Insurance serves as a mechanism to effectively manage and transfer revenue-related risks. We conducted a study to explore the potential financial advantages of index insurance, which protects agricultural producers, specifically sugarcane, against excessive rainfall. Creation of the index involved utilizing generalized additive regression models, allowing for consideration of non-linear effects and handling complex data by adjusting the complexity of the model through the addition or reduction of terms. Moreover, quantile generalized additive regression was deliberated to evaluate relationships with lower quantiles, such as low-yield events. To quantify the financial benefits for farmers, should they opt for excessive rainfall index insurance, we employed efficiency analysis based on metrics such as conditional tail expectation (CTE), certainty equivalence of revenue (CER), and mean root square loss (MRSL). The results of the regression model demonstrate its accuracy in predicting sugar cane yields, with a split testing R2 of 0.691. MRSL should be taken into consideration initially, as it is a farmer’s revenue assessment that distinguishes between those with and those without insurance. As a result, the GAM model indicates the least fluctuation in farmer income at the 90th percentile. Additionally, our study suggests that this type of insurance could apply to sugarcane farmers and other crop producers in regions where extreme rainfall threatens the financial sustainability of agricultural production.

中文翻译：

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遭受洪水风险的天气产量指数保险评估：以泰国甘蔗为例

保险是有效管理和转移收入相关风险的机制。我们进行了一项研究，探讨指数保险的潜在财务优势，该保险可以保护农业生产者（特别是甘蔗）免受过度降雨的影响。该指数的创建涉及利用广义加性回归模型，允许考虑非线性效应并通过添加或减少项来调整模型的复杂性来处理复杂数据。此外，还考虑了分位数广义加性回归来评估与较低分位数（例如低产量事件）的关系。为了量化农民是否选择过量降雨指数保险所获得的经济利益，我们采用了基于条件尾部预期 (CTE)、收入确定性等价 (CER) 和均方根损失 (MRSL) 等指标的效率分析。回归模型的结果证明了其预测甘蔗产量的准确性，对比测试 R2 为 0.691。首先应该考虑 MRSL，因为它是农民的收入评估，区分有保险和没有保险的农民。因此，GAM 模型表明，第 90 个百分位数的农民收入波动最小。此外，我们的研究表明，这种类型的保险可以适用于极端降雨威胁农业生产财务可持续性的地区的甘蔗种植者和其他农作物生产者。