Mitchell Roznik, Milton Boyd, Lysa Porth and C. Brock Porth
The purpose of this paper is to examine factors affecting the use of forage index insurance. Forage is a difficult crop to insure, and index insurance may be well suited for…
Abstract
Purpose
The purpose of this paper is to examine factors affecting the use of forage index insurance. Forage is a difficult crop to insure, and index insurance may be well suited for forage insurance and has been implemented in several countries, including Canada, the USA and France. Despite being a promising risk management tool, forage index insurance participation rates in Canada, and other countries are low relative to crop insurance participation rates for grain and oilseed producers.
Design/methodology/approach
A survey was conducted with 87 beef and cattle producers from Alberta and Saskatchewan, Canada. A probit regression model was used, and a number of variables were included to examine the use of forage index insurance.
Findings
In total, 6 of 11 variables in the model are found to be statistically significant in explaining forage producers’ use of forage index insurance. Results suggest that producers who maintain lower feed reserves are more likely to purchase forage index insurance. Also, producers with higher levels of knowledge of crop insurance and a more positive attitude toward forage insurance are more likely to use forage index insurance. Furthermore, producers are more likely to use forage index insurance if they perceive drought and weather risk as being of greater importance, and if they are younger. The importance of the variable forage index insurance premium price was statistically insignificant. This could be due to the effect of subsidization, reducing the importance of price for the decision to purchase. Similarly, the use of other subsidized risk management policies, including a whole-farm margin policy (e.g. the government program and AgriStability), did not reduce forage index insurance use. A possible explanation for this is that the subsidization of the policies may make it profitable to purchase both, despite the overlapping coverage.
Practical implications
These results may be useful for policy makers interested in increasing forage index insurance participation rates, as forage index insurance participation rates have historically been low relative to grain and oilseed producers.
Originality/value
This study is believed to be one of the first studies regarding the use of forage index insurance by forage producers. Producers can be exposed to catastrophic risks such as drought or other extreme weather events, and forage index insurance may be an effective means to manage these risks. Index insurance determines payments using an index that is correlated to producers’ actual yields. A downside of this method is basis risk, which is the mismatch between the insured index and the producer’s actual yield. Research has focused on basis risk and developing improved methods to reduce basis risk. However, less research has investigated the other important factors that may contribute to forage index insurance use. Producers may have a different risk management environment regarding forage production compared to other farm activities, and these differences have largely not been examined.
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Yugu Xiao, Ke Wang and Lysa Porth
While crop insurance ratemaking has been studied for many decades, it is still faced with many challenges. Crop insurance premium rates (PRs) are traditionally determined only by…
Abstract
Purpose
While crop insurance ratemaking has been studied for many decades, it is still faced with many challenges. Crop insurance premium rates (PRs) are traditionally determined only by point estimation, and this approach may lead to uncertainty because it is sensitive to the underwriter’s assumptions regarding the trend, yield distribution, and other issues such as data scarcity and credibility. Thus, the purpose of this paper is to obtain the interval estimate for the PR, which can provide additional information about the accuracy of the point estimate.
Design/methodology/approach
A bootstrap method based on the loss cost ratio ratemaking approach is proposed. Using Monte Carlo experiments, the performance of this method is tested against several popular methods. To measure the efficiency of the confidence interval (CI) estimators, the actual coverage probabilities and the average widths of these intervals are calculated.
Findings
The proposed method is shown to be as efficient as the non-parametric kernel method, and has the features of flexibility and robustness, and can provide insight for underwriters regarding uncertainty based on the width of the CI.
Originality/value
Comprehensive comparisons are conducted to show the advantage and the efficiency of the proposed method. In addition, a significant empirical example is given to show how to use the CIs to support ratemaking.
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Wenjun Zhu, Lysa Porth and Ken Seng Tan
The purpose of this paper is to propose an improved reinsurance pricing framework, which includes a crop yield forecasting model that integrates weather variables and crop…
Abstract
Purpose
The purpose of this paper is to propose an improved reinsurance pricing framework, which includes a crop yield forecasting model that integrates weather variables and crop production information from different geographically correlated regions using a new credibility estimator, and closed form reinsurance pricing formulas. A yield restatement approach to account for changing crop mix through time is also demonstrated.
Design/methodology/approach
The new crop yield forecasting model is empirically analyzed based on detailed farm-level data from Manitoba, Canada, covering 216 crop varieties from 19,238 farms from 1996 to 2011. As well, corresponding weather data from 30 stations, including daily temperature and precipitation, are considered. Algorithms that combine screening regression, cross-validation and principal component analysis are evaluated for the purpose of achieving efficient dimension reduction and model selection.
Findings
The results show that the new yield forecasting model provides significant improvements over the classical regression model, both in terms of in-sample and out-of-sample forecasting abilities.
Research limitations/implications
The empirical analysis is limited to data from the province of Manitoba, Canada, and other regions may show different results.
Practical implications
This research is useful from a risk management perspective for insurers and reinsurers, and the framework may also be used to develop improved weather risk management strategies to help manage adverse weather events.
Originality/value
This is the first paper to integrate a credibility estimator for crop yield forecasting, and develop a closed form reinsurance pricing formula.
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Jia Lin, Milton Boyd, Jeffrey Pai, Lysa Porth, Qiao Zhang and Ke Wang
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
In total, 11 of 15 variables in the model are found to be statistically significant in explaining farmers’ willingness to purchase weather index insurance.
Research limitations/implications
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.
Practical implications
Weather index insurance may provide a lower cost alternative than traditional crop insurance, however, basis risk remains a main challenge.
Originality/value
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.
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Lysa Porth, Wenjun Zhu and Ken Seng Tan
The purpose of this paper is to address some of the fundamental issues surrounding crop insurance ratemaking, from the perspective of the reinsurer, through the development of a…
Abstract
Purpose
The purpose of this paper is to address some of the fundamental issues surrounding crop insurance ratemaking, from the perspective of the reinsurer, through the development of a scientific pricing framework.
Design/methodology/approach
The generating process of the historical loss cost ratio's (LCR's) are reviewed, and the Erlang mixture distribution is proposed. A modified credibility approach is developed based on the Erlang mixture distribution and the liability weighted LCR, and information from the observed data of the individual region/province is integrated with the collective experience of the entire crop reinsurance program in Canada.
Findings
A comprehensive data set representing the entire crop insurance sector in Canada is used to show that the Erlang mixture distribution captures the tails of the data more accurately compared to conventional distributions. Further, the heterogeneous credibility premium based on the liability weighted LCR's is more conservative, and provides a more scientific approach to enhance the reinsurance pricing.
Research limitations/implications
Credibility models are in the early stages of application in the area of agriculture insurance, therefore, the credibility models presented in this paper could be verified with data from other geographical regions.
Practical implications
The credibility-based Erlang mixture model proposed in this paper should be useful for crop insurers and reinsurers to enhance their ratemaking frameworks.
Originality/value
This is the first paper to introduce the Erlang mixture model in the context of agricultural risk modeling. Two modified versions of the Bühlmann-Straub credibility model are also presented based on the liability weighted LCR to enhance the reinsurance pricing framework.
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The purpose of this paper is to illustrate the benefits of utilizing teams of personal and financial consultants to work with farm families in New York State on issues affecting…
Abstract
Purpose
The purpose of this paper is to illustrate the benefits of utilizing teams of personal and financial consultants to work with farm families in New York State on issues affecting farm business performance.
Design/methodology/approach
Program experience in implementing an integrated consulting model provides a framework for illustrating how such a model may be utilized on farms and other family businesses for succession planning.
Findings
An integrated personal and financial consulting model is effective in producing lasting business results such as business growth, improved profitability, and reduced interpersonal conflict on farms in New York State.
Originality/value
Farmers employ a multitude of risk management tools, such as crop insurance, to reduce various types of risk affecting their farm businesses in New York State, but an area often overlooked by farmers is managing human resource risk, namely succession risk. As the average age of farmers in the USA continues to increase, employing new tools and strategies is critical when developing an effective business succession plan for farmers.
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The federal crop insurance program has become the cornerstone of US agricultural policy. Since its introduction in the mid-1990s, crop revenue insurance has grown in prominence…
Abstract
Purpose
The federal crop insurance program has become the cornerstone of US agricultural policy. Since its introduction in the mid-1990s, crop revenue insurance has grown in prominence and now represents nearly 90 percent of liability for major crops. The pricing and design of revenue insurance raises a number of important challenges. The 2014 Farm Bill brought about several important changes in the program, resulting in a moving target for analysts and researchers. The paper aims to discuss these issues.
Design/methodology/approach
The risks are of a multivariate nature and are likely to be highly dependent on one another. The crop insurance setting is also constantly changing, with technological changes in production practices and highly volatile commodity prices. Compounding these challenges is the fact that US policymakers continually change the program.
Findings
The program has indeed undergone many changes and a number of important research questions need to be addressed.
Originality/value
Original research based upon recent policy.