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Measuring resource inequalities: The concepts and methodology for an area-based Gini coefficient

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  • Druckman, A.
  • Jackson, T.
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    Abstract

    Although inequalities in income and expenditure are relatively well researched, comparatively little attention has been paid, to date, to inequalities in resource use. This is clearly a shortcoming when it comes to developing informed policies for sustainable consumption and social justice. This paper describes an indicator of inequality in resource use called the AR-Gini. The AR-Gini is an area-based measure of resource inequality that estimates inequalities between neighbourhoods with regard to the consumption of specific consumer goods. It is also capable of estimating inequalities in the emissions resulting from resource use, such as carbon dioxide emissions from energy use, and solid waste arisings from material resource use. The indicator is designed to be used as a basis for broadening the discussion concerning 'food deserts' to inequalities in other types of resource use. By estimating the AR-Gini for a wide range of goods and services we aim to enhance our understanding of resource inequalities and their drivers, identify which resources have highest inequalities, and to explore trends in inequalities. The paper describes the concepts underlying the construction of the AR-Gini and its methodology. Its use is illustrated by pilot applications (specifically, men's and boys' clothing, carpets, refrigerators/freezers and clothes washer/driers). The results illustrate that different levels of inequality are associated with different commodities. The paper concludes with a brief discussion of some possible policy implications of the AR-Gini.

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    Bibliographic Info

    Article provided by Elsevier in its journal Ecological Economics.

    Volume (Year): 65 (2008)
    Issue (Month): 2 (April)
    Pages: 242-252

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    Handle: RePEc:eee:ecolec:v:65:y:2008:i:2:p:242-252

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    Web page: http://www.elsevier.com/locate/ecolecon

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    7. Fernandez, E. & Saini, R.P. & Devadas, V., 2005. "Relative inequality in energy resource consumption: a case of Kanvashram village, Pauri Garhwal district, Uttranchall (India)," Renewable Energy, Elsevier, vol. 30(5), pages 763-772.
    8. Saboohi, Y., 2001. "An evaluation of the impact of reducing energy subsidies on living expenses of households," Energy Policy, Elsevier, vol. 29(3), pages 245-252, February.
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    Cited by:
    1. Bouvier, Rachel, 2014. "Distribution of income and toxic emissions in Maine, United States: Inequality in two dimensions," Ecological Economics, Elsevier, vol. 102(C), pages 39-47.
    2. Boukary OUEDRAOGO (CEDRES - Université de Ouaga II) & Sylvie FERRARI (GREThA, CNRS, UMR5113), 2012. "Incidence of forest income in reducing poverty and inequalities:\r\nEvidence from forest dependent households in managed forests’ areas in Burkina Faso," Cahiers du GREThA 2012-28, Groupe de Recherche en Economie Théorique et Appliquée.
    3. Wiedenhofer, Dominik & Lenzen, Manfred & Steinberger, Julia K., 2013. "Energy requirements of consumption: Urban form, climatic and socio-economic factors, rebounds and their policy implications," Energy Policy, Elsevier, vol. 63(C), pages 696-707.
    4. Sovacool, Benjamin K., 2011. "Conceptualizing urban household energy use: Climbing the "Energy Services Ladder"," Energy Policy, Elsevier, vol. 39(3), pages 1659-1668, March.
    5. Steinberger, Julia K. & Krausmann, Fridolin & Eisenmenger, Nina, 2010. "Global patterns of materials use: A socioeconomic and geophysical analysis," Ecological Economics, Elsevier, vol. 69(5), pages 1148-1158, March.
    6. Chancel, Lucas, 2014. "Are younger generations higher carbon emitters than their elders?," Ecological Economics, Elsevier, vol. 100(C), pages 195-207.
    7. Druckman, Angela & Jackson, Tim, 2009. "The carbon footprint of UK households 1990-2004: A socio-economically disaggregated, quasi-multi-regional input-output model," Ecological Economics, Elsevier, vol. 68(7), pages 2066-2077, May.

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