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Population Prediction of Chinese Prefecture-Level Cities Based on Multiple Models

Author

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  • Lixuan Chen

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Tianyu Mu

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Xiuting Li

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China)

  • Jichang Dong

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China)

Abstract

In recent years, the population growth rate has been gradually declining in China. As the population problem becomes increasingly significant, the accurate prediction of population development trends has become a top priority, used to facilitate national scientific planning and effective decision making. Based on historical data spanning a period of 20 years (1999–2018), this article presents predictions of the populations of 210 prefecture-level cities using the Malthusian model, Unary linear regression model, Logistic model, and Gray prediction model. Furthermore, because the gray prediction model exhibited the highest degree of accuracy in formulating predictions, this study uses the model to predict and analyze future population development trends. The results reveal that the population gap between cities is gradually widening, and the total urban population shows a pattern of rising in middle-tier cities (second-tier cities and third-tier cities) and declining in high-tier cities (first-tier cities and new first-tier cities) and low-tier cities (fourth-tier cities and fifth-tier cities). From the viewpoint of geographical distribution, the population growth rate is basically balanced between the northern part and the southern part of China. In addition, the population growth of the high-tier cities is gradually slowing while the low-tier cities are experiencing a negative growth of population, but middle-tier cities are experiencing skyrocketing population growth. From the viewpoint of regional development, although the development of regional integration has been strengthened over the years, the radiative driving effect of large urban agglomerations and metropolitan areas is relatively limited.

Suggested Citation

  • Lixuan Chen & Tianyu Mu & Xiuting Li & Jichang Dong, 2022. "Population Prediction of Chinese Prefecture-Level Cities Based on Multiple Models," Sustainability, MDPI, vol. 14(8), pages 1-23, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4844-:d:796369
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    References listed on IDEAS

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    Cited by:

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    2. Haowei Sun & Jinghan Ma & Li Wang, 2023. "Changes in per capita wheat production in China in the context of climate change and population growth," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 15(3), pages 597-612, June.
    3. Jingru Chen & Hengyuan Zeng & Qiang Gao, 2023. "Using the Sustainable Development Capacity of Key Counties to Guide Rural Revitalization in China," IJERPH, MDPI, vol. 20(5), pages 1-26, February.
    4. Xiaojun Guo & Rui Zhang & Houxue Shen & Yingjie Yang, 2022. "An Optimized Damping Grey Population Prediction Model and Its Application on China’s Population Structure Analysis," IJERPH, MDPI, vol. 19(20), pages 1-25, October.
    5. Sebal Oo & Makoto Tsukai, 2022. "Long-Term Impact of Interregional Migrants on Population Prediction," Sustainability, MDPI, vol. 14(11), pages 1-21, May.

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