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Estimating the impact of climate change on crop yields: The importance of non-linear temperature effects

  • Wolfram Schlenker

    ()

    (Columbia University - Department of Economics)

  • Michael J. Roberts

    ()

    (U.S. Department of Agriculture (USDA) - Economic Research Service (ERS))

There has been an active debate whether global warming will result in a net gain or net loss for United States agriculture. With mounting evidence that climate is warming, we show that such warming will have substantial impacts on agricultural yields by the end of the century: yields of three major crops in the United States are predicted to decrease by 60 to 79% under the most rapid warming scenario. We use a 55-year panel of crop yields in the United States and pair it with a unique fine-scale weather data set that incorporates the whole distribution of temperatures between the minimum and maximum within each day and across all days in the growing season. The key contribution of our study is in identifying a highly non-linear and asymmetric relationship between temperature and yields. Yields increase in temperature until about 29° C for corn and soybeans and 33° C for cotton, but temperatures above these thresholds quickly become very harmful, and the slope of the decline above the optimum is signifcantly steeper than the incline below it. Previous studies average temperatures over a season, month, or day and thereby dilute this highly non-linear relationship. We use encompassing tests to compare our model with others in the literature and find its out-of-sample forecasts are significantly better. The stability of the estimated relationship across regions, crops, and time suggests it may be transferable to other crops and countries.

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File URL: http://www.econ.columbia.edu/RePEc/pdf/DP0607-01.pdf
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Paper provided by Columbia University, Department of Economics in its series Discussion Papers with number 0607-01.

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Length: 52 pages
Date of creation: 2006
Date of revision:
Handle: RePEc:clu:wpaper:0607-01
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  1. Mendelsohn, Robert & Nordhaus, William D & Shaw, Daigee, 1994. "The Impact of Global Warming on Agriculture: A Ricardian Analysis," American Economic Review, American Economic Association, vol. 84(4), pages 753-71, September.
  2. Sean D. Campbell & Francis X. Diebold, 2002. "Weather Forecasting for Weather Derivatives," Center for Financial Institutions Working Papers 02-42, Wharton School Center for Financial Institutions, University of Pennsylvania.
  3. Michael Greenstone & Olivier Deschenes, 2006. "The Economic Impacts of Climate Change: Evidence from Agricultural Profits and Random Fluctuations in Weather," Working Papers 2006.6, Fondazione Eni Enrico Mattei.
  4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  5. Christopher Timmins, 2006. "Endogenous Land use and the Ricardian Valuation of Climate Change," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 33(1), pages 119-142, 01.
  6. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
  7. Beach, Robert H. & Thomson, Allison M. & McCarl, Bruce A., 2010. "Climate Change Impacts On Us Agriculture," Proceedings Issues, 2010: Climate Change in World Agriculture: Mitigation, Adaptation, Trade and Food Security, June 2010, Stuttgart- Hohenheim, Germany 91393, International Agricultural Trade Research Consortium.
  8. Olivier Desch�nes & Michael Greenstone, 2007. "The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather," American Economic Review, American Economic Association, vol. 97(1), pages 354-385, March.
  9. Kelly, David L. & Kolstad, Charles D. & Mitchell, Glenn T., 2005. "Adjustment costs from environmental change," Journal of Environmental Economics and Management, Elsevier, vol. 50(3), pages 468-495, November.
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