IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i9p4246-d1651062.html
   My bibliography  Save this article

Coupling Agricultural Carbon Emission Efficiency and Economic Growth: Evidence from Jiangxi Province, China

Author

Listed:
  • Lulu Yang

    (College of Economic and Management, Henan Agricultural University, Zhengzhou 450046, China
    These authors contributed equally to this work.)

  • Xieqihua Liu

    (Faculty of Humanities and Social Sciences, Macao Polytechnic University, Macao 999078, China
    These authors contributed equally to this work.)

  • Xiaolan Kang

    (School of Economics and Management, Jiangxi Agricultural University, Nanchang 330045, China)

  • Yuxia Zhu

    (Faculty of Humanities and Social Sciences, Macao Polytechnic University, Macao 999078, China)

  • Chaobao Wu

    (School of Economics and Management, Jiangxi Agricultural University, Nanchang 330045, China)

  • Bin Liu

    (Research Center for “Agriculture, Rural Areas, and Farmers”, Jiangxi Agricultural University, Nanchang 330045, China)

  • Wen Li

    (School of Humanities and Public Administration, Jiangxi Agricultural University, Nanchang 330045, China)

Abstract

Exploring the law and evolution mechanism of coupling and coordination between agricultural carbon emission efficiency (ACE) and agricultural economic growth (AEG) can provide a reference basis for agricultural low-carbon transformation. This study takes 11 cities in Jiangxi Province as the research object; measures the level of ACE based on the panel data from 2008 to 2022; and analyzes the development and influencing factors of the coupling and coordination between ACE and AEG by using the coupling coordination degree model, the Dagum Gini coefficient decomposition method, and the Tobit regression model. The results reveal the following: (1) The overall ACE in Jiangxi Province displays a significant upward trend, with the average efficiency value increasing from 0.172 to 0.624, reflecting an average annual growth rate of 72.43%. Nonetheless, there remains clear regional heterogeneity, characterized by lower efficiencies in Central and Southern Jiangxi compared to the higher efficiencies found in Northern and Western Jiangxi. (2) Despite gradual improvements in regional coordination, the Central and Southern Jiangxi regions still lag Northern and Western Jiangxi in terms of the linked coordination between ACE and AEG, symptoms of which had been previously misaligned. (3) The results of Dagum’s Gini coefficient decomposition show that inter-regional disparities are the main source of overall disparities, with a contribution of 37.43%, which is higher than the synergistic effect of intra-regional disparities and hyper-variable densities, corroborating the core contradiction of uneven development across regions. (4) The Tobit model reveals that government investment, industrial structure optimization, urbanization, and educational attainment exert a significant positive influence on promoting coupling coordination. To establish a scientific basis for achieving a low-carbon agricultural transformation and equitable AEG in Jiangxi Province, this research recommends bolstering regional cooperation, fostering innovations in agricultural science and technology, optimizing the industrial structure, and enhancing farmers’ awareness of low-carbon practices. This study expands the theoretical system of agricultural low-carbon transition in terms of research methods and scales to provide a scientific basis for agricultural provinces to realize agricultural low-carbon transition and balanced economic development.

Suggested Citation

  • Lulu Yang & Xieqihua Liu & Xiaolan Kang & Yuxia Zhu & Chaobao Wu & Bin Liu & Wen Li, 2025. "Coupling Agricultural Carbon Emission Efficiency and Economic Growth: Evidence from Jiangxi Province, China," Sustainability, MDPI, vol. 17(9), pages 1-28, May.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:9:p:4246-:d:1651062
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/9/4246/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/9/4246/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lei Wang & Yi Zhang & Jingyi Xia & Zilei Wang & Wenjing Zhang, 2024. "Agricultural Production Efficiency and Differentiation of City Clusters along the Middle Reaches of Yangtze River under Environmental Constraints," Sustainability, MDPI, vol. 16(14), pages 1-20, July.
    2. Wenxin Liu & Ruifan Xu & Yue Deng & Weinan Lu & Boyang Zhou & Minjuan Zhao, 2021. "Dynamic Relationships, Regional Differences, and Driving Mechanisms between Economic Development and Carbon Emissions from the Farming Industry: Empirical Evidence from Rural China," IJERPH, MDPI, vol. 18(5), pages 1-22, February.
    3. Christian H. Weiß & Fukang Zhu, 2025. "Tobit models for count time series," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 52(1), pages 381-415, March.
    4. Quan Xiao & Yu Wang & Haojie Liao & Gang Han & Yunjie Liu, 2023. "The Impact of Digital Inclusive Finance on Agricultural Green Total Factor Productivity: A Study Based on China’s Provinces," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    5. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    6. Qin Shu & Yang Su & Hong Li & Feng Li & Yunjie Zhao & Chen Du, 2023. "Study on the Spatial Structure and Drivers of Agricultural Carbon Emission Efficiency in Belt and Road Initiative Countries," Sustainability, MDPI, vol. 15(13), pages 1-27, July.
    7. Wise, Marshall & Dooley, James & Luckow, Patrick & Calvin, Katherine & Kyle, Page, 2014. "Agriculture, land use, energy and carbon emission impacts of global biofuel mandates to mid-century," Applied Energy, Elsevier, vol. 114(C), pages 763-773.
    8. Li Li & Lianqi Zhu & Nan Xu & Ying Liang & Zhengyu Zhang & Junjie Liu & Xin Li, 2022. "Climate Change and Diurnal Warming: Impacts on the Growth of Different Vegetation Types in the North–South Transition Zone of China," Land, MDPI, vol. 12(1), pages 1-16, December.
    9. Rendao Ye & Yue Qi & Wenyan Zhu, 2023. "Impact of Agricultural Industrial Agglomeration on Agricultural Environmental Efficiency in China: A Spatial Econometric Analysis," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    10. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    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. Ruomeng Zhou & Yunsheng Zhang, 2023. "Measurement of Urban Green Total Factor Productivity and Analysis of Its Temporal and Spatial Evolution in China," Sustainability, MDPI, vol. 15(12), pages 1-32, June.
    2. 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.
    3. Büschken, Joachim, 2009. "When does data envelopment analysis outperform a naïve efficiency measurement model?," European Journal of Operational Research, Elsevier, vol. 192(2), pages 647-657, January.
    4. 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).
    5. Xiao Zhang & Di Wang, 2023. "Beyond the Ecological Boundary: A Quasi-Natural Experiment on the Impact of National Marine Parks on Eco-Efficiency in Coastal Cities," Sustainability, MDPI, vol. 15(20), pages 1-19, October.
    6. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    7. Du, Xiaoyun & Meng, Conghui & Guo, Zhenhua & Yan, Hang, 2023. "An improved approach for measuring the efficiency of low carbon city practice in China," Energy, Elsevier, vol. 268(C).
    8. Pelloneová Natalie, 2023. "Evaluating Hockey Players Using Andersen and Petersen's Super-Efficiency Model: Who is the Best Czech Hockey Player in the NHL?," Polish Journal of Sport and Tourism, Sciendo, vol. 30(3), pages 23-28, September.
    9. Artur Wyszyński, 2017. "Sytuacja finansowa klubów Ekstraklasy w ujęciu metody DEA," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 69-99.
    10. Muliaman Hadad & Maximilian Hall & Karligash Kenjegalieva & Wimboh Santoso & Richard Simper, 2011. "Banking efficiency and stock market performance: an analysis of listed Indonesian banks," Review of Quantitative Finance and Accounting, Springer, vol. 37(1), pages 1-20, July.
    11. Jo, Ah-Hyun & Chang, Young-Tae, 2023. "The effect of airport efficiency on air traffic, using DEA and multilateral resistance terms gravity models," Journal of Air Transport Management, Elsevier, vol. 108(C).
    12. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    13. Roland Banya & Nicholas Biekpe, 2018. "Banking efficiency and its determinants in selected frontier african markets," Economic Change and Restructuring, Springer, vol. 51(1), pages 69-95, February.
    14. Mario Fortin & André Leclerc, 2011. "L’Efficience Des Cooperatives De Services Financiers: Une Analyse De La Contribution Du Milieu," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 82(1), pages 45-62, March.
    15. Yi-Chung Hsu, 2014. "Efficiency in government health spending: a super slacks-based model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 111-126, January.
    16. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    17. Fan Wang & Lili Feng & Jin Li & Lin Wang, 2020. "Environmental Regulation, Tenure Length of Officials, and Green Innovation of Enterprises," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    18. 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.
    19. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    20. Shih-Heng Yu & Chia-Wei Hsu, 2020. "A unified extension of super-efficiency in additive data envelopment analysis with integer-valued inputs and outputs: an application to a municipal bus system," Annals of Operations Research, Springer, vol. 287(1), pages 515-535, 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:17:y:2025:i:9:p:4246-:d:1651062. 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.