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.