HUBEI AGRICULTURAL SCIENCES ›› 2024, Vol. 63 ›› Issue (3): 150-156.doi: 10.14088/j.cnki.issn0439-8114.2024.03.023

• Agricultural Production Efficiency • Previous Articles     Next Articles

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

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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