G2TT
来源类型Monograph (IIASA Interim Report)
规范类型报告
Endogenous Risks and Learning in Climate Change Decision Analysis.
O'Neill BC; Ermoliev Y; Ermolieva T
发表日期2005
出版者IIASA, Laxenburg, Austria: IR-05-037
出版年2005
语种英语
摘要We analyze the effects of risks and learning on climate change decisions. A two-stage, dynamic, climate change stabilization problem is formulated. The explicit incorporation of ex-post learning induces risk aversion among ex-ante decisions, which is characterized in linear models by VaR- and CVaR-type risk measures. Combined with explicit introduction of "safety" constraints, it creates a "hit-or-miss" type decision-making situation and shows that, even in linear models, learning may lead to either less-or more restrictive ex-ante emission reductions. We analyze stylized elements of the model in order to identify the key factors driving outcomes, in particular, the critical role of quantiles of probability distributions characterizing key uncertainties.
主题Modeling Land-Use and Land-Cover Changes (LUC) ; Population and Climate Change (PCC)
URLhttp://pure.iiasa.ac.at/id/eprint/7799/
来源智库International Institute for Applied Systems Analysis (Austria)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/125431
推荐引用方式
GB/T 7714
O'Neill BC,Ermoliev Y,Ermolieva T. Endogenous Risks and Learning in Climate Change Decision Analysis.. 2005.
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