IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v152y2025ics0140988325007893.html

How does household engagement in the public-welfare carbon generalized system of preferences affect household carbon emissions? Evidence from ant forest and household survey data in China

Author

Listed:
  • Chi, Yuanying
  • Wu, Yuxi
  • Zhang, Yanzhao
  • Wang, Zhengzao
  • Zhang, Mengwan
  • Zhang, Xufeng

Abstract

The Carbon Generalized System of Preferences (CGSP) is an innovative mechanism proposed in China to quantify households' energy-saving and carbon-reducing behaviors and provide corresponding incentives. This mechanism is significant for promoting low-carbon consumption and fostering green and sustainable lifestyles. This study examines the influence of household engagement in the Public Welfare-oriented Carbon Generalized System of Preferences (PW-CGSP) on household carbon mitigation. The 2016 version of Ant Forest, an online public welfare project, was adopted as a quasi-natural experiment, and a generalized difference-in-differences model using household data from the 2014–2020 China Family Panel Studies (CFPS) was employed. The findings reveal that, first, participation in Ant Forest significantly curbs the growth of household carbon emissions (HCE). This conclusion remains robust after applying machine learning methods and various robustness checks. Second, the carbon-reduction effects of participation exhibit heterogeneity across space, household characteristics, and consumption structure. Specifically, the effect is stronger in urban than in rural areas and is more pronounced in the eastern and northeastern regions. Moreover, small-scale households experience relatively large reductions. From the perspective of household consumption structure, strong suppressive effects is observed on HCE from household appliances and supplies, and food consumption. Finally, participation in Ant Forest partly reduces HCE by enhancing environmental awareness among household members. The study outlines policy recommendations, including adopting gamification designs to further incentivize user behavior and developing differentiated mechanisms tailored to local conditions.

Suggested Citation

  • Chi, Yuanying & Wu, Yuxi & Zhang, Yanzhao & Wang, Zhengzao & Zhang, Mengwan & Zhang, Xufeng, 2025. "How does household engagement in the public-welfare carbon generalized system of preferences affect household carbon emissions? Evidence from ant forest and household survey data in China," Energy Economics, Elsevier, vol. 152(C).
    • Handle: RePEc:eee:eneeco:v:152:y:2025:i:c:s0140988325007893
    DOI: 10.1016/j.eneco.2025.108962
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988325007893
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2025.108962?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. Nathan Nunn & Nancy Qian, 2011. "The Potato's Contribution to Population and Urbanization: Evidence From A Historical Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(2), pages 593-650.
    3. Tan, Yang & Ying, Xiaoyu & Ge, Jian & Gao, Weijun & Zhang, Li & Wang, Shuai, 2024. "Driving role of perceived psychological factors in households’ low-carbon behaviors: A study based on the Chinese household carbon generalized system of preferences," Energy, Elsevier, vol. 303(C).
    4. 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).
    5. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    6. Wang, Yuanping & Hou, Lingchun & Hu, Lang & Cai, Weiguang & Wang, Lin & Dai, Cuilian & Chen, Juntao, 2023. "How family structure type affects household energy consumption: A heterogeneous study based on Chinese household evidence," Energy, Elsevier, vol. 284(C).
    7. Gordic, Dusan & Nikolic, Jelena & Vukasinovic, Vladimir & Josijevic, Mladen & Aleksic, Aleksandar D., 2023. "Offsetting carbon emissions from household electricity consumption in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    8. Gu, Jiafeng, 2025. "Did supply chain digitization contribute to corporate green energy innovation? The mediating role of asset receivable management and policy spillovers," Energy Economics, Elsevier, vol. 143(C).
    9. Tan, Ying & Li, Xiaoying, 2022. "The impact of internet on entrepreneurship," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 135-142.
    10. 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).
    11. 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).
    12. Massoud Moslehpour & Ka Yin Chau & Lijie Du & Ranfeng Qiu & Chia-Yang Lin & Batzaya Batbayar, 2023. "Predictors of green purchase intention toward eco-innovation and green products: Evidence from Taiwan," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 36(2), pages 2121934-212, July.
    13. 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).
    14. 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).
    15. Ding, Qun & Cai, Wenjia & Wang, Can & Sanwal, Mukul, 2017. "The relationships between household consumption activities and energy consumption in china— An input-output analysis from the lifestyle perspective," Applied Energy, Elsevier, vol. 207(C), pages 520-532.
    16. Yang, Jui-Chung & Chuang, Hui-Ching & Kuan, Chung-Ming, 2020. "Double machine learning with gradient boosting and its application to the Big N audit quality effect," Journal of Econometrics, Elsevier, vol. 216(1), pages 268-283.
    17. Zafar, Abaid Ullah & Shahzad, Mohsin & Shahzad, Khuram & Appolloni, Andrea & Elgammal, Islam, 2024. "Gamification and sustainable development: Role of gamified learning in sustainable purchasing," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    18. Pelucha, Martin & Shemetev, Alexander, 2025. "Unravelling the link between land use policy and digital infrastructure: Insights from Czech rural communities," Land Use Policy, Elsevier, vol. 150(C).
    19. 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).
    20. Lv, Xiaoting & Wu, Ziang, 2024. "The green effect of digital transformation: The impact of digital transformation in fiscal and taxation on regional green development," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 787-800.
    21. Richard H. Thaler, 2008. "Mental Accounting and Consumer Choice," Marketing Science, INFORMS, vol. 27(1), pages 15-25, 01-02.
    22. Yanmei Tang & Shuangzhou Chen & Zongjin Yuan, 2020. "The effects of hedonic, gain, and normative motives on sustainable consumption: Multiple mediating evidence from China," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 741-750, July.
    23. 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.
    24. Meng, Weilu & Yuan, Gecheng & Sun, Yongping, 2023. "Expansion of social networks and household carbon emissions: Evidence from household survey in China," Energy Policy, Elsevier, vol. 174(C).
    25. Du, Zhili & Xu, Jie & Lin, Boqiang, 2024. "What does the digital economy bring to household carbon emissions? – From the perspective of energy intensity," Applied Energy, Elsevier, vol. 370(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Du, Zhili & Xu, Jie & Lin, Boqiang, 2024. "What does the digital economy bring to household carbon emissions? – From the perspective of energy intensity," Applied Energy, Elsevier, vol. 370(C).
    3. Gao, Xue & Chen, Xuan & Liu, Lan-Cui, 2024. "Exploring the determinants of the evolution of urban and rural household carbon footprints inequality in China," Energy Policy, Elsevier, vol. 185(C).
    4. Weng, Shimei & Chen, Jianbao & Tao, Weiliang & Song, Malin, 2025. "Does incentive-based voluntary emission reduction mechanism improve urban carbon unlocking efficiency? A quasi-natural experiment on carbon inclusion policy," Energy, Elsevier, vol. 318(C).
    5. Wang, Yao & Wu, Xuenan & Lin, Boqiang, 2025. "Empowering green households: How does digital finance influence household carbon footprints?," Research in International Business and Finance, Elsevier, vol. 76(C).
    6. Jun Hwan Kim & Hyun Cheol Lee, 2019. "Understanding the Repurchase Intention of Premium Economy Passengers Using an Extended Theory of Planned Behavior," Sustainability, MDPI, vol. 11(11), pages 1-19, June.
    7. Shahzad, Khuram & Ashfaq, Muhammad & Zafar, Abaid Ullah & Basahel, Sarah, 2024. "Is the future of the metaverse bleak or bright? Role of realism, facilitators, and inhibitors in metaverse adoption," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    8. Yanjie Li & Guanfeng Yan, 2025. "The Heterogeneity in the Relationships Between Psychological Drivers and Construction and Demolition Waste Management Intention and Behaviors Among Tunnel Construction Managers: Insights from Personality Profiles," Sustainability, MDPI, vol. 17(5), pages 1-24, March.
    9. Michael Hallsworth, 2023. "A manifesto for applying behavioural science," Nature Human Behaviour, Nature, vol. 7(3), pages 310-322, March.
    10. Meng, Weilu & Yuan, Gecheng & Sun, Yongping, 2023. "Expansion of social networks and household carbon emissions: Evidence from household survey in China," Energy Policy, Elsevier, vol. 174(C).
    11. Cem Keskin & M. Pınar Mengüç, 2018. "On Occupant Behavior and Innovation Studies Towards High Performance Buildings: A Transdisciplinary Approach," Sustainability, MDPI, vol. 10(10), pages 1-33, October.
    12. Mashaal A. M. Saif & Nazimah Hussin & Maizaitulaidawati Md Husin & Ayed Alwadain & Ayon Chakraborty, 2022. "Determinants of the Intention to Adopt Digital-Only Banks in Malaysia: The Extension of Environmental Concern," Sustainability, MDPI, vol. 14(17), pages 1-32, September.
    13. An, Na & Huang, Chenyu & Shen, Yanting & Wang, Jinyu & Yu, Zhongqi & Fu, Jiayan & Liu, Xiao & Yao, Jiawei, 2024. "Efficient data-driven prediction of household carbon footprint in China with limited features," Energy Policy, Elsevier, vol. 185(C).
    14. Sunardi Sunardi & Theresia Woro Damayanti & Supramono Supramono, 2020. "Men, Money and Household Economy: How Behavioral Approach Explain It," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 23(77), pages 50-63, September.
    15. Santarius, Tilman & Soland, Martin, 2018. "How Technological Efficiency Improvements Change Consumer Preferences: Towards a Psychological Theory of Rebound Effects," Ecological Economics, Elsevier, vol. 146(C), pages 414-424.
    16. Flörchinger, Daniela & Frondel, Manuel & Sommer, Stephan & Andor, Mark A., 2025. "Pro-environmental behavior and environmentalist movements: Evidence from the identification with Fridays for Future," Ecological Economics, Elsevier, vol. 235(C).
    17. Baek, Tae Hyun & Yoon, Sukki, 2020. "Looking forward, looking back: The impact of goal progress and time urgency on consumer responses to mobile reward apps," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    18. Anuj Kumar & Amit Mehra & Subodha Kumar, 2019. "Why Do Stores Drive Online Sales? Evidence of Underlying Mechanisms from a Multichannel Retailer," Service Science, INFORMS, vol. 30(1), pages 319-338, March.
    19. Chen, Ching-Fu & Liu, Hsun-Ting, 2025. "Paying as you fly: Investigating air passengers’ preferences for voluntary carbon offset in Taiwan via the integrated choice and latent variable (ICLV) model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 201(C).
    20. Changyuan Li & Xin Yang & Hong Wei & Zheneng Hu & Zhuoya Zhang, 2025. "Research on the Influencing Factors of College Students’ Willingness-to-Pay for Carbon Offsets in the Context of Climate Change," Sustainability, MDPI, vol. 17(6), pages 1-18, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:152:y:2025:i:c:s0140988325007893. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.