Letting the (energy) Gini out of the bottle: Lorenz curves of cumulative electricity consumption and Gini coefficients as metrics of energy distribution and equity

By A. Jacobson, Anita Milman, Daniel M. Kammen. 2005

215 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Pollution, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/fce7924a6b9e888006a58e6779f69957e3833a7f

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Citations in the corpus

Connective Power: Solar Electrification and Social Change in Kenya (2004, background): “To put these numbers in further perspective, an average US household consumes about 10,000 kW h per year ( Jacobson, Milman, & Kammen, 2005 ).”
Measuring resource inequalities: The concepts and methodology for an area-based Gini coefficient (2008, methodology): “A commonly used measure of income inequality is the Gini coefficient (Ruitenbeek 1996; Fernandez et al. 2005; Jacobson et al. 2005; Bosi and Seegmuller 2006).”
Spatializing energy justice (2017, background): “…(Boardman, 2010; Oppenheim, 2016; Preston et al., 2013; Stockton and Campbell, 2011), despite lowincome groups generally having relatively minor carbon footprints (Jacobson et al., 2005) and often benefiting less from decarbonizationrelated interventions (Oppenheim, 2016; Walker, 2008).”
Electricity access and income inequality in South Africa: Evidence from Bayesian and NARDL analyses (2020, background): “The World Bank [27] noted that energy access is at the heart of development because of the many benefits especially in SSA, including improved health care, school operations, economic development and air quality [17,28].”
Beyond GDP: Measuring and achieving global genuine progress (2013, background): “A Gini coefficient of zero indicates perfect equality while a coefficient of one indicates maximum inequality (Jacobson et al., 2005).”
Measuring Resource Inequality: The Gini Coefficient (2009, methodology): “The Gini coefficient can be used to measure inequality in many other contexts besides income, including wealth, education, energy consumption (Jacobson et al. 2007), airport concentration, plant sizes and weights, or any other measurable quantity distributed across a population.”