IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i19p3723-d273116.html
   My bibliography  Save this article

The Impact of Economy on Carbon Emissions: An Empirical Study Based on the Synergistic Effect of Gender Factors

Author

Listed:
  • Shiran Li

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China
    Hubei Institutes of Soft Science on Regional Innovation Capacity Monitoring and Analysis, Wuhan 430074, China)

  • Hongbing Deng

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China
    Hubei Institutes of Soft Science on Regional Innovation Capacity Monitoring and Analysis, Wuhan 430074, China)

  • Kangkang Zhang

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China)

Abstract

The study of carbon emissions is of great significance for environmental change and economic development. Gender factors is an important perspective to examine the path of carbon emissions. Based on the panel data of 30 provinces in China from 2005 to 2016, this paper selects the optimal spatial measurement model structure by using the Bayesian posterior probability model structure selection method, and studies the impact of economy on carbon emissions and the influence mechanism of gender-based “synergy effect” on carbon emissions from the National level and regional levels. The research shows that the increase of economic promotes the increase of carbon emission in this region, but it has a restraining effect on the carbon emission in the surrounding areas. Moreover, gender factors have a significant positive effect on the region at the National level and the Eastern and Northeastern regions, but not significantly in other ones, and have a significant negative impact on carbon emissions in surrounding areas. Overall, the influence intensity of economy on carbon emission increases with the increase of gender in the National level and the Eastern and Northeastern, while the influence intensity of economy of peripheral regions on carbon emission in Central Region decreases with the increase of gender factors in peripheral regions.

Suggested Citation

  • Shiran Li & Hongbing Deng & Kangkang Zhang, 2019. "The Impact of Economy on Carbon Emissions: An Empirical Study Based on the Synergistic Effect of Gender Factors," IJERPH, MDPI, vol. 16(19), pages 1-16, October.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:19:p:3723-:d:273116
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/19/3723/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/19/3723/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. M Ensar Yesilyurt & J Paul Elhorst, 2017. "Impacts of neighboring countries on military expenditures," Journal of Peace Research, Peace Research Institute Oslo, vol. 54(6), pages 777-790, November.
    2. Olivier Parent & James Lesage, 2005. "Bayesian Model Averaging for Spatial Econometric Models," Post-Print hal-00375489, HAL.
    3. Wang, Zhaohua & Yin, Fangchao & Zhang, Yixiang & Zhang, Xian, 2012. "An empirical research on the influencing factors of regional CO2 emissions: Evidence from Beijing city, China," Applied Energy, Elsevier, vol. 100(C), pages 277-284.
    4. Kaika, Dimitra & Zervas, Efthimios, 2013. "The environmental Kuznets curve (EKC) theory. Part B: Critical issues," Energy Policy, Elsevier, vol. 62(C), pages 1403-1411.
    5. Jianjun Wang & Li Li & Fan Zhang & Qiannan Xu, 2014. "Carbon Emissions Abatement Cost in China: Provincial Panel Data Analysis," Sustainability, MDPI, vol. 6(5), pages 1-17, May.
    6. Vicente Rios & Pedro Pascual & Fermín Cabases, 2017. "What drives local government spending in Spain? A dynamic spatial panel approach," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(2-3), pages 230-250, July.
    7. Wang, Ping & Wu, Wanshui & Zhu, Bangzhu & Wei, Yiming, 2013. "Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China," Applied Energy, Elsevier, vol. 106(C), pages 65-71.
    8. Nathan J. Cook & Tara Grillos & Krister P. Andersson, 2019. "Gender quotas increase the equality and effectiveness of climate policy interventions," Nature Climate Change, Nature, vol. 9(4), pages 330-334, April.
    9. Yabe, Nobuko, 2004. "An analysis of CO2 emissions of Japanese industries during the period between 1985 and 1995," Energy Policy, Elsevier, vol. 32(5), pages 595-610, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiajia Li & Yucong Liu & Houjian Li & Abbas Ali Chandio, 2021. "Heterogeneous Driving Factors of Carbon Emissions Embedded in China’s Export: An Application of the LASSO Model," IJERPH, MDPI, vol. 18(19), pages 1-18, October.
    2. Fenghua Wen & Zhanlin Sun & Yu Luo, 2023. "Population Structure and Local Carbon Emission Reduction: Evidence from Guangdong, China," Sustainability, MDPI, vol. 15(5), pages 1-27, February.

    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. Shi, Changfeng & Zhi, Jiaqi & Yao, Xiao & Zhang, Hong & Yu, Yue & Zeng, Qingshun & Li, Luji & Zhang, Yuxi, 2023. "How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning," Energy, Elsevier, vol. 269(C).
    2. Ling Xiong & Shaozhou Qi, 2018. "Financial Development And Carbon Emissions In Chinese Provinces: A Spatial Panel Data Analysis," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(02), pages 447-464, March.
    3. Jinzhao Song & Qing Feng & Xiaoping Wang & Hanliang Fu & Wei Jiang & Baiyu Chen, 2018. "Spatial Association and Effect Evaluation of CO 2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis," Sustainability, MDPI, vol. 11(1), pages 1-19, December.
    4. Dong Jichang & He Jing & Li Xiuting & Mou Xindi & Dong Zhi, 2020. "The Effect of Industrial Structure Change on Carbon Dioxide Emissions: A Cross-Country Panel Analysis," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 1-16, February.
    5. Wang, Yuan & Zhang, Xiang & Kubota, Jumpei & Zhu, Xiaodong & Lu, Genfa, 2015. "A semi-parametric panel data analysis on the urbanization-carbon emissions nexus for OECD countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 704-709.
    6. Shanshan Wang & Tianhao Zhao & Haitao Zheng & Jie Hu, 2017. "The STIRPAT Analysis on Carbon Emission in Chinese Cities: An Asymmetric Laplace Distribution Mixture Model," Sustainability, MDPI, vol. 9(12), pages 1-13, December.
    7. Wang, Wei-Zheng & Liu, Lan-Cui & Liao, Hua & Wei, Yi-Ming, 2021. "Impacts of urbanization on carbon emissions: An empirical analysis from OECD countries," Energy Policy, Elsevier, vol. 151(C).
    8. Yin, Jianhua & Zheng, Mingzheng & Chen, Jian, 2015. "The effects of environmental regulation and technical progress on CO2 Kuznets curve: An evidence from China," Energy Policy, Elsevier, vol. 77(C), pages 97-108.
    9. Jiancheng Qin & Hui Tao & Minjin Zhan & Qamar Munir & Karthikeyan Brindha & Guijin Mu, 2019. "Scenario Analysis of Carbon Emissions in the Energy Base, Xinjiang Autonomous Region, China," Sustainability, MDPI, vol. 11(15), pages 1-18, August.
    10. Xie, Rui & Fang, Jiayu & Liu, Cenjie, 2017. "The effects of transportation infrastructure on urban carbon emissions," Applied Energy, Elsevier, vol. 196(C), pages 199-207.
    11. Shuai, Chenyang & Shen, Liyin & Jiao, Liudan & Wu, Ya & Tan, Yongtao, 2017. "Identifying key impact factors on carbon emission: Evidences from panel and time-series data of 125 countries from 1990 to 2011," Applied Energy, Elsevier, vol. 187(C), pages 310-325.
    12. Zhang, Chuanguo & Zhao, Wei, 2014. "Panel estimation for income inequality and CO2 emissions: A regional analysis in China," Applied Energy, Elsevier, vol. 136(C), pages 382-392.
    13. Wang, Shaojian & Wang, Jieyu & Fang, Chuanglin & Feng, Kuishuang, 2019. "Inequalities in carbon intensity in China: A multi-scalar and multi-mechanism analysis," Applied Energy, Elsevier, vol. 254(C).
    14. Haitao Zheng & Jie Hu & Rong Guan & Shanshan Wang, 2016. "Examining Determinants of CO 2 Emissions in 73 Cities in China," Sustainability, MDPI, vol. 8(12), pages 1-17, December.
    15. Fang, Chuanglin & Wang, Shaojian & Li, Guangdong, 2015. "Changing urban forms and carbon dioxide emissions in China: A case study of 30 provincial capital cities," Applied Energy, Elsevier, vol. 158(C), pages 519-531.
    16. Vélez-Henao, Johan-Andrés & Font Vivanco, David & Hernández-Riveros, Jesús-Antonio, 2019. "Technological change and the rebound effect in the STIRPAT model: A critical view," Energy Policy, Elsevier, vol. 129(C), pages 1372-1381.
    17. Wang, Shaojian & Shi, Chenyi & Fang, Chuanglin & Feng, Kuishuang, 2019. "Examining the spatial variations of determinants of energy-related CO2 emissions in China at the city level using Geographically Weighted Regression Model," Applied Energy, Elsevier, vol. 235(C), pages 95-105.
    18. Bo Li & Xuejing Liu & Zhenhong Li, 2015. "Using the STIRPAT model to explore the factors driving regional CO 2 emissions: a case of Tianjin, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 76(3), pages 1667-1685, April.
    19. Wang, Shaojian & Zeng, Jingyuan & Liu, Xiaoping, 2019. "Examining the multiple impacts of technological progress on CO2 emissions in China: A panel quantile regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 140-150.
    20. Wang, Shaojian & Fang, Chuanglin & Guan, Xingliang & Pang, Bo & Ma, Haitao, 2014. "Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces," Applied Energy, Elsevier, vol. 136(C), pages 738-749.

    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:gam:jijerp:v:16:y:2019:i:19:p:3723-:d:273116. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.