This paper presents a novel logarithmic mean Divisia index (LMDI) decomposition framework that is tailor-made for unit cost indicators. It adds four new models to the existing LMDI model family. The main novelty of the new framework lies in the separation of quantity and price effects captured in unit cost indicators, while retaining the same desirable properties of traditional models. Four case studies apply the novel LMDI framework to the total real unit energy costs (total RUEC) indicator. Total RUEC represents the sum of direct energy costs (for energy products) and indirect energy costs (energy costs embedded in intermediate inputs and passed on along global value chains) as a fraction of value added. This yardstick allows for monitoring shifts in the burden of energy costs on industries. The first three case studies, based on the World Input-Output Database, cover the period between 1995 and 2009. For an up-to-date analysis, a fourth case study collects additional data for 2009-2016 from energy and economic statistics' institutions. Globally, up until 2009, rising costs for crude petroleum/natural gas and the rise of China in the global economy were the largest drivers of total RUEC. In general, increases of indirect energy costs were more substantial than were those of direct energy costs. The total RUEC of Chinese car manufacturers increased much more strongly than did that of American car manufacturers. After 2009 (until 2016), prices for crude petroleum/natural gas and value added generation were major decelerating factors of global direct RUEC, while increases in energy consumption had offsetting effects. This paper provides a suitable tool to scientists who want to build on unit cost indicators in their research in general and to all policy-oriented institutions concerned with monitoring and analysing the energy transition in particular.
Logarithmic mean Divisia index Structural decomposition analysis Total real unit energy costs Monitoring energy transition Environmental-economic accounting Multi-regional input-output analysis