The assumptions on the rate of technological progress in energy technologies, land use productivity, labour productivity, etc. are among the major determinants of the typical output of IAM, such as emissions and economic competitiveness. Yet, little is known about how to calibrate technological change, and even less on how this can be endogenized in IAMs. Moreover, uncertainty is pervasive not only in technological change, but at all levels in climate change, from scientific to socio-economic. Models have partially attempted to account for uncertainty by running coordinated multi-model comparison projects, or to run model ensembles using techniques such as Monte Carlo scenarios. However, much work remains to be done before IAMs can fully account for the key uncertainties at play, and quantify their impacts on climate policy design.
ADVANCE addressed two intertwined issues in the field of modelling and evaluation of climate change policies: 1) technological innovation and 2) uncertainty. ADVANCE made progress on both fronts, by proposing new formulations and calibration of technological progress and testing new methods for modelling uncertainty into IAMs.