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Spatial variability in regional scale drought index insurance viability across Australia’s wheat growing regions

机译:澳大利亚小麦种植地区的区域尺度干旱指数保险生存力的空间变异性

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摘要

Wheat is key global food crop that is heavily influenced by climatic variability. There has been extensive research on improving forecasts and management practices to minimise climate related yield losses, but less on how to handle yield losses caused by climate variability. We investigated whether index insurance could be used to manage climate related losses, specifically from winter rainfall drought for wheat crops in Australia. We utilised 31?years of yield data from 15 of Australia’s key wheat producing regions. The winter rainfall index was developed and tested using generalised additive regression models, allowing for non-linear effects. Models with the winter rainfall index explained significant variation in wheat yields in each of the regions assessed. Wheat yield models had cross-validated Rsup2/sup values??0.5 for two-thirds of the 15 regions modelled and best explained wheat yields in the Mallee, Western Australia (cross-validated Rsup2/sup of 0.70). Calculated fair premiums ranged from $8.62 to $77.1?AUD/ha, while maximum liability was $59.25 to $212.12?AUD/ha. Throughout the eastern most wheat growing regions the winter rainfall index was consistently inefficient (i.e. not beneficial). In contrast, the winter rainfall index was financially efficient (i.e. beneficial) in the western wheat regions of eastern Australia and parts of Western Australia, with benefits of up to $97?AUD/ha and loss reductions of $9?AUD/ha. The spatial variability in insurance efficiency was explained by rainfall variance. As rainfall variance increased the efficiency of the winter rainfall index insurance for wheat decreased. Our findings have two important policy implications; (1) in areas where climate change is anticipated to increase rainfall variability risk-transfer options, such as index insurance, may become less viable and as such policies that support the development of index insurance without acknowledging or adjusting for variability in its benefit could lead to inefficient outcomes for both government and agricultural producers; and (2) where index rainfall insurance is not efficient then greater emphasise may need to be placed on developing alternate types of index insurance (e.g. using satellites) and/or on risk-management and climate adaptation strategies that minimise losses.
机译:小麦是全球主要的粮食作物,受气候变化的影响很大。在改进预测和管理方法以最大程度减少与气候相关的产量损失方面进行了广泛的研究,但在如何处理由气候多变性引起的产量损失方面却进行了较少的研究。我们调查了指数保险是否可用于管理与气候相关的损失,特别是澳大利亚小麦作物冬季降雨干旱造成的损失。我们利用了澳大利亚15个主要小麦产区的31年产量数据。冬季降水指数是使用广义加性回归模型开发和测试的,可以考虑非线性影响。带有冬季降雨指数的模型解释了每个评估区域小麦产量的显着变化。小麦产量模型的15个区域中有三分之二的交叉验证的R 2 值≥0.5,在西澳大利亚州的Mallee中,小麦的产量得到了最好的解释(交叉验证的R 2 的0.70)。计算出的公允保费在$ 8.62至$ 77.1?AUD / ha之间,最大责任在$ 59.25至$ 212.12?AUD / ha之间。在整个东部小麦种植区中,冬季降雨指数一直低效(即无益)。相反,在澳大利亚东部的西部小麦地区和西澳大利亚州的部分地区,冬季降雨指数在财务上是有效的(即有益的),其收益高达$ 97?AUD / ha,损失减少了$ 9?AUD / ha。保险效率的空间差异可以通过降雨差异来解释。随着降雨方差的增加,小麦冬季降雨指数保险的效率下降。我们的发现有两个重要的政策含义: (1)在预计气候变化会增加降雨多变性的地区,诸如指数保险之类的风险转移选择可能变得不可行,并且由于支持指数保险发展而未承认或调整其利益多变性的政策可能导致政府和农业生产者的效率低下; (2)在指数降雨保险效率不高的情况下,可能需要更加重视开发替代类型的指数保险(例如,使用卫星)和/或风险管理和气候适应策略,以最大程度地减少损失。

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