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  • 标题:Break-even year: a concept for understanding intergenerational trade-offs in climate change mitigation policy
  • 本地全文:下载
  • 作者:Patrick T Brown ; Juan Moreno-Cruz ; Ken Caldeira
  • 期刊名称:Environmental Research Communications
  • 印刷版ISSN:2515-7620
  • 出版年度:2020
  • 卷号:2
  • 期号:9
  • 页码:1-9
  • DOI:10.1088/2515-7620/abb413
  • 出版社:IOP Publishing
  • 摘要:Global climate change mitigation is often framed in public discussions as a tradeoff between environmental protection and harm to the economy. However, climate-economy models have consistently calculated that the immediate implementation of greenhouse gas emissions restriction (via e.g. a global carbon price) would be in humanity's best interest on purely economic grounds. Despite this, the implementation of global climate policy has been notoriously difficult to achieve. This evokes an apparent paradox: if the implementation of a global carbon price is not only beneficial to the environment, but is also 'economically optimal', why has it been so difficult to enact? One potential reason for this difficulty is that economically optimal greenhouse gas emissions restrictions are not economically beneficial for the generation of people that launch them. The purpose of this article is to explore this issue by introducing the concept of the break-even year, which we define as the year when the economically optimal policy begins to produce global mean net economic benefits. We show that in a commonly used climate-economy model (DICE), the break-even year is relatively far into the future—around 2080 for mitigation policy beginning in the early 2020s. Notably, the break-even year is not sensitive to the uncertain magnitudes of the costs of climate change mitigation policy or the costs of economic damages from climate change. This result makes it explicit and understandable why an economically optimal policy can be difficult to implement in practice.
  • 关键词:integrated assessment; climate-economy; damage function; social planner; DICE; mitigation cost; climate damage function
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