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Geography of Crop Yield Skewness

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  • Du, Xiaodong
  • Hennessy, David A.
  • Yu, Cindy L.
  • Miao, Ruiqing

Abstract

This study seeks to provide a rigorous theoretical and empirical understanding of the effects of exogenous geographic and climate-related factors on the first three moments of crop yields. We hypothesize that exogenous geographic and climate factors that have beneficial effects on crop production, such as better soils, less overheating damage, more growing season precipitation and irrigation should make crop yield distributions less positively or more negatively skewed. We employ a large crop insurance dataset for corn, soybean, and wheat to find general support for the hypothesis. The novel empirical method optimally uses correlations between the first three moments and thus significantly improves estimation performance over existing methods.

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Bibliographic Info

Paper provided by Agricultural and Applied Economics Association in its series 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington with number 124748.

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Date of creation: 2012
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Handle: RePEc:ags:aaea12:124748

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Keywords: cross-moment correlation; generalized method of moments; von Liebig production technology; Crop Production/Industries; Environmental Economics and Policy; Production Economics; Research and Development/Tech Change/Emerging Technologies; Q10; Q18; Q50.;

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  1. Wolfram Schlenker & W. Michael Hanemann & Anthony C. Fisher, 2005. "Will U.S. Agriculture Really Benefit from Global Warming? Accounting for Irrigation in the Hedonic Approach," American Economic Review, American Economic Association, vol. 95(1), pages 395-406, March.
  2. Phoebe Koundouri & CĂ©line 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.
  3. 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.
  4. Du, Xiaodong & Hennessy, David A. & Yu, Cindy, 2012. "Testing Day's Conjecture That More Nitrogen Decreases Crop Yield Skewness," Staff General Research Papers 35022, Iowa State University, Department of Economics.
  5. Bruce A. McCarl & Xavier Villavicencio & Ximing Wu, 2008. "Climate Change and Future Analysis: Is Stationarity Dying?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(5), pages 1241-1247.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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. Buchholz, Matthias & Musshoff, Oliver, 2014. "The role of weather derivatives and portfolio effects in agricultural water management," 2014 Conference (58th), February 4-7, 2014, Port Maquarie, Australia 165812, Australian Agricultural and Resource Economics Society.

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