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Exploring the factors that influence energy use intensity across low-, middle-, and high-income households in the United States

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  • Chen, Chien-fei
  • Xu, Xiaojing
  • Adua, Lazarus
  • Briggs, Morgan
  • Nelson, Hannah

Abstract

This study examines the relationships between energy use intensity (EUI), which is considered to be an indicator of energy efficiency, and dwelling or housing characteristics, technology (appliances), socio-demographic characteristics, geographic factors, and energy-related behavioral actions. Additionally, it explores whether these relationships vary across low-, medium-, and high-income households. The study is based on regression analyses conducted on a representative sample of households, the 2015 U.S. Residential Energy Consumption Survey. Overall, the analysis revealed two important findings. First, residential energy use intensity is shaped significantly by housing characteristics, socio-demographic factors, technology, and energy-related behavioral actions. Second, the relationships between the factors examined and energy use intensity vary quite substantially across income groups. Lower income households have a higher EUI than higher income households. The policy implications of these findings are that reducing EUI in the residential sector, which may help with addressing energy burdens and poverty among low-income households, will require paying careful attention to these factors and their dynamic impacts across income groups.

Suggested Citation

  • Chen, Chien-fei & Xu, Xiaojing & Adua, Lazarus & Briggs, Morgan & Nelson, Hannah, 2022. "Exploring the factors that influence energy use intensity across low-, middle-, and high-income households in the United States," Energy Policy, Elsevier, vol. 168(C).
    • Handle: RePEc:eee:enepol:v:168:y:2022:i:c:s0301421522002968
    DOI: 10.1016/j.enpol.2022.113071
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    References listed on IDEAS

    as
    1. Sun, Huaping & Edziah, Bless Kofi & Kporsu, Anthony Kwaku & Sarkodie, Samuel Asumadu & Taghizadeh-Hesary, Farhad, 2021. "Energy efficiency: The role of technological innovation and knowledge spillover," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    2. Leahy, Eimear & Lyons, Sean, 2010. "Energy use and appliance ownership in Ireland," Energy Policy, Elsevier, vol. 38(8), pages 4265-4279, August.
    3. Chen, Chien-fei & Nelson, Hannah & Xu, Xiaojing & Bonilla, Gregory & Jones, Nicholas, 2021. "Beyond technology adoption: Examining home energy management systems, energy burdens and climate change perceptions during COVID-19 pandemic," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    4. Chen, Chien-fei & Li, Jiaxin & Shuai, Jing & Nelson, Hannah & Walzem, Allen & Cheng, Jinhua, 2021. "Linking social-psychological factors with policy expectation: Using local voices to understand solar PV poverty alleviation in Wuhan, China," Energy Policy, Elsevier, vol. 151(C).
    5. Lucas W. Davis, 2011. "Evaluating the Slow Adoption of Energy Efficient Investments: Are Renters Less Likely to Have Energy Efficient Appliances?," NBER Chapters, in: The Design and Implementation of US Climate Policy, pages 301-316, National Bureau of Economic Research, Inc.
    6. Jones, Rory V. & Fuertes, Alba & Lomas, Kevin J., 2015. "The socio-economic, dwelling and appliance related factors affecting electricity consumption in domestic buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 901-917.
    7. Day, Rosie & Walker, Gordon & Simcock, Neil, 2016. "Conceptualising energy use and energy poverty using a capabilities framework," Energy Policy, Elsevier, vol. 93(C), pages 255-264.
    8. Trotta, Gianluca, 2018. "Factors affecting energy-saving behaviours and energy efficiency investments in British households," Energy Policy, Elsevier, vol. 114(C), pages 529-539.
    9. Elisha R. Frederiks & Karen Stenner & Elizabeth V. Hobman, 2015. "The Socio-Demographic and Psychological Predictors of Residential Energy Consumption: A Comprehensive Review," Energies, MDPI, vol. 8(1), pages 1-37, January.
    10. Belaïd, Fateh & Roubaud, David & Galariotis, Emilios, 2019. "Features of residential energy consumption: Evidence from France using an innovative multilevel modelling approach," Energy Policy, Elsevier, vol. 125(C), pages 277-285.
    11. Janet L. Reyna & Mikhail V. Chester, 2017. "Energy efficiency to reduce residential electricity and natural gas use under climate change," Nature Communications, Nature, vol. 8(1), pages 1-12, August.
    12. Ma, Jun & Cheng, Jack C.P., 2016. "Identifying the influential features on the regional energy use intensity of residential buildings based on Random Forests," Applied Energy, Elsevier, vol. 183(C), pages 193-201.
    13. Kavousian, Amir & Rajagopal, Ram & Fischer, Martin, 2013. "Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior," Energy, Elsevier, vol. 55(C), pages 184-194.
    14. Wrigley, Koel & Crawford, Robert H., 2017. "Identifying policy solutions for improving the energy efficiency of rental properties," Energy Policy, Elsevier, vol. 108(C), pages 369-378.
    15. Saunders, Harry D., 2013. "Historical evidence for energy efficiency rebound in 30 US sectors and a toolkit for rebound analysts," Technological Forecasting and Social Change, Elsevier, vol. 80(7), pages 1317-1330.
    16. Michelle Graff & Sanya Carley, 2020. "COVID-19 assistance needs to target energy insecurity," Nature Energy, Nature, vol. 5(5), pages 352-354, May.
    17. Brounen, Dirk & Kok, Nils & Quigley, John M., 2013. "Energy literacy, awareness, and conservation behavior of residential households," Energy Economics, Elsevier, vol. 38(C), pages 42-50.
    18. Vanesa Castán Broto & Joshua Kirshner, 2020. "Energy access is needed to maintain health during pandemics," Nature Energy, Nature, vol. 5(6), pages 419-421, June.
    19. Adua, Lazarus, 2022. "Super polluters and carbon emissions: Spotlighting how higher-income and wealthier households disproportionately despoil our atmospheric commons," Energy Policy, Elsevier, vol. 162(C).
    20. Langevin, Jared & Gurian, Patrick L. & Wen, Jin, 2013. "Reducing energy consumption in low income public housing: Interviewing residents about energy behaviors," Applied Energy, Elsevier, vol. 102(C), pages 1358-1370.
    21. Vivian W. Y. Tam & Laura Almeida & Khoa Le, 2018. "Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review," Sustainability, MDPI, vol. 10(8), pages 1-20, July.
    22. Susan Clayton & Patrick Devine-Wright & Paul C. Stern & Lorraine Whitmarsh & Amanda Carrico & Linda Steg & Janet Swim & Mirilia Bonnes, 2015. "Psychological research and global climate change," Nature Climate Change, Nature, vol. 5(7), pages 640-646, July.
    23. Xu, Xiaojing & Chen, Chien-fei, 2019. "Energy efficiency and energy justice for U.S. low-income households: An analysis of multifaceted challenges and potential," Energy Policy, Elsevier, vol. 128(C), pages 763-774.
    24. Steg, Linda, 2008. "Promoting household energy conservation," Energy Policy, Elsevier, vol. 36(12), pages 4449-4453, December.
    25. Stephan, André & Crawford, Robert H., 2016. "The relationship between house size and life cycle energy demand: Implications for energy efficiency regulations for buildings," Energy, Elsevier, vol. 116(P1), pages 1158-1171.
    26. Huang, Wen-Hsiu, 2015. "The determinants of household electricity consumption in Taiwan: Evidence from quantile regression," Energy, Elsevier, vol. 87(C), pages 120-133.
    27. Reames, Tony Gerard, 2016. "Targeting energy justice: Exploring spatial, racial/ethnic and socioeconomic disparities in urban residential heating energy efficiency," Energy Policy, Elsevier, vol. 97(C), pages 549-558.
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