湖北农业科学 ›› 2024, Vol. 63 ›› Issue (3): 150-156.doi: 10.14088/j.cnki.issn0439-8114.2024.03.023

• 农业生产效率 • 上一篇    下一篇

中国粮食生产效率的时空演变特征及影响因素

季张含昱, 杨慧文   

  1. 河海大学商学院,南京 211100
  • 收稿日期:2022-08-04 出版日期:2024-03-25 发布日期:2024-04-07
  • 作者简介:季张含昱(2002-),男,江苏无锡人,在读本科生,研究方向为资源经济,(电话)15312213918(电子信箱)2063310235@hhu.edu.cn。
  • 基金资助:
    中央高校基本科研业务费项目(B210202157)

Spatial-temporal evolution characteristics and influencing factors of grain production efficiency in China

JI-Zhang Han-yu, YANG Hui-wen   

  1. Business School of Hohai University, Nanjing 211100, China
  • Received:2022-08-04 Online:2024-03-25 Published:2024-04-07

摘要: 基于投入产出框架设计粮食生产效率测算指标体系,构建基于DDF的粮食生产效率动态DEA测算模型,测算2011—2019年中国粮食生产效率,然后结合ESTAD模型和地理探测器模型识别中国粮食生产效率的时空演变特征及其影响因素。结果表明,2011—2019年,中国粮食生产效率总体水平较高,呈小幅度动态下降趋势,并呈明显的地区差异性;中国粮食生产效率的局部空间结构和空间依赖方向上具有较强的稳定性,东西部地区局部空间结构稳定性高于中部地区,而中西部的局部空间稳定性高于东部沿海地区;粮食生产效率与邻域协同增长的省(市、自治区)占比为51.6%,集中于黄河以南,空间格局整合性呈多元化和差异化特征;宏观经济因素对粮食生产效率的影响最大,政策支持因素影响最小,但政策支持与其余因素的交互作用具有非线性增强效果。

关键词: 粮食生产效率, 时空演变, 影响因素, ESTDA模型, 地理探测器

Abstract: The grain production efficiency measurement index system was designed based on the input-output framework, and a dynamic DEA calculation model of grain production efficiency based on DDF was constructed to calculate the grain production efficiency of China from 2011 to 2019. ESTAD model and geographic detectors were used to identify the spatial-temporal evolution characteristics of grain production efficiency in China as well as its influencing factors. The results showed that, from 2011 to 2019, China’s grain production efficiency was relatively high on the whole, showing a small dynamic decline trend, as well as obvious regional differences. The stability of local spatial structure and spatial dependence direction of grain production efficiency in China was strong. The stability of local spatial structure in eastern and western China was higher than that in central China, while the stability in central and western China was higher than that in eastern coastal China. The proportion of provinces (cities, autonomous regions) with synergistic growth of grain production efficiency and neighboring regions was 51.6%, mainly located in the south of the Yellow River, and the spatial pattern integration showed the characteristics of diversification and differentiation. Macroeconomic factors had the greatest impact on grain production efficiency, while policy support factors had the least impact. However, the interaction between policy support and other factors had a nonlinear enhancing effect.

Key words: grain production efficiency, spatial-temporal evolution, influencing factors, ESTDA model, geographic detector

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