Technological learning in energy–environment–economy modelling: A survey

This paper aims at providing an overview and a critical analysis of the technological learning concept and its incorporation in energy–environment–economy models. A special emphasis is put on surveying and discussing, through the so-called learning curve, both studies estimating learning rates in the energy field and studies incorporating endogenous technological learning in bottom-up and top-down models. The survey of learning rate estimations gives special attention to interpreting and explaining the sources of variability of estimated rates, which is shown to be mainly inherent in R&D expenditures, the problem of omitted variable bias, the endogeneity relationship and the role of spillovers. Large-scale models survey show that, despite some methodological and computational complexity related to the non-linearity and the non-convexity associated with the learning curve incorporation, results of the numerous modelling experiments give several new insights with regard to the analysis of the prospects of specific technological options and their cost decrease potential (bottom-up models), and with regard to the analysis of strategic considerations, especially inherent in the innovation and energy diffusion process, in particular the energy sector's endogenous responses to environment policy instruments (top-down models).