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Modeling Dependence in the Design of Whole Farm---A Copula-Based Model Approach

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  • Zhu, Ying
  • Ghosh, Sujit K.
  • Goodwin, Barry K.

Abstract

The objective of this study is to evaluate and model the risks of corn and soybean production. This study focuses on the risk of revenue variability that arises from changes in prices, yields shortfalls or both. There are several models for price and yield risk factors for corn and soybeans. For instance, yield risks can be modeled by a family of Beta distributions, whereas price shocks can be modeled by log-normal distributions. In order to develop a multivariate model that preserves a given set of marginals, a copula approach can be used to characterize the joint yield and price risk of corn and soybeans, which are usually highly correlated. The copula approach has been spurred by the recent developments in the whole farm insurance (WFI), resulting in an increasing need for the modeling of multivariate risk factors and their interaction. As a part of the study, various copula models are investigated for their suitability in modeling yield and price risks. Finally, the proposed copula approach is illustrated with simulated data to calculate the premium rate of the whole farm insurance. Results show that WFI is superior to crop-specific insurance with premia 36% cheaper than the latter.

Suggested Citation

  • Zhu, Ying & Ghosh, Sujit K. & Goodwin, Barry K., 2008. "Modeling Dependence in the Design of Whole Farm---A Copula-Based Model Approach," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6282, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea08:6282
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    File URL: http://purl.umn.edu/6282
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    References listed on IDEAS

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    1. Coble, Keith H. & Heifner, Richard G. & Zuniga, Manuel, 2000. "Implications Of Crop Yield And Revenue Insurance For Producer Hedging," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(02), December.
    2. David A. Hennessy & Bruce A. Babcock & Dermot J. Hayes, 1997. "Budgetary and Producer Welfare Effects of Revenue Insurance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(3), pages 1024-1034.
    3. David A. Hennessy & Bruce A. Babcock & Dermot J. Hayes, 1997. "Budgetary and Producer Welfare Effects of Revenue Insurance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(3), pages 1024-1034.
    4. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
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    Cited by:

    1. Miao, Ruiqing & Hennessy, David A. & Feng, Hongli, 2016. "The Effects of Crop Insurance Subsidies and Sodsaver on Land-Use Change," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(2), May.
    2. Bokusheva, Raushan, 2010. "Measuring the dependence structure between yield and weather variables," MPRA Paper 22786, University Library of Munich, Germany.
    3. 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.
    4. Larsen, Ryan A. & Leatham, David J. & Mjelde, James W. & Wolfley, Jared L., 2008. "Geographical Diversification: An Application of Copula Based CVaR," Proceedings: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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    Keywords

    Copula; Crop Insurance; Loss Distribution; Farm Management;

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