Catastrophic crop insurance effectiveness: does it make a difference how yield losses are conditioned?
The study evaluates the effectiveness of a catastrophic drought-index insurance developed by applying two alternative methods - the standard regression analysis and the copula approach. Most empirical analyses obtain estimates of the dependence of crop yields on weather by employing linear regression. By doing so, they assume that the sensitivity of yields to weather remains constant over the whole distribution of the weather variable and can be captured by the effect of the weather index on the yield conditional mean. In our study we evaluate, whether the prediction of farm yield losses can be done more accurately by conditioning yields on extreme realisations of a weather index. Therefore, we model the dependence structure between yields and weather by employing the copula approach. Our preliminary results suggests that the use of copulas might be a more adequate way to design and rate weather-based insurance against extreme events.
|Date of creation:||10 Apr 2012|
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- 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.
- Conradt, Sarah & Bokusheva, Raushan & Finger, Robert & Kussaiynov, Talgat, 2012. "Yield trend estimation in the presence of non-constant technological change and weather effects," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122541, European Association of Agricultural Economists.
- Raushan Bokusheva, 2011. "Measuring dependence in joint distributions of yield and weather variables," Agricultural Finance Review, Emerald Group Publishing, vol. 71(1), pages 120-141, May.
- 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.
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