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Empirical study on optimal reinsurance for crop insurance in China from an insurer’s perspective |
ZHOU Xian-hua, WANG Yun-bo, ZHANG Hua-dong, WANG Ke |
1、China Institute for Actuarial Science, Center University of Finance and Economics, Beijing 100081, P.R.China
2、Anhua Insurance Institute, Beijing 100037, P.R.China
3、Agriculture Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China |
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摘要 This study investigates the optimal reinsurance for crop insurance in China in an insurer’s perspective using the data from Inner Mongolia, Jilin, and Liaoning, China. On the basis of the loss ratio distributions modeled by AnHua Crop Risk Evaluation System, we use the empirical model developed by Tan and Weng (2014) to study the optimal reinsurance design for crop insurance in China. We find that, when the primary insurer’s loss function, the principle of the reinsurance premium calculation, and the risk measure are given, the level of risk tolerance of the primary insurer, the safety loading coefficient of the reinsurer, and the constraint on reinsurance premium budget affect the optimal reinsurance design. When a strict constraint on reinsurance premium budget is implemented, which often occurs in reality, the limited stop loss reinsurance is optimal, consistent with the common practice in reality. This study provides suggestions for decision making regarding the crop reinsurance in China. It also provides empirical evidence for the literature on optimal reinsurance from the insurance market of China. This evidence undoubtedly has an important practical significance for the development of China’s crop insurance.
Abstract This study investigates the optimal reinsurance for crop insurance in China in an insurer’s perspective using the data from Inner Mongolia, Jilin, and Liaoning, China. On the basis of the loss ratio distributions modeled by AnHua Crop Risk Evaluation System, we use the empirical model developed by Tan and Weng (2014) to study the optimal reinsurance design for crop insurance in China. We find that, when the primary insurer’s loss function, the principle of the reinsurance premium calculation, and the risk measure are given, the level of risk tolerance of the primary insurer, the safety loading coefficient of the reinsurer, and the constraint on reinsurance premium budget affect the optimal reinsurance design. When a strict constraint on reinsurance premium budget is implemented, which often occurs in reality, the limited stop loss reinsurance is optimal, consistent with the common practice in reality. This study provides suggestions for decision making regarding the crop reinsurance in China. It also provides empirical evidence for the literature on optimal reinsurance from the insurance market of China. This evidence undoubtedly has an important practical significance for the development of China’s crop insurance.
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Received: 31 July 2014
Accepted:
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Fund: This authors thank the supports of the “Young Talents Plan” Project from the Beijing Education Committee, China, the Youth Project of National Natural Science Foundation of China (71102125), and the MOE (Ministry of Education, China) Project of the Key Research Institute of Humanities and Social Sciences at Universities (13JJD790041). |
Corresponding Authors:
WANG Ke, Tel: +86-10-82106259,E-mail: wangke01@caas.cn
E-mail: wangke01@caas.cn
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About author: ZHOU Xian-hua, E-mail: zhouxh@cufe-ins.sinanet.com; |
Cite this article:
ZHOU Xian-hua, WANG Yun-bo, ZHANG Hua-dong, WANG Ke.
2015.
Empirical study on optimal reinsurance for crop insurance in China from an insurer’s perspective. Journal of Integrative Agriculture, 14(10): 2121-2133.
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Alizadeh F, Goldfarb D. 2003. Second-order cone programming.Mathematical Programming, 95, 3-51Beard R E, Pentikainen T, Pesonen E. 1977. Risk Theory. 2nded. Chapman and Hall, London.Ben-Tal A, Nemirovski? A S. 2001. Lectures on modern convexoptimization. In: Analysis, Algorithms, and EngineeringApplications. Siam, Philadelphia.Borch K. 1960. The safety loading of reinsurance premiums.Scandinavian Actuarial Journal, 43, 163-184Borch K. 1969. The optimal reinsurance treaty. ASTIN Bulletin,5, 293-297Bu Y. 2005. On optimal reinsurance arrangement. CasualtyActuarial Society Forum, 2005, 1-20Cai J, Tan K S. 2007. Optimal retention for a stop-lossreinsurance under the VaR and CTE risk measures. ASTINBulletin, 37, 93.Cai J, Tan K S, Weng C, Zhang Y. 2008. Optimal reinsuranceunder VaR and CTE risk measures. Insurance: Mathematicsand Economics, 43, 185-196Froot K A. 2001. The market for catastrophe risk: A clinicalexamination. Journal of Financial Economics, 60, 529-571Froot K, Posner S. 2000. Issues in the Pricing of CatastropheRisk. Trade Notes, Marsh & Mclennan Securities.Fu L, Khury C K. 2010. Optimal layers for catastrophereinsurance. Variance, 4, 191-208Gajek L, Zagrodny D. 2000. Insurer’s optimal reinsurancestrategies. Insurance: Mathematics and Economics, 27,105-112Gajek L, Zagrodny D. 2004. Optimal reinsurance under thegeneral risk measures. Insurance: Mathematics andEconomics, 34, 227-240Gerber H U. 1979. An Introduction to Mathematical Risk Theory.SS Huebner Foundation for Insurance Education, WhartonSchool, University of Pennsylvania, Philadelphia.Grant M, Boyd S, Ye Y. 2013. CVX: Matlab software fordisciplined convex programming. (Web page and software),version 2.0 beta. [2013-12-30]. http://cvxr.com/cvx/download/Guerra M, Centeno M L. 2008. Optimal reinsurance policy:The adjustment coefficient and the expected utility criteria.Insurance: Mathematics and Economics, 42, 529-539Kahn P M. 1961. Some remarks on a recent paper by Borch.ASTIN Bulletin, 1, 265-272Kaluszka M. 2004. Mean-variance optimal reinsurancearrangements. Scandinavian Actuarial Journal, 2004,28-41Lobo M S, Vandenberghe L, Boyd S, Lebret H. 1998.Applications of second-order cone programming. LinearAlgebra and Its Applications, 284, 193-228Ohlin J. 1969. On a class of measures of dispersion withapplication to optimal reinsurance. ASTIN Bulletin, 5,249-266Porth L, Tan K S, Weng C. 2013. Optimal reinsurance analysisfrom a crop insurer’s perspective. Agricultural FinanceReview, 73, 310-328Tan K S, Weng C. 2014. Empirical Approach for optimalreinsurance design. North American Actuarial Journal, 18,315-342Tan K S, Weng C G, Zhang Y. 2009. VaR and CTE criteriafor optimal quota-share and stop-loss reinsurance. NorthAmerican Actuarial Journal, 13, 459-482Venter G G, Gluck S M, Brehm P J. 2001. Measuring value inreinsurance. CAS Forum, 2001,179-199Weng C. 2009. Optimal Reinsurance Designs: From an Insurer’sPerspective. University of Waterloo, Canada.Zhou X H, Fan Q Q, Zhou M, Li Z G. 2012. A comparativestudy of Chinese and american crop insurance products.Insurance Studies, (7), 52-60 (in Chinese) |
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