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Predicting fuel poverty at a small-area level in England
This paper describes the development of a series of models for predicting the incidence of fuel poverty in England at a small-area level and examines the adequacy of the modelled results in informing our understanding of the geography of fuel poverty. This paper summarises the development of alterna...
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Published in: | Energy policy 2011-07, Vol.39 (7), p.4370-4377 |
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creator | Fahmy, Eldin Gordon, David Patsios, Demi |
description | This paper describes the development of a series of models for predicting the incidence of fuel poverty in England at a small-area level and examines the adequacy of the modelled results in informing our understanding of the geography of fuel poverty. This paper summarises the development of alternative approaches to model specification based upon different approaches to the treatment of household income. Since 2003 small-area fuel poverty estimates have been widely used to inform affordable warmth policies and local targeting of fuel poverty programs. Whilst improvements in data sources and methods in recent years provide an opportunity to better understand the spatial distribution of fuel poverty, these analyses suggest that our understanding of the incidence and spatial distribution of fuel poverty is highly sensitive to the way in which household incomes are measured.
► The proposed models estimate fuel poverty incidence at a small-area level. ► This is necessary in order to accurately target local fuel poverty interventions. ► Fuel poverty estimates are highly sensitive to differences in income measurement. ► Fewer children and more pensioners are fuel poor using EHCS income measures. ► More children and fewer pensioners are fuel poor using HBAI income measures. |
doi_str_mv | 10.1016/j.enpol.2011.04.057 |
format | article |
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► The proposed models estimate fuel poverty incidence at a small-area level. ► This is necessary in order to accurately target local fuel poverty interventions. ► Fuel poverty estimates are highly sensitive to differences in income measurement. ► Fewer children and more pensioners are fuel poor using EHCS income measures. ► More children and fewer pensioners are fuel poor using HBAI income measures.</description><identifier>ISSN: 0301-4215</identifier><identifier>EISSN: 1873-6777</identifier><identifier>DOI: 10.1016/j.enpol.2011.04.057</identifier><identifier>CODEN: ENPYAC</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Applied sciences ; Data analysis ; Deprivation ; Economic data ; Energy ; Energy economics ; Energy policy ; Exact sciences and technology ; Family income ; Fuel poverty ; Fuel poverty Housing quality Deprivation ; Fuels ; General, economic and professional studies ; geography ; household income ; Housing ; Housing quality ; issues and policy ; Low income ; Methodology. Modelling ; Poverty ; prediction ; Regions ; Studies ; United Kingdom</subject><ispartof>Energy policy, 2011-07, Vol.39 (7), p.4370-4377</ispartof><rights>2011 Elsevier Ltd</rights><rights>2014 INIST-CNRS</rights><rights>Copyright Elsevier Science Ltd. Jul 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c603t-a9cc6d4b77c0923df3467e5b2fa09c34f0c67779482651a2df45656d9afefe883</citedby><cites>FETCH-LOGICAL-c603t-a9cc6d4b77c0923df3467e5b2fa09c34f0c67779482651a2df45656d9afefe883</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27866,27924,27925,33223,33224</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24303037$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttp://econpapers.repec.org/article/eeeenepol/v_3a39_3ay_3a2011_3ai_3a7_3ap_3a4370-4377.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Fahmy, Eldin</creatorcontrib><creatorcontrib>Gordon, David</creatorcontrib><creatorcontrib>Patsios, Demi</creatorcontrib><title>Predicting fuel poverty at a small-area level in England</title><title>Energy policy</title><description>This paper describes the development of a series of models for predicting the incidence of fuel poverty in England at a small-area level and examines the adequacy of the modelled results in informing our understanding of the geography of fuel poverty. This paper summarises the development of alternative approaches to model specification based upon different approaches to the treatment of household income. Since 2003 small-area fuel poverty estimates have been widely used to inform affordable warmth policies and local targeting of fuel poverty programs. Whilst improvements in data sources and methods in recent years provide an opportunity to better understand the spatial distribution of fuel poverty, these analyses suggest that our understanding of the incidence and spatial distribution of fuel poverty is highly sensitive to the way in which household incomes are measured.
► The proposed models estimate fuel poverty incidence at a small-area level. ► This is necessary in order to accurately target local fuel poverty interventions. ► Fuel poverty estimates are highly sensitive to differences in income measurement. ► Fewer children and more pensioners are fuel poor using EHCS income measures. ► More children and fewer pensioners are fuel poor using HBAI income measures.</description><subject>Applied sciences</subject><subject>Data analysis</subject><subject>Deprivation</subject><subject>Economic data</subject><subject>Energy</subject><subject>Energy economics</subject><subject>Energy policy</subject><subject>Exact sciences and technology</subject><subject>Family income</subject><subject>Fuel poverty</subject><subject>Fuel poverty Housing quality Deprivation</subject><subject>Fuels</subject><subject>General, economic and professional studies</subject><subject>geography</subject><subject>household income</subject><subject>Housing</subject><subject>Housing quality</subject><subject>issues and policy</subject><subject>Low income</subject><subject>Methodology. 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Modelling</topic><topic>Poverty</topic><topic>prediction</topic><topic>Regions</topic><topic>Studies</topic><topic>United Kingdom</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fahmy, Eldin</creatorcontrib><creatorcontrib>Gordon, David</creatorcontrib><creatorcontrib>Patsios, Demi</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>PAIS Index</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>International Bibliography of the Social Sciences</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>International Bibliography of the Social Sciences</collection><collection>Materials Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><jtitle>Energy policy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fahmy, Eldin</au><au>Gordon, David</au><au>Patsios, Demi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting fuel poverty at a small-area level in England</atitle><jtitle>Energy policy</jtitle><date>2011-07-01</date><risdate>2011</risdate><volume>39</volume><issue>7</issue><spage>4370</spage><epage>4377</epage><pages>4370-4377</pages><issn>0301-4215</issn><eissn>1873-6777</eissn><coden>ENPYAC</coden><abstract>This paper describes the development of a series of models for predicting the incidence of fuel poverty in England at a small-area level and examines the adequacy of the modelled results in informing our understanding of the geography of fuel poverty. This paper summarises the development of alternative approaches to model specification based upon different approaches to the treatment of household income. Since 2003 small-area fuel poverty estimates have been widely used to inform affordable warmth policies and local targeting of fuel poverty programs. Whilst improvements in data sources and methods in recent years provide an opportunity to better understand the spatial distribution of fuel poverty, these analyses suggest that our understanding of the incidence and spatial distribution of fuel poverty is highly sensitive to the way in which household incomes are measured.
► The proposed models estimate fuel poverty incidence at a small-area level. ► This is necessary in order to accurately target local fuel poverty interventions. ► Fuel poverty estimates are highly sensitive to differences in income measurement. ► Fewer children and more pensioners are fuel poor using EHCS income measures. ► More children and fewer pensioners are fuel poor using HBAI income measures.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.enpol.2011.04.057</doi><tpages>8</tpages></addata></record> |
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source | International Bibliography of the Social Sciences (IBSS); ScienceDirect Journals; PAIS Index |
subjects | Applied sciences Data analysis Deprivation Economic data Energy Energy economics Energy policy Exact sciences and technology Family income Fuel poverty Fuel poverty Housing quality Deprivation Fuels General, economic and professional studies geography household income Housing Housing quality issues and policy Low income Methodology. Modelling Poverty prediction Regions Studies United Kingdom |
title | Predicting fuel poverty at a small-area level in England |
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