The income elasticity of household energy demand: a quantile regression analysis
J. Harold,
J. Cullinan and
Sean Lyons
Applied Economics, 2017, vol. 49, issue 54, 5570-5578
Abstract:
This article examines variation in the income elasticity of household energy demand across the energy expenditure distribution using expenditure data from the five most recent Household Budget Surveys (HBSs) in Ireland: the 1987, 1994/1995, 1999/2000, 2004/2005 and 2009/2010 HBS. The analysis uses a two-stage instrumental variable quantile regression approach and is based on each HBS cross section, as well as the overall pooled observations. The estimated elasticities are compared across low- and high-energy-consumption scenarios and to a benchmark elasticity estimated using two-stage least squares. The results provide evidence that there is significant variation in the income elasticities across the energy expenditure distribution and that care must be taken when using the constant mean elasticity for policy purposes. More specifically, any examination of the future impact of a change in income support policy measures on energy consumption should recognize the substantial context-dependent variation in the income elasticity.
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2017.1313952 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:49:y:2017:i:54:p:5570-5578
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20
DOI: 10.1080/00036846.2017.1313952
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().