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Application of Copulas to Estimation of Joint Crop Yield Distributions

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  • Vedenov, Dmitry V.

Abstract

This paper presents a copula-based methodology for modeling joint yield distributions. Copulas have been used extensively in financial literature, but have not been widely used in agricultural economics and particularly risk management. The copula approach provides a powerful and flexible method to model multivariate distributions and thus go beyond joint normality, regressibility, and mean-variance criterion. Accurate estimation of joint distributions may help to improve the results in the area of risk management and insurance obtained under more limiting assumptions.

Suggested Citation

  • Vedenov, Dmitry V., 2008. "Application of Copulas to Estimation of Joint Crop Yield Distributions," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6264, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea08:6264
    DOI: 10.22004/ag.econ.6264
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    10. Bruce J. Sherrick & Fabio C. Zanini & Gary D. Schnitkey & Scott H. Irwin, 2004. "Crop Insurance Valuation under Alternative Yield Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 406-419.
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    Cited by:

    1. Wei Xu & Guenther Filler & Martin Odening & Ostap Okhrin, 2010. "On the systemic nature of weather risk," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 70(2), pages 267-284, August.
    2. Ostap Okhrin & Martin Odening & Wei Xu, 2013. "Systemic Weather Risk and Crop Insurance: The Case of China," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(2), pages 351-372, June.
    3. Liu, X. & Xu, W. & Odening, M., 2011. "Lassen sich Ertragsrisiken in der Landwirtschaft global diversifizieren?," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 46, March.
    4. Raushan Bokusheva, 2011. "Measuring dependence in joint distributions of yield and weather variables," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 71(1), pages 120-141, May.
    5. Ying-Erh Chen & Barry K Goodwin, 2015. "Policy Design of Multi-Year Crop Insurance Contracts with Partial Payments," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-15, December.
    6. Wienand Kölle & Andrea Martínez Salgueiro & Matthias Buchholz & Oliver Musshoff, 2021. "Can satellite‐based weather index insurance improve the hedging of yield risk of perennial non‐irrigated olive trees in Spain?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(1), pages 66-93, January.
    7. Xiaodong Du & David A. Hennessy, 2012. "The planting real option in cash rent valuation," Applied Economics, Taylor & Francis Journals, vol. 44(6), pages 765-776, February.
    8. Bokusheva, Raushan, 2010. "Measuring the dependence structure between yield and weather variables," MPRA Paper 22786, University Library of Munich, Germany.
    9. Songjiao Chen & William W. Wilson & Ryan Larsen & Bruce Dahl, 2015. "Investing in Agriculture as an Asset Class," Agribusiness, John Wiley & Sons, Ltd., vol. 31(3), pages 353-371, June.
    10. repec:hum:wpaper:sfb649dp2009-002 is not listed on IDEAS
    11. Mubenga-Tshitaka, Jean-Luc & Muteba Mwamba, John W. & Dikgang, Johane & Gelo, Dambala, 2021. "Risk spillover between climate variables and the agricultural commodity market in East Africa," EconStor Preprints 243160, ZBW - Leibniz Information Centre for Economics.
    12. Larsen, Ryan A. & Vedenov, Dmitry V. & Leatham, David J., 2009. "Enterprise-level risk assessment of geographically diversified commercial farms: a copula approach," 2009 Annual Meeting, January 31-February 3, 2009, Atlanta, Georgia 46763, Southern Agricultural Economics Association.
    13. Feng, Xiaoguang & Hayes, Dermot, 2014. "Is Government Involvement Really Necessary: Implications for Systemic Risk and Crop Reinsurance Contracts," 2014 AAEA: Crop Insurance and the 2014 Farm Bill Symposium: Implementing Change in U.S. Agricultural Policy, October 8-9, 2014, Louisville, KY 184241, Agricultural and Applied Economics Association.
    14. Wagner, Stephan M. & Bode, Christoph & Koziol, Philipp, 2009. "Supplier default dependencies: Empirical evidence from the automotive industry," European Journal of Operational Research, Elsevier, vol. 199(1), pages 150-161, November.
    15. Zhang, Yifei & Goodwin, Barry K., 2020. "Implications of U.S. Crop Insurance -- A Perspective from Copulas," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304343, Agricultural and Applied Economics Association.
    16. Franziska Gaupp & Georg Pflug & Stefan Hochrainer‐Stigler & Jim Hall & Simon Dadson, 2017. "Dependency of Crop Production between Global Breadbaskets: A Copula Approach for the Assessment of Global and Regional Risk Pools," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2212-2228, November.
    17. Songjiao Chen & William Wilson & Ryan Larsen & Bruce Dahl, 2016. "Risk Management for Grain Processors and “Copulas”," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(2), pages 365-382, June.
    18. Liu, Xiaoliang & Xu, Wei & Odening, Martin, 2011. "Can crop yield risk be globally diversified?," SFB 649 Discussion Papers 2011-018, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Larsen, Ryan A. & Leatham, David J. & Mjelde, James W. & Wolfley, Jared L., 2008. "Geographical Diversification: An Application of Copula Based CVaR," 2008 Agricultural and Rural Finance Markets in Transition, September 25-26, 2008, Kansas City, Missouri 119533, Regional Research Committee NC-1014: Agricultural and Rural Finance Markets in Transition.

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