The Transition to Endogenous Technical Change in Climate-Economy Models: A Technical Overview to the Innovation Modeling Comparison Project
|Author:||David Popp with Jonathan Köhler, Michael Grubb, and Ottmar Edenhofer|
|Publication:||Energy Journal, Special Issue: Endogenous Technological Change and the Economics of Atmospheric Stabilization, 2006, 17-55|
|Link:||Transition to Endogenous Technical Change in Climate-Economy Models: A Technical Overview to the Innovation Modeling Comparison Project|
This paper assesses endogenous technical change (ETC) in climate-economy models, using the models in the Innovation Modeling Comparison Project as a representative cross-section. ETC is now a feature of most leading models. Following the new endogenous growth literature and the application of learning curves to the energy sector, there are two main concepts employed: knowledge capital and learning curves. The common insight is that technical change is driven by the development of knowledge capital and its characteristics of being partly non-rival and partly non-excludable. There are various different implementations of ETC. Recursive CGE models face particular difficulties in incorporating ETC and increasing returns. The main limitations of current models are: the lack of uncertainty analysis, the limited representation of the diffusion of technology and the homogeneous nature of agents in the models, including the lack of representation of institutional structures in the innovation process.