It is not immediately clear how to discount distant-future events, like climate change, when the distant-future discount rate itself is uncertain. The so-called “Weitzman-Gollier puzzle” is the fact that two seemingly symmetric and equally plausible ways
of dealing with uncertain future discount rates appear to give diametrically opposed results with the opposite policy implications. We explain how the “Weitzman-Gollier puzzle” is resolved. When agents optimize their consumption plans and probabilities
are adjusted for risk, the two approaches are identical. What we would wish a reader to take away from this paper is the bottom-line message that the appropriate long run discount rate declines over time toward its lowest possible value.
This paper in applied theory argues that there is a loose chain of reasoning connecting the following three basic links in the economics of climate change: 1) additive disutility damages may be appropriate for analyzing some impacts of global warming; 2) an uncertain feedback-forcing coefficient, which might be near one with infinitesimal probability, can cause the distribution of the future time trajectory of global temperatures to have fat tails and a high variance; 3) when high-variance additive damages are discounted at an uncertain rate of pure time preference, which might be near zero with infinitesimal probability, it can make expected present discounted disutility very large. Some possible implications for welfare analysis and climate-change policy are briefly noted.
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.
Climate change is characterized by deep structural uncertainty in the science coupled with an economic inability to evaluate meaningfully the welfare losses from high temperature changes. The probability of a disastrous collapse of planetary welfare
from too much CO2 is non-negligible, even if this low probability is not objectively knowable. This paper attempts to explain (in not excessively technical language) some of the most basic issues in modeling the economics of catastrophic climate change.
The paper builds to a tentative conclusion that, no matter what else is done realistically to slow CO2 buildups, economic analysis lends some support to undertaking serious research now into the prospects of "fast geoengineering preparedness" - as a state-contingent emergency option offering at least the possibility of knocking down
catastrophic temperatures rapidly.