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Some economics of 'dangerous' climate change: reflections on the Stern review

By Simon Dietz, Chris Hope and Nicola Ranger


The Stern Review on the Economics of Climate Change concluded that there can be “no doubt” the economic risks of business-as-usual (BAU) climate change are “very severe” [Stern, 2006. The Economics of Climate Change. HM Treasury, London, p. 188]. The total cost of climate change was estimated to be equivalent to a one-off, permanent 5–20% loss in global mean per-capita consumption today. And the marginal damage cost of a tonne of carbon emitted today was estimated to be around $312 [p. 344]. Both of these estimates are higher than most reported in the previous literature. Subsequently, a number of critiques have appeared, arguing that discounting is the principal explanation for this discrepancy. Discounting is important, but in this paper we emphasise that how one approaches the economics of risk and uncertainty, and how one attempts to model the very closely related issue of low-probability/high-damage scenarios (which we connect to the recent discussion of ‘dangerous’ climate change), can matter just as much. We demonstrate these arguments empirically, using the same models applied in the Stern Review. Together, the issues of risk and uncertainty on the one hand, and ‘dangerous’ climate change on the other, raise very strongly questions about the limits of a welfare-economic approach, where the loss of natural capital might be irreversible and impossible to compensate. Thus we also critically reflect on the state-of-the-art in integrated assessment modelling. There will always be an imperative to carry out integrated assessment modelling, bringing together scientific ‘fact’ and value judgement systematically. But we agree with those cautioning against a literal interpretation of current estimates. Ironically, the Stern Review is one of those voices. A fixation with cost-benefit analysis misses the point that arguments for stabilisation should, and are, built on broader foundations

Topics: GE Environmental Sciences
Publisher: Elsevier
Year: 2007
DOI identifier: 10.1016/j.gloenvcha.2007.05.008
OAI identifier: oai:eprints.lse.ac.uk:4845
Provided by: LSE Research Online

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