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@article{weitzman_modeling_2009,
	title = {On {Modeling} and {Interpreting} the {Economics} of {Catastrophic} {Climate} {Change}},
	volume = {91},
	issn = {0034-6535, 1530-9142},
	url = {http://www.mitpressjournals.org/doi/10.1162/rest.91.1.1},
	doi = {10.1162/rest.91.1.1},
	abstract = {With climate change as prototype example, this paper analyzes the implications of structural uncertainty for the economics of low-probability, high-impact catastrophes. Even when updated by Bayesian learning, uncertain structural parameters induce a critical “tail fattening” of posterior-predictive distributions. Such fattened tails have strong implications for situations, like climate change, where a catastrophe is theoretically possible because prior knowledge cannot place sufficiently narrow bounds on overall damages. This paper shows that the economic consequences of fat-tailed structural uncertainty (along with unsureness about high-temperature damages) can readily outweigh the effects of discounting in climate-change policy analysis.},
	language = {en},
	number = {1},
	urldate = {2017-05-15},
	journal = {Review of Economics and Statistics},
	author = {Weitzman, Martin L},
	month = feb,
	year = {2009},
	keywords = {GA, Untagged},
	pages = {1--19},
}