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Crop Yield Skewness Under Law of the Minimum Technology

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  • David A. Hennessy

Abstract

No satisfactory motivation has been forwarded in favor of any crop yield distribution, including the normal. This article explores the foundations of yield distributions for the Law of the Minimum resource constraint technology at the plot level of analysis. With independent, identical, uniform resource availability distributions the yield skew is positive, whereas it is negative whenever the distributions are normal. Simulations show how asymmetries in resource availabilities determine skewness. It is suggested that a negative yield skew occurs whenever production is tightly controlled so that the left tails of some resources availabilities distributions are thin. Irrigation may increase yield skewness. Copyright 2009, Oxford University Press.

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  • 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.
    • Handle: RePEc:oup:ajagec:v:91:y:2009:i:1:p:197-208
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    File URL: http://hdl.handle.net/10.1111/j.1467-8276.2008.01181.x
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    Cited by:

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    2. Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    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. Martinet, Vincent, 2014. "The economics of the Food versus Biodiversity debate," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182800, European Association of Agricultural Economists.
    5. Huang, Pei & McCarl, Bruce A., 2014. "Estimating Decadal Climate Variability Effects on Crop Yields: A Bayesian Hierarchical Approach," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169828, Agricultural and Applied Economics Association.
    6. Yu, Tian, 2011. "Three essays on weather and crop yield," ISU General Staff Papers 201101010800002976, Iowa State University, Department of Economics.
    7. Buchholz, Matthias & Musshoff, Oliver, 2014. "The role of weather derivatives and portfolio effects in agricultural water management," Agricultural Water Management, Elsevier, vol. 146(C), pages 34-44.
    8. 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.
    9. Arora, Gaurav & Agarwal, Sandip K., 2020. "Agricultural input use and index insurance adoption: Concept and evidence," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304508, Agricultural and Applied Economics Association.
    10. Xiaodong Du & Cindy L. Yu & David A. Hennessy & Ruiqing Miao, 2015. "Geography of crop yield skewness," Agricultural Economics, International Association of Agricultural Economists, vol. 46(4), pages 463-473, July.
    11. Paulson, Nicholas D. & Babcock, Bruce A., 2010. "Readdressing the Fertilizer Problem," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 35(3), pages 1-17, December.
    12. Vincent Martinet, 2010. "Soil heterogeneity, agricultural supply and land-use change: an application to biofuels production," Working Papers 2010/05, INRA, Economie Publique.
    13. Vincent Martinet, 2012. "Effect of soil heterogeneity on the welfare economics of biofuel policies," EconomiX Working Papers 2012-13, University of Paris Nanterre, EconomiX.
    14. Danso, G.K. & Jeffrey, S.R. & Dridi, C. & Veeman, T., 2021. "Modeling irrigation technology adoption and crop choices: Gains from water trading with farmer heterogeneity in Southern Alberta, Canada," Agricultural Water Management, Elsevier, vol. 253(C).
    15. Joseph Cooper & A. Nam Tran & Steven Wallander, 2017. "Testing for Specification Bias with a Flexible Fourier Transform Model for Crop Yields," American Journal of Agricultural Economics, John Wiley & Sons, vol. 99(3), pages 800-817, April.
    16. Jesse Tack & Ardian Harri & Keith Coble, 2012. "More than Mean Effects: Modeling the Effect of Climate on the Higher Order Moments of Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(5), pages 1037-1054.
    17. Hennessy, David A., 2009. "Crop Yield Skewness and the Normal Distribution," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(1), pages 1-19, April.
    18. Alan D. Hutson & Albert Vexler, 2018. "A Cautionary Note on Beta Families of Distributions and the Aliases Within," The American Statistician, Taylor & Francis Journals, vol. 72(2), pages 121-129, April.
    19. Christopher N. Boyer & B. Wade Brorsen & Emmanuel Tumusiime, 2015. "Modeling skewness with the linear stochastic plateau model to determine optimal nitrogen rates," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 1-10, January.

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    More about this item

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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