Abstract
Several major economies rely heavily on fossil fuel production and exports, yet current low-carbon technology diffusion, energy efficiency and climate policy may be substantially reducing global demand for fossil fuels1,2,3,4. This trend is inconsistent with observed investment in new fossil fuel ventures1,2, which could become stranded as a result. Here, we use an integrated global economy–environment simulation model to study the macroeconomic impact of stranded fossil fuel assets (SFFA). Our analysis suggests that part of the SFFA would occur as a result of an already ongoing technological trajectory, irrespective of whether or not new climate policies are adopted; the loss would be amplified if new climate policies to reach the 2 °C target of the Paris Agreement are adopted and/or if low-cost producers (some OPEC countries) maintain their level of production (‘sell out’) despite declining demand; the magnitude of the loss from SFFA may amount to a discounted global wealth loss of US$1–4 trillion; and there are clear distributional impacts, with winners (for example, net importers such as China or the EU) and losers (for example, Russia, the United States or Canada, which could see their fossil fuel industries nearly shut down), although the two effects would largely offset each other at the level of aggregate global GDP.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
World Energy Investment (OECD/IEA, 2017).
World Energy Outlook (OECD/IEA, 2016).
Global Trends in Renewable Energy Investment (UNEP, 2016).
Global EV Outlook (OECD/IEA, 2017).
Paris Agreement Article 2(1)(a) (UNFCCC, 2015); http://unfccc.int/files/essential_background/convention/application/pdf/english_paris_agreement.pdf
McGlade, C. & Ekins, P. The geographical distribution of fossil fuels unused when limiting global warming to 2 °C. Nature 517, 187–190 (2015).
McGlade, C. & Ekins, P. Un-burnable oil: an examination of oil resource utilisation in a decarbonised energy system. Energy Policy 64, 102–112 (2014).
Sussams, L. & Leaton, J. Expect the Unexpected: The Disruptive Power of Low-Carbon Technology (Carbon Tracker and Grantham Institute, 2017); https://www.carbontracker.org/reports/expect-the-unexpected-the-disruptive-power-of-low-carbon-technology
Leaton, J. & Sussams, L. Unburnable Carbon: Are the World’s Financial Markets Carrying a Carbon Bubble? (Carbon Tracker, 2011); https://www.carbontracker.org/reports/carbon-bubble/
Heede, R. & Oreskes, N. Potential emissions of CO2 and methane from proved reserves of fossil fuels: an alternative analysis. Glob. Environ. Change 36, 12–20 (2016).
Carney, M. Breaking the Tragedy of the Horizon—Climate Change and Financial Stability—Speech by Mark Carney (Bank of England, 2015); http://www.bankofengland.co.uk/publications/Pages/speeches/2015/844.aspx
The Impact of Climate Change on the UK Insurance Sector (Bank of England Prudential Regulation Authority, 2015); https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/publication/impact-of-climate-change-on-the-uk-insurance-sector.pdf
Recommendations of the Task Force on Climate-Related Financial Disclosures (TCFD, 2017); https://www.fsb-tcfd.org/wp-content/uploads/2017/06/FINAL-TCFD-Report-062817.pdf
Battiston, S., Mandel, A., Monasterolo, I., Schütze, F. & Visentin, G. A climate stress-test of the financial system. Nat. Clim. Change 7, 283–288 (2017).
Nachmany, M. et al. The Global Climate Legislation Study—2016 Update (LSE and Grantham Institute, 2016); http://www.lse.ac.uk/GranthamInstitute/publication/2015-global-climate-legislation-study/
Marrakech Action Proclamation for Our Climate and Sustainable Development (UNFCCC, 2016); https://unfccc.int/files/meetings/marrakech_nov_2016/application/pdf/marrakech_action_proclamation.pdf
Sinn, H.-W. Public policies against global warming: a supply side approach. Int. Tax Public Finance 15, 360–394 (2008).
Blanchard, O. J. The Crisis: Basic Mechanisms, and Appropriate Policies Working Paper WP/09/80 (IMF, 2008); https://www.imf.org/external/pubs/ft/wp/2009/wp0980.pdf
Clarke, L. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) Ch. 6 (IPCC, Cambridge Univ. Press, 2014).
McCollum, D. L. et al. Quantifying uncertainties influencing the long-term impacts of oil prices on energy markets and carbon emissions. Nat. Energy 1, 16077 (2016).
Bauer, N. et al. CO2 emission mitigation and fossil fuel markets: dynamic and international aspects of climate policies. Technol. Forecast. Social Change 90, 243–256 (2015).
Mercure, J.-F. et al. Environmental impact assessment for climate change policy with the simulation-based integrated assessment model E3ME-FTT-GENIE. Energy Strategy Reviews 20, 195–208(2018).
Mercure, J.-F., Pollitt, H., Bassi, A. M., Viñuales, J. E. & Edwards, N. R. Modelling complex systems of heterogeneous agents to better design sustainability transitions policy. Glob. Environ. Change 37, 102–115 (2016).
Mercure, J. et al. Policy-induced Energy Technological Innovation and Finance for Low-carbon Economic Growth. Study on the Macroeconomics of Energy and Climate Policies (European Commission, 2016); https://ec.europa.eu/energy/sites/ener/files/documents/ENER%20Macro-Energy_Innovation_D2%20Final%20(Ares%20registered).pdf
Mercure, J.-F. et al. The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector. Energy Policy 73, 686–700 (2014).
Mercure, J.-F., Lam, A., Billington, S. & Pollitt, H. Integrated assessment modelling as a positive science: private passenger road transport policies to meet a climate target well below 2 degrees C. Preprint at https://arxiv.org/abs/1702.04133 (2018).
Fuss, S. et al. Betting on negative emissions. Nat. Clim. Change 4, 850–853 (2014).
Mercure, J.-F. & Salas, P. On the global economic potentials and marginal costs of non-renewable resources and the price of energy commodities. Energy Policy 63, 469–483 (2013).
World Energy Outlook (OECD/IEA, 2014).
The E3ME Model (Cambridge Econometrics, 2017); http://www.e3me.com
Barker, T., Alexandri, E., Mercure, J.-F., Ogawa, Y. & Pollitt, H. GDP and employment effects of policies to close the 2020 emissions gap. Clim. Policy 16, 393–414 (2016).
Pollitt, H., Alexandri, E., Chewpreecha, U. & Klaassen, G. Macroeconomic analysis of the employment impacts of future EU climate policies. Clim. Policy 15, 604–625 (2015).
Pollitt, H. & Mercure, J.-F. The role of money and the financial sector in energy-economy models used for assessing climate and energy policy. Clim. Policy 18, 184–197 (2017).
Lavoie, M. Post-Keynesian Economics: New Foundations (Edward Elgar, Cheltenham, 2014).
McLeay, M., Radia, A. & Thomas, R. Money in the Modern Economy: An Introduction (Bank of England, 2014); http://www.bankofengland.co.uk/publications/Pages/quarterlybulletin/2014/qb14q1.aspx
McLeay, M., Radia, A. & Thomas, R. Money Creation in the Modern Economy (Bank of England, 2014); http://www.bankofengland.co.uk/publications/Pages/quarterlybulletin/2014/qb14q1.aspx
Employment Effects of Selected Scenarios from the Energy Roadmap 2050 (Cambridge Econometrics, 2013); http://ec.europa.eu/energy/sites/ener/files/documents/2013_report_employment_effects_roadmap_2050_2.pdf
Assessing the Employment and Social Impact of Energy Efficiency (Cambridge Econometrics, 2015); https://ec.europa.eu/energy/sites/ener/files/documents/CE_EE_Jobs_main%2018Nov2015.pdf
Lee, S., Pollitt, H. & Park, S.-J. (eds) Low-Carbon, Sustainable Future in East Asia: Improving Energy Systems, Taxation and Policy Cooperation (Routledge, London, 2015).
Ackerman, F., DeCanio, S. J., Howarth, R. B. & Sheeran, K. Limitations of integrated assessment models of climate change. Clim. Change 95, 297–315 (2009).
Pindyck, R. S. Climate change policy: what do the models tell us? J. Econ. Lit. 51, 860–872 (2013).
Weyant, J. P. A perspective on integrated assessment. Clim. Change 95, 317–323 (2009).
Geels, F. W., Berkhout, F. & van Vuuren, D. P. Bridging analytical approaches for low-carbon transitions. Nat. Clim. Change 6, 576–583 (2016).
Turnheim, B. et al. Evaluating sustainability transitions pathways: bridging analytical approaches to address governance challenges. Glob. Environ. Change 35, 239–253 (2015).
Popp, D. & Newell, R. Where does energy R&D come from? Examining crowding out from energy R&D. Energy Econ. 34, 980–991 (2012).
Hottenrott, H. & Rexhäuser, S. Policy-induced environmental technology and inventive efforts: is there a crowding out? Ind. Innov. 22, 375–401 (2015).
Barker, T. & Crawford-Brown, D. (eds) Decarbonising the World’s Economy: Assessing the Feasibility of Policies to Reduce Greenhouse Gas Emissions (Imperial College Press, London, 2014).
Grübler, A., Nakićenović, N. & Victor, D. G. Dynamics of energy technologies and global change. Energy Policy 27, 247–280 (1999).
Mercure, J.-F. FTT:Power: a global model of the power sector with induced technological change and natural resource depletion. Energy Policy 48, 799–811 (2012).
Mercure, J.-F. & Lam, A. The effectiveness of policy on consumer choices for private road passenger transport emissions reductions in six major economies. Environ. Res. Lett. 10, 064008 (2015).
Hofbauer, J. & Sigmund, K. Evolutionary Games and Population Dynamics (Cambridge Univ. Press, Cambridge, 1998).
Mercure, J.-F. Fashion, fads and the popularity of choices: micro-foundations for diffusion consumer theory. Preprint at https://arxiv.org/abs/1607.04155 (2018).
Mercure, J.-F. An age structured demographic theory of technological change. J. Evolut. Econ. 25, 787–820 (2015).
Geels, F. W. Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study. Res. Policy 31, 1257–1274 (2002).
Wilson, C. Up-scaling, formative phases, and learning in the historical diffusion of energy technologies. Energy Policy 50, 81–94 (2012).
Rogers, E. M. Diffusion of Innovations (Simon and Schuster, New York, NY, 2010).
Holden, P. B., Edwards, N. R., Gerten, D. & Schaphoff, S. A model-based constraint on CO2 fertilisation. Biogeosciences 10, 339–355 (2013).
Marsh, R., Müller, S., Yool, A. & Edwards, N. Incorporation of the C-GOLDSTEIN efficient climate model into the GENIE framework: “eb_go_gs” configurations of GENIE. Geosci. Model Dev. 4, 957–992 (2011).
Ridgwell, A. & Hargreaves, J. Regulation of atmospheric CO2 by deep-sea sediments in an Earth system model. Glob. Biogeochem. Cycles 21, GB2008 (2007).
Ridgwell, A. et al. Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling. Biogeosciences 4, 87–104 (2007).
Williamson, M., Lenton, T., Shepherd, J. & Edwards, N. An efficient numerical terrestrial scheme (ENTS) for Earth system modelling. Ecol. Model. 198, 362–374 (2006).
Foley, A. Climate model emulation in an integrated assessment framework: a case study for mitigation policies in the electricity sector. Earth Syst. Dynam. 7, 119–132 (2016).
Eby, M. et al. Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity. Clim. Past 9, 1111–1140 (2013).
Jackson, R. B. et al. Reaching peak emissions. Nat. Clim. Change 6, 7–10 (2016).
Vuuren, D. P. et al. RCP2.6: exploring the possibility to keep global mean temperature increase below 2 °C. Clim. Change 109, 95–116 (2011).
IPCC: Summary for Policymakers. In Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).
Acknowledgements
The authors acknowledge C-EERNG and Cambridge Econometrics for support, and funding from EPSRC (J.-F.M., fellowship no. EP/K007254/1), the Newton Fund (J.-F.M., P.S., J.E.V., H.P., U.C., EPSRC grant no. EP/N002504/1 and ESRC grant no. ES/N013174/1), NERC (N.R.E., P.B.H., H.P., U.C., grant no. NE/P015093/1), CONICYT (P.S.), the Philomathia Foundation (J.E.V.), the Cambridge Humanities Research Grants Scheme (J.E.V.), Horizon 2020 (J.-F.M., F.K., Sim4Nexus project no. 689150) and the European Commission (J.-F.M., H.P., F.K., U.C., DG ENERGY contract no. ENER/A4/2015-436/SER/S12.716128). J.-F.M. acknowledges the support of L. J. Turner during extended critical medical treatment, and H. de Coninck and M. Grubb for discussions. We are grateful to N. Bauer for sharing data from his study.
Author information
Authors and Affiliations
Contributions
J.-F.M. designed and coordinated the research. J.-F.M., J.E.V., N.R.E., H.P. and I.S. wrote the article. J.-F.M., H.P. and U.C. ran simulations. U.C. and H.P. managed E3ME. J.-F.M. and A.L. developed FTT:Transport. J.-F.M. and P.S. developed FTT:Power and the resource depletion model. F.K. and J.-F.M. developed FTT:Heat. P.B.H. and N.R.E. ran GENIE simulations and provided scientific support on climate change. J.E.V. contributed geopolitical expertise.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information
Supplementary notes 1–5, Supplementary tables 1–8, Supplementary figures 1–11, Supplementary references
Supplementary Data 1
Dataset for detailed public policies assumed in model scenarios
Rights and permissions
About this article
Cite this article
Mercure, JF., Pollitt, H., Viñuales, J.E. et al. Macroeconomic impact of stranded fossil fuel assets. Nature Clim Change 8, 588–593 (2018). https://doi.org/10.1038/s41558-018-0182-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41558-018-0182-1