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The purpose of this paper is to explain the sources of energy system lock-in. It presents a comparative analysis of the respective contributions of some features of increasing returns to adoption factors, i.e. learning-by-doing, learning-by-searching and returns to scale effects in explaining the technological change dynamics in the energy system. The paper is technically based on a critical analysis of the learning curve approach. Econometric estimation of learning and scale effects inherent to seven energy technologies were performed by the use of several learning curve specifications. These specifications permit to deal with some crucial issues related to the learning curve estimation which are associated with the problem of omitted variable bias, the endogeneity effects and the choice of learning indicators. Results show that dynamic economies from learning effects coupled with static economies from scale effects are responsible for the lock-in phenomena of the energy system. They also show that the magnitude of such effects is correlated with the technology life cycle (maturity). In particular, results point out that, 1) the emerging technologies exhibit low learning rates associated with diseconomies of scale which are argued to be symptomatic of the outset of the deployment of new technologies characterized by diffusion barriers and high level of uncertainty, 2) the evolving technologies present rather high learning rates meaning that they respond quickly to capacity expansion and R&D activities development, 3) conventional mature technologies display low learning rates but increasing returns to scale implying that they are characterized by a limited additional diffusion prospects. [Copyright &y& Elsevier]

This paper investigates the economic efficiency–oil consumption relationship in 42 countries during the period 1986–2006. In a first stage by using DEA window analysis countries' economic efficiencies are obtained. In a second stage an econometric analysis based on robust GMM estimators reveals an inverted ‘U’-shape relationship between oil consumption and economic efficiency. In order to capture heterogeneities among countries' development stages the analysis has been separated into two groups (advanced economies and developing/emerging economies). The results show that advanced economies have much higher turning points compared to emerging and developing economies. It appears that oil consumption increases countries' economic efficiency. In addition the consumption patterns of oil products and its derivatives have changed through years and among countries. The different turning points from the econometric analysis indicate the dependence of oil consumption in advanced economies (higher turning points) is driven mainly by household purchasing activities and their standards of living (transport, housing and water, food, etc.). Finally, it appears that oil consumption is the main driver behind the progress of industrialization and urbanization regardless of the country's development stage. [Copyright &y& Elsevier]