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Agricultural Production Efficiency and Differentiation of City Clusters along the Middle Reaches of Yangtze River under Environmental Constraints

Author

Listed:
  • Lei Wang

    (School of Business, Hohai University, Nanjing 320100, China)

  • Yi Zhang

    (School of Business, Hohai University, Nanjing 320100, China)

  • Jingyi Xia

    (School of Business, Hohai University, Nanjing 320100, China)

  • Zilei Wang

    (School of Business, Hohai University, Nanjing 320100, China)

  • Wenjing Zhang

    (School of Management, Xi’an University of Finance and Economics, Xi’an 710000, China)

Abstract

The improvement of overall agricultural efficiency in the city clusters along the middle reaches of the Yangtze River is crucial for promoting stable regional agricultural production and ensuring food security. This study employs the SBM (slack-based measure) model with the unexpected environmental outputoutputs, including agricultural surface pollution and agricultural carbon emissions, and the SFA (stochastic frontier approach) model to investigate the overall agricultural efficiency and its influencing factors in 31 prefecture-level cities in the middle reaches of the Yangtze River urban agglomeration from 2008 to 2021. The research findings indicate the following: (1) Without eliminating the impact of environmental variables, the overall agricultural efficiency in the middle reaches of the Yangtze River city clusters shows a rise–fall–stability trend and limited level. The scale of production input is relatively reasonable, but there is inefficiency in the utilization of factor resources. (2) The SFA model reveals that economic development, urbanization construction, industrial structure, and government influence have significant but different impacts on agricultural production factor input. Accelerating economic development is helpful for reducing excessive inputs of agricultural capital, labor, planting area, agricultural film, and irrigation. Increasing the level of urbanization can promote the efficient allocation of planting area and effective irrigation area. The improvement of industrialization level pushes the rational input of planting area and agricultural film, but it may also lead to excessive input of agricultural capital, labor, pesticides, and effective irrigation area. Expanding government influence can restrain the excessive use of pesticides. (3) After eliminating environmental variables, there is a low and slow declining trend of the overall agricultural efficiency over time. Neither production scale efficiency nor pure technical efficiency reached optimal levels; the former one is significantly lower than the latter. In terms of spatial distribution, there exists a “higher in the west and lower in the east” feature, with obvious and expanding regional efficiency differences and high-efficiency areas gradually concentrating in the Wuhan urban circle. In summary, this article puts forward the following suggestions: optimize the structure of the government’s support for agriculture, focusing on the construction of agricultural infrastructure and the support for green production in agriculture; improve the research and development and promotion of green production technology and encourage the establishment of the use of resources and recycling; and absorb the population of farmers who have been transferred to urban areas reasonably and orderly under the adjustment of industrial structure.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:6126-:d:1437448
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    References listed on IDEAS

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    1. Vernon W. Ruttan, 2002. "Productivity Growth in World Agriculture: Sources and Constraints," Journal of Economic Perspectives, American Economic Association, vol. 16(4), pages 161-184, Fall.
    2. Dietrich Vollrath, 2007. "Land Distribution and International Agricultural Productivity," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(1), pages 202-216.
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    4. Restuccia, Diego & Yang, Dennis Tao & Zhu, Xiaodong, 2008. "Agriculture and aggregate productivity: A quantitative cross-country analysis," Journal of Monetary Economics, Elsevier, vol. 55(2), pages 234-250, March.
    5. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
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    1. Xiejun Cheng & Jinxin Bian & Dongmei He & Decai Tang, 2025. "An analysis of agricultural production efficiency of Yellow River Basin based on a three-stage DEA Malmquist model," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
    2. Yuqing Geng & Yan Yan & Qinjun Xiang & Naiguang Zhang & Xinlei Yang & Xinying Jiang, 2025. "Achieving sustainable development goals: coupling coordination between agricultural industrialization and rural infrastructure with the case of China," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-28, December.
    3. 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.

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