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  • Although the EU is one of the wealthiest societies the world has ever known, around 10% of households cannot heat their homes adequately, rising to almost 40% in some countries. This chapter tests the hypothesis that a country’s level of economic inequality—measured by the Gini coefficient of income after tax and welfare transfers—is a predictor of that country’s percentage of households unable to heat their homes. I perform sets of multivariate regression analyses for EU countries plus the UK, for each of the years 2010–16. I use the natural logarithm of the percentage unable to heat their homes, as the dependent variable. For independent variables, I use the Gini coefficient (after tax and transfers), GDP per capita, wealth per household, heating degree-days, household debt-to-income ratio and the percentage of “inadequate” homes, i.e., showing leaks, mold or rot. In all analyses I find the Gini coefficient a significant predictor. Further, each 1-percentage-point difference in the Gini is associated with a difference of up to 4.6% points in the number unable to heat their homes. While regression analyses cannot not prove causation, the results alert us to the strong possibility that fiscal and social policy to reduce income inequality may also reduce the percentage unable to hear their homes. More robust energy efficiency policy would also be needed, to bring about even deeper reductions. (xsd:string)
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  • (SILC) (xsd:string)
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  • EU-SILC-Bibliography (xsd:string)
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  • 2020 (xsd:gyear)
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  • 2020 (xsd:gyear)
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  • 10.1016/B978-0-12-817674-0.00007-2 ()
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  • 145 (xsd:string)
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  • english (xsd:string)
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  • 978-0-12-817674-0 ()
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  • Cold homes and Gini coefficients in EU countries (xsd:string)
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  • Inequality and Energy (xsd:string)
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  • Bibsonomy (xsd:string)
  • In Inequality and Energy, edited by Galvin, Ray, 145-171, Academic Press, 2020 (xsd:string)
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  • European Union Statistics on Income and Living Conditions (EU-SILC) (xsd:string)
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  • 2020 (xsd:string)
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  • SILC (xsd:string)
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