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The purpose of this paper is to examine the reduction of crop yield uncertainty using rainfall index insurances. The insurance payouts are determined by a transparent rainfall index rather than actual crop yield of any producer, thereby circumventing problems of adverse selection and moral hazard. The authors consider insurances on rainfall indexes of various months and derive an optimal insurance portfolio that minimizes the income variance for a crop producer.

Various regression models are considered to relate crop yield to monthly mean temperature and monthly cumulative precipitation. A bootstrapping method is used to simulate weather indexes and corn yield in a future year with the correlation between precipitation and temperature incorporated. Based on the simulated scenarios, the optimal insurance portfolio that minimizes the income variance for a crop producer is obtained. In addition, the impact of correlation between temperature and precipitation, availability of temperature index insurance and geographical basis risk on the effectiveness of rainfall index insurance is examined.

The authors illustrate the approach with the corn yield in Illinois east crop reporting district and weather data of a city in the same district. The analysis shows that corn yield in this district is negatively influenced by excessive precipitation in May and drought in June–August. Rainfall index insurance portfolio can reduce the income variance by up to 51.84 percent. Failing to incorporate the correlation between temperature and precipitation decreases variance reduction by 11.6 percent. The presence of geographical basis risk decreases variance reduction by a striking 24.11 percent. Allowing for the purchase of both rainfall and temperature index insurances increases variance reduction by 13.67 percent.

By including precipitation shortfall into explanatory variables, the extended crop yield model explains more fluctuation in crop yield than existing models. The authors use a bootstrapping method instead of complex parametric models to simulate weather indexes and crop yield for a future year and assess the effectiveness of rainfall index insurance. The optimal insurance portfolio obtained provides insights on the practical development of rainfall insurance for corn producers, from the selection of triggering index to the demand of the insurance.

The purpose of this paper is to explain the factors affecting crop insurance purchases by farmers in Inner Mongolia, China.

A survey of farmers in Inner Mongolia, China, is undertaken. Selected variables are used to explain crop insurance purchases, and a probit regression model is used for the analysis.

Results show that a number of variables explain crop insurance purchases by farmers in Inner Mongolia. Of the eight variables in the model, seven are statistically significant. The eight variables used to explain crop insurance purchases are: knowledge of crop insurance, previous purchases of crop insurance, trust of the crop insurance company, amount of risk taken on by the farmer, importance of low crop insurance premium, government as the main information source for crop insurance, role of head of village, and number of family members working in the city.

A possible limitation of the study is that data includes only one geographic area, Inner Mongolia, China, and so results may not always fully generalize to all regions of China, for all situations.

Crop insurance has been recently expanded in China, and the information from this study should be useful for insurance companies and government policy makers that are attempting to increase the adoption rate of crop insurance in China.

Crop insurance may be a useful approach for stabilizing the agricultural sector, and for increasing agricultural production and food security in China.

This is the first study to quantitatively model the factors affecting crop insurance purchases by farmers in Inner Mongolia, China.

In the USA, private insurance companies serve as an integral part of the delivery and risk sharing of the federal crop insurance program. Governed by the Standard Reinsurance Agreement (SRA), private crop insurance companies must designate an eligible crop insurance contract to the assigned risk, developmental, or commercial funds. While the SRA restricts the private sector delivery system in a number of ways, the assignment of contracts to crop insurance funds, however, is left solely to the discretion of individual crop insurance companies. Thus, as to the companies' profitability viewpoint, the optimal selection of the crop insurance funds is the most important task. Therefore, the purpose of this paper is to provide a decision framework for crop insurance companies to make optimal decisions regarding the purchases of crop reinsurance. This information and framework may also be useful for crop insurance firms in China when considering crop reinsurance decisions.

The paper studied three commonly used parametric loss distributions and presented a general guideline to choose the most profitable fund within the company's risk bearing level.

The paper finds many important features in the commonly used loss distributions, which are useful to maximize the company's underwriting returns.

The paper provides a general decision framework for optimally ceding risks to reinsurance. While this paper focused on agricultural insurance decisions by firms, the concept could be applied to general reinsurance decisions.

The application of weather derivatives in hedging crop yield risk is gaining more interest. However, the further development of weather derivatives – particularly exchange-traded – in the agricultural sector has been impeded by concerns over their hedging performance. The purpose of this paper is to develop a new framework to derive the optimal hedging strategy and evaluate hedging effectiveness.

This framework incorporates a stochastic temperature model, a crop yield model, a risk-neutral pricing method and a profit optimization procedure. Based on a large number of simulated scenarios, the authors study crop yield hedge for a future year. The authors allow the hedger to choose from different types of exchange-traded weather derivatives, and examine the impact of various factors on the optimal hedging strategy.

The analysis shows that hedging objective, pricing method and geographical location of the hedged exposure all play important roles in choosing the best hedging strategy and assessing hedging effectiveness.

This framework is forward-looking, because it focusses on the crop yield hedge for a future year rather than on the historical hedging effectiveness often studied in literature. It utilizes the most up-to-date information related to temperature and crop yield, and hence produces a hedging strategy which is more relevant to the year under consideration.

The purpose of this paper is to explain the factors affecting farmers’ willingness to purchase weather index insurance for crops in China, in the Province of Hainan, and to also provide additional background information on weather index insurance.

A survey of 134 farmers was undertaken in Hainan, China, regarding their willingness to purchase weather index insurance. A probit regression model was used, and a number of variables were included to explain willingness of farmers to purchase weather index insurance.

In total, 11 of 15 variables in the model are found to be statistically significant in explaining farmers’ willingness to purchase weather index insurance.

First, farmers’ interest in weather index insurance may be limited due to basis risk. Second, some farmers may not sufficiently understand weather index insurance and so may not purchase it, and a considerable portion of farmers may also require a subsidy if they are to purchase weather insurance.

Weather index insurance may provide a lower cost alternative than traditional crop insurance, however, basis risk remains a main challenge.

This is the first study to quantitatively study the factors affecting the willingness of farmers to purchase weather index insurance for agriculture in the province of Hainan, China.

The purpose of this research is examine the development of livestock mortality insurance, and associated challenges, in order to provide an improved understanding regarding the operation of livestock mortality insurance.

In a many countries, livestock mortality insurance has been either unavailable or underdeveloped. A descriptive analysis is provided regarding the background and development of livestock mortality insurance, along with an example.

Livestock mortality insurance is considerably more complex than crop insurance, and some of the complexities of livestock mortality insurance include multi‐stage production, consequential losses, occasional large event losses, animal health management, moral hazard, and adverse selection.

This study provides background and development information regarding livestock mortality insurance, and also highlights a number of important differences between livestock mortality insurance and crop insurance.

Examines Spain’s problems in implementing regulatory reform and offers suggestions for addressing them. Hopes to be instructive to other countries embarking on regulatory reform. Concludes that other countries should concentrate on problems on implementation that they are likely to face and should be prepared for.