College of Economics, Hebei GEO University, Shijiazhuang 050030, China.
Business School, Hebei Normal University, Shijiazhuang 050024, China.
Int J Environ Res Public Health. 2023 Jan 29;20(3):2397. doi: 10.3390/ijerph20032397.
Agricultural eco-efficiency is an important indicator used to measure agriculture's high-quality and sustainable development. Therefore, this paper uses the EBM-Super-ML method with strong disposability of undesired output to calculate Chinese agricultural eco-efficiency and uses a geographical detector to measure the driving force of the factor. The research conclusions are mainly reflected in three aspects. Firstly, from the perspective of eco-efficiency changes, the overall mean value of agricultural eco-efficiency increased by 3.5%, and the regional heterogeneity is significant, with the fastest growth in the eastern region. Secondly, the results of driving force analysis show that the main driving factors of agricultural eco-efficiency divergence are capital inputs, total carbon emissions, labor inputs, agricultural film residues, fertilizer use, and pesticide residues, with driving forces of 0.43, 0.37, 0.34, 0.31, 0.28, and 0.20, respectively. Finally, from the perspective of eco-efficiency improvement potential, the mean value of output improvement potential is 5%, and the input factor is 7%. Among the non-desired outputs, the reduction rate of agricultural films can reach 40%. Among the input factors, labor input has the highest potential for intensive use, while agricultural machinery has a negative effect. Therefore, strengthening the development of the agricultural service industry is of great significance to improve the utilization rate of mechanical equipment and reduce the undesired output of agriculture.
农业生态效率是衡量农业高质量和可持续发展的重要指标。因此，本文采用具有强非期望产出处置能力的 EBM-Super-ML 方法来计算中国农业生态效率，并利用地理探测器来衡量各因素的驱动力。研究结论主要体现在三个方面。首先，从生态效率变化的角度来看，农业生态效率的整体平均值增长了 3.5%，区域异质性显著，东部地区增长最快。其次，驱动力分析结果表明，农业生态效率差异的主要驱动因素是资本投入、总碳排放量、劳动力投入、农业残膜、化肥使用和农药残留，驱动力分别为 0.43、0.37、0.34、0.31、0.28 和 0.20。最后，从生态效率改进潜力的角度来看，产出改进潜力的平均值为 5%，投入因子为 7%。在非期望产出中，农业薄膜的削减率可达 40%。在投入要素中，劳动力投入具有最高的集约利用潜力，而农业机械则具有负效应。因此，加强农业服务业的发展对于提高农业机械装备的利用率和减少农业非期望产出具有重要意义。
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