IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v14y2025i3p590-d1610088.html
   My bibliography  Save this article

Evaluation of the Coordinated Development of the “Population–Economy” in Counties Within the Beijing–Tianjin–Hebei Urban Agglomeration

Author

Listed:
  • Yanmin Ren

    (Key Laboratory of Land Use, Ministry of Natural Resources, Beijing 100035, China
    Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
    National Agricultural Information Engineering Technology Research Center, Beijing 100097, China)

  • Yanyu Zhang

    (Key Laboratory of Land Use, Ministry of Natural Resources, Beijing 100035, China
    China Land Surveying and Planning Institute, Beijing 100035, China)

  • Shuhua Li

    (Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
    National Agricultural Information Engineering Technology Research Center, Beijing 100097, China)

  • Yu Liu

    (Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
    National Agricultural Information Engineering Technology Research Center, Beijing 100097, China)

  • Lan Yao

    (Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
    National Agricultural Information Engineering Technology Research Center, Beijing 100097, China)

  • Linnan Tang

    (Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
    National Agricultural Information Engineering Technology Research Center, Beijing 100097, China)

Abstract

The coordinated development of urban agglomerations is a crucial means of establishing a territorial development and protection pattern with complementary advantages and high-quality development. In this study, an evaluation was performed on the coordinated development of the “population–economy” in the counties within the Beijing–Tianjin–Hebei urban agglomeration (BTHUA), focusing on the macro trend of coordinated development in this region. The evaluation methods included spatial autocorrelation analysis, the Gini coefficient, a comprehensive evaluation model, and a coupling coordination model. The results revealed that, in 2010 and 2022, the counties within the BTHUA exhibited strong positive spatial autocorrelation between evaluation indicators such as the population and economy, with notable and enhancing spatial clustering effects. The regional balance among all indicators was improved. The population distribution indicator and economic development indicator exhibited upward trends. The level of coupling coordination between the population and economy improved markedly. At the end of this paper, applicable strategies are recommended to drive economic growth and quality improvement in these counties, e.g., the orderly decentralization of the population and functions away from central urban areas to reduce the spatial carrying pressure and putting “policy guidance–fast-track resources–industrial upgrading” into practice. The purpose is to boost population–economy layout optimization and efficient resource allocation within the BTHUA.

Suggested Citation

  • Yanmin Ren & Yanyu Zhang & Shuhua Li & Yu Liu & Lan Yao & Linnan Tang, 2025. "Evaluation of the Coordinated Development of the “Population–Economy” in Counties Within the Beijing–Tianjin–Hebei Urban Agglomeration," Land, MDPI, vol. 14(3), pages 1-19, March.
  • Handle: RePEc:gam:jlands:v:14:y:2025:i:3:p:590-:d:1610088
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/14/3/590/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/14/3/590/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ma, Wenliang & Gao, Huiwen, 2024. "Impact of high-speed railway network improvement on consumption synergy in Beijing-Tianjin-Hebei region," Transport Policy, Elsevier, vol. 158(C), pages 29-41.
    2. Li, Sinan & Zhao, Xiaoqing & Pu, Junwei & Miao, Peipei & Wang, Qian & Tan, Kun, 2021. "Optimize and control territorial spatial functional areas to improve the ecological stability and total environment in karst areas of Southwest China," Land Use Policy, Elsevier, vol. 100(C).
    3. Zidao Lu & Maomao Zhang & Chunguang Hu & Lianlong Ma & Enqing Chen & Cheng Zhang & Guozhen Xia, 2024. "Spatiotemporal Changes and Influencing Factors of the Coupled Production–Living–Ecological Functions in the Yellow River Basin, China," Land, MDPI, vol. 13(11), pages 1-24, November.
    4. Dagum, Camilo, 1997. "A New Approach to the Decomposition of the Gini Income Inequality Ratio," Empirical Economics, Springer, vol. 22(4), pages 515-531.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kui Ying & Lin Ha & Yaohua Kuang & Jinhong Ding, 2024. "Population Distribution in Guizhou’s Mountainous Cities: Evolution of Spatial Pattern and Driving Factors," Land, MDPI, vol. 13(9), pages 1-18, September.
    2. Stéphane Mussard & Kuan Xu, 2006. "Multidimensional Decomposition of the Sen Index: Some Further Thoughts," Cahiers de recherche 06-08, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    3. Charles Condevaux & Stéphane Mussard & Téa Ouraga & Guillaume Zambrano, 2020. "Generalized Gini linear and quadratic discriminant analyses," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 219-236, August.
    4. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    5. Xianpu Xu & Tieshan Zhao, 2024. "Towards Green Development: Exploring the Impact of Housing Price Bubbles on Regional Green Innovation Efficiency Based on Chinese Provincial Panel Data Analysis," Sustainability, MDPI, vol. 16(23), pages 1-23, November.
    6. Lee, Chien-Chiang & Qian, Anqi, 2024. "Regional differences, dynamic evolution, and obstacle factors of cultivated land ecological security in China," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).
    7. Pan Wenjie & Mei Daniel Weiyue, 2022. "Comprehensive Evaluation of China's Green Urbanization Level--Measurement Based on Provincial Panel Data," International Business Research, Canadian Center of Science and Education, vol. 15(9), pages 1-16, September.
    8. Long Qian & Yunjie Zhou & Ying Sun, 2023. "Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    9. Nan Li & Beibei Shi & Rong Kang, 2023. "Analysis of the Coupling Effect and Space-Time Difference between China’s Digital Economy Development and Carbon Emissions Reduction," IJERPH, MDPI, vol. 20(1), pages 1-25, January.
    10. Yaoyao Wang & Yuanpei Kuang, 2023. "Evaluation, Regional Disparities and Driving Mechanisms of High-Quality Agricultural Development in China," Sustainability, MDPI, vol. 15(7), pages 1-20, April.
    11. Zhao, Feifei & Hu, Zheng & Yi, Ping & Zhao, Xu, 2024. "Does environmental decentralization improve industrial ecology? Evidence from China's Yangtze River Economic Belt," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 1250-1270.
    12. Gangfei Luo & Shouzhen Zeng & Tomas Baležentis, 2022. "Multidimensional Measurement and Comparison of China’s Educational Inequality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(2), pages 857-874, September.
    13. Masato Okamoto, 2009. "Decomposition of gini and multivariate gini indices," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 7(2), pages 153-177, June.
    14. Ke Huang & Martin Dallimer & Lindsay C. Stringer & Anlu Zhang & Ting Zhang, 2021. "Does Economic Agglomeration Lead to Efficient Rural to Urban Land Conversion? An Examination of China’s Metropolitan Area Development Strategy," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    15. Liang Zheng & Yajing Wang & Hui Yang & Yuzhe Bi & Lei Xu & Ying Wang, 2024. "Identifying Trade-Offs and Synergies of Production–Living–Ecological Functions and Their Drivers: The Case of Yangtze River Urban Agglomerations in China," Land, MDPI, vol. 13(8), pages 1-20, August.
    16. Ningyi Liu & Yongyu Wang, 2022. "Urban Agglomeration Ecological Welfare Performance and Spatial Convergence Research in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-18, November.
    17. Nicole Palan, 2010. "Measurement of Specialization – The Choice of Indices," FIW Working Paper series 062, FIW.
    18. Huanhuan Xiong & Lingyu Lan & Longwu Liang & Yaobin Liu & Xiaoyu Xu, 2020. "Spatiotemporal Differences and Dynamic Evolution of PM 2.5 Pollution in China," Sustainability, MDPI, vol. 12(13), pages 1-18, July.
    19. Maria Ana Lugo & Esfandiar Maasoumi, 2008. "Multidimensional Poverty Measures from an Information Theory Perspective," Working Papers 85, ECINEQ, Society for the Study of Economic Inequality.
    20. Achille VERNIZZI & Maria Giovanna MONTI & Marek KOSNY, 2006. "An overall inequality reducing and horizontally equitable tax system with application to Polish data," Departmental Working Papers 2006-15, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:14:y:2025:i:3:p:590-:d:1610088. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.