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The Impact of Urbanization on Cultivated Land Use Efficiency in the Yangtze River Economic Belt in China

Author

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  • Xiuju Feng

    (School of Business, Shandong University of Political Science and Law, Jinan 250014, China)

  • Jian Gao

    (School of Business, Shandong University of Political Science and Law, Jinan 250014, China)

  • Jittaporn Sriboonjit

    (Faculty of Commerce and Accountancy, Thammasat University, Bangkok 10200, Thailand)

  • Zhongmin Wang

    (Institute of Automation, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China)

  • Jianxu Liu

    (School of Economics, Shandong University of Finance and Economics, Jinan 250014, China
    Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Songsak Sriboonchitta

    (Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

The Yangtze River Economic Belt (YREB), an important industrial belt for food security for China, is facing the challenge of decreasing cultivated land in the process of rapid urbanization. In this case, how to improve the cultivated land use efficiency (CLUE) has become the top priority. Based on data from 108 cities of YREB from 2001 to 2019, we measured CLUE using a slack-based measure with undesirable output (SBM-Undesirable). The high-value area of CLUE shows a trend from multi-core agglomeration to two-core agglomeration, mainly concentrated in Chengdu-Chongqing urban agglomeration and the northern part of the YREB. Then the paper examines the spatial effect of urbanization on CLUE using the Spatial Error Model (SEM). The result shows that population urbanization has significantly promoted the improvement of CLUE in YREB during the sample period. With each percentage point increase in population urbanization, CLUE will increase by 2.99%. Land urbanization has a negative impact on CLUE, for each percent increase in the expansion of urban spatial scope, CLUE will decrease by 0.06%. The spatial heterogeneity analysis shows that population urbanization in the lower reaches has significantly promoted CLUE, with a coefficient of 1.053. The population urbanization level in the middle and lower reaches of the region has no obvious effect on CLUE. The coefficient of land urbanization in the downstream region is 0.35, which significantly promotes CLUE. The coefficient in the middle is −0.26, which implies the CLUE decreases by 0.26% for every one percentage point increase in land urbanization. Land urbanization in the upper has no significant impact on the CLUE. Policy implications include improving the quality of the three major urban clusters along the YREB, building an ecologic protective screen in the upper, encouraging a new agricultural management system and detailed regulations related to the cultivated land protection in YREB.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:3:p:666-:d:1096060
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    References listed on IDEAS

    as
    1. Koroso, Nesru H. & Zevenbergen, Jaap A. & Lengoiboni, Monica, 2020. "Urban land use efficiency in Ethiopia: An assessment of urban land use sustainability in Addis Ababa," Land Use Policy, Elsevier, vol. 99(C).
    2. Xie, Hualin & Huang, Yingqian & Choi, Yongrok & Shi, Jiaying, 2021. "Evaluating the sustainable intensification of cultivated land use based on emergy analysis," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    3. Lai, Zhaohao & Chen, Meiqiu & Liu, Taoju, 2020. "Changes in and prospects for cultivated land use since the reform and opening up in China," Land Use Policy, Elsevier, vol. 97(C).
    4. Zhao, Zhe & Bai, Yuping & Wang, Guofeng & Chen, Jiancheng & Yu, Jiangli & Liu, Wei, 2018. "Land eco-efficiency for new-type urbanization in the Beijing-Tianjin-Hebei Region," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 19-26.
    5. Luc Anselin & Daniel A. Griffith, 1988. "Do Spatial Effecfs Really Matter In Regression Analysis?," Papers in Regional Science, Wiley Blackwell, vol. 65(1), pages 11-34, January.
    6. Meg Elizabeth Rithmire, 2017. "Land Institutions and Chinese Political Economy," Politics & Society, , vol. 45(1), pages 123-153, March.
    7. Mertz, Ole & Mertens, Charlotte Filt, 2017. "Land Sparing and Land Sharing Policies in Developing Countries – Drivers and Linkages to Scientific Debates," World Development, Elsevier, vol. 98(C), pages 523-535.
    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. 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.
    10. Zhiyuan Zhu & Jiajia Duan & Ruolan Li & Yongzhong Feng, 2022. "Spatial Evolution, Driving Mechanism, and Patch Prediction of Grain-Producing Cultivated Land in China," Agriculture, MDPI, vol. 12(6), pages 1-12, June.
    11. Shili Guo & Zhiyong Hu & Hanzhe Ma & Dingde Xu & Renwei He, 2022. "Spatial and Temporal Variations in the Ecological Efficiency and Ecosystem Service Value of Agricultural Land in China," Agriculture, MDPI, vol. 12(6), pages 1-23, June.
    12. Song, Ge & Ren, Gaofeng, 2022. "Spatial response of cultivated land use efficiency to the maize structural adjustment policy in the "Sickle Bend" region of China: An empirical study from the cold area of northeast," Land Use Policy, Elsevier, vol. 123(C).
    13. 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.
    14. Qingqing Yang & Yanhui Gao & Xinjun Yang & Jian Zhang, 2022. "Rural Transformation Driven by Households’ Adaptation to Climate, Policy, Market, and Urbanization: Perspectives from Livelihoods–Land Use on Chinese Loess Plateau," Agriculture, MDPI, vol. 12(8), pages 1-23, July.
    15. 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.
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