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My research has been divided into 3 separate but closely linked papers that together consider the effectiveness of experience curves and their application within an Integrated Assessment Model (IAM) of climate change to determine optimal abatement strategies under uncertainty. My first article published in Energy Policy presents the results of the inclusion of uncertain learning using a simplified aggregate measure of costs and experience to develop the PAGE2002 model with Endogenous Technical Change (ETC). PAGE2002 is an IAM of climate change developed by Chris Hope from the Judge Business School Cambridge which has been widely used in the recent Stern Report. The results of the various stabilisation scenarios, as well as the results of heuristic “optimisations” carried out using genetic algorithms, showed that the uncertainty associated with climate change abatement plays a vital role in resolving climate change issues. A second paper used the PAGE2002 with ETC model to determine the value of imperfect information on the model’s key uncertain parameters: the value of better information about the learning rate to make costly abatement reductions on the costs side and the value of better information about the climate sensitivity on the damages side. Here we were able to make a first order approximation of the value of reducing uncertainty by about half for the parameters in question. Here it was found that information about abatement costs are of a similar magnitude than that of climate sensitivity and that the value of reducing uncertainty of either of these parameters is in the order of 4 Billion USD (2000) for every year earlier that the information becomes available. Assuming that this reduction in uncertainty would come for free in 50 years time, then efforts to reduce uncertainty over the next 10 years would be about worth 160 Billion USD (2000). This value is for uncertainty reduction alone with the value of the technologies or products produced coming over and above. Hence, information may in fact be one of the low hanging fruits that to a great extent remain unharvested. More recent research considers the effectiveness of experience curves to forecast individual technology costs. Here the relative merits of experience and time as explanatory variables are also compared and an attempt is made to understand the usefulness of the experience curve paradigm in reducing future uncertainties of individual technologies. A more dynamic understanding of the uncertainties of experience curves will become more and more vital as IAMs themselves become more dynamic.
Article Source: http://www.climate-change.net.au
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