Technical change dynamics: evidence from the emerging renewable energy technologies

Abstract

This paper explores the respective contributions of the effects of learning and returns to scale in the capital costs reduction pattern experienced by renewables. Causality analysis and econometric estimation of learning curves are performed on two emerging renewable energy technologies, namely PV and wind. Learning effects appear as an essential driving force, a result which concurs with the widely acknowledged importance of experience in technical progress inherent to economic growth. The existence of non-constant and flexible returns to scale are further highlighted. Their effect on diffusion dynamics is shown to be potentially considerable, particularly at the outset of innovation deployment. However, returns to scale are suggested to be constant in the long term. Institutional commitment in supporting innovation therefore seems justified, both on the basis of the occurrence of learning effects and diseconomies of scale. These findings appear to be essential to the dynamics of innovation diffusion and market structure.