Technological progress and long-term energy demand — a survey of recent approaches and a Danish case

Abstract

This paper discusses different approaches to incorporating technological progress in energy-economy models and the effect on long-term energy demand projections. Approaches to modelling based on an exogenous annual change of energy efficiency to an endogenous explanation of innovation for energy technologies are covered. Technological progress is an important issue for modelling long-term energy demand and is often characterised as the main contributor to the different energy demand forecasts from different models. New economic theoretical developments in the fields of endogenous growth and industrial organisation have important implications for the attempts to endogenise technological innovation and diffusion of new energy technologies. A range of analytical and empirical models with different descriptions of technological progress is surveyed in the paper. To analyse the importance of the technology description, two models of residential energy demand in Denmark are compared. A Danish macroeconometric model is compared to a technological vintage model that is covering electric appliances and residential heating demand. The energy demand projection of the two models diverges, and the underlying assumptions regarding technological progress must be made comparable in order to demonstrate whether or not these assumptions are the reason. Assumptions about energy efficiency improvement in the vintage models are found to be important for the projection. The vintage modelling approach is found to be less important for long-term projections. A limitation of the vintage modelling approach applied in the long term explains some of the differences in projections among the two types of models. The applied vintage model of electric appliances does not adequately describe the category of new energy-consuming appliances that are expected to become available in the long term. If it is to be used for long-term projections this category must be more carefully modelled.