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Is Organic Vegetable Production Paid for Increased Risk? A Quick Scan

机译:有机蔬菜生产是否有增加风险?快速扫描

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According to common perceptions, questions arise whether risks really increase when farming organically and, if risk indeed increases, whether it is paid for. As basic data are mostly missing, answering these questions needs best managerial estimates and a transparent analysis framework. A Monte Carlo simulation model, using a theoretical "volatility-return" benchmark from financial markets, is constructed as a quick scan for estimating extra risk and the linked risk premium for some vegetable crops. Despite data scarcity and uncertainty, return on capital employed (ROCE) and its variation can be robustly compared between organic and non-organic farming through decomposing ROCE by yield, price and cost components and performing sensitivity analysis. Robustness is mainly achieved when expressing the risk premium on a per-ha basis. The quick scan is used for finding factors that highly influence the risk premium. For early potatoes, the risk is paid for by a sufficient income under the considered conditions, in which the organic price premium is crucial. Other crops like cauliflower need a slightly higher yield or price to turn the forgone risk premium in a sufficient one. Transparency and easiness to apply makes the quick scan a useful instrument to produce risk-related information from scarce data, to support decision making at farm level and to indicate factors important for further support and development of the organic sector.
机译:根据常见的看法,问题出现了风险是否在有机地养殖时真正增加,如果风险确实增加,是否被支付。由于基本数据大多少次丢失,回答这些问题需要最好的管理估计和透明分析框架。蒙特卡罗仿真模型,使用金融市场的理论“波动率回报”基准,作为快速扫描,以估算一些蔬菜作物的额外风险和链接风险溢价。尽管数据稀缺和不确定性,但在有机和非有机农业通过产量,价格和成本分配和进行敏感性分析,可以在有机和非有机养殖之间进行资本回报(ROCE)及其变化。在按公顷的基础上表达风险溢价时主要实现稳健性。快速扫描用于查找高度影响风险溢价的因素。对于早期土豆,风险是在考虑条件下获得足够收入的风险,其中有机价格溢价至关重要。其他作物如花椰菜需要略高的产量或价格,以便以足够的风险溢价转动。透明度和易用的易用性使得快速扫描一个有用的仪器,以产生来自稀缺数据的风险相关信息,以支持在农业水平的决策中,并表示有机部门进一步支持和发展的因素。

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