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Empirical Investigation of Cultivated Land Green Use Efficiency and Influencing Factors in China, 2000–2020

Author

Listed:
  • Bin Yang

    (School of Public Policy & Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Ying Wang

    (Department of Land Resources Management, China University of Geosciences, Wuhan 430074, China)

  • Yan Li

    (School of Public Policy & Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Lizi Mo

    (School of Public Policy & Management, China University of Mining and Technology, Xuzhou 221116, China)

Abstract

The rapid industrialization and urbanization promote socioeconomic development, but also pose a certain threat to food and ecological security. Cultivated land green use efficiency (CLGUE) is an important indictor to comprehensively reflect the coordinated relationship between cultivated land utilization and ecological protection. Therefore, it is of great practical significance to explore CLGUE to guarantee efficient and sustainable utilization of cultivated land resources. This paper thus conducts an empirical investigation of 31 provinces in mainland China during 2000–2020, aiming to measure the CLGUE level using the Super-SBM model and explore its influencing factors based on panel regression model. The data, which were mainly derived from various statistical yearbooks, together with the reference dataset, were all accurate. The results show that the average CLGUE value in China exhibited a fluctuating upward development trend, with the highest efficiency value of 0.957 in 2020 and the lowest one of 0.853 in 2003. Northeastern China had the highest efficiency value, while Central China had the lowest efficiency value. The overall ranking of CLGUE in the four major regions from high to low is Northeastern, Eastern, Western, and Central China. Spatially, there are significant diversities in CLGUE across China, which means that differentiated measures need to be taken to improve the efficiency based on regional natural conditions and the socioeconomic level. The regression model indicated that the crop diversity index, GDP per capita, urbanization level, effective irrigation rate, and fiscal support for agriculture positively influenced the CLGUE, while the proportion of natural disaster area had a negative impact. The findings had important implications for improving the CLGUE and achieving sustainable agricultural development.

Suggested Citation

  • Bin Yang & Ying Wang & Yan Li & Lizi Mo, 2023. "Empirical Investigation of Cultivated Land Green Use Efficiency and Influencing Factors in China, 2000–2020," Land, MDPI, vol. 12(8), pages 1-17, August.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:8:p:1589-:d:1215636
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    References listed on IDEAS

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