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Urban Residential Energy Demand and Rebound Effect in China: A Stochastic Energy Demand Frontier Approach

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  • Kerui Du, Shuai Shao, and Zheming Yan

Abstract

The energy rebound effect is a potential threat to energy-saving targets based on energy efficiency improvements. This paper employs a stochastic energy demand frontier model to analyze the energy demand and rebound effect in China's urban residential sector. Using a panel data set of 30 Chinese provincial-level regions over the period 20012014, for the first time, we investigate the degrees and determinants of China's urban residential energy demand and energy rebound effect. The results show that residents' income level, energy price, temperature deviation, population scale, household size, and district heating system are significant influencing factors of residential energy consumption. Regarding the energy rebound effect, we find that energy price is negatively correlated with the rebound effect, and an inverted U-shaped relationship between residents' income level and rebound-effect size exists. The magnitude of the rebound effect varies across regions, with an average of 65.4%. The main policy implication generated by this study is that it should be in urgent need of energy pricing reform to mitigate the rebound effect in China.

Suggested Citation

  • Kerui Du, Shuai Shao, and Zheming Yan, 2021. "Urban Residential Energy Demand and Rebound Effect in China: A Stochastic Energy Demand Frontier Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    • Handle: RePEc:aen:journl:ej42-4-shao
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    Cited by:

    1. Tian, Zhihua & Tian, Yanfang & Shen, Liangping & Shao, Shuai, 2021. "The health effect of household cooking fuel choice in China: An urban-rural gap perspective," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    2. Dorothée Charlier & Mouez Fodha & Djamel Kirat, 2023. "Residential CO2 Emissions in Europe and Carbon Taxation: A Country-Level Assessment," PSE-Ecole d'économie de Paris (Postprint) hal-03901487, HAL.
    3. Zhang, Zhenhua & Zhang, Guoxing & Su, Bin, 2022. "The spatial impacts of air pollution and socio-economic status on public health: Empirical evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    4. Zhen, Wei & Qin, Quande & Miao, Lu, 2023. "The greenhouse gas rebound effect from increased energy efficiency across China's staple crops," Energy Policy, Elsevier, vol. 173(C).
    5. Jia, Zhijie & Wen, Shiyan & Sun, Zao, 2022. "Current relationship between coal consumption and the economic development and China's future carbon mitigation policies," Energy Policy, Elsevier, vol. 162(C).
    6. Maliyamu Abudureheman & Qingzhe Jiang & Jiong Gong & Abulaiti Yiming, 2023. "Estimating and Decomposing the TFP Growth of Service-Oriented Manufacturing in China: A Translogarithmic Stochastic Frontier Approach," Sustainability, MDPI, vol. 15(7), pages 1-20, March.
    7. Li, Guohao & Niu, Miaomiao & Xiao, Jin & Wu, Jiaqian & Li, Jinkai, 2023. "The rebound effect of decarbonization in China’s power sector under the carbon trading scheme," Energy Policy, Elsevier, vol. 177(C).
    8. Ouyang, Xiaoling & Yang, Yuchuan & Du, Kerui & Cheng, Zhenyu, 2022. "How does residential electricity consumption respond to electricity efficiency improvement? Evidence from 287 prefecture-level cities in China," Energy Policy, Elsevier, vol. 171(C).
    9. Miao, Zhuang & Chen, Xiaodong, 2022. "Combining parametric and non-parametric approach, variable & source -specific productivity changes and rebound effect of energy & environment," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    10. Wang, Lijun & Zha, Donglan & O’Mahony, Tadhg & Zhou, Dequn, 2023. "Energy efficiency lags and welfare boons: Understanding the rebound and welfare effects through China's urban households," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    11. Lin, Boqiang & Zhu, Penghu, 2021. "Measurement of the direct rebound effect of residential electricity consumption: An empirical study based on the China family panel studies," Applied Energy, Elsevier, vol. 301(C).
    12. Jia, Zhijie & Wen, Shiyan & Lin, Boqiang, 2021. "The effects and reacts of COVID-19 pandemic and international oil price on energy, economy, and environment in China," Applied Energy, Elsevier, vol. 302(C).
    13. Wang, Xiong & Wang, Xiao & Ren, Xiaohang & Wen, Fenghua, 2022. "Can digital financial inclusion affect CO2 emissions of China at the prefecture level? Evidence from a spatial econometric approach," Energy Economics, Elsevier, vol. 109(C).
    14. Boqiang Lin & Kai Wei, 2022. "Does Use of Solid Cooking Fuels Increase Family Medical Expenses in China?," IJERPH, MDPI, vol. 19(3), pages 1-17, January.
    15. Jin Zhang & Lianrui Ma & Jinkai Li, 2021. "Why Low-Carbon Publicity Effect Limits? The Role of Heterogeneous Intention in Reducing Household Energy Consumption," Energies, MDPI, vol. 14(22), pages 1-17, November.
    16. Maliyamu Abudureheman & Qingzhe Jiang & Xiucheng Dong & Cong Dong, 2022. "CO 2 Emissions in China: Does the Energy Rebound Matter?," Energies, MDPI, vol. 15(12), pages 1-25, June.
    17. Xu, Le & Fan, Meiting & Yang, Lili & Shao, Shuai, 2021. "Heterogeneous green innovations and carbon emission performance: Evidence at China's city level," Energy Economics, Elsevier, vol. 99(C).

    More about this item

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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