期刊
WILEY INTERDISCIPLINARY REVIEWS-CLIMATE CHANGE
卷 11, 期 3, 页码 -出版社
WILEY
DOI: 10.1002/wcc.638
关键词
bioinformatics; docking; lead optimization; machine learning; virtual screening
Even though real options analysis (ROA) is often thought as the best tool available for evaluating flexible strategies, there are profound problems with the assumptions underpinning ROA rendering it unsuitable for use in supporting planning and decision-making on climate adaptation. In the face of dynamic and deep uncertainty about the future, flexible strategies which can be adapted in response to how the uncertainty is resolving are attractive. Traditional cost-benefit analysis cannot account for the value created through optionality. ROA sets out to amend this. There are however several profound problems with how ROA tries to do this. It is typically not clear what is the baseline plan, without options, against which value is to be estimated. Different baselines significantly change option value. Even if option value can unequivocally be established for a given scenario, ROA relies on expected values over a set of scenarios. First, this requires assigning weights, or probabilities, to scenarios. Given the long-time horizon involved in climate adaptation, these probabilities are meaningless. Second, the expected value over a set of scenarios need not obtain in any single scenario and is thus not a meaningful summary of option value. This article is categorized under: Climate Economics > Iterative Risk-Management Policy Portfolios
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