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Residential responses to service-specific electricity demand: Case of China

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  • Jia, Jun-Jun
  • Ni, Jinlan
  • Wei, Chu

Abstract

Understanding the diversity of the residential demand for various electrical services is critical for utilities and policymakers in conducting effective demand side management and narrowing urban-rural inequality. Previous research has usually treated the household as a unit of analysis, and thus may have ignored the fact that household electricity consumption is derived demand driven by specific services, which fails to examine the heterogeneous behavioral responses. Therefore, this paper presents a new pattern of residential demand for various electrical services and quantifies the impacts of socioeconomic determinants in China. The conditional demand analysis is performed on the unique dataset of the Chinese Residential Energy Consumption Survey of 2014 to estimate the electricity demand distribution in eight types of services and to investigate the effect of socioeconomic variables on service-specific electricity consumption. The results show that, together, entertainment and food refrigeration account for about half of the total annual electricity consumption, followed by laundry, lighting, space cooling, and hot water. Rural households use about 7.2% of total electricity for cooking purposes, while urban counterparts hardly use electricity to cook at all. Electricity consumption for space heating is negligible for both urban and rural households. Heterogeneity in socioeconomic determinants is found not only among different electrical services but also between urban and rural households.

Suggested Citation

  • Jia, Jun-Jun & Ni, Jinlan & Wei, Chu, 2023. "Residential responses to service-specific electricity demand: Case of China," China Economic Review, Elsevier, vol. 78(C).
  • Handle: RePEc:eee:chieco:v:78:y:2023:i:c:s1043951x23000020
    DOI: 10.1016/j.chieco.2023.101917
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    as
    1. John M. Quigley, 1984. "The Production of Housing Services and the Derived Demand for Residential Energy," RAND Journal of Economics, The RAND Corporation, vol. 15(4), pages 555-567, Winter.
    2. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    3. Maximilian Auffhammer & Catherine D. Wolfram, 2014. "Powering Up China: Income Distributions and Residential Electricity Consumption," American Economic Review, American Economic Association, vol. 104(5), pages 575-580, May.
    4. Hung, Ming-Feng & Huang, Tai-Hsin, 2015. "Dynamic demand for residential electricity in Taiwan under seasonality and increasing-block pricing," Energy Economics, Elsevier, vol. 48(C), pages 168-177.
    5. Guo, Jin & Huang, Ying & Wei, Chu, 2015. "North–South debate on district heating: Evidence from a household survey," Energy Policy, Elsevier, vol. 86(C), pages 295-302.
    6. Zhang, Hongwu & Shi, Xunpeng & Wang, Keying & Xue, Jinjun & Song, Ligang & Sun, Yongping, 2020. "Intertemporal lifestyle changes and carbon emissions: Evidence from a China household survey," Energy Economics, Elsevier, vol. 86(C).
    7. Bas J. van Ruijven & Enrica De Cian & Ian Sue Wing, 2019. "Amplification of future energy demand growth due to climate change," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    8. Matteo Muratori, 2018. "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," Nature Energy, Nature, vol. 3(3), pages 193-201, March.
    9. Rapson, David, 2014. "Durable goods and long-run electricity demand: Evidence from air conditioner purchase behavior," Journal of Environmental Economics and Management, Elsevier, vol. 68(1), pages 141-160.
    10. Shimei Wu & Xinye Zheng & Chu Wei, 2017. "Measurement of inequality using household energy consumption data in rural China," Nature Energy, Nature, vol. 2(10), pages 795-803, October.
    11. Bernard, Jean-Thomas & Bolduc, Denis & Yameogo, Nadège-Désirée, 2011. "A pseudo-panel data model of household electricity demand," Resource and Energy Economics, Elsevier, vol. 33(1), pages 315-325, January.
    12. Kamerschen, David R. & Porter, David V., 2004. "The demand for residential, industrial and total electricity, 1973-1998," Energy Economics, Elsevier, vol. 26(1), pages 87-100, January.
    13. Robert Bartels & Denzil G. Fiebig, 2000. "Residential End-Use Electricity Demand: Results from a Designed Experiment," The Energy Journal, , vol. 21(2), pages 51-81, April.
    14. Jia, Zhijie & Wen, Shiyan & Liu, Yu, 2022. "China's urban-rural inequality caused by carbon neutrality: A perspective from carbon footprint and decomposed social welfare," Energy Economics, Elsevier, vol. 113(C).
    15. Matsumoto, Shigeru, 2016. "How do household characteristics affect appliance usage? Application of conditional demand analysis to Japanese household data," Energy Policy, Elsevier, vol. 94(C), pages 214-223.
    16. Wang, Keying & Cui, Yongyan & Zhang, Hongwu & Shi, Xunpeng & Xue, Jinjun & Yuan, Zhao, 2022. "Household carbon footprints inequality in China: Drivers, components and dynamics," Energy Economics, Elsevier, vol. 115(C).
    17. Dennis Tao Yang, 2012. "Aggregate Savings and External Imbalances in China," Journal of Economic Perspectives, American Economic Association, vol. 26(4), pages 125-146, Fall.
    18. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    19. Halicioglu, Ferda, 2007. "Residential electricity demand dynamics in Turkey," Energy Economics, Elsevier, vol. 29(2), pages 199-210, March.
    20. Brounen, Dirk & Kok, Nils & Quigley, John M., 2012. "Residential energy use and conservation: Economics and demographics," European Economic Review, Elsevier, vol. 56(5), pages 931-945.
    21. Hanne Marit Dalen and Bodil M. Larsen, 2015. "Residential End-use Electricity Demand: Development over Time," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    22. Frank A. Wolak, 2011. "Do Residential Customers Respond to Hourly Prices? Evidence from a Dynamic Pricing Experiment," American Economic Review, American Economic Association, vol. 101(3), pages 83-87, May.
    23. Yating Li & William A. Pizer & Libo Wu, 2019. "Climate change and residential electricity consumption in the Yangtze River Delta, China," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(2), pages 472-477, January.
    24. Larsen, Bodil Merethe & Nesbakken, Runa, 2004. "Household electricity end-use consumption: results from econometric and engineering models," Energy Economics, Elsevier, vol. 26(2), pages 179-200, March.
    25. Xinye Zheng & Chu Wei (ed.), 2019. "Household Energy Consumption in China: 2016 Report," Springer Books, Springer, number 978-981-13-7523-1, December.
    26. Jia, Jun-Jun & Guo, Jin & Wei, Chu, 2021. "Elasticities of residential electricity demand in China under increasing-block pricing constraint: New estimation using household survey data," Energy Policy, Elsevier, vol. 156(C).
    27. Cao, Jing & Ho, Mun Sing & Li, Yating & Newell, Richard G. & Pizer, William A., 2019. "Chinese residential electricity consumption: Estimation and forecast using micro-data," Resource and Energy Economics, Elsevier, vol. 56(C), pages 6-27.
    28. Peter C. Reiss & Matthew W. White, 2005. "Household Electricity Demand, Revisited," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 853-883.
    29. Newsham, Guy R. & Donnelly, Cara L., 2013. "A model of residential energy end-use in Canada: Using conditional demand analysis to suggest policy options for community energy planners," Energy Policy, Elsevier, vol. 59(C), pages 133-142.
    30. Shi, Xunpeng & Wang, Keying & Cheong, Tsun Se & Zhang, Hongwu, 2020. "Prioritizing driving factors of household carbon emissions: An application of the LASSO model with survey data," Energy Economics, Elsevier, vol. 92(C).
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    More about this item

    Keywords

    Chinese residential sector; Service-specific electricity consumption; Socioeconomic determinants; Heterogeneous responses; Conditional demand analysis;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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