Regional Disparities and Influencing Factors of Eco-Efficiency of Arable Land Utilization in China

Nan Ke, Xupeng Zhang, Xinhai Lu, Bing Kuang and Bin Jiang
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Nan Ke: College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China
Xupeng Zhang: School of Public Administration, China University of Geosciences, Wuhan 430074, China
Xinhai Lu: College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China
Bing Kuang: School of Public Administration, Central China Normal University, Wuhan 430079, China
Bin Jiang: College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China

Land, 2022, vol. 11, issue 2, 1-17

Abstract: Eco-efficiency of arable land utilization (EALU) emphasizes efficient coordination between land use systems and ecosystems. It is therefore of great significance for agricultural sustainability based on the systematic assessment of EALU. This study took carbon emissions and non-point source pollution resulting from arable land utilization into the measurement system of EALU, and a super-SBM model, kernel density estimation and Tobit regression model were used to analyze regional differences and influencing factors of EALU for 31 provinces in China from 2000 to 2019. The results showed that there was an upward trend in EALU in China from 0.4393 in 2000 to 0.8929 in 2019, with an average annual growth rate of 4.01%. At the regional level, the EALU of three categories of grain functional areas generally maintains an increasing trend, with the highest average value of EALU in main grain marketing areas (MGMAs), followed by grain producing and marketing balance areas (GPMBAs) and main grain producing areas (MGPAs). There are obvious differences in EALU among provinces, and the number of provinces with high eco-efficiency has increased significantly, showing a spatial distribution pattern of “block” clustering. In terms of dynamic evolution, kernel density curves reflect the evolution of EALU in China and grain functional areas with different degrees of polarization characteristics. The results of Tobit regression show that natural conditions, financial support for agriculture, science and technology inputs, level of industrialization, agricultural mechanization, and the living standards of farmers are significant factors resulting in regional disparities of EALU. Therefore, this study proposes the implementation of differentiated arable land use/agricultural management strategies to improve the sustainable utilization of arable land.

Keywords: eco-efficiency of arable land utilization (EALU); regional disparities; influencing factors; carbon emissions (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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