IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i18p11155-d908138.html
   My bibliography  Save this article

Analysis of the Efficiency of Forest Carbon Sinks and Its Influencing Factors—Evidence from China

Author

Listed:
  • Junmin Wei

    (College of Economics and Management, Zhejiang A&F University, Hangzhou 311300, China)

  • Manhong Shen

    (College of Economics and Management, Zhejiang A&F University, Hangzhou 311300, China
    Institute of Ecological Civilization, Zhejiang A&F University, Hangzhou 311300, China
    Research Academy for Rural Revitalization of Zhejiang Province, Zhejiang A&F University, Hangzhou 311300, China)

Abstract

The study of the input–output efficiency and influencing factors of forest carbon sinks is beneficial for the realization of the rational allocation of forest carbon sink resources. Based on the DEA-SBM model, the efficiency of forest carbon sinks is measured and analyzed in 30 provinces (cities) of China from 2005 to 2018; the influencing factors of forest carbon sink efficiency are constructed from the three perspectives of pressure subsystem, state subsystem, and response subsystem with the help of the PSR model and regression analysis is conducted using the FGLS model so that the results of the study can provide a basis for formulating a regionally differentiated forest carbon sink system. The empirical results show that the average annual forest carbon sink efficiency in China is only 0.29, and there is much room for improvement. The level of urbanization, the degree of natural damage to forests, precipitation, and the proportion of financial support for forestry are positively correlated with forest carbon sink efficiency, while temperature is negatively correlated with forest sink efficiency. Additionally, different influencing factors have regional heterogeneity on forest carbon sink efficiency. Based on the above findings, we propose the following policy recommendations: formulate forest carbon sink strategies according to local conditions, adjust and optimize the forestry industry structure at the right time, minimize the intervention in forest ecosystems, improve the supervision mechanism of special forestry funds, improve the level of forestry human capital, and accelerate the transformation of scientific and technological achievements.

Suggested Citation

  • Junmin Wei & Manhong Shen, 2022. "Analysis of the Efficiency of Forest Carbon Sinks and Its Influencing Factors—Evidence from China," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11155-:d:908138
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/18/11155/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/18/11155/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Daigneault, Adam & Favero, Alice, 2021. "Global forest management, carbon sequestration and bioenergy supply under alternative shared socioeconomic pathways," Land Use Policy, Elsevier, vol. 103(C).
    2. Zhang, Kerong & Song, Conghe & Zhang, Yulong & Zhang, Quanfa, 2017. "Natural disasters and economic development drive forest dynamics and transition in China," Forest Policy and Economics, Elsevier, vol. 76(C), pages 56-64.
    3. R. A. Houghton, 2002. "Magnitude, distribution and causes of terrestrial carbon sinks and some implications for policy," Climate Policy, Taylor & Francis Journals, vol. 2(1), pages 71-88, March.
    4. Johnston, Craig & Buongiorno, Joseph & Nepal, Prakash & Prestemon, Jeff, 2019. "From Source to Sink: Past Changes and Model Projections of Carbon Sequestration in the Global Forest Sector," Journal of Forest Economics, now publishers, vol. 34(1-2), pages 47-72, August.
    5. 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)

    Citations

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


    Cited by:

    1. Ke Zhang & Jing Qian & Zhenhua Zhang & Shijiao Fang, 2023. "The Impact of Carbon Trading Pilot Policy on Carbon Neutrality: Empirical Evidence from Chinese Cities," IJERPH, MDPI, vol. 20(5), pages 1-23, March.
    2. Wu Yang & Zhang Min & Mingxing Yang & Jun Yan, 2022. "Exploration of the Implementation of Carbon Neutralization in the Field of Natural Resources under the Background of Sustainable Development—An Overview," IJERPH, MDPI, vol. 19(21), pages 1-28, October.
    3. Yue Jiang & Yufang Wang & Rui Wang, 2022. "Coupling and Coordination Relationship between Economic and Ecologic-Environmental Developments in China’s Key State-Owned Forest Areas," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
    4. Hongyi Liu & Tianyu He, 2023. "Sustainable Management of Land Resources: The Case of China’s Forestry Carbon Sink Mechanism," Land, MDPI, vol. 12(6), pages 1-18, June.

    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. Hongge Zhu & Yingli Cai & Hong Lin & Yuchen Tian, 2022. "Impacts of Cross-Sectoral Climate Policy on Forest Carbon Sinks and Their Spatial Spillover: Evidence from Chinese Provincial Panel Data," IJERPH, MDPI, vol. 19(21), pages 1-21, November.
    2. Baker, Justin S. & Van Houtven, George & Phelan, Jennifer & Latta, Gregory & Clark, Christopher M. & Austin, Kemen G. & Sodiya, Olakunle E. & Ohrel, Sara B. & Buckley, John & Gentile, Lauren E. & Mart, 2023. "Projecting U.S. forest management, market, and carbon sequestration responses to a high-impact climate scenario," Forest Policy and Economics, Elsevier, vol. 147(C).
    3. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    4. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, April.
    5. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    6. Chen, Ya & Pan, Yongbin & Liu, Haoxiang & Wu, Huaqing & Deng, Guangwei, 2023. "Efficiency analysis of Chinese universities with shared inputs: An aggregated two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    7. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2020. "Plant capacity notions in a non-parametric framework: a brief review and new graph or non-oriented plant capacities," Annals of Operations Research, Springer, vol. 288(2), pages 837-860, May.
    8. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    9. Juan Aparicio & Jesus T. Pastor & Jose L. Sainz-Pardo & Fernando Vidal, 2020. "Estimating and decomposing overall inefficiency by determining the least distance to the strongly efficient frontier in data envelopment analysis," Operational Research, Springer, vol. 20(2), pages 747-770, June.
    10. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.
    11. Atris, Amani Mohammed & Goto, Mika, 2019. "Vertical structure and efficiency assessment of the US oil and gas companies," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    12. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    13. Mohammad Nourani & Qian Long Kweh & Evelyn Shyamala Devadason & V.G.R. Chandran, 2020. "A decomposition analysis of managerial efficiency for the insurance companies: A data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 885-901, September.
    14. Honma, Satoshi, 2012. "Environmental and economic efficiencies in the Asia-Pacific region," MPRA Paper 43361, University Library of Munich, Germany.
    15. Bao Jiang & Enxin Chi & Jian Li, 2022. "Uncertain Data Envelopment Analysis for Cross Efficiency Evaluation with Imprecise Data," Mathematics, MDPI, vol. 10(13), pages 1-9, June.
    16. Jia Li & Yahong Zheng & Bing Liu & Yanyi Chen & Zhihang Zhong & Chenyu Dong & Chaoqun Wang, 2024. "The Synergistic Relationship between Low-Carbon Development of Road Freight Transport and Its Economic Efficiency—A Case Study of Wuhan, China," Sustainability, MDPI, vol. 16(7), pages 1-22, March.
    17. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    18. Eder, Andreas, 2024. "The effect of land fragmentation on risk and technical efficiency of crop farms," FORLand Working Papers 31 (2024), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    19. Zhuang Miao & Tomas Baležentis & Zhihua Tian & Shuai Shao & Yong Geng & Rui Wu, 2019. "Environmental Performance and Regulation Effect of China’s Atmospheric Pollutant Emissions: Evidence from “Three Regions and Ten Urban Agglomerations”," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(1), pages 211-242, September.
    20. Yu-Chuan Chen & Yung-Ho Chiu & Tzu-Han Chang & Tai-Yu Lin, 2023. "Sustainable Development, Government Efficiency, and People’s Happiness," Journal of Happiness Studies, Springer, vol. 24(4), pages 1549-1578, April.

    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:18:p:11155-:d:908138. 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.