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Spatial Network and Driving Factors of Agricultural Green Total Factor Productivity in China

Author

Listed:
  • Zhou Zhou

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Jianqiang Duan

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Shaoqing Geng

    (School of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China)

  • Ran Li

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

Abstract

Agricultural green total factor productivity (AGTFP) is an important indicator to reflect the sustainability level of agriculture. The AGTFP network reflects the spatial correlations of the AGTFP among regions; thus, exploring its network structure and influencing factors can provide targeted policy guidance to the coordinated development of the agriculture sector. This study builds an epsilon-based measurement data envelopment analysis (EBM-DEA) model to calculate 31 provincial AGTFPs in China from 2002 to 2020. Then, social network analysis (SNA) was utilized to explore the characteristics of the AGTFP network, and the quadratic assignment procedure (QAP) was applied to find its external influencing factors. We reached four central conclusions: (1) Overall, there was a gradual upward trend of AGTFP in China during 2002~2020, and the average value rose from 0.75 in 2002 to 0.90 in 2020, but there were some differences among regions. (2) There is a complex and stable network characteristic of AGTFP; the average network density is 0.3753, and the average network efficiency is 0.4714. Meanwhile, some eastern and central areas, such as Henan, Anhui, Hubei, Hebei, Jiangsu, etc., have relatively high centrality and are a bridge in the entire network. (3) The AGTFP network can be divided into eight blocks, including two net beneficial blocks (the central-eastern provinces with high centrality); two net spillover blocks, including the provinces located in the developed urban areas (Beijing, Tianjin, Shanghai, and Jilin), the underdeveloped northwest regions (Ningxia, Qinghai, Xinjiang, and Tibet). The other areas are two-way spillover blocks. (4) Transportation development gap, technological progress gap, and the similarities of the agricultural industry structure are critical factors influencing the AGTFP network. Hence, improving the efficiency of the logistics and transportation industry, promoting technology transfer from developed areas to underdeveloped areas, and developing characteristic agriculture are all conducive to promoting the whole region’s AGTFP. Our research provides policy implications for sustainable agricultural development in China and other developing countries.

Suggested Citation

  • Zhou Zhou & Jianqiang Duan & Shaoqing Geng & Ran Li, 2023. "Spatial Network and Driving Factors of Agricultural Green Total Factor Productivity in China," Energies, MDPI, vol. 16(14), pages 1-26, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5380-:d:1194242
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