Knowing what we don't know (and won't learn): Environmental Regulation under ''Conscious Unawareness'' and ''Negative learning''

减缓气候变化措施的最佳规模和时机在很大程度上取决于我们对未来气候结果的了解和不了解，以及我们期望通过科学进步提高认识的速度。虽然存在很大的不确定性通常是为了采取及时和实质性行动，但通过快速学习减少不确定性的前景支持相反的呼吁，即推迟昂贵和不可撤销的缓解措施，直到达到更好的知识状态。使这个和类似的环境辩论复杂化的是社会通常面临的不确定性的本质。不仅不可能精确地确定控制系统行为的概率分布，决策者甚至常常不知道与结果相关的突发事件，比如尚未发现的气候反馈过程。这些“未知的未知”，使事情进一步恶化，也往往使新的信息无效甚至误导，即所谓的“消极学习”。环境经济学已经开发了一个丰富的工具包，为环境监管的规范分析提供信息。虽然环境经济学多次采用决策理论和贝叶斯推理的见解来证实不确定性和学习下的决策，但目前环境经济学仍然无法以健全和证实的方式解决未知未知数和负学习的存在。这个理论环境经济学的研究项目将为缩小这一差距迈出第一步，从而为现有文献增加了一个重要的维度。它的主要贡献和挑战是用决策理论的最新成就来补充环境管制的研究。决策理论的“无意识”文献已经开发出能够捕捉决策者不知道相关偶然事件的设置的框架。重要的是，这一文献的一个分支已经明确了决策者在多大程度上可以意识到她自己有限的理解。这种“有意识的无意识”是对环境问题监管中典型的社会信息水平的一个特别恰当的描述，因此有望成为环境经济学中现有模型的一个有价值的延伸。第一个工作包将开发一个易于处理的框架，使抽象的决策理论见解能够为更广泛的受众所接受。基于这一方法学贡献，进一步的工作包将为关于预防原则的一般文献、关于气候行动最佳时机的辩论以及消极学习条件增加新的角度。将这些见解结合起来，最终的工作包将提供一个综合气候评估框架，以确定在有意识的无意识和消极学习下的最佳气候决策。

Optimal scale and timing of climate change mitigation measures crucially depend on what we do and do not know about future climate outcomes as well as the rate at which we expect to improve our understanding via scientific progress. While the presence of large uncertainties is typically invoked for timely and substantive action, the prospect of diminishing uncertainty through quick learning supports opposite calls for postponing costly and irrevocable mitigation measures until a better state of knowledge has been reached. What complicates this and similar environmental debates is the nature of uncertainty society is typically confronted with. Not only is it impossible to pinpoint exact probability distributions governing the system's behavior, decision-makers are often even unaware of outcome-relevant contingencies like yet undiscovered climate feedback processes. These ''unknown unknowns'', aggravating things further, also tend to make new information unproductive or even misleading, so-called ''negative learning''. Environmental Economics has developed a rich tool-kit for informing the normative analysis of environmental regulation. While it has repeatedly adopted insights from decision-theory and Bayesian inference to substantiate decision-making under uncertainty and learning, what Environmental Economics currently still cannot address in a sound and substantiated way is the presence of unknown unknowns and negative learning. This research project in theoretical Environmental Economics will make the first step in closing this gap, thus adding an important dimension to the existing literature. Its main contribution and challenge is to complement studies on environmental regulation with recent achievements in decision-theory. The decision-theoretic ''unawareness'' literature has developed frameworks capable of capturing set-ups in which a decision-maker is unaware of relevant contingencies. Importantly, one strand of this literature has specified to what extent a decision-maker can be aware of her own limited understanding. This ''conscious unawareness'' is a particularly apt description of the typical societal level of information in the regulation of environmental problems and thus promises to be a valuable extension of existing models in Environmental Economics. The first work package will develop a tractable framework that makes the abstract decision-theoretical insights accessible to a wider audience. Based on this methodological contribution, further work packages will add novel angles to the general literature on the Precautionary Principle, the debate about the optimal timing of climate actions, and the conditions for negative learning. Bringing these insights together, the final work package will deliver an integrated climate assessment framework for determining optimal climate decision-making under conscious unawareness and negative learning.