The Impact of Demographic Transition on Energy Poverty in China: Potential Challenges and Opportunities
Abstract
Energy poverty is a serious concern and an influential global determinant of subjective well-being (SWB). This paper seeks to explore the impact of demographic transition on energy poverty. Data for the study was obtained through panel data from 30 provinces of China from 2010 to 2022. The old dependency ratio is selected to address the shift in the total population. The negative population growth is anticipated to increase further and may not be easy to reverse. Demographic shifts also cause the gap to widen and alter the patterns of energy consumption. The energy poverty concept is measured through a multidimensional energy poverty index (MEPI) established on five key indicators: electricity consumption, clean cooking fuel like natural gas, telecommunication, heating, and cooling appliances. A Generalized Method of Moments (GMM) estimation technique is used to analyze the impact of the old dependency ratio (ODR) on energy poverty and a fixed effects model is performed to confirm the stability of the results. The outcome reveals that ODR and the demographic transition strongly contribute to worsening energy poverty. Effective policy implications regarding regional disparities among the elderly can change these challenges into opportunities and enhance clean energy access and infrastructure development across all regions.
References
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57. Cheng, L., Liu, H., Zhang, Y., & Zhao, Z. (2018). The health implications of social pensions: Evidence from China's new rural pension scheme. Journal of Comparative Economics, 46(1), 53-77.
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59. Wei, T., Turhong, Y., Duan, Z., & Yao, X. Regional Disparities and Variation Sources Decomposition of Energy System Resilience in China. Available at SSRN 5030281.
2. Nussbaumer, P., Bazilian, M., & Modi, V. (2012). Measuring energy poverty: Focusing on what matters. Renewable and sustainable energy reviews, 16(1), 231-243.
3. Independent Evaluation, G. (2020). Renewable Energy: Evaluation of the World Bank Group’s Support for Electricity from Renewable Energy Resources, 2000-2017. World Bank.
4. United nation 2019 highlights. 2019. https://digitallibrary.un.org/record/3813698/files/WPP2019_Highlights.pdf
5. Hong, X., Wu, S., & Zhang, X. (2022). Clean energy powers energy poverty alleviation: reference from Chinese micro-survey data. Technological Forecasting and Social Change, 182, 121737.
6. Tang, X., & Liao, H. (2014). Energy poverty and solid fuels use in rural China: Analysis based on national population census. Energy for Sustainable Development, 23, 122-129.
7. Kaygusuz, K. (2011). Energy services and energy poverty for sustainable rural development. Renewable and sustainable energy reviews, 15(2), 936-947.
8. Sesan, T. (2012). Navigating the limitations of energy poverty: Lessons from the promotion of improved cooking technologies in Kenya. Energy Policy, 47, 202-210.
9. Zhou, D., Gu, X., & Ding, H. (2021). Impact of Demographic Transition on Household Energy Consumption: A Case from China. Energy Engineering, 118(4), 961-979.
10. Li, X., Li, S., & Liu, C. (2024). Labor Force Participation Rate Prediction of China: Scenario Simulation Based on Education and Retirement Strategies. Journal of Advanced Computational Intelligence and Intelligent Informatics, 28(3), 704-713.
11. Cai, Y. (2013). China's new demographic reality: learning from the 2010 census. Population and development review, 39(3), 371-396.
12. Shi, X., Cui, L., Huang, Z., Zeng, P., Qiu, T., Fu, L., & Jiang, Q. (2023). Impact of internal migration on household energy poverty: empirical evidence from rural China. Applied Energy, 350, 121780.
13. Maestas, N., Mullen, K. J., & Powell, D. (2023). The effect of population aging on economic growth, the labor force, and productivity. American Economic Journal: Macroeconomics, 15(2), 306-332.
14. Cai, F. (2012). Chapter Five Growing Pains: What Employment Dilemma Does China Face at Its Lewis Turning Point? In The China Population and Labor Yearbook, Volume 3 (pp. 113-134). Brill.
15. World Health Organization. 2024. Aging and health. https://www.who.int/china/health-topics/ageing.
16. Chen, Y., Guo, F., Wang, J., Cai, W., Wang, C., & Wang, K. (2020). Provincial and gridded population projection for China under shared socioeconomic pathways from 2010 to 2100. Scientific Data, 7(1), 83.
17. Dong, K., Dou, Y., & Jiang, Q. (2022). Income inequality, energy poverty, and energy efficiency: Who cause who and how? Technological Forecasting and Social Change, 179, 121622.
18. Cai, F. (1998). Regional characteristics of labor migration in the transitional period. Zhongguo Renkou Kexue (Chinese Journal of Population Research), 5, 18-24.
19. Prices, R. E. Their Impact on the Manufacturing Industry: Which Sectors Are Being Hit the Hardest. In.
20. Liu, Y., Li, Z., & Yin, X. (2018). Environmental regulation, technological innovation and energy consumption---a cross-region analysis in China. Journal of Cleaner Production, 203, 885-897.
21. Zhang, J., Faraz Raza, S. M., Huang, Y., & Wang, C. (2023). What affect energy poverty in China? A path towards sustainable development. Economic research-Ekonomska istraživanja, 36(2).
22. International Energy Agency. (2002). Energy and poverty: The case of China. International Energy Agency. https://www.iea.org/reports/energy-and-poverty-the-case-of-china.
23. Hills, J. (2011). Fuel poverty: The problem and its measurement. Interim report of the Fuel Poverty Review.
24. Zhang, D., Li, J., & Han, P. (2019). A multidimensional measure of energy poverty in China and its impacts on health: An empirical study based on the China family panel studies. Energy Policy, 131, 72-81.
25. Lin, B., & Zhao, H. (2021). Does off-farm work reduce energy poverty? Evidence from rural China. Sustainable Production and Consumption, 27, 1822-1829.
26. Ren, Y.-S., Jiang, Y., Narayan, S., Ma, C.-Q., & Yang, X.-G. (2022). Marketisation and rural energy poverty: Evidence from provincial panel data in China. Energy Economics, 111, 106073.
27. Zhou, Y., Liu, Z., Wang, H., & Cheng, G. (2023). Targeted poverty alleviation narrowed China's urban-rural income gap: A theoretical and empirical analysis. Applied Geography, 157, 103000.
28. Adkins, E., Eapen, S., Kaluwile, F., Nair, G., & Modi, V. (2010). Off-grid energy services for the poor: introducing LED lighting in the Millennium Villages Project in Malawi. Energy Policy, 38(2), 1087-1097.
29. Leitão, N. C. (2021). The effects of corruption, renewable energy, trade and CO2 emissions. Economies, 9(2), 62.
30. Sato, Y., & Yamamoto, K. (2005). Population concentration, urbanization, and demographic transition. Journal of Urban Economics, 58(1), 45-61.
31. Qi, G., Wang, Z., Wei, L., & Wang, Z. (2022). Multidimensional effects of urbanization on PM2. 5 concentration in China. Environmental Science and Pollution Research, 29(51), 77081-77096.
32. Lin, B., & Wang, Y. (2020). Does energy poverty really exist in China? From the perspective of residential electricity consumption. Energy Policy, 143, 111557.
33. Hu, S., Yan, D., Guo, S., Cui, Y., & Dong, B. (2017). A survey on energy consumption and energy usage behavior of households and residential building in urban China. Energy and Buildings, 148, 366-378.
34. Wang, X., Delina, L. L., & Matus, K. (2023). Living with energy poverty: Uncovering older people’s fuel choices in urban China. Energy Research & Social Science, 104, 103247.
35. Igawa, M., & Managi, S. (2022). Energy poverty and income inequality: An economic analysis of 37 countries. Applied Energy, 306, 118076.
36. Boardman, B. (1991). Fuel poverty: from cold homes to affordable warmth. (No Title).
37. Bollino, C. A., & Botti, F. (2017). Energy poverty in Europe: A multidimensional approach. PSL Quarterly Review, 70(283), 473-507.
38. Okushima, S. (2016). Measuring energy poverty in Japan, 2004–2013. Energy Policy, 98, 557-564.
39. Pachauri, S., & Spreng, D. (2011). Measuring and monitoring energy poverty. Energy Policy, 39(12), 7497-7504.
40. Sadath, A. C., & Acharya, R. H. (2017). Assessing the extent and intensity of energy poverty using Multidimensional Energy Poverty Index: Empirical evidence from households in India. Energy Policy, 102, 540-550.
41. Wang, B., Li, H.-N., Yuan, X.-C., & Sun, Z.-M. (2017). Energy poverty in China: A dynamic analysis based on a hybrid panel data decision model. Energies, 10(12), 1942.
42. Barnes, D. F., Khandker, S. R., & Samad, H. A. (2011). Energy poverty in rural Bangladesh. Energy Policy, 39(2), 894-904.
43. Foster, V., Tre, J.-P., & Wodon, Q. (2000). Energy prices, energy efficiency, and fuel poverty. Latin America and Caribbean Regional Studies Programme. Washington, DC: World Bank, 131(42), 1-7.
44. Behera, B., & Ali, A. (2016). Patterns and determinants of household use of fuels for cooking: Empirical evidence from sub-Saharan Africa. Energy, 117, 93-104.
45. Legendre, B., & Ricci, O. (2015). Measuring fuel poverty in France: Which households are the most fuel vulnerable? Energy Economics, 49, 620-628.
46. Zhuang, J., Vandenberg, P., & Huang, Y. (2012). Growing beyond the low-cost advantage: How the People's Republic of China can avoid the middle-income trap. Asian Development Bank.
47. Zhang, S.-H., Yang, J., & Feng, C. (2023). Can internet development alleviate energy poverty? Evidence from China. Energy Policy, 173, 113407.
48. Holdren, J. (2018). A brief history of IPAT. the journal of population and sustainability, 2(2), 66–74-66–74.
49. Nguyen, T.-H., & Vo, H.-H. (2020). Principal eigenvalue and positive solutions for Fractional $ PQ $ Laplace operator in quantum field theory. arXiv preprint arXiv:2006.03233.
50. Pais-Magalhães, V., Moutinho, V., & Robaina, M. (2022). Is an ageing population
51. impacting energy use in the European Union? Drivers, lifestyles, and consumption patterns of elderly households. Energy Research & Social Science, 85, 102443.
52. Wang, Z., Wei, L., Zhang, X., & Qi, G. (2023). Impact of demographic age structure on energy consumption structure: Evidence from population aging in mainland China. Energy, 273, 127226.
53. Lee, C.-C., Yuan, Z., Lee, C.-C., & Chang, Y.-F. (2022). The impact of renewable energy technology innovation on energy poverty: does climate risk matter? Energy Economics, 116, 106427.
54. Tao, Z., Chen, Y., Wang, Z., & Deng, C. (2024). The impact of climate change and environmental regulation on energy poverty: evidence from China. Energy, Sustainability and Society, 14(1), 54.
55. Chester, L., & Morris, A. (2011). A new form of energy poverty is the hallmark of liberalised electricity sectors. Australian Journal of Social Issues, 46(4), 435-459.
56. Li, H., Li, H., Cao, A., & Guo, L. (2022). Does attending in social pension program promotes household energy transition? Evidence from ethnical minority regions of rural China. Energy for Sustainable Development, 70, 361-370.
57. Cheng, L., Liu, H., Zhang, Y., & Zhao, Z. (2018). The health implications of social pensions: Evidence from China's new rural pension scheme. Journal of Comparative Economics, 46(1), 53-77.
58. Li, H., Hanewald, K., & Wu, S. (2017). Estimating healthy life expectancy: a Province-by-Province study for China. ARC Centre of Excellence in Population Ageing Research (CEPAR) Working Paper(2017/14).
59. Wei, T., Turhong, Y., Duan, Z., & Yao, X. Regional Disparities and Variation Sources Decomposition of Energy System Resilience in China. Available at SSRN 5030281.
Authors
[1]
“The Impact of Demographic Transition on Energy Poverty in China: Potential Challenges and Opportunities”, Soc. sci. humanities j., vol. 9, no. 01, pp. 6585–6605, Jan. 2025, doi: 10.18535/sshj.v9i01.1619.
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