IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p11919-d921283.html
   My bibliography  Save this article

Analysis of Green Credit and the Ecological Welfare Performance Based on Empirical Models and ARIMA(2,3,2): Taking China as an Example

Author

Listed:
  • Haoyang Lu

    (College of Bangor, Central South University of Forestry Technology, Changsha 410004, China)

  • Jing Tong

    (College of Bangor, Central South University of Forestry Technology, Changsha 410004, China)

  • Yajiao Tang

    (College of Economics, Central South University of Forestry and Technology, Changsha 410004, China)

Abstract

We study the relationship between green credit and ecological welfare performance, green credit’s mechanism, and future trends of ecological welfare performance in China. We aim to determine whether the green credit policy has a positive or negative effect on ecological welfare performance and to give suggestions about green credit for emerging markets, with China as an example. These problems are evaluated with two empirical models by using quadratic and interaction terms, as well as a time series model, ARIMA(2,3,2). The results show that the relationship between green credit and ecological welfare performance is an inverted U shape, and ecological welfare performance peaks when loans approach 2934.2 billion yuan, which equals 441.7446 billion dollars, corresponding to loans between 2015 and 2016. In addition, national income and ecological footprint have a suppressive effect on the impact of green credit on ecological welfare performance, and lifespan can positively affect the mechanism. Moreover, the result of ARIMA(2,3,2) corresponds to previous results and indicates that the ecological welfare performance will fluctuate within a range if green credits continue to be issued.

Suggested Citation

  • Haoyang Lu & Jing Tong & Yajiao Tang, 2022. "Analysis of Green Credit and the Ecological Welfare Performance Based on Empirical Models and ARIMA(2,3,2): Taking China as an Example," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:11919-:d:921283
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/11919/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/19/11919/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Min Hong & Zhenghui Li & Benjamin Drakeford, 2021. "Do the Green Credit Guidelines Affect Corporate Green Technology Innovation? Empirical Research from China," IJERPH, MDPI, vol. 18(4), pages 1-21, February.
    2. Guo, Shu & Zhang, ZhongXiang, 2023. "Green credit policy and total factor productivity: Evidence from Chinese listed companies," Energy Economics, Elsevier, vol. 128(C).
    3. Tan, Xiujie & Yan, Yaxue & Dong, Yuyang, 2022. "Peer effect in green credit induced green innovation: An empirical study from China's Green Credit Guidelines," Resources Policy, Elsevier, vol. 76(C).
    4. George Lăzăroiu & Luminița Ionescu & Cristian Uță & Iulian Hurloiu & Mihai Andronie & Irina Dijmărescu, 2020. "Environmentally Responsible Behavior and Sustainability Policy Adoption in Green Public Procurement," Sustainability, MDPI, vol. 12(5), pages 1-12, March.
    5. Daly, Herman E, 1974. "The Economics of the Steady State," American Economic Review, American Economic Association, vol. 64(2), pages 15-21, May.
    6. Yu Song & Dong Mei, 2022. "Sustainable development of China's regions from the perspective of ecological welfare performance: analysis based on GM(1,1) and the malmquist index," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 1086-1115, January.
    7. Xiao Yan Zhou & Ben Caldecott & Andreas G. F. Hoepner & Yao Wang, 2022. "Bank green lending and credit risk: an empirical analysis of China's Green Credit Policy," Business Strategy and the Environment, Wiley Blackwell, vol. 31(4), pages 1623-1640, May.
    8. Wen, Huwei & Lee, Chien-Chiang & Zhou, Fengxiu, 2021. "Green credit policy, credit allocation efficiency and upgrade of energy-intensive enterprises," Energy Economics, Elsevier, vol. 94(C).
    9. George Lăzăroiu & Luminița Ionescu & Mihai Andronie & Irina Dijmărescu, 2020. "Sustainability Management and Performance in the Urban Corporate Economy: A Systematic Literature Review," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    10. Yanli Wang & Xiaodong Lei & Dongxiao Zhao & Ruyin Long & Meifen Wu, 2021. "The Dual Impacts of Green Credit on Economy and Environment: Evidence from China," Sustainability, MDPI, vol. 13(8), pages 1-13, April.
    11. Lan Yao & Zhenning Yu & Mengya Wu & Jiachen Ning & Tiangui Lv, 2020. "The Spatiotemporal Evolution and Trend Prediction of Ecological Wellbeing Performance in China," Land, MDPI, vol. 10(1), pages 1-17, December.
    12. Lindong Ma & Yuanxiao Hong & Xihui Chen, 2022. "Can Green Economy and Ecological Welfare Achieve Synergistic Development? The Perspective of the “Two Mountains” Theory," IJERPH, MDPI, vol. 19(11), pages 1-24, May.
    13. Undp, 1990. "HDR 1990 - Concept and Measurement of Human Development," Human Development Report (1990 to present), Human Development Report Office (HDRO), United Nations Development Programme (UNDP), number hdr1990, September.
    14. Jing Bian & Feng Lan & Yulin Zhou & Zhenzhen Peng & Mingfang Dong, 2022. "Spatial and Temporal Evolution and Driving Factors of Urban Ecological Well-Being Performance in China," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
    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. Jie Yang & Zhigang Li, 2024. "Improving Urban Ecological Welfare Performance: An ST-LMDI Approach to the Yangtze River Economic Belt," Land, MDPI, vol. 13(8), pages 1-21, August.

    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. Ling Bai & Tianran Guo & Wei Xu & Kang Luo, 2022. "The Spatial Differentiation and Driving Forces of Ecological Welfare Performance in the Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
    2. Chuansheng Wu & Yuyue Li & Lingling Qi, 2022. "Assessing the Impact of Green Transformation on Ecological Well-Being Performance: A Case Study of 78 Cities in Western China," IJERPH, MDPI, vol. 19(18), pages 1-21, September.
    3. Yuanyuan Zhu & Rui Zhang & Jiaxing Cui, 2022. "Spatial Differentiation and Influencing Factors in the Ecological Well-Being Performance of Urban Agglomerations in the Middle Reaches of the Yangtze River: A Hierarchical Perspective," IJERPH, MDPI, vol. 19(19), pages 1-22, October.
    4. Can Zhang & Jixia Li & Tengfei Liu & Mengzhi Xu & Huachun Wang & Xu Li, 2022. "The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance," IJERPH, MDPI, vol. 19(19), pages 1-27, October.
    5. Su, Chi-Wei & Li, Wenhao & Umar, Muhammad & Lobonţ, Oana-Ramona, 2022. "Can green credit reduce the emissions of pollutants?," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 205-219.
    6. Mo Du & Ruirui Zhang & Shanglei Chai & Qiang Li & Ruixuan Sun & Wenjun Chu, 2022. "Can Green Finance Policies Stimulate Technological Innovation and Financial Performance? Evidence from Chinese Listed Green Enterprises," Sustainability, MDPI, vol. 14(15), pages 1-28, July.
    7. Wang, Mei Ling, 2023. "Effects of the green finance policy on the green innovation efficiency of the manufacturing industry: A difference-in-difference model," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    8. Lee, Chien-Chiang & Wang, Fuhao & Lou, Runchi & Wang, Keying, 2023. "How does green finance drive the decarbonization of the economy? Empirical evidence from China," Renewable Energy, Elsevier, vol. 204(C), pages 671-684.
    9. Ningyi Liu & Yongyu Wang, 2022. "Urban Agglomeration Ecological Welfare Performance and Spatial Convergence Research in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-18, November.
    10. Zhicheng Lai & Lei Li & Zhuomin Tao & Tao Li & Xiaoting Shi & Jialing Li & Xin Li, 2023. "Spatio-Temporal Evolution and Influencing Factors of Ecological Well-Being Performance from the Perspective of Strong Sustainability: A Case Study of the Three Gorges Reservoir Area, China," IJERPH, MDPI, vol. 20(3), pages 1-25, January.
    11. Yu Zhang & Xi Cai & Yanying Mao & Liudan Jiao & Liu Wu, 2023. "What Is the State of Development of Eco-Wellbeing Performance in China? An Analysis from a Three-Stage Network Perspective," Land, MDPI, vol. 12(8), pages 1-18, July.
    12. Tan, Xiujie & Xiao, Ziwei & Liu, Yishuang & Taghizadeh-Hesary, Farhad & Wang, Banban & Dong, Hanmin, 2022. "The effect of green credit policy on energy efficiency: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    13. Ge, Yongbo & Zhu, Yuexiao, 2022. "Boosting green recovery: Green credit policy in heavily polluted industries and stock price crash risk," Resources Policy, Elsevier, vol. 79(C).
    14. Ma, Yanbai & Lu, Ling & Cui, Jingbo & Shi, Xunpeng, 2024. "Can green credit policy stimulate firms’ green investments?," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 123-137.
    15. Xu, Aiting & Zhu, Yuhan & Wang, Wenpu, 2023. "Micro green technology innovation effects of green finance pilot policy—From the perspectives of action points and green value," Journal of Business Research, Elsevier, vol. 159(C).
    16. Wang, Xiaoyin & Gao, Cuiyun, 2024. "Does green finance policy help to improve carbon reduction welfare performance? Evidence from China," Energy Economics, Elsevier, vol. 132(C).
    17. Xijia Huang & Yiting Guo & Yuming Lin & Liping Liu & Kai Yan, 2022. "Green Loans and Green Innovations: Evidence from China’s Equator Principles Banks," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    18. Zheng, Shuxia & Zhang, Xiaoming & Wang, Hu, 2023. "Green credit policy and the stock price synchronicity of heavily polluting enterprises," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 251-264.
    19. Dandong Ge & Yanyan Zheng & Shenning Zhang & Jiayi Fu & Fei Su, 2022. "Spatio-Temporal Pattern and Influence Mechanism of Rural Human Settlements System Resilience: Case from China," Sustainability, MDPI, vol. 14(21), pages 1-24, November.
    20. Wu, Sheng & Zhou, Xiaoyong, 2024. "A theoretical framework for modeling dual-track granting orientation in green credit policy," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 249-268.

    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:jsusta:v:14:y:2022:i:19:p:11919-:d:921283. 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.