Residential energy demand modelling in developing regions. The use of multivariate statistical techniques

Assimakopoulos, V

dc.contributor.author	Assimakopoulos, V	en
dc.date.accessioned	2014-03-01T01:09:01Z
dc.date.available	2014-03-01T01:09:01Z
dc.date.issued	1992	en
dc.identifier.issn	0140-9883	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/10801
dc.subject	Forecasting	en
dc.subject	Greece	en
dc.subject	Residential energy demand	en
dc.subject.classification	Economics	en
dc.subject.other	demand modelling	en
dc.subject.other	developing region	en
dc.subject.other	energy demand	en
dc.subject.other	multi-variate analysis	en
dc.subject.other	residential energy	en
dc.subject.other	simulation model	en
dc.subject.other	statistical technique	en
dc.subject.other	Greece, Cyclades	en
dc.title	Residential energy demand modelling in developing regions. The use of multivariate statistical techniques	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/0140-9883(92)90025-9	en
heal.identifier.secondary	http://dx.doi.org/10.1016/0140-9883(92)90025-9	en
heal.language	English	en
heal.publicationDate	1992	en
heal.abstract	This paper presents a new approach for modelling residential energy demand. In developing regions it is considered a new approach as energy demand equations apply to 'homogeneous' groups of consumers which are endogenously defined. The structural analysis of energy demand is the first phase of the approach which defines the set (tree) of consumption groups. These are obtained by applying multivariate statistical techniques on cross-section pooled data. Principal components analysis and discriminant analysis are the main methods used. The set of groups obtained is linked to a set of equations through a qualitative response model which simulates the decisions of households. Equations concerning energy consumption, the choice of energy equipment and the repartition by energy products are then estimated for each group. An application for the Cyclades region is presented. The model consists of 269 equations, 261 parameters and 15 exogenous variables. Scenarios and results for 1985-2000 are given together with a number of suggestions for further research.	en
heal.publisher	BUTTERWORTH-HEINEMANN LTD	en
heal.journalName	Energy Economics	en
dc.identifier.doi	10.1016/0140-9883(92)90025-9	en
dc.identifier.isi	ISI:A1992HC59900007	en
dc.identifier.volume	14	en
dc.identifier.issue	1	en
dc.identifier.spage	57	en
dc.identifier.epage	63	en