IDEAS home Printed from https://ideas.repec.org/a/eee/streco/v60y2022icp496-511.html
   My bibliography  Save this article

An Evaluation of the Efficiency of China’s green investment in the “Belt and Road” countries

Author

Listed:
  • Fan, Qiufang
  • Liu, Jintao
  • Zhang, Tao
  • Liu, Haomin

Abstract

GI (Green Investment) plays an important role in China's building of the Green B&R (Belt and Road). Studying China's GIE (Green Investment Efficiency) not only investigates the effectiveness and progress of the construction of “B&Rs” but also establishes a foundation for China's reasonable investment decisions. In this paper, we first employed Min-DS-U-M (a minimum distance to a strong efficient frontier with an undesirable output model) to evaluate China's GIE in 51 B&R countries from 2009 to 2018 and subsequently analyzed the influence of the domestic investment environment of B&R countries on GIE with SLM (Spatial Lag Model). The study results showed that (1) China's GIE in B&R countries is low, and there is still great potential for investment and cooperation. (2) In 51 B&R countries, there are nine countries whose GISE (Green Investment Scale Efficiency) is invalid and ten countries whose GIPTE (Green Investment Pure Technical Efficiency) is invalid. Moreover, both GISE and GIPTE of 24 countries are invalid. (3) The B&R countries have formed a solid spatial cluster, and the spatial advantage cluster shows a gradual expansionary trend, which indicates that China's GI has improved the spatial agglomeration of B&R countries. (4) On the whole, the domestic investment environment of B&R countries has a negative influence. The restraining effect of industrialization on GIE is far greater than the total facilitation of service industrialization, technological investment and dependence on foreign trade.

Suggested Citation

  • Fan, Qiufang & Liu, Jintao & Zhang, Tao & Liu, Haomin, 2022. "An Evaluation of the Efficiency of China’s green investment in the “Belt and Road” countries," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 496-511.
    • Handle: RePEc:eee:streco:v:60:y:2022:i:c:p:496-511
    DOI: 10.1016/j.strueco.2022.01.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0954349X22000030
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.strueco.2022.01.003?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Ficawoyi Donou-Adonsou & Sokchea Lim, 2018. "On the importance of Chinese investment in Africa," Review of Development Finance Journal, Chartered Institute of Development Finance, vol. 8(1), pages 63-73.
    2. Guolei Chen & Jing Luo & Chunyan Zhang & Liang Jiang & Lingling Tian & Guangping Chen, 2018. "Characteristics and Influencing Factors of Spatial Differentiation of Urban Black and Odorous Waters in China," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    3. Wu, Jie & Li, Mingjun & Zhu, Qingyuan & Zhou, Zhixiang & Liang, Liang, 2019. "Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs," Energy Economics, Elsevier, vol. 78(C), pages 468-480.
    4. Kathrin Lesser & Sebastian Lobe & Christian Walkshäusl, 2014. "Green and socially responsible investing in international markets," Journal of Asset Management, Palgrave Macmillan, vol. 15(5), pages 317-331, October.
    5. Zhao, Xingrong & Zhang, Xi & Shao, Shuai, 2016. "Decoupling CO2 emissions and industrial growth in China over 1993–2013: The role of investment," Energy Economics, Elsevier, vol. 60(C), pages 275-292.
    6. Han, Lei & Han, Botang & Shi, Xunpeng & Su, Bin & Lv, Xin & Lei, Xiao, 2018. "Energy efficiency convergence across countries in the context of China’s Belt and Road initiative," Applied Energy, Elsevier, vol. 213(C), pages 112-122.
    7. An, Simin & Li, Bo & Song, Dongping & Chen, Xue, 2021. "Green credit financing versus trade credit financing in a supply chain with carbon emission limits," European Journal of Operational Research, Elsevier, vol. 292(1), pages 125-142.
    8. Martin, Patrick R. & Moser, Donald V., 2016. "Managers’ green investment disclosures and investors’ reaction," Journal of Accounting and Economics, Elsevier, vol. 61(1), pages 239-254.
    9. Zhu, Qingyuan & Li, Xingchen & Li, Feng & Wu, Jie & Zhou, Dequn, 2020. "Energy and environmental efficiency of China's transportation sectors under the constraints of energy consumption and environmental pollutions," Energy Economics, Elsevier, vol. 89(C).
    10. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    11. Lesser, Kathrin & Rößle, Felix & Walkshäusl, Christian, 2016. "Socially responsible, green, and faith-based investment strategies: Screening activity matters!," Finance Research Letters, Elsevier, vol. 16(C), pages 171-178.
    12. Liu, Zuankuo & Xin, Li, 2019. "Has China's Belt and Road Initiative promoted its green total factor productivity？——Evidence from primary provinces along the route," Energy Policy, Elsevier, vol. 129(C), pages 360-369.
    13. Sebastián Lozano, 2017. "Technical and environmental efficiency of a two-stage production and abatement system," Annals of Operations Research, Springer, vol. 255(1), pages 199-219, August.
    14. Wang, Miao & Feng, Chao, 2021. "The consequences of industrial restructuring, regional balanced development, and market-oriented reform for China's carbon dioxide emissions: A multi-tier meta-frontier DEA-based decomposition analysi," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    15. Li, Yongjun & Lei, Xiyang & Dai, Qianzhi & Liang, Liang, 2015. "Performance evaluation of participating nations at the 2012 London Summer Olympics by a two-stage data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 243(3), pages 964-973.
    16. Fankhauser, Samuel & Kverndokk, Snorre, 1996. "The global warming game -- Simulations of a CO2-reduction agreement," Resource and Energy Economics, Elsevier, vol. 18(1), pages 83-102, March.
    17. Boyd, Gale A. & Pang, Joseph X., 2000. "Estimating the linkage between energy efficiency and productivity," Energy Policy, Elsevier, vol. 28(5), pages 289-296, May.
    18. Fang, Chuandi & Cheng, Jinhua & Zhu, Yongguang & Chen, Jiahao & Peng, Xinjie, 2021. "Green total factor productivity of extractive industries in China: An explanation from technology heterogeneity," Resources Policy, Elsevier, vol. 70(C).
    19. Juan Aparicio & José Ruiz & Inmaculada Sirvent, 2007. "Closest targets and minimum distance to the Pareto-efficient frontier in DEA," Journal of Productivity Analysis, Springer, vol. 28(3), pages 209-218, December.
    20. Liu, Haiyue & Wang, Yile & Jiang, Jie & Wu, Peng, 2020. "How green is the “Belt and Road Initiative”? – Evidence from Chinese OFDI in the energy sector," Energy Policy, Elsevier, vol. 145(C).
    21. Shahbaz, Muhammad & Solarin, Sakiru Adebola & Mahmood, Haider & Arouri, Mohamed, 2013. "Does financial development reduce CO2 emissions in Malaysian economy? A time series analysis," Economic Modelling, Elsevier, vol. 35(C), pages 145-152.
    22. Xia, Fan & Xu, Jintao, 2020. "Green total factor productivity: A re-examination of quality of growth for provinces in China," China Economic Review, Elsevier, vol. 62(C).
    23. Eyraud, Luc & Clements, Benedict & Wane, Abdoul, 2013. "Green investment: Trends and determinants," Energy Policy, Elsevier, vol. 60(C), pages 852-865.
    24. Cui, Qiang & Jin, Zi-yin, 2020. "Airline environmental efficiency measures considering negative data: An application of a modified network Modified Slacks-based measure model," Energy, Elsevier, vol. 207(C).
    25. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    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. Shuangjie Li & Li Li & Liming Wang, 2020. "2030 Target for Energy Efficiency and Emission Reduction in the EU Paper Industry," Energies, MDPI, vol. 14(1), pages 1-17, December.
    2. Meiling Wang & Silu Pang & Ikram Hmani & Ilham Hmani & Cunfang Li & Zhengxia He, 2021. "Towards sustainable development: How does technological innovation drive the increase in green total factor productivity?," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(1), pages 217-227, January.
    3. Chang, Ming-Chung, 2013. "A comment on the calculation of the total-factor energy efficiency (TFEE) index," Energy Policy, Elsevier, vol. 53(C), pages 500-504.
    4. Lv, Chengchao & Song, Jie & Lee, Chien-Chiang, 2022. "Can digital finance narrow the regional disparities in the quality of economic growth? Evidence from China," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 502-521.
    5. Zhou, Anhua & Li, Jun, 2021. "Investigate the impact of market reforms on the improvement of manufacturing energy efficiency under China’s provincial-level data," Energy, Elsevier, vol. 228(C).
    6. Bowen Sun & Haibo Wang & Jaime Ortiz & Jun Huang & Can Zhao & Zelang Wang, 2022. "A Decomposed Data Analysis Approach to Assessing City Sustainable Development Performance: A Network DEA Model with a Slack-Based Measure," Sustainability, MDPI, vol. 14(17), pages 1-23, September.
    7. Qingshan Ma & Yuanmeng Zhang & Kexin Yang & Lingyun He, 2021. "Have China’s Pilot Free Trade Zones Improved Green Total Factor Productivity?," IJERPH, MDPI, vol. 18(21), pages 1-20, November.
    8. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    9. Yan Wu & Cong Hu & Xunpeng Shi, 2021. "Heterogeneous Effects of the Belt and Road Initiative on Energy Efficiency in Participating Countries," Energies, MDPI, vol. 14(18), pages 1-21, September.
    10. Bin Wang & Chenyang Meng & Hongwei Yu, 2023. "The Impact of Economic Policy Uncertainty on Regional Total-Factor Energy Productivity in China," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    11. Yuxin Fang & Hongjun Cao, 2022. "Environmental Decentralization, Heterogeneous Environmental Regulation, and Green Total Factor Productivity—Evidence from China," Sustainability, MDPI, vol. 14(18), pages 1-20, September.
    12. Li Xie & Chunlin Chen & Yihua Yu, 2019. "Dynamic Assessment of Environmental Efficiency in Chinese Industry: A Multiple DEA Model with a Gini Criterion Approach," Sustainability, MDPI, vol. 11(8), pages 1-22, April.
    13. Zhu, Qingyuan & Aparicio, Juan & Li, Feng & Wu, Jie & Kou, Gang, 2022. "Determining closest targets on the extended facet production possibility set in data envelopment analysis: Modeling and computational aspects," European Journal of Operational Research, Elsevier, vol. 296(3), pages 927-939.
    14. Jiang, Lei & Zhou, Haifeng & He, Shixiong, 2021. "Does energy efficiency increase at the expense of output performance: Evidence from manufacturing firms in Jiangsu province, China," Energy, Elsevier, vol. 220(C).
    15. Liu, Liyun & Zhao, Zhenzhi & Zhang, Mingming & Zhou, Dequn, 2022. "Green investment efficiency in the Chinese energy sector: Overinvestment or underinvestment?," Energy Policy, Elsevier, vol. 160(C).
    16. Pan, Xiongfeng & Chu, Junhui & Tian, Mengyuan & Li, Mengna, 2022. "Non-linear effects of outward foreign direct investment on total factor energy efficiency in China," Energy, Elsevier, vol. 239(PD).
    17. Wang, Xipan & Song, Junnian & Duan, Haiyan & Wang, Xian'en, 2021. "Coupling between energy efficiency and industrial structure: An urban agglomeration case," Energy, Elsevier, vol. 234(C).
    18. Tao Xu & Jianxin You & Hui Li & Luning Shao, 2020. "Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review," Energies, MDPI, vol. 13(14), pages 1-20, July.
    19. Wang, Mei & Xu, Mi & Ma, Shaojun, 2021. "The effect of the spatial heterogeneity of human capital structure on regional green total factor productivity," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 427-441.
    20. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "Energy and Environmental Efficiency in Different Chinese Regions," Sustainability, MDPI, vol. 11(4), pages 1-26, February.

    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:streco:v:60:y:2022:i:c:p:496-511. 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/inca/525148 .

    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.