IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i15p6392-d1443161.html
   My bibliography  Save this article

Land Management Scale and Net Carbon Effect of Farming in China: Spatial Spillover Effects and Threshold Characteristics

Author

Listed:
  • Wenjin Wu

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China
    These authors contributed equally to this work. Both are considered as the co-first authors.)

  • Qianlei Yu

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China
    These authors contributed equally to this work. Both are considered as the co-first authors.)

  • Yaping Chen

    (College of Forestry, Northeast Forestry University, Harbin 150040, China)

  • Jun Guan

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Yule Gu

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Anqi Guo

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Hao Wang

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China)

Abstract

The net carbon effect of farming is crucial for climate change mitigation, yet there is insufficient research on the impact of land management scale on it in China. This study aims to explore the magnitude and role of land management scale on the net carbon effect of farming at the spatial level, including threshold characteristics. Unlike previous studies focused on the domestic agricultural economy, this study employs ecological findings to calculate carbon sinks and certain carbon emissions. The carbon-balance ratio is used to characterise the net carbon effect of farming. The spatial Durbin model and threshold regression model were utilised with a sample of 30 provincial-level regions in China from 2004 to 2019. The results indicate that national farming generally exhibits a net sink effect, with significant interannual fluctuations. After applying robust standard errors, the expansion of the land management scale significantly increases sinks and reduces emissions, and it has a positive spatial spillover effect on the carbon-balance ratio, demonstrating significant spatial heterogeneity. Furthermore, as the land management scale expands, the influence of rural residents’ income and education level on the carbon-balance ratio changes direction, showing significant non-linear relationship characteristics.

Suggested Citation

  • Wenjin Wu & Qianlei Yu & Yaping Chen & Jun Guan & Yule Gu & Anqi Guo & Hao Wang, 2024. "Land Management Scale and Net Carbon Effect of Farming in China: Spatial Spillover Effects and Threshold Characteristics," Sustainability, MDPI, vol. 16(15), pages 1-22, July.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6392-:d:1443161
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/15/6392/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/15/6392/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tasso Adamopoulos & Diego Restuccia, 2014. "The Size Distribution of Farms and International Productivity Differences," American Economic Review, American Economic Association, vol. 104(6), pages 1667-1697, June.
    2. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    3. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    4. Martin Jung & Markus Reichstein & Christopher R. Schwalm & Chris Huntingford & Stephen Sitch & Anders Ahlström & Almut Arneth & Gustau Camps-Valls & Philippe Ciais & Pierre Friedlingstein & Fabian Gan, 2017. "Compensatory water effects link yearly global land CO2 sink changes to temperature," Nature, Nature, vol. 541(7638), pages 516-520, January.
    5. Shulong Li & Zhizhang Wang, 2023. "The Effects of Agricultural Technology Progress on Agricultural Carbon Emission and Carbon Sink in China," Agriculture, MDPI, vol. 13(4), pages 1-21, March.
    6. Gene M. Grossman & Alan B. Krueger, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 353-377.
    7. Ning Zeng & Fang Zhao & George J. Collatz & Eugenia Kalnay & Ross J. Salawitch & Tristram O. West & Luis Guanter, 2014. "Agricultural Green Revolution as a driver of increasing atmospheric CO2 seasonal amplitude," Nature, Nature, vol. 515(7527), pages 394-397, November.
    8. Joeri Rogelj & Alexander Popp & Katherine V. Calvin & Gunnar Luderer & Johannes Emmerling & David Gernaat & Shinichiro Fujimori & Jessica Strefler & Tomoko Hasegawa & Giacomo Marangoni & Volker Krey &, 2018. "Scenarios towards limiting global mean temperature increase below 1.5 °C," Nature Climate Change, Nature, vol. 8(4), pages 325-332, April.
    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. Eduardo Polloni-Silva & Diogo Ferraz & Flávia de Castro Camioto & Daisy Aparecida do Nascimento Rebelatto & Herick Fernando Moralles, 2021. "Environmental Kuznets Curve and the Pollution-Halo/Haven Hypotheses: An Investigation in Brazilian Municipalities," Sustainability, MDPI, vol. 13(8), pages 1-19, April.
    2. Xiaosheng Li & Xia Yan & Qingxian An & Ke Chen & Zhen Shen, 2016. "The coordination between China’s economic growth and environmental emission from the Environmental Kuznets Curve viewpoint," 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. 83(1), pages 233-252, August.
    3. Saia, Artjom, 2023. "Digitalization and CO2 emissions: Dynamics under R&D and technology innovation regimes," Technology in Society, Elsevier, vol. 74(C).
    4. Xiaoping He & Xin Yao, 2017. "Foreign Direct Investments and the Environmental Kuznets Curve: New Evidence from Chinese Provinces," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(1), pages 12-25, January.
    5. Liu, Liyun & Zhao, Zhenzhi & Su, Bin & Ng, Tsan Sheng & Zhang, Mingming & Qi, Lin, 2021. "Structural breakpoints in the relationship between outward foreign direct investment and green innovation: An empirical study in China," Energy Economics, Elsevier, vol. 103(C).
    6. Elisa Toledo & Wilman Santiago Ochoa-Moreno & Rafael Alvarado & Lizeth Cuesta & Muntasir Murshed & Abdul Rehman, 2022. "Forest Area: Old and New Factors That Affect Its Dynamics," Sustainability, MDPI, vol. 14(7), pages 1-17, March.
    7. Deng, Dandan & Dong, Jiayun & Zhang, Yiwen & Liang, Wenyuan & Liu, Kun & Li, Lingchao, 2023. "Analysis of the environmental Kuznets curve for forest fragmentation: The case of Beijing-Tianjin-Hebei region in China," Forest Policy and Economics, Elsevier, vol. 151(C).
    8. Ulucak, Recep & Koçak, Emrah & Erdoğan, Seyfettin & Kassouri, Yacouba, 2020. "Investigating the non-linear effects of globalization on material consumption in the EU countries: Evidence from PSTR estimation," Resources Policy, Elsevier, vol. 67(C).
    9. Zhao, Jun & Shahbaz, Muhammad & Dong, Xiucheng & Dong, Kangyin, 2021. "How does financial risk affect global CO2 emissions? The role of technological innovation," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    10. Zheng-Xin Wang & Peng Hao & Pei-Yi Yao, 2017. "Non-Linear Relationship between Economic Growth and CO 2 Emissions in China: An Empirical Study Based on Panel Smooth Transition Regression Models," IJERPH, MDPI, vol. 14(12), pages 1-11, December.
    11. Song, Tao & Zheng, Tingguo & Tong, Lianjun, 2008. "An empirical test of the environmental Kuznets curve in China: A panel cointegration approach," China Economic Review, Elsevier, vol. 19(3), pages 381-392, September.
    12. Giedrė Lapinskienė & Kęstutis Peleckis & Neringa Slavinskaitė, 2017. "Energy consumption, economic growth and greenhouse gas emissions in the European Union countries," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 18(6), pages 1082-1097, November.
    13. Emrah Kocak & Hayriye Hilal Baglitas, 2022. "The path to sustainable municipal solid waste management: Do human development, energy efficiency, and income inequality matter?," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(6), pages 1947-1962, December.
    14. Jingwen Lu & Lihua Dai, 2023. "Examining the Threshold Effect of Environmental Regulation: The Impact of Agricultural Product Trade Openness on Agricultural Carbon Emissions," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    15. Bradford David F. & Fender Rebecca A & Shore Stephen H. & Wagner Martin, 2005. "The Environmental Kuznets Curve: Exploring a Fresh Specification," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 4(1), pages 1-28, June.
    16. G. Mythili & Shibashis Mukherjee, 2011. "Examining Environmental Kuznets Curve for river effluents in India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 13(3), pages 627-640, June.
    17. Muhammad Shahbaz & Syed Jawad Hussain Shahzad & Mantu Kumar Mahalik & Perry Sadorsky, 2018. "How strong is the causal relationship between globalization and energy consumption in developed economies? A country-specific time-series and panel analysis," Applied Economics, Taylor & Francis Journals, vol. 50(13), pages 1479-1494, March.
    18. Badunenko, Oleg & Galeotti, Marzio & Hunt, Lester C., 2021. "Better to grow or better to improve? Measuring environmental efficiency in OECD countries with a Stochastic Environmental Kuznets Frontier," FEEM Working Papers 316226, Fondazione Eni Enrico Mattei (FEEM).
    19. Fabian Knorre & Martin Wagner & Maximilian Grupe, 2021. "Monitoring Cointegrating Polynomial Regressions: Theory and Application to the Environmental Kuznets Curves for Carbon and Sulfur Dioxide Emissions," Econometrics, MDPI, vol. 9(1), pages 1-35, March.
    20. Stern, David I. & Gerlagh, Reyer & Burke, Paul J., 2017. "Modeling the emissions–income relationship using long-run growth rates," Environment and Development Economics, Cambridge University Press, vol. 22(6), pages 699-724, December.

    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:16:y:2024:i:15:p:6392-:d:1443161. 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.