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Energy poverty and its relationship with health: empirical evidence on the dynamics of energy poverty and poor health in Australia

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  • Heather Brown

    (Newcastle University, Population Health Sciences Institute, Royal Victoria Infirmary)

  • Esperanza Vera-Toscano

    (University of Melbourne, Level 4)

Abstract

Does poor health increase the likelihood of energy poverty or vice versa creating a vicious poverty trap? We use data from the Household, Income and Labour Dynamics of Australia (HILDA) survey from 2005–2018 to explore if these two processes are dynamically related across a number of subjective and objective measures of physical and mental health as well as subjective and objective measures of energy poverty. We employ univariate dynamic models, introduce controls for initial conditions, and explore inter-dependence between energy poverty and health using a dynamic bivariate probit model. Our results show that controlling for initial conditions impacts on the magnitude and significance of the lagged coefficients. We only find cross-dependency effects between energy poverty and health for subjective measures of energy poverty. This suggests that individuals’ feelings about being in energy poverty may impact on their health leading to poor health/energy poverty traps. Targeting individuals in financial stress/debt may be one way to reduce these poor health/energy poverty traps.

Suggested Citation

  • Heather Brown & Esperanza Vera-Toscano, 2021. "Energy poverty and its relationship with health: empirical evidence on the dynamics of energy poverty and poor health in Australia," SN Business & Economics, Springer, vol. 1(10), pages 1-34, October.
    • Handle: RePEc:spr:snbeco:v:1:y:2021:i:10:d:10.1007_s43546-021-00149-3
    DOI: 10.1007/s43546-021-00149-3
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    Cited by:

    1. Esperanza Vera‐Toscano & Heather Brown, 2022. "Empirical Evidence on the Incidence and Persistence of Energy Poverty in Australia," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 55(4), pages 515-529, December.
    2. Drago, Carlo & Gatto, Andrea, 2023. "Gauging energy poverty in developing countries with a composite metric of electricity access," Utilities Policy, Elsevier, vol. 81(C).
    3. Awan, Ashar & Bilgili, Faik & Rahut, Dil Bahadur, 2022. "Energy poverty trends and determinants in Pakistan: Empirical evidence from eight waves of HIES 1998–2019," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. Siyou Xia & Yu Yang & Xiaoying Qian & Xin Xu, 2022. "Spatiotemporal Interaction and Socioeconomic Determinants of Rural Energy Poverty in China," IJERPH, MDPI, vol. 19(17), pages 1-15, August.

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    More about this item

    Keywords

    Energy poverty; Health; Dynamic bivariate probit; Australia;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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