<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>Iran Energy Association (IEA)</PublisherName>
				<JournalTitle>Journal of Energy Management and Technology</JournalTitle>
				<Issn>2588-3372</Issn>
				<Volume>2</Volume>
				<Issue>3</Issue>
				<PubDate PubStatus="epublish">
					<Year>2018</Year>
					<Month>09</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>An analysis of the determinants of electricity consumption in Benin</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>42</FirstPage>
			<LastPage>59</LastPage>
			<ELocationID EIdType="pii">68541</ELocationID>
			
<ELocationID EIdType="doi">10.22109/jemt.2018.125839.1075</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Paul Adjei</FirstName>
					<LastName>Kwakwa</LastName>
<Affiliation>School of Business and Economics
Presbyterian University College, Ghana</Affiliation>
<Identifier Source="ORCID">0000-0002-6516-217X</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2018</Year>
					<Month>03</Month>
					<Day>27</Day>
				</PubDate>
			</History>
		<Abstract>Available data indicate that close to two-thirds of the population of the Republic of Benin lacks access to electricity which has dire consequences on the country’s development agenda. Although electricity consumption has been increasing, the supply of electricity is not enough to meet the growing demand in the country. Managing electricity consumption in Benin has therefore become critical owing to the expected rise in the future consumption. This will help ensure future electricity security. Accordingly, this paper examines the determinants of electricity consumption for Benin using annual time series data for the period of 1971-2014. Estimation from the Autoregressive Distributed Lag model, the Fully Modified Ordinary Least Squares and the Canonical Co-integrating Regression reveal that population, urbanization, education and industrialisation positively affect electricity consumption for the country while income negatively reduces it. A further analysis using the rolling regression indicates that the effects of the above variables are time-varying with some social, political and economic changes. Among others, the paper recommends the need to increase awareness on environmental-energy issues; and the need for a policy to make new residential and non residential buildings that would be constructed in the urban centres especially, to be energy efficiently designed.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Electricity consumption</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Benin</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">STIRPAT model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">time-varying</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">rolling regression</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://www.jemat.org/article_68541_4b0a1f6acf16729624941f6a2da7c6f2.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
