Poverty Traps and Disaster Insurance in a Bi-Level Decision Framework

Raimund M. Kovacevic, W. Semmler
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引用次数: 7

Abstract

In this paper, we study mechanisms of poverty traps that can occur after large disaster shocks. Our starting point is a stylized deterministic dynamic model with locally increasing returns to scale possibly generating multiple equilibria paths with finite upper equilibrium. The deterministic dynamics is then overlayed by random dynamics where catastrophic events happen at random points of time. The number of events follows a Poisson process, whereas the proportional capital losses (given a catastrophic event) are beta distributed. In a setup with fixed insurance premium per unit of insured capital, a fraction of the capital might be insured, and this fraction may change after each event. We seek for an optimal strategy with respect to the insured fraction. Falling below the instable equilibrium of the deterministic dynamics introduces the possibility of ending up in a poverty trap after the disaster shocks. We show that the trapping probability (over an infinite time horizon) is equal to one when the stable upper equilibrium of the deterministic dynamics is finite. This is true regardless of the chosen amount of insured capital. Optimization then is done with the expected discounted capital after the next catastrophic event as the objective. Our model may also be useful to assess risk premia and creditworthiness of borrowers when a sequence of shocks at uncertain times and of uncertain size occurs.
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双层决策框架下的贫困陷阱与灾害保险
在本文中,我们研究了大型灾害冲击后可能出现的贫困陷阱的机制。我们的出发点是一个程式化的确定性动态模型,该模型局部收益随比例递增,可能产生具有有限上限均衡的多个均衡路径。然后,确定性动力学被随机动力学覆盖,其中灾难性事件在随机时间点发生。事件的数量遵循泊松过程,而资本损失的比例(给定灾难性事件)是贝塔分布的。在单位保险资本的固定保险费的设置中,一部分资本可能被保险,而这一部分在每次事件后可能会发生变化。我们寻求关于保险部分的最优策略。如果低于确定性动态的不稳定平衡,就有可能在灾害冲击之后陷入贫困陷阱。我们证明了当确定性动力学的稳定上平衡是有限时,捕获概率(在无限时间范围内)等于1。无论选择多少保险资本,这都是正确的。然后以下一次灾难性事件后的预期贴现资本为目标进行优化。当在不确定的时间和规模发生一系列冲击时,我们的模型也可能对评估借款人的风险溢价和信誉有用。
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