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Subjective versus objective energy burden: A look at drivers of different metrics and regional variation of energy poor populations

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  • Agbim, Chinelo
  • Araya, Felipe
  • Faust, Kasey M.
  • Harmon, Dana

Abstract

Energy poverty is typically assessed using the energy expenditure-to-income ratio as a metric. This metric fails to account, though, for residents' demographics and regional variation in energy consumption. In the United States, policymakers dealing with energy poverty have faced challenges estimating the needs for energy-assistance programs. This study seeks to explore regional variations in energy poverty. Using Texas as the region of study, this work also explores differences in the populations captured via objective and subjective metrics (i.e., those who are unable to pay their bill and those who state they struggle to do so). Drawing on survey data, this work uses statistical analyses to (1) assess the regional variation of energy poverty defined as a ratio of household income spent on electricity bills, (2) determine if there is an association between objective and subjective metrics of energy poverty, and (3) identify statistical drivers of objective and subjective energy poverty metrics. Of respondents, 51% of objectively energy-burdened individuals indicated they struggled to pay electricity bills and 53% faced great stress due to the electricity bill. If policymakers can use metrics that are more accurate in capturing populations facing energy poverty, more effective energy poverty policies might be formulated.

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  • Agbim, Chinelo & Araya, Felipe & Faust, Kasey M. & Harmon, Dana, 2020. "Subjective versus objective energy burden: A look at drivers of different metrics and regional variation of energy poor populations," Energy Policy, Elsevier, vol. 144(C).
    • Handle: RePEc:eee:enepol:v:144:y:2020:i:c:s0301421520303529
    DOI: 10.1016/j.enpol.2020.111616
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    2. Pereira, Diogo Santos & Marques, António Cardoso, 2023. "Are dynamic tariffs effective in reducing energy poverty? Empirical evidence from US households," Energy, Elsevier, vol. 282(C).
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    4. Tony G. Reames & Dorothy M. Daley & John C. Pierce, 2021. "Exploring the Nexus of Energy Burden, Social Capital, and Environmental Quality in Shaping Health in US Counties," IJERPH, MDPI, vol. 18(2), pages 1-13, January.
    5. Ku, Arthur Lin & Qiu, Yueming (Lucy) & Lou, Jiehong & Nock, Destenie & Xing, Bo, 2022. "Changes in hourly electricity consumption under COVID mandates: A glance to future hourly residential power consumption pattern with remote work in Arizona," Applied Energy, Elsevier, vol. 310(C).
    6. Feng, Tong & Du, Huibin & Coffman, D'Maris & Qu, Aiyu & Dong, Zhanfeng, 2021. "Clean heating and heating poverty: A perspective based on cost-benefit analysis," Energy Policy, Elsevier, vol. 152(C).
    7. Deller, David & Turner, Glen & Waddams Price, Catherine, 2021. "Energy poverty indicators: Inconsistencies, implications and where next?," Energy Economics, Elsevier, vol. 103(C).

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