我國林業(yè)巨災(zāi)風(fēng)險的分散路徑研究——基于大數(shù)定理的分析
發(fā)布時間:2018-08-21 14:42
【摘要】:目前,我國并沒有有效分散林業(yè)巨災(zāi)風(fēng)險的路徑,遭遇巨災(zāi),林農(nóng)缺乏基本的保障。林業(yè)巨災(zāi)風(fēng)險具有不同于其他風(fēng)險的獨特性。文章首先基于大數(shù)定理,以林農(nóng)為例,分析如何能夠有效地降低風(fēng)險。在此基礎(chǔ)上,探討如何有效分散我國林業(yè)巨災(zāi)風(fēng)險,提出林業(yè)巨災(zāi)保險、再保險、巨災(zāi)證券、天氣指數(shù)保險4種途徑,并分析是否能有效分散林業(yè)巨災(zāi)風(fēng)險。最后提出相應(yīng)的對策建議。
[Abstract]:At present, there is no effective way to disperse forest catastrophe risk in our country. Forestry catastrophe risk is different from other risks. Based on the large number theorem, this paper analyzes how to reduce the risk effectively by taking forest farmers as an example. On this basis, this paper discusses how to effectively disperse the forest catastrophe risk in China, puts forward four ways of forestry catastrophe insurance, reinsurance, catastrophe securities and weather index insurance, and analyzes whether the forest catastrophe risk can be effectively dispersed. Finally, the corresponding countermeasures and suggestions are put forward.
【作者單位】: 湖北工程學(xué)院經(jīng)濟與管理學(xué)院;武漢市科技金融創(chuàng)新促進(jìn)中心;
【基金】:教育部人文社會科學(xué)青年基金“農(nóng)業(yè)天氣風(fēng)險管理的金融創(chuàng)新路徑研究——基于湖北省78個縣市的實證分析”(編號:16YJC630002)
【分類號】:F326.2;F842.6
,
本文編號:2196065
[Abstract]:At present, there is no effective way to disperse forest catastrophe risk in our country. Forestry catastrophe risk is different from other risks. Based on the large number theorem, this paper analyzes how to reduce the risk effectively by taking forest farmers as an example. On this basis, this paper discusses how to effectively disperse the forest catastrophe risk in China, puts forward four ways of forestry catastrophe insurance, reinsurance, catastrophe securities and weather index insurance, and analyzes whether the forest catastrophe risk can be effectively dispersed. Finally, the corresponding countermeasures and suggestions are put forward.
【作者單位】: 湖北工程學(xué)院經(jīng)濟與管理學(xué)院;武漢市科技金融創(chuàng)新促進(jìn)中心;
【基金】:教育部人文社會科學(xué)青年基金“農(nóng)業(yè)天氣風(fēng)險管理的金融創(chuàng)新路徑研究——基于湖北省78個縣市的實證分析”(編號:16YJC630002)
【分類號】:F326.2;F842.6
,
本文編號:2196065
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