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Temporal-Spatial Differentiation and Optimization Analysis of Cultivated Land Green Utilization Efficiency in China

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  • Qianru Chen

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

  • Hualin Xie

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

Abstract

Cultivated land is closely related to national food security, rural economic development and social stability. The cultivated land pollution and carbon emissions caused by chemical fertilizers, pesticides, film residues, etc., in the process of cultivated land utilization pose a serious threat to the cultivated land ecosystem in China. The comprehensive analysis on the cultivated land green utilization efficiency (GUECL), its influencing factors, and optimization direction provides a valuable basis for the green utilization of cultivated land. Based on a panel data of 30 provinces (cities or districts) in China from 2001 to 2016, the GUECL in China under the constraints of pollution and carbon emissions was measured by using a super-efficient SBM-VRS (slack based model-variable return to scale) model. The influencing factors and optimization directions of the GUECL were analyzed through the Tobit model and slack values, respectively. The results show that the GUECL in China rose with fluctuations from 2001 to 2016. Since 2014, the eastern region has surpassed the western region and has become the region with the highest mean GUECL value. The room for resource conservation and pollution reduction varies in different regions of China. Farmers’ dependence on cultivated land and agricultural added value are positively related to the GUECL in China. Farmers’ occupational differentiation, agricultural machinery density, and agricultural disaster rate have had negative effects on the GUECL in China. The loss of the GUECL in China is mainly due to the redundancies of land input, pollution emission, and mechanical input. By analyzing these influencing factors and optimization directions, it is concluded that improving rural land transfer market and agricultural infrastructure construction, establishing a new agricultural technology extension system, and vigorously cultivating new professional farmers are the targeted measures to improve the GUECL.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jlands:v:8:y:2019:i:11:p:158-:d:279912
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    References listed on IDEAS

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    1. 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.
    2. Fukuyama, Hirofumi & Weber, William L., 2010. "A slacks-based inefficiency measure for a two-stage system with bad outputs," Omega, Elsevier, vol. 38(5), pages 398-409, October.
    3. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    4. MAHDHI Naceur & SGHAIER Mongi, 2013. "The Technical Efficiency of Collective Irrigation Schemes in South-Eastern of Tunisia," International Journal of Sustainable Development & World Policy, Conscientia Beam, vol. 2(6), pages 87-103.
    5. Mahdhi Naceur & Sghaier Mongi, 2013. "The Technical Efficiency of Collective Irrigation Schemes in South-Eastern of Tunisia," International Journal of Sustainable Development & World Policy, Conscientia Beam, vol. 2(6), pages 87-103.
    6. Yung-Ho Chiu & Chin-Wei Huang & Chung-Te Ting, 2011. "Measuring The Repair Performance For Stricken Cultivated Land And Agricultural Efficiency In China With A Modified Two-Stage Dea Model," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 28(05), pages 633-649.
    7. Xiangbin Kong, 2014. "China must protect high-quality arable land," Nature, Nature, vol. 506(7486), pages 7-7, February.
    8. Barros, Carlos Pestana & Managi, Shunsuke & Matousek, Roman, 2012. "The technical efficiency of the Japanese banks: Non-radial directional performance measurement with undesirable output," Omega, Elsevier, vol. 40(1), pages 1-8, January.
    9. Mahlberg, Bernhard & Sahoo, Biresh K., 2011. "Radial and non-radial decompositions of Luenberger productivity indicator with an illustrative application," International Journal of Production Economics, Elsevier, vol. 131(2), pages 721-726, June.
    10. 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.
    11. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
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    5. Xiuqing Zou & Meihui Xie & Zhiyuan Li & Kaifeng Duan, 2022. "Spatial Spillover Effect of Rural Labor Transfer on the Eco-Efficiency of Cultivated Land Use: Evidence from China," IJERPH, MDPI, vol. 19(15), pages 1-17, August.
    6. 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.
    7. 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.
    8. 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.
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    10. 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.
    11. Min Zhou & Bixia Hu, 2020. "Decoupling of carbon emissions from agricultural land utilisation from economic growth in China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(11), pages 510-518.
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