IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-30146-5.html
   My bibliography  Save this article

Unveiling hidden energy poverty using the energy equity gap

Author

Listed:
  • Shuchen Cong

    (Carnegie Mellon University)

  • Destenie Nock

    (Carnegie Mellon University
    Carnegie Mellon University)

  • Yueming Lucy Qiu

    (University of Maryland College Park)

  • Bo Xing

    (Salt River Project)

Abstract

Income-based energy poverty metrics ignore people’s behavior patterns, particularly reducing energy consumption to limit financial stress. We investigate energy-limiting behavior in low-income households using a residential electricity consumption dataset. We first determine the outdoor temperature at which households start using cooling systems, the inflection temperature. Our relative energy poverty metric, the energy equity gap, is defined as the difference in the inflection temperatures between low and high-income groups. In our study region, we estimate the energy equity gap to be between 4.7–7.5 °F (2.6–4.2 °C). Within a sample of 4577 households, we found 86 energy-poor and 214 energy-insecure households. In contrast, the income-based energy poverty metric, energy burden (10% threshold), identified 141 households as energy-insecure. Only three households overlap between our energy equity gap and the income-based measure. Thus, the energy equity gap reveals a hidden but complementary aspect of energy poverty and insecurity.

Suggested Citation

  • Shuchen Cong & Destenie Nock & Yueming Lucy Qiu & Bo Xing, 2022. "Unveiling hidden energy poverty using the energy equity gap," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30146-5
    DOI: 10.1038/s41467-022-30146-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-30146-5
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-30146-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Weihua Dong & Zhao Liu & Hua Liao & Qiuhong Tang & Xian’en Li, 2015. "New climate and socio-economic scenarios for assessing global human health challenges due to heat risk," Climatic Change, Springer, vol. 130(4), pages 505-518, June.
    2. Trevor Memmott & Sanya Carley & Michelle Graff & David M. Konisky, 2021. "Sociodemographic disparities in energy insecurity among low-income households before and during the COVID-19 pandemic," Nature Energy, Nature, vol. 6(2), pages 186-193, February.
    3. Pachauri, Shonali & Spreng, Daniel, 2011. "Measuring and monitoring energy poverty," Energy Policy, Elsevier, vol. 39(12), pages 7497-7504.
    4. Jean-Yves Duclos & David Sahn & Stephen D. Younger, 2006. "Robust Multidimensional Spatial Poverty Comparisons in Ghana, Madagascar, and Uganda," The World Bank Economic Review, World Bank, vol. 20(1), pages 91-113.
    5. Jean-Yves Duclos & David E. Sahn & Stephen D. Younger, 2006. "Robust Multidimensional Poverty Comparisons," Economic Journal, Royal Economic Society, vol. 116(514), pages 943-968, October.
    6. Dominic J. Bednar & Tony G. Reames, 2020. "Recognition of and response to energy poverty in the United States," Nature Energy, Nature, vol. 5(6), pages 432-439, June.
    7. Jean-Yves Duclos & David Sahn & Stephen D. Younger, 2006. "Robust Multidimensional Poverty Comparisons with Discrete Indicators of Well-being," Cahiers de recherche 0628, CIRPEE.
    8. Primc, Kaja & Slabe-Erker, Renata & Majcen, Boris, 2019. "Constructing energy poverty profiles for an effective energy policy," Energy Policy, Elsevier, vol. 128(C), pages 727-734.
    9. Sovacool, Benjamin K., 2015. "Fuel poverty, affordability, and energy justice in England: Policy insights from the Warm Front Program," Energy, Elsevier, vol. 93(P1), pages 361-371.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ackermann, Klaus & Awaworyi Churchill, Sefa & Smyth, Russell, 2023. "High-speed internet access and energy poverty," Energy Economics, Elsevier, vol. 127(PB).
    2. Huang, Luling & Nock, Destenie & Cong, Shuchen & Qiu, Yueming (Lucy), 2023. "Inequalities across cooling and heating in households: Energy equity gaps," Energy Policy, Elsevier, vol. 182(C).
    3. Spandagos, Constantine & Tovar Reaños, Miguel & Lynch, Muireann Á, 2023. "Energy poverty prediction and effective targeting for just transitions with machine learning," Papers WP762, Economic and Social Research Institute (ESRI).
    4. Gu, Jiafeng, 2023. "Energy poverty and government subsidies in China," Energy Policy, Elsevier, vol. 180(C).
    5. Furszyfer Del Rio, Dylan D. & Sovacool, Benjamin K., 2023. "Of cooks, crooks and slum-dwellers: Exploring the lived experience of energy and mobility poverty in Mexico's informal settlements," World Development, Elsevier, vol. 161(C).
    6. Jones, Andrew & Nock, Destenie & Samaras, Constantine & Qiu, Yueming (Lucy) & Xing, Bo, 2023. "Climate change impacts on future residential electricity consumption and energy burden: A case study in Phoenix, Arizona," Energy Policy, Elsevier, vol. 183(C).
    7. Pezalla, Simon & Obringer, Renee, 2023. "Evaluating the household-level climate-electricity nexus across three cities through statistical learning techniques," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    8. Kwon, Minji & Cong, Shuchen & Nock, Destenie & Huang, Luling & Qiu, Yueming (Lucy) & Xing, Bo, 2023. "Forgone summertime comfort as a function of avoided electricity use," Energy Policy, Elsevier, vol. 183(C).
    9. Yanelli Nunez & Jaime Benavides & Jenni A. Shearston & Elena M. Krieger & Misbath Daouda & Lucas R. F. Henneman & Erin E. McDuffie & Jeff Goldsmith & Joan A. Casey & Marianthi-Anna Kioumourtzoglou, 2024. "An environmental justice analysis of air pollution emissions in the United States from 1970 to 2010," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    10. Muhammad Shafiullah & Zhilun Jiao & Muhammad Shahbaz & Kangyin Dong, 2023. "Examining energy poverty in Chinese households: An Engel curve approach," Australian Economic Papers, Wiley Blackwell, vol. 62(1), pages 149-184, March.
    11. Heleno, Miguel & Sigrin, Benjamin & Popovich, Natalie & Heeter, Jenny & Jain Figueroa, Anjuli & Reiner, Michael & Reames, Tony, 2022. "Optimizing equity in energy policy interventions: A quantitative decision-support framework for energy justice," Applied Energy, Elsevier, vol. 325(C).
    12. Laibao Liu & Gang He & Mengxi Wu & Gang Liu & Haoran Zhang & Ying Chen & Jiashu Shen & Shuangcheng Li, 2023. "Climate change impacts on planned supply–demand match in global wind and solar energy systems," Nature Energy, Nature, vol. 8(8), pages 870-880, August.
    13. Benjamin K. Sovacool & Paul Upham & Mari Martiskainen & Kirsten E. H. Jenkins & Gerardo A. Torres Contreras & Neil Simcock, 2023. "Policy prescriptions to address energy and transport poverty in the United Kingdom," Nature Energy, Nature, vol. 8(3), pages 273-283, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Okushima, Shinichiro, 2017. "Gauging energy poverty: A multidimensional approach," Energy, Elsevier, vol. 137(C), pages 1159-1166.
    2. Espinoza-Delgado, José & Silber, Jacques, 2018. "Multi-dimensional poverty among adults in Central America and gender differences in the three I’s of poverty: Applying inequality sensitive poverty measures with ordinal variables," MPRA Paper 88750, University Library of Munich, Germany.
    3. Jing Yang & Pundarik Mukhopadhaya, 2019. "Is the ADB’s Conjecture on Upward Trend in Poverty for China Right? An Analysis of Income and Multidimensional Poverty in China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(2), pages 451-477, June.
    4. Christophe Muller & Asha Kannan & Roland Alcindor, 2016. "Multidimensional Poverty in Seychelles," Working Papers halshs-01264444, HAL.
    5. Alkire, Sabina & Santos, Maria Emma, 2014. "Measuring Acute Poverty in the Developing World: Robustness and Scope of the Multidimensional Poverty Index," World Development, Elsevier, vol. 59(C), pages 251-274.
    6. David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2020. "Bayesian assessment of Lorenz and stochastic dominance," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 767-799, May.
    7. Fotis Papadopoulos & Panos Tsakloglou, 2015. "Chronic material deprivation and long-term poverty in Europe in the pre-crisis period," ImPRovE Working Papers 15/16, Herman Deleeck Centre for Social Policy, University of Antwerp.
    8. M. Azhar Hussain & Nikolaj Siersbæk & Lars Peter Østerdal, 2020. "Multidimensional welfare comparisons of EU member states before, during, and after the financial crisis: a dominance approach," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 55(4), pages 645-686, December.
    9. Marcello Basili & Paulo Casaca & Alain Chateauneuf & Maurizio Franzini, 2017. "Multidimensional Pigou–Dalton transfers and social evaluation functions," Theory and Decision, Springer, vol. 83(4), pages 573-590, December.
    10. Gaston Yalonetzky, 2014. "Conditions for the most robust multidimensional poverty comparisons using counting measures and ordinal variables," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 43(4), pages 773-807, December.
    11. David Lander & David Gunawan & William E. Griffiths & Duangkamon Chotikapanich, 2016. "Bayesian Assessment of Lorenz and Stochastic Dominance Using a Mixture of Gamma Densities," Department of Economics - Working Papers Series 2023, The University of Melbourne.
    12. Koen Decancq & Marc Fleurbaey & François Maniquet, 2019. "Multidimensional poverty measurement with individual preferences," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(1), pages 29-49, March.
    13. David Madden, 2015. "Health and Wealth on the Roller-Coaster: Ireland, 2003–2011," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 121(2), pages 387-412, April.
    14. Nicolas Gravel & Patrick Moyes & Benoît Tarroux, 2009. "Robust International Comparisons of Distributions of Disposable Income and Regional Public Goods," Economica, London School of Economics and Political Science, vol. 76(303), pages 432-461, July.
    15. Bénédicte Apouey & David Madden, 2023. "Health poverty," Chapters, in: Jacques Silber (ed.), Research Handbook on Measuring Poverty and Deprivation, chapter 19, pages 202-211, Edward Elgar Publishing.
    16. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.
    17. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2022. "Stochastic dominance spanning and augmenting the human development index with institutional quality," Annals of Operations Research, Springer, vol. 315(1), pages 341-369, August.
    18. Aaberge, Rolf & Peluso, Eugenio & Sigstad, Henrik, 2019. "The dual approach for measuring multidimensional deprivation: Theory and empirical evidence," Journal of Public Economics, Elsevier, vol. 177(C), pages 1-1.
    19. LABAR, Kelly & BRESSON, Florent, 2011. "A multidimensional analysis of poverty in China from 1991 to 2006," China Economic Review, Elsevier, vol. 22(4), pages 646-668.
    20. M. Azhar Hussain & Mette Møller Jørgensen & Lars Peter Østerdal, 2016. "Refining Population Health Comparisons: A Multidimensional First Order Dominance Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(2), pages 739-759, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30146-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.