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Measurement of Green Total Factor Productivity and Its Spatial Convergence Test on the Pig-Breeding Industry in China

Author

Listed:
  • Ning Geng

    (School of Public Administration, Shandong Normal University, Jinan 250014, China)

  • Zengjin Liu

    (Shanghai Academy of Agricultural Sciences, Shanghai 201403, China)

  • Xuejiao Wang

    (Agricultural Economy and Information Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650205, China)

  • Lin Meng

    (School of Public Administration, Shandong Normal University, Jinan 250014, China)

  • Jiayan Pan

    (School of Public Administration, Shandong Normal University, Jinan 250014, China)

Abstract

The pig-breeding industry is one of the pillar industries of China’s agriculture. Improving the green total factor productivity of pig breeding is the basis for ensuring the stable supply of pork, and is also the key to the green transformation of the pig industry. The existing studies about the green total factor productivity of pig breeding lack an analysis of regional coordination and the spillover of spatial technology efficiency at the macro level, and most studies focus on the impact of agricultural production’s environment pollution and other undesirable outputs. Based on the input–output index system of the pig-breeding industry’s green production, the DDF directional distance function model and the Malmquist–Luenberger (ML) productivity index were combined to measure the green total factor productivity of the pig-breeding industry. Moran’s I-Theil index model was used to measure and reveal the technical efficiency differences among the dominant regions of the pig-breeding industry in China and the σ-convergence test was adopted to reveal the convergence trend of green total factor productivity. The results showed that: (1) The growth level of green total factor productivity of pig breeding in China was generally low from 2006 to 2018, and there were obvious regional and scale differences. (2) The green total factor productivity of pig breeding in each province had spatial autocorrelation; that is, there was technology spillover. From 2006 to 2018, with the advance of time, a pattern of gradual evolution from low-level equilibrium to high-level imbalance was formed. (3) Through the convergence test, the convergence trend of large and medium-scale development between different regions fluctuated, while the convergence trend of small-scale development between different regions was not obvious. Therefore, it is necessary to increase investment in technological innovation, promote the large-scale and standardized development of the pig-breeding industry, and strengthen the promotion of technology in producing areas with advantages in pig breeding.

Suggested Citation

  • Ning Geng & Zengjin Liu & Xuejiao Wang & Lin Meng & Jiayan Pan, 2022. "Measurement of Green Total Factor Productivity and Its Spatial Convergence Test on the Pig-Breeding Industry in China," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13902-:d:953736
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    4. Yue Zhang & Hui Zhang & Haozhaoxing Liao & Xiang Sun & Lisi Jiang & Yufeng Wang & Yue Wang, 2024. "Heterogeneous Porter Effect or Crowded-Out Effect: Nonlinear Impact of Environmental Regulation on County-Level Green Total Factor Productivity of Pigs in the Yangtze River Basin of China," Agriculture, MDPI, vol. 14(9), pages 1-33, September.

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