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Testing Day's Conjecture That More Nitrogen Decreases Crop Yield Skewness

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  • Du, Xiaodong
  • Hennessy, David A.
  • Yu, Cindy

Abstract

While controversy surrounds skewness attributes of typical yield distributions, a better understanding is important for agricultural policy assessment and for crop-insurance rate setting. Day (1965) conjectured that crop yield skewness declines with an increase in nitrogen use at low levels but not at higher levels. Employing four corn yield experimental plot datasets, we investigate the conjecture by introducing (a) a flexible Bayesian extension of the Just–Pope technology to incorporate skewness and (b) a quantile-based measure of skewness shift. Bayesian estimation provides strong evidence in favor of negative skewness at commercial nitrogen rates and for Day’s conjecture. There was weaker evidence in favor of positively skewed cotton yield and little evidence in favor of the conjecture. The results are confirmed by the quantile-based measure. We also find evidence that skewness becomes more negative upon moving from corn-after-corn to corn-after-soybean.

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Bibliographic Info

Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 35022.

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Date of creation: 29 Mar 2012
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Publication status: Published in American Journal of Agricultural Economics, January 2012, vol. 94 no. 1, pp. 225-237
Handle: RePEc:isu:genres:35022

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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
Phone: +1 515.294.6741
Fax: +1 515.294.0221
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Web page: http://www.econ.iastate.edu
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Keywords: crop insurance; Gibbs sampler; Just and Pope technology; negative skewness; quantile regression; rotation effect;

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  1. john M. Antle, 2010. "Asymmetry, Partial Moments, and Production Risk," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 92(5), pages 1294-1309.
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  9. Seo, Sangtaek & Mitchell, Paul D. & Leatham, David J., 2005. "Effects of Federal Risk Management Programs on Optimal Acreage Allocation and Nitrogen Use in a Texas Cotton-Sorghum System," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, Southern Agricultural Economics Association, vol. 37(03), December.
  10. Antle, John M, 1983. "Testing the Stochastic Structure of Production: A Flexible Moment-based Approach," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 1(3), pages 192-201, July.
  11. Weninger, Quinn & Just, Richard E., 1999. "Are Crop Yields Normally Distributed?," Staff General Research Papers, Iowa State University, Department of Economics 5064, Iowa State University, Department of Economics.
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  13. Phoebe Koundouri & Nikolaos Kourogenis, . "On the Distribution of Crop Yields: Does the Central Limit Theorem Apply?," DEOS Working Papers 1007, Athens University of Economics and Business.
  14. David A. Hennessy, 2009. "Crop Yield Skewness Under Law of the Minimum Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 91(1), pages 197-208.
  15. David A. Hennessy, 2004. "On Monoculture and the Structure of Crop Rotations," Center for Agricultural and Rural Development (CARD) Publications 04-wp369, Center for Agricultural and Rural Development (CARD) at Iowa State University.
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Cited by:
  1. Jesse Tack & David Ubilava, 2013. "The effect of El Niño Southern Oscillation on U.S. corn production and downside risk," Climatic Change, Springer, Springer, vol. 121(4), pages 689-700, December.
  2. Du, Xiaodong & Hennessy, David A. & Yu, Cindy L. & Miao, Ruiqing, 2012. "Geography of Crop Yield Skewness," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington, Agricultural and Applied Economics Association 124748, Agricultural and Applied Economics Association.
  3. Tolhurst, Tor & Ker, Alan P., 2013. "On Technological Change in Crop Yields," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C., Agricultural and Applied Economics Association 151269, Agricultural and Applied Economics Association.
  4. Brorsen, B. Wade, 2013. "Using Bayesian Estimation and Decision Theory to Determine the Optimal Level of Nitrogen in Cotton," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida, Southern Agricultural Economics Association 142951, Southern Agricultural Economics Association.

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