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Development Dynamics and Influencing Factors of China’s Agricultural Green Ecological Efficiency Based on an Evaluation Model Incorporating Ecosystem Service Value and Carbon Emissions

Author

Listed:
  • Yuxuan Wang

    (Business School, Hohai University, Nanjing 211100, China)

  • Ze Tian

    (Business School, Hohai University, Nanjing 211100, China
    Low Carbon Economy Research Institute, Hohai University, Nanjing 210098, China)

  • Xiaodong Jing

    (Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment of China, Nanjing 210042, China)

  • Mengyao Li

    (Asia Institute, The University of Melbourne, Melbourne, VIC 3010, Australia
    School of Environment, Education and Development, University of Manchester, Manchester M13 9PL, UK)

Abstract

Sustainable agricultural development requires ensuring food security while preserving essential ecological conditions. This study incorporated ecosystem service value and carbon emissions as the positive and negative ecological outputs of agriculture, respectively, to account for the AGEE of 31 Chinese provinces from 2012 to 2021 and to analyse its spatiotemporal characteristics. The Malmquist Index was employed to calculate the green total factor productivity (GTP) as a quantitative indicator of AGEE dynamics, providing further insights into the sources and equilibrium of AGEE growth, as well as provincial-level improvement paths. Furthermore, the Spatial Durbin Model was applied to systematically analyse the influencing factors and their associated spatial spillover effects. The results show the following: (1) AGEE demonstrated steady improvement, with a mean value of 0.576, and was spatially concentrated along a northeast–southwest axis, exhibiting regional disparities and polarisation. (2) GTP consistently exceeded 1, indicating overall AGEE growth, primarily driven by technological scale expansion. Regional imbalances in AGEE growth had emerged, with heterogeneous causes across economic regions. Three identified AGEE improvement paths—technological catch-up, green innovation, and technological progress—varied by province, with green innovation being the most common priority. (3) AGEE exhibited spatial autocorrelation, with rural income, adequate irrigation, and cropping structure promoting AGEE. Effective irrigation also exhibited a positive spatial spillover effect, whereas industrial structure hindered AGEE. These findings provide valuable insights for advancing green agricultural practices and sustainable regional development.

Suggested Citation

  • Yuxuan Wang & Ze Tian & Xiaodong Jing & Mengyao Li, 2025. "Development Dynamics and Influencing Factors of China’s Agricultural Green Ecological Efficiency Based on an Evaluation Model Incorporating Ecosystem Service Value and Carbon Emissions," Sustainability, MDPI, vol. 17(18), pages 1-31, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:18:p:8253-:d:1749172
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