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Dependency of Crop Production between Global Breadbaskets: A Copula Approach for the Assessment of Global and Regional Risk Pools

机译：全球粮仓之间的作物生产依存关系：一种Copula方法评估全球和区域风险池

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摘要

As recent events have shown, simultaneous crop losses in different parts of the world can cause serious risks to global food security. However, to date, little is known about the spatial dependency of lower than expected crop yields from global breadbaskets. This especially applies in the case of extreme events, i.e., where one or more breadbaskets are experiencing far below average yields. Without such information, risk management approaches cannot be applied and vulnerability to extremes may remain high or even increase in the future around the world. We tackle both issues from an empirical perspective focusing on wheat yield. Interdependencies between historically observed wheat yield deviations in five breadbaskets (United States, Argentina, India, China, and Australia) are estimated via copula approaches that can incorporate increasing tail dependencies. In doing so, we are able to attach probabilities to interregional as well as global yield losses. To address the robustness of our results, we apply three different methods for constructing multivariate copulas: vine copulas, ordered coupling using a minimax approach, and hierarchical structuring. We found interdependencies between states within breadbaskets that led us to the conclusion that risk pooling for extremes is less favorable on the regional level. However, notwithstanding evidence of global climatic teleconnections that may influence crop production, we also demonstrate empirically that wheat production losses are independent between global breadbaskets, which strengthens the case for interregional risk pooling strategies. We argue that through interregional risk pooling, postdisaster liabilities of governments and international donors could be decreased.
机译：正如最近发生的事件所表明的那样，世界不同地区同时发生的作物减产可能对全球粮食安全造成严重风险。然而，迄今为止，关于全球粮仓低于预期产量的空间依赖性知之甚少。这在极端事件的情况下尤其适用，例如，一个或多个面包篮的收成大大低于平均水平。没有这些信息，风险管理方法将无法应用，极端情况的脆弱性在未来的世界范围内可能仍然很高，甚至还会增加。我们从以小麦产量为重点的经验角度解决这两个问题。通过copula方法可以估计五个面包篮（美国，阿根廷，印度，中国和澳大利亚）历史上观察到的小麦单产偏差之间的相互依赖性，该方法可以纳入增加的尾部依赖性。这样一来，我们就能将概率归因于区域间以及全球的产量损失。为了解决我们的结果的鲁棒性，我们应用了三种不同的方法来构建多变量copula：藤蔓copula，使用minimax方法的有序耦合以及分层结构。我们发现，各篮子之间的国家之间存在相互依存关系，这使我们得出以下结论：极端风险分担在区域一级不利。但是，尽管有证据表明全球气候遥相关可能影响农作物生产，但我们也凭经验证明，小麦生产损失在全球粮仓之间是独立的，这加强了区域间风险分担策略的依据。我们认为，通过区域间风险分担，可以减少政府和国际捐助者的灾后负债。

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