. Change 90, 8–23 (2015).

    Google Scholar 

  58. 58.

    Kriegler, E. et al. Will economic growth and fossil fuel scarcity help or hinder climate stabilization? Climatic Change 136, 7–22 (2016).

    ADS  Google Scholar 

  59. 59.

    Roelfsema, M. et al. Taking stock of national climate policies to evaluate implementation of the Paris Agreement. Nat. Commun. 11, 2096 (2020).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  60. 60.

    McCollum, D. L. et al. Energy investment needs for fulfilling the Paris Agreement and achieving the Sustainable Development Goals. Nat. Energy 3, 589–599 (2018); correction 3, 699 (2018).

    ADS  Google Scholar 

  61. 61.

    Bauer, N. et al. Global energy sector emission reductions and bioenergy use: overview of the bioenergy demand phase of the EMF-33 model comparison. Climatic Change https://doi.org/10.1007/s10584-018-2226-y (2018).

  62. 62.

    Riahi, K. et al. in Global Energy Assessment—Toward a Sustainable Future 1203–1306 (Cambridge Univ. Press, 2012).

  63. 63.

    Krey, V. et al. in IPCC Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) 1281–1328 (Cambridge Univ. Press, 2014).

  64. 64.

    Huppmann, D., Rogelj, J., Krey, V., Kriegler, E. & Riahi, K. A new scenario resource for integrated 1.5 °C research. Nat. Clim. Change 8, 1027–1030 (2018)

    ADS  Google Scholar 

  65. 65.

    KC, S. & Lutz, W. The human core of the shared socioeconomic pathways: population scenarios by age, sex and level of education for all countries to 2100. Glob. Environ. Change 42, 181–192 (2017).

    PubMed  PubMed Central  Google Scholar 

  66. 66.

    South, A. rworldmap: a new R package for mapping global data. The R Journal 3, 35–43 (2011).

    Google Scholar 

  67. 67.

    Bauer, N. et al. Bio-energy and CO2 emission reductions: an integrated land-use and energy sector perspective. Clim. Change https://doi.org/10.1007/s10584-020-02895-z (2020).

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Acknowledgements

We acknowledge funding from the German Federal Ministry of Education and Research (BMBF) in the Funding Priority ‘Economics of Climate Change’ (DIPOL: 01LA1809A). This work was supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement numbers 730403 and 821124.

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Contributions

N.B., C.B., D.K. and A.S. developed the policy analysis framework and designed the experiments. N.B. and A.S. implemented the policy framework. N.B. wrote the manuscript (with assistance from C.B. and G.L.). N.B. led the analysis and writing of the manuscript with contributions from all authors.

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Correspondence to Nico Bauer.

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The authors declare no competing interests.

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Peer review information Nature thanks Hancheng Dai, Ritu Mathur, Wei Peng and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1

Graphical illustration of the distributional effects between advanced economy A and developing economy B for different policy frameworks characterized by different marginal abatement cost functions fA and fB. The case ‘Uniform price w/o transfers’ with carbon prices equal to p in both regions implies different mitigation costs. In the case ‘Uniform price w/ transfers’ these differences are neutralized by transfers T. Alternatively, in the case ‘No transfer’ the differentiation of policies leads to equal costs; this case is not depicted explicitly. The case ‘Hybrid’ differentiates carbon prices to reduce T. The change of global mitigation cost is only the difference between the regional mitigation costs ΔACa − ΔACb (indicated by the red triangles), whereas the changes of transfers are represented by the orange rectangles pΔR. As long as the differentiation of prices is relatively small, the decline of transfers exceeds the increase in global mitigation costs.

Extended Data Fig. 2 Illustration of the exponential compression function.

The x axis shows the 2030 carbon prices in the full differentiation case (see Fig. 2a). The example applies the parameter α = 0.5 to the compression function \({p}_{r}={\tilde{p}}^{{\rm{\min }}}{({\tilde{p}}_{r}/{\tilde{p}}^{{\rm{\min }}})}^{\alpha }\) that has been introduced in the Methods. The y axis shows the carbon prices after compression. The figure shows a subset of regions and the light grey line highlights the compression for Latin America and the EU. We note that the set of compressed carbon prices is scaled to comply with the global carbon budget (that is, the relative differences of the carbon price spread remain constant).

Extended Data Fig. 3 Socioeconomic drivers and CO2 emissions in the no-policy baseline scenario.

a, b, Population (a) and economic growth (b) from history 1990–2015 and in the SSP2 baseline scenario 2015–210030,65. c, d, Energy and industry CO2 emissions (c) as well as total CO2 emissions (d). See ‘Data availability’ section for more details.

Extended Data Fig. 4 Time path of transfers in the default case with uniform carbon prices.

The transfers are expressed as percentages of GDP in the OECD and the non-OECD regions. The dashed line serves as a point of orientation. It represents the share of the US$100 billion relative to the OECD’s GDP in 2020.

Extended Data Fig. 5 Effect of carbon price differentiation on primary and final energy use.

a, b, Changes in the global energy mixes distinguished by energy carriers and regions. The figure depicts differences compared with the uniform carbon tax case for the 1,300 GtCO2 carbon budget. Primary energy (a) is measured according to the direct equivalence principle; final energy (b) is measured as delivered to final consumer. This means that fossil fuels, biomass and geothermal energy are measured in primary energy input, whereas renewables (hydro, wind and solar) as well as nuclear energy are measured by their electricity output. Notable results are as follows. First, the total amount of energy use increases. Second, OECD countries mostly reduce residual oil and gas consumption, but non-OECD countries mostly increase the use of coal; therefore, the total consumption of coal increases, whereas the global use of oil and gas decreases. Third, the total use of biomass increases due to increasing demand in OCED countries. Fourth, OECD countries accelerate modernization of final energy use by mainly reducing the use of liquids and gases, but increasing electricity and hydrogen. Finally, non-OECD countries delay modernization of energy use by mainly increasing the use of solids, liquids and gases with corresponding implications for air pollution and so on.

Extended Data Fig. 6 Effect of carbon price differentiation on land-use change and investments.

a, b, Changes in global land use (a) and investment and regions (b). The figure depicts differences compared with the uniform carbon tax case for the 1,300 GtCO2 carbon budget. The two regions show opposite changes in the variables; for example, OECD countries convert agricultural land into forests to remove carbon by afforestation, whereas non-OECD countries convert forests into cropland to grow biomass that is exported to OECD countries. Moreover, OECD countries increase investments in the energy sector substantially to facilitate the transition to low-carbon technologies and to invest into carbon-removal technologies (which are counted as part of the energy sector). The higher OECD investments crowd-out the macroeconomic investments in OECD countries and energy sector investments in non-OECD countries.

Extended Data Fig. 7 Sensitivity analysis of the trade-off curve.

a, The sensitivity of the ban on bioenergy trade. b, The sensitivity with respect to the carbon budget. c, The variation of the maximum annual retirement rate of fossil-fuelled infrastructure from 9% to 6% and the delayed availability of technologies that rely on underground geological storage of CO2 (that is, CCS including direct air capture). d, The application of the linear compression function; in this sensitivity analysis the case of uniform taxes and the no-transfer case are identical.

Extended Data Fig. 8 Regional aggregates used in REMIND and MAgPIE.

Regions and countries belonging to the OECD region are coloured in blue tones. See ‘Data availability’ section for more details. World map based on rworldmap package66.

Extended Data Table 1 Overview of data sources for model comparisons
Extended Data Table 2 Overview of selected sensitivity cases

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Bauer, N., Bertram, C., Schultes, A. et al. Quantification of an efficiency–sovereignty trade-off in climate policy. Nature 588, 261–266 (2020). https://doi.org/10.1038/s41586-020-2982-5

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