Crop Insurance Premium Ratemaking Based on Survey Data: A Case Study from Dingxing County, China

Xingming Zhang; Weixia Yin; Jun Wang; Tao Ye; Jintao Zhao; Jing'ai Wang

doi:10.1007/s13753-015-0059-0

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Article Navigation > International Journal of Disaster Risk Science > 2015 > 6(3): 207-215

Xingming Zhang, Weixia Yin, Jun Wang, Tao Ye, Jintao Zhao, Jing'ai Wang. Crop Insurance Premium Ratemaking Based on Survey Data: A Case Study from Dingxing County, China[J]. International Journal of Disaster Risk Science, 2015, 6(3): 207-215. doi: 10.1007/s13753-015-0059-0

Citation:

Xingming Zhang, Weixia Yin, Jun Wang, Tao Ye, Jintao Zhao, Jing'ai Wang. Crop Insurance Premium Ratemaking Based on Survey Data: A Case Study from Dingxing County, China[J]. International Journal of Disaster Risk Science, 2015, 6(3): 207-215. doi: 10.1007/s13753-015-0059-0

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Crop Insurance Premium Ratemaking Based on Survey Data: A Case Study from Dingxing County, China

doi: 10.1007/s13753-015-0059-0

Xingming Zhang^1,2,3,
Weixia Yin^2,3,
Jun Wang^1,4,5,
Tao Ye^1,4,
Jintao Zhao⁶,
Jing'ai Wang^{1,2,3
,
,}

1 State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China;
2 School of Geography, Beijing Normal University, Beijing 100875, China;
3 Key Laboratory of Regional Geography, Beijing Normal University, Beijing 100875, China;
4 Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China;
5 People's Insurance Company of China, Beijing 100022, China;
6 School of Management, Langfang Teachers College, Langfang 065000, China

Funds:

This study was supported by the State Key Scientific Program of China (973 project): Global Change, Environmental Risk and Its Adaptation Paradigms (No. 2012CB955403). We are grateful to Ming Wang at Beijing Normal University of China for his valuable comments on the manuscript. In particular, our heartfelt thanks should be given to the anonymous reviewers for their helpful comments that greatly helped to improve the quality of this article.

Available Online: 2021-04-26

Abstract

Abstract

Premium ratemaking is an important issue to guarantee insurance balance of payments. Most ratemaking methods require large samples of long-term loss data or farm-level yield data, which are often unavailable in developing countries. This study develops a crop insurance ratemaking method with survey data. The method involves a questionnaire survey on characteristic yield information (average yield, high yield, and low yield) of farming households’ cropland. After compensating for random error, the probability distributions of farm-level yields are simulated with characteristic yields based on the linear additive model. The premium rate is calculated based on Monte Carlo yield simulation results. This method was applied to Dingxing County, North China to arrive at the insurance loss cost ratio and calculate the necessary premium rate. The method proposed in this study could serve as a feasible technique for crop insurance ratemaking in regions that lack sufficient long-term yield data, especially in developing countries with smallholder agriculture.
- Agricultural risk,
- Characteristic agricultural yield,
- Crop insurance,
- North China,
- Premium ratemaking

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References(34)

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