Gauging energy poverty: A multidimensional approach

Okushima, Shinichiro

doi:10.1016/j.energy.2017.05.137

Cited by 196 publications

(103 citation statements)

References 33 publications

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“…Palabras clave: an alisis espacial, PCA geogr aficamente ponderado, pobreza energ etica, SIG, vulnerabilidad. E nergy poverty in the home has attracted considerable attention in research, policymaking, and practice during recent years (Liddell et al 2012;Boardman 2013), and this interest is becoming increasingly global (Harrison and Popke 2011;Thomson and Snell 2013;Okushima 2017;Sadath and Acharya 2017). Subsequently some of the stark, relative inequalities in access to domestic energy services that exist between and within different national contexts (J.…”

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confidence: 99%

The Spatially Varying Components of Vulnerability to Energy Poverty

Robinson

Lindley

Bouzarovski

2019

Annals of the American Association of Geographers

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A household's vulnerability to energy poverty is socially and spatially variable. Efforts to measure energy poverty, however, have focused on narrow, expenditure-based metrics or area-based targeting. These metrics are not spatial per se, because the relative importance of drivers does not vary between neighborhoods to reflect localized challenges. Despite recent advancements in geographically weighted methodologies that have the potential to yield important information about the sociospatial distribution of vulnerability to energy poverty, the phenomenon has not been approached from this perspective. For a case study of England, global principal component analysis (PCA) and local geographically weighted PCA (GWPCA) are applied to a suite of neighborhood-scale vulnerability indicators. The explicit spatiality of this methodological approach addresses a common criticism of vulnerability assessments. The global PCA reaffirms the importance of well-established vulnerabilities, including older age, disability, and energy efficiency. It also demonstrates striking new evidence of vulnerabilities among precarious and transient households that are less well understood and have become starker during austerity. In contrast, rather than providing a single estimate of propensity to energy poverty for neighborhoods based on a national understanding of what drives the condition, the GWPCA identifies a diverse array of vulnerability factors of greatest importance in different locales. These local results destabilize the geographical configurations of an urban-rural and north-south divide that typify understandings of deprivation in this context. The geographically weighted approach therefore draws attention to vulnerabilities often hidden in policymaking, allowing for reflection on the applicability of spatially constituted methodologies to wider social vulnerability assessments.

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confidence: 99%

The Spatially Varying Components of Vulnerability to Energy Poverty

Robinson

Lindley

Bouzarovski

2019

Annals of the American Association of Geographers

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“…Year of house construction Greece, Japan, Portugal, (housing's age) [42,[45][46][47][48]59] Global South, Attika(Greece), Zaragoza(Spain)…”

Section: Category Indicator Country/region Applied Tomentioning

confidence: 99%

Big Data and Energy Poverty Alleviation

Hassani

Yeganegi

Beneki

et al. 2019

BDCC

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The focus of this paper is to bring to light the vital issue of energy poverty alleviation and how big data could improve the data collection quality and mechanism. It also explains the vicious circle of low productivity, health risk, environmental pollution and energy poverty and presents currently used energy poverty measures and alleviation policies and stresses the associated problems in application due to the underlying dynamics.

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“…Multi-Tier Framework (MTF) proposed by the World Bank. Energy Poverty Index (EPI) proposed by Mirza and Szirmai in 2010 [17] and calculated in Nussbaumer et al in 2013 [18], Fabbri (2015) for Italy [19] and Okushima (2017) for the case of Japan [20].…”

Section: Measurement Of Energy Povertymentioning

confidence: 99%

Energy Poverty in Ecuador

2019

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This paper aims to identify the presence of energy poverty in Ecuador. Three indicators proposed by the European Union Energy Poverty Observatory (EPOV) are used to construct a multidimensional energy poverty index (MEPI) based on measure conditions associated with energy poverty, in areas related to delays in the payment of electricity bills, disproportionate expenses, hidden energy poverty, and the 10% Boardman (1991) rule. The information comes from the Ecuatorian Life Conditions Survey. The results show that energy poverty is present in Ecuadorian households, at the national level, and just as these indicators have restrictions, advantages and disadvantages, which demand decisions about the choice of their use.

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Gauging energy poverty: A multidimensional approach

Cited by 196 publications

References 33 publications

The Spatially Varying Components of Vulnerability to Energy Poverty

The Spatially Varying Components of Vulnerability to Energy Poverty

Big Data and Energy Poverty Alleviation

Energy Poverty in Ecuador

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