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.

中文翻译：

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作物产量保险定价的一种引导方法

目的-尽管对作物保险费率制定进行了数十年研究，但仍然面临许多挑战。传统上，农作物保险费率（PRs）仅由点估计来确定，这种方法可能会导致不确定性，因为它对保险人关于趋势，收益分配以及其他问题（例如数据稀缺性和可信度）的假设敏感。因此，本文的目的是获得PR的间隔估计，它可以提供有关点估计准确性的其他信息。设计/方法/方法-提出了一种基于损失成本比率评估方法的自举方法。使用蒙特卡洛实验，针对几种流行的方法测试了该方法的性能。为了衡量置信区间（CI）估算器的效率，计算实际的覆盖率和这些间隔的平均宽度。结果-所提出的方法被证明与非参数核方法一样有效，并且具有灵活性和鲁棒性的特征，并且可以为承销商提供基于CI宽度的不确定性的见解。原创性/价值-进行了全面的比较，以显示所提出方法的优势和效率。此外，给出了一个重要的经验示例，以显示如何使用配置项来支持评估。并可以为承销商提供基于CI宽度不确定性的见解。原创性/价值-进行了全面的比较，以显示所提出方法的优势和效率。此外，给出了一个重要的经验示例，以显示如何使用配置项来支持评估。并可以为承销商提供有关基于配置项宽度的不确定性的见解。原创性/价值-进行了全面的比较，以显示所提出方法的优势和效率。此外，给出了一个重要的经验示例，以显示如何使用配置项来支持评估。