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Analysis and Projection of the Relationship between Industrial Structure and Land Use Structure in China

Author

Listed:
  • Qin Jin

    (School of Mathematics and Physics, China University of Geosciences (Wuhan), Wuhan 430074, China)

  • Xiangzheng Deng

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Center for Chinese Agricultural Policy, Chinese Academy of Sciences, Beijing 100101, China)

  • Zhan Wang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Center for Chinese Agricultural Policy, Chinese Academy of Sciences, Beijing 100101, China)

  • Chenchen Shi

    (State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China)

  • Xing Li

    (School of Mathematics and Physics, China University of Geosciences (Wuhan), Wuhan 430074, China)

Abstract

Based on the computable general equilibrium (CGE) modelling method, this research analyzes the relationship between industrial structure and land use structure in China. The results show that our model is feasible, and the simulation results are of a certain stability. Under the scenario analysis and projection of the relationship between the industrial structure and land use structure of the thirty-one provinces in China from 2010 to 2020, the proportions of secondary and tertiary industry in each province have been increasing; correspondingly, the proportion of agriculture has been decreasing. This means that the industrial structure of China is changing. As for land use, in general, the trend is similar to the industrial structure changes. The transformation of the structure of industrial development and land use has driven economic structure changes in China. The economic structure has an inclination to transform from agriculture to both secondary and tertiary industry. Along with industrial transformation, the cultivated land in China shows a trend of continuous decline. Empirical analysis results indicate that a decrease of cultivated land is acceptable under the scenario of economic growth in the next ten years. This shows a possibility that the economic efficiency of land use for cultivation and business services will decline, and more attention ought to be paid to increasing the economic efficiency of land use.

Suggested Citation

  • Qin Jin & Xiangzheng Deng & Zhan Wang & Chenchen Shi & Xing Li, 2014. "Analysis and Projection of the Relationship between Industrial Structure and Land Use Structure in China," Sustainability, MDPI, vol. 6(12), pages 1-28, December.
    • Handle: RePEc:gam:jsusta:v:6:y:2014:i:12:p:9343-9370:d:43570
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    References listed on IDEAS

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    1. Klaus Hubacek & Laixiang Sun, 2005. "Economic and Societal Changes in China and their Effects onWater Use A Scenario Analysis," Journal of Industrial Ecology, Yale University, vol. 9(1‐2), pages 187-200, January.
    2. Xiangzheng Deng & Fan Zhang & Zhan Wang & Xing Li & Tao Zhang, 2014. "An Extended Input Output Table Compiled for Analyzing Water Demand and Consumption at County Level in China," Sustainability, MDPI, vol. 6(6), pages 1-20, May.
    3. Adam Rose & Shu‐Yi Liao, 2005. "Modeling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions," Journal of Regional Science, Wiley Blackwell, vol. 45(1), pages 75-112, February.
    4. Noelwah R. Netusil & Thomas R. Harris & Chang K. Seung & Jeffrey E. Englin, 2000. "Impacts of water reallocation: A combined computable general equilibrium and recreation demand model approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 34(4), pages 473-487.
    5. John Gowdy & Jon D. Erickson, 2005. "The approach of ecological economics," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 29(2), pages 207-222, March.
    6. Lee C. Adkins & Dan S. Rickman & Abid Hameed, 2003. "Bayesian Estimation of Regional Production for CGE Modeling," Journal of Regional Science, Wiley Blackwell, vol. 43(4), pages 641-661, November.
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    Cited by:

    1. Wang, Zhan & Deng, Xiangzheng & Bai, Yuping & Chen, Jiancheng & Zheng, Wentang, 2016. "Land use structure and emission intensity at regional scale: A case study at the middle reach of the Heihe River basin," Applied Energy, Elsevier, vol. 183(C), pages 1581-1593.
    2. Zhao, Zhe & Wang, Pei & Chen, Jiancheng & Zhang, Fan, 2021. "Economic spillover effect of grass-based livestock husbandry on agricultural production—A case study in Hulun Buir, China," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    3. Wei Chen & Rui He & Qun Wu, 2017. "A Novel Efficiency Measure Model for Industrial Land Use Based on Subvector Data Envelope Analysis and Spatial Analysis Method," Complexity, Hindawi, vol. 2017, pages 1-11, December.
    4. Zhan Wang & Xiangzheng Deng & Cecilia Wong, 2016. "Integrated Land Governance for Eco-Urbanization," Sustainability, MDPI, vol. 8(9), pages 1-16, September.

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