Regulatory policies under uncertainty, value of information and greenhouse gas emissions

Abstract

Would it be better now to act decisively and globally to cut down greenhouse gas emissions or to wait for a reduction in scientific uncertainties? Using a model of optimal statistical decisions it is shown when it pays to act and learn and when to learn and act. The value of information in reducing uncertainty can be shown to be sensitive to the accuracy and likelihood of scientific research results. Some interesting policy results are obtained for the dynamic intertemporal decision situation when the value of new information is an outcome of stochastic optimization with learning.