Counting energy poverty in Spain between 2004 and 2015

Counting energy poverty in Spain between 2004 and 2015 In this paper, energy poverty is measured in Spain between 2004 and 2015. It has been analyzed globally for Spain and we have also decomposed and analyzed energy poverty for two different groups: three different types of areas, depending on their population share, and regions. The variables used to measure energy poverty are the three energy accessibility indicators: the ability to keep the home adequately warm, the arrears on utility bills (electricity, water, gas) and the presence of a leaking roof, damp walls or rotten windows. Energy poverty is measured using Chakravarty and D'Ambrosio counting poverty measures. These indices have been chosen since they are able to capture inequality, and in our opinion they are the most appropriate poverty indices when multidimensional poverty needs to be measured for dichotomous variables. In addition, counting dominance curves have been computed in order to give more robustness to the obtained results. Results suggest that energy poverty in Spain worsened between 2004 and 2015. Specifically, rural areas and Southern regions show the highest energy poverty values. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Energy Policy Elsevier

Counting energy poverty in Spain between 2004 and 2015

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0301-4215
D.O.I.
10.1016/j.enpol.2017.11.027
Publisher site
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Abstract

In this paper, energy poverty is measured in Spain between 2004 and 2015. It has been analyzed globally for Spain and we have also decomposed and analyzed energy poverty for two different groups: three different types of areas, depending on their population share, and regions. The variables used to measure energy poverty are the three energy accessibility indicators: the ability to keep the home adequately warm, the arrears on utility bills (electricity, water, gas) and the presence of a leaking roof, damp walls or rotten windows. Energy poverty is measured using Chakravarty and D'Ambrosio counting poverty measures. These indices have been chosen since they are able to capture inequality, and in our opinion they are the most appropriate poverty indices when multidimensional poverty needs to be measured for dichotomous variables. In addition, counting dominance curves have been computed in order to give more robustness to the obtained results. Results suggest that energy poverty in Spain worsened between 2004 and 2015. Specifically, rural areas and Southern regions show the highest energy poverty values.

Journal

Energy PolicyElsevier

Published: Feb 1, 2018

References

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