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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. Weninger, Quinn & Just, Richard E., 1999. "Are Crop Yields Normally Distributed?," Staff General Research Papers 5064, Iowa State University, Department of Economics.
  2. Koop, Gary M & Poirier, Dale J & Tobias, Justin, 2007. "Bayesian Econometric Methods," Staff General Research Papers 12722, Iowa State University, Department of Economics.
  3. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
  4. Terrell, Dek, 1996. "Incorporating Monotonicity and Concavity Conditions in Flexible Functional Forms," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(2), pages 179-94, March-Apr.
  5. Yu, Tian & Babcock, Bruce A., 2010. "Are U.S. Corn and Soybeans Becoming More Drought Tolerant?," Staff General Research Papers 32098, Iowa State University, Department of Economics.
  6. David A. Hennessy, 2009. "Crop Yield Skewness Under Law of the Minimum Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 197-208.
  7. Antle, John M, 1983. "Testing the Stochastic Structure of Production: A Flexible Moment-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 192-201, July.
  8. 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.
  9. Phoebe Koundouri & Céline Nauges & Vangelis Tzouvelekas, 2006. "Technology Adoption under Production Uncertainty: Theory and Application to Irrigation Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(3), pages 657-670.
  10. Phoebe Koundouri & Nikolaos Kourogenis, 2011. "On the Distribution of Crop Yields: Does the Central Limit Theorem Apply?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(5), pages 1341-1357.
  11. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
  12. Mitchell, Paul D., 2004. "Nutrient Best Management Practice Insurance and Farmer Perceptions of Adoption Risk," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 36(03), December.
  13. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, 06.
  14. Salvatore Di Falco & Jean-Paul Chavas, 2007. "On Crop Biodiversity, Risk Exposure, and Food Security in the Highlands of Ethiopia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(3), pages 599-611.
  15. Bruce A. Babcock & Joseph A. Herriges, 1994. "Input Demand Under Yield and Revenue Insurance," Center for Agricultural and Rural Development (CARD) Publications 94-wp127, Center for Agricultural and Rural Development (CARD) at Iowa State University.
  16. 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, vol. 37(03), December.
  17. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
  18. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
  19. john M. Antle, 2010. "Asymmetry, Partial Moments, and Production Risk," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(5), pages 1294-1309.
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Cited by:
  1. 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 124748, Agricultural and Applied Economics Association.
  2. 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 142951, Southern Agricultural Economics Association.
  3. Jesse Tack & David Ubilava, 2013. "The effect of El Niño Southern Oscillation on U.S. corn production and downside risk," Climatic Change, Springer, vol. 121(4), pages 689-700, December.
  4. Tolhurst, Tor & Ker, Alan P., 2013. "On Technological Change in Crop Yields," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151269, Agricultural and Applied Economics Association.

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