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Does household lifestyle impact the decarbonization effect of carbon generalized system of preferences? Evidence from household survey in China

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  • Su, Xiaoying
  • Zha, Donglan
  • Zhang, Chaoqun
  • Zhao, Kuokuo

Abstract

The household carbon emissions (HCEs) account for a large proportion of China’s overall carbon emissions. The Carbon Generalized System of Preferences (CGSP) plays a pivotal role in transforming household lifestyle, aiming at reducing HCEs. Previous research on the CGSP are limited to analysis its public acceptance, with less emphasis on analysis its mitigating effect on HCEs. Therefore, this study explores the mitigating effect of CGSP on HCEs and discover the underlying mechanism of household lifestyle by using the Double Machine Learning (DML) method. We further analyze the heterogeneous effects on different household income levels, urban and rural areas, and consumption categories. Our benchmark regression analysis demonstrates that CGSP effectively mitigates HCEs. After categorizing household lifestyle into household consumption upgrading (HCU) and household sustainable lifestyle (HSL), we find that the HCU negatively affects the relationship between CGSP and HCEs, whereas HSL enhance the effectiveness of reducing HCEs. The heterogeneity analysis results reveal that CGSP is more effective for households at the lowest, higher and highest income levels and has a stronger impact on carbon emissions for urban households compared to their rural counterparts. Additionally, the CGSP has heterogeneous mitigation effects across consumption categories, with significant impacts on food, residential utilities, facilities, transport and communication, recreation-education-culture, and other services. These findings provide quantitative insights into the implementation of CGSP in China.

Suggested Citation

  • Su, Xiaoying & Zha, Donglan & Zhang, Chaoqun & Zhao, Kuokuo, 2025. "Does household lifestyle impact the decarbonization effect of carbon generalized system of preferences? Evidence from household survey in China," Journal of Asian Economics, Elsevier, vol. 98(C).
    • Handle: RePEc:eee:asieco:v:98:y:2025:i:c:s1049007825000314
    DOI: 10.1016/j.asieco.2025.101907
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    1. Huang, Liqiao & Yoshida, Yoshikuni & Li, Yuan & Cheng, Nan & Xue, Jinjun & Long, Yin, 2024. "Sustainable lifestyle: Quantification and determining factors analysis of household carbon footprints in Japan," Energy Policy, Elsevier, vol. 186(C).
    2. Francesco Fuso Nerini & Tina Fawcett & Yael Parag & Paul Ekins, 2021. "Personal carbon allowances revisited," Nature Sustainability, Nature, vol. 4(12), pages 1025-1031, December.
    3. Wu, Haixia & Ge, Yan & Li, Jianping, 2023. "Uncertainty, time preference and households’ adoption of rooftop photovoltaic technology," Energy, Elsevier, vol. 276(C).
    4. Zhou, Qiuyang, 2024. "Does the digital economy promote the consumption structure upgrading of urban residents? Evidence from Chinese cities," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 543-551.
    5. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    6. Li, Rui & Fang, Debin & Xu, Jiajun, 2024. "Does China's carbon inclusion policy promote household carbon emissions reduction? Theoretical mechanisms and empirical evidence," Energy Economics, Elsevier, vol. 132(C).
    7. Zhao, Xiaoli & Li, Na & Ma, Chunbo, 2012. "Residential energy consumption in urban China: A decomposition analysis," Energy Policy, Elsevier, vol. 41(C), pages 644-653.
    8. Zha, Donglan & Chen, Qian & Wang, Lijun, 2022. "Exploring carbon rebound effects in Chinese households’ consumption: A simulation analysis based on a multi-regional input–output framework," Applied Energy, Elsevier, vol. 313(C).
    9. Helmut Farbmacher & Martin Huber & Lukáš Lafférs & Henrika Langen & Martin Spindler, 2022. "Causal mediation analysis with double machine learning [Mediation analysis via potential outcomes models]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 277-300.
    10. Zha, Donglan & Yang, Guanglei & Wang, Wenzhong & Wang, Qunwei & Zhou, Dequn, 2020. "Appliance energy labels and consumer heterogeneity: A latent class approach based on a discrete choice experiment in China," Energy Economics, Elsevier, vol. 90(C).
    11. Xiao, De & Yu, Fan & Guo, Chenhao, 2023. "The impact of China's pilot carbon ETS on the labor income share: Based on an empirical method of combining PSM with staggered DID," Energy Economics, Elsevier, vol. 124(C).
    12. Diana Ivanova & Konstantin Stadler & Kjartan Steen-Olsen & Richard Wood & Gibran Vita & Arnold Tukker & Edgar G. Hertwich, 2016. "Environmental Impact Assessment of Household Consumption," Journal of Industrial Ecology, Yale University, vol. 20(3), pages 526-536, June.
    13. Zhang, Jin & Shi, Dan & Ma, Lianrui & Wu, Yuan & Liu, Shoulin & Li, Jinkai, 2024. "The role of household energy consumption behavior in environmental policy outcomes —the case of driving restriction policy in zhengzhou," Energy Policy, Elsevier, vol. 188(C).
    14. Bai, Chunyue & Zhan, Jinyan & Wang, Huihui & Yang, Zheng & Liu, Huizi & Liu, Wei & Wang, Chao & Chu, Xi & Teng, Yanmin, 2023. "Heating choices and residential willingness to pay for clean heating: Evidence from a household survey in rural China," Energy Policy, Elsevier, vol. 178(C).
    15. Li, Jiachen & Jiang, Meiru & Li, Ge, 2024. "Does the new energy vehicles subsidy policy decrease the carbon emissions of the urban transport industry? Evidence from Chinese cities in Yangtze River Delta," Energy, Elsevier, vol. 298(C).
    16. Cheng, Shulei & Wang, Kexin & Meng, Fanxin & Liu, Gengyuan & An, Jiafu, 2024. "The unanticipated role of fiscal environmental expenditure in accelerating household carbon emissions: Evidence from China," Energy Policy, Elsevier, vol. 185(C).
    17. Li, Jiajia & Li, Jun & Zhang, Jian, 2024. "Can digitalization facilitate low carbon lifestyle? --Evidence from households’ embedded emissions in China," Technology in Society, Elsevier, vol. 76(C).
    18. Zhang, Yimeng & Wang, Feng & Zhang, Bing, 2023. "The impacts of household structure transitions on household carbon emissions in China," Ecological Economics, Elsevier, vol. 206(C).
    19. Zhang, Yingheng & Li, Haojie & Ren, Gang, 2022. "Quantifying the social impacts of the London Night Tube with a double/debiased machine learning based difference-in-differences approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 288-303.
    20. Tan, Xueping & Wang, Xinyu & Zaidi, Syed Haider Ali, 2019. "What drives public willingness to participate in the voluntary personal carbon-trading scheme? A case study of Guangzhou Pilot, China," Ecological Economics, Elsevier, vol. 165(C), pages 1-1.
    21. Zhifu Mi & Jiali Zheng & Jing Meng & Jiamin Ou & Klaus Hubacek & Zhu Liu & D’Maris Coffman & Nicholas Stern & Sai Liang & Yi-Ming Wei, 2020. "Economic development and converging household carbon footprints in China," Nature Sustainability, Nature, vol. 3(7), pages 529-537, July.
    22. Hu, Debao & Zhai, Chenzhe & Zhao, Sibo, 2023. "Does digital finance promote household consumption upgrading? An analysis based on data from the China family panel studies," Economic Modelling, Elsevier, vol. 125(C).
    23. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey, 2017. "Double/Debiased/Neyman Machine Learning of Treatment Effects," American Economic Review, American Economic Association, vol. 107(5), pages 261-265, May.
    24. Thorsten Beck & Ross Levine & Alexey Levkov, 2010. "Big Bad Banks? The Winners and Losers from Bank Deregulation in the United States," Journal of Finance, American Finance Association, vol. 65(5), pages 1637-1667, October.
    25. Adua, Lazarus, 2022. "Super polluters and carbon emissions: Spotlighting how higher-income and wealthier households disproportionately despoil our atmospheric commons," Energy Policy, Elsevier, vol. 162(C).
    26. Xu, Dandan & Guo, Dongli & Yue, Pengpeng & Li, Mengshi, 2024. "Household green consumption: Does digital inclusion matter?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    27. Chen, G.Q. & Wu, X.D. & Guo, Jinlan & Meng, Jing & Li, Chaohui, 2019. "Global overview for energy use of the world economy: Household-consumption-based accounting based on the world input-output database (WIOD)," Energy Economics, Elsevier, vol. 81(C), pages 835-847.
    28. Li, Jun & Zhang, Dayong & Su, Bin, 2019. "The Impact of Social Awareness and Lifestyles on Household Carbon Emissions in China," Ecological Economics, Elsevier, vol. 160(C), pages 145-155.
    29. Kuai, Peng & Zhang, Xiaoxiao & Zhang, Shuan & Li, Jing, 2022. "Environmental awareness and household energy saving of Chinese residents: Unity of knowing and doing or easier said than done?," Journal of Asian Economics, Elsevier, vol. 82(C).
    30. Pitkänen, Atte & von Wright, Tuuli & Kaseva, Janne & Kahiluoto, Helena, 2022. "Distributional fairness of personal carbon trading," Ecological Economics, Elsevier, vol. 201(C).
    31. Grabs, Janina, 2015. "The rebound effects of switching to vegetarianism. A microeconomic analysis of Swedish consumption behavior," Ecological Economics, Elsevier, vol. 116(C), pages 270-279.
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