Index based crop insurance product design and ratemaking : the case of modified NAIS in India
Designing and rating insurance products requires both science and judgment. In developing and emerging economies, actuarial procedures must be robust and implementable, as well as offering a sufficient degree of transparency and flexibility so as to allow expert judgment to be incorporated. This paper outlines an approach to designing and rating a portfolio of index insurance products that uses both temporal and spatial aspects of the data to increase the efficiency of statistical estimates. The approach has formed the basis for the design and ratemaking methodology implemented by the Agriculture Insurance Company of India for the modified National Agricultural Insurance Scheme, which was initiated by the Government of India in late 2010.
|Date of creation:||01 Mar 2012|
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- Stephens M. Stohs & Jeffrey T. LaFrance, 2004. "A learning rule for inferring local distributions over space and time," Monash Economics Working Papers archive-29, Monash University, Department of Economics.
- 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.
- World Bank, 2011. "Enhancing Crop Insurance in India," World Bank Other Operational Studies 2748, The World Bank.
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- Clarke, Daniel & Mahul, Olivier, 2011. "Disaster risk financing and contingent credit : a dynamic analysis," Policy Research Working Paper Series 5693, The World Bank.
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