Estimating the impact of climate change on crop yields: The importance of non-linear temperature effects
AbstractThere 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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Bibliographic InfoPaper provided by Columbia University, Department of Economics in its series Discussion Papers with number 0607-01.
Length: 52 pages
Date of creation: 2006
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- Wolfram Schlenker & Michael J. Roberts, 2008. "Estimating the Impact of Climate Change on Crop Yields: The Importance of Nonlinear Temperature Effects," NBER Working Papers 13799, National Bureau of Economic Research, Inc.
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters
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