IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v15y2025i15p1621-d1710674.html
   My bibliography  Save this article

Spatiotemporal Differentiation of Carbon Emission Efficiency and Influencing Factors in the Five Major Maize Producing Areas of China

Author

Listed:
  • Zhiyuan Zhang

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

  • Huiyan Qin

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

Abstract

Understanding the carbon emission efficiency (CEE) of maize production and its determinants is critical to supporting China’s dual-carbon goals and advancing sustainable agriculture. This study employs a super-efficiency slack-based measure model (SBM) to evaluate the CEE of five major maize-producing regions in China from 2001 to 2022. Kernel density estimation and the Dagum Gini coefficient are used to analyze spatiotemporal disparities, while a geographically and temporally weighted regression (GTWR) model explores the underlying drivers. Results indicate that the national average maize CEE was 0.86, exhibiting a “W-shaped” fluctuation with turning points in 2009 and 2016. From 2001 to 2015, the Southwestern Mountainous Region led with an average efficiency of 0.76. Post-2015, the Northern Spring Maize Region emerged as the most efficient area, reaching 0.90. Efficiency levels have generally become more concentrated across regions, though the Southern Hilly and Northwest Irrigated Regions showed higher volatility. Inter-regional differences were the primary source of overall CEE disparity, with an average annual contribution of 46.66%, largely driven by the efficiency gap between the Northwest Irrigated Region and other areas. Spatial heterogeneity was evident in the impact of key factors. Agricultural mechanization, cropping structure, and environmental regulation exhibited region-specific effects. Rural economic development and agricultural fiscal support were positively associated with CEE, while urbanization had a negative correlation. These findings provide a theoretical foundation and policy reference for region-specific emission reduction strategies and the green transition of maize production in China.

Suggested Citation

  • Zhiyuan Zhang & Huiyan Qin, 2025. "Spatiotemporal Differentiation of Carbon Emission Efficiency and Influencing Factors in the Five Major Maize Producing Areas of China," Agriculture, MDPI, vol. 15(15), pages 1-23, July.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:15:p:1621-:d:1710674
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/15/15/1621/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/15/15/1621/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    2. Tone, Kaoru & Tsutsui, Miki, 2010. "An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1554-1563, December.
    3. Weini Chen & Dejun Han & Yu Zhan & Bo Chen, 2025. "The Impact of Rural Population Decline on the Economic Efficiency of Agricultural Carbon Emissions: A Case Study of the Contiguous Karst Areas in Yunnan–Guizhou Provinces, China," Agriculture, MDPI, vol. 15(10), pages 1-25, May.
    4. Li, Xiang & Chen, Beizi & Liu, Haijun & Xu, Mengqi & Yang, Haijun, 2025. "Characteristics of agricultural carbon emissions in arid zones, drivers and decoupling effects: evidence from Xinjiang, China," Energy, Elsevier, vol. 328(C).
    5. Stéphane Cara & Martin Houzé & Pierre-Alain Jayet, 2005. "Methane and Nitrous Oxide Emissions from Agriculture in the EU: A Spatial Assessment of Sources and Abatement Costs," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 32(4), pages 551-583, December.
    6. IGNATIUS, Joshua & GHASEMI, M.-R. & ZHANG, Feng & EMROUZNEJAD, Ali & HATAMI-MARBINI, Adel, 2016. "Carbon Efficiency Evaluation: An Analytical Framework Using Fuzzy DEA," LIDAM Reprints CORE 2735, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. O’Brien, Travis A. & Kashinath, Karthik & Cavanaugh, Nicholas R. & Collins, William D. & O’Brien, John P., 2016. "A fast and objective multidimensional kernel density estimation method: fastKDE," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 148-160.
    8. Wang, Jieyu & Shan, Yuli & Cui, Can & Zhao, Congyu & Meng, Jing & Wang, Shaojian, 2024. "Investigating the fast energy-related carbon emissions growth in African countries and its drivers," Applied Energy, Elsevier, vol. 357(C).
    9. Guanghe Han & Jiahui Xu & Xin Zhang & Xin Pan, 2024. "Efficiency and Driving Factors of Agricultural Carbon Emissions: A Study in Chinese State Farms," Agriculture, MDPI, vol. 14(9), pages 1-22, August.
    10. Kaoru Tone & Miki Tsutsui, 2010. "An epsilon-based measure of efficiency in DEA revisited -A third pole of technical efficiency," GRIPS Discussion Papers 09-21, National Graduate Institute for Policy Studies.
    11. Dagum, Camilo, 1997. "A New Approach to the Decomposition of the Gini Income Inequality Ratio," Empirical Economics, Springer, vol. 22(4), pages 515-531.
    12. Lianguang Mo, 2024. "Evaluation model of carbon emission efficiency of land intensive use based on SBM model," International Journal of Environmental Technology and Management, Inderscience Enterprises Ltd, vol. 27(3), pages 200-215.
    13. Ignatius, Joshua & Ghasemi, M.-R. & Zhang, Feng & Emrouznejad, Ali & Hatami-Marbini, Adel, 2016. "Carbon efficiency evaluation: An analytical framework using fuzzy DEA," European Journal of Operational Research, Elsevier, vol. 253(2), pages 428-440.
    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. Yashuo Liu & Huanan Liu, 2023. "Temporal and Spatial Evolution Characteristics and Influencing Factors Analysis of Green Production in China’s Dairy Industry: Based on the Perspective of Green Total Factor Productivity," Sustainability, MDPI, vol. 15(23), pages 1-21, November.
    2. Danyu Liu & Ke Zhang, 2022. "Analysis of Spatial Differences and the Influencing Factors in Eco-Efficiency of Urban Agglomerations in China," Sustainability, MDPI, vol. 14(19), pages 1-21, October.
    3. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    4. Xiangqian Wang & Shudong Wang & Yongqiu Xia, 2022. "Evaluation and Dynamic Evolution of the Total Factor Environmental Efficiency in China’s Mining Industry," Energies, MDPI, vol. 15(3), pages 1-19, February.
    5. Xuejuan Wang & Qi Deng & Riccardo Natoli & Li Wang & Wei Zhang & Catherine Xiaocui Lou, 2025. "Analyzing Regional Disparities in China’s Green Manufacturing Transition," Sustainability, MDPI, vol. 17(15), pages 1-19, August.
    6. Adel Hatami-Marbini & Per J. Agrell & Hirofumi Fukuyama & Kobra Gholami & Pegah Khoshnevis, 2017. "The role of multiplier bounds in fuzzy data envelopment analysis," Annals of Operations Research, Springer, vol. 250(1), pages 249-276, March.
    7. Khoshroo, Alireza & Izadikhah, Mohammad & Emrouznejad, Ali, 2022. "Total factor energy productivity considering undesirable pollutant outputs: A new double frontier based malmquist productivity index," Energy, Elsevier, vol. 258(C).
    8. Ze Tian & Fang-Rong Ren & Qin-Wen Xiao & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Cross-Regional Comparative Study on Carbon Emission Efficiency of China’s Yangtze River Economic Belt Based on the Meta-Frontier," IJERPH, MDPI, vol. 16(4), pages 1-19, February.
    9. Xiaoling Wang & Yiting Han & Baofeng Shi & Mohammad Zoynul Abedin, 2025. "The impacts of green credit guidelines on total factor productivity of heavy-polluting enterprises: A quasi-natural experiment from China," Annals of Operations Research, Springer, vol. 347(1), pages 41-68, April.
    10. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2022. "Stochastic dominance spanning and augmenting the human development index with institutional quality," Annals of Operations Research, Springer, vol. 315(1), pages 341-369, August.
    11. Wang, Changjian & Miao, Zhuang & Chen, Xiaodong & Cheng, Yu, 2021. "Factors affecting changes of greenhouse gas emissions in Belt and Road countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    12. Chen, Zhenni & Zhang, Zengkai & Feng, Tong & Liu, Diyi, 2023. "What drives the temporal dynamics and spatial differences of urban and rural household emissions in China?," Energy Economics, Elsevier, vol. 125(C).
    13. Zhou Zhou & Jianqiang Duan & Shaoqing Geng & Ran Li, 2023. "Spatial Network and Driving Factors of Agricultural Green Total Factor Productivity in China," Energies, MDPI, vol. 16(14), pages 1-26, July.
    14. Xuefen Liu & Chang Gan & Mihai Voda, 2024. "Analysis of the Effect of Environmental Regulation on Eco-Efficiency of Service Sector," Sustainability, MDPI, vol. 16(13), pages 1-20, July.
    15. Yiyang Sun & Guolin Hou, 2021. "Analysis on the Spatial-Temporal Evolution Characteristics and Spatial Network Structure of Tourism Eco-Efficiency in the Yangtze River Delta Urban Agglomeration," IJERPH, MDPI, vol. 18(5), pages 1-29, March.
    16. Ren, Fang-rong & Tian, Ze & Liu, Jingjing & Shen, Yu-ting, 2020. "Analysis of CO2 emission reduction contribution and efficiency of China’s solar photovoltaic industry: Based on Input-output perspective," Energy, Elsevier, vol. 199(C).
    17. Baitong Li & Jian Li & Chen Liu & Xinyan Yao & Jingxuan Dong & Meijun Xia, 2023. "Provincial Inclusive Green Growth Efficiency in China: Spatial Correlation Network Investigation and Its Influence Factors," Land, MDPI, vol. 12(3), pages 1-24, March.
    18. Cayir Ervural, Beyzanur & Zaim, Selim & Delen, Dursun, 2018. "A two-stage analytical approach to assess sustainable energy efficiency," Energy, Elsevier, vol. 164(C), pages 822-836.
    19. You, Jiansheng & Hu, Jin & Jiang, Bing, 2024. "The correlation evolution and formation mechanism of energy ecological efficiency in China: A spatial network approach," Energy, Elsevier, vol. 313(C).
    20. Meijuan Hu & Zaijun Li & Bing Hou, 2023. "The Influencing Effect of Tourism Economy on Green Development Efficiency in the Yangtze River Delta," IJERPH, MDPI, vol. 20(2), pages 1-18, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jagris:v:15:y:2025:i:15:p:1621-:d:1710674. 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.