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Abstract

Indonesia's rapidly ageing population faces an increasing risk of multidimensional energy poverty (MEP) due to limited household resources and persistent disparities in infrastructure and energy access. This study provides a descriptive and correlational assessment of MEP among individuals aged 60 years and above using pooled data from the 2019–2021 National Socio-Economic Survey (Susenas). An individual-level MEP index is constructed following the Alkire–Foster counting methodology across six dimensions: cooking, lighting, household appliances, education and entertainment, communication, and travel. At the conventional deprivation cut-off (k = 0.3), 72.0% of the 356,611 elderly individuals in the pooled sample are classified as multidimensionally energy poor. Descriptive comparisons show that MEP is most strongly associated with lower household expenditure, fewer years of schooling, rural residence, limited access to tap water, and lower rates of migration and land ownership, whereas house ownership is not significantly associated with MEP. Correlation analysis further identifies three broad patterns of association among the explanatory variables, corresponding to household roles, socioeconomic development, and asset ownership, while indicating no evidence of severe multicollinearity. Overall, household economic resources, educational attainment, and access to basic infrastructure emerge as the characteristics most strongly associated with MEP among Indonesia's elderly population. These findings provide an accessible and easily replicable evidence base for identifying vulnerable groups and may inform the targeting of energy assistance programmes and the implementation of Indonesia's Gender Equality, Disability, and Social Inclusion (GEDSI) agenda.

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How to Cite
Suhendra, S. (2026). Multidimensional Energy Poverty (MEP) among Older Adults in Indonesia: Descriptive Evidence and Correlation Analysis. Jurnal Ekonomi Dan Statistik Indonesia, 6(1), 1-10. https://doi.org/10.11594/jesi.06.01.01

References

Adioetomo, S. M., Cicih, L. M., & Asmanedi, T. R. (2018). Menjadi lansia tangguh: antara anugerah dan tantangan. Memetik bonus demografi membangun manusia sejak dini. Rajawali Pers.
Alkire, S., & Foster, J. (2011). Counting and multidimensional poverty measurement. Journal of Public Economics, 95(7–8), 476–487. https://doi.org/10.1016/j.jpubeco.2010.11.006
Awaworyi Churchill, S., & Smyth, R. (2021). Energy poverty and health: Panel data evidence from Australia. Energy Econom-ics, 97, 105219. https://doi.org/10.1016/j.eneco.2021.105219
Awaworyi Churchill, S., Smyth, R., & Farrell, L. (2020). Fuel poverty and subjective well-being. Energy Economics, 86, 104650. https://doi.org/10.1016/j.eneco.2019.104650
De Vries, R., & Blane, D. (2013). Fuel poverty and the health of older people: The role of local climate. Journal of Public Health (United Kingdom), 35(3), 361–366. https://doi.org/10.1093/pubmed/fds094
Fry, J. M., Farrell, L., & Temple, J. B. (2022). Energy poverty and retirement income sources in Australia. Energy Economics, 106, 105793. https://doi.org/10.1016/j.eneco.2021.105793
Hanna, R., & Oliva, P. (2015). Moving up the energy ladder: The effect of an increase in economic well being on the fuel con-sumption choices of the poor in India. American Economic Review, 105(5), 242–246. https://doi.org/10.1257/aer.p20151097
Henning-Smith, C., & Gonzales, G. (2020). The relationship between living alone and self-rated health varies by age: Evidence from the National Health Interview Sur-vey. Journal of Applied Gerontology, 39(9), 971–980. https://doi.org/10.1177/0733464819835113
Hills, J. (2011). Fuel poverty: The problem and its measurement (Interim report). Centre for Analysis of Social Exclusion, London School of Economics.
Hou, J., Zhou, W., & Jiang, Y. (2022). Multidi-mensional energy poverty and depres-sion among China's older adults. Fron-tiers in Public Health, 10, 977958. https://doi.org/10.3389/fpubh.2022.977958
Jamalludin, J. (2020). Keputusan pekerja lansia tetap bekerja pascapensiun dan kai-tannya dengan kebahagiaan. Jurnal Sam-udra Ekonomi Dan Bisnis, 12(1), 89–101. https://doi.org/10.33059/jseb.v12i1.2450
Li, Y., Ning, X., Wang, Z., Cheng, J., Li, F., & Hao, Y. (2022). Would energy poverty affect the wellbeing of senior citizens? Evidence from China. Ecological Economics, 200, 107515. https://doi.org/10.1016/j.ecolecon.2022.107515
Mendoza, C. B., Cayonte, D. D. D., Leabres, M. S., & Manaligod, L. R. A. (2019). Under-standing multidimensional energy pov-erty in the Philippines. Energy Policy, 133, 110886. https://doi.org/10.1016/j.enpol.2019.110886
Nussbaumer, P., Bazilian, M., & Modi, V. (2012). Measuring energy poverty: Fo-cusing on what matters. Renewable and Sustainable Energy Reviews, 16(1), 231–243. https://doi.org/10.1016/j.rser.2011.07.150
Piekut, M. (2021). Between poverty and ener-gy satisfaction in Polish households run by people aged 60 and older. Energies, 14(19), 6032. https://doi.org/10.3390/en14196032
Rizal, R. N., Hartono, D., Dartanto, T., & Gultom, Y. M. L. (2024). Multidimensional energy poverty: A study of its measure-ment, decomposition, and determinants in Indonesia. Heliyon, 10(3), e24135. https://doi.org/10.1016/j.heliyon.2024.e24135
Sadath, A. C., & Acharya, R. H. (2017). As-sessing the extent and intensity of energy poverty using Multidimensional Energy Poverty Index: Empirical evidence from households in India. Energy Policy, 102, 540–550. https://doi.org/10.1016/j.enpol.2016.12.056
Sambodo, M. T., & Novandra, R. (2019). The state of energy poverty in Indonesia and its impact on welfare. Energy Policy, 132, 113–121. https://doi.org/10.1016/j.enpol.2019.05.029
Saputri, N. K., Setyonugroho, L. D., & Hartono, D. (2024). Exploring the determinants of energy poverty in Indonesia's house-holds: Empirical evidence from the 2015–2019 SUSENAS. Humanities and Social Sciences Communications, 11(1), 60. https://doi.org/10.1057/s41599-023-02514-z
Zhang, D., Li, J., & Han, P. (2019). A multidi-mensional measure of energy poverty in China and its impacts on health: An em-pirical study based on the China Family Panel Studies. Energy Policy, 131, 72–81. https://doi.org/10.1016/j.enpol.2019.04.037
Zhang, Z., Shu, H., Yi, H., & Wang, X. (2021). Household multidimensional energy pov-erty and its impacts on physical and men-tal health. Energy Policy, 156, 112381. https://doi.org/10.1016/j.enpol.2021.112381
Zhao, J. P., Liu, X. X., Gao, Y., Li, D. X., Liu, F. F., Zhou, J., Zha, F. B., & Wang, Y. L. (2024). Estimates of multidimensional poverty and its determinants among older people in rural China: Evidence from a multicen-ter cross-sectional survey. BMC Geriat-rics, 24, 835. https://doi.org/10.1186/s12877-024-05413-3