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Energy Cost Burdens for Low-Income and Minority Households

Author

Listed:
  • Constantine E. Kontokosta
  • Vincent J. Reina
  • Bartosz Bonczak

Abstract

Problem, research strategy, and findings: Of the three primary components of housing affordability measures—rent, transportation, and utilities—utility costs are the least understood yet are the one area where the cost burden can be reduced without household relocation. Existing data sources to estimate energy costs are limited to surveys with small samples and low spatial and temporal resolution, such as the American Housing Survey and the Residential Energy Consumption Survey. In this study, we present a new method for small-area estimates of household energy cost burdens (ECBs) that leverages actual building energy use data for approximately 13,000 multifamily properties across five U.S. cities and links energy costs to savings opportunities by analyzing 3,000 energy audit reports. We examine differentials in cost burdens across household demographic and socioeconomic characteristics and analyze spatial, regional, and building-level variations in energy use and expenditures. Our results show the average low-income household has an ECB of 7%, whereas higher income households have an average burden of 2%. Notably, even within defined income bands, minority households experience higher ECBs than non-Hispanic White households. For lower income households, low-cost energy improvements could reduce energy costs by as much as $1,500 per year.Takeaway for practice: In this study we attempt to shift the focus of energy efficiency investments to their impact on household cost burdens and overall housing affordability. Our analysis explores new and unique data generated from measurement-driven urban energy policies and shows low-income households disproportionately bear the burden of poor-quality and energy-inefficient housing. Cities can use these new data resources and methods to develop equity-based energy policies that treat energy efficiency and climate mitigation as issues of environmental justice and that apply data-driven, targeted policies to improve quality of life for the most vulnerable urban residents.

Suggested Citation

  • Constantine E. Kontokosta & Vincent J. Reina & Bartosz Bonczak, 2020. "Energy Cost Burdens for Low-Income and Minority Households," Journal of the American Planning Association, Taylor & Francis Journals, vol. 86(1), pages 89-105, January.
  • Handle: RePEc:taf:rjpaxx:v:86:y:2020:i:1:p:89-105
    DOI: 10.1080/01944363.2019.1647446
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    Cited by:

    1. Excell, Lauren E. & Jain, Rishee K., 2024. "Examining the impact of energy efficiency retrofits and vegetation on energy performance of institutional buildings: An equity-driven analysis," Applied Energy, Elsevier, vol. 357(C).
    2. Steven Beattie & Wai-Kin (Victor) Chan & Zixuan Wei & Zhibin Zhu, 2022. "Simulation Analysis of a Double Auction-Based Local Energy Market in Socio-Economic Context," Sustainability, MDPI, vol. 14(13), pages 1-25, June.
    3. Haiyang Shang & Fang Su & Serhat Yüksel & Hasan Dinçer, 2021. "Identifying the Strategic Priorities of the Technical Factors for the Sustainable Low Carbon Industry Based on Macroeconomic Conditions," SAGE Open, , vol. 11(2), pages 21582440211, May.
    4. Pennell, Grace & Newman, Sarah & Tarekegne, Bethel & Boff, Daniel & Fowler, Richard & Gonzalez, Juan, 2022. "A comparison of building system parameters between affordable and market-rate housing in New York City," Applied Energy, Elsevier, vol. 323(C).
    5. Ali Ghofrani & Esmat Zaidan & Mohsen Jafari, 2021. "Reshaping energy policy based on social and human dimensions: an analysis of human-building interactions among societies in transition in GCC countries," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-26, December.
    6. Jacobsen, Grant D., 2024. "Race, ethnicity, and the distribution of energy efficiency incentives," Energy Economics, Elsevier, vol. 130(C).

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