Charles Kolstad
Regulating Stock Externalities (greenhouse gases) With Learning
This is a major project, funded by the US Department of Energy, the US
Department of Agriculture and the National Science Foundation. The
problem arises out of climate change and the greenhouse effect.
Greenhouse gases (primarily carbon dioxide) are accumulating with
uncertain but possibly significant effects. To control the problem,
costs must be incurred today although benefits (in terms of less
significant climate change) will not occur for decades or centuries.
Although a considerable amount of uncertainty exists, more information
is being acquired over time. Thus there is a question of timing: when
to control the problem, when to acquire more information. The problem
can be addressed from a theoretical point of view, through simple
models of a stock externality and the model can also be addressed
through more complex simulation models, based on macro models of the
economy with a stock externality and uncertainty appended. An
important issue that arises is in characterizing the learning or
information acquisition process. In the work to date, learning has
either been exogenous or following a Bayesian experimentation model.
Models of endogenous learning are currently being explored. This
research also involves Dr.
David Kelly and several research
assistants, all at UCSB.
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Bren School
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Created 24-Mar-97 by Catherine Dibble (updated 28-Jan-98)
(cath@econ.ucsb.edu)