Scholarlink

<p>We study optimal adaptation to extreme climate events in a setup where events are dynamically uncertain and the decision maker does not know the true probabilities of events. We analyze different policy decision rules minimizing expected welfare losses for sites with different expected damages from the catastrophic event. We show under which conditions it is optimal to wait before implementing prevention measures in order to obtain more information about the underlying probabilistic process. This waiting time crucially depends on the information set of the planner and the implemented learning procedure. We study different learning procedures of the planner, ranging from simple perfect learning to two-layers Bayesian updating in the form of Dirichlet mixture processes. This latter, to the best of our knowledge, is a novel tool in the climate adaptation economics literature.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Adaptation to Catastrophic Events with Two Layers of Uncertainty: Central Planner Perspective

  • 期刊论文

  • 发表日期：

    2025年9月5日

查看全文
  • Anton Bondarev,
  • Frank C. Krysiak

摘要

We study optimal adaptation to extreme climate events in a setup where events are dynamically uncertain and the decision maker does not know the true probabilities of events. We analyze different policy decision rules minimizing expected welfare losses for sites with different expected damages from the catastrophic event. We show under which conditions it is optimal to wait before implementing prevention measures in order to obtain more information about the underlying probabilistic process. This waiting time crucially depends on the information set of the planner and the implemented learning procedure. We study different learning procedures of the planner, ranging from simple perfect learning to two-layers Bayesian updating in the form of Dirichlet mixture processes. This latter, to the best of our knowledge, is a novel tool in the climate adaptation economics literature.