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Analysis of Measurement, Regional Differences, Convergence and Dynamic Evolutionary Trends of the Green Production Level in Chinese Agriculture

Author

Listed:
  • Jiale Yan

    (Economics Department, Irvine Valley College, Irvine, CA 92618, USA)

  • Zhengyuan Tang

    (School of Economics and Management, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Yinuo Guan

    (School of Media and Design, Beijing Technology and Business University, Beijing 102488, China)

  • Mingjian Xie

    (School of Business, Macau University of Science and Technology, Macau 999078, China)

  • Yongjian Huang

    (School of Finance, Central University of Finance and Economics, Beijing 102206, China)

Abstract

The development of green agriculture is conducive to accelerating the agricultural modernization process, making a significance for the sustainable development of agriculture and the environment in China. This paper constructs a comprehensive evaluation model by selecting 17 representative indicators from the perspective of sustainability. Then, this paper uses the entropy value method to measure the level of green agricultural production in 31 provinces from 2011 to 2021. We use Dagum’s Gini coefficient and decomposition method, the kernel density estimation method and spatial Markov chain analysis method to explore the main sources of spatial differences and dynamic evolution trends. The results show that: (1) The overall level of green production in Chinese agriculture is low, and the level in the central region is higher than that in eastern and western regions; (2) There are significant regional differences in the level of green production in China’s agriculture, and this is likely to widen. The interaction of inter- and intra-regional differences is the main reason for overall differences; (3) The trend of polarization in the level of green agricultural production is more obvious in the eastern part of China, while it is weaker in central and western regions; (4) There is a spatial spillover effect in the dynamic evolution of China’s agricultural green production level. And the longer the overall time, the more obvious the spillover effect is. This paper analyzes the past development of green agriculture in China, makes predictions and provides constructive suggestions for the improvement and development of green agricultural production in China in the future.

Suggested Citation

  • Jiale Yan & Zhengyuan Tang & Yinuo Guan & Mingjian Xie & Yongjian Huang, 2023. "Analysis of Measurement, Regional Differences, Convergence and Dynamic Evolutionary Trends of the Green Production Level in Chinese Agriculture," Agriculture, MDPI, vol. 13(10), pages 1-18, October.
  • Handle: RePEc:gam:jagris:v:13:y:2023:i:10:p:2016-:d:1261947
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    References listed on IDEAS

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    1. Puneet Vatsa & Junpeng Li & Phong Quoc Luu & Julio Cesar Botero‐R, 2023. "Internet use and consumption diversity: Evidence from rural China," Review of Development Economics, Wiley Blackwell, vol. 27(3), pages 1287-1308, August.
    2. Nanak Kakwani & Xiaobing Wang & Ning Xue & Peng Zhan, 2022. "Growth and Common Prosperity in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 30(1), pages 28-57, January.
    3. Ray, Subhash C. & Ghose, Arpita, 2014. "Production efficiency in Indian agriculture: An assessment of the post green revolution years," Omega, Elsevier, vol. 44(C), pages 58-69.
    4. Shen, Zhiyang & Wang, Songkai & Boussemart, Jean-Philippe & Hao, Yu, 2022. "Digital transition and green growth in Chinese agriculture," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    5. Nihal Ahmed & Zeeshan Hamid & Farhan Mahboob & Khalil Ur Rehman & Muhammad Sibt e Ali & Piotr Senkus & Aneta Wysokińska-Senkus & Paweł Siemiński & Adam Skrzypek, 2022. "Causal Linkage among Agricultural Insurance, Air Pollution, and Agricultural Green Total Factor Productivity in United States: Pairwise Granger Causality Approach," Agriculture, MDPI, vol. 12(9), pages 1-17, August.
    6. Volkov, Artiom & Morkunas, Mangirdas & Balezentis, Tomas & Streimikiene, Dalia, 2022. "Are agricultural sustainability and resilience complementary notions? Evidence from the North European agriculture," Land Use Policy, Elsevier, vol. 112(C).
    7. Du, Yuqiu & Wang, Wendi, 2023. "The role of green financing, agriculture development, geopolitical risk, and natural resource on environmental pollution in China," Resources Policy, Elsevier, vol. 82(C).
    8. Jiuliang Xu & Zhihua Zhang & Xian Zhang & Muhammad Ishfaq & Jiahui Zhong & Wei Li & Fusuo Zhang & Xuexian Li, 2020. "Green Food Development in China: Experiences and Challenges," Agriculture, MDPI, vol. 10(12), pages 1-15, December.
    9. Hongpeng Guo & Xin Yi & Chulin Pan & Baiming Yang & Yin Li, 2021. "Analysis on the Temporal and Spatial Features of the Coupling and Coordination of Industrialization and Agricultural Green Development in China during 1990–2019," IJERPH, MDPI, vol. 18(16), pages 1-27, August.
    10. 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.
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