IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i19p12786-d934700.html
   My bibliography  Save this article

Cultivated Land Transfer, Management Scale, and Cultivated Land Green Utilization Efficiency in China: Based on Intermediary and Threshold Models

Author

Listed:
  • Min Zhou

    (School of Public Management, Liaoning University, Shenyang 110036, China)

  • Hua Zhang

    (Sunwah International Business School, Liaoning University, Shenyang 110036, China)

  • Nan Ke

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430079, China)

Abstract

Cultivated land utilization around the world is accompanied by the cultivated land fragmentation, which is a significant agricultural feature of countries with economies in transition. Thereby, governments of the PRC have successively promulgated a series of relevant policies to promote the cultivated land transfer (CLT) and stimulate the transformation of cultivated land utilization to be both green and efficient. In the context of large-scale CLT and the implementation of a rural revitalization strategy for China, it is of great significance to explore the effect of CLT on cultivated land green utilization efficiency (CLGUE). In this work, 30 provinces of China were selected as the objects of investigation; the super-efficiency SBM model was used to evaluate CLGUE; the mediation effect model and threshold regression model were used to gain a more comprehensive understanding of the CLT’s influence on CLGUE. According to the results of this study, the following conclusions were drawn. First of all, the CLGUE in China as a whole showed an upward trend improvement from 2005 to 2019. Due to the different natural and economic conditions, the CLGUE trends showed significant spatial disparities at both the grain functional areas level and provincial level. Secondly, the CLT could promote CLGUE directly, and the mediation regression results demonstrated that CLT was able to enhance CLGUE indirectly through the mediator of cultivated land management scale. Thirdly, the threshold effect test confirmed the existence of a single threshold, indicating that when the level of CLT gradually crossed the threshold, the promotion effects of CLT on CLGUE would slow down. Lastly, the heterogeneity analysis indicated that the promotion effects of CLT on CLGUE in different geographical location areas and grain functional areas were positive, and that there were significant differences in regression coefficients.

Suggested Citation

  • Min Zhou & Hua Zhang & Nan Ke, 2022. "Cultivated Land Transfer, Management Scale, and Cultivated Land Green Utilization Efficiency in China: Based on Intermediary and Threshold Models," IJERPH, MDPI, vol. 19(19), pages 1-20, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12786-:d:934700
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/19/12786/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/19/12786/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Su, Baozhong & Li, Yuheng & Li, Lequn & Wang, Yue, 2018. "How does nonfarm employment stability influence farmers' farmland transfer decisions? Implications for China’s land use policy," Land Use Policy, Elsevier, vol. 74(C), pages 66-72.
    2. 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.
    3. Mugera, Amin W. & Langemeier, Michael R., 2011. "Does Farm Size and Specialization Matter for Productive Efficiency? Results from Kansas," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 43(4), pages 515-528, November.
    4. Xie, Hualin & Chen, Qianru & Wang, Wei & He, Yafen, 2018. "Analyzing the green efficiency of arable land use in China," Technological Forecasting and Social Change, Elsevier, vol. 133(C), pages 15-28.
    5. Xu, Bin & Lin, Boqiang, 2017. "Factors affecting CO2 emissions in China’s agriculture sector: Evidence from geographically weighted regression model," Energy Policy, Elsevier, vol. 104(C), pages 404-414.
    6. 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.
    7. Shichao Yuan & Jian Wang, 2022. "Involution Effect: Does China’s Rural Land Transfer Market Still Have Efficiency?," Land, MDPI, vol. 11(5), pages 1-18, May.
    8. Fei, Rilong & Lin, Ziyi & Chunga, Joseph, 2021. "How land transfer affects agricultural land use efficiency: Evidence from China’s agricultural sector," Land Use Policy, Elsevier, vol. 103(C).
    9. Liu, Yu & Yan, Binjian & Wang, Yue & Zhou, Yingheng, 2019. "Will land transfer always increase technical efficiency in China?—A land cost perspective," Land Use Policy, Elsevier, vol. 82(C), pages 414-421.
    10. Xinhai Lu & Bing Kuang & Jing Li & Jing Han & Zuo Zhang, 2018. "Dynamic Evolution of Regional Discrepancies in Carbon Emissions from Agricultural Land Utilization: Evidence from Chinese Provincial Data," Sustainability, MDPI, vol. 10(2), pages 1-13, February.
    11. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    12. Bruce Hansen, 1999. "Testing for Linearity," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 551-576, December.
    13. Yi Qu & Xiao Lyu & Wenlong Peng & Zongfei Xin, 2021. "How to Evaluate the Green Utilization Efficiency of Cultivated Land in a Farming Household? A Case Study of Shandong Province, China," Land, MDPI, vol. 10(8), pages 1-18, July.
    14. Qianru Chen & Hualin Xie, 2019. "Temporal-Spatial Differentiation and Optimization Analysis of Cultivated Land Green Utilization Efficiency in China," Land, MDPI, vol. 8(11), pages 1-17, October.
    15. Hansen,B.E., 1999. "Testing for linearity," Working papers 7, Wisconsin Madison - Social Systems.
    16. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    17. Xingyuan Xiao & Luxiang Shang & Yaqun Liu, 2022. "Comparative Study on Farmland Circulation between Plains and Mountainous Areas in an Arid Region: A Case Study of Zhangye City in Northwest China," Land, MDPI, vol. 11(4), pages 1-15, April.
    18. Nan Ke & Xupeng Zhang & Xinhai Lu & Bing Kuang & Bin Jiang, 2022. "Regional Disparities and Influencing Factors of Eco-Efficiency of Arable Land Utilization in China," Land, MDPI, vol. 11(2), pages 1-17, February.
    19. Ge, Dazhuan & Long, Hualou & Zhang, Yingnan & Ma, Li & Li, Tingting, 2018. "Farmland transition and its influences on grain production in China," Land Use Policy, Elsevier, vol. 70(C), pages 94-105.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hua Zhang & Ying Li & Hanxiaoxue Sun & Xiaohui Wang, 2023. "How Can Digital Financial Inclusion Promote High-Quality Agricultural Development? The Multiple-Mediation Model Research," IJERPH, MDPI, vol. 20(4), pages 1-19, February.
    2. Yuanhe Yu & Jinkuo Lin & Peixiang Zhou & Shuwei Zheng & Zijun Li, 2022. "Cultivated Land Input Behavior of Different Types of Rural Households and Its Impact on Cultivated Land-Use Efficiency: A Case Study of the Yimeng Mountain Area, China," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
    3. Hua Zhang & Qiwang Zhang & Man An & Zixuan Zhang & Nanqiao He, 2023. "Unveiling the Impact of Digital Financial Inclusion on Low-Carbon Green Utilization of Farmland: The Roles of Farmland Transfer and Management Scale," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    4. Min Zhou & Hua Zhang & Zixuan Zhang & Hanxiaoxue Sun, 2023. "Digital Financial Inclusion, Cultivated Land Transfer and Cultivated Land Green Utilization Efficiency: An Empirical Study from China," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    5. Weijia Wang & Wen Wang & Kun Wang & Yanyun Zhao & Ran Yu, 2023. "Remote Sensing Application in Pure Premium Rate-Making of Winter Wheat Crop Insurance," Sustainability, MDPI, vol. 15(9), pages 1-15, April.
    6. Min Zhou & Hanxiaoxue Sun & Nan Ke, 2022. "The Spatial and Temporal Evolution of Coordination Degree Concerning China’s Cultivated Land Green Utilization Efficiency and High-Quality Agricultural Development," Land, MDPI, vol. 12(1), pages 1-21, December.
    7. Jie Li & Zhengchuan Sun & Jie Zhou & Yaya Sow & Xufeng Cui & Haipeng Chen & Qianling Shen, 2023. "The Impact of the Digital Economy on Carbon Emissions from Cultivated Land Use," Land, MDPI, vol. 12(3), pages 1-18, March.
    8. Guoqun Ma & Danyang Lv & Tuanbiao Jiang & Yuxi Luo, 2023. "Can Land Transfer Promote Agricultural Green Transformation? The Empirical Evidence from China," Sustainability, MDPI, vol. 15(18), pages 1-17, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Min Zhou & Bing Kuang & Min Zhou & Nan Ke, 2022. "The Spatial and Temporal Evolution of the Coordination Degree in Regard to Farmland Transfer and Cultivated Land Green Utilization Efficiency in China," IJERPH, MDPI, vol. 19(16), pages 1-16, August.
    2. Min Zhou & Hua Zhang & Zixuan Zhang & Hanxiaoxue Sun, 2023. "Digital Financial Inclusion, Cultivated Land Transfer and Cultivated Land Green Utilization Efficiency: An Empirical Study from China," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    3. Min Zhou & Hanxiaoxue Sun & Nan Ke, 2022. "The Spatial and Temporal Evolution of Coordination Degree Concerning China’s Cultivated Land Green Utilization Efficiency and High-Quality Agricultural Development," Land, MDPI, vol. 12(1), pages 1-21, December.
    4. Mengna Li & Li Tan & Xi Yang, 2023. "The Impact of Environmental Regulation on Cultivated Land Use Eco-Efficiency: Evidence from China," Agriculture, MDPI, vol. 13(9), pages 1-20, August.
    5. Kuang, Bing & Lu, Xinhai & Zhou, Min & Chen, Danling, 2020. "Provincial cultivated land use efficiency in China: Empirical analysis based on the SBM-DEA model with carbon emissions considered," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    6. Yi Qu & Xiao Lyu & Wenlong Peng & Zongfei Xin, 2021. "How to Evaluate the Green Utilization Efficiency of Cultivated Land in a Farming Household? A Case Study of Shandong Province, China," Land, MDPI, vol. 10(8), pages 1-18, July.
    7. Hua Zhang & Qiwang Zhang & Man An & Zixuan Zhang & Nanqiao He, 2023. "Unveiling the Impact of Digital Financial Inclusion on Low-Carbon Green Utilization of Farmland: The Roles of Farmland Transfer and Management Scale," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    8. Mengchao Yao & Yihua Zhang, 2021. "Evaluation and Optimization of Urban Land-Use Efficiency: A Case Study in Sichuan Province of China," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    9. Xiuju Feng & Jian Gao & Jittaporn Sriboonjit & Zhongmin Wang & Jianxu Liu & Songsak Sriboonchitta, 2023. "The Impact of Urbanization on Cultivated Land Use Efficiency in the Yangtze River Economic Belt in China," Agriculture, MDPI, vol. 13(3), pages 1-17, March.
    10. 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.
    11. Jie Zhang & Yajing Wang & Jiangfeng Li, 2023. "Maximize Eco-Economic Benefits with Minimum Land Resources Input: Evaluation and Evolution of Land Use Eco-Efficiency of Agglomerations in Middle Reaches of Yangtze River, China," IJERPH, MDPI, vol. 20(3), pages 1-19, January.
    12. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    13. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    14. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    15. Muliaman Hadad & Maximilian Hall & Karligash Kenjegalieva & Wimboh Santoso & Richard Simper, 2011. "Banking efficiency and stock market performance: an analysis of listed Indonesian banks," Review of Quantitative Finance and Accounting, Springer, vol. 37(1), pages 1-20, July.
    16. Jo, Ah-Hyun & Chang, Young-Tae, 2023. "The effect of airport efficiency on air traffic, using DEA and multilateral resistance terms gravity models," Journal of Air Transport Management, Elsevier, vol. 108(C).
    17. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    18. Yi-Chung Hsu, 2014. "Efficiency in government health spending: a super slacks-based model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 111-126, January.
    19. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    20. Fan Wang & Lili Feng & Jin Li & Lin Wang, 2020. "Environmental Regulation, Tenure Length of Officials, and Green Innovation of Enterprises," IJERPH, MDPI, vol. 17(7), pages 1-16, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12786-:d:934700. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.