英文标题：
《When does a disaster become a systemic event? Estimating indirect
  economic losses from natural disasters》
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作者：
Sebastian Poledna, Stefan Hochrainer-Stigler, Michael Gregor Miess,
  Peter Klimek, Stefan Schmelzer, Johannes Sorger, Elena Shchekinova, Elena
  Rovenskaya, JoAnne Linnerooth-Bayer, Ulf Dieckmann and Stefan Thurner
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最新提交年份：
2018
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英文摘要：
  Reliable estimates of indirect economic losses arising from natural disasters are currently out of scientific reach. To address this problem, we propose a novel approach that combines a probabilistic physical damage catastrophe model with a new generation of macroeconomic agent-based models (ABMs). The ABM moves beyond the state of the art by exploiting large data sets from detailed national accounts, census data, and business information, etc., to simulate interactions of millions of agents representing \\emph{each} natural person or legal entity in a national economy. The catastrophe model introduces a copula approach to assess flood losses, considering spatial dependencies of the flood hazard. These loss estimates are used in a damage scenario generator that provides input for the ABM, which then estimates indirect economic losses due to the event. For the first time, we are able to link environmental and economic processes in a computer simulation at this level of detail. We show that moderate disasters induce comparably small but positive short- to medium-term, and negative long-term economic impacts. Large-scale events, however, trigger a pronounced negative economic response immediately after the event and in the long term, while exhibiting a temporary short- to medium-term economic boost. We identify winners and losers in different economic sectors, including the fiscal consequences for the government. We quantify the critical disaster size beyond which the resilience of an economy to rebuild reaches its limits. Our results might be relevant for the management of the consequences of systemic events due to climate change and other disasters.
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中文摘要：
目前，科学无法对自然灾害造成的间接经济损失作出可靠的估计。为了解决这个问题，我们提出了一种新的方法，将概率物理损伤突变模型与新一代基于宏观经济主体的模型（ABMs）相结合。ABM超越了最先进的技术，利用详细的国民账户、人口普查数据和商业信息等的大型数据集，模拟国民经济中代表每个自然人或法人实体的数百万代理人之间的互动。突变模型引入了copula方法来评估洪水损失，考虑到洪水灾害的空间相关性。这些损失估算用于损害情景生成器，该生成器为ABM提供输入，然后由ABM估算事件造成的间接经济损失。我们第一次能够在计算机模拟中以这种详细程度将环境和经济过程联系起来。我们表明，中等程度的灾害会产生相对较小但积极的中短期和消极的长期经济影响。然而，大规模事件在事件发生后立即和长期引发了明显的负面经济反应，同时表现出暂时的中短期经济提振。我们确定不同经济部门的赢家和输家，包括政府的财政后果。我们量化了临界灾害规模，超过该规模，经济重建的恢复力将达到极限。我们的结果可能与管理气候变化和其他灾害引起的系统性事件的后果有关。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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