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Dynamic multilevel modelling of industrial energy demand in Europe

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journal contribution
posted on 02.07.2018, 13:26 authored by Akinsehinwa Sharimakin, Anthony Glass, David SaalDavid Saal, Karligash GlassKarligash Glass
Previous studies of industry level energy demand have not accounted for the hierarchical nesting of industries within a system that also adequately allows for country specific determinants of energy demand. The principal contribution of this paper is therefore to analyse energy demand for European industries over the period 1995–2009 using a dynamic multilevel model that accounts for this hierarchical data structure. Among other things, we find, firstly, that our dynamic multilevel model suggests that if industry income and the industry energy price increase by 10%, long run energy demand will increase by 8.1% and fall by 6.8%, respectively. Secondly, we find that the corresponding long run income and price elasticities are substantially larger in a standard dynamic model of industry level energy demand which does not account for the hierarchical data structure. Our results therefore suggest that not accounting for the hierarchical data structure results in unreliable estimates of energy demand elasticities. From a policy perspective we argue that it is imperative that future industry level energy demand studies account for the hierarchical structure of the data. This is to prevent energy policy making being based on industry level evidence that substantially inflates the responsiveness of long run energy demand to income and price changes.

History

School

  • Business and Economics

Department

  • Economics

Published in

Energy Economics

Volume

74

Pages

120 - 130

Citation

SHARIMAKIN, A. ...et al., 2018. Dynamic multilevel modelling of industrial energy demand in Europe. Energy Economics, 74, pp. 120-130.

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Publisher statement

This paper was accepted for publication in the journal Energy Economics and the definitive published version is available at https://doi.org/10.1016/j.eneco.2018.06.001

Acceptance date

01/06/2018

Publication date

2018-06-04

Copyright date

2018

ISSN

0140-9883

Language

en