Abstract
Integrated assessment models compare the costs of greenhouse gas mitigation with damages from climate change to evaluate the social welfare implications of climate policy proposals and inform optimal emissions reduction trajectories. However, these models have been criticized for lacking a strong empirical basis for their damage functions, which do little to alter assumptions of sustained gross domestic product (GDP) growth, even under extreme temperature scenarios1,2,3. We implement empirical estimates of temperature effects on GDP growth rates in the DICE model through two pathways, total factor productivity growth and capital depreciation4,5. This damage specification, even under optimistic adaptation assumptions, substantially slows GDP growth in poor regions but has more modest effects in rich countries. Optimal climate policy in this model stabilizes global temperature change below 2 °C by eliminating emissions in the near future and implies a social cost of carbon several times larger than previous estimates6. A sensitivity analysis shows that the magnitude of climate change impacts on economic growth, the rate of adaptation, and the dynamic interaction between damages and GDP are three critical uncertainties requiring further research. In particular, optimal mitigation rates are much lower if countries become less sensitive to climate change impacts as they develop, making this a major source of uncertainty and an important subject for future research.
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Change history
28 January 2015
In the version of this Letter originally published, in equation (1) and in the explanatory sentence following the equation, jTFP should have read rTFP. In the second line of the equation, jDJOj,t should have read rDJOj,t. These errors have been corrected in the online versions of the Letter.
References
Pindyck, R. S. Uncertain outcomes and climate change policy. J. Environ. Econ. Manage. 63, 289–303 (2012).
Stern, N. The structure of economic modeling of the potential impacts of climate change: Grafting gross underestimation of risk onto already narrow science models. J. Econ. Lit. 51, 838–859 (2013).
Revesz, R. L. et al. Global warming: Improve economic models of climate change. Nature 508, 173–175 (2014).
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).
Nordhaus, W. D. & Sztorc, P. DICE 2013R: Introduction and User’s Manual 1–102 (2013); http://www.econ.yale.edu/˜nordhaus/homepage/documents/DICE_Manual_103113r2.pdf
IAWG, U. Technical support document: Technical update of the social cost of carbon for regulatory impact analysis under executive order 12866. 1–22 (US government, 2013)
Deschênes, O. & Greenstone, M. Climate change, mortality, and adaptation: Evidence from annual fluctuations in weather in the US. Am. Econ. J. Appl. Econ. 3, 152–185 (2011).
Schlenker, W. & Roberts, D. L. Nonlinear temperature effects indicate severe damages to US corn yields under climate change. Proc. Natl Acad. Sci. 106, 15594–15598 (2009).
Dell, M., Jones, B. F. & Olken, B. A. What do we learn from the weather? The new climate-economy literature. J. Econ. Lit. 52, 740–798 (2014).
Hope, C. W. The marginal impact of CO2 from PAGE2002: An integrated assessment model incorporating the IPCC’s five reasons for concern. Integr. Assess. J. 6, 19–56 (2006).
Anthoff, D. & Tol, R. S. J. The Climate Framework for Uncertainty, Negotiation and Distribution (FUND), Technical Description, Version 3.6. (2012); http://www.fund-model.org/versions
Moyer, E., Woolley, M. M., Matteson, N. J., Glotter, M. M. & Weisbach, D. Drivers of uncertainty in the Social Cost of Carbon. J. Leg. Stud. 43, 401–425 (2014).
Bansal, R. & Ochoa, M. Temperature, Aggregate Risk, and Expected Returns (National Bureau for Economic Research, 2011).
Hsiang, S. M., Burke, M. & Miguel, E. Quantifying the influence of climate on human conflict. Science 341, 1235367 (2013).
Graff Zivin, J. & Neidell, M. Temperature and the allocation of time: Implications for climate change. J. Labor Econ. 32, 1–26 (2014).
Dietz, S. & Stern, N. Endogenous Growth, Convexity of Damages and Climate Risk: How Nordhaus’ Framework Supports Deep Cuts in Carbon Emissions (Center for Climate Change Economics and Policy, 2014).
Nordhaus, W. D. Economic aspects of global warming in a post-Copenhagen environment. Proc. Natl Acad. Sci. USA 107, 11721–11726 (2010).
Moore, F. C. & Lobell, D. B. The adaptation potential of European agriculture in response to climate change. Nature Clim. Change 4, 610–614 (2014).
Hornbeck, R. The enduring impact of the American dust bowl: Short and long-run adjustments to environmental catastrophe. Am. Econ. Rev. 102, 1477–1507 (2012).
Hsiang, S. M. & Narita, D. Adaptation to cyclone risk: Evidence from the global cross-section. Clim. Change Econ. 03 (2012).
Lobell, D. B., Banziger, M., Magorokosho, C. & Vivek, B. Nonlinear heat effects on African maize as evidenced by historical yield trials. Nature Clim. Change 1, 42–45 (2011).
Keller, K., McInerney, D. & Bradford, D. F. Carbon dioxide sequestration: How much and when? Climatic Change 88, 267–291 (2008).
Ha-Duong, M., Grubb, M. & Hourcade, J. Influence of socioeconomic inertia and uncertainty on optimal CO2-emission abatement. Nature 390, 270–273 (1997).
Richels, R. G. & Blanford, G. J. The value of technological advance in decarbonizing the US economy. Energy Econ. 30, 2930–2946 (2008).
Hogan, W. W. & Jorgenson, D. W. Productivity trends and the cost of reducing CO2 emissions. Energy J. 12, 67–85 (1991).
Weitzman, M. L. GHG targets as insurance against catastrophic climate damages. J. Public Econ. Theory 14, 221–244 (2012).
Stern, N. & Taylor, C. Climate change: Risk, ethics, and the Stern review. Science 317, 203–204 (2007).
Stanton, E. A. Negishi welfare weights in integrated assessment models: The mathematics of global inequality. Clim. Change 107, 417–432 (2010).
NASA GISS Surface Temperature Analysis (GISTEMP) (Goddard Institute for Space Studies, 2014); http://data.giss.nasa.gov/gistemp/graphs_v3/Fig.A2.txt
IPCC Summary for Policymakers in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).
Acknowledgements
We would like to thank J. Koomey, C. Reichard and M. Craxton for comments on the manuscript. F.C.M. is supported by the Neukermans Family Foundation Stanford Interdisciplinary Graduate Fellowship.
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F.C.M. and D.B.D. designed the analysis. D.B.D. performed the analysis. F.C.M. and D.B.D. analysed results and wrote the paper.
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Moore, F., Diaz, D. Temperature impacts on economic growth warrant stringent mitigation policy. Nature Clim Change 5, 127–131 (2015). https://doi.org/10.1038/nclimate2481
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DOI: https://doi.org/10.1038/nclimate2481