IDEAS home Printed from https://ideas.repec.org/p/aep/anales/4828.html

Cuál es el perfil de los hogares en condicion de pobreza energética? Un análisis de regresión por cuantiles

Author

Listed:
  • Poggiese Milena
  • Ibáñez Martín Maria
  • London Maria Silvia

Abstract

La pobreza energética se ha convertido en un problema central en el debate sobre des-igualdad y transición energética, pero la literatura argentina sigue siendo escasa y centrada en descripciones o modelos lineales convencionales. Este trabajo aporta evidencia novedosa utilizando una base de datos propia, reciente y local de la ciudad de Bahía Blanca a partir de la Encuesta de Ingresos y Servicios de los Hogares 2024, utilizando principalmente técnicas de regresión condicional por cuantiles y comparando dos enfoques de medición: el criterio del 10% del ingreso destinado a energía y un índice multidimensional de privaciones (MEPI). Los resultados muestran que la pobreza monetaria es un determinante robusto, aunque los dos indicadores capturan dimensiones distintas de vulnerabilidad: el primero refleja restricciones de asequibilidad, mientras que el segundo expone carencias estructurales vinculadas a vivienda y equipamiento. El análisis por cuantiles revela fuertes heterogeneidades a lo largo de la distribución. Los hallazgos destacan la necesidad de políticas diferenciadas que combinen transferencias focalizadas con intervenciones estructurales en vivienda y acceso a energías limpias.

Suggested Citation

  • Poggiese Milena & Ibáñez Martín Maria & London Maria Silvia, 2025. "Cuál es el perfil de los hogares en condicion de pobreza energética? Un análisis de regresión por cuantiles," Asociación Argentina de Economía Política: Working Papers 4828, Asociación Argentina de Economía Política.
    • Handle: RePEc:aep:anales:4828
    as

    Download full text from publisher

    File URL: https://aaep.org.ar/works/works2025/4828.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fateh Belaid & Christophe Rault, 2020. "Energy Expenditure in Egypt: Empirical Evidence Based on A Quantile Regression Approach," Working Papers 1446, Economic Research Forum, revised 20 Dec 2020.
    2. Yuxiang Xie & E. Xie, 2023. "Measuring and Analyzing the Welfare Effects of Energy Poverty in Rural China Based on a Multi-Dimensional Energy Poverty Index," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    3. Awaworyi Churchill, Sefa & Smyth, Russell, 2021. "Energy poverty and health: Panel data evidence from Australia," Energy Economics, Elsevier, vol. 97(C).
    4. Javier Alejo & Federico Favata & Gabriel Montes-Rojas & Martín Trombetta, 2021. "Conditional vs Unconditional Quantile Regression Models: A Guide to Practitioners," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 44(88), pages 76-93.
    5. Fernando Rios-Avila & Michelle Lee Maroto, 2024. "Moving Beyond Linear Regression: Implementing and Interpreting Quantile Regression Models With Fixed Effects," Sociological Methods & Research, , vol. 53(2), pages 639-682, May.
    6. Abbas, Khizar & Li, Shixiang & Xu, Deyi & Baz, Khan & Rakhmetova, Aigerim, 2020. "Do socioeconomic factors determine household multidimensional energy poverty? Empirical evidence from South Asia," Energy Policy, Elsevier, vol. 146(C).
    7. Fumo, Nelson & Rafe Biswas, M.A., 2015. "Regression analysis for prediction of residential energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 332-343.
    8. J. Harold & J. Cullinan & S. Lyons, 2017. "The income elasticity of household energy demand: a quantile regression analysis," Applied Economics, Taylor & Francis Journals, vol. 49(54), pages 5570-5578, November.
    Full references (including those not matched with items on IDEAS)

    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. Cheng, Shulei & Wang, Kexin & Chen, Yongtao & Meng, Fanxin, 2025. "Temporal-spatial decomposition and multi-scenario prediction analysis of energy poverty in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 219(C).
    2. Junpeng Li & Wanglin Ma, 2025. "Alleviating Multidimensional Energy Poverty and Energy Unaffordability in Rural Areas: The Role of Renting-Out Land," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 178(1), pages 465-497, May.
    3. Jun Zhang & Yuang He & Jing Zhang, 2022. "Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach," IJERPH, MDPI, vol. 19(2), pages 1-21, January.
    4. Sen, Kanchan Kumar & Karmaker, Shamal Chandra & Hosan, Shahadat & Chapman, Andrew J. & Uddin, Md Kamal & Saha, Bidyut Baran, 2023. "Energy poverty alleviation through financial inclusion: Role of gender in Bangladesh," Energy, Elsevier, vol. 282(C).
    5. Li, Zhiqun & Xie, Shang & Wei, Dongming, 2025. "Household energy poverty and personal time allocation: Empirical evidence from China," Utilities Policy, Elsevier, vol. 93(C).
    6. Dogan, Eyup & Madaleno, Mara & Inglesi-Lotz, Roula & Taskin, Dilvin, 2022. "Race and energy poverty: Evidence from African-American households," Energy Economics, Elsevier, vol. 108(C).
    7. Budrìa, S.; & Li Donni, P.; & Zucchelli, E.;, 2025. "Sick and Cold? Evidence on the dynamic interplay between energy poverty and health," Health, Econometrics and Data Group (HEDG) Working Papers 25/01, HEDG, c/o Department of Economics, University of York.
    8. Rosy Pradhan Shrestha & Brijesh Mainali & Charafeddine Mokhtara & Sunil Prasad Lohani, 2025. "Bearing the Burden: Understanding the Multifaceted Impact of Energy Poverty on Women," Sustainability, MDPI, vol. 17(5), pages 1-27, March.
    9. Wang, Chao & Geng, Wei, 2025. "Local government debt and household human capital investment," Finance Research Letters, Elsevier, vol. 79(C).
    10. Keyu Chen & Chao Feng, 2022. "Linking Housing Conditions and Energy Poverty: From a Perspective of Household Energy Self-Restriction," IJERPH, MDPI, vol. 19(14), pages 1-17, July.
    11. Ssennono, Vincent Fred & Ntayi, Joseph M. & Buyinza, Faisal & Wasswa, Francis & Aarakit, Sylvia Manjeri & Mukiza, Chris Ndatira, 2021. "Energy poverty in Uganda: Evidence from a multidimensional approach," Energy Economics, Elsevier, vol. 101(C).
    12. Ang'u, Cohen & Muthama, Nzioka John & Mutuku, Mwanthi Alexander & M’IKiugu, Mutembei Henry, 2023. "Analysis of energy poverty in Kenya and its implications for human health," Energy Policy, Elsevier, vol. 176(C).
    13. Bagnoli, Lisa & Bertoméu-Sánchez, Salvador, 2022. "How effective has the electricity social rate been in reducing energy poverty in Spain?," Energy Economics, Elsevier, vol. 106(C).
    14. Prakash, Kushneel & Awaworyi Churchill, Sefa & Smyth, Russell, 2022. "Are you puffing your Children's future away? Energy poverty and childhood exposure to passive smoking," Economic Modelling, Elsevier, vol. 114(C).
    15. Ren, Yi-Shuai & Jiang, Yong & Narayan, Seema & Ma, Chao-Qun & Yang, Xiao-Guang, 2022. "Marketisation and rural energy poverty: Evidence from provincial panel data in China," Energy Economics, Elsevier, vol. 111(C).
    16. Budría, Santiago & Bravo Chew, Leslie, 2025. "Enduring Inequalities: Analyzing Energy Poverty Inertia Across K-Means Clusters," IZA Discussion Papers 17809, Institute of Labor Economics (IZA).
    17. Omar, Md Abdullah & Hasanujzaman, Muhammad, 2021. "Multidimensional energy poverty in Bangladesh and its effect on health and education: A multilevel analysis based on household survey data," Energy Policy, Elsevier, vol. 158(C).
    18. Apergis, Nicholas & Polemis, Michael & Soursou, Simeoni-Eleni, 2022. "Energy poverty and education: Fresh evidence from a panel of developing countries," Energy Economics, Elsevier, vol. 106(C).
    19. Ye Fan & Tim Döring & Shouhao Li & Xin Zhang & Ming Fang & Yongda Yu, 2024. "Energy poverty and public health vulnerability: A multi‐country analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(5), pages 5161-5180, October.
    20. Gan, Hongwu & Lin, Chuan & Zhou, Yang & Zhuo, Zhiyi, 2025. "Adult children's education and elderly parents' energy poverty: Evidence from China," Energy Policy, Elsevier, vol. 202(C).

    More about this item

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    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:aep:anales:4828. 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: Juan Manuel Quintero (email available below). General contact details of provider: https://edirc.repec.org/data/aaeppea.html .

    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.