Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Response of corn markets to climate volatility under alternative energy futures

Abstract

Recent price spikes1,2 have raised concern that climate change could increase food insecurity by reducing grain yields in the coming decades3,4. However, commodity price volatility is also influenced by other factors5,6, which may either exacerbate or buffer the effects of climate change. Here we show that US corn price volatility exhibits higher sensitivity to near-term climate change than to energy policy influences or agriculture–energy market integration, and that the presence of a biofuels mandate enhances the sensitivity to climate change by more than 50%. The climate change impact is driven primarily by intensification of severe hot conditions in the primary corn-growing region of the United States, which causes US corn price volatility to increase sharply in response to global warming projected to occur over the next three decades. Closer integration of agriculture and energy markets moderates the effects of climate change, unless the biofuels mandate becomes binding, in which case corn price volatility is instead exacerbated. However, in spite of the substantial impact on US corn price volatility, we find relatively small impact on food prices. Our findings highlight the critical importance of interactions between energy policies, energy–agriculture linkages and climate change.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Figure 1: Standard deviation of year-on-year percentage change in US corn prices under alternative climate, policy and economic scenarios.
Figure 2: US corn yield ratios in the historic and future climate.
Figure 3: Nearest distance to equivalent temperature envelope in the future climate.

References

  1. Wright, B. D. The economics of grain price volatility. Appl. Econom. Perspect. Policy 33, 32–58 (2011).

    Article  Google Scholar 

  2. Abbott, P., Hurt, C. & Tyner, W. E. What’s Driving Farm Prices in 2011? (Farm Foundation, 2011).

  3. Schlenker, W. & Roberts, M. J. Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc. Natl Acad. Sci. USA 106, 15594–15598 (2009).

    Article  CAS  Google Scholar 

  4. Battisti, D. S. & Naylor, R. L. Historical warnings of future food insecurity with unprecedented seasonal heat. Science 323, 240–244 (2009).

    Article  CAS  Google Scholar 

  5. Anderson, K. & Nelgen, S. Trade barrier volatility and agricultural price stabilization. World Dev. 40, 36–48 (2011).

    Article  Google Scholar 

  6. Hertel, T. W. & Beckman, J. in The Intended and Unintended Effects of US Agricultural and Biotechnology Policies (eds Zivin, J. G. & Perloff, J.) (NBER and Univ. Chicago Press, 2011).

    Google Scholar 

  7. Diffenbaugh, N. S. & Scherer, M. Observational and model evidence of global emergence of permanent, unprecedented heat in the 20th and 21st centuries. Climatic Change 107, 615–624 (2011).

    Article  Google Scholar 

  8. USDA National Agricultural Statistics Service Quick Statshttp://quickstats.nass.usda.gov/ (2011).

  9. Diffenbaugh, N. S. & Ashfaq, M. Intensification of hot extremes in the United States. Geophys. Res. Lett. 37, L15701 (2010).

    Article  Google Scholar 

  10. Taheripour, F., Hertel, T. W. & Tyner, W. E. Implications of biofuels mandates for the global livestock industry: A computable general equilibrium analysis. Agr. Econom. 42, 325–342 (2011).

    Article  Google Scholar 

  11. Energy Information Agency Annual Energy Outlook 2010 (EIA, US Department of Energy, 2010).

  12. Diffenbaugh, N. S., Ashfaq, M. & Scherer, M. Transient regional climate change: Analysis of the summer climate response in a high-resolution, century-scale ensemble experiment over the continental United States. J. Geophys. Res. 116, D24111 (2011).

    Article  Google Scholar 

  13. Ainsworth, E. A., Leakey, A. D. B., Ort, D. R. & Long, S. P. FACE-ing the facts: Inconsistencies and interdependence among field, chamber and modeling studies of elevated CO2 impacts on crop yield and food supply. New Phytol. 179, 5–9 (2008).

    Article  CAS  Google Scholar 

  14. Leakey, A. D. B. Rising atmospheric carbon dioxide concentration and the future of C4 crops for food and fuel. Proc. R. Soc. B 276, 2333–2343 (2009).

    Article  CAS  Google Scholar 

  15. Gohin, A. & Treguer, D. On the (de)stabilization effects of biofuels: Relative contributions of policy instruments and market forces. J. Agr. Res. Econom. 35, 72–86 (2010).

    Google Scholar 

  16. Ahmed, S. A., Diffenbaugh, N. S., Hertel, T. W. & Martin, W. J. Agriculture and trade opportunities for Tanzania: Past volatility and future climate change. Rev. Dev. Econom. (in the press).

  17. National Research Council Renewable Fuel Standard: Potential Economic and Environmental Effects of US Biofuel Policy (NRC, 2011).

  18. Thompson, W., Meyer, S. & Weshoff, P. The new markets for renewable identification numbers. Appl. Econom. Perspect. Policy 32, 588–603 (2010).

    Article  Google Scholar 

  19. H.R. 3097: Renewable Fuel Standard Flexibility Act (112th Congress: 2011–2012) (United States House of Representatives, 2011).

  20. Thompson, W. & Meyer, S. EPA mandate waivers create new uncertainties in biodiesel markets. Choices 26 (2011).

  21. Pal, J. S. et al. Regional climate modeling for the developing world: The ICTP RegCM3 and RegCNET. Bull. Amer. Meteorol. Soc. 89, 1395–1409 (2007).

    Article  Google Scholar 

  22. Collins, W. D. et al. The Community Climate System Model version 3 (CCSM3). J. Clim. 19, 2122–2143 (2006).

    Article  Google Scholar 

  23. Diffenbaugh, N. S., Pal, J. S., Trapp, R. J. & Giorgi, F. Fine-scale processes regulate the response of extreme events to global climate change. Proc. Natl Acad. Sci. USA 102, 15774–15778 (2005).

    Article  CAS  Google Scholar 

  24. IPCC Special Report on Emissions Scenarios (eds Nakicenovic, N. R. & Swart, R.) (Cambridge Univ. Press, 2000).

  25. Ashfaq, M., Bowling, L. C., Cherkauer, K., Pal, J. S. & Diffenbaugh, N. S. Influence of climate model biases and daily-scale temperature and precipitation events on hydrological impacts assessment: A case study of the United States. J. Geophys. Res. 115, D14116 (2010).

    Article  Google Scholar 

  26. Ashfaq, M., Skinner, C. B. & Diffenbaugh, N. S. Influence of SST biases on future climate change projections. Clim. Dynam. 36, 1303–1319 (2011).

    Article  Google Scholar 

  27. Valenzuela, E., Hertel, T. W., Keeney, R. & Reimer, J. J. Assessing global computable general equilibrium model validity using agricultural price volatility. Am. J. Agr. Econom. 89, 383–397 (2007).

    Article  Google Scholar 

  28. Beckman, J., Hertel, T. & Tyner, W. Validating energy-oriented CGE models. Energ. Econom. 33, 799–806 (2011).

    Article  Google Scholar 

  29. Food and Agricultural Policy Research Institute of the University of Missouri US Biofuels Baseline: The Impact of Extending the $0.45 Ethanol Blenders Credit Report #07-11 (FAPRI, 2011).

Download references

Acknowledgements

We thank W. Schlenker for sharing his data and parameter estimates with us. We are grateful for insightful and constructive comments from participants in the International Agricultural Trade Consortium theme day and the Stanford Environmental Economics Seminar series. We thank NCEP for providing access to the NARR data set, and the PRISM Climate Group for providing access to the PRISM observational data set. We thank the Rosen Center for Advanced Computing (RCAC) at Purdue University and the Center for Computational Earth and Environmental Science (CEES) at Stanford University for access to computing resources. The research reported here was primarily supported by the US DOE, Office of Science, Office of Biological and Environmental Research, Integrated Assessment Research Program, Grant No. DE-SC005171, along with supplementary support from NSF award 0955283 and NIH award 1R01AI090159-01.

Author information

Authors and Affiliations

Authors

Contributions

N.S.D. designed and performed the climate modelling, designed the climate–yield–economic modelling approach, analysed the results and wrote the paper. T.W.H. designed the climate–yield–economic modelling approach, designed the economic modelling, analysed the results and wrote the paper. M.S. designed the climate–yield–economic modelling approach, performed the yield calculations and analysed the results. M.V. designed the climate–yield–economic modelling approach, performed the economic modelling, analysed the results and wrote the paper.

Corresponding author

Correspondence to Noah S. Diffenbaugh.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Diffenbaugh, N., Hertel, T., Scherer, M. et al. Response of corn markets to climate volatility under alternative energy futures. Nature Clim Change 2, 514–518 (2012). https://doi.org/10.1038/nclimate1491

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nclimate1491

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing