Impact of disaggregated ICT capital on electricity intensity in European manufacturing

Abstract

In this article we empirically analyse the impact of disaggregated ICT capital on the electricity intensity in five major European manufacturing industries (chemical, food, metal, pulp and paper, textile). The analysis of each industrial sector is based on an unbalanced panel including data for eight EU member countries (Denmark, Finland, Germany, Italy, Portugal, Slovenia, Sweden and the UK) for the period 1991 to 2005. The panel-econometric approach, in which we account for country-specific fixed effects, is based on a factor demand model similar to the one derived in Collard et al. (2005) for the French service sector. On the one hand, our analysis provides some evidence for an electricity-saving effect on production, induced by communication technologies in all sectors considered. On the other hand, the effect of computers and software on the electricity intensity of industrial production is not that clear-cut, but it does seem to be strongly dependent on the sector-specific production processes involved. Overall, the net effect of ICT diffusion on electricity intensity of production appears to be in favour of an enhancement of electricity efficiency in production.

Acknowledgements

The authors acknowledge EU funding received from DG Enterprise and Industry within the Sectoral e-Business Watch project (http://www.ebusiness-watch.org).

Notes

¹Of course, this assumption is dependent on the choice of countries in the one case, and the choice of sectors in the other case. Our panel mainly consists of older member states of the European Union (except for Slovenia, which only joined the EU in May 2004).

²The time series for Finland, Portugal and Slovenia begin in 1995, whereas the earliest available complete data set for Sweden is only from 1996 onwards. Moreover, data for the Danish metal industry only start in 1993.

³Note that the metal industry is an aggregation of the ‘Iron and Steel’, ‘Non-Ferrous Metals’ and ‘Machinery’ industries (cf. Table 1). Moreover, due to differing aggregational groupings in the two data sets, it was impossible to construct a perfect data match for the metal sector. More specifically, and in contrast to the electricity consumption variable, the variables from the EU-KLEMS database also cover the ‘Medical, Precision and Optical Instruments’ sector (NACE code 33).

⁴The numbers in parentheses after the sector names are the corresponding NACE codes (Rev. 1); see Table 1.