Interim study report - Executive Summary (January 2008)
(The final study report will be available by the end of September 2008.)
The role of ICT and e-business in shaping energy needs and energy consumer behaviour has increased tremendously. ICT and e-business can help to reduce energy consumption and thus costs by reorganising production processes, but it can also lead to additional demand for energy due to new products and services provided and the energy consumption of the ICT capital stock itself. Hence, the overall impact of ICT on energy consumption is ambiguous, and depends on the relative magnitude of two countervailing forces: (1) an income effect, caused by the economic boost accruing from increased ICT use (increase in energy consumption) and (2) a substitution effect, caused by changes in the industrial structure and the capital stock towards higher productivity (decrease in energy consumption). Furthermore, there might also be some substitution of ICT and energy for labour and other input factors, so that it seems useful to look at the elasticities of substitution.
Empirically, a certain decoupling of GDP and energy use can be observed. In the U.S., for instance, GDP and energy consumption grew on average by 3.2% and 2.4% annually in the “pre-Internet era” (1992-1996) and by 4% and 1% in the “Internet era” (1996-2000). Of course this observed overall decrease in energy intensity, measured as the ratio between energy consumption and production, may not be the case in every single sector of the economy. Moreover, the IC sectors seem to be less energy intensive than the overall economy (U.S. figures for 1996: 4.4% vs. 0.8%).
In contrast to energy intensity, the intensity of electricity use is rising in many countries. It is thus interesting to study this potential causality between the diffusion of IC capital goods and the observed decrease in energy intensity of production. Methodologically, however, the evaluation of the causality is more complicated, due to the manifold consequences of ICT diffusion on the structures of the economy and society. Romm (2000) suggests to distinguish two types of energy gains related to the diffusion of ICT capital: (1) efficiency gains, for instance due to improved management of an assembly line, and (2) structural gains, for instance due to lowered individual transport needs because of increased Internet shopping. While appealing at first sight, these two kinds of gains, and especially structural gains, are very difficult to quantify.
This report surveys some of the relevant literature on ICT and energy consumption, and provides a description of the research objectives, the methodologies and data used, and some preliminary findings. Specifically, it contains a summary of three case studies conducted and some results from the econometric analysis conducted so far.
Econometric studies focusing on the links (and causality) between the diffusion of ICT capital and energy consumption (or energy intensity of production, respectively) are still scarce, and complement (typically case-based) expert analysis and microeconomic studies. An example for this kind of research, which forms one of the starting points for our own analysis, is Collard et al. (2005). For the French service sector (applied to six different subsectors) these authors employ a simple factor demand model for studying the relation between ICT (computers and software, communication devices) and electricity consumption. Using cross-sectional time series data, and controlling for technical progress, prices, and heated areas, they find that electricity intensity of production increases with the diffusion of computers and software, while it decreases with the diffusion of communications equipment. These results are shown to be robust when corrected for potential endogeneity of the diffusion of ICT.
It is of great policy relevance to better understand whether and under what particular circumstances the promotion of ICT and e-business can actually help to reduce energy consumption. In the literature, the majority of the research undertaken so far is based on case studies and qualitative analysis and has focused on the residential sector (e.g. PCs) and service sectors (e.g. data centres), rather than on the industrial sectors, as it is done in the sectoral econometric studies presented in this report. Due to the heterogeneity of industrial structures and ICT diffusion patterns across different industries, such an analysis is likely most useful at the sectoral level. Moreover, it seems useful to also look on the role of other input factors of production, such as material input, service input, and non-ICT capital stock.
