We present an uncertainty analysis conducted using CETA-R, a model in
which the costs of climate change are specified as Risks of large loss
es. In this analysis, we assume that three key parameters may each tak
e on ''high'' or ''low'' values, leading to eight possible states of t
he world. We then explore optimal policies when the state of the world
is known, and under uncertainty. Also, we estimate the benefits of re
solving uncertainty earlier. We find that the optimal policy under unc
ertainty is similar to the policy that is optimal when each of the key
parameters is at its low value. We also find that the value of immedi
ate uncertainty resolution rises sharply as the alternative to immedia
te resolution is increasingly delayed resolution.