• Core Journal of Chinese Humanities and Social Sciences of AMI
  • National Excellent Social Science Journal of Agricultural Universities
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Volume 16 Issue 6
Oct.  2022
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HU Dashuang, CHEN Xiaoling, LI Min, ZHOU Linglin. Measurement of Agricultural Production Efficiency and Its Spatial-temporal Differences in Anhui Province Based on Three-stage SBM Model[J]. Journal of Yunnan Agricultural University (Social Science), 2022, 16(6): 46-56. DOI: 10.12371/j.ynau(s).202206043
Citation: HU Dashuang, CHEN Xiaoling, LI Min, ZHOU Linglin. Measurement of Agricultural Production Efficiency and Its Spatial-temporal Differences in Anhui Province Based on Three-stage SBM Model[J]. Journal of Yunnan Agricultural University (Social Science), 2022, 16(6): 46-56. DOI: 10.12371/j.ynau(s).202206043
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Measurement of Agricultural Production Efficiency and Its Spatial-temporal Differences in Anhui Province Based on Three-stage SBM Model

DOI: 10.12371/j.ynau(s).202206043

  • College of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China

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  • Received Date: June 09, 2022
  • Revised Date: September 19, 2022
  • Accepted Date: September 20, 2022
  • Available Online: September 26, 2022
  • Published Date: October 13, 2022
    Graphical Abstract
    • Abstract
  • Based on the data of 16 prefectures in Anhui Province, this article selects the period of 2010—2020 as the study time period, takes into account the influence of environmental factors and random disturbances, and analyzes the agricultural production efficiency and temporal and spatial characteristics of Anhui Province from static and dynamic perspectives by using the super-efficient three-stage SBM model and Malmquist index method. The results show that both environmental factors and random disturbances significantly affect agricultural production efficiency. After excluding the above disturbances:（1）The average efficiency of agricultural production in Anhui Province is stable and growing overall from 2010 to 2020, with only three years of non-DEA validity. Among the 16 prefecture-level cities measured, 7 regions have average efficiency in DEA effective state and 9 regions are in non-DEA effective state.（2）According to the analysis results of spatial and temporal characteristics, the average efficiency and efficiency of cities from 2010 to 2020 are mainly concentrated in the southwest region of Anhui, while the average efficiency in the northeast region is relatively low.（3）Malmquist index results show that Anhui province has the highest annual average growth rate of total factors. Among prefecture-level cities, the top three regions’ total factor productivity improvement is mainly due to the promotion effect of technical efficiency, while the third to ninth regions’ total factor productivity improvement is due to the promotion effect of technological progress factors. The prefecture-level cities ranked after the 9th are mainly due to the scale efficiency which affects the increase of technical efficiency value and thus the improvement of total factor productivity. Finally, the article proposes policy recommendations to address the remaining shortcomings of agricultural production efficiency in Anhui Province.
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