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Insurance premiums and GM traits

  • Nolan, Elizabeth
  • Santos, Paulo
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    An argument in favor of the development of genetically modified (GM) hybrids is that their presence is considered to be risk decreasing., and hence, insurance premiums for US corn growers who plant approved hybrids have been reduced. In this study we investigate, using a large set of experimental data, whether the presence in a corn hybrid of various combinations of GM traits is likely to affect production variability and downside risk. We estimate a heteroskedastic production function that allows for the variance of yield to change with the level of inputs, and use the residuals of the mean function to estimate the marginal effect of each input on variance and skewness of yield. The results show that the presence of most combinations of GM traits leads to an increase in both yield variability and downside risk.

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    File URL: http://purl.umn.edu/125942
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    Paper provided by International Association of Agricultural Economists in its series 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil with number 125942.

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    Date of creation: 2012
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    Handle: RePEc:ags:iaae12:125942
    Contact details of provider: Web page: http://www.iaae-agecon.org/
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    1. Babcock, Bruce A. & Hart, Chad E. & Hayes, Dermot J., 2004. "Actuarial Fairness of Crop Insurance Rates with Constant Rate Relativities," Staff General Research Papers 11283, Iowa State University, Department of Economics.
    2. Barry K. Goodwin & Monte L. Vandeveer & John L. Deal, 2004. "An Empirical Analysis of Acreage Effects of Participation in the Federal Crop Insurance Program," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1058-1077.
    3. Jeffrey LaFrance & Rulon Pope & Jesse Tack, 2011. "Risk Response in Agriculture," NBER Working Papers 16716, National Bureau of Economic Research, Inc.
      • Jeffrey LaFrance & Rulon Pope & Jesse Tack, 2011. "Risk Response in Agriculture," NBER Chapters, in: The Intended and Unintended Effects of U.S. Agricultural and Biotechnology Policies, pages 143-186 National Bureau of Economic Research, Inc.
    4. Jock R. Anderson & William E. Griffiths, 1981. "Production Risk And Input Use: Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 25(2), pages 149-159, 08.
    5. Bhavani Shankar & Richard Bennett & Stephen Morse, 2008. "Production risk, pesticide use and GM crop technology in South Africa," Applied Economics, Taylor & Francis Journals, vol. 40(19), pages 2489-2500.
    6. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-98, November.
    7. Kim, Kwansoo & Chavas, Jean-Paul, 2001. "Technological Change And Risk Management: An Application To The Economics Of Corn Production," 2001 Annual meeting, August 5-8, Chicago, IL 20605, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Quiggin, John, 1992. "Some observations on insurance, bankruptcy and input demand," Journal of Economic Behavior & Organization, Elsevier, vol. 18(1), pages 101-110, June.
    9. Babcock, Bruce A. & Chalfant, James A. & Collender, Robert N., 1987. "Simultaneous Input Demands And Land Allocation In Agricultural Production Under Certainty," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 12(02), 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, vol. 1(3), pages 192-201, July.
    11. Ardian Harri & Cumhur Erdem & Keith H. Coble & Thomas O. Knight, 2009. "Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(1), pages 163-182.
    12. Wan, Guang H & Griffiths, William E & Anderson, Jock R, 1992. "Using Panel Data to Estimate Risk Effects in Seemingly Unrelated Production Functions," Empirical Economics, Springer, vol. 17(1), pages 35-49.
    13. Brennan, John P., 1984. "Measuring the Contribution of New Varieties to Increasing Wheat Yields," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 52(03), December.
    14. 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.
    15. Pannell, David J., 1991. "Pests and pesticides, risk and risk aversion," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 5(4), August.
    16. Vincent H. Smith & Barry K. Goodwin, 1996. "Crop Insurance, Moral Hazard, and Agricultural Chemical Use," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 428-438.
    17. Joseph W. Glauber, 2004. "Crop Insurance Reconsidered," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(5), pages 1179-1195.
    18. Deepthi Elizabeth Kolady & William Lesser, 2009. "But are they Meritorious? Genetic Productivity Gains under Plant Intellectual Property Rights," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(1), pages 62-79.
    19. Terrance M. Hurley & Paul D. Mitchell & Marlin E. Rice, 2004. "Risk and the Value of Bt Corn," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 345-358.
    20. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-65, May.
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