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Improving the Effectiveness of Weather-based Insurance: An Application of Copula Approach

Author

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  • Bokusheva, Raushan
Abstract
The study develops the methodology for a copula-based weather index insurance rating. As the copula approach is better suited for modeling tail dependence than the standard linear correlation method, we suppose that copulas are more adequate for pricing a weather index insurance contract against extreme weather events. To capture the dependence structure in the left tail of the joint distribution of a weather variable and the farm yield, we employ the Gumbel survival copula. Our results indicate that, given the choice of an appropriate weather index to signal extreme drought occurrence, a copula-based weather insurance contact might provide higher risk reduction compared to a regression-based indemnification.

Suggested Citation

  • Bokusheva, Raushan, 2014. "Improving the Effectiveness of Weather-based Insurance: An Application of Copula Approach," MPRA Paper 62339, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:62339
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    File URL: https://mpra.ub.uni-muenchen.de/62339/1/MPRA_paper_62339.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    3. H. Holly Wang & Raphael N. Karuaihe & Douglas L. Young & Yuehua Zhang, 2013. "Farmers' demand for weather-based crop insurance contracts: the case of maize in south africa," Agrekon, Taylor & Francis Journals, vol. 52(1), pages 87-110, March.
    4. Bokusheva, Raushan & Breustedt, Gunnar, 2012. "The Effectiveness of Weather-Based Index Insurance and Area-Yield Crop Insurance: How Reliable are ex post Predictions for Yield Risk Reduction?," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 51(2), pages 1-22, May.
    5. Norton, Michael T. & Holthaus, Eric & Madajewicz, Malgosia & Osgood, Daniel E. & Peterson, Nicole & Gebremichael, Mengesha & Mullally, Conner & Teh, TseLing, 2011. "Investigating Demand for Weather Index Insurance: Experimental Evidence from Ethiopia," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 104022, Agricultural and Applied Economics Association.
    6. S. Viswanathan & Adriano Rampini, 2013. "Household risk management," 2013 Meeting Papers 647, Society for Economic Dynamics.
    7. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    8. Shawn Cole & Xavier Gine & Jeremy Tobacman & Petia Topalova & Robert Townsend & James Vickery, 2013. "Barriers to Household Risk Management: Evidence from India," American Economic Journal: Applied Economics, American Economic Association, vol. 5(1), pages 104-135, January.
    9. Mobarak, A. Mushfiq & Rosenzweig, Mark R., 2012. "Selling formal Insurance to the Informally Insured," Center Discussion Papers 121671, Yale University, Economic Growth Center.
    10. Jerry R. Skees & J. Roy Black & Barry J. Barnett, 1997. "Designing and Rating an Area Yield Crop Insurance Contract," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 430-438.
    11. Georg Mainik & Eric Schaanning, 2012. "On dependence consistency of CoVaR and some other systemic risk measures," Papers 1207.3464, arXiv.org, revised Aug 2012.
    12. Barry J. Barnett & Olivier Mahul, 2007. "Weather Index Insurance for Agriculture and Rural Areas in Lower-Income Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(5), pages 1241-1247.
    13. Vedenov, Dmitry V. & Barnett, Barry J., 2004. "Efficiency of Weather Derivatives as Primary Crop Insurance Instruments," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(3), pages 1-17, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    catastrophic insurance; weather index insurance; copula; insurance contract design;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

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