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Measuring the Cultivated Land Use Efficiency of the Main Grain-Producing Areas in China under the Constraints of Carbon Emissions and Agricultural Nonpoint Source Pollution

Author

Listed:
  • Hualin Xie

    (Institute of Ecological Civilization, Jiangxi University of Finance and Economics, Nanchang 330013, China)

  • Yanwei Zhang

    (Institute of Ecological Civilization, Jiangxi University of Finance and Economics, Nanchang 330013, China
    School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330032, China)

  • Yongrok Choi

    (Department of International Trade and Regional Studies, Inha University, 100 Inha-ro, Nam-gu, Incheon 402-751, Korea)

Abstract

The carbon emissions and agricultural nonpoint source pollution constraints were incorporated into the input–output index system, and the epsilon-based measure (EBM) super efficiency model and global Malmquist–Luenberger (GML) index were used to measure the cultivated land use efficiency and changes in the total factor productivity (TFP) of cultivated land use in the main grain-producing areas in China from 1993–2016. The results indicate that: (1) from 1993 to 2016, the cultivated land use efficiency in the main grain-producing areas in China showed a tendency to fluctuate and increase, with obvious stage characteristics; however, the overall level was not high. (2) There is a significant difference in the cultivated land use efficiency under the constraints of carbon emissions and nonpoint source pollution in the main grain-producing areas in the different provinces, and low-efficiency provinces have higher input redundancy and undesired output redundancy than high-efficiency provinces. It can be observed that input redundancy and undesired output redundancy have a significant negative effect on cultivated land use efficiency. (3) The TFP of cultivated land use under the constraints of carbon emissions and nonpoint source pollution in China’s main grain-producing areas is estimated by the GML index. The results show that the TFP of cultivated land use in the main provinces in the main grain-producing regions is greater than 1, indicating that the productivity levels of all the provinces in China’s main grain-producing areas are increasing. From the perspective of the power sources in each province, global pure technological change (GPTC) and global scale technological change (GSTC) are the main driving forces for the TFP of cultivated land use, while global pure efficiency change (GPEC) and global scale efficiency change (GSEC) are the bottlenecks for increasing the TFP of cultivated land use.

Suggested Citation

  • Hualin Xie & Yanwei Zhang & Yongrok Choi, 2018. "Measuring the Cultivated Land Use Efficiency of the Main Grain-Producing Areas in China under the Constraints of Carbon Emissions and Agricultural Nonpoint Source Pollution," Sustainability, MDPI, vol. 10(6), pages 1-32, June.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:6:p:1932-:d:151523
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    References listed on IDEAS

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    Cited by:

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    5. Luo Muchen & Rosita Hamdan & Rossazana Ab-Rahim, 2022. "Data-Driven Evaluation and Optimization of Agricultural Environmental Efficiency with Carbon Emission Constraints," Sustainability, MDPI, vol. 14(19), pages 1-22, September.
    6. Ying Chen & Suran Li & Long Cheng, 2020. "Evaluation of Cultivated Land Use Efficiency with Environmental Constraints in the Dongting Lake Eco-Economic Zone of Hunan Province, China," Land, MDPI, vol. 9(11), pages 1-15, November.
    7. Xiao Lu & Yi Qu & Piling Sun & Wei Yu & Wenlong Peng, 2020. "Green Transition of Cultivated Land Use in the Yellow River Basin: A Perspective of Green Utilization Efficiency Evaluation," Land, MDPI, vol. 9(12), pages 1-22, November.
    8. Guijie Qiu & Xiaonan Xing & Guanqiao Cong & Xinyu Yang, 2022. "Measuring the Cultivated Land Use Efficiency in China: A Super Efficiency MinDS Model Approach," IJERPH, MDPI, vol. 20(1), pages 1-15, December.
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    10. Deping Ye & Shangsong Zhen & Wei Wang & Yunqiang Liu, 2023. "Spatial double dividend from China’s main grain-producing areas policy: total factor productivity and the net carbon effect," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-22, December.
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    12. Xiaowei Yao & Ting Luo & Yingjun Xu & Wanxu Chen & Jie Zeng, 2022. "Prediction of Spatiotemporal Changes in Sloping Cropland in the Middle Reaches of the Yangtze River Region under Different Scenarios," IJERPH, MDPI, vol. 20(1), pages 1-22, December.
    13. Min Cao & Yanhui Zhu & Guonian Lü & Min Chen & Weifeng Qiao, 2019. "Spatial Distribution of Global Cultivated Land and Its Variation between 2000 and 2010, from Both Agro-Ecological and Geopolitical Perspectives," Sustainability, MDPI, vol. 11(5), pages 1-16, February.
    14. Meng Qu & Kai Zhao & Renhui Zhang & Yuan Gao & Jing Wang, 2022. "Divergence between Willingness and Behavior of Farmers to Purchase Socialized Agricultural Services: From a Heterogeneity Perspective of Land Scale," Land, MDPI, vol. 11(8), pages 1-21, July.
    15. Yajuan Wang & Xi Wu & Hongbo Zhu, 2022. "Spatio-Temporal Pattern and Spatial Disequilibrium of Cultivated Land Use Efficiency in China: An Empirical Study Based on 342 Prefecture-Level Cities," Land, MDPI, vol. 11(10), pages 1-15, October.
    16. Xinhai Lu & Yanwei Zhang & Handong Tang, 2021. "Modeling and Simulation of Dissemination of Cultivated Land Protection Policies in China," Land, MDPI, vol. 10(2), pages 1-21, February.
    17. Chaozheng Zhang & Yangyue Su & Gangqiao Yang & Danling Chen & Rongxuan Yang, 2020. "Spatial-Temporal Characteristics of Cultivated Land Use Efficiency in Major Function-Oriented Zones: A Case Study of Zhejiang Province, China," Land, MDPI, vol. 9(4), pages 1-20, April.

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