Fat tails and climate change: the case for a new approach to major infrastructure appraisal

M. Hurst
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Abstract

Abstract Conventional project appraisal techniques such as net present value and P50/90 have a strong assumption of symmetric ‘bell curve’ probability distributions and rely heavily on ‘comparative static’ approaches assuming past trends can be extrapolated into the future. For long term mega infrastructure, or portfolios of, projects, these are probably not acceptable assumptions. The case for abandoning normal distribution approaches is strengthened by the presence of ‘disruptors’ (e.g., COVID-19) and tipping points/non-linearities. Among these, climate change is typified by highly asymmetric probability distributions with great uncertainty about the probability of, for example, higher temperature change and sea level rise. Furthermore, the consequences of the events at the top end of the probability distribution are not only very high but also extremely uncertain in themselves. Recent UK guidance accepts that conventional approaches to project appraisal may be sub-optimal here. Moves to reduce carbon emissions impose an extra uncertainty on many infrastructure projects in terms of technological development and the related pathways to net zero. So, distributions even if symmetric may display ‘fat tails’ with higher-than-Normal probability of extreme outcomes. Probability distributions will also be ‘skewed’: with a much higher than conventionally assumed probability of adverse consequences. But the more extreme, ‘regression to the tail’ concept needs further exploration before it can be used in practice. While there remains a place for NPV approaches, practitioners need to rebalance towards scenario analysis, adaptive pathways/more continuous assurance and non-monetised approaches. More work is also required to identify how and how far it is reasonable to adapt NPVs to skewed probability distributions.
肥尾与气候变化:大型基础设施评估新方法的案例
传统的项目评估技术,如净现值和P50/90,对对称的“钟形曲线”概率分布有很强的假设,并且严重依赖于“比较静态”方法,假设过去的趋势可以外推到未来。对于长期的大型基础设施或项目组合来说,这些假设可能是不可接受的。“颠覆者”(如COVID-19)和临界点/非线性的存在加强了放弃正态分布方法的理由。其中,气候变化具有高度不对称的概率分布特征,例如温度升高和海平面上升的概率具有很大的不确定性。此外,发生在概率分布顶端的事件的后果不仅非常高,而且本身也极不确定。英国最近的指导意见承认,传统的项目评估方法在这里可能不是最优的。减少碳排放的举措给许多基础设施项目带来了额外的不确定性,包括技术发展和实现净零排放的相关途径。因此,即使分布是对称的,也可能显示“肥尾”,极端结果的概率高于正态。概率分布也将“偏斜”:出现不良后果的概率远高于传统假设的概率。但更极端的是,“回归到尾巴”的概念需要进一步的探索才能在实践中使用。虽然NPV方法仍有一席之地,但从业者需要重新平衡情景分析、自适应途径/更持续的保证和非货币化方法。还需要做更多的工作来确定如何以及在多大程度上合理地使npv适应倾斜概率分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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