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The Agricultural Green Production following the Technological Progress: Evidence from China

Author

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  • Shuxing Xiao

    (School of Public Administration and Law, Hunan Agricultural University, Changsha 410128, China
    School of Teacher Education, Shaoguan University, Shaoguan 512005, China)

  • Zuxin He

    (School of Economics, Guangdong University of Finance & Economics, Guangzhou 510320, China)

  • Weikun Zhang

    (School of Social and Public Administration, Lingnan Normal University, Zhanjiang 524088, China)

  • Xiaoming Qin

    (Guangdong Provincial Key Laboratory of Aquatic Products Processing and Safety, Guangdong Ocean University, Zhanjiang 524088, China)

Abstract

This study performs the spatial Durbin model (SDM) and threshold model to analyze the efficiency of agricultural green production following technological progress from 1998 through 2019. The SDM supports a nonlinear contribution of technological progress spillover to agricultural green total factor productivity (GTFP), exacerbated by upgrading agricultural structure. Moreover, the threshold model confirms that technological progress has a single threshold effect on agricultural GTFP with the rationalization of the agrarian system as a threshold variable; meanwhile, the contribution of technological progress to agricultural GTFP is less than that of agricultural total factor productivity. Out of the expanded application of dissipative structure theory in agricultural GTFP systems innovatively, this study reveals the urgency to strengthen the innovation of independent technology, lower the threshold for introducing technology, and optimize the agrarian structure in the long-term sustainable agriculture for the economies that are undergoing a similar development stage as China.

Suggested Citation

  • Shuxing Xiao & Zuxin He & Weikun Zhang & Xiaoming Qin, 2022. "The Agricultural Green Production following the Technological Progress: Evidence from China," IJERPH, MDPI, vol. 19(16), pages 1-16, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:9876-:d:885088
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    References listed on IDEAS

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    1. William Brock & M. Taylor, 2010. "The Green Solow model," Journal of Economic Growth, Springer, vol. 15(2), pages 127-153, June.
    2. Yuan Zhao & Tian Zhang & Ting Wu & Shujing Xu & Shuwang Yang, 2021. "Effects of Technological Progress from Different Sources on Haze Pollution in China," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    3. Weber, William L. & Domazlicky, Bruce R., 1999. "Total factor productivity growth in manufacturing: a regional approach using linear programming," Regional Science and Urban Economics, Elsevier, vol. 29(1), pages 105-122, January.
    4. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    5. Huang, Junbing & Cai, Xiaochen & Huang, Shuo & Tian, Sen & Lei, Hongyan, 2019. "Technological factors and total factor productivity in China: Evidence based on a panel threshold model," China Economic Review, Elsevier, vol. 54(C), pages 271-285.
    6. Pan, Xiuzhen & Wei, Zixiang & Han, Botang & Shahbaz, Muhammad, 2021. "The heterogeneous impacts of interregional green technology spillover on energy intensity in China," Energy Economics, Elsevier, vol. 96(C).
    7. Zhang, Wei & Li, Jing & Li, Guoxiang & Guo, Shucen, 2020. "Emission reduction effect and carbon market efficiency of carbon emissions trading policy in China," Energy, Elsevier, vol. 196(C).
    8. Peneder, Michael, 2003. "Industrial structure and aggregate growth," Structural Change and Economic Dynamics, Elsevier, vol. 14(4), pages 427-448, December.
    9. Späti, Karin & Huber, Robert & Finger, Robert, 2021. "Benefits of Increasing Information Accuracy in Variable Rate Technologies," Ecological Economics, Elsevier, vol. 185(C).
    10. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    11. Li, Ye & Chen, Yiyan, 2021. "Development of an SBM-ML model for the measurement of green total factor productivity: The case of pearl river delta urban agglomeration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    12. Zhai, Xueqi & An, Yunfei, 2021. "The relationship between technological innovation and green transformation efficiency in China: An empirical analysis using spatial panel data," Technology in Society, Elsevier, vol. 64(C).
    13. Hadi A. AL-agele & Lloyd Nackley & Chad W. Higgins, 2021. "A Pathway for Sustainable Agriculture," Sustainability, MDPI, vol. 13(8), pages 1-14, April.
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    Cited by:

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