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Uncertainty is ubiquitous in environmental economics. This is inevitable: we study the interactions between socioeconomic systems and biogeochemical systems, and in general neither of these is fully understood. As a consequence, our grasp of their interactions is necessarily rather limited. Climate change is a good example: the scientific community understands some aspects of the behaviour of the climate system well, but others poorly. We are certainly no better off, and often worse off, when it comes to our understanding of economic systems. And we are particularly weak on the interactions between the two.

Biodiversity loss is another important problem for which our lack of knowledge is striking. We are in the midst of a mass extinction comparable to those of prehistory, yet we have little formal understanding of why biodiversity matters to us or of how to model the economic consequences of its loss.

In this paper, the authors’ treatment of uncertainty in environmental applications is motivated by two leading examples: climate change and biodiversity loss. They argue that in these cases uncertainty is sufficiently far-reaching that standard decision-making tools such as expected utility theory may no longer capture important aspects of our uncertainty preferences. Richer models of decision-making, which allow us to express lack of confidence in our information, may be more desirable.

ISSN 2515-5717 (Online) – Grantham Research Institute Working Paper series

ISSN 2515-5709 (Online) – CCCEP Working Paper series

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